Ep 26 | Real-World AI Use Cases with Ned Moorfield

In this episode of Digital Nexus, we explore groundbreaking AI news and practical applications with tech entrepreneur Ned Moorfield from Product Edge AI. Ned, a veteran of Google, Eventbrite, and co-founder of GoCatch, shares insider insights into AI strategies transforming businesses.

🔔 Subscribe for more updates!

AI news, Anthropic Claude, XAI, OpenAI modules, Google Gemini 2.5, ChatGPT image generation, deepfakes, Apple AI, AI in business, AI adoption strategies, Ned Moorfield, Product Edge AI, reskilling workforce, hyper-personalization, business AI applications.

🎯 Episode Highlights:
• Learn why X’s acquisition of XAI matters for the future of social media and AI collaboration.
• Discover Anthropic Claude’s unique ability to pre-plan sentences and utilize an internal universal language.
• Explore Google's Gemini 2.5 advancements and how it's shifting AI beyond traditional predictive models.
• Understand practical AI applications with Ned Moorfield, improving efficiency in real business scenarios.

🌐 About Ned Moorfield:
Ned Moorfield, founder of Product Edge AI, leverages his extensive tech industry experience to help businesses adopt strategic AI solutions. From scaling startups like GoCatch to his leadership roles at Google and Eventbrite, Ned's approach focuses on real, measurable impacts of AI.

📧 Connect with Ned:
Email: ned@productedge.ai
LinkedIn: Follow Ned for more AI insights and practical use-case demonstrations.

👍 Like, Comment, and Share this video to help others learn about AI!

#AI #ArtificialIntelligence #Anthropic #OpenAI #GoogleGemini #NedMoorfield #DigitalNexusPodcast

Transcript

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Yeah, this is the first time we're doing

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like three threesome.

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Yeah.

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Three threesome, not

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the digital threesome.

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What an honor to be

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here for first threesome.

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You'll be the revolution of digital

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nexus, the takeover that is.

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Yeah, it's happening.

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It's happening and we don't have the mic

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on here, so this is weird.

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I'm used to something.

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Yeah, you used to have it like tilt your

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head around like this

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central ball object.

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Yeah, this is good.

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This is episode 26.

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It's, I don't know, like what's

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significant about 26?

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What did you do on your 26th, Chris?

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Well, the funny thing about the 26th is

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that it's not actually

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26, which we realized.

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Somehow we magically skipped 24.

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No, we don't need to know that though.

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I think it's funny.

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Yeah, yeah, yeah, yeah.

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Just like OtonAI, you know, going GPT,

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you know what, it's just 4.0.

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It's not GPT 5, it's just, you know,

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we're just having like

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all these like different

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weird naming conventions, like Apple.

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They skipped two, didn't they?

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There was GPT 2 and 1.

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2 and 1?

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GPT 1.

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They didn't call it GPT 3.

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No, they did.

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Did they?

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It was all called GPT 1, 2, 3.

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And then they went backwards to 01 and

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then they went 4 and 4.0 and then 3.5.

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People got the public

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release of chat GPT.

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The API was always there.

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Yeah, it was the chat interface that

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really like, it was the breakthrough.

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That was on 3.5.

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See, Net is right.

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Net is already better than Chris.

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Sorry, Chris, we'll

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educate you a long time.

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What the hell, wow, that just...

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If you would like to also attack Chris,

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put it right in to www.net.

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Anyway, Ned, welcome in.

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Thank you, it's great to be here, guys.

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Great to join you.

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Big fan of the show.

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Thanks, man.

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For folks that might be at various

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industry events, they might

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have seen you at AI events,

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some other product events, you were at an

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interesting retail event, what was that?

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Yeah, it was down in Melbourne a couple

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of weeks ago for a Gen

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AI summit down there with

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the National Online Retail Association.

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So that was really interesting.

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A big focus for me, my business is

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e-commerce online retail.

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So I had some good conversation.

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Great, actually really

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good content down there.

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So yeah, good trip down there.

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Fantastic.

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Yeah, we'll talk more about that.

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And the reason why we got Net here is

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because we really want to

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dive into all of this kind

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of stuff that where AI is actually used.

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It's not in the vacuum.

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It's just the fun stuff that we get to

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play with, but it's

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actually applied, right?

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So yeah, it would be interesting.

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Chris has got some great questions there.

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And as always, we're

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going to cover the news.

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That's the thing we're trying to move

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more into that

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exploration of applicability in

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the space, particularly in business and

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product and, you know, AI

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is ever evolving and ever

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changing.

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So I guess the more experts that we have

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coming in to talk about

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their stuff, the more I can

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be put in my place.

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Yeah, exactly.

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This is this has always been the goal.

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The only reason I want this podcast is

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just to put Chris in his place.

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To put Chris baby in

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the corner, as always.

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But yeah, shall we shall we get started?

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Yeah.

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26.

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Awesome.

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Um, latest news, Mark, kick us off.

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What have you been

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seeing in the world of AI?

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Well, look, if we're going to do that,

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I'm going to have to

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share my screen and jump

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into straight into it.

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One of the first ones that I had as like

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a piece of news is this

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really interesting stuff

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where Musk talks to Musk to buy more Musk

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or actually it's like,

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I'm moving money from

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my checkings account

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to my savings account.

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I saw someone like put up on LinkedIn

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that XAI being bought by X.

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So is it a merger?

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Is it a rebranding?

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It's to combine data models and compute

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and distribution and

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talent is what's being served.

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But it sounds more like we kind of need

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more user data servers,

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all that kind of stuff

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to increase valuations.

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And am I right?

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He bought it for less than

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what he originally bought.

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More, $1 billion more.

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$1 billion more.

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If he bought X originally Twitter,

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Twitter at the time when

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he brought the sink in, he

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goes, let that sink in.

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He physically brought a sink into the

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offices, bought it for 44 million.

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This is for 45 million.

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So at least there's

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that 1 billion plot more.

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I'm surprised X has got any money to

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spend on buying

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anything at the moment with the

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loss of users that they've had say and

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loss of advertising revenue.

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You're saying X bought XAI.

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Yeah, my brothers are not

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the other way around actually.

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Yeah.

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You'd get X on a fire sale.

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Oh, exactly.

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So anyway, now combined, a

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lot of people do use Grok.

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There's a lot of interesting stuff there.

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The videos that they have product

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releases is very interesting.

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So it was the other way.

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XAI bought X.

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Right, right, right.

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So XAI has acquired X in an all stock

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transaction, valuing

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X as the $33 billion.

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Potato, Kitato.

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It's a bit.

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But that's why there's

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an evaluation of the 33.

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So they bought it for

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$1 billion more of X.

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Yeah.

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It's been sold for $1 billion more.

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Combining them into this big strategic

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powerhouse in brackets.

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Valuing them both now at

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one company at $80 billion.

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110, over $110 billion.

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He's going to need to do something since

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he is probably being

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pushed out of the White

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House as per other reports.

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So maybe he'll get back onto

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the business side of things.

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Another interesting thing was anthropic

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and getting deep into the

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weeds into what is going

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on under the hood.

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So they started last year around this

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time being able to trace

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the synapses, the connections

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of what AI is doing,

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like basically the AI brain.

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So they found interesting things further.

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They said things like, it seems like

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Claude, their model thinks ahead of time.

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So it demonstrates planning before it

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actually complete sentences.

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It's got a universal language.

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So it doesn't matter whatever the

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language is that it needs

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to translate to, but there's

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some sort of internal language that it

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uses first and then

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translates it into English,

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Spanish, et cetera.

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So that was interesting.

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And that reasoning can be fabricated.

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So this concept that it might give you

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the right answer to do

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math, but the ways that

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it gets to those answers is really vague

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and like weird, but

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also that it might not

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be when you ask it, like reason with me,

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explain your reasoning,

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it might not be the actual

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thing that it's done.

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So it can be two separate pathways.

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So it leads to interesting things.

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If you're ever going to order, there

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needs to be not just

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showing me the outputs, but

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let's actually look

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at the inputs as well.

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So interesting stuff

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there from anthropic.

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The key thing I think was really

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interesting was this

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thing called DeepSight.

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So I'll show you this example.

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So DeepSight is this new thing.

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It's powered by Deep,

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what were they called again?

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DeepSikh.

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So this is something

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that's on hugging face.

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You can type something in here like, hey,

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create a website for a

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podcast called Digital

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Village.

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And then that will wear away.

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So on the free, just the front page, you

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can see doing coding,

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just like we see with lovable

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bolts, cursor, manners, etc.

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Here's something I tried earlier.

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I got it to create a

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bit of a markets website.

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And it is clickable.

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You can see the stuff it creates there on

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page, but it's using

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DeepSikh as the model

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that powers this rather than Claude.

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So some interesting stuff that you can

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see on screen there.

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That was the new one that I thought would

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be something to highlight.

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And then OpenAI opening up basically and

270
01:07:11,986 --> 01:07:12,820
saying that they're

271
01:07:12,820 --> 01:07:14,238
going to release open source

272
01:07:14,613 --> 01:07:14,822
modules.

273
01:07:14,989 --> 01:07:17,533
So whatever that means, I'm sure there

274
01:07:17,533 --> 01:07:19,285
will be some close element to it as well.

275
01:07:20,035 --> 01:07:21,203
But yeah, those are some of the key

276
01:07:21,203 --> 01:07:22,121
things I think I

277
01:07:22,121 --> 01:07:23,414
highlighted my news this week.

278
01:07:23,831 --> 01:07:24,039
Chris.

279
01:07:24,957 --> 01:07:25,833
Yeah, it was really good.

280
01:07:26,333 --> 01:07:28,294
The you touched on some interesting

281
01:07:28,294 --> 01:07:29,086
things that particularly

282
01:07:29,086 --> 01:07:31,088
around Claude and Anthropik

283
01:07:31,589 --> 01:07:32,506
and coding has anyone played

284
01:07:32,506 --> 01:07:34,341
with the Gemini 2.5 at all?

285
01:07:34,341 --> 01:07:35,551
I think vice you guys is.

286
01:07:35,843 --> 01:07:37,386
Not a whole lot.

287
01:07:37,595 --> 01:07:38,971
Yeah, I mean, this is super interesting.

288
01:07:38,971 --> 01:07:40,389
This is two week old news, but I've been

289
01:07:40,389 --> 01:07:41,140
playing a lot around

290
01:07:41,140 --> 01:07:43,267
jumping into Google Studio and

291
01:07:43,267 --> 01:07:45,144
just trying to replicate a lot of the

292
01:07:45,144 --> 01:07:45,811
things that people have

293
01:07:45,811 --> 01:07:47,855
been talking about with its

294
01:07:47,855 --> 01:07:48,564
coding capabilities.

295
01:07:48,856 --> 01:07:51,442
And I have to say Gemini 2.5 is winning

296
01:07:51,442 --> 01:07:53,486
the race when it comes to coding.

297
01:07:53,486 --> 01:07:55,488
So hard coders out there, particularly

298
01:07:55,488 --> 01:07:57,114
people using custom, I

299
01:07:57,114 --> 01:07:58,991
don't know whether using bolt.io

300
01:07:59,200 --> 01:08:01,035
installed into their systems or even VO,

301
01:08:01,744 --> 01:08:03,204
Envacel and other things

302
01:08:03,204 --> 01:08:05,873
like using the Gemini 2.5

303
01:08:05,873 --> 01:08:08,876
coding tool is far and away one of the

304
01:08:08,876 --> 01:08:09,710
best things right now.

305
01:08:10,002 --> 01:08:11,212
So definitely jump in and have a play if

306
01:08:11,212 --> 01:08:11,962
you guys haven't done it.

307
01:08:12,671 --> 01:08:15,633
Just wanted to call out the APIs for you.

308
01:08:15,633 --> 01:08:17,092
You do need a subscription to play for to

309
01:08:17,092 --> 01:08:18,302
use the Gemini 2.5 Pro.

310
01:08:19,053 --> 01:08:20,387
So but a lot of businesses probably have

311
01:08:20,387 --> 01:08:21,305
access to it if you're on

312
01:08:21,305 --> 01:08:23,390
the Google suite or obviously

313
01:08:23,390 --> 01:08:25,768
if you have the the updated Google

314
01:08:25,768 --> 01:08:27,103
accounts in your system.

315
01:08:27,520 --> 01:08:27,770
Fantastic.

316
01:08:28,229 --> 01:08:28,521
What else?

317
01:08:28,521 --> 01:08:28,729
Yeah.

318
01:08:29,146 --> 01:08:29,772
Oh, yeah.

319
01:08:29,772 --> 01:08:32,399
I was going to say on the Gemini 2.5

320
01:08:32,399 --> 01:08:33,400
announcement, it was pretty

321
01:08:33,400 --> 01:08:35,277
interesting to read about how

322
01:08:35,277 --> 01:08:36,487
the model actually works.

323
01:08:36,529 --> 01:08:38,572
So what I was reading up was it's moving

324
01:08:38,572 --> 01:08:39,657
beyond simply

325
01:08:39,657 --> 01:08:42,284
predicting text based patterns

326
01:08:42,451 --> 01:08:43,744
that we've seen in the first generation.

327
01:08:44,286 --> 01:08:46,330
So it's moving towards just a quote here,

328
01:08:46,956 --> 01:08:47,665
analyzing information

329
01:08:47,665 --> 01:08:48,999
deeply, drawing logical

330
01:08:49,083 --> 01:08:49,500
conclusions,

331
01:08:49,750 --> 01:08:51,168
incorporating nuanced context.

332
01:08:51,710 --> 01:08:53,379
So it definitely feels to me like we're

333
01:08:53,379 --> 01:08:54,880
moving on now to this

334
01:08:54,880 --> 01:08:56,215
kind of second generation of

335
01:08:56,215 --> 01:08:59,218
LLS that are doing deeper thinking in the

336
01:08:59,218 --> 01:08:59,677
assets that are

337
01:08:59,677 --> 01:09:00,427
providing and we're seeing

338
01:09:00,427 --> 01:09:02,596
now in the image gen side of as well, I

339
01:09:02,596 --> 01:09:04,682
think with open AI has been doing it.

340
01:09:04,682 --> 01:09:05,140
I think we're going to

341
01:09:05,140 --> 01:09:06,058
talk about it as well.

342
01:09:06,100 --> 01:09:07,143
Yeah, let's bring that up.

343
01:09:08,060 --> 01:09:10,896
Introducing 4o image generation and if

344
01:09:10,896 --> 01:09:12,439
you haven't seen it, it

345
01:09:12,439 --> 01:09:13,440
is this whole like where

346
01:09:13,440 --> 01:09:14,859
people have all these cartoons,

347
01:09:14,859 --> 01:09:15,943
especially Studio Ghibli

348
01:09:15,943 --> 01:09:17,862
style question the morals and

349
01:09:17,862 --> 01:09:18,863
ethics of that later on.

350
01:09:18,863 --> 01:09:20,155
But yeah, what have you seen about that?

351
01:09:20,781 --> 01:09:22,533
Yeah, I mean, a couple of things that I

352
01:09:22,533 --> 01:09:22,992
think are big

353
01:09:22,992 --> 01:09:26,036
improvements from the 4o image gen.

354
01:09:26,328 --> 01:09:27,872
So it can handle text a

355
01:09:27,872 --> 01:09:29,039
lot better in the images.

356
01:09:29,039 --> 01:09:29,498
So I think you might

357
01:09:29,498 --> 01:09:30,457
have some examples here.

358
01:09:30,457 --> 01:09:32,459
There's really impressive example image

359
01:09:32,459 --> 01:09:33,919
in front of a

360
01:09:33,919 --> 01:09:35,170
whiteboard with the reflection

361
01:09:35,379 --> 01:09:36,297
of the Golden Gate

362
01:09:36,297 --> 01:09:37,464
Bridge in the background.

363
01:09:37,464 --> 01:09:37,756
It's on.

364
01:09:38,674 --> 01:09:40,009
So that's a huge improvement.

365
01:09:40,134 --> 01:09:42,011
I've had quite a few use cases where it's

366
01:09:42,011 --> 01:09:43,262
just mangled the text up.

367
01:09:43,512 --> 01:09:44,847
And the other other thing

368
01:09:44,847 --> 01:09:46,056
was, yeah, the consistency.

369
01:09:46,640 --> 01:09:48,726
Yeah, if you feed it in a character, and

370
01:09:48,726 --> 01:09:49,685
then you can iterate and

371
01:09:49,685 --> 01:09:50,978
it doesn't keep changing

372
01:09:50,978 --> 01:09:52,521
the core character of the middle.

373
01:09:52,730 --> 01:09:54,982
So I think they're too big on unlocks to

374
01:09:54,982 --> 01:09:56,942
make the image generally more useful.

375
01:09:57,318 --> 01:09:57,985
What are they you Mark?

376
01:09:57,985 --> 01:09:59,111
Are you guys what you're saying?

377
01:09:59,278 --> 01:10:00,654
I've been playing around with it and what

378
01:10:00,654 --> 01:10:01,739
you can see on screen here.

379
01:10:01,739 --> 01:10:02,448
So we're in a meetup.

380
01:10:03,240 --> 01:10:06,368
And Chris is the key glue for us to be

381
01:10:06,368 --> 01:10:08,621
able to run these like Australian defies.

382
01:10:08,621 --> 01:10:09,455
So blockchain related

383
01:10:09,455 --> 01:10:10,372
association meetups.

384
01:10:10,789 --> 01:10:12,499
This was the panel where I literally fed

385
01:10:12,499 --> 01:10:13,792
the AI a couple of

386
01:10:13,792 --> 01:10:16,045
different images of the people

387
01:10:16,045 --> 01:10:18,213
speaking and then it created this.

388
01:10:18,672 --> 01:10:20,966
Mark is solely responsible for all the

389
01:10:20,966 --> 01:10:21,800
news you're hearing

390
01:10:21,800 --> 01:10:23,969
about the overuse of people

391
01:10:24,178 --> 01:10:26,931
generating Studio Ghibli-esque images and

392
01:10:26,931 --> 01:10:30,225
crashing bloody open AI server rooms with

393
01:10:30,768 --> 01:10:31,727
inundated queries.

394
01:10:32,603 --> 01:10:33,437
That's my picture into

395
01:10:33,437 --> 01:10:35,022
a Studio Ghibli image.

396
01:10:35,356 --> 01:10:36,941
He's Chris behind the scenes like it

397
01:10:36,941 --> 01:10:37,942
literally took and it got

398
01:10:37,942 --> 01:10:39,151
the style of his t shirt that

399
01:10:39,151 --> 01:10:39,610
I copied.

400
01:10:40,110 --> 01:10:41,695
And then me is like, yeah,

401
01:10:41,695 --> 01:10:42,780
you think it's nailed the hair?

402
01:10:43,572 --> 01:10:44,657
At the time, at the

403
01:10:44,657 --> 01:10:46,241
time, maybe look this way.

404
01:10:46,241 --> 01:10:47,034
You've come a bit longer.

405
01:10:47,034 --> 01:10:48,202
Yeah, you could you could

406
01:10:48,202 --> 01:10:49,954
do a bit more of the quaff.

407
01:10:50,663 --> 01:10:51,538
I mean, quiff.

408
01:10:52,081 --> 01:10:53,082
And then this is me

409
01:10:53,082 --> 01:10:54,250
kind of like a ringmaster.

410
01:10:55,167 --> 01:10:57,169
So that's me if I was a cartoon, my life

411
01:10:57,169 --> 01:10:58,295
does feel like that some ways.

412
01:10:59,046 --> 01:11:00,130
This is Lucinda who

413
01:11:00,130 --> 01:11:01,590
we're at Stone and Chalk.

414
01:11:01,590 --> 01:11:04,259
So we give shout out to shout outs.

415
01:11:04,843 --> 01:11:06,845
So look, to the point around like the

416
01:11:06,845 --> 01:11:09,348
text, it gets the text right really well.

417
01:11:09,348 --> 01:11:10,099
That's the great part.

418
01:11:10,599 --> 01:11:11,809
Pretty, pretty frickin crazy.

419
01:11:11,809 --> 01:11:12,851
So one of the biggest things like I love

420
01:11:12,851 --> 01:11:14,770
you're able to now take

421
01:11:14,770 --> 01:11:16,522
multiple images, put it into

422
01:11:16,522 --> 01:11:18,774
chat TPT and ask it to combine them.

423
01:11:18,774 --> 01:11:20,150
And if even if one of those images had

424
01:11:20,150 --> 01:11:21,026
text, as we saw in this

425
01:11:21,026 --> 01:11:22,653
example, so what was what

426
01:11:22,653 --> 01:11:23,904
happened here is that we took a picture

427
01:11:23,904 --> 01:11:25,197
of Lucinda took a

428
01:11:25,197 --> 01:11:26,198
picture of the stone and chalk

429
01:11:26,365 --> 01:11:28,075
logo, put them together and say, hey,

430
01:11:28,325 --> 01:11:29,660
make an image of her presenting.

431
01:11:30,369 --> 01:11:33,038
And it puts the text back in the image,

432
01:11:33,455 --> 01:11:34,748
replicated perfectly, which

433
01:11:34,748 --> 01:11:35,833
you don't usually get with

434
01:11:35,833 --> 01:11:36,250
these engines.

435
01:11:36,458 --> 01:11:37,042
I don't even think

436
01:11:37,042 --> 01:11:38,544
Leonardo gets those right.

437
01:11:38,544 --> 01:11:40,879
Yeah, 100% of the time, I fed it as well,

438
01:11:40,879 --> 01:11:42,548
like our background that we have for some

439
01:11:42,548 --> 01:11:44,008
of these shots like that we've done.

440
01:11:45,009 --> 01:11:46,510
And then also this is Ned.

441
01:11:47,052 --> 01:11:48,971
I tried to change it later on to having

442
01:11:48,971 --> 01:11:50,055
his product like what

443
01:11:50,055 --> 01:11:51,015
you see on Ned's t shirt

444
01:11:51,015 --> 01:11:51,682
right now.

445
01:11:52,808 --> 01:11:54,685
It gave us a horrible kind of looking one

446
01:11:54,685 --> 01:11:55,894
where it made four

447
01:11:55,894 --> 01:11:57,146
people and too many people.

448
01:11:57,563 --> 01:11:57,980
Really weird.

449
01:11:58,188 --> 01:11:59,773
But this is the first shot at just

450
01:11:59,773 --> 01:12:00,899
putting in LinkedIn photos

451
01:12:00,899 --> 01:12:02,276
and stuff and then trying

452
01:12:02,276 --> 01:12:03,736
to create something out of that.

453
01:12:03,736 --> 01:12:04,278
It's not bad.

454
01:12:04,486 --> 01:12:05,320
That's definitely gonna be the cover

455
01:12:05,320 --> 01:12:06,447
image for our next episode.

456
01:12:07,156 --> 01:12:08,073
Yeah, LinkedIn profile.

457
01:12:08,240 --> 01:12:10,200
I'm wearing a shirt and jacket like that.

458
01:12:10,200 --> 01:12:11,744
So it's just a good job on actually

459
01:12:11,744 --> 01:12:12,953
taking the image in that way.

460
01:12:13,328 --> 01:12:15,497
And there's a great, we were talking

461
01:12:15,497 --> 01:12:16,457
about examples and stuff.

462
01:12:17,041 --> 01:12:19,501
Matt Wolf, the other AI, like major

463
01:12:19,501 --> 01:12:20,627
content creator and

464
01:12:20,627 --> 01:12:21,462
stuff, he's got something where

465
01:12:21,462 --> 01:12:22,713
it's like 50 examples

466
01:12:22,713 --> 01:12:23,922
he's seen people using.

467
01:12:24,298 --> 01:12:25,257
So we'll make sure that we

468
01:12:25,257 --> 01:12:26,550
put that link in the show notes.

469
01:12:26,550 --> 01:12:27,718
But what else have you got?

470
01:12:27,718 --> 01:12:29,845
One of the things I've been able to use

471
01:12:29,845 --> 01:12:31,013
it a lot with is my

472
01:12:31,013 --> 01:12:32,222
presentations and pictures

473
01:12:32,389 --> 01:12:35,267
and proposals and even just general

474
01:12:35,267 --> 01:12:36,602
consulting documentation that

475
01:12:36,602 --> 01:12:37,519
I'm using with my customers.

476
01:12:39,021 --> 01:12:40,981
You're able to ask it a query for like

477
01:12:40,981 --> 01:12:43,358
iconography, for example, and then you

478
01:12:43,358 --> 01:12:44,610
can tell it to generate

479
01:12:44,651 --> 01:12:46,820
similar icons to make sure that there's a

480
01:12:46,820 --> 01:12:47,821
consistency on the style.

481
01:12:48,697 --> 01:12:50,741
So no longer is it gonna regenerate a new

482
01:12:50,741 --> 01:12:51,158
image that's

483
01:12:51,158 --> 01:12:52,284
completely different or random.

484
01:12:52,618 --> 01:12:54,161
I can keep that consistency on the color

485
01:12:54,161 --> 01:12:56,205
and the framework with

486
01:12:56,205 --> 01:12:57,456
the inside of that one

487
01:12:57,456 --> 01:12:58,624
chat window, which is awesome.

488
01:12:59,249 --> 01:13:00,292
I've been playing with others instances

489
01:13:00,292 --> 01:13:01,168
where it'll generate an

490
01:13:01,168 --> 01:13:01,960
image and I'm like, oh,

491
01:13:01,960 --> 01:13:03,545
I don't like that piece.

492
01:13:03,962 --> 01:13:04,713
Can you edit that?

493
01:13:05,339 --> 01:13:07,674
And it adjusts that portion of the image

494
01:13:07,674 --> 01:13:08,509
without affecting the

495
01:13:08,509 --> 01:13:09,885
whole thing, which previously,

496
01:13:10,094 --> 01:13:12,262
obviously, Dali wasn't very good at all.

497
01:13:12,679 --> 01:13:14,223
So now I have in this context window that

498
01:13:14,223 --> 01:13:15,265
maintains consistency

499
01:13:15,265 --> 01:13:17,726
for an image like creme

500
01:13:17,810 --> 01:13:18,227
or dilla cram.

501
01:13:18,477 --> 01:13:19,561
I can see there's a really

502
01:13:19,561 --> 01:13:21,063
big unlock for e-commerce here.

503
01:13:21,271 --> 01:13:22,439
I mean, speaking with quite a few

504
01:13:22,439 --> 01:13:23,315
e-commerce companies where

505
01:13:23,315 --> 01:13:24,858
it's really expensive for

506
01:13:24,858 --> 01:13:26,485
them to produce all the product images,

507
01:13:26,485 --> 01:13:27,486
like they have they have

508
01:13:27,486 --> 01:13:28,570
photo studios, they have

509
01:13:28,570 --> 01:13:30,489
to get a product in, get a

510
01:13:30,489 --> 01:13:31,573
model in all that kind of stuff.

511
01:13:31,824 --> 01:13:33,575
So I've been playing around with it this

512
01:13:33,575 --> 01:13:34,576
week at just like fee

513
01:13:34,576 --> 01:13:35,619
in a product and asking

514
01:13:35,619 --> 01:13:37,204
it to put the product on someone.

515
01:13:37,204 --> 01:13:38,664
And yeah, it's looking really promising.

516
01:13:39,039 --> 01:13:40,707
It's a little bit more finessing to get

517
01:13:40,707 --> 01:13:41,875
it really ready for

518
01:13:41,875 --> 01:13:43,293
putting out in a while.

519
01:13:43,460 --> 01:13:46,338
But that'll just be a big time and money

520
01:13:46,338 --> 01:13:48,006
saver for e-commerce companies.

521
01:13:48,006 --> 01:13:49,383
But even dropping in an image now, I

522
01:13:49,383 --> 01:13:49,967
mean, you can do this

523
01:13:49,967 --> 01:13:50,926
pretty easily in Adobe and

524
01:13:50,926 --> 01:13:51,468
other suites.

525
01:13:51,468 --> 01:13:52,469
But if you're not part of the Adobe

526
01:13:52,469 --> 01:13:53,262
suite, or you don't want

527
01:13:53,262 --> 01:13:54,304
to pay for Canva, you can

528
01:13:54,304 --> 01:13:55,764
just drop images and say, get

529
01:13:55,764 --> 01:13:56,598
rid of the background, please.

530
01:13:57,057 --> 01:13:58,016
And it will remove

531
01:13:58,016 --> 01:13:58,976
the background for you.

532
01:13:59,309 --> 01:14:02,271
This is the attempt that it tried to put

533
01:14:02,271 --> 01:14:05,315
on the product edge, AI, a needs company.

534
01:14:06,233 --> 01:14:07,484
It put on the wrong person.

535
01:14:08,360 --> 01:14:10,529
It gave it created extra little things.

536
01:14:10,821 --> 01:14:11,613
Who's the extra person?

537
01:14:12,072 --> 01:14:12,739
Go to Twitter.

538
01:14:13,490 --> 01:14:13,949
Mark's Twitter.

539
01:14:14,867 --> 01:14:16,201
You've been recruited to product.

540
01:14:16,201 --> 01:14:16,827
Yeah, exactly.

541
01:14:17,161 --> 01:14:18,203
So you literally you

542
01:14:18,203 --> 01:14:19,121
can do this kind of stuff.

543
01:14:19,121 --> 01:14:19,913
So if we just scroll back

544
01:14:19,913 --> 01:14:21,123
through here's some of this.

545
01:14:21,623 --> 01:14:23,375
Look, I've got a newsletter founder's

546
01:14:23,375 --> 01:14:24,084
journey I put out like

547
01:14:24,084 --> 01:14:24,877
later this afternoon.

548
01:14:24,877 --> 01:14:25,169
It's Friday.

549
01:14:25,752 --> 01:14:26,628
I'm going to record this.

550
01:14:26,628 --> 01:14:27,379
The first time I did it,

551
01:14:27,379 --> 01:14:28,422
it was like way too angry.

552
01:14:30,591 --> 01:14:32,259
That's that's standard you though.

553
01:14:32,467 --> 01:14:32,885
It is.

554
01:14:33,135 --> 01:14:34,052
And then I made it

555
01:14:34,052 --> 01:14:35,012
like happier and stuff.

556
01:14:35,012 --> 01:14:35,888
That is literally how

557
01:14:35,888 --> 01:14:36,722
I do ride those folks.

558
01:14:37,139 --> 01:14:39,141
So, you know, so you get these one style.

559
01:14:39,141 --> 01:14:40,684
I've seen people do stuff with like Lego

560
01:14:40,684 --> 01:14:43,395
with Minecraft with a whole heap of like

561
01:14:43,395 --> 01:14:45,689
other styles like even make me look like

562
01:14:45,689 --> 01:14:47,065
I'm crocheted kind of

563
01:14:47,065 --> 01:14:48,192
thing like really cool

564
01:14:48,192 --> 01:14:50,235
stuff that if your mind can

565
01:14:50,235 --> 01:14:51,737
imagine it, it can be created.

566
01:14:52,070 --> 01:14:53,488
So scary, interesting

567
01:14:53,488 --> 01:14:55,282
and fun at the same time.

568
01:14:55,490 --> 01:14:55,699
Really.

569
01:14:56,074 --> 01:14:57,659
What other news did you have?

570
01:14:57,659 --> 01:14:59,870
Did you have anything you also saw a

571
01:14:59,870 --> 01:15:02,623
really interesting article on a new video

572
01:15:02,664 --> 01:15:04,708
generation model from

573
01:15:04,708 --> 01:15:06,001
TikTok owner Blight Dance.

574
01:15:06,126 --> 01:15:08,420
So the headline for this was around deep,

575
01:15:08,670 --> 01:15:10,881
deep fact videos getting shockingly good.

576
01:15:11,423 --> 01:15:13,509
So yeah, Blight Dance has released some

577
01:15:13,509 --> 01:15:14,301
research on a model

578
01:15:14,301 --> 01:15:15,427
called On the Human One.

579
01:15:16,178 --> 01:15:18,680
And it takes a single reference of image

580
01:15:18,680 --> 01:15:22,184
and audio and yeah, is generating really

581
01:15:22,267 --> 01:15:25,479
convincing like human videos that could

582
01:15:25,479 --> 01:15:26,355
be used for deep fakes.

583
01:15:26,563 --> 01:15:28,982
So I just think like way things are

584
01:15:28,982 --> 01:15:30,108
heading, I just don't

585
01:15:30,108 --> 01:15:31,360
know where this all lands in

586
01:15:31,401 --> 01:15:33,153
terms of like, you know, the political

587
01:15:33,153 --> 01:15:34,196
process and people

588
01:15:34,196 --> 01:15:36,615
putting together via content in

589
01:15:36,615 --> 01:15:37,950
that kind of domain.

590
01:15:38,200 --> 01:15:39,993
But so they finally watch it because we

591
01:15:39,993 --> 01:15:41,036
remember we talked about this.

592
01:15:41,036 --> 01:15:42,788
This is like many, many months ago, I was

593
01:15:42,788 --> 01:15:43,830
doing like heavy beta.

594
01:15:44,581 --> 01:15:46,875
And it was and obviously the controversy

595
01:15:46,875 --> 01:15:48,585
is how these how this

596
01:15:48,585 --> 01:15:49,419
tool is generating those

597
01:15:49,419 --> 01:15:51,171
videos, which is obviously utilizing

598
01:15:51,171 --> 01:15:53,090
TikTok and social content.

599
01:15:53,966 --> 01:15:55,926
It's this is this is research output.

600
01:15:55,926 --> 01:15:56,760
So I don't think it's

601
01:15:56,760 --> 01:15:57,552
like fully production.

602
01:15:57,844 --> 01:15:58,804
No, no, it's interesting.

603
01:15:58,845 --> 01:16:00,472
They were talking about training 19,000

604
01:16:00,472 --> 01:16:01,640
hours of video content

605
01:16:01,640 --> 01:16:03,308
where underscore sources is.

606
01:16:03,850 --> 01:16:04,059
Yeah.

607
01:16:05,602 --> 01:16:06,270
Same as that.

608
01:16:06,395 --> 01:16:06,812
Yeah.

609
01:16:06,812 --> 01:16:07,104
Yeah.

610
01:16:07,396 --> 01:16:08,522
Yeah, that's that's also a picture.

611
01:16:08,814 --> 01:16:10,357
But on that, like the deep fakes and

612
01:16:10,357 --> 01:16:11,400
stuff, that's a video like

613
01:16:11,400 --> 01:16:12,609
just going back to the image

614
01:16:13,235 --> 01:16:14,820
generation and stuff from OpenAI, the

615
01:16:14,820 --> 01:16:16,029
latest model, like people have been

616
01:16:16,029 --> 01:16:17,030
posting some stuff and you

617
01:16:17,030 --> 01:16:18,198
can find a lot of these examples.

618
01:16:18,407 --> 01:16:19,908
But one was like creating

619
01:16:19,908 --> 01:16:22,035
a deep fake of a passport.

620
01:16:22,452 --> 01:16:23,996
And it looks like the guy's just given

621
01:16:23,996 --> 01:16:25,831
his image and create a passport for it.

622
01:16:25,831 --> 01:16:26,999
Like so the

623
01:16:26,999 --> 01:16:30,627
verification KYC KYB type checks.

624
01:16:31,044 --> 01:16:32,212
Oh, my God, like this is

625
01:16:32,212 --> 01:16:34,006
going to be ridiculously hard.

626
01:16:34,381 --> 01:16:38,176
I think it's a new threat vector for the

627
01:16:38,176 --> 01:16:39,720
cybersecurity around that kind of stuff.

628
01:16:39,928 --> 01:16:41,722
So it's interesting how people will try

629
01:16:41,722 --> 01:16:43,140
to figure all this kind of stuff out.

630
01:16:43,140 --> 01:16:44,308
You know who could solve that?

631
01:16:44,975 --> 01:16:45,183
Blockchain.

632
01:16:46,810 --> 01:16:48,186
Blockchain blocks.

633
01:16:48,937 --> 01:16:49,521
Yeah, it is.

634
01:16:49,730 --> 01:16:50,689
Like I was just saying, like some of the

635
01:16:50,689 --> 01:16:51,773
exchanges, some of the blockchain

636
01:16:51,773 --> 01:16:52,691
exchanges and you have

637
01:16:52,733 --> 01:16:54,776
to hold up your ID and then you have to

638
01:16:54,776 --> 01:16:55,944
swivel the camera around

639
01:16:55,944 --> 01:16:57,571
like you could fool all of that

640
01:16:57,571 --> 01:16:58,739
using Gen AI.

641
01:16:59,031 --> 01:16:59,531
We should try.

642
01:16:59,740 --> 01:17:00,157
We should try.

643
01:17:00,866 --> 01:17:02,200
Look, the next time I leave the country

644
01:17:02,200 --> 01:17:03,160
and come back, you know,

645
01:17:03,160 --> 01:17:04,202
just like hold up some deep

646
01:17:04,202 --> 01:17:04,953
fake photos.

647
01:17:05,662 --> 01:17:05,871
Yeah.

648
01:17:06,204 --> 01:17:07,372
Oh, who knows what will

649
01:17:07,372 --> 01:17:08,248
happen there and stuff.

650
01:17:08,248 --> 01:17:09,583
But I'm definitely on the blockchain side

651
01:17:09,583 --> 01:17:11,126
of things and just like you

652
01:17:11,126 --> 01:17:12,336
there's concepts and we can

653
01:17:12,336 --> 01:17:14,046
dive into that like separately in another

654
01:17:14,046 --> 01:17:15,047
kind of conversation.

655
01:17:15,380 --> 01:17:18,175
But around like how you can the only

656
01:17:18,175 --> 01:17:19,676
person that could have generated that

657
01:17:19,676 --> 01:17:20,927
initial image or that

658
01:17:20,969 --> 01:17:23,680
ID and anything subsequent to that, there

659
01:17:23,680 --> 01:17:24,848
are ways that blockchain

660
01:17:24,848 --> 01:17:25,807
and something called zero

661
01:17:25,807 --> 01:17:29,144
knowledge proofs can be used to create

662
01:17:29,144 --> 01:17:30,020
those ways that it's

663
01:17:30,020 --> 01:17:31,313
only ever that person.

664
01:17:31,313 --> 01:17:32,606
I mean, the Australian government is

665
01:17:32,606 --> 01:17:35,150
testing decentralized kind of technology.

666
01:17:35,150 --> 01:17:36,401
They're not saying blockchain, but hey,

667
01:17:36,652 --> 01:17:37,611
decentralized is probably

668
01:17:37,611 --> 01:17:38,653
blockchain and cryptography

669
01:17:38,779 --> 01:17:41,281
involved around national digital IDs.

670
01:17:41,907 --> 01:17:43,658
There being use cases that have come out

671
01:17:43,658 --> 01:17:44,493
of the Commonwealth Bank

672
01:17:44,493 --> 01:17:46,620
and a GP up in Queensland.

673
01:17:46,912 --> 01:17:49,539
So it's starting to be tested and honed.

674
01:17:49,539 --> 01:17:51,583
So yeah, I think there will be solutions

675
01:17:51,583 --> 01:17:53,668
coming, but it might just be

676
01:17:53,668 --> 01:17:55,128
this period of time where we

677
01:17:55,128 --> 01:17:57,464
don't have a proper full blown solution

678
01:17:57,464 --> 01:17:59,091
for the deep fakes right now.

679
01:17:59,091 --> 01:17:59,966
But but let's see.

680
01:18:01,760 --> 01:18:04,513
In small quick find use something that

681
01:18:04,513 --> 01:18:06,932
there's been a big media sort of I

682
01:18:06,932 --> 01:18:08,016
wouldn't say outrage, but just

683
01:18:08,016 --> 01:18:09,351
big call out around

684
01:18:09,351 --> 01:18:11,728
Apple's integration of AI.

685
01:18:11,728 --> 01:18:12,729
Has anyone seen this stuff yet?

686
01:18:12,938 --> 01:18:14,439
No, it was a Google user.

687
01:18:14,731 --> 01:18:15,565
Sorry, Google users.

688
01:18:15,565 --> 01:18:17,192
Yeah, I'm a Google user like Marquez

689
01:18:17,192 --> 01:18:18,026
Brownlee, one of the

690
01:18:18,026 --> 01:18:19,486
famous YouTubers out there.

691
01:18:19,820 --> 01:18:21,571
He was came out and just talking about

692
01:18:21,571 --> 01:18:23,949
the fact that Apple in its has been

693
01:18:23,949 --> 01:18:25,033
talking about integration of

694
01:18:25,033 --> 01:18:27,411
AI into their tools for so long now.

695
01:18:27,911 --> 01:18:29,955
And they are so far behind the playing

696
01:18:29,955 --> 01:18:31,873
field that it's become almost

697
01:18:31,873 --> 01:18:32,582
uncomfortable for

698
01:18:32,582 --> 01:18:33,792
people to talk about it.

699
01:18:34,876 --> 01:18:35,627
They've you know, they've even just

700
01:18:35,627 --> 01:18:36,753
raised their latest, I think, another

701
01:18:36,753 --> 01:18:37,838
update to the iOS and

702
01:18:37,838 --> 01:18:39,256
still no update to any of

703
01:18:39,256 --> 01:18:41,341
the the AI features.

704
01:18:41,883 --> 01:18:43,176
And so there's just been a little bit of

705
01:18:43,176 --> 01:18:45,470
a kind of like a fear.

706
01:18:45,470 --> 01:18:46,638
Are they falling behind?

707
01:18:46,638 --> 01:18:49,141
Are they losing that battle in that space

708
01:18:49,141 --> 01:18:50,642
to keeping up with the other

709
01:18:50,642 --> 01:18:51,726
players that are out there?

710
01:18:52,060 --> 01:18:53,228
We've seen the likes of this.

711
01:18:53,228 --> 01:18:55,772
Like there was comparisons drawn to, you

712
01:18:55,772 --> 01:18:56,982
know, like Nokia in the

713
01:18:56,982 --> 01:18:59,484
past and other brands like

714
01:18:59,484 --> 01:19:03,947
what was the comparison of like

715
01:19:03,947 --> 01:19:05,907
Blackberry, all those brands who used to

716
01:19:05,907 --> 01:19:07,033
be the big players, right?

717
01:19:07,159 --> 01:19:08,076
Maybe suddenly weren't

718
01:19:08,076 --> 01:19:08,952
innovating in the space.

719
01:19:08,952 --> 01:19:10,454
I don't think Apple is going to fall into

720
01:19:10,454 --> 01:19:13,874
those categories, but it is a sort of

721
01:19:13,874 --> 01:19:15,417
like that first step where you start to

722
01:19:15,459 --> 01:19:17,002
recognize someone who is such a big

723
01:19:17,002 --> 01:19:20,589
player suddenly lag behind where everyone

724
01:19:20,589 --> 01:19:21,631
is going in that space.

725
01:19:21,840 --> 01:19:24,092
Is it because they tried to name it Apple

726
01:19:24,092 --> 01:19:26,219
Intelligence rather than guys?

727
01:19:26,511 --> 01:19:27,596
It's just AI. It's

728
01:19:27,596 --> 01:19:28,513
artificial intelligence.

729
01:19:28,805 --> 01:19:30,056
Just stick with the public.

730
01:19:30,640 --> 01:19:31,141
It's probably one of

731
01:19:31,141 --> 01:19:32,517
their weird media pushes.

732
01:19:32,726 --> 01:19:34,769
I think it's also a lot to do with the I

733
01:19:34,769 --> 01:19:36,313
think with how their business focuses on

734
01:19:36,313 --> 01:19:37,731
that hardware and

735
01:19:37,731 --> 01:19:38,607
they've fallen a bit behind

736
01:19:38,607 --> 01:19:39,691
on the software when it comes to

737
01:19:39,691 --> 01:19:41,443
integration with their phones.

738
01:19:43,111 --> 01:19:43,904
No one knows why.

739
01:19:43,904 --> 01:19:45,030
I think they had a few

740
01:19:45,030 --> 01:19:46,114
issues when they launched.

741
01:19:46,615 --> 01:19:48,700
We talked about this where they were

742
01:19:48,700 --> 01:19:50,827
summarizing posts really badly.

743
01:19:50,827 --> 01:19:52,120
You know, when you pull down and you've

744
01:19:52,120 --> 01:19:52,454
got all your

745
01:19:52,454 --> 01:19:54,080
summarizations on your Apple phone?

746
01:19:54,331 --> 01:19:54,748
No, is there?

747
01:19:54,748 --> 01:19:55,290
Yeah, you're on Apple phone.

748
01:19:55,749 --> 01:19:58,960
And what it was doing was someone might

749
01:19:58,960 --> 01:20:00,837
have a bunch of cameras around the house

750
01:20:00,837 --> 01:20:02,088
and people are walking by.

751
01:20:02,088 --> 01:20:03,632
And if a camera might pick up two or

752
01:20:03,632 --> 01:20:04,716
three people as walk by and

753
01:20:04,716 --> 01:20:05,717
suddenly the alert will say,

754
01:20:05,926 --> 01:20:07,135
"Your house is being attacked by all

755
01:20:07,135 --> 01:20:08,261
these people surrounding you."

756
01:20:09,054 --> 01:20:12,182
One of the hilarious ones was a mother

757
01:20:12,182 --> 01:20:14,518
was going for a hike and she

758
01:20:14,518 --> 01:20:15,852
messaged her daughter going,

759
01:20:15,852 --> 01:20:17,896
"Oh man, that hike killed me."

760
01:20:18,063 --> 01:20:18,897
And I sent an emergency

761
01:20:18,897 --> 01:20:20,232
saying, "Oh, your mum's dying."

762
01:20:22,192 --> 01:20:22,943
So it was summarizing

763
01:20:22,943 --> 01:20:23,818
things really poorly.

764
01:20:23,818 --> 01:20:24,986
So it was a lot of the they were having a

765
01:20:24,986 --> 01:20:25,987
lot of problems with their integration

766
01:20:25,987 --> 01:20:27,364
with their eye to a point where

767
01:20:27,989 --> 01:20:30,784
they stopped a lot of the media that was

768
01:20:30,784 --> 01:20:32,202
surrounding it and really

769
01:20:32,202 --> 01:20:33,662
haven't just spoken about it.

770
01:20:33,662 --> 01:20:35,413
I could imagine one where it's like,

771
01:20:35,413 --> 01:20:35,830
because I was thinking

772
01:20:35,830 --> 01:20:36,623
there was a funny one.

773
01:20:36,665 --> 01:20:37,999
I thought it might be something like, you

774
01:20:37,999 --> 01:20:39,584
know, you might send me a message going,

775
01:20:39,584 --> 01:20:40,627
"Hey, man, I'm running out of time."

776
01:20:40,627 --> 01:20:41,169
And then this summer

777
01:20:41,169 --> 01:20:42,546
would be, "Chris has expired."

778
01:20:43,838 --> 01:20:45,090
What the heck, Apple?

779
01:20:45,507 --> 01:20:47,259
This is not what we meant, like figure

780
01:20:47,259 --> 01:20:49,010
out context and stuff. It's crazy.

781
01:20:49,803 --> 01:20:51,388
Chris, I was going to ask you, so Siri,

782
01:20:51,680 --> 01:20:53,139
have they rolled out any improvements?

783
01:20:53,390 --> 01:20:53,682
No.

784
01:20:53,682 --> 01:20:54,015
With Siri?

785
01:20:54,266 --> 01:20:55,642
No. So Siri hasn't had any

786
01:20:55,642 --> 01:20:57,561
improvements for AI integration.

787
01:20:58,812 --> 01:21:01,481
None of the Apple pods or the, you know,

788
01:21:01,773 --> 01:21:04,067
any of their headset devices or speaker

789
01:21:04,067 --> 01:21:05,360
devices haven't had any updates.

790
01:21:05,777 --> 01:21:06,862
Whereas you've got businesses like

791
01:21:06,862 --> 01:21:08,446
Google, like Gemini, is fully integrated

792
01:21:08,446 --> 01:21:09,698
into the Android and all

793
01:21:09,698 --> 01:21:10,615
of their speaker systems.

794
01:21:10,991 --> 01:21:11,199
Yeah.

795
01:21:11,700 --> 01:21:13,451
Google Assistant still sucks. I don't

796
01:21:13,451 --> 01:21:14,452
know if they've ever rolled out.

797
01:21:14,452 --> 01:21:16,454
Well, the Gemini, if you have the Gemini

798
01:21:16,454 --> 01:21:17,664
subscription or you

799
01:21:17,664 --> 01:21:19,040
are now on the Gemini,

800
01:21:19,040 --> 01:21:21,251
all of my stuff at home is Gemini. It's

801
01:21:21,251 --> 01:21:22,794
not. It's no longer Google Assistant.

802
01:21:22,794 --> 01:21:23,128
Yeah, okay.

803
01:21:24,045 --> 01:21:24,796
But don't you prompt for me

804
01:21:24,796 --> 01:21:25,714
to stay up time for that one.

805
01:21:25,880 --> 01:21:26,089
Yeah.

806
01:21:26,506 --> 01:21:27,465
It's a good thing to explore.

807
01:21:27,924 --> 01:21:29,801
Yeah, because I mean, yeah, Google

808
01:21:29,801 --> 01:21:31,595
Assistant and Siri have both been just a

809
01:21:31,595 --> 01:21:32,304
joke for a long time.

810
01:21:32,345 --> 01:21:34,306
They have been. They really have been

811
01:21:34,306 --> 01:21:35,890
falling behind. But Gemini

812
01:21:35,890 --> 01:21:37,017
does change the game of that.

813
01:21:37,767 --> 01:21:40,020
But yeah, so just a little funny call out

814
01:21:40,020 --> 01:21:41,605
there. Interesting to see

815
01:21:41,605 --> 01:21:42,731
someone who is such a big

816
01:21:42,731 --> 01:21:44,232
player in the tech space not been up

817
01:21:44,232 --> 01:21:45,734
there with the other AI systems.

818
01:21:46,693 --> 01:21:47,485
Not at all.

819
01:21:47,861 --> 01:21:48,945
Any last call outs?

820
01:21:49,988 --> 01:21:51,448
Oh, a quick one I had was just like

821
01:21:51,448 --> 01:21:53,074
interesting to see where investments

822
01:21:53,074 --> 01:21:54,242
going in the VC space.

823
01:21:54,784 --> 01:21:59,122
Right. 110 billion dollars out of a total of 227

824
01:21:59,122 --> 01:22:01,041
invested from VCs and

825
01:22:01,041 --> 01:22:02,917
startups in the last year went into

826
01:22:03,209 --> 01:22:06,087
Gen AI. So actually investment in non Gen

827
01:22:06,087 --> 01:22:07,339
AI related startups went

828
01:22:07,339 --> 01:22:09,215
backwards 17%. So I mean,

829
01:22:09,215 --> 01:22:11,509
not surprising, just just a flood of

830
01:22:11,509 --> 01:22:12,469
money going in that direction

831
01:22:12,469 --> 01:22:14,220
and fueling the explosion of

832
01:22:14,304 --> 01:22:15,722
startups that we're seeing in that space.

833
01:22:16,306 --> 01:22:18,058
So if you're if you're a founder of a Gen

834
01:22:18,099 --> 01:22:19,559
AI related startup,

835
01:22:19,809 --> 01:22:20,477
you're in a good spot.

836
01:22:21,186 --> 01:22:24,564
Yeah, nice. There's a great little tool

837
01:22:24,564 --> 01:22:26,066
here on crunch base,

838
01:22:26,066 --> 01:22:27,067
which talks to a lot of the

839
01:22:27,067 --> 01:22:28,568
businesses and organizations. So we're

840
01:22:28,568 --> 01:22:29,611
looking at like almost up to

841
01:22:29,611 --> 01:22:31,905
10,000 AI businesses coming

842
01:22:31,905 --> 01:22:36,409
through the ranks and just getting a

843
01:22:36,409 --> 01:22:37,619
refresh on how to pay

844
01:22:37,619 --> 01:22:38,828
billions of dollars that are getting

845
01:22:38,870 --> 01:22:40,622
thrown into the system, like all the big

846
01:22:40,622 --> 01:22:41,456
call outs of the anyone's

847
01:22:41,456 --> 01:22:43,750
coming up like Celestial AI and

848
01:22:44,334 --> 01:22:46,378
Nextoper getting lots of investments. And

849
01:22:46,378 --> 01:22:48,129
yeah, like money is being

850
01:22:48,129 --> 01:22:49,214
thrown around in this space

851
01:22:49,297 --> 01:22:51,132
funding there we go. 300 billion dollars

852
01:22:51,132 --> 01:22:51,966
has been thrown in the

853
01:22:51,966 --> 01:22:53,677
last sort of like year or so.

854
01:22:53,843 --> 01:22:55,178
It is it's insane.

855
01:22:55,178 --> 01:22:56,680
What's happening? A lot of parallels of

856
01:22:56,680 --> 01:22:58,556
late 90s in the original dot com.

857
01:22:58,556 --> 01:23:00,767
It is absolutely very well show companies

858
01:23:00,767 --> 01:23:02,310
and just like hopefully this time around,

859
01:23:02,310 --> 01:23:03,812
we're not going to see as large bubble

860
01:23:03,812 --> 01:23:05,480
pop at the end of it. But you know,

861
01:23:05,480 --> 01:23:06,106
there's definitely a lot

862
01:23:06,106 --> 01:23:06,523
of substance.

863
01:23:06,815 --> 01:23:07,899
The damage blockchain right when that

864
01:23:07,899 --> 01:23:09,734
that boom couple years ago, like the

865
01:23:09,734 --> 01:23:10,276
money getting thrown

866
01:23:10,360 --> 01:23:13,196
into that was insane. But AI

867
01:23:13,196 --> 01:23:15,073
much larger. But yeah, cool.

868
01:23:17,200 --> 01:23:19,035
Ned. Right. Yeah, we'd love to have a

869
01:23:19,035 --> 01:23:19,953
proper chat with you, man.

870
01:23:19,953 --> 01:23:21,204
It was great. Thank you for

871
01:23:21,204 --> 01:23:23,039
contributing to the news, man. Yeah,

872
01:23:23,039 --> 01:23:23,998
there's lots of stuff happening in the

873
01:23:23,998 --> 01:23:25,125
space and we'll share

874
01:23:25,125 --> 01:23:28,420
those links out. But so we didn't really

875
01:23:28,420 --> 01:23:30,547
do a proper introduction. No, we don't.

876
01:23:30,547 --> 01:23:35,760
At the start, but husband, father, one,

877
01:23:35,969 --> 01:23:37,262
two, two kids, two kids.

878
01:23:37,679 --> 01:23:39,180
Yeah. My dad stats.

879
01:23:39,597 --> 01:23:40,390
Oh, very nice.

880
01:23:40,390 --> 01:23:41,599
As he my flake says. And

881
01:23:41,599 --> 01:23:42,976
yes, that great podcast.

882
01:23:43,685 --> 01:23:44,602
Two's a good balance.

883
01:23:44,602 --> 01:23:44,936
Dad's dad.

884
01:23:45,228 --> 01:23:47,063
Two's a good balance. I like that. Tech

885
01:23:47,063 --> 01:23:48,398
entrepreneur, 20 years of

886
01:23:48,398 --> 01:23:49,399
experience in innovation.

887
01:23:49,733 --> 01:23:51,317
You worked at Google, Eventbrite,

888
01:23:51,317 --> 01:23:53,319
Macquarie Bank, even you

889
01:23:53,319 --> 01:23:55,029
co-founded a taxi and ride

890
01:23:55,029 --> 01:23:56,865
sharing platform with go

891
01:23:56,865 --> 01:23:57,741
catch, which is awesome.

892
01:23:58,032 --> 01:23:58,908
Went ahead to head with

893
01:23:58,908 --> 01:24:00,160
Uber in the Australian markets.

894
01:24:00,493 --> 01:24:01,619
Yeah, which is pretty massive.

895
01:24:01,911 --> 01:24:02,579
That was interesting.

896
01:24:02,829 --> 01:24:05,415
Scaled that to over $30 million and now

897
01:24:05,415 --> 01:24:07,041
you've started your own company,

898
01:24:07,041 --> 01:24:08,001
Product Edge AI.

899
01:24:08,334 --> 01:24:08,668
That's right.

900
01:24:09,252 --> 01:24:10,795
So you're helping businesses grow through

901
01:24:10,795 --> 01:24:15,508
strategic adoption and scaling rapidly as

902
01:24:15,842 --> 01:24:17,969
they're getting a lot of traction. So do

903
01:24:17,969 --> 01:24:18,636
you want to talk to us a bit

904
01:24:18,636 --> 01:24:20,346
about what your business is?

905
01:24:20,597 --> 01:24:22,223
Yeah, sure. Yeah, I mean, the business

906
01:24:22,223 --> 01:24:23,767
model that I'm pursuing

907
01:24:23,767 --> 01:24:25,894
gets referred to a bit as an AI

908
01:24:25,894 --> 01:24:27,687
automation agency. So coming into a

909
01:24:27,687 --> 01:24:28,980
company, basically helping

910
01:24:28,980 --> 01:24:30,356
them to just navigate where

911
01:24:30,565 --> 01:24:33,401
the best areas are to invest into rapidly

912
01:24:33,401 --> 01:24:35,361
prototyping solutions for them as well.

913
01:24:35,737 --> 01:24:37,238
Just like act as a catalyst because at

914
01:24:37,238 --> 01:24:37,947
the moment, there's just a

915
01:24:37,947 --> 01:24:38,865
hell of a lot of companies out

916
01:24:38,865 --> 01:24:40,533
there where they just don't really know

917
01:24:40,533 --> 01:24:41,576
where to start and not getting the

918
01:24:41,576 --> 01:24:42,452
traction internally.

919
01:24:43,536 --> 01:24:44,662
The client I've been working really

920
01:24:44,662 --> 01:24:46,456
closely with, the founder was hearing

921
01:24:46,456 --> 01:24:47,665
from other founders of

922
01:24:47,665 --> 01:24:49,042
the kind of impacts that they were

923
01:24:49,042 --> 01:24:50,585
getting from Gen AI. And he's like, we

924
01:24:50,585 --> 01:24:51,294
need to get more of this

925
01:24:51,294 --> 01:24:53,463
happening ourselves. So yeah, so coming

926
01:24:53,463 --> 01:24:54,214
into a business, helping

927
01:24:54,214 --> 01:24:55,840
them with that, getting on the

928
01:24:55,840 --> 01:24:57,675
tools, building out things, just like

929
01:24:57,675 --> 01:24:58,760
demonstrating to them what's

930
01:24:58,760 --> 01:25:00,470
possible and then helping the

931
01:25:00,512 --> 01:25:02,180
teams to run with it from there. So yeah,

932
01:25:02,180 --> 01:25:02,931
it's a huge opportunity in

933
01:25:02,931 --> 01:25:04,140
that space as you guys can

934
01:25:04,557 --> 01:25:06,142
no doubt imagine. Yeah, that's awesome.

935
01:25:06,768 --> 01:25:07,644
What type of like, I

936
01:25:07,644 --> 01:25:08,478
guess in that opportunity,

937
01:25:08,478 --> 01:25:10,480
so speaking of the client, obviously,

938
01:25:10,480 --> 01:25:11,606
don't have to say names or

939
01:25:11,606 --> 01:25:12,524
call them out, but what are the

940
01:25:12,524 --> 01:25:14,317
types of things when it comes to Gen AI,

941
01:25:14,818 --> 01:25:15,610
are you seeing that they're

942
01:25:15,610 --> 01:25:16,903
needing to start implementing

943
01:25:16,945 --> 01:25:19,197
to help them that scale? What are the

944
01:25:19,197 --> 01:25:20,532
tools that are benefiting

945
01:25:20,532 --> 01:25:21,449
them in the product space?

946
01:25:22,200 --> 01:25:23,743
Yeah, well, I mean, it was probably

947
01:25:23,743 --> 01:25:25,495
useful for me to talk a little bit about

948
01:25:25,495 --> 01:25:26,371
the use cases that we

949
01:25:26,412 --> 01:25:28,665
narrowed down on and ended up building

950
01:25:28,665 --> 01:25:30,500
some solutions around. So,

951
01:25:30,500 --> 01:25:32,293
you know, the low hanging

952
01:25:32,293 --> 01:25:34,337
fruit for a lot of companies is internal

953
01:25:34,337 --> 01:25:35,505
efficiencies, like

954
01:25:35,505 --> 01:25:36,965
optimizing and automating

955
01:25:37,298 --> 01:25:39,134
internal workflows. So I've got a couple

956
01:25:39,134 --> 01:25:39,968
of solutions for them

957
01:25:39,968 --> 01:25:41,469
around that. So yeah, e-commerce

958
01:25:41,511 --> 01:25:43,805
client, and they had a pretty common use

959
01:25:43,805 --> 01:25:45,348
case where they had a lot of products

960
01:25:45,348 --> 01:25:46,015
that they're having to

961
01:25:46,015 --> 01:25:47,851
load onto the site. And they get a whole

962
01:25:47,851 --> 01:25:49,060
bunch of information from

963
01:25:49,060 --> 01:25:50,854
the suppliers of the products.

964
01:25:51,104 --> 01:25:52,522
And then they have to apply all their

965
01:25:52,522 --> 01:25:54,399
tagging and categorization

966
01:25:54,399 --> 01:25:55,775
to load it up onto the site.

967
01:25:55,859 --> 01:25:57,694
It's like super manual process. It's like

968
01:25:57,694 --> 01:25:58,736
a human sitting down

969
01:25:58,736 --> 01:26:00,363
half an hour per product,

970
01:26:00,363 --> 01:26:01,990
reading through the description and doing

971
01:26:01,990 --> 01:26:03,199
all the tagging. So anyway,

972
01:26:03,199 --> 01:26:04,617
like great application for

973
01:26:04,784 --> 01:26:06,828
LLMs, because you just feed both those

974
01:26:06,828 --> 01:26:07,537
bits of information

975
01:26:07,537 --> 01:26:08,955
and have it auto generate

976
01:26:09,455 --> 01:26:11,541
on the output. And the good one about

977
01:26:11,541 --> 01:26:12,542
that, it's an example of

978
01:26:12,542 --> 01:26:14,002
where like the technology can

979
01:26:14,002 --> 01:26:16,045
probably get you about 70 or 80% of where

980
01:26:16,045 --> 01:26:17,005
you need, because you still

981
01:26:17,005 --> 01:26:18,631
need a human to review that and

982
01:26:18,882 --> 01:26:21,134
add to it and refine it a bit. But the

983
01:26:21,134 --> 01:26:22,719
time saving of that

984
01:26:22,719 --> 01:26:24,178
automation piece is massive,

985
01:26:24,262 --> 01:26:25,930
because it's like you can cut half an

986
01:26:25,930 --> 01:26:27,140
hour down to five minute

987
01:26:27,140 --> 01:26:28,308
review of what comes out of the

988
01:26:28,308 --> 01:26:30,852
LMs. So yeah, so there's really good

989
01:26:30,852 --> 01:26:32,061
opportunities in that space. The other

990
01:26:32,061 --> 01:26:32,854
thing in e-commerce as

991
01:26:32,854 --> 01:26:34,898
well is around personalization and

992
01:26:34,898 --> 01:26:35,732
marketing. Like marketing,

993
01:26:36,190 --> 01:26:37,150
out of all the functional parts

994
01:26:37,150 --> 01:26:38,693
of business, marketing was where there

995
01:26:38,693 --> 01:26:39,277
were the most

996
01:26:39,277 --> 01:26:42,697
opportunities, I think. And so like for a

997
01:26:42,697 --> 01:26:44,699
long time, I think hyper personalization

998
01:26:44,699 --> 01:26:46,159
has been like this holy grail in

999
01:26:46,159 --> 01:26:46,993
e-commerce that people

1000
01:26:46,993 --> 01:26:48,703
were moving towards and trying to

1001
01:26:48,703 --> 01:26:49,704
achieve, but the technology

1002
01:26:49,704 --> 01:26:51,164
hasn't been there. So yeah,

1003
01:26:51,205 --> 01:26:53,291
so building us some solutions for them to

1004
01:26:53,291 --> 01:26:54,792
deliver on that. So you

1005
01:26:54,792 --> 01:26:55,793
know a lot about the customer,

1006
01:26:56,252 --> 01:26:58,379
generate the images and content that's

1007
01:26:58,379 --> 01:27:00,423
like super tailored to what they need.

1008
01:27:00,798 --> 01:27:01,883
And that all converts

1009
01:27:01,925 --> 01:27:03,426
much better and makes marketing and foot

1010
01:27:03,426 --> 01:27:04,344
more effective. And are

1011
01:27:04,344 --> 01:27:07,180
we talking like workflow or

1012
01:27:07,180 --> 01:27:10,350
agentic generation in terms of creating

1013
01:27:10,350 --> 01:27:12,685
solutions that there's like one click

1014
01:27:12,685 --> 01:27:13,561
based on the insights

1015
01:27:13,603 --> 01:27:15,688
or still are they at that level of just

1016
01:27:15,688 --> 01:27:16,439
playing around with the

1017
01:27:16,439 --> 01:27:18,149
tools to help them? Yeah, so for

1018
01:27:18,149 --> 01:27:20,026
the personalization when I built a web

1019
01:27:20,026 --> 01:27:21,736
app for them that their

1020
01:27:21,736 --> 01:27:23,237
marketing team can then feed the

1021
01:27:23,237 --> 01:27:25,531
images in, it'll generate all the

1022
01:27:25,531 --> 01:27:28,201
variants of the images. But there's a

1023
01:27:28,201 --> 01:27:29,911
human curation step to that

1024
01:27:29,911 --> 01:27:31,371
because like you guys have seen like a

1025
01:27:31,371 --> 01:27:33,414
lot of, you just get a lot of

1026
01:27:33,414 --> 01:27:34,874
like it's hit and miss work,

1027
01:27:34,874 --> 01:27:36,250
kind of the images it generates. Although

1028
01:27:36,250 --> 01:27:37,210
I'm gonna say like playing

1029
01:27:37,210 --> 01:27:38,795
around with OpenAI's latest

1030
01:27:38,795 --> 01:27:41,047
image gen and I've used it for the type

1031
01:27:41,047 --> 01:27:42,090
of use case I've built for

1032
01:27:42,090 --> 01:27:44,217
this client and it is actually

1033
01:27:44,300 --> 01:27:45,885
hitting it each time. So it's awesome

1034
01:27:45,885 --> 01:27:47,428
because it can cut down the

1035
01:27:47,428 --> 01:27:48,638
need for the human curation.

1036
01:27:48,638 --> 01:27:51,015
Are you using the new one that like is

1037
01:27:51,015 --> 01:27:51,933
out in charge UBT? Is

1038
01:27:51,933 --> 01:27:53,226
there API for that already?

1039
01:27:53,518 --> 01:27:55,061
No, yes, I've just been like manually

1040
01:27:55,061 --> 01:27:56,771
testing that in the entire interface. So

1041
01:27:56,771 --> 01:27:57,772
next step will be to

1042
01:27:57,939 --> 01:28:00,066
get into the product solution. And yeah,

1043
01:28:00,066 --> 01:28:02,819
you can swap out LM. So anyway, so to

1044
01:28:02,819 --> 01:28:03,444
answer your question

1045
01:28:03,486 --> 01:28:06,155
Chris, yeah, so it's a tool that they

1046
01:28:06,155 --> 01:28:07,865
then do the human creation and it pushes

1047
01:28:07,865 --> 01:28:08,992
the images into their

1048
01:28:08,992 --> 01:28:11,160
email marketing platform. So like that's

1049
01:28:11,160 --> 01:28:11,744
a big thing is like

1050
01:28:11,744 --> 01:28:13,663
plugging their pieces together of

1051
01:28:13,663 --> 01:28:15,790
their existing platforms like Legos.

1052
01:28:16,374 --> 01:28:17,875
Yeah, yeah. So like, you know, automation

1053
01:28:17,875 --> 01:28:19,127
platforms like make.com

1054
01:28:19,127 --> 01:28:21,170
and n8n are great for doing that in a

1055
01:28:21,170 --> 01:28:24,298
really in a low code way. But yeah, I

1056
01:28:24,298 --> 01:28:24,966
mean, that's another

1057
01:28:24,966 --> 01:28:26,551
thing I do is come in and like help them

1058
01:28:26,551 --> 01:28:27,719
work out out of all the

1059
01:28:27,719 --> 01:28:29,220
platforms are already paying for,

1060
01:28:29,429 --> 01:28:31,139
how can I get more out of it because all

1061
01:28:31,139 --> 01:28:32,098
these SaaS platforms are

1062
01:28:32,098 --> 01:28:33,474
all rolling out lots of gen AI

1063
01:28:33,474 --> 01:28:35,435
features. So it's like, let's start

1064
01:28:35,435 --> 01:28:36,561
there. Let's just try and get the most

1065
01:28:36,561 --> 01:28:37,353
out of the tools that

1066
01:28:37,353 --> 01:28:38,896
you're using at the moment before we

1067
01:28:38,896 --> 01:28:39,897
start trying to build custom

1068
01:28:39,897 --> 01:28:41,274
things and add on top of that.

1069
01:28:41,274 --> 01:28:43,818
How do you figure with like, whether it's

1070
01:28:43,818 --> 01:28:45,737
those existing tools, or

1071
01:28:45,737 --> 01:28:47,321
it's like the ones where maybe

1072
01:28:47,530 --> 01:28:49,574
there isn't something that really hits

1073
01:28:49,574 --> 01:28:50,575
the mark with what it is

1074
01:28:50,575 --> 01:28:52,160
that they're after? Yeah. How do

1075
01:28:52,160 --> 01:28:54,662
you engage with folks when it comes to A

1076
01:28:54,662 --> 01:28:55,997
and I think these are

1077
01:28:55,997 --> 01:28:58,833
related. One concept or one area

1078
01:28:58,833 --> 01:29:00,960
is around education. And then the other

1079
01:29:00,960 --> 01:29:02,628
areas around trust, right?

1080
01:29:02,628 --> 01:29:03,629
And they kind of go hand in

1081
01:29:03,629 --> 01:29:05,798
hand because we see it a lot in the

1082
01:29:05,798 --> 01:29:08,676
business that we do where there are some

1083
01:29:08,676 --> 01:29:10,053
levels of maturity that

1084
01:29:10,094 --> 01:29:12,221
need to be hit before they even want to

1085
01:29:12,221 --> 01:29:13,306
engage and stuff with you.

1086
01:29:13,306 --> 01:29:14,515
And even then when they're

1087
01:29:14,515 --> 01:29:16,309
starting to roll through it, it's like

1088
01:29:16,309 --> 01:29:17,477
seeing the outputs, can they

1089
01:29:17,477 --> 01:29:19,020
trust it? How do they have,

1090
01:29:19,312 --> 01:29:21,064
how do these tools have a process to

1091
01:29:21,064 --> 01:29:23,149
ensure that humans are in the loop kind

1092
01:29:23,149 --> 01:29:23,941
of thing and like they

1093
01:29:23,941 --> 01:29:25,401
can review and all that kind of stuff.

1094
01:29:25,401 --> 01:29:26,944
What have you experienced there and like

1095
01:29:26,944 --> 01:29:27,904
education and trust?

1096
01:29:28,446 --> 01:29:30,490
Yeah, I mean, like I definitely, early

1097
01:29:30,490 --> 01:29:31,282
part of this engagement

1098
01:29:31,282 --> 01:29:32,366
with this client, there was an

1099
01:29:32,366 --> 01:29:33,951
education piece to it rolling out and

1100
01:29:33,951 --> 01:29:35,828
doing some workshops with the various

1101
01:29:35,828 --> 01:29:36,621
teams and just kind of

1102
01:29:36,704 --> 01:29:38,873
starting to present back really relevant

1103
01:29:38,873 --> 01:29:39,665
information to them

1104
01:29:39,665 --> 01:29:40,500
around how they can apply

1105
01:29:40,500 --> 01:29:41,626
in their business and what other

1106
01:29:41,626 --> 01:29:42,460
companies are doing. I think

1107
01:29:42,460 --> 01:29:44,545
that people need proof points

1108
01:29:44,545 --> 01:29:46,339
with new technology that like see that

1109
01:29:46,339 --> 01:29:46,881
it's actually

1110
01:29:46,881 --> 01:29:48,716
delivering results and having the

1111
01:29:48,716 --> 01:29:51,177
impact that the teams need. So it's kind

1112
01:29:51,177 --> 01:29:52,512
of just like leading them a

1113
01:29:52,512 --> 01:29:53,262
little bit with that kind of

1114
01:29:53,262 --> 01:29:55,973
information and then just jumping in and

1115
01:29:55,973 --> 01:29:56,641
building something that

1116
01:29:56,641 --> 01:29:58,101
actually saves them time straight

1117
01:29:58,101 --> 01:30:00,269
away. They can start getting a sense of

1118
01:30:00,269 --> 01:30:01,020
how it's going to be

1119
01:30:01,020 --> 01:30:02,396
valuable to them. But yeah, look,

1120
01:30:02,480 --> 01:30:05,274
there's a lot. I find you get companies

1121
01:30:05,274 --> 01:30:07,318
where it tends to be like

1122
01:30:07,318 --> 01:30:09,529
CEO founder led initiative of

1123
01:30:09,529 --> 01:30:11,531
like we need to do this. Like I go to top

1124
01:30:11,531 --> 01:30:12,532
leadership level. That's

1125
01:30:12,532 --> 01:30:13,574
where the imperative is like,

1126
01:30:13,699 --> 01:30:15,159
there's a big opportunity around Gen AI,

1127
01:30:15,159 --> 01:30:16,994
let's get moving on this. But

1128
01:30:16,994 --> 01:30:18,496
everyone kind of on the cold

1129
01:30:18,496 --> 01:30:20,998
face is kind of like so busy with BAU

1130
01:30:20,998 --> 01:30:22,208
work. It's hard to get

1131
01:30:22,208 --> 01:30:24,168
them to allocate the time to

1132
01:30:24,418 --> 01:30:26,045
up around. So yeah, you've got to

1133
01:30:26,045 --> 01:30:27,296
convince them that it's going to be worth

1134
01:30:27,296 --> 01:30:28,214
making that investment.

1135
01:30:28,464 --> 01:30:30,174
And best way to do that is just like

1136
01:30:30,174 --> 01:30:31,217
demonstrate first and

1137
01:30:31,217 --> 01:30:32,260
what people are doing.

1138
01:30:32,510 --> 01:30:34,178
And what can you expand on some of the

1139
01:30:34,178 --> 01:30:35,054
challenges there that you

1140
01:30:35,054 --> 01:30:36,180
see these businesses are

1141
01:30:36,389 --> 01:30:38,349
experiencing when it comes to adopting

1142
01:30:38,349 --> 01:30:39,725
these types of tools? Like

1143
01:30:39,725 --> 01:30:40,518
I mean, you did highlight

1144
01:30:42,061 --> 01:30:44,522
around trust security is another one that

1145
01:30:44,522 --> 01:30:46,149
we hear a lot about making

1146
01:30:46,149 --> 01:30:47,775
time is a big one. So what are

1147
01:30:47,775 --> 01:30:48,818
the things you're seeing in there? And

1148
01:30:48,818 --> 01:30:49,735
what are the ways that

1149
01:30:49,735 --> 01:30:51,654
you're able to get around that to

1150
01:30:51,654 --> 01:30:53,531
help these businesses move forward? Like

1151
01:30:53,531 --> 01:30:54,365
I think at the moment, it's like,

1152
01:30:54,949 --> 01:30:56,701
people are just getting so overwhelmed

1153
01:30:56,701 --> 01:30:57,451
with the amount of

1154
01:30:57,451 --> 01:31:00,037
information and the pace of change in

1155
01:31:00,037 --> 01:31:02,081
this space that it's I think it's hard

1156
01:31:02,081 --> 01:31:04,500
for business leaders to be able to go,

1157
01:31:04,500 --> 01:31:05,877
okay, this is the thing

1158
01:31:05,877 --> 01:31:07,712
to something new is like every day,

1159
01:31:07,712 --> 01:31:09,130
right? Yeah, I mean, I

1160
01:31:09,130 --> 01:31:10,715
wouldn't blame, I wouldn't blame, you

1161
01:31:10,715 --> 01:31:12,133
know, founders and business leaders out

1162
01:31:12,133 --> 01:31:12,758
there just being like,

1163
01:31:12,758 --> 01:31:13,759
okay, I'm just gonna wait till

1164
01:31:13,759 --> 01:31:15,219
the dust settles a little bit more before

1165
01:31:15,219 --> 01:31:16,220
I because you don't want

1166
01:31:16,220 --> 01:31:17,054
to pack the wrong horse

1167
01:31:17,054 --> 01:31:19,390
or invest into technologies can become

1168
01:31:19,390 --> 01:31:21,392
redundant. So I think like

1169
01:31:21,392 --> 01:31:23,394
getting past that is just like

1170
01:31:23,895 --> 01:31:25,813
showing to them, like helping them narrow

1171
01:31:25,813 --> 01:31:27,607
down to just at least one

1172
01:31:27,607 --> 01:31:28,482
thing to get started with.

1173
01:31:28,482 --> 01:31:29,859
What's the biggest pain point you have in

1174
01:31:29,859 --> 01:31:30,568
the business? What's

1175
01:31:30,568 --> 01:31:32,195
the most time consuming,

1176
01:31:32,445 --> 01:31:34,947
tedious tasks that you have that's best

1177
01:31:34,947 --> 01:31:36,282
suited to automating with

1178
01:31:36,282 --> 01:31:38,326
AI, and just jump in and just

1179
01:31:38,326 --> 01:31:39,660
start building on it and just try and

1180
01:31:39,660 --> 01:31:40,536
push through the

1181
01:31:40,536 --> 01:31:42,079
analysis paralysis? Because the

1182
01:31:42,079 --> 01:31:43,247
other thing as well is like, I think with

1183
01:31:43,247 --> 01:31:43,873
the nature of this

1184
01:31:43,873 --> 01:31:45,708
technology is, it's so far,

1185
01:31:45,708 --> 01:31:49,503
thankfully, on my website, and so yeah,

1186
01:31:49,503 --> 01:31:50,713
the technology is so far

1187
01:31:50,713 --> 01:31:51,881
reaching, it really touches

1188
01:31:52,423 --> 01:31:53,716
every single part of the business, you

1189
01:31:53,716 --> 01:31:55,760
could find a way to use technology,

1190
01:31:55,760 --> 01:31:57,428
right? So it's like,

1191
01:31:57,428 --> 01:31:59,472
okay, so how do we actually narrow down

1192
01:31:59,472 --> 01:32:00,723
and work out which bit to

1193
01:32:00,723 --> 01:32:01,891
invest into? So I think that's

1194
01:32:01,891 --> 01:32:04,435
like a big blocker for companies. And

1195
01:32:04,435 --> 01:32:05,728
then yeah, just the internal know, I

1196
01:32:05,728 --> 01:32:06,979
mean, this client I've

1197
01:32:06,979 --> 01:32:08,272
been working with, they just they were

1198
01:32:08,272 --> 01:32:09,065
really aside from the

1199
01:32:09,065 --> 01:32:10,566
engineering team, I would say that just

1200
01:32:10,566 --> 01:32:12,360
wasn't really the knowledge across the

1201
01:32:12,360 --> 01:32:13,319
company on where to even

1202
01:32:13,319 --> 01:32:14,987
get started. And also, again,

1203
01:32:14,987 --> 01:32:16,113
they just need someone to act as a

1204
01:32:16,113 --> 01:32:18,366
catalyst. And the engineering team, who

1205
01:32:18,366 --> 01:32:19,242
really like, you know,

1206
01:32:19,283 --> 01:32:20,785
this is kind of the more their bread and

1207
01:32:20,785 --> 01:32:22,536
butter, they're so busy with

1208
01:32:22,536 --> 01:32:24,497
just BAU, like they're doing

1209
01:32:24,497 --> 01:32:26,457
big re-platforming this client. And I see

1210
01:32:26,457 --> 01:32:27,124
that with a lot of clients

1211
01:32:27,124 --> 01:32:29,502
I speak with, that they just

1212
01:32:29,502 --> 01:32:31,170
don't have the bandwidth to invest into

1213
01:32:31,170 --> 01:32:32,672
it either. So you know, that's

1214
01:32:32,672 --> 01:32:33,464
a benefit of bringing someone

1215
01:32:33,464 --> 01:32:35,091
in externally just to act as a catalyst,

1216
01:32:35,341 --> 01:32:36,676
add some extra bandwidth and

1217
01:32:36,676 --> 01:32:37,718
yeah, that's where I come into

1218
01:32:37,718 --> 01:32:40,012
play. Fantastic. Even on those, some of

1219
01:32:40,012 --> 01:32:42,807
those, where people go, oh, well, and

1220
01:32:42,807 --> 01:32:43,516
I've seen this coming

1221
01:32:43,516 --> 01:32:45,768
from a data science, data analytics kind

1222
01:32:45,768 --> 01:32:47,144
of background. Our data

1223
01:32:47,144 --> 01:32:48,187
is not ready yet, it's not

1224
01:32:48,271 --> 01:32:49,480
clean, you know, we've got to like

1225
01:32:49,480 --> 01:32:50,731
reshape and do all these

1226
01:32:50,731 --> 01:32:51,732
things. We don't have the

1227
01:32:51,941 --> 01:32:53,484
processes or the workflow or the

1228
01:32:53,484 --> 01:32:55,236
structures in place. And

1229
01:32:55,236 --> 01:32:56,654
sure, that makes sense there,

1230
01:32:56,654 --> 01:32:57,863
because you can't, you know, it's garbage

1231
01:32:57,863 --> 01:32:59,198
in garbage out. And it is

1232
01:32:59,198 --> 01:33:00,616
true to an extent with AI,

1233
01:33:00,783 --> 01:33:03,661
but the missing data or we don't even

1234
01:33:03,661 --> 01:33:05,705
have things in place, guess what, you

1235
01:33:05,705 --> 01:33:07,248
should be using AI to do

1236
01:33:07,248 --> 01:33:08,916
that. Like, hey, we don't have this type

1237
01:33:08,916 --> 01:33:09,834
of documentation, we

1238
01:33:09,834 --> 01:33:10,751
don't have a data governance

1239
01:33:10,751 --> 01:33:13,087
kind of strategy. Cool, let's get the AI

1240
01:33:13,087 --> 01:33:14,755
to help you create a data governance

1241
01:33:14,755 --> 01:33:15,881
strategy so that we,

1242
01:33:15,923 --> 01:33:20,594
you know, AI itself helping you get and

1243
01:33:20,594 --> 01:33:22,054
move forward. So it's not

1244
01:33:22,054 --> 01:33:23,306
just like, okay, we can only

1245
01:33:23,306 --> 01:33:24,765
execute on AI once we've got these

1246
01:33:24,765 --> 01:33:26,892
things. There is a lot of truth to that.

1247
01:33:26,892 --> 01:33:28,185
But it should not be

1248
01:33:28,185 --> 01:33:31,188
a roadblock. If you just play around with

1249
01:33:31,188 --> 01:33:31,814
it, like you don't know

1250
01:33:31,814 --> 01:33:32,606
where to get started, like

1251
01:33:32,606 --> 01:33:34,567
literally tell the AI, I need to do this

1252
01:33:34,567 --> 01:33:35,818
task. I don't know where

1253
01:33:35,818 --> 01:33:37,486
to get started. Cool. Here's

1254
01:33:37,486 --> 01:33:39,238
the things you need to think about. It is

1255
01:33:39,238 --> 01:33:40,948
this library of, I think

1256
01:33:40,948 --> 01:33:42,366
it was Alexandria was like

1257
01:33:42,408 --> 01:33:44,702
the great library of Alexandria was like

1258
01:33:44,702 --> 01:33:46,704
this thing way back,

1259
01:33:46,912 --> 01:33:48,039
maybe it burned down. I don't

1260
01:33:48,039 --> 01:33:50,291
know. But I keep remembering that maybe

1261
01:33:50,291 --> 01:33:51,375
I'm hallucinating, but

1262
01:33:51,375 --> 01:33:52,960
the concept of a world

1263
01:33:53,294 --> 01:33:55,880
library of knowledge, wherever these

1264
01:33:55,880 --> 01:33:57,006
things are trained on images

1265
01:33:57,006 --> 01:33:59,425
are trained on, etc. That you

1266
01:33:59,425 --> 01:34:01,886
can use as a source as an oracle of

1267
01:34:01,886 --> 01:34:03,888
insights. And sure, it can

1268
01:34:03,888 --> 01:34:06,140
hallucinate, but there's ways to

1269
01:34:06,140 --> 01:34:08,351
hone in on that by giving it like the

1270
01:34:08,351 --> 01:34:09,143
correct sources or

1271
01:34:09,143 --> 01:34:10,478
getting it to use web search and

1272
01:34:10,519 --> 01:34:11,979
checking the sources where it's reading

1273
01:34:11,979 --> 01:34:13,606
from like perplexity or,

1274
01:34:13,606 --> 01:34:15,733
you know, goo checking your

1275
01:34:15,733 --> 01:34:17,318
sources now you're right. The great

1276
01:34:17,318 --> 01:34:19,403
library of Alexander was burnt down by

1277
01:34:19,403 --> 01:34:20,446
Julius Caesar himself

1278
01:34:20,488 --> 01:34:24,200
accidentally. Mark GPT. Just it's

1279
01:34:24,200 --> 01:34:25,326
interesting because like, you

1280
01:34:25,326 --> 01:34:26,452
know, as you're saying, like

1281
01:34:26,452 --> 01:34:28,329
you're helping these businesses, the

1282
01:34:28,329 --> 01:34:29,580
barriers that they're

1283
01:34:29,580 --> 01:34:31,207
different barriers now, basically,

1284
01:34:31,207 --> 01:34:32,833
some of the things that you see major

1285
01:34:32,833 --> 01:34:34,919
barriers of entry, like they shouldn't

1286
01:34:34,919 --> 01:34:35,753
really be barriers of

1287
01:34:35,795 --> 01:34:37,922
entry when we now that we have AI. Yeah,

1288
01:34:37,922 --> 01:34:39,340
I mean, the data one, I've

1289
01:34:39,340 --> 01:34:40,633
definitely heard that from

1290
01:34:40,633 --> 01:34:42,510
clients. And you know, what I would say

1291
01:34:42,510 --> 01:34:44,470
that is, you can really run these in

1292
01:34:44,470 --> 01:34:45,554
parallel, because let's

1293
01:34:45,554 --> 01:34:47,431
take personalization, for example, like

1294
01:34:47,431 --> 01:34:48,849
that will to do that at

1295
01:34:48,849 --> 01:34:50,267
scale, yeah, your data is going to

1296
01:34:50,267 --> 01:34:51,519
need to be in a really good place need to

1297
01:34:51,519 --> 01:34:52,395
have all of your customer

1298
01:34:52,395 --> 01:34:53,604
information or consolidated

1299
01:34:53,687 --> 01:34:56,315
somewhere. But you need you can run in

1300
01:34:56,315 --> 01:34:57,400
parallel, actually

1301
01:34:57,400 --> 01:35:00,194
prototyping and demonstrating at a

1302
01:35:00,194 --> 01:35:01,862
smaller manageable scale that it's going

1303
01:35:01,862 --> 01:35:02,696
to deliver the results

1304
01:35:02,696 --> 01:35:04,156
that you need and and refine

1305
01:35:04,407 --> 01:35:06,575
that and work on refining the data. And

1306
01:35:06,575 --> 01:35:07,493
then what happened, what

1307
01:35:07,493 --> 01:35:08,577
you need is that they these

1308
01:35:08,577 --> 01:35:11,580
two things come together. And then you

1309
01:35:11,580 --> 01:35:13,749
can really apply it at scale. But

1310
01:35:13,749 --> 01:35:15,084
actually, if you just sat

1311
01:35:15,084 --> 01:35:16,836
and waited to get the data right, and

1312
01:35:16,836 --> 01:35:18,337
you're not doing this bit in parallel,

1313
01:35:18,921 --> 01:35:19,880
then they become like

1314
01:35:19,880 --> 01:35:21,507
they have to be run in series and the

1315
01:35:21,507 --> 01:35:23,134
whole thing takes longer to get the end

1316
01:35:23,134 --> 01:35:24,009
result. And meanwhile,

1317
01:35:24,009 --> 01:35:25,219
your competitors are running off and

1318
01:35:25,219 --> 01:35:27,221
doing it. That's, that should be the

1319
01:35:27,221 --> 01:35:27,930
thing that's pushing

1320
01:35:27,930 --> 01:35:29,056
them. Like what are your competitors

1321
01:35:29,056 --> 01:35:30,141
doing? So there's there's

1322
01:35:30,141 --> 01:35:31,642
like, the way I see it, there's

1323
01:35:31,684 --> 01:35:34,937
like a barrier sort of limit for certain

1324
01:35:34,937 --> 01:35:35,938
industries where you

1325
01:35:35,938 --> 01:35:36,939
have things like e commerce,

1326
01:35:36,939 --> 01:35:38,399
as long as there's not a lot of rich

1327
01:35:38,399 --> 01:35:41,485
personalized data, retail and all these

1328
01:35:41,485 --> 01:35:42,486
other kind of business

1329
01:35:42,486 --> 01:35:43,904
structures that sit down here,

1330
01:35:43,904 --> 01:35:45,156
universities, the schools and stuff where

1331
01:35:45,156 --> 01:35:46,949
you can kind of make do a

1332
01:35:46,949 --> 01:35:48,492
lot of testing with the business

1333
01:35:48,492 --> 01:35:50,327
structures you have before you hit this,

1334
01:35:50,327 --> 01:35:51,537
okay, we're approaching

1335
01:35:51,620 --> 01:35:52,955
something that could have some security

1336
01:35:52,955 --> 01:35:54,248
problems. When you start

1337
01:35:54,248 --> 01:35:55,499
getting into like the banks and

1338
01:35:55,541 --> 01:35:57,960
finances, finance industries, that

1339
01:35:57,960 --> 01:36:00,504
security risk increases exponentially,

1340
01:36:01,005 --> 01:36:02,131
for particularly for

1341
01:36:02,131 --> 01:36:03,549
private data, business data, all that

1342
01:36:03,549 --> 01:36:06,760
type of stuff. But then, at

1343
01:36:06,760 --> 01:36:08,721
the same time, in support of

1344
01:36:08,721 --> 01:36:10,514
what you're saying, there should be a way

1345
01:36:10,514 --> 01:36:11,432
for you to be able to

1346
01:36:11,432 --> 01:36:12,725
start testing things in pilot.

1347
01:36:14,185 --> 01:36:16,520
By what you can do now with AI is just

1348
01:36:16,520 --> 01:36:18,981
generate fake data. You can

1349
01:36:18,981 --> 01:36:20,191
use these tools to generate

1350
01:36:20,191 --> 01:36:22,860
dummy data, synthetic data, whether it's

1351
01:36:22,860 --> 01:36:24,153
like replicating databases

1352
01:36:24,153 --> 01:36:24,945
with the same structures,

1353
01:36:25,029 --> 01:36:26,947
but just putting fake information into

1354
01:36:26,947 --> 01:36:28,616
it, siloing those out in

1355
01:36:28,616 --> 01:36:29,700
a completely separate box,

1356
01:36:29,700 --> 01:36:31,035
and then running a whole bunch of AI

1357
01:36:31,035 --> 01:36:34,205
tests to see what the risk is, or what

1358
01:36:34,205 --> 01:36:35,122
you can do with that

1359
01:36:35,122 --> 01:36:36,999
insight and that information, whether it

1360
01:36:36,999 --> 01:36:38,626
is doing something as simple

1361
01:36:38,626 --> 01:36:40,377
as plugging in an LLM over the

1362
01:36:40,377 --> 01:36:41,712
top of it and seeing what insights we can

1363
01:36:41,712 --> 01:36:43,589
pull from this cluster of

1364
01:36:43,589 --> 01:36:45,132
data, of fake data and seeing

1365
01:36:45,132 --> 01:36:47,092
what the output is, or building platforms

1366
01:36:47,092 --> 01:36:48,135
and apps around these

1367
01:36:48,135 --> 01:36:49,261
structured data. And then once you

1368
01:36:49,261 --> 01:36:51,263
know and you can trust it, then pivot

1369
01:36:51,263 --> 01:36:52,765
into the real data space, because now

1370
01:36:52,765 --> 01:36:53,516
you've got the blocks and

1371
01:36:53,557 --> 01:36:55,226
securities and places. But that

1372
01:36:55,226 --> 01:36:56,685
obviously, you've got

1373
01:36:56,685 --> 01:36:57,686
business like ComBank and stuff,

1374
01:36:57,686 --> 01:36:58,562
who do a lot of that stuff where they

1375
01:36:58,562 --> 01:36:59,647
actually have their innovation team

1376
01:36:59,647 --> 01:37:00,940
siloed. But for other

1377
01:37:00,940 --> 01:37:02,608
teams to be out of businesses, being able

1378
01:37:02,608 --> 01:37:04,276
to spin off that is quite

1379
01:37:04,276 --> 01:37:05,361
difficult, which comes in line

1380
01:37:05,361 --> 01:37:07,196
with what you were saying before, that

1381
01:37:07,196 --> 01:37:09,073
they're down in the weeds,

1382
01:37:09,073 --> 01:37:09,823
they're doing lots of stuff

1383
01:37:09,823 --> 01:37:11,283
on a day to day basis. And them having

1384
01:37:11,283 --> 01:37:12,660
the time to step aside and be like,

1385
01:37:12,660 --> 01:37:13,327
"Okay, let's test this

1386
01:37:13,327 --> 01:37:14,620
thing." They just don't have it because

1387
01:37:14,620 --> 01:37:15,371
they're trying to move so

1388
01:37:15,371 --> 01:37:16,872
quickly with everything else

1389
01:37:16,872 --> 01:37:17,915
that's growing in their organization.

1390
01:37:18,499 --> 01:37:19,416
Yeah, I think on the

1391
01:37:19,416 --> 01:37:20,751
banks and finance and

1392
01:37:20,960 --> 01:37:22,628
large enterprise side of things as well,

1393
01:37:22,628 --> 01:37:23,587
what I'd say on that is,

1394
01:37:23,587 --> 01:37:26,173
there's a really high threshold

1395
01:37:26,173 --> 01:37:28,300
for doing anything that's customer facing

1396
01:37:28,300 --> 01:37:31,178
in that case. And at this event in

1397
01:37:31,178 --> 01:37:32,471
Melbourne, the CTO of

1398
01:37:32,471 --> 01:37:33,806
Kohl's was talking about this actually,

1399
01:37:33,806 --> 01:37:34,473
because they tried to put

1400
01:37:34,473 --> 01:37:35,516
together a chatbot that could

1401
01:37:35,516 --> 01:37:37,059
help you with your recipe, putting your

1402
01:37:37,059 --> 01:37:38,060
recipe together and your

1403
01:37:38,060 --> 01:37:40,145
ingredients, which sounds

1404
01:37:40,145 --> 01:37:42,189
like a pretty innocent, easy kind of

1405
01:37:42,189 --> 01:37:44,817
thing. But there's all

1406
01:37:44,817 --> 01:37:46,318
these edge cases and people have

1407
01:37:46,360 --> 01:37:48,904
allergies and what if you give them an

1408
01:37:48,904 --> 01:37:49,989
ingredient that they have an

1409
01:37:49,989 --> 01:37:50,948
allergy to all this kind of

1410
01:37:50,948 --> 01:37:53,158
stuff. But when they did this, this would

1411
01:37:53,158 --> 01:37:53,909
have been like six or so

1412
01:37:53,909 --> 01:37:55,411
months ago, it ended up

1413
01:37:55,411 --> 01:37:58,330
generating recipes with chemicals in it.

1414
01:37:58,330 --> 01:38:00,332
So, add some detergent and

1415
01:38:00,332 --> 01:38:01,166
just to see what happens.

1416
01:38:02,001 --> 01:38:03,419
I've got potatoes, bleach

1417
01:38:03,419 --> 01:38:04,837
and cucumbers. What can I do?

1418
01:38:06,171 --> 01:38:07,423
Exactly. That's what was happening.

1419
01:38:08,257 --> 01:38:09,258
So, you can imagine if they're a company

1420
01:38:09,258 --> 01:38:10,384
like Kohl's, they're

1421
01:38:10,384 --> 01:38:12,136
just not... That project got

1422
01:38:12,344 --> 01:38:13,470
canned because they were just like, this

1423
01:38:13,470 --> 01:38:14,346
is not going to meet

1424
01:38:14,346 --> 01:38:16,890
criteria. So, this point,

1425
01:38:16,890 --> 01:38:18,475
which I thought was a good one was that

1426
01:38:18,475 --> 01:38:19,727
if you're in a big corporate,

1427
01:38:19,935 --> 01:38:21,437
just start with the internal

1428
01:38:21,437 --> 01:38:23,897
use cases, the optimization of internal

1429
01:38:23,897 --> 01:38:25,274
workflows. It's a way easier

1430
01:38:25,274 --> 01:38:26,859
conversation to have and agree,

1431
01:38:26,859 --> 01:38:27,943
get traction with that and

1432
01:38:27,943 --> 01:38:29,153
then you can move on to...

1433
01:38:29,528 --> 01:38:30,904
And it's becoming easy and easy with the

1434
01:38:30,904 --> 01:38:31,530
tools that you're talking

1435
01:38:31,530 --> 01:38:32,489
about with things like Nate

1436
01:38:32,489 --> 01:38:34,199
creating workflows and doing testing in

1437
01:38:34,199 --> 01:38:35,451
real time. It's very,

1438
01:38:35,451 --> 01:38:37,828
very large amounts of value.

1439
01:38:38,078 --> 01:38:39,246
Yeah, that's one of the tools that I need

1440
01:38:39,246 --> 01:38:40,956
to dive into more and more

1441
01:38:41,206 --> 01:38:44,043
and I've been definitely pushing the

1442
01:38:44,043 --> 01:38:44,835
boundaries with the image

1443
01:38:44,835 --> 01:38:46,003
generation kind of stuff as...

1444
01:38:46,295 --> 01:38:48,047
And sorry folks, if it is slow, it's

1445
01:38:48,047 --> 01:38:49,673
probably my fault. But,

1446
01:38:50,716 --> 01:38:52,926
BOLST for example is like something that

1447
01:38:52,926 --> 01:38:53,761
I've been really keen on.

1448
01:38:53,761 --> 01:38:54,470
They have increased their

1449
01:38:54,470 --> 01:38:56,138
prices though, which I'm not too happy

1450
01:38:56,138 --> 01:38:57,181
with. No, I saw that come

1451
01:38:57,181 --> 01:38:58,182
through in my latest invoice.

1452
01:38:58,599 --> 01:39:00,351
What? Angry Chris.

1453
01:39:00,351 --> 01:39:02,978
Anyway, but there are ways around it like

1454
01:39:02,978 --> 01:39:04,188
and I'm using client a lot

1455
01:39:04,188 --> 01:39:05,147
more, which is the open source

1456
01:39:05,189 --> 01:39:07,399
tool that we had shown a few weeks ago

1457
01:39:07,399 --> 01:39:09,401
where Manus, what Chris

1458
01:39:09,401 --> 01:39:11,362
has as one of the lucky few

1459
01:39:11,362 --> 01:39:13,697
millions of the millions to get access

1460
01:39:13,697 --> 01:39:14,948
to. I think it's up now.

1461
01:39:15,324 --> 01:39:16,325
Is it properly out?

1462
01:39:16,325 --> 01:39:18,160
Well, yeah, release their pricing now.

1463
01:39:18,160 --> 01:39:18,577
That's it.

1464
01:39:18,702 --> 01:39:19,161
And also quite

1465
01:39:19,161 --> 01:39:20,287
expensive, which is disappointing.

1466
01:39:20,621 --> 01:39:22,539
But there's open source tools that Manus

1467
01:39:22,539 --> 01:39:23,540
is built on. So you

1468
01:39:23,540 --> 01:39:24,541
can literally do that.

1469
01:39:24,541 --> 01:39:26,460
Now the great thing, and maybe this goes

1470
01:39:26,460 --> 01:39:27,378
to the product side of

1471
01:39:27,378 --> 01:39:29,004
things and I wasn't really

1472
01:39:29,046 --> 01:39:30,673
going into it with the question, but on

1473
01:39:30,673 --> 01:39:32,174
the fly, my AI

1474
01:39:32,174 --> 01:39:33,592
internally is generating this. But

1475
01:39:33,926 --> 01:39:35,052
if you think about it, some of these

1476
01:39:35,052 --> 01:39:36,470
tools like Manus showed

1477
01:39:36,470 --> 01:39:37,680
that you don't have to

1478
01:39:37,930 --> 01:39:39,640
make innovations just by building new

1479
01:39:39,640 --> 01:39:41,475
models and innovations in the training

1480
01:39:41,475 --> 01:39:42,434
and the inference of

1481
01:39:42,434 --> 01:39:44,061
these models, but you can actually have

1482
01:39:44,061 --> 01:39:45,646
new tools where you're piecing open

1483
01:39:45,646 --> 01:39:47,106
source things together

1484
01:39:47,106 --> 01:39:50,067
in a very useful way. It's basically a

1485
01:39:50,067 --> 01:39:51,485
wrapper, but they've made

1486
01:39:51,485 --> 01:39:54,655
it really useful versus like

1487
01:39:54,655 --> 01:39:56,156
people just going out and figuring out

1488
01:39:56,156 --> 01:39:57,408
themselves. How do you see

1489
01:39:57,408 --> 01:39:59,034
that kind of like mix between

1490
01:39:59,284 --> 01:40:01,537
people going for convenience versus like

1491
01:40:01,537 --> 01:40:02,329
some of the teams going

1492
01:40:02,329 --> 01:40:03,163
now, we just want to do it

1493
01:40:03,205 --> 01:40:04,164
ourselves. Do you see

1494
01:40:04,164 --> 01:40:05,457
much of that in your travels?

1495
01:40:06,542 --> 01:40:08,001
So are you saying in between like

1496
01:40:08,001 --> 01:40:09,378
engaging someone to come

1497
01:40:09,378 --> 01:40:10,754
in and help with them versus

1498
01:40:10,754 --> 01:40:12,297
just trying to, yeah, just for using

1499
01:40:12,297 --> 01:40:13,465
tools as well, or using

1500
01:40:13,465 --> 01:40:14,717
tools like whether they engage

1501
01:40:14,717 --> 01:40:16,510
someone or they use like third party

1502
01:40:16,510 --> 01:40:18,303
tools, like clients going after that

1503
01:40:18,303 --> 01:40:19,346
versus just going, you

1504
01:40:19,346 --> 01:40:20,848
know what, we know enough, we can just

1505
01:40:20,848 --> 01:40:21,932
try to build it ourselves.

1506
01:40:22,141 --> 01:40:23,100
What are you kind of seeing

1507
01:40:23,183 --> 01:40:26,687
there is a bit of mix. So I mean, what I

1508
01:40:26,687 --> 01:40:27,646
see is like there's

1509
01:40:27,646 --> 01:40:29,189
different, he's just got a full

1510
01:40:29,189 --> 01:40:31,400
spectrum of companies, types of companies

1511
01:40:31,400 --> 01:40:32,192
and their level of

1512
01:40:32,192 --> 01:40:33,402
maturity around this and their

1513
01:40:33,402 --> 01:40:35,904
internal capability. So there are

1514
01:40:35,904 --> 01:40:38,240
companies that are very tech first, like

1515
01:40:38,240 --> 01:40:39,950
that, you know, it's in

1516
01:40:39,950 --> 01:40:42,202
their DNA to build out product and

1517
01:40:42,202 --> 01:40:43,120
they've got large engineering

1518
01:40:43,120 --> 01:40:44,538
functions and they've got it

1519
01:40:44,538 --> 01:40:47,166
like they don't need external help. But

1520
01:40:47,166 --> 01:40:48,125
there's a whole bunch of

1521
01:40:48,125 --> 01:40:49,626
companies that, you know, this

1522
01:40:49,626 --> 01:40:51,754
is completely alien to them and they just

1523
01:40:51,754 --> 01:40:53,005
don't have any internal

1524
01:40:53,005 --> 01:40:54,047
capability around this. So,

1525
01:40:54,089 --> 01:40:56,633
so yeah, you just got to, you know, for

1526
01:40:56,633 --> 01:40:58,552
me, I focus more on the companies that

1527
01:40:58,552 --> 01:41:00,262
don't, aren't in that

1528
01:41:00,262 --> 01:41:02,055
end of like completely digitally enabled,

1529
01:41:02,055 --> 01:41:03,223
like how did in their DNA,

1530
01:41:03,223 --> 01:41:04,099
because like, I don't think

1531
01:41:04,099 --> 01:41:06,101
there's a big as big a problem for them.

1532
01:41:06,101 --> 01:41:07,603
And then focus on the rest

1533
01:41:07,603 --> 01:41:08,645
of the spectrum. But yeah,

1534
01:41:08,645 --> 01:41:10,522
it's a massive part of the economy. So do

1535
01:41:10,522 --> 01:41:11,273
you think there's like a

1536
01:41:11,273 --> 01:41:12,941
Goldilocks zone there where

1537
01:41:12,941 --> 01:41:15,194
it's like, the best kind of companies,

1538
01:41:15,194 --> 01:41:15,944
because from what we're

1539
01:41:15,944 --> 01:41:17,321
seeing, because we, you know,

1540
01:41:17,321 --> 01:41:18,614
engage in that space, whether it is

1541
01:41:18,614 --> 01:41:19,615
building products and

1542
01:41:19,615 --> 01:41:20,949
helping clients, or it's like,

1543
01:41:21,033 --> 01:41:22,785
just helping them use some of the tools a

1544
01:41:22,785 --> 01:41:23,744
bit less on that we

1545
01:41:23,744 --> 01:41:25,037
actually prefer building.

1546
01:41:25,746 --> 01:41:28,248
So our preference is to, you know, engage

1547
01:41:28,248 --> 01:41:29,291
with clients that actually

1548
01:41:29,291 --> 01:41:30,375
create something new. But

1549
01:41:30,626 --> 01:41:32,419
the Goldilocks have zone being that

1550
01:41:32,419 --> 01:41:35,005
they're big enough that

1551
01:41:35,005 --> 01:41:36,507
they can actually afford stuff,

1552
01:41:36,507 --> 01:41:37,883
but small enough that they can make

1553
01:41:37,883 --> 01:41:39,885
decisions like quite quickly. Are you

1554
01:41:39,885 --> 01:41:40,886
seeing that as like a

1555
01:41:40,886 --> 01:41:43,055
key area for you? Yeah, for sure. Like

1556
01:41:43,055 --> 01:41:44,890
the client that I've done a

1557
01:41:44,890 --> 01:41:46,141
lot of work for recently found

1558
01:41:46,141 --> 01:41:48,435
the lead, pretty substantial business,

1559
01:41:48,769 --> 01:41:49,394
pretty substantial

1560
01:41:49,394 --> 01:41:51,647
turnover, like, got the appetite and

1561
01:41:51,647 --> 01:41:53,148
the willingness to pay for some expertise

1562
01:41:53,148 --> 01:41:54,024
coming in and help them.

1563
01:41:54,942 --> 01:41:55,692
But yeah, I think and there's

1564
01:41:55,692 --> 01:41:57,110
also this, there's gonna be a whole bunch

1565
01:41:57,110 --> 01:41:58,111
of industries that are

1566
01:41:58,111 --> 01:42:01,114
just like, don't, not as

1567
01:42:01,198 --> 01:42:03,242
driven by technology investment. And so

1568
01:42:03,242 --> 01:42:05,118
they were not as gonna, as

1569
01:42:05,118 --> 01:42:06,370
gonna be prepared to make as

1570
01:42:06,370 --> 01:42:07,746
big an investment. But see, like the

1571
01:42:07,746 --> 01:42:08,580
e-commerce is great for

1572
01:42:08,580 --> 01:42:09,581
this, because they're completely

1573
01:42:09,581 --> 01:42:11,500
tech enabled businesses for pure play

1574
01:42:11,500 --> 01:42:13,085
online retailer. That is

1575
01:42:13,085 --> 01:42:14,336
how they differentiate from

1576
01:42:14,545 --> 01:42:16,547
bricks and mortar retailers. So yeah,

1577
01:42:16,547 --> 01:42:17,089
you're right, there's

1578
01:42:17,089 --> 01:42:18,590
definitely a bit of a Goldilocks zone

1579
01:42:18,590 --> 01:42:19,883
there that's worth it. And it's, it's

1580
01:42:19,883 --> 01:42:20,801
experiment. It's at the

1581
01:42:20,801 --> 01:42:21,927
moment, there's a narrow set of

1582
01:42:21,927 --> 01:42:23,512
companies that are making a superiority,

1583
01:42:23,512 --> 01:42:24,388
but I think that's just

1584
01:42:24,388 --> 01:42:25,430
getting completely expanded

1585
01:42:25,430 --> 01:42:27,933
at a time as well. Fantastic. I mean, you

1586
01:42:27,933 --> 01:42:28,892
kind of touched on another

1587
01:42:28,892 --> 01:42:30,352
key pointed there around like,

1588
01:42:30,811 --> 01:42:32,479
what are your competitors doing, getting

1589
01:42:32,479 --> 01:42:33,188
people to think about

1590
01:42:33,188 --> 01:42:34,314
that? I think that FOMO

1591
01:42:35,023 --> 01:42:36,358
definitely helps. Do you think that

1592
01:42:36,358 --> 01:42:37,818
that's been increasing more

1593
01:42:37,818 --> 01:42:38,944
and more in the industries that

1594
01:42:38,944 --> 01:42:41,196
you deal with? I suspect there's probably

1595
01:42:41,196 --> 01:42:42,406
a bit of FOMO fatigue

1596
01:42:42,406 --> 01:42:43,991
amongst teams and founders,

1597
01:42:44,074 --> 01:42:47,411
because they get told that a lot. So, so

1598
01:42:47,411 --> 01:42:48,787
just saying your

1599
01:42:48,787 --> 01:42:50,706
competitors are doing this isn't

1600
01:42:50,706 --> 01:42:52,291
enough, like you're really demonstrated.

1601
01:42:52,291 --> 01:42:53,542
But I think actually more of the

1602
01:42:53,542 --> 01:42:54,501
conversations I've had

1603
01:42:54,501 --> 01:42:56,461
is there's less focus on what the

1604
01:42:56,461 --> 01:42:57,421
competitors doing, but more

1605
01:42:57,421 --> 01:42:59,089
just like, can this technology

1606
01:42:59,214 --> 01:43:01,925
actually meet the quality bar of what we

1607
01:43:01,925 --> 01:43:03,468
need? Yeah, yeah, I think

1608
01:43:03,468 --> 01:43:04,261
that's probably the more

1609
01:43:04,261 --> 01:43:06,179
bigger barriers, like bit of skepticism

1610
01:43:06,179 --> 01:43:07,890
over whether it can

1611
01:43:07,890 --> 01:43:09,224
deliver on the promise. Because I

1612
01:43:09,224 --> 01:43:10,767
think a lot of companies have seen these

1613
01:43:10,767 --> 01:43:11,894
hype cycles come through

1614
01:43:11,894 --> 01:43:13,562
with previous technology and

1615
01:43:13,604 --> 01:43:16,356
being disappointed. I mean, personally, I

1616
01:43:16,356 --> 01:43:17,441
think this technology is

1617
01:43:17,441 --> 01:43:19,109
absolute game changers, as I

1618
01:43:19,109 --> 01:43:20,861
know you guys do, and there's a hell of a

1619
01:43:20,861 --> 01:43:21,862
lot of substance to the

1620
01:43:21,862 --> 01:43:24,281
hype as well. So but it's just

1621
01:43:24,323 --> 01:43:27,451
getting people over that little blocker

1622
01:43:27,451 --> 01:43:29,328
if I, there's just a lot

1623
01:43:29,328 --> 01:43:30,329
of hype here, you know.

1624
01:43:30,579 --> 01:43:32,039
So I want to talk to that a little bit,

1625
01:43:32,039 --> 01:43:33,373
like, so one of the talking

1626
01:43:33,373 --> 01:43:34,666
back to the points we're making

1627
01:43:34,666 --> 01:43:35,709
around businesses and integration

1628
01:43:35,709 --> 01:43:36,960
simplicity, you don't see

1629
01:43:36,960 --> 01:43:38,545
this a lot, but so AMX did really

1630
01:43:38,629 --> 01:43:41,924
some how AI has increased and improved

1631
01:43:41,924 --> 01:43:44,051
the efficiencies within their

1632
01:43:44,051 --> 01:43:45,886
organization. So they're

1633
01:43:46,011 --> 01:43:47,804
starting like 40% for your IT

1634
01:43:47,804 --> 01:43:50,015
escalations, 85% travel assistance

1635
01:43:50,015 --> 01:43:52,726
boosts. And this is there's

1636
01:43:52,726 --> 01:43:54,019
two things that they've kind of done.

1637
01:43:54,394 --> 01:43:56,021
First thing is integration of AI tools

1638
01:43:56,021 --> 01:43:57,022
into their coding houses.

1639
01:43:57,606 --> 01:43:58,899
So a lot of their teams are using

1640
01:43:58,899 --> 01:44:00,692
platforms, I'm not sure which ones to

1641
01:44:00,692 --> 01:44:01,485
help them with their

1642
01:44:01,485 --> 01:44:03,487
coding and solution to say to whether

1643
01:44:03,487 --> 01:44:04,655
it's like Vercel and other

1644
01:44:04,655 --> 01:44:06,698
tools like that. But more

1645
01:44:06,740 --> 01:44:08,075
importantly, from a customer facing

1646
01:44:08,075 --> 01:44:10,327
standpoint, they have integrated AI into

1647
01:44:10,327 --> 01:44:12,079
their bots. So their

1648
01:44:12,079 --> 01:44:14,623
chat tools on the lines are all now AI

1649
01:44:14,623 --> 01:44:17,542
based. And that has meant what they've

1650
01:44:17,542 --> 01:44:19,419
seen is a reduction in

1651
01:44:19,670 --> 01:44:21,672
follow up complaints or need to escalate

1652
01:44:21,672 --> 01:44:23,340
to humans. They're saying

1653
01:44:23,340 --> 01:44:24,591
that they are tools are actually

1654
01:44:24,633 --> 01:44:27,552
resolving the problems better than their

1655
01:44:27,552 --> 01:44:28,595
bots have previously,

1656
01:44:28,595 --> 01:44:29,513
which obviously their bots have

1657
01:44:29,513 --> 01:44:31,139
always been if this then that kind of

1658
01:44:31,139 --> 01:44:31,682
very simplistic

1659
01:44:31,682 --> 01:44:33,100
statements. And now they're able

1660
01:44:33,100 --> 01:44:34,309
to actually guide them through these

1661
01:44:34,309 --> 01:44:35,519
proper assistance. Yeah,

1662
01:44:35,519 --> 01:44:36,478
this is a good example. And

1663
01:44:36,478 --> 01:44:38,105
this is a great example of Yeah, I've

1664
01:44:38,105 --> 01:44:39,856
been able to integrate some stuff in in

1665
01:44:39,856 --> 01:44:40,732
like, you know, these

1666
01:44:40,732 --> 01:44:42,859
aren't game changing tools, like the chat

1667
01:44:42,859 --> 01:44:43,986
tools are very simple, and

1668
01:44:43,986 --> 01:44:44,945
that might be trained on some of

1669
01:44:44,945 --> 01:44:47,072
the local data. But someone who has some

1670
01:44:47,072 --> 01:44:48,782
basic skills could would be

1671
01:44:48,782 --> 01:44:49,408
able to integrate something

1672
01:44:49,408 --> 01:44:51,118
like that tests and then launch it out to

1673
01:44:51,118 --> 01:44:52,244
the customer base to see

1674
01:44:52,244 --> 01:44:54,079
what the impact is. And

1675
01:44:54,871 --> 01:44:56,498
in this instance, it's a massive impact.

1676
01:44:57,624 --> 01:44:58,500
This is a very brainer to

1677
01:44:58,500 --> 01:44:59,251
me. I mean, I think yeah,

1678
01:44:59,292 --> 01:45:01,086
like actually you've pulled out two ones.

1679
01:45:01,086 --> 01:45:01,837
I just think like, if

1680
01:45:01,837 --> 01:45:02,629
you're not doing these,

1681
01:45:02,963 --> 01:45:04,673
and you're a tech related business, like

1682
01:45:04,673 --> 01:45:06,550
there's just like, why?

1683
01:45:06,550 --> 01:45:07,843
Because yeah, I mean, the

1684
01:45:08,010 --> 01:45:10,095
productivity gains on the coding side,

1685
01:45:10,554 --> 01:45:11,304
I'm sure you guys talked

1686
01:45:11,304 --> 01:45:12,931
about cursor a bit. And yeah,

1687
01:45:12,931 --> 01:45:14,349
it's the incredible productivity gain

1688
01:45:14,349 --> 01:45:16,476
them that so every engineering team

1689
01:45:16,476 --> 01:45:17,102
should be using that

1690
01:45:17,144 --> 01:45:18,895
tooling. It's like almost criminal if

1691
01:45:18,895 --> 01:45:22,566
they're not in my view. Yeah. And yeah,

1692
01:45:22,566 --> 01:45:24,067
and this the chatbot,

1693
01:45:24,401 --> 01:45:26,403
I mean, I've seen in retail space, temple

1694
01:45:26,403 --> 01:45:28,572
and webster putting out figures of 60% of

1695
01:45:28,905 --> 01:45:31,241
companies getting better resolved. These

1696
01:45:31,241 --> 01:45:32,117
are easy, these are

1697
01:45:32,117 --> 01:45:34,327
relatively easy things to switch on

1698
01:45:34,327 --> 01:45:36,663
using existing vendors like Zendesk and

1699
01:45:36,663 --> 01:45:38,957
yep, and intercom. So you

1700
01:45:38,957 --> 01:45:40,292
know, like the kind I've been

1701
01:45:40,292 --> 01:45:41,752
working with their vendor that just

1702
01:45:41,752 --> 01:45:43,253
working closely with the vendor to switch

1703
01:45:43,253 --> 01:45:44,087
feature on and get it

1704
01:45:44,087 --> 01:45:45,589
set up. But it's a lot of this stuff's

1705
01:45:45,589 --> 01:45:46,673
out the box. So I reckon

1706
01:45:46,673 --> 01:45:48,759
that they should pass on temple

1707
01:45:48,759 --> 01:45:50,385
and webster just shout out to you guys.

1708
01:45:50,635 --> 01:45:51,845
You know, the savings of

1709
01:45:51,845 --> 01:45:52,888
cost to your customers,

1710
01:45:52,888 --> 01:45:54,389
that'd be great. Because there's a bits

1711
01:45:54,389 --> 01:45:55,223
of furniture that I'd

1712
01:45:55,223 --> 01:45:56,058
like to buy. So just just

1713
01:45:56,099 --> 01:45:59,478
a little bit there. I think no, I think

1714
01:45:59,478 --> 01:46:00,020
it's I think it's

1715
01:46:00,020 --> 01:46:01,897
fantastic. Like that. There are those

1716
01:46:01,897 --> 01:46:03,273
folks engaging, there will be those

1717
01:46:03,273 --> 01:46:04,399
leaders. And I think, you know,

1718
01:46:04,649 --> 01:46:06,026
conferences, whether it is online

1719
01:46:06,026 --> 01:46:07,402
or in person, like the one that you went

1720
01:46:07,402 --> 01:46:08,570
to really gets to showcase

1721
01:46:08,570 --> 01:46:10,197
what a lot of these businesses

1722
01:46:10,197 --> 01:46:14,326
are doing. We see it. You know, we deal

1723
01:46:14,326 --> 01:46:17,329
with the finance, the legal and the

1724
01:46:17,329 --> 01:46:19,039
healthcare industry,

1725
01:46:19,122 --> 01:46:21,416
and it's a bit slower in some spaces

1726
01:46:21,416 --> 01:46:22,250
there. But then there are

1727
01:46:22,250 --> 01:46:23,502
those stand out. So I saw one

1728
01:46:23,543 --> 01:46:26,088
business that they're what they're doing

1729
01:46:26,088 --> 01:46:27,756
is pretty amazing in

1730
01:46:27,756 --> 01:46:29,883
terms of how they are piecing

1731
01:46:29,883 --> 01:46:31,510
together with a whole lot because they

1732
01:46:31,510 --> 01:46:33,386
they're an asset manager. So

1733
01:46:33,386 --> 01:46:34,679
like a hedge fund, right? And

1734
01:46:34,679 --> 01:46:36,723
the way that they piece together and use

1735
01:46:36,723 --> 01:46:37,808
these different AI tools.

1736
01:46:38,100 --> 01:46:39,226
And they were very early on

1737
01:46:39,226 --> 01:46:41,520
in this space, like before the the whole

1738
01:46:41,520 --> 01:46:42,646
popularity of it, they were

1739
01:46:42,646 --> 01:46:43,855
already using a lot of the APIs.

1740
01:46:44,564 --> 01:46:47,067
But piecing how things normally are done

1741
01:46:47,067 --> 01:46:48,401
by humans, like looking at

1742
01:46:48,401 --> 01:46:49,653
news, looking at research,

1743
01:46:49,945 --> 01:46:51,738
analyzing how does it compare to the

1744
01:46:51,738 --> 01:46:53,532
views that they've got internally, and

1745
01:46:53,532 --> 01:46:54,699
having AI help them,

1746
01:46:54,991 --> 01:46:56,451
and even building their own kind of

1747
01:46:56,451 --> 01:46:57,744
internal systems where they

1748
01:46:57,744 --> 01:46:58,745
can see a bit of news that

1749
01:46:58,745 --> 01:47:00,997
they like it, they swipe left, do they

1750
01:47:00,997 --> 01:47:02,833
they like it like swipe

1751
01:47:02,833 --> 01:47:04,292
right and, you know, swipe left,

1752
01:47:04,292 --> 01:47:05,877
if they don't like it and stuff. And just

1753
01:47:05,877 --> 01:47:06,837
having the system just

1754
01:47:06,837 --> 01:47:08,004
continue to feed on itself.

1755
01:47:08,630 --> 01:47:10,340
End to end was probably one of the most

1756
01:47:10,340 --> 01:47:13,844
intricate and full blown. And best

1757
01:47:13,844 --> 01:47:14,719
examples of use cases

1758
01:47:14,803 --> 01:47:16,596
across many other industries, despite

1759
01:47:16,596 --> 01:47:19,057
that one example, not being

1760
01:47:19,057 --> 01:47:20,809
how the rest of finance is

1761
01:47:20,809 --> 01:47:22,227
really doing it to a little bit slower.

1762
01:47:22,686 --> 01:47:23,562
So it's interesting finding

1763
01:47:23,562 --> 01:47:25,105
these gems of how people are

1764
01:47:25,105 --> 01:47:26,690
doing and getting to showcase. I think we

1765
01:47:26,690 --> 01:47:27,899
need to see more of that, basically.

1766
01:47:28,567 --> 01:47:30,360
I think the legal industry is a really

1767
01:47:30,360 --> 01:47:32,028
interesting one for applying this tech,

1768
01:47:32,112 --> 01:47:34,656
because it's clear as data like it's

1769
01:47:34,656 --> 01:47:36,241
going to disrupt the legal

1770
01:47:36,241 --> 01:47:38,201
industry. But a very risk

1771
01:47:38,201 --> 01:47:41,163
adverse industry, that's I'm sure there's

1772
01:47:41,163 --> 01:47:41,788
a lot of hesitation,

1773
01:47:42,038 --> 01:47:42,539
particularly in large

1774
01:47:42,581 --> 01:47:44,332
orphan homes to adopt some of the tech. I

1775
01:47:44,332 --> 01:47:47,544
think the moment they get past the

1776
01:47:47,544 --> 01:47:48,545
hallucination factor,

1777
01:47:48,545 --> 01:47:50,088
when we can be assured that no matter

1778
01:47:50,088 --> 01:47:51,339
what the output is like

1779
01:47:51,339 --> 01:47:53,300
that, definitely that that layer

1780
01:47:53,300 --> 01:47:55,051
will be gone. I do want to the risk

1781
01:47:55,051 --> 01:47:56,803
against one line being made

1782
01:47:56,803 --> 01:47:58,889
up by an AI tool as an output

1783
01:47:58,889 --> 01:48:00,599
piece, and the headlight could completely

1784
01:48:00,599 --> 01:48:01,600
do throw in everything

1785
01:48:01,600 --> 01:48:03,727
that a any kind of lawyer or

1786
01:48:04,060 --> 01:48:06,021
person is doing. I would be pretty high

1787
01:48:06,021 --> 01:48:07,063
is pretty risky. Can I

1788
01:48:07,063 --> 01:48:08,273
just say that I would not,

1789
01:48:08,481 --> 01:48:09,941
and I'll give you a use case that I've

1790
01:48:09,941 --> 01:48:11,193
seen. There's some tools out

1791
01:48:11,193 --> 01:48:12,277
there that do, for example,

1792
01:48:12,527 --> 01:48:15,113
tenders and what they do, and this is not

1793
01:48:15,113 --> 01:48:16,323
to I'm not going to name in

1794
01:48:16,323 --> 01:48:17,365
shame or anything like that,

1795
01:48:17,365 --> 01:48:19,826
but they're using a generative and non

1796
01:48:19,826 --> 01:48:20,785
deterministic to

1797
01:48:20,785 --> 01:48:22,287
borrow data science speak,

1798
01:48:22,287 --> 01:48:24,998
but like it's a it is a probability, even

1799
01:48:24,998 --> 01:48:27,667
if it's a 99.999% probability

1800
01:48:27,667 --> 01:48:28,835
that it's going to get things

1801
01:48:28,835 --> 01:48:30,337
right, there is that point zero, zero,

1802
01:48:30,337 --> 01:48:32,339
zero, one, whatever it is that it gets

1803
01:48:32,339 --> 01:48:33,006
things wrong. And for

1804
01:48:33,048 --> 01:48:35,592
example, a tool where you feed it in the

1805
01:48:35,592 --> 01:48:36,927
tenders and it goes, Okay,

1806
01:48:37,177 --> 01:48:39,054
here are the questions, I would

1807
01:48:39,054 --> 01:48:41,640
still not rely on just an AI to tell me

1808
01:48:41,640 --> 01:48:43,016
what the questions are, I would still

1809
01:48:43,016 --> 01:48:43,808
have the human in the

1810
01:48:43,808 --> 01:48:45,560
loop there. And same thing with the

1811
01:48:45,560 --> 01:48:48,021
lawyers and stuff. I think it's not to

1812
01:48:48,021 --> 01:48:48,980
because I think complaints

1813
01:48:48,980 --> 01:48:50,941
like I will if I have to check or what's

1814
01:48:50,941 --> 01:48:52,609
the point, the point is to what you

1815
01:48:52,609 --> 01:48:53,818
alluded to earlier, if it

1816
01:48:53,818 --> 01:48:55,779
goes from 50 minutes down to like five

1817
01:48:55,779 --> 01:48:57,697
minutes, that's a better

1818
01:48:57,697 --> 01:48:59,157
thing. And you can have the

1819
01:48:59,199 --> 01:49:01,409
assurance that a human has checked it and

1820
01:49:01,409 --> 01:49:03,161
having a way that you make

1821
01:49:03,161 --> 01:49:04,663
it easier for the humans to

1822
01:49:04,663 --> 01:49:05,914
check. So let's say that there's an

1823
01:49:05,914 --> 01:49:07,707
output and it shows you the different

1824
01:49:07,707 --> 01:49:09,793
chunks from a document or

1825
01:49:09,793 --> 01:49:11,628
a PDF or whatever it is that it's read

1826
01:49:11,628 --> 01:49:14,464
from that the junior or the senior,

1827
01:49:14,464 --> 01:49:15,674
whoever it is in the law

1828
01:49:15,674 --> 01:49:17,634
firm can check to make sure that yes,

1829
01:49:17,634 --> 01:49:19,344
this is exactly right. The

1830
01:49:19,344 --> 01:49:20,553
work still needs to be done

1831
01:49:20,553 --> 01:49:22,013
by humans because we're living in a world

1832
01:49:22,013 --> 01:49:23,431
where it's probability and

1833
01:49:23,431 --> 01:49:25,642
even though if it is 99.99%

1834
01:49:26,101 --> 01:49:28,270
where it does go wrong in healthcare,

1835
01:49:28,561 --> 01:49:30,272
legal and finance, the

1836
01:49:30,272 --> 01:49:32,023
repercussions are potentially a lot

1837
01:49:32,023 --> 01:49:33,358
greater. So I think you still need to

1838
01:49:33,358 --> 01:49:35,068
think about that. There's a,

1839
01:49:35,485 --> 01:49:37,153
you know, in support of the idea

1840
01:49:37,153 --> 01:49:38,405
of everything when it comes to even

1841
01:49:38,405 --> 01:49:40,323
integrating AI with with organizations

1842
01:49:40,323 --> 01:49:41,199
that I've dealt with,

1843
01:49:41,199 --> 01:49:43,034
and even in the process I deal with, it's

1844
01:49:43,034 --> 01:49:45,120
that AI tools tend to help

1845
01:49:45,120 --> 01:49:47,330
you get to that 90%. And in a

1846
01:49:47,330 --> 01:49:49,332
traditional field, let's just let's put

1847
01:49:49,332 --> 01:49:50,709
it to time, let's say that's let's call

1848
01:49:50,709 --> 01:49:51,876
it a week, the first

1849
01:49:52,294 --> 01:49:55,380
four days of effort can now be done in IA

1850
01:49:55,380 --> 01:50:00,302
with AI with AI. And then

1851
01:50:00,302 --> 01:50:01,886
that last day, you know,

1852
01:50:01,886 --> 01:50:05,181
that 10% now you is where you can

1853
01:50:05,181 --> 01:50:06,599
maintain most of your focus. So if you

1854
01:50:06,599 --> 01:50:07,600
put it into human hours,

1855
01:50:07,600 --> 01:50:09,561
now the AI can do those four days within

1856
01:50:09,561 --> 01:50:11,855
a day, and then you're able

1857
01:50:11,855 --> 01:50:13,565
to spend four days on what

1858
01:50:13,565 --> 01:50:15,275
traditionally would have been that 10% of

1859
01:50:15,275 --> 01:50:16,359
time you have spent, which

1860
01:50:16,359 --> 01:50:17,819
is usually when most of the

1861
01:50:17,861 --> 01:50:20,155
quality for any kind of strategic output

1862
01:50:20,155 --> 01:50:21,323
ends up being so you can

1863
01:50:21,323 --> 01:50:23,450
now focus more time doing,

1864
01:50:23,908 --> 01:50:26,077
having greater impact on the solution and

1865
01:50:26,077 --> 01:50:27,162
the outcome. And that's

1866
01:50:27,162 --> 01:50:27,912
the same with the legal

1867
01:50:27,996 --> 01:50:30,874
entity example, 90% of the work is done,

1868
01:50:30,874 --> 01:50:31,750
and then that the human

1869
01:50:31,750 --> 01:50:32,751
is able to come in and add

1870
01:50:32,751 --> 01:50:34,336
that 10% make sure it's all the checks

1871
01:50:34,336 --> 01:50:36,171
and balances. And now you're able to

1872
01:50:36,171 --> 01:50:37,422
achieve more and do more

1873
01:50:37,756 --> 01:50:39,674
in a lot less time. Yeah, I mean, the

1874
01:50:39,674 --> 01:50:41,134
professional service model tends to be

1875
01:50:41,134 --> 01:50:42,260
have a bunch of juniors

1876
01:50:42,260 --> 01:50:43,762
do a lot of the grunt work and then the

1877
01:50:43,762 --> 01:50:44,554
partner comes in and

1878
01:50:44,554 --> 01:50:45,972
reviews it. Yes, that's the other

1879
01:50:46,014 --> 01:50:47,766
part, you wouldn't want to be in the job

1880
01:50:47,766 --> 01:50:48,600
market for a junior.

1881
01:50:48,850 --> 01:50:51,519
Yeah, heady insert that is the

1882
01:50:51,519 --> 01:50:53,438
years. I think they need to evolve. Yeah,

1883
01:50:53,438 --> 01:50:54,439
I like that it needs to

1884
01:50:54,439 --> 01:50:55,940
change like how how they do

1885
01:50:55,940 --> 01:50:56,983
things. There was this really interesting

1886
01:50:56,983 --> 01:50:57,984
video that kind of touches

1887
01:50:57,984 --> 01:50:58,860
on this topic. And it was

1888
01:50:58,860 --> 01:51:02,072
something from, let's call it 1977. Now

1889
01:51:02,072 --> 01:51:03,281
folks, that's nearly 50

1890
01:51:03,281 --> 01:51:05,283
years ago. And it was a different

1891
01:51:05,283 --> 01:51:07,619
world at the time and stuff baggy, weight

1892
01:51:07,619 --> 01:51:08,661
baggy jeans. Yeah, they had

1893
01:51:08,661 --> 01:51:09,662
bell bottoms and stuff like

1894
01:51:09,704 --> 01:51:12,248
that. But the concept was like around

1895
01:51:12,248 --> 01:51:14,250
bottom jeans, boots with

1896
01:51:14,250 --> 01:51:15,502
the fur. Anyway, we are old.

1897
01:51:16,628 --> 01:51:18,588
The idea was that they were talking about

1898
01:51:18,588 --> 01:51:19,881
personal computing and what

1899
01:51:19,881 --> 01:51:21,257
it was going to do. And they

1900
01:51:21,257 --> 01:51:23,802
were imagining, you know, things and some

1901
01:51:23,802 --> 01:51:25,637
of the phrases that really

1902
01:51:25,637 --> 01:51:27,013
still resonate today. So they

1903
01:51:27,013 --> 01:51:28,348
said something like, well, if the

1904
01:51:28,348 --> 01:51:30,850
computer doesn't eliminate tedium, you

1905
01:51:30,850 --> 01:51:31,976
probably didn't need one,

1906
01:51:31,976 --> 01:51:33,478
you needed more arms and legs, you need,

1907
01:51:33,478 --> 01:51:35,188
you know, people. So it's

1908
01:51:35,188 --> 01:51:36,022
gold, because it's like,

1909
01:51:36,189 --> 01:51:38,400
it's a litmus test for should we apply

1910
01:51:38,400 --> 01:51:39,859
this to every kind of

1911
01:51:39,859 --> 01:51:41,236
emerging tech, even like AI,

1912
01:51:41,694 --> 01:51:43,613
does it reduce the friction, you know,

1913
01:51:43,613 --> 01:51:44,239
that was there, we're

1914
01:51:44,239 --> 01:51:45,198
talking about friction. And there

1915
01:51:45,198 --> 01:51:46,741
was another line, which was like, we

1916
01:51:46,741 --> 01:51:47,867
should be the ones that adapt

1917
01:51:47,867 --> 01:51:49,077
and let the computer take over

1918
01:51:49,077 --> 01:51:50,787
the tedium. Okay, interesting. A third

1919
01:51:50,787 --> 01:51:51,746
one that really hit for me

1920
01:51:51,746 --> 01:51:53,581
was that a computer has never

1921
01:51:53,581 --> 01:51:55,667
obsoleted a job that didn't need to be

1922
01:51:55,667 --> 01:51:57,293
obsolete. To say a thing

1923
01:51:57,293 --> 01:51:59,045
without like, we're still talking

1924
01:51:59,045 --> 01:52:01,965
about that right now. Like if it can be

1925
01:52:01,965 --> 01:52:03,174
fully automated by the

1926
01:52:03,174 --> 01:52:04,592
computer, but you know, because

1927
01:52:04,676 --> 01:52:06,136
there is this probability thing, you

1928
01:52:06,136 --> 01:52:07,220
still need the human there,

1929
01:52:07,512 --> 01:52:09,097
maybe we have less of those jobs,

1930
01:52:09,347 --> 01:52:12,016
or maybe it's less of those jobs, because

1931
01:52:12,016 --> 01:52:14,436
we're moving people into

1932
01:52:14,436 --> 01:52:16,146
other areas. Now, unfortunately,

1933
01:52:16,146 --> 01:52:19,774
that does mean people losing their jobs

1934
01:52:19,774 --> 01:52:20,817
whilst we are in this

1935
01:52:20,817 --> 01:52:22,527
like phase of transition, but

1936
01:52:23,194 --> 01:52:25,363
we will find jobs for these people, like

1937
01:52:25,363 --> 01:52:26,197
there's going to be other

1938
01:52:26,197 --> 01:52:27,532
ways that we can do things we

1939
01:52:27,532 --> 01:52:30,618
need to like it's Yeah, yes, it's a good

1940
01:52:30,618 --> 01:52:31,619
it's a good topic, because it's

1941
01:52:31,619 --> 01:52:32,537
definitely something I

1942
01:52:32,579 --> 01:52:35,165
see a bit of concern about with clients.

1943
01:52:35,707 --> 01:52:37,375
They're very, you know,

1944
01:52:37,584 --> 01:52:38,835
tuned into the fact that some of

1945
01:52:38,835 --> 01:52:40,295
their teams might be quite nervous about

1946
01:52:40,295 --> 01:52:42,672
impact on jobs. But I really think

1947
01:52:42,672 --> 01:52:43,673
there's there's a strong

1948
01:52:43,673 --> 01:52:45,175
argument that the tooling is going to

1949
01:52:45,175 --> 01:52:47,177
help people just do higher value work

1950
01:52:47,177 --> 01:52:48,261
rather than I think in

1951
01:52:48,261 --> 01:52:50,388
a lot of areas, the headcount won't

1952
01:52:50,388 --> 01:52:52,182
change people will just step up and do

1953
01:52:52,182 --> 01:52:53,141
high value thing there

1954
01:52:53,141 --> 01:52:54,601
there will be some areas with customer

1955
01:52:54,601 --> 01:52:57,020
support for sure. I've seen a reduction

1956
01:52:57,020 --> 01:52:58,104
in the sizes support

1957
01:52:58,271 --> 01:53:00,148
team. So I'm not gonna pretend that's not

1958
01:53:00,148 --> 01:53:01,232
gonna happen in some parts.

1959
01:53:01,441 --> 01:53:03,443
But yeah, a lot of functional

1960
01:53:03,443 --> 01:53:04,861
areas of business, I think everyone just

1961
01:53:04,861 --> 01:53:06,112
steps up and career wise,

1962
01:53:06,112 --> 01:53:06,863
you know, there's the people

1963
01:53:06,863 --> 01:53:08,448
that embrace it and up skill on it,

1964
01:53:08,740 --> 01:53:10,074
they're gonna have thriving careers as a

1965
01:53:10,074 --> 01:53:10,909
result. And those that

1966
01:53:11,117 --> 01:53:12,619
resist it and put their head in the sand,

1967
01:53:12,619 --> 01:53:13,286
I think are gonna

1968
01:53:13,286 --> 01:53:14,370
really struggle career wise.

1969
01:53:15,288 --> 01:53:16,539
And it I mean, the other part of that is

1970
01:53:16,539 --> 01:53:19,292
that this conversation in relation to AI,

1971
01:53:19,918 --> 01:53:21,878
it has not just happened during this

1972
01:53:21,878 --> 01:53:23,713
transition into AI, it has been a

1973
01:53:23,713 --> 01:53:24,631
conversation that has been

1974
01:53:24,672 --> 01:53:27,509
happening for the last 10 years around,

1975
01:53:27,509 --> 01:53:28,510
hey, guys, this AI thing

1976
01:53:28,510 --> 01:53:29,802
is coming. There's always

1977
01:53:29,802 --> 01:53:31,596
been a list of the jobs that you're going

1978
01:53:31,596 --> 01:53:32,805
to see in the next 10 years

1979
01:53:32,805 --> 01:53:33,681
that are going to be at high

1980
01:53:33,681 --> 01:53:35,308
risk, you should be upskilling in all

1981
01:53:35,308 --> 01:53:37,268
these areas. And those people who took

1982
01:53:37,268 --> 01:53:38,019
advantage of that and

1983
01:53:38,019 --> 01:53:39,020
actually listened to what was happening

1984
01:53:39,020 --> 01:53:39,729
in the market will be the

1985
01:53:39,729 --> 01:53:40,563
ones that thrive. And those

1986
01:53:40,563 --> 01:53:42,524
who were like, never gonna happen are

1987
01:53:42,524 --> 01:53:43,650
gonna fail. But you have

1988
01:53:43,650 --> 01:53:44,859
you've had the opportunity.

1989
01:53:45,360 --> 01:53:47,570
If you have you heard that phrase, God is

1990
01:53:47,570 --> 01:53:50,240
coming look busy. I think

1991
01:53:50,240 --> 01:53:51,741
it, you know, the old phrase,

1992
01:53:51,741 --> 01:53:53,201
the older dodge, like God is coming look

1993
01:53:53,201 --> 01:53:54,953
busy, like, you know, the

1994
01:53:54,953 --> 01:53:56,120
rapture or whatever it is

1995
01:53:56,120 --> 01:53:57,497
going to happen, God's come back to

1996
01:53:57,497 --> 01:53:58,790
earth, depending on whatever your

1997
01:53:58,790 --> 01:53:59,582
religion is, I don't

1998
01:53:59,582 --> 01:54:01,793
care. But the idea that you need to look

1999
01:54:01,793 --> 01:54:02,544
like you're doing something

2000
01:54:02,544 --> 01:54:03,753
positive because you know,

2001
01:54:03,753 --> 01:54:06,256
the big checker of balances is coming.

2002
01:54:06,965 --> 01:54:09,592
Imagine AI is coming look busy. God's AI

2003
01:54:09,592 --> 01:54:10,385
is what you're saying.

2004
01:54:10,802 --> 01:54:13,763
Well, maybe, maybe rapture is AI. This

2005
01:54:13,763 --> 01:54:14,722
just reminds me of all the

2006
01:54:14,722 --> 01:54:16,015
federal workers in the US.

2007
01:54:16,015 --> 01:54:17,392
And it will master us in the term. Oh,

2008
01:54:17,392 --> 01:54:18,893
yeah. We send an email each

2009
01:54:18,893 --> 01:54:19,936
week on what they're doing.

2010
01:54:20,228 --> 01:54:23,523
I would go to chat GPT and describe it

2011
01:54:23,523 --> 01:54:24,649
all. But um, it does

2012
01:54:24,649 --> 01:54:26,109
what you spoke about there

2013
01:54:26,109 --> 01:54:27,860
something that tapped into my brain on

2014
01:54:27,860 --> 01:54:29,028
that was like the the

2015
01:54:29,028 --> 01:54:30,530
reskilling that's needed. Now,

2016
01:54:30,738 --> 01:54:31,906
a lot of people might think that Oh my

2017
01:54:31,906 --> 01:54:32,657
god, I have to learn this

2018
01:54:32,657 --> 01:54:33,658
new skill is going to be really

2019
01:54:33,658 --> 01:54:35,118
hard. Like I went to school for four

2020
01:54:35,118 --> 01:54:36,160
years just to learn my blah,

2021
01:54:36,160 --> 01:54:37,787
blah, blah, whatever it is that

2022
01:54:37,787 --> 01:54:39,205
their their skill and profession is and

2023
01:54:39,205 --> 01:54:40,456
over the many years of fine

2024
01:54:40,456 --> 01:54:42,375
tuning in terms of your work.

2025
01:54:43,167 --> 01:54:45,712
AI does not have to be that hard to

2026
01:54:45,712 --> 01:54:47,088
actually figure out some

2027
01:54:47,088 --> 01:54:48,923
stuff. You could there's tools

2028
01:54:48,965 --> 01:54:50,633
that are just easy to use. You've heard

2029
01:54:50,633 --> 01:54:52,802
the term vibe coding. And it

2030
01:54:52,802 --> 01:54:54,345
is like mocked a little bit

2031
01:54:54,345 --> 01:54:55,805
and stuff because it's going to produce

2032
01:54:55,805 --> 01:54:57,098
errors. Sure, it'll produce

2033
01:54:57,098 --> 01:54:58,516
these errors, but at least

2034
01:54:58,516 --> 01:55:00,143
people can prototype at least they can

2035
01:55:00,143 --> 01:55:01,477
step up and learn things that

2036
01:55:01,477 --> 01:55:03,104
never would have before. And

2037
01:55:03,104 --> 01:55:04,814
we're going to have new types of jobs

2038
01:55:04,814 --> 01:55:06,774
where people are checking the vibe code

2039
01:55:06,774 --> 01:55:07,775
that's been created the

2040
01:55:07,775 --> 01:55:09,819
validators that was never really a job

2041
01:55:09,819 --> 01:55:11,404
before because you only

2042
01:55:11,404 --> 01:55:13,865
really entrusted that work to

2043
01:55:14,073 --> 01:55:15,491
the people that could actually do the

2044
01:55:15,491 --> 01:55:16,451
code in the first place.

2045
01:55:16,451 --> 01:55:17,827
But now you've got this new

2046
01:55:17,827 --> 01:55:19,912
opportunity for a new kind of role. So

2047
01:55:19,912 --> 01:55:21,205
already we're seeing this

2048
01:55:21,205 --> 01:55:22,123
kind of stuff created. But my

2049
01:55:22,123 --> 01:55:24,208
point is is that the barrier is low to

2050
01:55:24,208 --> 01:55:27,795
learn, I think. So yeah, I agree very

2051
01:55:27,795 --> 01:55:28,588
much. So like I mean,

2052
01:55:28,921 --> 01:55:31,215
all three of us here, none of us studied

2053
01:55:31,215 --> 01:55:33,843
AI in our in university. Yeah,

2054
01:55:33,843 --> 01:55:35,178
it's not a it's not of course

2055
01:55:35,178 --> 01:55:36,095
that we did, we didn't do machine

2056
01:55:36,095 --> 01:55:37,889
learning, we didn't learn, like high

2057
01:55:37,889 --> 01:55:39,390
levels of code, I did a

2058
01:55:39,390 --> 01:55:40,642
bit of C plus back in because I started

2059
01:55:40,642 --> 01:55:42,060
in engineering. But the

2060
01:55:42,060 --> 01:55:43,645
that transition happened

2061
01:55:43,853 --> 01:55:46,564
later in our careers. And we applied our

2062
01:55:46,564 --> 01:55:47,899
experience to what we

2063
01:55:47,899 --> 01:55:49,275
were doing to this new

2064
01:55:49,275 --> 01:55:50,860
world. And that is how you adapt, you

2065
01:55:50,860 --> 01:55:51,778
need to be able to adapt

2066
01:55:51,778 --> 01:55:52,904
to the change that's coming.

2067
01:55:53,488 --> 01:55:55,406
And there's still opportunity to do it.

2068
01:55:56,115 --> 01:55:58,826
That's the thing. So do it.

2069
01:55:58,826 --> 01:56:00,244
Yeah, do it. I think, I think

2070
01:56:00,244 --> 01:56:02,455
some people just need a little bit more

2071
01:56:02,455 --> 01:56:04,123
help to unpack it on that

2072
01:56:04,123 --> 01:56:05,124
adoption journey. And that's

2073
01:56:05,124 --> 01:56:06,668
why we're here. That's why we're here.

2074
01:56:06,668 --> 01:56:09,337
Right. And YouTube, plenty of people

2075
01:56:09,337 --> 01:56:10,046
talking about the latest

2076
01:56:10,088 --> 01:56:11,756
things and how to do it. You've got

2077
01:56:11,756 --> 01:56:12,882
plenty of web sources. In

2078
01:56:12,882 --> 01:56:14,425
fact, you can even jump onto

2079
01:56:14,425 --> 01:56:18,471
GPT and just type, how do I use AI in my

2080
01:56:18,471 --> 01:56:20,139
work? Or you can click on

2081
01:56:20,139 --> 01:56:20,890
this. That's a great first

2082
01:56:20,890 --> 01:56:22,100
step. You can converse with other

2083
01:56:22,100 --> 01:56:24,227
actually love the conversation. Yeah,

2084
01:56:24,268 --> 01:56:24,894
feature with it and just

2085
01:56:24,894 --> 01:56:26,979
have a chat. Yeah, a lot of simple ways.

2086
01:56:27,271 --> 01:56:28,690
And it's free. It's also

2087
01:56:28,690 --> 01:56:30,483
free. That entry point is free

2088
01:56:30,733 --> 01:56:32,985
for that testing. So there's no excuse.

2089
01:56:33,277 --> 01:56:34,028
And you can go to product

2090
01:56:34,028 --> 01:56:35,321
edge.ai and book a call.

2091
01:56:35,988 --> 01:56:38,074
Thanks, Mark. Right, right. Yeah. You

2092
01:56:38,074 --> 01:56:39,992
know, and I didn't need

2093
01:56:39,992 --> 01:56:42,036
AI to do that. It just,

2094
01:56:42,078 --> 01:56:43,705
it just works. So yeah, booking a call

2095
01:56:43,705 --> 01:56:45,206
with Ned, if you're a business that's

2096
01:56:45,206 --> 01:56:45,790
looking at that kind

2097
01:56:45,790 --> 01:56:46,874
of stuff. But how was the people reach

2098
01:56:46,874 --> 01:56:48,167
out to you, by the way?

2099
01:56:48,167 --> 01:56:50,420
Like what's the easiest way?

2100
01:56:50,420 --> 01:56:52,213
Yeah, email on net at product edge.ai

2101
01:56:52,213 --> 01:56:54,340
over the website. I'm

2102
01:56:54,340 --> 01:56:56,175
pretty active on LinkedIn and on

2103
01:56:56,175 --> 01:56:57,760
YouTube, doing up some videos there. I'm

2104
01:56:57,760 --> 01:56:59,053
going to be showcasing, I've already

2105
01:56:59,053 --> 01:57:00,138
showcased a number of

2106
01:57:00,179 --> 01:57:03,015
the use cases I've built for in online

2107
01:57:03,015 --> 01:57:05,143
retail. I'm actually I'm

2108
01:57:05,143 --> 01:57:06,185
going to put one up soon around

2109
01:57:06,227 --> 01:57:07,854
how I've integrated AI into my sales

2110
01:57:07,854 --> 01:57:09,188
process as well using your

2111
01:57:09,188 --> 01:57:10,565
fly flies and plugging into my

2112
01:57:10,565 --> 01:57:11,941
CRM. So I'll check out for that one.

2113
01:57:12,233 --> 01:57:13,609
Yeah, but yeah, they've got

2114
01:57:13,609 --> 01:57:14,527
the main ways to get in touch.

2115
01:57:14,861 --> 01:57:16,904
And what does Ned stand for? Like many

2116
01:57:16,904 --> 01:57:17,739
people might know that

2117
01:57:17,739 --> 01:57:19,115
it's non executive director,

2118
01:57:19,115 --> 01:57:21,117
but what does it create? Oh, yeah, it's

2119
01:57:21,117 --> 01:57:22,326
quite handy that that

2120
01:57:22,326 --> 01:57:23,327
acronym has come along since

2121
01:57:23,911 --> 01:57:26,080
my name is Danil. Yeah.

2122
01:57:27,290 --> 01:57:29,709
Any final call outs? Before we close,

2123
01:57:29,709 --> 01:57:30,710
don't go get started,

2124
01:57:30,710 --> 01:57:32,253
folks. Like you just have to,

2125
01:57:32,253 --> 01:57:34,255
we say it again and again and again. If

2126
01:57:34,255 --> 01:57:36,048
you get stuck, you don't know what to do.

2127
01:57:36,424 --> 01:57:37,341
You're watching this video,

2128
01:57:37,341 --> 01:57:39,051
you just got to get started. So

2129
01:57:39,427 --> 01:57:40,970
you can reach out to any of us if you

2130
01:57:40,970 --> 01:57:41,512
want to have a chat

2131
01:57:41,512 --> 01:57:42,680
or some help about it.

2132
01:57:42,722 --> 01:57:44,348
Yeah, there's just so much incredible

2133
01:57:44,348 --> 01:57:45,641
content out there. I mean,

2134
01:57:46,017 --> 01:57:47,477
aside from this incredible,

2135
01:57:48,060 --> 01:57:49,937
you know, podcast, but you just keep

2136
01:57:49,937 --> 01:57:50,897
jumping on YouTube and just

2137
01:57:50,897 --> 01:57:51,731
like there's so many of those

2138
01:57:51,856 --> 01:57:53,733
great stuff to help ramp up on there. And

2139
01:57:53,733 --> 01:57:54,942
then most of the tooling

2140
01:57:54,942 --> 01:57:56,360
you can sign up for, for free,

2141
01:57:56,694 --> 01:57:58,821
to start playing around with it. It's not

2142
01:57:58,821 --> 01:58:00,156
hard to get started with it.

2143
01:58:00,156 --> 01:58:02,533
You heard it first. Guys, thank you so

2144
01:58:02,533 --> 01:58:04,368
much. Ned, we appreciate you coming.

2145
01:58:04,368 --> 01:58:05,453
Thanks for having me on the show. I just

2146
01:58:05,453 --> 01:58:06,329
think it's a pleasure to be here.

2147
01:58:06,662 --> 01:58:08,539
Returning guest, I think is a must be.

2148
01:58:09,165 --> 01:58:13,044
Yeah, everyone. Stay chill. Bye.

2149
01:58:13,503 --> 01:58:13,836
See you guys.