The UnNoticed Entrepreneur - how to overcome being overlooked.

How can AI create marketing content for you now quickly and cost effectively?

November 30, 2020
The UnNoticed Entrepreneur - how to overcome being overlooked.
How can AI create marketing content for you now quickly and cost effectively?
Show Notes Transcript

The Power of AI in marketing is that it levels the playing field for small companies to compete with large ones by using technology instead of resources.  Dr. Stylianos (Stelios) Kampakis is on a mission to educate the public about the power of data science,  He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School and CEO of The Tesseract Academy. A natural polymath, with a PhD in Machine Learning and degrees in Artificial Intelligence, Statistics, Psychology, and Economics he loves using his broad skillset to solve difficult problems and so we discuss how AI can help business owners to #getnoticed.

You can track down Stelios at his Academy.
http://tesseract.academy

If you want to know how to get noticed this show is for you. I have interviews, tools, tips, everything that an entrepreneur could need in order to help their organization to get noticed for free. Thank you for joining me on the unnoticed show.

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Jim James:

Hello and welcome to this episode of speak piano. I am really delighted to have Stelios compactors with me today and Stelios is also a doctor. Stelios is on a mission to educate the public about the power of data science, artificial intelligence and blockchain. He's a member of the royal statistical society, an honorary research fellow at the UCL Centre for blockchain, and a data science advisor for the London Business School. So he's also the CEO of Tesseract. Wow, Stelios. That's a lot. I'm so delighted, you've had time to come on the call with us.

Dr. Stylianos Kampakis:

Yeah, happy to be here.

Jim James:

Now, Stelios, as you know, speed PR is all about helping business owners to get noticed. And especially using tools like like AI, tell us, what's your experience, how AI can help business owners in their marketing.

Dr. Stylianos Kampakis:

So I think AI can help in multiple ways in marketing. And we only recently started to discover some of these ways. I think that I mean, there are many different use cases, the obvious one being around analytics. And, you know, trying to to answer some traditional marketing problems, from improved ways to do a B testing, to understanding and to understand whether tribution in a better way, but then we can move on to some fancier ways or fancy, maybe not the right word, like quantum degeneration, for example, where I think it's one of the this is one of the hottest areas of publication, that where we're seeing some tools coming out over the last couple of years or so in the British, we're going to see some very interesting things happening in the next few years. But content generation, I'm referring to anything from articles, to titles, to images, even to videos, I saw a company the other day, where you write the product is basically you provide a script, and then it creates a video of that script. Very, very interesting and impressive, when no knows where it will be in the next five to 10 years. Really.

Jim James:

What do you think, though? Is the sort of the challenge for the smaller business that wants to use AI? Because it's the danger? Is it quite complicated, isn't it? I mean, people have got to understand how to deploy it. How do you how do you make?

Dr. Stylianos Kampakis:

Yeah, I mean, it really depends. I seem to see a large part of my work over the last few years has been around explaining a guide to decision makers, especially startups, but also some bigger organizations and helping them understand how they can implement AI in the best possible way, and how they can get the most value out of AI and data science, how they can design a data strategy, etc. But that being said, I think that many of the tools for Mark, there's they are more focused and easier to use. So the idea behind this tools is that you can, you can use them for very specific purposes, right. So you can use them for, let's say, again, right titles, for instance. Yeah. So in this case, there's less risk if there is a fight been implemented, because the use case is very, very clear.

Jim James:

If you have an AI writing, is it really doing plagiarism? Is it going out and finding other articles and just reassembling bits and pieces? Or is it creating fresh content that you're not at risk of, for example, being sued for copyright?

Dr. Stylianos Kampakis:

We can create fresh content as well. That's the whole idea behind generative models. So another thing, there's much risk around these, I guess it's still I wouldn't say it's early days, we've advanced a lot in the sense that we now have algorithms to try to create realistic content. Obviously, there are improvements to be made. But I don't expect copyright to be such a big issue. I expect realism and right relevant contents to be a bigger issue.

Jim James:

How do you get the AI writer to create things that have a personality because companies have got their own style? And they've got their own set of vocabulary, for example, that they use? How can you teach? Can you teach the AI tools to write like you would like to write otherwise, they're all going to kind of sound the same?

Dr. Stylianos Kampakis:

Yes, absolutely. You can. I mean, that's actually not very difficult to do because a natural language generation, we have this big models like GPT, three these days. And typically two is available, like open source. And you can simply find him this model, as we say on for some texts. And what the model is does is it learns how to speak in the language of those texts. And this means that you let's say, to give you a bit of a fast example, if you want to make the network speak like Shakespeare, then you can just find themselves sounds like Shakespear, and is that speaking in this manner? So that's an entirely solvable problem, you're not going to get an army of bolts that basically are they have

Jim James:

Can you give us an example of a of a tool like content generation platform that you could recommend that people could, if you like, trained to write, like them, if you like,

Dr. Stylianos Kampakis:

I can tell you that the state of the art and natural language generation is GPT three, which is a model developed by open AI, it's not open source. But if you type GPT, two, in Python, then you're going to find some implementations in Python. And it's fairly easy to use. This model is pre trained, so it knows English basically. And then you can find through it on texts. And I did the for a friend of mine, and I, you know, written up a book called The decision makers handbook to data science. And I had my book into the Southworth, and they started speaking in this manner, and we came up with some sentences, which were pretty realistic. So the whole piece of text that we produced, it read the bait like something with let's say, a high school student with write about computer science, only those factually correct, there are no deep insights in there. But it has really uncovered all the relationships between them, like the AI is a subfield of computer science. And databases are also something related to these topics, and so on and so forth. It was really it was pretty interesting.

Jim James:

Is AI writing really only in English? Because obviously, the Chinese are also pursuing AI, you've got the Spanish will the Indian languages, how does that work? If you're a multi multinational company?

Dr. Stylianos Kampakis:

Well, you can have a neural network that can be trained on any language, or sometimes even multiple languages simultaneously. So that's not an issue. Obviously, a training a network requesting these resources. So if you want to train a network in a language that you know, hasn't seen before, you need to spend time training it but also collecting a dataset. And this will be challenging times. With I think four languages spoken by many people. That's a, you know, it's not very difficult to create something for those languages. Not at all.

Jim James:

What about the different formats? For example, we talked about writing? Well, of course, you've got long form articles. What about things like headlines or even or advertising copy? Because there's humor, for example, a nuance in, in advertising? That isn't in a long form article? Can you can you use the same AI engine or use different ones?

Dr. Stylianos Kampakis:

I mean, there's a bit of a technical mark there, right. So again, make sure that I mean, yeah, these are really technically this, I mean, you can, you can use a similar technology. But then when it comes down to a use case, it's to be fine. Sure. So that the quality is there, I guess it's just not refined enough to be used, like, in general, right, you need to fine tune it, you need to also the models, models are quite big. So they're not necessarily be easy to serve to, you know, to users. So but these are actually technical models, which are going to be solved sooner or later. So I think it's only a few years before, con AI content generation becomes widely available. That's not to say that humans don't have a role, obviously, you know, because AI learns from humans. So I don't think that AI will be able to come up with very novel ideas, at least for now, it might in the near future. But in the very near future, I would expect that we will see some very good content generation services based on AI for content which is largely vanilla, you know, maybe you want to do if you have 10 articles talking about one topic, you just want to produce 10 more articles, you know of the same topic. And maybe you also want the human to edit this a third day I write it but Either says it becomes a very good productive.

Jim James:

And what about things like technical writing? Because if you're writing, for example, brochures, or handbooks, can AI help with that, because that's a big body of work as well, for most companies.

Dr. Stylianos Kampakis:

That's not the best approach. Because when we're talking about handbooks or guides or textbooks, we're talking about facts and very systematized knowledge that is good, that has been put into boxes. And it's when AI I mean, it captures the distant relationships between different things. And I believe that it's not, I mean, if you try to create a guide for that, it might come up with some final results. That's not what you're after. Right? Because when you read the guide, you want to be very precise. Whereas when we talk about AI, it uses content, which looks as if it isn't created by human. But I guess most people would agree that doesn't really understand what this content is.

Jim James:

What about then the intellectual property rights? If you use AI to create an article? Technically, you haven't written it yourself? Do you own the copyright? Or can you copyright content that wasn't generated by you, but just as a function of you pressing the button?

Dr. Stylianos Kampakis:

Good question. I'm not sure that's more of a legal question. But that's a great point. I say, why not? I mean, if you're generated by AI, and then you publish a book, I mean, what does it matter?

Jim James:

You mentioned that AI is great at reaching out across various bodies of information, and kind of compiling it and synthesizing it and generating some narrative. Where do you think this is going for? Sort of relating? text, and audio and video? Are these three data formats? All entirely separate, as far as AI is concerned? Or could you be gradient article that could then be creating, for example, a video from the same? content?

Dr. Stylianos Kampakis:

Yeah. This is what many researchers are trying to do they try to caption videos, and yeah, absolutely, yeah, we want to connect all these different, let's say, creative parts,

Jim James:

they absolutely. Have you got any examples of smaller companies using AI, from your own work, and maybe from your own center, that you could share with the listeners where you've gone, okay, we've taken a problem used AI, and that's either, you know, replace people that couldn't be hired for that job, or was much more cost effective than it could have been done with with people.

Dr. Stylianos Kampakis:

I think there are plenty of examples, right? Not necessarily in marketing, but like in all industries. I guess, especially now, with the donation. It's not just about the efficiency with the pandemic still going on. It's also about using technology, in, you know, in those domains, where humans might not be able to sometimes work because of a virus, right. And we've seen some even pretty imaginative cases and things like a robotic vironment. For example,

Jim James:

your sort of future view Stelios on the impact of AI on marketing.

Dr. Stylianos Kampakis:

I discussed this with speakers of the AI marketing meetup, which were organized last week, and I think everyone agreed that it was see lower barriers to entry into the game for smaller agencies and smaller companies. And AI tools for marketing become cheaper, it will be easier for a smaller company to do the job that the bigger company with 10 employees, just for the marketing department, they just don't. And Claire, Lisa thing is going to level the playing field. Obviously, bigger companies can use these tools for them, it can only serve so much content, right? So it's so the problem that smaller companies have is probably the continuation of content, because you have people trying to do too many things at once. But with these tools will will will ever will see that the playing field will be leveled. Maybe we'll see more and more and better than better tools. But it gives the first step is to quit cheaper tools, because now some of the solutions out there, they're meant for big companies. And I think eventually they will get cheaper and cheaper.

Jim James:

What do you think the tools are coming from Stelios? Because the, you know, the goal of China, for example, is to be an AI leader that has some great products like proudly coming out of Poland. This product coming out of Ukraine. Do you see as being a global innovation, or do you see certain pockets being more innovative than others?

Dr. Stylianos Kampakis:

I think that we see a lot of innovation taking place in many countries. The word leader is the US, China is a close second. And then outside of these two countries, I think the UK just from an AI, Israel as well, Canada, and we're really witnessing. Like, what we're really witnessing is a global arms race around AI and data science. And it's what we're going to see over the next few years The thing is multiple different pockets of innovation. Right? This more countries realize the hidden value in at least the college's Stellios, if people want to find out about you, and obviously you have a your own Tesseract Academy, tell us just a little bit about the academy that you run, and how you help companies to understand and adopt AI. So the goal that they serve the content needs to help decision makers and decision makers I mean, anyone from an executive to to even bigger company to a premier where a manager better understand how they can use probably implement data science will help without having to go through the all the technicalities and, and the details, which can sometimes seem obscure or esoteric. And so that got me worked on topics like data strategy, on scoping on AI projects. At three I've worked with some some small companies, two big companies like the US Navy Vodafone British land. And they that's a very, like recurring theme in my work, not only with a desert Academy, but also with some of the universities and work with explaining AI to the stakeholders, calculate them understand how AI and data science can be used, and also relate with the college's like blockchain and help them achieve their goals. Because what often people lose sight of the big picture, we make hiring decisions, which are not good, they might not have the right plan in place, no matter No, you know how you should build the right culture for data science adoption. It's really these are the things that the decision maker needs to deal with early on. So they make sure that they get the most value out of their data. And I think these days as data science and AI become more and more widespread. There's it's also a question as to whether you can do this better than the competition, because everyone will start doing and the sooner or later you have to, we have to make a step by step plan and implement AI if you haven't already in the organization. So this is where the the circular kind of doing business. I have been doing as well over the last few years helping decision makers get the most out of this technology in the simplest way possible in the most efficient way possible.

Jim James:

Still is compactness. Where can people find out about you?

Dr. Stylianos Kampakis:

Yes, so people can find about me on my personal website, the data cientist.com and they want to earn more about data strategy. hen they can visit the site, specially Academy. It's esseract.academy. There, you c n also find the website of t e desert Academy from a perso al website, the datascientis .com

Jim James:

Stelios, thank you so much for joining me today on the CPR podcast.

Dr. Stylianos Kampakis:

Yeah. Thanks, Jim. It has been my pleasure, very interesting conversation.

Jim James:

We've been talking with studios, comm pockets, and I'll put those links in the show notes. So thanks so much for listening to this episode of speak PR, we've been talking about the power of AI and technology assisted marketing. So until we meet again, I wish you the best of health Most importantly, a profitable business. And if you're a small company, look at the resources that AI have, because it really does give you a huge amount of tools, really at a fraction of the cost of traditional tool sets. Thank you so much for listening