“Neural processing units” and AI-on-the-go with Intel Canada’s Cameron Allen

The biggest architectural change to the humble chipset is underway. Its aim: deliver artificial intelligence to the PC. 

Host Aaron Brooks meets with Cameron Allen, partner account manager at Intel Canada, to get the details. We'll hear about all the reasons Intel is taking this quantum leap toward portable AI, herald the arrival of neural processing units (NPUs), and discuss what all this means for technology and business leaders.

Hear Cameron explain the concepts behind NPUs, and how they direct the CPU and GPU for optimization, performance and security gains. With GPU scarcity hindering AI innovation, he articulates the need for an open, sustainable supply chain. He also dives into customer outcomes and use cases, including all the ways NPUs can support AI democratization.  Don't miss this fascinating glimpse into the next evolution of the PC.

Featuring: Cameron Allen, Partner Account Manager at Intel Canada

This episode is brought to you by Intel. Deliver all the AI results you need, everywhere you need them, with Intel and Softchoice, together. Contact a Softchoice representative today to learn about Intel’s comprehensive AI solutions, and how we can unlock them for you. Or get started here: https://www.softchoice.com/technology-partners/intel

The Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology.

Transcript

Producer: 0:00

This episode is brought to you by Intel. Deliver all the AI results you need, everywhere you need them, with Intel and Softchoice, together. Contact a Softchoice representative today to learn about Intel's comprehensive AI solutions, and how we can unlock them for you. Or visit Softchoice. com to get started.

Aaron: 0:18

Aaron Brooks You're listening to The Catalyst by Softchoice, a podcast about unleashing the potential in people and technology. I'm your host, Aaron Brooks. Imagine a world where PCs can learn, adapt, and process complex data in real time without needing constant cloud connectivity. This isn't a distant dream. AI PCs are bringing that to life with the latest advancements of an NPU, or Neural Processing Unit. But what exactly are NPUs? And why should you or your business care? How can they transform the way you do business and how people engage with AI? To help answer these questions, I'm talking to Cameron Allen, the Partner Account Manager at Intel Canada. He'll share how Intel is keeping pace with rapid AI advancements and how NPUs are making AI solutions more accessible and sustainable for everyone. So hey Cameron, welcome to The Catalyst. I'm really excited when I hear the word Intel. I kind of have a bit of a flashback to being younger and spending countless hours building my own gaming rig, trying to figure out which CPU I'm going to purchase, what RAM type the GPU for my video card. I've always loved this space of technology. And so I'm excited about all the advancements Intel has been making over the years and changing the tech game and devices and processing and how it's evolved the impact on the AI boom. God, there's just. So much to talk about, but before we get into that, I'm really curious how you found your love for technology. Sure. Absolutely.

Cameron: 1:47

Likewise, I've always been around technology. I had family members that grew up in the tech industry. We built PCs. I remember same thing on the, on the kitchen counter as a kid, plugging in all the fans and, you know, seeing the lights and everything were together. So I've always been amazed by technologies in technology. Impact on our lives and it starts out as that kind of nerdy techie. Let's just see what this can do And you know, they say to do something that you love for work and it's relayed itself into that I started my career in another industry and when I was looking to get out of that I thought you know What do I like and I like technology and so? Absolutely intel is one of those companies when you look back at the history of it Just the sheer innovation of what intel has developed, right? You know people take for granted things like what? Wi Fi, USB, these are Intel inventions that are just so synonymous with the world around us now. So yeah, I've, I've been in the tech industry for about 10 years now. For me, it really is about how technology enables things and enables people's lives. You know, we make people's lives better. And that was what really drew me to Intel was the fact that our mission statement is using technology to make everybody's life better. You know, it's not necessarily about business. It's not about profits and losses. It's how do we make people's lives better with technology?

Aaron: 2:58

I love that. I love that. You bring up a really interesting point about Intel that they're in so much that we don't see they're like that behind the scenes juggernaut that's making all these things a reality, which is so cool to remind everybody just the impact that they're having. Now, I love the fact that you brought up your company's purpose. We're on this bit of a journey ourselves. At soft choice, not just realizing our corporate purpose, but also our individual purposes. What makes us tick? How do we show up to the world, to our people, to our customers? So I'm just curious if you'd be comfortable sharing what your personal purposes with the audience.

Cameron: 3:33

Yeah. Again, I think the reason why I joined Intel was a very close alignment with those, those personal values. I think when you look at companies nowadays. You can't just have a corporate mission statement. You need to have a culture. You need to have a mission statement that resonates with your customers, you know, social responsibility. And, uh, you know, I didn't tell sustainability is a big thing for us that we're really focused on in terms of the manufacturing process that we have. It's important to us that we're net water positive, that we're going to be carbon neutral in the next 10 years. So those types of things definitely resonated. I think my personal mission is helping to find win win. Win solutions for everyone involved. I really like being able to take a technology, a solution and bring it from conception all the way through implementation and seeing that moment for the customer where they go, Hey, this is what we were looking for. This is what we got. And, you know, soft choice wins, Intel wins. And at the end of the day, the customer wins, which is, which is always the best

Aaron: 4:29

part. I love that. I'm totally going to make note of the win, win, win strategy. I always hear like the win, win strategy, third, it's the third win. I love that. All right. So I know we geeked out a little bit at the beginning around CPUs and GPUs, and that's where you're getting ready for this conversation. I came across something I probably should have known, but didn't. An NPU, a neural processing unit. It sounds so cyberpunk. I love it. What is it?

Cameron: 4:54

Yeah. So the, the NPU, the neural processing unit is really what is going to make. this AI PC happen. So without getting too technical and getting too far into the weeds, uh, the neural processing unit is the latest technology from Intel that is going to enable AI on the PC device. So when you think about a chiplet, you used to have a CPU, then we integrated the GPU, and now we've taken this really a quantum leap forward. In adding an NPU, so it's going to be integrated on the chip and it's really going to be driving everything in the background. So you're going to have things that are going to run on the CPU, things that are going to run on the GPU, and then in the background it's going to be this NPU really directing it all. And that's what's going to drive these outcomes and is really what is going to help enable AI on the PC locally for users.

Aaron: 5:43

What would be some of the quote unquote things that would run on that? Is that the whole natural language model and the processing algorithms around that? Like maybe a little example of what that would look like.

Cameron: 5:53

Sure. Yeah, it really varies. And I think the thing to keep in mind is that. AI is going to be a software play, and the software is only going to be as good as the hardware that it's enabled on. So all the different software applications that, you know, your customers and your users are making use of, those applications will be written for a specific chiplet. And again, I don't want to go too technical or too nerdy today, but an example would be, you know, Microsoft Teams is going to run on the CPU, but The NPU in the background is going to take some of that workload off to allow the CPU to run more efficiently. I gotcha. So we talked about the gains, you're going to see performance gains, battery gains, because a lot of that workload is being taken off of the CPU. And so things like your large language model are actually going to run on the CPU. I think a lot of times people associate large language models with AI, and that's true, but different things are going to run on different parts of the chiplet. And actually it's about having all three of them working well together and having that optimization to really see those gains. We're trying to help customers understand that this isn't just the next generation. This isn't just a small little gain to the chipset. This really is the biggest architectural change to the chipset in the last 40 years. And I think, you know, Over those last 40 years, we've really gotten customers used to the idea that, Hey, every couple of years, the new chips that comes out and you know, you get your marginal gains. This isn't just a small increase. This is a brand new technology and a brand new architecture. And really in the last 40 years is the biggest architectural change that we've ever made to the chip set by adding this NPU to the chiplet.

Aaron: 7:23

The real question is, would this make a difference on my old gaming rig? So, yes, I

Cameron: 7:29

mean, ideally, I think the rest of the hardware in there might be a little bit further behind. So you probably have to update some of the other components in there as well. Um, but that, that really is the way that we're pushing the AIPC and the NPU is. Again, there's a little bit of a misnomer. AI has become such a buzzword and everyone thinks it's brand new. And the reality is it's not AI has been around for a long time. It just used to take massive supercomputers and data centers to be able to process all of that. And so while you could run. These AI applications on an older PC, it's just going to get throttled because it wasn't made for that. And so this is really about getting the right hardware for the new

Aaron: 8:06

technology and for the new applications that are coming. I gotcha. So it'll help with a lot of the frustration normal users have on their phones being slow because there are a couple revisions behind and the applications coming out can't take advantage of that hardware. And so it's conceptually like that, but on a grander scale. Exactly. Like that PC just was never made for what we're asking it to do now. And speaking of PCs and the buzzword AI, I understand that Intel's got AI PCs now. Maybe help me understand a little bit about what an AI PC is and how it's different than traditional laptops. For sure. Yeah. So at its root,

Cameron: 8:40

an AI PC has that NPU in it. The broader definition though, is really bringing AI to The end user to the PC level. Like I mentioned, AI is not anything new. AI has been around. It's just taken, you know, massive amounts of hardware to really analyze and to really process these things. The AI PC is going to do those things at the client level for the individual users. The other cool thing is because it's going to be local, it's going to be your AI. So an A IPC is gonna learn the way you respond to emails. It's going to look at the way you do things, and it's gonna start building that knowledge. And you're gonna have these almost SLM small language models able to run on the pc. And so an A IPC will be really individual to the user, and you'll be able to train it on yourself. And so it'll become very much a reflection of you and become your own ai. This is like a bit of a digital personal assistant it is Yeah So I think the one that obviously people recognize or associate with most is co pilot and it really is a co pilot I think that's an important distinction. It's not an autopilot. It's a co pilot. So based on what you were doing with it It's gonna work Alongside you and that that's one application and then it'll also expand into all that other software that we talked about depending on the application It's going to go into your security applications. It's going to go into your adobe It's going to go through all the different applications that you're using and it's going to be able to do it all locally So the benefit there again of what makes an aipc an aipc Is you don't need to do those applications or you don't have to run those workloads on the edge or in the cloud. So you're going to get latency improvements. You're going to get efficiencies. It's going to save on power and it's going to be more secure because it's running on the device and not in a data center on a cloud somewhere.

Aaron: 10:21

Very interesting. One of the things that every time I hear somebody say it goes into your apps, we have customers that instantly go to, Whoa, I don't want you in my apps. And so when you think about the ethical side of A. I. And the privacy related issues that somebody doesn't want the copilot of the A. I. P. C. Poking around and like, how do you have that conversation with somebody that's got those concerns?

Cameron: 10:46

Yeah, it's a valid concern. I think it's maybe not why we're seeing a hesitation in adoption, but certainly why larger enterprise customers are taking a long look at this, right? This is something new, and we're still really waiting for that first big customer to say, yeah, we're going to adopt this fully. So it's a valid concern. I think when you look at it, though, like any application, there's going to be security in the background. And I would argue that it's actually going to be More secure because AI is going to be in all of your security applications. So we look at something like CrowdStrike is a great use case that we're coming across so far where any security threats are actually more easily detected and they're more efficient by utilizing AI threat detection efficiencies go up significantly. By using AI. So absolutely privacy is always going to be a concern, especially in healthcare, in legal settings, you know, user privacy is absolutely going to remain an issue, but that's not anything new. And it's something that we've always been able to address and work through. I think the benefit of the applications will far outweigh any of the security risks.

Aaron: 11:47

Yeah, I think, you know, when I think about security, it's always this teeter totter, and there's the feeling of security, and then there's the reality of the security, and feeling always trumps reality. It's why people are more afraid to fly than they are to drive, even though it's statistically safer. Um, and you reflect back to any new technology, people are a little bit leery because they want to see that it's safe to use. So I, I totally get what you're saying, and it makes a lot of sense. You did say something interesting around the use case of security. Now, my experience with AI over the last couple of years and talking to customers is this is such a use case driven dialogue and the importance of that. So you're pointing it at an outcome, not just using it because it's fun. Maybe you can share with us a couple of other use cases for an AI PC that you're seeing in your customer base.

Cameron: 12:31

For sure. Um, I think when we look at, at Intel as well, and in the kind of. Let's call it commercial space. It's not necessarily rocket science or anything exciting, but it's cool little things that we're starting to see. So we've kind of classified when we talk about personas and use cases, we're really looking at your knowledge workers, your everyday PC users, some of your more high end than mobile two and one on the go type of professional, and then what we're calling our extreme users, which would fall into the kind of, uh, Heavy data users, your creative types, ones that would traditionally use maybe more of a workstation. And then in terms of outcomes, we're trying to classify it down to productivity gains, time saving gains, and then what we're calling, wow, you know, the brand new stuff, and so some of the use cases we're seeing in commercial that we've started using at Intel, there's a couple applications. One is called iterate. ai. It's a software that helps basically draft emails. And again, going back to that, your type of AI, and it's going to be personalized to you. It would know how. Camera would respond to this email. Whereas if you're using it, it's here's how Aaron would respond to the email. And it does a fairly decent job of drafting long emails, complex emails in your tone of voice. The other one that I think is already fairly prevalent that a lot of people are using things like meeting recaps. So every meeting that we have at Intel. The video is uploaded, the transcription is uploaded, and it spits out here's a one page summary of what this meeting was about, here are the action items, who's responsible for them, when they said that they're going to get them done. So as opposed to me being, you know, note taker in the meeting and having to send it out and spend an hour after the meeting summarizing, AI does it for me, it sends it to all the pertinent people, and I'm able to get that hour back in my day. And I think the next step here is. AI is not going to solve all the world's problems. We still need to figure out what we're going to do with that. And so when we say, Hey, I get an hour back in my day, that's great. Is that an hour that I use to browse YouTube and talk by the water cooler or do I actually do something productive with that? And I think where we extrapolate this out is okay. An hour back in your day. That's great. Do that five days a week, do that 52 weeks a year. How much more can you get done in that time? And I'll take it one step further. That's great in a corporate setting. Hey, I answered more emails. I finished that PowerPoint faster. How about a doctor? How about a doctor who's taking patient notes and has to summarize patient visits? If that doctor gets three hours back a day that he doesn't need to spend transcribing from his dictaphone and he can see 20 more patients a day. Extrapolate that out over 52 weeks. You're talking about hundreds of patients a year That we are able to interesting help enable those outcomes and again going back to what we said at the beginning technology enabling people's lives Think about wait times in hospitals if we can shrink that because doctors are more efficient That's an outcome.

Aaron: 15:09

That's something that's really cool that I think AI in real life is going to cause. I love that. We've come across so many customers that have the need for high compute power, but also the need for that personalized AI, whether it's architecture firms, the legal industry, there's so many different types of use cases. One of the things I found interesting, you mentioned. About the personal assistant, if you will, that sits on the device you're calling an AI PC is the idea of putting it in tone and understanding reactions because some of the feedback we've had so far to date is, oh, it's fine, but it feels very plastic. The way that I get a feedback from the large language modeled isn't sounding authentic. And so if you can get past that, I think that just. Super drives up adoption. Are you finding your team using it? Like, how are you personally using it? What's your favorite use case outside of the meetings? Like what's, what's got you excited?

Cameron: 15:59

For me, Copilot and being able to access large language models, but also just vast amounts of data. So, uh, another example, you know, Intel's a huge corporation, Softchoice is a big corporation. We have all kinds of documents, SharePoint sites, HR documents, different policies using AI. to quickly find answers to fairly simple questions, you know, whether it's parsing through an HR document of, hey, how many vacation days do I get instead of the individual having to find the document, look through it, you know, control F, they hit a button on their PC, and again, this will be another thing that makes an AI PC and AI PCs, it's going to come with a copilot button going forward. So you'll hit it. The co pilot button and say, Hey, how many, uh, vacation days am I entitled to at soft choice? And it will know, Hey, Aaron's been at software for 20 years. So he's entitled to X number of weeks. It'll look in the system and say, Hey, he's taken four already. He's got X number of days left in his vacation time. And so again, it's simple uses, but these are things that will just run in the background very smoothly that you won't even have to start thinking about. It's going to become. Second nature. It's very cool and new right now. But I think about my daughter who's seven years old. This is just going to be innate for her. She's going to grow up in a world where this is just the way things have always been. And again, you think about Intel technology creations. USB is just everywhere now. At one point, USB was cool and new. Eventually AI will get to this. Oh yeah, it's just, it's

Aaron: 17:26

just AI. It's just, it's just there. I'm still waiting for the day. Like as these more of these personal assistant type of technologies come out, we start getting into naming them and having different. personality types, kind of like the series and the Alexa's and like all those different elements of it.

Cameron: 17:41

Yeah. Going back to the tone that you mentioned, we like to use the example, everyone remembers Clippy, the little paper clip in Microsoft Word. That was AI, right? It was a rudimentary version, but that was, that was the first AI assistant. And what you're going to be able to see now on the AIPC, again, without getting super technical is something called a reg model, which will basically bridge. An online large language model with your personal device. And so you'll be able to access large language models, pull answers from, from a cloud, from, from the internet, from a public domain and cross reference it with your personal AI and get tone response and things that are personalized and applicable to you.

Producer: 18:26

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Aaron: 19:34

So I know, uh, last year we actually had a couple of podcast discussions around the democratization of AI. And I think this is obviously in support of that. However, I'd be curious how Intel is ensuring that these capabilities are accessible for all users, not just those that have the high end hardware. Um, so maybe talk a little bit about that. For sure.

Cameron: 19:54

I think firstly, it's important to recognize the awareness of what AI is and where it runs. There's been a lot of talk that, oh, in order to do AI, you need to have a GPU. And that's not necessarily true. At Intel, our tagline is bringing AI everywhere and for everyone. And so it's about making sure that you have the right hardware and running the right application on the right workload on the right chiplet. So. Our focus is making sure that there's awareness around the fact that AI does not equal a GPU. Depending on the application, it's going to run either on the CPU, it's going to run on the GPU, or it's going to run on the MPU. And Intel really is one of the only company that can offer a solution on what we call the AI Continuum. And so that's in the cloud. That's in the data center. That's at the edge and now it's on the PC and on the device. So regardless of what workload you're looking to run, we have a solution for you and it's not about shoehorning or pigeonholing a customer into, Oh, you need to buy this solution again, going back to right customer outcomes. It's what do you want? What does success look like for you? Okay, cool. Here's what we can do and here's how we can enable it through software. I think that's the other part that gets lost sometimes is it's not just a hardware play. It's the two of them together. It's hardware and software. So, hey, here's the hardware that Intel has that will enable this. And here's the software optimizations that we can help you with to get to that solution. And so yet we use the term democratizing AI. I think Intel has always been a proponent of open ecosystems, again, without getting super nerdy, but, uh, you know, the X 86 architecture is an Open architecture. It is literally the defining architecture of our industry. It is open in the long run. AI is going to be no different. Rising tides are going to lift all boats. And if we're going to see these futuristic, great outcomes that AI is going to change the world, it's not going to happen in a silo and it's not going to happen in a closed ecosystem. It's going to happen in an open democratized ecosystem where everybody gets access regardless of the workload, regardless of the hardware that they're

Aaron: 21:47

running. It's totally true. And it's one of the things I find special about Intel is just how closely they do work with other technology providers. It's such a cooperative model that Intel has built. And you just mentioned everything from end user devices to cloud and Intel is everywhere. And so I love that concept of being able to put the right process into the right environment. processor in order to get the right outcome. So you did three wins. I did three rights. There you go. There you go. Right.

Cameron: 22:16

Yeah. We play well with everybody in the sandbox. Right. And that's again, what I love about Intel from both a historical standpoint, as well as where we're going in the future, it really is about bringing everybody along with us, making sure that it's win, win, win. And, you know, we see those outcomes benefiting everybody.

Aaron: 22:34

Love that. So on the conversation of cost, I know life is expensive. You mentioned you have a young one. I have two that are not so young. They're 19 and 22 and they cannot leave the house because life is too expensive. If we look at technology, it's no different. There's a real price increase in scarcity of GPUs and they're high costs and there's always mining and logistic issues. So I'm just curious how Intel is planning to address that market challenge while still supporting the high demand that's clearly coming around AI. So, I mean, the good news is with our

Cameron: 23:05

new Meteor Lake chipsets, which were the 14th gen chipsets that launched last December, we're not seeing massive price increases. It's inflationary, small price increases. So from that level, there's not too much to be concerned about right now. Absolutely. You're right around the GPU scarcity. There's going to be GPU haves and GPU have nots. Geographically, there are going to be countries that just eat up the supply of GPUs, which is another reason why we believe in an open supply chain in a sustainable supply chain and why we want to drive the message that AI is CPU, GPU and MPU altogether. The reality is that a lot of AI is inference based. So we use the analogy of take a weather forecast. If you're a meteorologist, you need one person. That is a trained meteorologist. You need one person to train that AI model. Maybe it's on a GPU. But then the rest of us, we just need to look at the weather forecast on our phones and consume that. That would be the CPU, right? Most of the users aren't training models. They're using the models. Gotcha. And so that's where we want to, again, democratize AI around. It's happens at an inference level on the CPU. Um, everybody can have access to it depending on their devices. And so you're absolutely right. GPUs are going to be scarce. They're going to be centralized in countries that have in countries that have not. And unfortunately, Canada is a have not when it comes to GPUs. And so why we're really focused on that awareness message of. AI is more than just a GPU. Now, I'm now you got me curious. Why is Canada have not, uh, comes to population comes to, you know, economically we can get into all the geopolitical reasons behind that. Sure. Um, I think where Canada is going to see the benefit and where Intel is helping to drive this is from a North American standpoint, you know, we're investing heavily in our supply chain in the United States, building foundries so that we can create these chips. locally in North America without going into all the geopolitical, you know, reasonings behind it. There's a need to have a diverse supply chain. I think when you look at 2020, if you remember trying to buy a fridge or any type of electronic device at the outset of the pandemic, you couldn't get it because the reality is now chips are everywhere. Chips aren't just a PC play. You've got chips in your dishwasher. Chips in your fridge. Think about a car. There's something like 70 chips in a car nowadays. And so this isn't just about making PCs accessible. This is about making technology accessible. And that's why we're investing in, you know, fabs and, and production facilities in Phoenix and Ohio so that we can create. A more sustained supply chain for, for users in Canada will benefit from that, but you know, the GPUs will be eaten up by the regular suspects on the geopolitical stage.

Aaron: 25:51

Understood. Well, well handled question, my friend. I like that. So as we wrap up today, I did want to get a little bit personal insight from you. I'm gonna do like a hypothetical with you. So imagine you're on stage a year from now, maybe two years from now, and you're talking to a group of peers and customers. What do you foresee the one or two things you're going to be talking about that you're super excited about a couple of years from now? Yeah, that's,

Cameron: 26:15

that's a great question. I'll reframe it a little bit first around the timeframe, because I think it's not necessarily going to be a year from now. The one example that I like to give is when we talk about how long it's going to take AI. So I'll give you a couple of dates. January 1st, 1983 was the day that the internet first went online. September 4th, 1998. was the day that Google launched, effectively bringing the internet to the masses. So if you do the quick math on that, that's a 16 year gap. And so we don't think it's going to take AI that long to get to that point, but just to reframe, Hey, AI is not going to happen. overnight. I know it feels like it. We all kind of roll our eyes at another AI presentation. The reality is, is that this isn't a flash in the pan and it's going to take years to figure out what those use cases really become. Going back to the security question, seeing where this goes, how this develops. And so, you know, I gave a talk recently where I laid that out. If you take the same timeframe, that 16 year timeframe from when we launched our AI PCs on December 14th, last year. That gets us into August, 2039. So you and I can sit down in 2039 and we'll regroup and debrief on how AI turned out. But getting back to your question, I think when I look at where I want to see this in a couple of years, I think it's really going to change critical thinking skills. And again, I take it back to my daughter and, you know, the next generation of people coming up. If we go back, you know, five, 10, 15 years, everyone said, Oh, you got to get into coding. Right? The way the curriculum changed and the way that we as a society approach things, that was a big advent. I think the next one is going to be prompt engineering. Because the way that you use AI is going to be dependent on what you feed it and how you prompt it. You know, AI is only as good as the applications you use and only as good as the user using it. And so when you take a philosophical stance back on this, people are going to have to change the way they think. And that's a big shift right at a very granular level. We need to be more focused on prompt engineering. We need to be more critical in our thinking to get those outcomes. Another thing I'll mention here is AI is not going to replace people. People who can use AI will replace people who can't use AI. And that really gets to that, that prompt engineering, right? And so again, from a philosophical stance, I think it's really cool. when you think about how is society going to improve because we have an entire generation of people who think more critically, who look at things from a different lens and approach a problem differently. These are fundamental skill sets that I think, again, are beneficial to society. And I take it right back to the reason why I love Intel is it's about improving people's lives, not about improving the technology, not about improving the business. If we improve people's lives, how do people then extrapolate that out and improve their community, their city, their country, you know, the overall society. And so I think that's where, again, we believe AI is, is for good. There's always going to be bad actors. There's always going to be the threat of, of negative things happening with it, but technology and AI at the end of the day, I believe are always going to be positive beneficial forces. And so yeah. The cool part for me is, like I said, how is society going to benefit from an entire generation of people that think differently about a problem? Right? Like if you take a, if you take a positive approach to that, that's a cool thought, right? It's easy to be pessimistic. It's easy to be, oh, everything's going to be terrible. But you know what? What if it's not? What if we all decide that, hey, this is going to be really cool and really awesome and we

Aaron: 30:02

choose to believe in that instead? That's a win for you, a win for me, and a win for everyone else. That's triple win, right? That's what we're shooting for. The triple win. I appreciate you taking the time today, Cameron, and by my math, by Season 21 of The Catalyst, we will have you back to talk about how AI has progressed.

Cameron: 30:19

Absolutely. We'll do the before and after. Thanks again for having me here, and this is great. Maybe we'll get a couple touchpoints in between now and 2039.

Aaron: 30:27

Absolutely. Look

Cameron: 30:28

forward to chatting then

Aaron: 30:28

as well. Alright, take care of yourself my friend. Likewise. NPUs are set to revolutionize personal computing, making AI more accessible and efficient. They could empower business and people to achieve unprecedented levels of innovation and productivity. But as we embrace these exciting advancements, it's critical to ensure that these capabilities are available to everyone. Not just those with the latest technology. And I love the conversation with Cameron for two reasons. One, he introduced me to a wonderful new saying, win, win, win. We win, you win, and the industry wins. And secondly, AI is not going to replace people. People with AI will replace people. Well, that's it for now. If you enjoyed this episode, please leave us a review on Apple podcasts. Join us again in two weeks for another episode of The Catalyst. The Catalyst is brought to you by Softchoice, a leading North American technology solution provider. Written and produced by Angela Cope, Felipe Dimas, and Braden Banks, in partnership with Pilgrim Content Marketing.

Producer: 31:32

This episode is brought to you by Intel. Deliver all the AI results you need, everywhere you need them, with Intel and Softchoice together. Contact a Softchoice representative today to learn about Intel's comprehensive AI solutions and how we can unlock them for you. Or visit Softchoice. com to get started.