← The Artificial Intelligence Show
The Artificial Intelligence Show
#132: OpenAI’s Operator, Stargate, The AI Literacy Project, Trump AI Executive Order, Perplexity Assistant & Zapier Agents
01:22:00
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- [00:00]
Paul Raitzer
I do think that most of these leading AI researchers think that those breakthroughs are coming. Like, we're not going to have to wait long for some of the breakthroughs they're referring to. Welcome to the Artificial Intelligence show, the podcast that helps your business grow smarter by making AI approachable and actionable. My name is Paul Raitzer. I'm the founder and CEO of Marketing AI Institute and I'm your host. Each week I'm joined by my co host and Marketing AI Institute Chief Content Officer, Mike Caput, as we break down all the AI news that matters and give you insights and perspectives that you can use to advance your company and your career. Join us as we accelerate AI literacy for all. Welcome to episode 132 of the Artificial Intelligence Show. I'm your host, Paul Racer, along with my co host, Mike Kaput. We have a unique week going on right now. We are going to do two episodes. So last week was crazier than normal. There was a whole bunch of massive things that happened to the point by Thursday I felt like we'd already lived like three months of AI news.
- [01:13]
Mike Kaput
Yeah.
- [01:13]
Paul Raitzer
And it was so funny because I've, I've mentioned on the show before, the way this works is like, throughout the week as we're listening to, you know, podcasts, watching videos, reading articles, seeing tweets, we just keep like a running sandbox of topics for Mike and I to go through and then we go through and kind of curate those on Sunday night. Well, things that on like Tuesday of last week I had noted as, like, hey Mike, let's make sure we do a main topic on this thing. Didn't even make the cut for two episodes. Like there was, there was things that I, I had planned to be one of the three most important things we talk about that isn't going to be covered on two episodes. So we are going to break all of last week's News into episode 132 and 133. So we are recording 132 the morning of January 27th pre market as the stocks are tumbling as we speak in pre market trading as a result of deepsea, the new Chinese AI model and app that we will definitely be talking about. So we are kind of watching those stocks plummeting as we get into this episode. And then we're going to take a little break. Mike and I are going to take a brief break and then we're going to come back and we're going to record episode 133. So if you're a regular listener, listener You've got, you know, double the episodes to get through today. So that's how it's going to work there. There's going to be plenty of more news to start this week out. But episodes 132 and 133 are both covering everything kind of up until January 27th. This is how to think about this. All right, so this episode is brought to us by the AI Mastery Membership Program. We've been talking a lot about this, if any of you joined us. On Friday, January 24, we had that quarterly AI trends briefing in which I introduced the AI literacy project, which we're going to talk about. As part of that initiative, we dramatically are expanding the AI Mastery Program. So this is an annual membership that includes generative AI Mastery classes, these quarterly briefings, Ask me Anything sessions where I do live, one hour sessions with members. And then we introduced on Friday that that membership, for the same annual fee, is now going to include our piloting and scaling AI course series. So that's, I think like $1,300 in value or something is now getting added onto that membership. I'll explain more about why we did that and kind of what the bigger vision is around AI education and driving literacy. But the AI Mastery Membership program is available now. You can get that with the piloting and scaling courses. So if you've been thinking about taking either of those kind of flagship courses, courses we offer, you can now do it as part of that membership. So just go to SmarterX AI AI mastery, or you can just go to SmarterX AI and click on Education and then just click on the AI mastery membership. It's right there. And you can use pod 100, that's pod 100 as a promo code to save $100 off of the membership. All right, so more to come on AI Mastery membership and the AI Literacy Project. And then a reminder before we get rolling here that our 6th Annual Marketing AI Conference or Macon is taking place October 14th to the 16th in Cleveland, Ohio. And registration is now open. So you can go to Macon AI, that's M A I C O N AI to learn more. But if you want to speak at the conference or if you know someone who should be speaking, the the opportunity is open right now to submit a speaker application location. Those are open through February 28th. So we got one month left to get your submissions in. I would tell you do it sooner than later because we are reviewing those submissions as they come in and we're building the agenda sort of in real time. We're not waiting till March to do all this. So as those spots fill, the, the opportunities to speak will kind of lessen. So if you have an idea, if you have a great story to tell, a case study, a unique perspective on, you know, applied AI, strategic AI, we would love to hear about it. And go to Macon AI and you can right on the homepage see the submit your speaker application button and just click that and send that to us. All right, Mike, we so much to talk about, so many, so many big ideas and topics. But let's get started with what I guess sort of stole the news the second half of the week. Maybe, I don't even know. Like it's so hard to compare. Like there was like Monday Tuesday news and then there was Wednesday and some point Deepseek shows up and just it became the news. But let's start off with Operator from OpenAI.
- [05:58]
Mike Kaput
All right, Paul, so OpenAI released Operator, an AI agent that can literally take control of a web browser and perform tasks for you. So this means Operator can actually do things like book your flight, order your groceries, make restaurant reservations, and even complete online purchases. So here's how this works. Operator gets its own dedicated browser window where it can click, type and scroll just like a human would. It combines GPT4O's ability to understand what it's looking at with advanced reasoning capabilities that help it navigate websites and solve problems. If it makes a mistake or gets stuck, it can try to correct itself or hand control back over to you, or ask you follow up questions for logins and things like that if it needs them. And you can take control of it at any time. So this tool is powered by what OpenAI calls their computer using agent model CUA, which is trained to interact with regular website interfaces rather than requiring special programming connections, Meaning this can work with virtually any website right out of the box. Now, initially, Operator is only available to US users who subscribe to ChatGPT's 200aMonth Pro Plan. Now, as part of this release, the company is implementing strict safety measures. Operator will ask for user approval before completing any significant actions like submitting an order or sending an email. Email. When it does have sensitive things like involving payments or login credentials, it hands control back to you to input that information or give it that information to go input. And it also tries to include defenses against malicious websites and monitors for suspicious behavior. Now, OpenAI does plan to make Operator available to more users through its plus Team and Enterprise tiers. They eventually want to integrate it directly into ChatGPT as well. So Paul, let's maybe first. Talk about the first impressions of Operator. Now that people are out in the world trying to use it for different things. What are you seeing?
- [08:17]
Paul Raitzer
Yeah. So just contextually, we'll put the links in the show notes. But you know, one thing to note is this is a. We've known this technology was coming for a long time. So back In February of 23, I think February, March 23rd, we. We talked about World of Bits, which is a research paper from OpenAI back in 2017 led by Andrej Karpathy, where they tried to give computer use to these agents. They tried to enable the AI to use a keyboard and mouse, but it was too early. And eventually the transformers and GPTs or, you know, large language models led to the ability for OpenAI, anthropic, Google and others to revisit this idea of computers. We got it in fall of last year, fall of 24, anthropic was the first to market with like a research preview of this. We talked about Google integrating it into Chrome on a recent episode and now we have OpenAI's OpenAI seems like it's probably the most advanced of the previews of this technology that we've gotten. I would say my general perception at the moment is this is definitely more of like an experimentation thing. It is. I've definitely seen some people online really impressed with it and that have got it to do actual things. But more than anything, I think it's really a preview of what may be coming. And I don't know that the average person would find this incredibly useful. Like you might, you know, play around with it. It's fun. It's kind of cool that it does these things, but I don't know that most people would get this technology and think this just changed my life. So a few reactions. Vedant Misra, who we've talked about recently on the podcast works at Google DeepMind, was at OpenAI previously. He said, I just use Operator for the first time. It nailed my test requests. If even I can barely process the fact that this is already a real product, surely the general population has no idea what is about to happen. So again, sort of like a hint at this is really impressive that they're able to do this. Most people won't comprehend how impressive this actually is. And more is coming. Ali Miller, who we've talked about on the show many times, she said it's. And these are. These are tweets that I'm quoting here. It's not AGI, but it's a step toward more autonomous systems The Operator UI is sleeker than anthropic Claude computer use. I like that it punts it back to the user for logins and payments as you had said Mike, but navigation and typing is slow. I had several times where the website detected it was an AI and blocked it. OpenAI may be using operator to inform their AI strategy. Maybe the first AI agent that's really accessible to non developers. Ethan Malik said implications of Operator Number one general purpose web agents aren't there yet but seem more workable than expected. Operator is quite good. Number two, companies aren't thinking enough about how to market to preference of agents. I actually saw a couple examples Mike where like people's websites didn't work in the Operator I saw too. Yeah, so it's like that thing about as a marketer, as like a, you know, a business leader starting to think about what happens if this stuff starts working in six months and people actually start using this technology. And then Molik said security is going to get very weird very fast. And then the last one. So right as it came out I think I tweeted like anxious to see what Karpathi has to say. So again, Andre Karpathi led the team trying to do this eight years ago at OpenAI. Went back to OpenAI in 2023 to work on this again. So it's like there's no one more qualified to assess Operator than Karpathi. And he did end up tweeting later that day after it came out and he said people on my timeline are saying 2025 is the year of agents. Personally I think 2025 to 2035 is the decade of agents. I feel a huge amount of work across the board to make it actually work is still needed but it should work. He says in quotes today Operator can find you lunch on doordash or check a hotel, etc. Sometimes and maybe doesn't really always work. Tomorrow you'll spin up organizations of operators for long running tasks of your choice. For example running a whole company, which if you Remember is level five of OpenAI's levels of AI is basically organizations. You could be a kind of CEO monitoring 10 of them at once, maybe dropping into the trenches sometimes to unblock something and things will get pretty interesting. So that that was my overall take. I have not personally used it yet. I do start to think about these ramifications around search. So as these agents start working more and more, start doing more of the web work for us. What does that mean to search business SEO? What does it mean to corporate websites Are we building websites specifically for agent experiences? Like do you start building these versions that it's really just for the agent to use? Implications on marketing, sales, customer service, These things aren't being talked about yet enough because most people can't even wrap their minds around what this could mean in 12 to 18 months as they start becoming more reliable. I know you have a pro license. Like have you played around with operator at all? Have you had any experiences with it?
- [13:39]
Mike Kaput
Yeah, I mean, I played with it a very small amount to start and I'll actually get into in a second why that's the case. I only did kind of these cursory, you know, looking for flights or like making restaurant reservations. I kind of felt along the lines of Ethan Malik, that I realized it was very limited and slow and not totally autonomous because I had to keep, you know, jumping in. But it worked surprisingly well. Like it worked better than ChatGPT tasks did out of the box, which I still haven't explored that much because it keeps breaking. Maybe I'm using it wrong, but it worked fine for things like booking a table on OpenTable. But I didn't push the limits by any means. And a reason for that I, within seconds ran into the problem that I don't know how we solve, which is I can think of a hundred extremely high value experiments to run and 99 of them require information or access to accounts that I'm either not, I definitely should not be doing as part of our work or personally don't feel comfortable with.
- [14:46]
Paul Raitzer
Yeah, actually now you're saying that that act, that, that introduces a whole new element of generative AI policies and companies. Like if, if you haven't addressed computer use in your generative AI policies, back to the drawing board, you're going to have to, you know, integrate that. This is only available in those pro licenses. Like you can't get this in team and enterprise accounts yet in Chat GPT. But again, we know that employees are using personal accounts to do business work. So yeah, you may need to, you know, address that because the risks are huge here. Like, yeah, yeah, OpenAI isn't even aware of all the ways this could go wrong and people get access to data and things like that. So I, I don't know, like, I, I don't know how you feel about this, Mike. I see this probably being a novelty for consumers, like really advanced people. If you follow a bunch of people on Twitter, you may see like the 1% or the 1/10 of 1% who make it seem like this is changing the world. And everything's going to change in the next six to 12 months. The game has changed. Like those tweets you see from people. Like, it hasn't like this. This is not transforming your business life or your personal life yet. I think enterprise adoption is going to be insanely slow because the risks the it would have to solve for are so massive and so many are completely unknown that there's no way they're going to allow this kind of thing to be used within enterprises. So I don't know, I think it's like really interesting technology. I think if you step back and you know what you're looking at, you can start to see 6, 12, 18 months out how this really does start to affect things. But so much of it is going to be underlying and it's going to be like websites and the marketing and sales processes and then it's going to start to get domain specific. Like, what does this mean for lawyers? What does it mean for accountants when it can reliably fill out forms and do tax forms, like things like that, where you start to look at industry by industry and say, okay, this might actually affect this industry way sooner than maybe this industry.
- [16:47]
Mike Kaput
Yeah, I couldn't agree more. Based on kind of limited tests with it. I do think this is a really good example of what you mentioned in your talk thought, which is, look, we can't predict exactly what's going to happen when, but we know the broad strokes of what's coming. Like, agents are going to be a thing. And if I'm a marketer especially, I had like 12 questions immediately about like, well, what if someone used an agent to fill out a form a thousand times on our website? Like, that would be a huge pain. That would like, derail us for like a peak to figure it out. Stuff like that could be worth starting the game out even if we're not there yet.
- [17:24]
Paul Raitzer
And that's one of the exciting things for me with like our Marketing Institute community and now kind of the emerging Smarter X community, is we're seeing these domain experts who are starting to pull on the threads specific to their industry. So doing what like Mike and I do, where we're trying to like drink from the fire hose and then make that fire hose make sense every Tuesday for people, that that's like one area here. If you're a lawyer or if you're an accountant or an HR professional or a CEO or a consultant or an SEO expert, like, there is, there are careers to be made figuring all this out. When you zoom into a specific department or industry or career path. Mike and I aren't gonna be the ones to figure that out. Like, we can guide you on, like, the foundational knowledge, but this is the opportunity I see for so many people, and we see it happening in our community where you get these people or experts on the legal side or the finance side, and they're now going and saying, okay, I'm gonna be the one to figure this out in my company or in my industry. And there's tremendous opportunities to do that, to become like a thought leader in your own company, in your industry that understands the implications of AI for specific professions and companies.
- [18:39]
Mike Kaput
In our next big topic that hit us this week, there has been a dramatic announcement at the White house that involves OpenAI, SoftBank, and Oracle kind of unveiling plans for a huge AI infrastructure project that is called Stargate. This venture aims to invest up to $500 billion over four years to build massive AI data centers across the U.S. starting with an initial $100 billion deployment, OpenAI and SoftBank say they'll each commit 19 billion. As the project's lead partners, SoftBank will be handling financial responsibilities. OpenAI managing operations. This venture apparently is going to be exclusively dedicated to serving OpenAI's computing needs, so this will also have a significant impact on the company's relationship with its primary backer, Microsoft. The project's first facility is apparently under construction in Texas, where Oracle and data center developer Crusoe are building a massive complex that will require enough power to run a city the size of Boston. This facility will house a hundred thousand of Nvidia's newest AI chips and represents just the beginning of Stargate's planned expansion across the country. Now, the timing and structure of this deal also have a lot of complexity to to them. So OpenAI CEO Sam Altman, he'd kind of grown frustrated. There had been some leaks and rumors about stories where he was frustrated with the pace of infrastructure development through Microsoft, and he is simultaneously facing a legal feud with Elon Musk. So it seems like Stargate could serve multiple purposes for the company. They'll get some more independent computing resources, strengthen ties with the Trump administration, maybe head off some of Musk's mounting legal pressure. But there's a lot of unknowns here still. Like the 38 billion from OpenAI and SoftBank looks to have been confirmed. But the path to getting that full 500 billion seems to remain unclear. And some experts are skeptical about if they're going to be able to secure enough power and resources for facilities at this scale. And however, despite all this, if this even gets to this 500 billion level, Stargate would actually represent the largest private investment in AI infrastructure to date. And according to the information, would surpass even the inflation adjusted cost of NASA's Apollo program. So Paul, first up, before I ask you this first question, I'm just glad we have a cool name for something in AI finally, instead of all how badly all these models are named.
- [21:25]
Paul Raitzer
So follow up, I. Nvidia recently introduced something called Jetson Thor. And I was like, that's great, man. Let's just like mash up sci fi cartoons with movies. Like I, I do appreciate this. Like, let's just go more sci fi and have some fun with it. Yeah, I love the name.
- [21:44]
Mike Kaput
So you know what's interesting though is like, I want to get kind of just your overall thoughts on this. You know, the Apollo mission comparison was kind of interesting because you actually said on episode 120 you mentioned we needed an Apollo level mission for AI literacy and upskilling. And while this is not directly related to that, this seems like one that they're attempting for infrastructure.
- [22:05]
Paul Raitzer
Yeah, definitely. So at a high level, this is exactly what I assumed was coming, thought needed to come. I think this is just the tip of the iceberg we'll get into whether or not this 500 billion is real money or not. I think more is coming. I think trillions, I really do, like in the next four years think that we'll have trillions committed to infrastructure, build out of data centers, energy infrastructure. How it happens is going to, you know, it's up for debate and who the main players are, but this is the direction that we always knew this was going. It is a complex deal. So this was announced 24 hours after Trump took office. I think it was Tuesday night, right. Like, I think the inauguration was maybe Monday night and this was Tuesday night. He's holding what seemed like a kind of an impromptu press conference with Altman, Larry Ellison and Masa Son. Who's the guy?
- [22:59]
Mike Kaput
Masahiyoshi Son.
- [23:00]
Paul Raitzer
Yeah, yeah. So it's, it is, it is being formed as a new company. So that came out in an open AI release and I think an information article that it was actually a new venture that OpenAI is like the operating controller of. And I think OpenAI is like 40% equity or something. It's really convoluted, like how exactly the structure is going to work and what it's set up as and where it's incorporated at. And like there's all these questions. It's very apparent OpenAI doesn't actually have this kind of money. Like, they're, they're going to have to raise this on their balance sheet. They don't have $19 billion sitting there that they can just fund. There was a great podcast like BG2. I've mentioned this many times. Gerstner and Gurley do this incredible podcast that's more on like the financial VC side. But they have awesome guests and they had the CEO of ARM who's actually heavily involved in this deal, he came from Nvidia and they were analyzing, like, how could they possibly even spend this kind of money? Like, even if they could get this many chips from Nvidia, which is doubtful, they don't have the energy to run a 2 1/2 gigawatt data center. So, like, nothing seems to actually add up for this. Yeah, we're going to spend 500 billion over the next year. And so Gerstner's analyst firm basically went through like, they couldn't possibly even spend a hundred billion this year. Like, there isn't, there isn't enough energy to, to provide and there aren't enough chips to buy to actually spend this. And then they get into like, is this mostly going to be debt? And they're actually going to borrow most of that 500 billion and they're going to use the data centers as collateral. Like, it's really complicated. So keep that in mind. Again, headlines don't always equal reality. In this case, that is definitely the case. That is the 500 billion is not real yet. And there's all these other open questions. It does hint at the complexities of the Microsoft relationship. So the whole reason this seems to have come together is because Microsoft refused to build the data centers that Sam wanted to build this power. And so Microsoft let Sam out of their exclusive deal so he could go do a deal with Oracle to bring this to life. And it was for a facility that was already being built. So, like, it's not even opening eyes facility. The whole thing is really weird. And then you had Satya is at Nadella from Microsoft is at Davos last week where there was just all kinds of insane interviews and news we'll get into over the next two episodes. But one of them, I think was on Wednesday, so the day after this. And. And Sorkin says to Satya, like, well, what do you think about this? Is this real? And Satya has this like, total, you know, amazing line. He's like, all I know is I'm good for my 80 billion. Like, I'm putting 80 billion into capex and like, I don't know, spending it all, but like, I've got the money. And then it's funny because then this leads to this Twitter feud. So of course Elon Musk shows up and starts like questioning the, the validity of this deal. And so he tweets, let's see. He. So he said, okay. So I tweeted it was only a matter of time till Mus showed up. They don't actually have the money was his tweet, to which Altman replied, I genuinely respect your accomplishments and I think you're the most inspiring entrepreneur of our time. A little time goes by and then Musk replies to OpenAI's tweet Again, SoftBank has well under 10 billion secured. I have that on good authority. To which Altman replied, wrong, as you surely know. Want to come visit the first site already underway, which again was already underway before this deal. And so it leads to this whole thing. But then the really interesting one is Musk on January 23rd, so this is now Thursday, retweets Satya saying, I've got, I'm good for my 80 billion. So Elon says, on the other hand, Satya definitely does have the money. Satya replies with the crying emoji laughing. And all this money is not about hyping AI but is about building useful things for the real world. It's like that sure seems like a shot at Sam right now. All of a sudden, Satya is getting injected into this Elon Altman feud. The whole thing is just like weird and funny and really important. Like it's, it's all of these things at one time and it's really fascinating to watch. But like this was the Tuesday to Thursday news. This was like deep seek taking over the world news. But at the end of the day, I think all of that, considering all of those elements, it demonstrates how infrastructure and energy is going to drive everything in America. For this coming certainly half decade, if not more, how it plays out, who the players are, how much money actually gets spent. Do we have the energy? Where's the energy come from? Fossil fuels versus new energy. Trump was on record on like Wednesday saying he hates solar energy, it's ugly and he obviously isn't a fan of wind. And yet Elon and Sundar, like, that's. They're huge. It is truly a soap opera. Like it's, it's amazing to watch this all unfold.
- [28:04]
Mike Kaput
Well, what is shocking is like again with the caveat, who knows what will actually come to fruition here? But it really just feels like in the last month it's just green lights everywhere. All systems go. Accelerate as fast as you want, basically. Or can.
- [28:21]
Paul Raitzer
Yeah. And we'll talk a little bit more about the Trump executive order and the rescinding of the previous executive order. But as we said on the podcast many times last year and definitely last week, it is all about deregulation and acceleration of technology. Like that is fundamentally what is going to happen, how it plays out, who the winners are. It was easier to predict the winners last Wednesday than it probably is today as the stock market crashes, or at least the technology stock crashes as a result of deep seek. But it, yeah, infrastructure and energy we are fairly confident are going to keep being built.
- [29:00]
Mike Kaput
All right, our third big topic for this episode involves some news from you, Paul and our team. So, Paul, on Friday, January 24, SmartRx, your research and education firm, launched a major new initiative that aims to tackle one of the most pressing challenges we're seeing, which is the growing gap between AI's rapid advancement and people's understanding of it. So this initiative that you announced, and you'll talk about a bit more in a second here, is called the AI Literacy Project. And this is an effort to democratize AI education and prepare professionals across all industries, not just marketing and sales, for the future of work by making AI education accessible and personalized. So through it, SmartRx is setting out to drive AI understanding and across industries and personal professions through affordable courses and education. You're out to provide a path to AI mastery through content, events and experiences, and also personalize learning journeys to maximize the positive impact of AI on people's careers and lives. So we've talked many times that stuff like this cannot come at a more critical time. We've cited some recent research from Accenture which says that while 94% of workers say they want to learn new skills to work with generative AI, only 5% of organizations currently provide AI training at scale. Similarly, in our 2024 State of Marketing AI report, we found that 67% of professionals cite a lack of education and training as a top barrier to AI adoption, and 75% say their company does not provide AI education and training. So, Paul, maybe walk me through the phases of the AI Literacy Project, like this whole big initiative over the next several years designed to address this problem.
- [30:57]
Paul Raitzer
As we're doing this, Nvidia is down 12% to start the day. So one of the real important parts of AI literacy is like, why is Nvidia down 12% if you're holding that in your retirement account. Why did your stock portfolio just plummet this morning? If you understand the fundamental elements of AI, you would actually, like, understand that really quickly. What's going on. Yeah. So this AI literacy thing, I alluded to this multiple times on the podcast at the end of 2024 and early in 2025, that we were working on something, the, the AI Literacy Project itself. And you go to literacyproject AI and learn more about this. What had happened is I think that what we do individually, so as our company. So The Institute and SmartRx are sister companies. It's. I own both these companies. Like, it's kind of like a fundamental effort by these two entities. The institutes focus on the marketing segment. SmartRx is focusing on the story beyond marketing. So it's like all these other industries and Personas we see time and time again that there's this lack of preparedness, that, yes, most executives, most professionals, most knowledge workers now are aware that AI is really important, that it is starting to change things. It's in the mainstream media all the time now. Like, you can't not see it. So there is an understanding that it's there and it's important, but there is not an understanding of how quickly it's going to change things and how much it can start to impact individual people, you, your family members, your kids. Like, this is fundamentally going to change everything. And, you know, we can say in the next five to 10, 10 years, we'll talk about some of these timelines and some of these other interviews. We're going to go through these next two episodes. But there is almost universal agreement among AI researchers and leaders that within five years, everything is different, that, that AGI will have been achieved and surpassed. We are either at or on the path to super intelligence, where AI is as good or better than all humans at all cognitive tasks. Like, they think that is a very real future, like five years out. So if that's the case, we have to have a far greater sense of urgency as a society to figure this stuff out to, to enable more people in more professions to develop domain expertise about AI relevant to them and their career paths and their companies. And so, so much of what I try and do with this podcast with our free Intro to AI courses, it's like try to democratize AI education. We're trying to bring this to as many people as possible in hopes that they pick up a piece of it and start figuring out their thing. So I'll go through the three phases, but first I want to I want to read you the core principles. So again, you can go to literacyproject AI and you can see all this for yourself. But this is the basic premise of the AI Literacy Project. So first, we believe AI education should be accessible to all. And we're going to try and do our part to make as much of what we offer free and available to people, if not at extremely low prices or having it underwritten by sponsors, things like that, so we can bring this stuff to people. We believe AI education will be the foundation of success in every organization. We believe in a human centered approach to AI that empowers and augments people. We believe in the value of human knowledge, experience, emotion, imagination and creativity. This is an important one to me. Like, I don't know how this plays out. Like I, I truly believe this. Like there's, there's unique things humans are capable of doing, the things that provide fulfillment to us. I just don't know how each of those things looks five years from now. And that's like part of this is this aspirational thing to figure this out as we're kind of going through these changes next. We believe in the potential of AI to have profound benefits for humanity and society. There are certainly dangers, but again, I try and remain optimistic about the opportunities ahead of us. We believe in an open approach to sharing our AI research knowledge, ideas, experiences and processes. We believe in the importance of upskilling and reskilling professionals and using AI to build more fulfilling careers and lives. We believe in, this is an important one, in the potential to reimagine business models, reinvent industries and careers, and rethink what's possible. That to me is the framing that allows us to be optimistic that we are at this like once in a lifetime, once in a generation, opportunity to reimagine everything. It's scary, but it's also inspiring if you think about it. This next one is maybe the most important one for our business leader listeners. We believe in the redistribution of talent to drive growth and innovation, rather than the displacement of jobs to maximize profits from AI powered efficiency gains. So we want to do our part to push business leaders to be proactive in figuring out how to redistribute talent, not displace it. And then we believe in partnering with organizations and people who share our principles. So the phase, as you mentioned, Mike, the first step is what I talked about up front with AI Academy when we did kind of a brought to you by the AI mastery membership program. Phase one is as of last Friday, our piloting and scaling AI courses which were individually 299 and 999, those are now included in the Mastery membership program. So that's $1,300 savings for anybody who wants to take those. They're built into it. The bigger story for us is Academy 2.0 coming in spring of 2025. This will be a new AI powered learning management system that creates entirely new user experiences, learning paths, customer journeys where they can go through and kind of build these journeys based on careers and departments and industries. And then dramatic expansion of our courses and professional certificates, all part of the same AI Mastery membership program for the same price. There's no increase in price to get all these other benefits. And then a turnkey AI academy solution for businesses. This is really important to me. So as you called out Mike in the data, we know that these corporations all around the world do not have AI academies. They do not have AI training and education that is going to help their employees get reskilled and upskilled fast enough. So I've been trying to kind of crack, crack the code on how to do this where you can get these like out of the box AI academies to where a business could come to us and say we have 3,000 people, we need to teach them all like AI fundamentals, how do we do it? And we have a solution where we can turn it on tomorrow for them. Now, now we can't turn it on tomorrow yet, but this is the vision is that we're going to buy spring of this year you will be able to come in get there's business account pricing like much more affordable than the standard plan and it's going to not only include the current stuff, we're going to have a new AI fundamentals course series which is kind of like AI 101 for knowledge workers. The piloting and scaling courses. We're going to do. The thing I'm maybe most excited about, a new gen A A gen AI app course series where every week we're going to drop AI reviews of AI apps across productivity, image, vision, writing, whatever they are. Like there's like five or six guys, AI agents and so Mike and I are going to collaborate on creating this new weekly gen AI app series. There's going to be AI for industry series where it gets specific into like healthcare, financial services, professional services and then AI for departments like marketing, sales, service ops, hr, finance. So all that is coming this spring. We're going to be building those courses over the next few months and then that will launch with the new platform and then Phase three in the fall, again, more courses that are all enabling people to get specific, like AI for executive series, AI for careers. You can imagine, like, writers, podcasters, marketers, attorneys. Like, it'll kind of start building specific and then AI for businesses. So, like, agencies, law firms, things like that. And so the idea is that, you know, as we go throughout this year, people are going to be able to go in and say, okay, I'm. I'm an accountant. I'm very beginner level at this. Like, what do I do? And it's like, okay, you're going to take AI fundamentals, you're going to do piloting to learn how to prioritize use cases. Then you're going to take AI for attorneys. And. And so you can imagine this, like, truly personalized experience. And then going beyond courses into, like, what newsletter should I follow, what videos should I watch, what books should I read? Like, all of that is kind of being envisioned where you can have this, like, learning inventory that's then personalized to people. And then beyond that, it's about partnering with other organizations that believe in this vision of accelerating AI literacy. And so I've already, like, Friday afternoon after we did this webinar, I had, like, four conversations with people, different ideas of, like, bringing this to different audiences. And so we're open and starting to, like, have these conversations around. What else can we do together with other people who share this vision to make this AI literacy project way more than just about us discounting, you know, the pricing on our courses and offering more things for free and trying to, like, bring this into schools. It's like, what can we do as, like, a society to. To really expand and focus on this vision. So it's, you know, obviously, like, hopefully you can hear my voice. Like, I'm really excited about this. Like, I. I think that we have. The time is right now to do this. I think we have the right partners. We have. We have access to, you know, amazing people, some of whom I've already spoken with, and things like that that I think will hopefully will help create a platform to really drive this change. Because I. I do believe urgency matters right now.
- [40:32]
Mike Kaput
Yeah. And if everything else is going to accelerate, I mean, AI literacy needs to accelerate with it.
- [40:38]
Paul Raitzer
Yes. I don't know that we're going to keep up with, like, the rate of change of the technology, but we're going to do our best to try.
- [40:46]
Mike Kaput
All right, Paul, let's dive into a bunch of rapid fire for this episode. So, first up, just days after returning to the White House President Donald Trump has pretty dramatically shifted the direction of US AI policy. In a new executive order that was signed last Thursday, Trump revoked the Biden administration's executive order on AI. This was a document that was heavily focused on regulation and safety, and he called for the development of AI systems, quote, free from ideological bias or engineered social agendas. Trump's new directive gives White House officials 180 days to develop an alternative AI action plan focused on maintaining American global leadership in AI development. This effort will be led by a small group of tech and science authority officials, including David Sachs, the venture capitalist and former PayPal executive who has been appointed as the administration's AI and crypto czar. The order also instructs agencies to remove and potentially suspend or revise any policies stemming from Biden's previous directive. This includes revisiting guidelines that affect how government agencies acquire and use AI tools. Now, predictably, reactions to these changes have been divided. So supporters of the changes argue that Biden's regulations were overly burdensome and threatened American technological leadership. Critics, including the former acting director of the White House Office of Science and Technology Policy under Biden, contend that the previous administration's policies successfully balanced innovation with public protection. PAUL we made some predictions about what to expect from the Trump administration on AI way back in episode 1 23, which feels like a lifetime ago, the week after the election. It seems like so far this is unfolding pretty much as we expected.
- [42:46]
Paul Raitzer
Yeah, no, no surprises at all. I, I, I think now we just wait, like see what, 180 days from now, which I didn't do the math in my head, was that six months. So June ish, July ish this year will probably be the next. I'm sure we'll hear, you know, things along the way, but basically by the, by the summer 2025, yeah, these action plans are being delivered to the President and we'll go from there. So, yeah, I mean, like we've talked about many times, they're going to pull back on regulation, they're going to accelerate technology. There's going to be many of the risks we've addressed previously on the podcast are going to come to life. Like they're, there will be, there will be very noteworthy incidents as a result of pulling back on this, but a lot of, certainly the people in Silicon Valley feel like it is the only path forward. As we'll talk a little bit more about kind of the growing AI war with China and some of that challenges and, and they feel like this is necessary to win, so to be determined I guess. But yeah, this, this is the inevitable outcome at this point.
- [43:57]
Mike Kaput
Yeah, it seems like maybe get ready for maybe a little bit of the Wild West.
- [44:02]
Paul Raitzer
Yeah, yeah, it's gonna be wild. Yeah. And then there's just new wrinkles, you know, that technological advancements that are, are gonna kind of make us step back and look at this stuff through a new lens, whether it's, you know, new models from other countries or some of these breakthroughs that you hear Demis and Yann Lecun and others talking about is like, we need a couple of breakthroughs. I I Based on the growing sentiment I'm getting from these different interviews that are happening, I I, I do think that most of these leading AI researchers think that those breakthroughs are coming. Like, we're not going to have to wait super long for some of the breakthroughs they're referring to to get to the next levels of AI and that that'll change the dialogue.
- [44:48]
Mike Kaput
Next up, Perplexity has released Perplexity Assistant, which is a new tool that can actively across multiple apps on your phone. Now, Assistant can purportedly handle everyday tasks like writing emails, setting reminders, and booking dinner reservations. What makes it particularly interesting is its ability to work across different apps. So, for instance, it can open Uber and set up a ride for you or start playing specific content on Spotify or YouTube. It is also multimodal. It can see and understand what's on your screen or what's in front of your phone's camera. In testing by the Verge, the Assistant successfully identified recent promotional items and helped compose text messages using information from a phone's contacts. Currently, this assistant works with apps like Spotify, YouTube and Uber, and other basic phone functions like email messaging and clock apps. There are limitations. They can't yet interact with some major platforms like Slack or Reddit, and it is currently only available on Android. Perplexity says they're ready to bring the assistant to iPhone users as soon as Apple provides the necessary permissions. Now, Paul, we have talked more and more about how Perplexity seems to be kind of struggling to differentiate itself. And, like, I found this really interesting of what it can do, but I guess I also maybe naively feel like this is a bit like grasping at straws. Like, I get agents are the next big thing, assistants are the next big thing. But, like, how does this fit in with Perplexity's core business as an AI search engine? Like, what is going on here?
- [46:28]
Paul Raitzer
I, I don't know. I mean, it's like, this sounds like OpenAI's tasks some element of. Are they doing computer use? Like, is it, I don't even know.
- [46:38]
Mike Kaput
Sounds like it is app use.
- [46:39]
Paul Raitzer
Yeah, yeah, it sounds like it. I, I don't know, I, I again, like, I can be completely wrong here. And Perplexity could end up being, you know, IPOing in 18 months and end up being this massive, you know, 50 year company. I just don't see it. Like, so much of this is kind of like a. Me too. They don't have their own models, so they're right, they're building this on somebody else's models. This may be OpenAI's API, it might be Llama. I know they like to build on top of Llama and then like name it and make it sound like it's their own model. They don't have their own models. So they're pulling through the API and they're building these, these things and, and again, it's like, it's, I'm not saying it's not functional. And if you're not a Perplexity user, this isn't cool. I'm just saying, so what, like, any, any tech company could do this. Like they're not doing anything that isn't already done, or someone else can't just do better because they're using their own models or Apple can't do themselves and basically blackball them from the App Store. Like, I don't know, like, so again, I haven't tried it. It could be really cool. Um, if, if people have had good experiences with it, like, you know, let me know, I'd love to, you know, hear, hear that. But yeah, I just increasingly worry that Perplexity just doesn't have a really strong foundation in the future. And that's super differentiated. Yeah. So, and I think I did tweet this one that they picked a great day. I think they launched this on the same day as operator from OpenAI. Yeah, or like Claude introduced something last week, like citations or something.
- [48:16]
Mike Kaput
Yeah. Yep.
- [48:17]
Paul Raitzer
Like they were just in the middle of. It was the worst week.
- [48:20]
Mike Kaput
Right. All right, so next up, Zapier has also announced a revamped Agent workspace, which helps users create and deploy agents that work with their apps. So this is called Zapier Agents. It's a kind of a rebranded and overhauled version, it sounds like, of the company's Zapier Central workspace, which debuted back in 2024. So using it, you can create with the company kind of terms, AI teammates that can work independently across your entire suite of business tools. Now, what makes this Particularly noteworthy is that through Zapier, they're able to interact with over 7,000 different applications and require no coding knowledge to set up. So these agents, when you set them up, can end up accessing live business data, make decisions, and work independently. The system includes a bunch of specialized agents for different business tasks that are kind of already built. There's a lead enrichment agent, which researches prospects and updates your database, a sales outreach agent that crafts personalized messages to potential customers, and a support email agent that can do basic customer service inquiries using your company's knowledge base. There's also a Chrome extension that lets the agents follow you around the web and help with whatever you're working on. So, Paul, this is, I guess, technically a rebranding and expansion of an existing thing, but it does seem really interesting just given. I know there's a ton of hype around AI agents, but Zapier has this interesting angle with all these existing connections to current software.
- [50:02]
Paul Raitzer
Yeah, I would put Zapier in that category of they've got distribution. So we talk often about, like, differentiators can be data and distribution. Do you have proprietary data that you can put into these models that makes them do things that no one else can do? Like, I think you and I use the example of CB Insights recently. Like, we have a subscription to CB Insights, and they have this really cool, like, model layer where the models aren't trained on CB Insights data, at least not legally. And so if you have a subscription to CB Insights, you can go in and experience a chatbot that has access to that proprietary data. And that makes it valuable to you and I, Mike, as users of CV Insights, right away.
- [50:40]
Mike Kaput
Right.
- [50:41]
Paul Raitzer
So they have proprietary data and they have the distribution of their customer base. So in Zapier's case, again, they have distribution to an existing customer base. They're doing something that other companies could emulate pretty quickly, you know, because again, they're not building their own models here. So. But. But they're integrating it right into an experience people are already familiar with. That just increases the, I guess, the experience you have using it. And so it could work like. And that's the. That's the challenge here. Again, like, perplexity could do something very similar, but perplexity isn't built into my existing workflow as an enterprise user. Or maybe Zapier is.
- [51:18]
Mike Kaput
Right.
- [51:19]
Paul Raitzer
And so that's where I think, like, this unknown about the future of adoption of all these different things. They're all building on the same six models, and now some are going to be building on Deep Seq from China. But like they're building on these models and they come up with unique wrappers or applications that are valuable. But if you don't have the distribution already, why would you adopt it? So another example would be like, you know, if you use QuickBooks, for example, online and QuickBooks introduces a chatbot right into the QuickBooks experience that's already connected to my financial data. And I trust them with that financial data.
- [51:52]
Mike Kaput
Right.
- [51:52]
Paul Raitzer
I'm far more likely to just use whatever QuickBooks creates than some third party company that wants access to my QuickBooks that I don't trust with access to my QuickBooks. And so I think a lot of these conversations are happening in like IT departments. It's like, who do we trust with our data? And maybe their chat experience or their AI agent experience isn't as good as Company X, but we trust them. Let's just go ahead and like we'll roll with the thing we already know and trust. And I think a lot of decisions are going to be made around that as this uncertainty about how these agents work and what they get access to and what the risks are with them. I think a lot of companies will play it really safe, especially in 2025, and like let other people make the mistakes.
- [52:37]
Mike Kaput
Anthropic is making some waves with a couple major announcements. So first, Google has just said they are going to put an additional $1 billion investment into Anthropic that builds on their existing channel 2 billion stake. And it comes as Anthropic is reportedly close to securing another 2 billion from other venture capital investors, potentially valuing them at about $60 billion. Now the company has grown very well, it sounds like. According to sources familiar with its finances, Anthropic's revenue reached an annualized rate of $1 billion in December, which represented a tenfold increase from the previous year. Now, alongside this, Anthropic has also launched a interesting new technical feature called citations for its Claude AI models. This allows Claude to ground its answers in source documents by providing detailed references to the exact sentences and passages it use. It uses, which addresses a key challenge in AI application which is verifying all the sources behind what AI is telling you. So Paul, these two things aren't directly related, but I did find them interesting at the same time, maybe they are.
- [53:51]
Paul Raitzer
Actually, as you were saying, that it's. I started thinking like, hold on a second, who's really good at citations?
- [53:57]
Mike Kaput
That's what I was, I was kind of getting into like conspiracy theory in this question here. I was like, well this is something A, Google would be super interested in and B, I think even two. We talked about on our trends briefing how much Apple's been struggling recently with Apple intelligence. We were like, oh, maybe they'll buy Anthropic or something. Well, what they struggled with recently was grounding their AI news sources, news summaries in factual content. So this is pretty interesting. So, like, yeah, should we, what should we be expecting here based on this? Like, can you speculate?
- [54:29]
Paul Raitzer
Yeah, I don't know. I, I do still think Anthropic gets acquired at some point and I, I think that it's getting harder. So if you think about their valuation at 60 billion, your, your potential buyer market shrinks when they were valued at 10, 15, 20 billion. It's a little bit easier to like, you have a much broader spectrum of companies that could come in and buy them. Yeah, but Apple, Google certainly still, you know, in the running there. Yeah, I don't know, the citation thing's really interesting because that is definitely the sweet spot for Google. You can see it in Notebook LM where the citations are happening in line. We'll talk a little bit about Demis Asabas. A couple of interviews he did last week and he was talking about, you know, truth grounding and things like that. So this is a hot topic like solving hallucinations and making models more reliable by grounding them in some truth that you provide, you know, if it's in your company. I, I don't know. I do. I think Anthropic sitting on something like, I get more and more the sense they've been so quiet that they have to have made some progress on their models and, and maybe they just haven't released them. We'll Talk in episode 133 about Dario Amade's interviews. He, he was unusually high profile last week at Davos. He doesn't do a ton of interviews. He was all over the place doing interviews and panels and things. So I think something's coming from Anthropic. I, I wouldn't be shocked if they don't have a new model in the next 30 to 60 days that jumps to the top of the leaderboard again. I think they'll have more to talk about with AI agents. Like they're going to keep doing their thing. I just do increasingly feel like they are a very ripe target for acquisition sooner than later because they've tripled their valuation, I think in the last 12 months. Doubled it. Doubled it. One more, you know, getting to a hundred billion and all of a sudden That's a, that's a real challenging acquisition target. There's very few companies playing in that space. So I would think that if something was going to happen with Anthropic, you could see it happening in the next 12 to 18 months before their valuation just gets too big. And they either have to IPO or, I don't know, you're just perpetually raising. But they're already one of the bigger private companies in the world at this point.
- [56:54]
Mike Kaput
For our next few topics, we have a handful of conversations that came out of the World Economic Forum's meeting in Davos this year with some major AI leaders. So we're going to go through these one by one. And first up, OpenAI's Chief Product Officer painted a pretty dramatic picture of AI's evolution in 2025. So speaking at Davos, OpenAI CPO Kevin Weil outlined how OpenAI's products are rapidly advancing with the costs of AI dropping by 99% over the last few years, while simultaneously becoming faster, smarter and safer. According to Weill, the heart of this transformation is OpenAI's new O series of models, which represent a fundamental breakthrough in how AI systems think. So we've talked about these at length. They reason step by step through complex problems, unlike the current models, which provide just quick surface level answers. And this is more similar to how humans approach challenging tasks. And he mentioned the company's upcoming O3 model has progressed from ranking as the millionth best coder in the world to just to the 175th best in just three months. He also talked about how OpenAI is rolling out early versions of AI agents. And he emphasized that they're taking a cautious approach, ensuring that users maintain control over any significant decisions or transactions. Interestingly, he also suggested that by 2027, or potentially earlier, AI systems might surpass human capabilities at most cognitive tasks. However, he pushed back against doomsday scenarios, arguing that like previous revolutions in technology, AI will ultimately change society for the better by freeing people from mundane tasks and enabling them to focus on more meaningful work. He obviously then mentioned the Stargate project, saying that this was needed to realize this future he was outlining. So, Paul, there's plenty to unpack there, but that prediction about 2027 jumped out at me like, I feel like this timeline is getting talked about a lot more as we kind of hit something that might be considered AGI. Like multiple people have mentioned, hey, it's maybe coming by like 2027 or sooner. Like, what did you take away from that in this interview?
- [59:19]
Paul Raitzer
Yeah, I I think if I remember correctly, I watched so many interviews and listen to so many podcasts the last seven days, but I think he was asked about Dario Amade's comment that it was going to be in like three to five.
- [59:32]
Mike Kaput
Yeah, I think you're right. Yeah, yeah.
- [59:33]
Paul Raitzer
And then he said, or they asked him, like by 2027, he goes, it could be sooner than that. Yeah. So that was definitely noteworthy. Now, there are a lot of people in the AI space who do believe OpenAI is the number one culprit of overhyping kind of this, this AGI path. As we heard, Satya kind of taking a shot at Sam. Maybe on the hype side, their argument is they're trying to raise tens of billions of dollars, if not trillions eventually. And so they, they need this hype to continue. So whether it's real or not, I, I don't know. They, they do certainly have some data points and some research showing that they have reason to be confident in their path and their predictions. I did certainly take note, as you did, of the O3, how quickly they went from 01 being like millionth best coder to like 175th best coder. He did say in the interview that 04 is in training. So we don't even have full 03 yet. And they are in training in 04. So this is what we mentioned, I think on the last episode, that these new sort of test time compute scaling laws seem to be accelerating faster than was expected. So, you know, they're training these models really fast and they seem to be able to bring them to market way faster. So that was of. Of note. And then, you know, this idea of, I mean, it sounds like he's talking about super intelligence by 2027, not just AGI, like where it's good at, like, most cognitive tasks are on par with human level. Most cognitive. He's talking about like superhuman, like better than humans at everything. So, yeah, I don't know. OpenAI's timelines definitely seem to be shrinking faster than most. And it, it is a concentrated effort on their part to get that message out. Because you have, their CPO has now said this, their CFO has said this. Sam keeps saying it in varying degrees. People working at OpenAI are saying it on Twitter like this is a, if not a, a orchestrated effort, it is certainly an approved effort to be allowed to say these things. So I don't know, there's, there is a strategy behind what they're doing.
- [61:45]
Mike Kaput
Another interview that came out of Davos was with Google DeepMind CEO Demis Hassabis. So Demis is actually fresh off winning the Nobel Prize for Chemistry as part of work with the AlphaFold system. And he revealed in this interview that over 2.5 million researchers worldwide now use AlphaFold to map proteins. So far, the system has mapped 200 million proteins, work that would have taken, he claims, a billion years of traditional PhD research time. He sees this as just the beginning of scientific progress, thanks to AI. So they actually now have a spinoff company through DeepMind called isomore isomorphic Labs that is now working to revolutionize drug discovery, combining AlphaFold with other AI models to design new medicines. He actually expects the first AI designed drugs to enter clinical trials by the end of this year. Looking ahead, Hasab is predicted we're five to 10 years away from AGI systems that can match or exceed human cognitive capabilities across the board. However, he emphasizes that this timeline depends heavily on how AGI is defined and likely requires one or two new breakthroughs that haven't happened yet. As part of all this, he's advocated quite a bit for international cooperation and oversight, even considering an international body that could guide development of the most advanced AI systems. So, Paul, we've talked about Demis a ton of times. I think he's such a good person to listen to with all this stuff, especially with scientific discovery, given his background. Like, he is really somehow has this balance of being over. Not over overstated, not like a hype machine, but still communicating. This is going to be transformative. Like, can you walk me through why he's so focused on AI for scientific progress?
- [63:43]
Paul Raitzer
Yeah, I think this is where he's always been. Like, his, his whole mission in life is to solve intelligence and then solve everything else. So, you know, we've talked many times about interviews Demis has done. He doesn't, he doesn't do a ton, but he was definitely on the circuit last week. Also, there was the interview you're talking about. And then I'll sprinkle in a couple of notes from the big technology podcast where he also did an interview. And it's so funny, like, when you, when you listen to two or three in the same week and you realize, okay, the PR people have specific talking points they're trying to hit because, like, literally the same exact line will come out and you find ways to say the same stuff and you can actually start to tell what the PR people fed the interviewer of, like, here's the six things we want you to cover. And then you're allowed to talk to them about other Stuff now again, like Mike and I did PR when I owned my agency. We lived in the PR world. So I kind of know how this game works a little bit. Um, so yeah, a couple of, of notes here. There's, I think he said a lot of interesting things, built on some things we've talked about before, but a few noteworthy items. So this idea of AlphaFold folded all 200 million proteins known to science. It takes several years on average to find the structure of a single protein. He often says like A. A PhD will spend their entire time in PhD figuring out how to fold a single protein. They figured out how to fold 200 million of them. It would have taken a billion years of PhD time and they just gave it free to the world. So this, like we're always trying to find ways to not feel the AGI, feel what an exponential growth curve looks like. And I think this is a practical example. And so take this and apply it to your industry. Like, what is this like unsolvable problem that like we could put a billion hours or years of human time at. We're just not going to figure it out. Now imagine something being so intelligent that it can do it in hours. That would have taken a billion years. So it. And it has happened. So now we have like a point of reference to look at. This is super intelligent. This is like beyond what a human could do in a very narrow application. Now imagine every human problem being able to be solved like this. And that's the vision that Demis has for the world, like cancer research, climate change, why does the universe exist? How was it created? Like all these big questions. That's what he wants to do. And so biology, chemistry moves into like drug discovery comes out of that. That's what they're working on. He talked a lot in that interview about like some of the breakthroughs they had, like VO2, which again is the video generation model. Project Astra, he said, would like be coming to consumers later this year, which I think is the first time they publicly said that that would probably start coming. He Talked about Gemini 2.0 where they're working on what they call a thinking model. So same as reasoning, they just kind of brand it differently. Interesting. Go back to the citations thing, Mike. We talked about hallucinations and factuality. He said there's three basic paths to solving this. One is filter out misinformation in the training. So you go through all the data in the training and you try and get all that out. That is not a reasonable solution. That's too, too hard and becomes too biased, like who's deciding, like what's misinformation. The second is tool use, specifically being able to use Google search to fact check things. And then the third is reasoning. They have found that the more time you give these models to think, the more factual they can become when they go through like this process. AGI. I thought this was interesting because his definition of AGI, he said it's what they've always defined it as. Yet I don't, I'm not sure that I've seen him say it exactly this way before, but he describes it as a system that is capable of exhibiting all the cognitive capabilities that humans have. But he said we are maybe five to 10 years away, maybe one to two breakthroughs. But then in the next interview he said three to five. So again, like their timelines all kind of vary. He talked about emergent capabilities, too much hype in the short term, not enough hype for midterm and long term, like the open AIs of the world maybe are hyping too much. But Demis's belief is five to 10 years, it's underrated and underappreciated how much society is going to change. And then in the big technology podcast, which we'll drop those links into, he got a little bit deeper because the interviewer asked like more questions specific like AGI. So he said what's missing is advanced reasoning, which we talk about all the time, hierarchical planning, long term memory, those are kind of like the main things. And then he said, well, what do you want to see to like know we're kind of getting to AGI? And he said that it should be able to invent its own hypothesis or conjectures about science, not just prove existing ones. So that's it's big on like invention. He said lots of outlandish and exaggerated claims right now just to raise money. They talked a lot about world models. This is what they're trying to work on is like this understanding of the world around the AI, the physics of the world. He said VO2 is surprisingly accurate on physics, still makes mistakes, but like they were a little bit shocked at how well it did. He asked him about scaling laws, which we talk about all the time. He said they are working like they're still going but they are slowing needs to improve ideas. Like he said, what are the big breakthroughs? Like where are these one to two breakthroughs going to come from? Demis said planning, memory, search, reasoning, creativity were the big ones. And then I thought he had this cool perspective on Creativity. He was asked specifically about, like, his thoughts on creativity, and he said there's three types of creativity he thinks about. One is interpolation, which is like averaging what you see to come up with something new. So create a cat for me. It's seen a million cats and it creates a cat when you ask it for that image. That's interpolation. Extrapolation is learn from examples and come up with something new a human would never do. Which he related then to AlphaGo and the infamous Move 37, where it did something that a human go player would have just never done. So he considers that extrapolation and that's kind of where he thinks we are right now. The third element of creativity is invention. That's when it creates an entirely new game, an entirely new mathematical model, an entirely new hypothesis that a human hadn't come up with yet. It's not in the training data. And so he said that's. We don't have that yet. But he thinks that that's coming like the extrapolation part is coming in agents, but like the invention part is sort of the next level. And then a couple of quick notes. Deceptiveness. He talked about that, that they are seeing the same deceptiveness. I think Anthropic had the paper on like faking alignment. He said, we are absolutely seeing the same things in our models. They are intentionally deceptive. And that is hard to kind of figure out. And it does make you have to question all the other results you're getting if you know it can be deceptive in one element. And then he got into the web, which, you know, again falls into the business marketing side of this, where it's like, what happens to the web when agents are everywhere, when operator is the thing visiting websites and agents are talking to agents and like, the human's not really doing the research and users just have these assistants. And he basically said, like, yeah, it's going to fundamentally change everything. We don't know yet what that looks like. I thought, oh man, if he doesn't know, like, then the rest of us are kind of in trouble. And then two other final notes, Deep Seek, which we're going to again talk more about in episode 133. He did reference one of the sort of sticking points that we'll get into a little bit more, which is it does definitely seem as though this company trained on open source models, like took data from open source models, took outputs and used it to train. And then they're very opaque about what their training data was because they assumed they stole a bunch of it from US companies or like they got it from other places. So there, there he's kind of like, it's really impressive. They probably had a bit of a head start that they're not going to disclose in the research papers, but it is what it is. And then the final one, I haven't read this Mike, but the interviewer asked him, like, what do you think a world looks like when we have super intelligence? And he said he actually leans on sci fi a lot to try and visualize that. And he mentioned Culture Series by Ian Banks. I don't know if you've heard of that. I had. Not as one of his favorite books on like a possible future where agents are everywhere and we've achieved super intelligence. But he did say, like, he's not going to figure this out. Like, we can't rely on these AI research labs to solve this. That need philosophers. And he said, we need our great philosophers to sort of step up and think about this future, which is. It's an interesting perspective like that you and I and these, you know, the tech people, they're not gonna be the ones that actually tell us what 20 years from now looks like. You, you really need these people who can think deeply about society and humanity. And so I don't know. Yeah, I mean, I obviously, I'm a huge Demis fan. I listen to every interview the guy does, but, you know, I think that each time he repeats some of the previous things. But you also build on it. And I think we got a lot of building on things in the last couple interviews last week.
- [72:49]
Mike Kaput
Yeah, that philosopher perspective is interesting. It's going to be important because if you read any of the culture books, it gets really weird really quick.
- [72:59]
Paul Raitzer
Have you read them?
- [73:00]
Mike Kaput
I've read a couple of them.
- [73:01]
Paul Raitzer
Have you?
- [73:02]
Mike Kaput
Okay, so a really good accessible one to start with, which is one of the earlier ones. They're all like. I think there's like many little series in the. Within this whole world, but a lot of them are one off books set in the same place, but one called Player of Games is the, like a really good one off story in this world. But it gets so strange so quick and you're like, oh my gosh, like, this is what might really happen if you had limitless intelligence and abundance. It's like humans are not the main character in a lot. A lot of it.
- [73:32]
Paul Raitzer
I may have to get a couple of the audiobooks and.
- [73:37]
Mike Kaput
All right, so one other big conversation with an AI leader that came out of Davos was with Yann LeCun, Sameta's chief AI scientist. He made some bold predictions about the future of AI, suggesting that current AI systems will be largely obsolete in five years. So he argued that today's large language models, despite how impressive they are, suffer from fundamental limitations that will drive the development of entirely new AI architectures. The current generation of AI, LeCun explained, falls short in four critical areas. Understanding the physical world, maintaining persistent memory, reasoning, and complex planning. So these limitations mean that while today's systems are good at manipulating language, they're not truly capable of thinking in the way humans do. He actually envisions a new paradigm built around what researchers call world models, which we just talked about, so systems that would help machines develop common sense, intuition, and genuine reasoning. He also thinks that the next decade could be the decade of robotics, um, but points out that even our most advanced AI systems cannot even match a cat's understanding of the physical world. He suggested that combining improved AI with robotics could unlock a lot of new possibilities. So, Paul, I guess what jumped out to me is not only how this relates to what Demis said very clearly, but also all those areas AI falls short in, according to Lecun, appear to be kind of all the areas AI labs are tackling now.
- [75:09]
Paul Raitzer
Yeah, I definitely was echoing almost exactly what Demis said. And Jan is, you know, as we've said on the show before, he is very adamant that the current language models are not the path to AGI, that things are missing. And I always think, generally speaking, these people take different positions and they, like, can be contrarian to each other, but at the end of the day, when you drill into what they're really saying, they're all kind of agreeing with each other that they all think some breakthroughs are needed. And I remember, I think it was in the fall, I, I, I remember listening to a Dario Amade interview where he was talking about, like, the research directions at Anthropic. And it, it reminds me of this now because, you know, here we see, like, you know, the memory, the reasoning, the planning, the search, the world models. They're all agreeing these, like, the breakthroughs are going to come from something, so they know the paths to look for. But each research lab has to make their bets about which of these is maybe the unlock. And so if you have like, five or six potential areas where the breakthroughs may come that take us to AGI or super intelligence, each lab has to figure out the recipe. How important is reasoning to this? How important is the world model? And they have to make some bets of what kind of model are they going to build. We're going to put X amount of time into the reasoning, we're going to put this into the search. We're going to put this in the multimodal aspect. And that's kind of, I think, where we're at. That's a good synopsis of where these AI models are in 2025. They're getting really powerful. They're getting generally capable. They seem to know the breakthroughs are going to come from one of, or two or three of five or six areas. Now they all have to place their bets on which, where it goes. And so it's, it is fascinating and, and to see where each of these, with the decisions they make is going to kind of decide which of these AI model companies maybe becomes the key player. But then as we'll talk about with Deep Seq, it's like, but how long of a lead did they really get when they figured out, is it three months, is it six months?
- [77:16]
Mike Kaput
All right, our final topic for this episode is about consumer appetite for AI. So this apparently reached new heights in 2024. According to some reporting from TechCrunch, the spending on AI mobile apps surpassed $1.1 billion, which is a 200% increase from the previous year. So in this report, TechCrunch is citing research from the app intelligence provider Sensor Tower. They released a report called the State of Mobile 2025. So according to that report, this surge in AI spending helped drive total consumer app spending to $150 billion globally. Now, interestingly, this wasn't just driven by periodic spikes around major releases like OpenAI's GPT4,001, whatever. Instead, consumer demand remained pretty consistently strong throughout the year. Users spent nearly 8 billion hours using AI apps. And applications mentioning AI were downloaded 17 billion times that year. ChatGPT, of course, though, emerged as a standout. It reached 50 million monthly active users, faster than major platforms like Disney plus or YouTube Music. And the scale of this growth has them predicting that AI apps could break into the top 10 categories by consumer spending within a year if the current trends continue. So, Paul, does this number surprise you at all? This rate of growth is pretty crazy.
- [78:45]
Paul Raitzer
Yeah, they're big numbers. I mean, it's, it's going to get so hard to differentiate, like AI app spending, right? Every app's going to be AI. So, yeah, it's it. I don't know. I always find this kind of data interesting to look at, the adoption curve, but I think at the high level what it's telling us is it's just becoming ubiquitous within society. Like, they're just. It's just going to be everywhere. It's going to be part of every piece of software, every app we use. And I guess it goes back to this whole idea of, like, the AI literacy thing is just so fundamentally important to understand how your kids are using these tools. I was listening to Interview this morning about, like, AI characters in video games and how that's going to be huge in the next, like, one to two years. And we, I think we've touched on that podcast before, but, like, your kids are going to be interacting with AI agents in games, and those agents are going to have, like, basically be built on top of language models where they can just carry on unscripted conversations and go in different paths. And, like, you don't know your kids are doing that stuff. Like, that's a whole nother world, but they're going to be doing that stuff. They're interacting with AI on Snapchat and wherever else they Roblox. Like, it's just gonna be everywhere. And we just need more people understanding that and, like, preparing for it.
- [80:00]
Mike Kaput
Yeah. I would also say the mobile aspect here is particularly interesting because if you're a listener of a certain age, I would highly encourage you to look at the top mobile apps versus top desktop apps, because it's a very different list. And a lot of them are apps that you and I, I think we've talked about in the past, are much more targeted towards younger generations and are pretty eye opening.
- [80:23]
Paul Raitzer
Yeah. And especially when you get into, like, the companionship and relationship side, those are very popular. And that was actually something Demis touched on was the, you know, this idea of companions. And you have your work life, your personal life, AI assistants, but people are going to increasingly look at them as friends and companions and stuff. And, yeah, it's going to get a little weird.
- [80:45]
Mike Kaput
All right, Paul, that is it for this episode. Like we talked about, we're going to record another one and release another one. This week will be for everyone who's kind of chomping at the bit about Deep Seek. We'll cover that and a bunch of other topics. So, Paul, appreciate you breaking all this down for us.
- [81:02]
Paul Raitzer
Yeah. And by the way, Nvidia, in the hour and 20 minutes we've been on this is now down 14%. Oddly. Meta is up slightly. I actually expected Meta to get crushed because, huh. Deep Seek, if anything, is an attack on Llama, I would have thought. But I don't know. We'll talk about that in the next episode. I gotta process this information in real time. All right, thanks everyone for joining us. We will be back on episode 133, I guess tomorrow, depending on when you're listening to this. Thanks Mike.
- [81:28]
Mike Kaput
Thanks Paul.
- [81:30]
Paul Raitzer
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