59 Min Read

[The AI Show Episode 132]: OpenAI’s Operator, Stargate, The AI Literacy Project, Trump AI Executive Order, Perplexity Assistant & Zapier Agents

By Claire Prudhomme on January 28, 2025

Podcasts

Join Mike and Paul as they navigate through a huge week in AI: They unpack OpenAI's Operator, Project Stargate, and explore SmarterX's ambitious push to democratize AI education. Plus, Trump’s actions on AI in his first week in office, Perplexity Assistant, Zapier Agents, and more in our rapid-fire section.

Listen or watch below—and see below for show notes and the transcript.

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Timestamps

00:05:57 — Open AI Introduces Operator

00:18:39 — Project Stargate Announced

00:29:00 — The AI Literacy Project

00:40:50 — Trump Actions on AI in First Week

00:44:47 — Perplexity Assistant

00:48:22 — Zapier Agents

00:52:36 — Google Invests Another $1B in Anthropic

00:56:53 — Davos Conversations with OpenAI CPO

01:01:45 — Demis Hassabis on AI for Scientific Progress

01:13:35 — LeCun Predicts New AI Architecture Paradigm in 5 Years

Meta’s Yann LeCun predicts ‘new paradigm of AI architectures’ within 5 years and ‘decade of robotics’ - TechCrunch

01:17:17 — AI Apps Saw $1B+ in Consumer Spending in 2024

AI apps saw over $1 billion in consumer spending in 2024 - TechCrunch

Summary

Operator

OpenAI just released Operator, an AI agent that can literally take control of a web browser and perform tasks for you.

That means Operator can actually do things like book your flights, order your groceries, make restaurant reservations, and even complete online purchases.

Here's how it works: Operator gets its own dedicated browser window where it can click, type, and scroll just like a human would. It combines GPT-4o'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 to you.

OpenAI is implementing strict safety measures. Operator will ask for user approval before completing any significant actions, like submitting an order or sending an email.

For sensitive tasks involving payments or login credentials, it hands control back to the user. The system also includes defenses against malicious websites and monitoring for suspicious behavior.

OpenAI plans to make Operator available to more users through its Plus, Team, and Enterprise tiers, and eventually integrate it directly into ChatGPT.

Stargate

In a dramatic announcement at the White House, OpenAI, SoftBank, and Oracle unveiled plans for an unprecedented AI infrastructure project called Stargate. The venture aims to invest up to $500 billion over four years to build massive AI data centers across the United States, starting with an initial $100 billion deployment.

OpenAI and SoftBank will each invest $19 billion as lead partners, with SoftBank handling finances and OpenAI managing operations. The venture will focus solely on OpenAI's computing needs, marking a shift in its relationship with primary backer Microsoft.

The first facility is under construction in Abilene, Texas, where Oracle and Crusoe are building a massive complex requiring enough power to run a city the size of Austin. The facility will house 100,000 of Nvidia's newest AI chips and is just the start of Stargate's planned expansion across the U.S.

However, questions remain about funding. While the initial $38 billion from OpenAI and SoftBank is confirmed, it’s unclear how the full $500 billion will be secured.

Experts also question whether enough power and resources can be obtained for multiple large-scale facilities, especially with 17 other major AI clusters already planned or in development across the U.S.

AI Literacy Project

SmarterX has launched a major new initiative that aims to tackle one of AI's most pressing challenges: the growing gap between AI's rapid advancement and people's understanding of it.

It’s called The AI Literacy Project, and it’s an ambitious effort to democratize AI education and prepare professionals across all industries for the future of work by making AI education accessible and personalized.

SmarterX is rolling out a three-phase plan throughout 2025. The first phase, launching immediately, expands the existing AI Mastery Membership program to include professional certificate courses in piloting and scaling AI. The second phase, coming this spring, will introduce a new technology platform with expanded course offerings and customizable solutions for businesses. The final phase, planned for fall 2025, will add specialized courses for executives, career development, and business applications.

This episode is brought to you by our AI Mastery Membership:

This 12-month membership gives you access to all the education, insights, and answers you need to master AI for your company and career. To learn more about the membership, go to www.smarterx.ai/ai-mastery.

As a special thank you to our podcast audience, you can use the code POD100 to save $100 on a membership.

Read the Transcription

Disclaimer: This transcription was written by AI, thanks to Descript, and has not been edited for content.

[00:00:00] Paul Roetzer: 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.

[00:00:18] Paul Roetzer: My name is Paul Roetzer. 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 Kaput 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.

[00:00:39] Paul Roetzer: Join us as we accelerate AI literacy for all.

[00:00:46] Paul Roetzer: Welcome to episode 132 of the Artificial Intelligence Show. I'm your host, Paul Roetzer, along with my co host, Mike Kaput. We have a unique week going on right now. We are going to do two episodes. [00:01:00] 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 bad news.

[00:01:12] Paul Roetzer: Yeah. 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.

[00:01:32] Paul Roetzer: Well, things that on like Tuesday of last week I had noted is 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 had planned to be one of the three most important things we talk about that isn't going to be covered on two episodes.

[00:01:52] Paul Roetzer: So we are going to break all of last week's news into episode 132 and 133. So we are recording. [00:02:00] 1. 32, the morning of January 27th, pre market as the stocks are tumbling as we speak in pre market trading as a result of DeepSeek, the new Chinese AI model and app that we will definitely be talking about.

[00:02:15] Paul Roetzer: 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, you've got, you know, double the episodes to get through, today.

[00:02:35] Paul Roetzer: 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. Alright, so, this episode is brought to us by the AI Mastery Membership Program.

[00:02:54] Paul Roetzer: We've been talking a lot about this. If any of you joined us on Friday, January 24th, we had [00:03:00] 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.

[00:03:18] Paul Roetzer: 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 on to that membership.

[00:03:38] Paul Roetzer: 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 we offer, You can now do it as part of that membership.

[00:03:57] Paul Roetzer: So just go to smarterx. ai [00:04:00] slash 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 POD100, that's P O D 100 as a promo code to save 100 off of the membership. Alright, so more to come on AI Mastery Membership and the AI Literacy Project.

[00:04:20] Paul Roetzer: And then a reminder before we get rolling here that our 6th Annual Marketing AI Conference or MAICON is taking place October 14th to the 16th in Cleveland, Ohio. And registration is now open, so you can go to MAICON. AI, that's M A I C O N. A I, to learn more. but, if you want to speak at the conference, or if you know someone who should be speaking, the opportunity is open right now to submit a speaker application.

[00:04:48] Paul Roetzer: 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 [00:05:00] they come in, and we're building the agenda sort of in real time. We're not waiting till March to, to do all this. So, as those, spots fill, the opportunities to speak will kind of lessen.

[00:05:11] Paul Roetzer: 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 MAICON. AI and you can, right on the homepage, see the Submit Your Speaker Application button, and just click that and send that to us.

[00:05:31] Paul Roetzer: All right, Mike, we, um. So much to talk about. So many, so many big ideas and topics, but let's get started with, 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.

[00:05:54] Paul Roetzer: but let's start off with Operator from OpenAI.

[00:05:57] Operator

[00:05:57] Mike Kaput: Alright, Paul, so OpenAI [00:06:00] 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.

[00:06:19] Mike Kaput: 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 GPT 4. 0'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.

[00:06:52] Mike Kaput: So this tool is powered by what OpenAI calls their Computer Using Agent Model, CUA, which is trained to [00:07:00] interact with regular website interfaces rather than requiring special programming 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 200 a month pro plan.

[00:07:20] Mike Kaput: 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. 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.

[00:07:45] Mike Kaput: 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 [00:08:00] 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.

[00:08:15] Mike Kaput: What are you seeing? Well,

[00:08:17] Paul Roetzer: Yeah, so, just contextually, we'll put the links, in the show notes, but, you know, one thing to note is, this is, we've known this technology was coming for a long time. So, back in February of 23, I think, February, March 23, we, we talked about World of Bits, which is a research paper from OpenAI back in 2017, led by Andrej Karpathy.

[00:08:39] Paul Roetzer: 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 computer. We got it [00:09:00] in fall of last year, fall of 24.

[00:09:04] Paul Roetzer: 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. 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.

[00:09:28] Paul Roetzer: 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's fun, it's kind of cool that it does these things.

[00:09:50] Paul Roetzer: 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 [00:10:00] recently on the podcast, works at Google DeepMind, was at OpenAI previously. He said, I just used Operator for the first time. It nailed my test requests.

[00:10:09] Paul Roetzer: 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 that 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.

[00:10:28] Paul Roetzer: Allie 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 Clawed computer use. I like that it punts it back to the user for logins and payments, as you had said, Mike.

[00:10:46] Paul Roetzer: 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, may be the first AI agent that's really accessible to non developers. [00:11:00] Ethan Mollick said, Implications of Operator, number one, general purpose web agents aren't there yet, but seem more workable than expected.

[00:11:09] Paul Roetzer: Operator is quite good. Number two, companies aren't thinking enough about how to market to preference of agents. I actually saw a couple of examples, Mike, where like people's websites didn't work in the operator. I saw that 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.

[00:11:32] Paul Roetzer: And then, Mollick 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 Karpathy has to say. So again, Andrej Karpathy led the team trying to do this eight years ago at OpenAI, went back to OpenAI in 2023 to work on this again.

[00:11:54] Paul Roetzer: So it's like, there's no one more qualified to assess Operator than Karpathy. And he did [00:12:00] 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.

[00:12:17] Paul Roetzer: But it should work, he says in quotes. Today operator can find you lunch on DoorDash or check a hotel, etc. Sometimes and maybe. It 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, remember, is level 5 of OpenAI's levels of AIs basically organizations.

[00:12:42] Paul Roetzer: 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 was my overall take. I have not personally used it yet. I do start to think about these [00:13:00] ramifications around search. So as these agents start working more and more, start doing more of the web work for us.

[00:13:06] Paul Roetzer: 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.

[00:13:33] Paul Roetzer: I know you have a pro license, but like, have you played around with Operator at all? Have you had any experiences with it?

[00:13:38] 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 res restaurant reservations.

[00:13:53] Mike Kaput: I kind of felt along the lines of Ethan Mollick that I realized it was very limited and slow and [00:14:00] 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.

[00:14:21] Mike Kaput: And a reason for that, I within seconds ran into the problem that I 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.

[00:14:47] Paul Roetzer: Actually, now you're saying that, that introduces a whole new element of generative AI policies in companies. Like if you haven't addressed computer use in your generative AI policies. Back to the drawing board, you're going to have to, you [00:15:00] know, integrate that. this is only available in those pro licenses.

[00:15:03] Paul Roetzer: Like, you can't get this in team and enterprise accounts yet in ChatGPT. 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, OpenAI isn't even aware of all the ways this could go wrong and people could get access to data and things like that.

[00:15:25] Paul Roetzer: so, I don't know, like, 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 percent or the one tenth of 1 percent who make it seem like this is changing the world and everything's gonna change in the next 6 12 months.

[00:15:45] Paul Roetzer: The game has changed, like those tweets you see from people. It hasn't. Like, this is not transforming your business life or your personal life yet. I think can, can, enterprise adoption is going to be insanely slow [00:16:00] 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.

[00:16:10] Paul Roetzer: So, I, 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.

[00:16:30] Paul Roetzer: 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. Okay, this might actually affect this industry way sooner than maybe this industry.

[00:16:47] 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 talks a lot, which is, look, we can't predict exactly what's going to happen when, but [00:17:00] we know the broad strokes of what's coming, like agents are going to be a thing.

[00:17:04] Mike Kaput: 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.

[00:17:24] Paul Roetzer: And that's one of the exciting things for me with like our Marketing Institute community and now kind of the emerging SmarterX 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.

[00:17:47] Paul Roetzer: 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 [00:18:00] to be made figuring all this out when you zoom into a specific department or industry or career path. Mike and I aren't going to be the ones to figure that out.

[00:18:09] Paul Roetzer: 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 going to be the one to figure this out in my company or in my industry.

[00:18:27] Paul Roetzer: 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.

[00:18:39] Stargate

[00:18:39] Mike Kaput: In our next big topic that hit us this week, there's been a dramatic announcement at the White House that involves OpenAI, SoftBank, and Oracle.

[00:18:50] Mike Kaput: Kind of unveiling plans for a huge AI infrastructure project that is called Stargate. This venture aims to invest up to 500 billion [00:19:00] 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.

[00:19:15] Mike Kaput: 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 Austin.

[00:19:46] Mike Kaput: 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 [00:20:00] lot of complexity to, to them. So, OpenAI CEO Sam Altman, he'd kind of grown frustrated.

[00:20:06] Mike Kaput: 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.

[00:20:34] Mike Kaput: But there's a lot of unknowns here still. Like the 38 billion from OpenAI and SoftBank looks to have been confirmed, 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.

[00:20:57] Mike Kaput: And however, despite all this, if this [00:21:00] 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.

[00:21:24] Mike Kaput: So follow the marketing hype.

[00:21:26] Paul Roetzer: 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 do appreciate this. Like, let's just go more sci fi and have some fun with it. Yeah, I love them. So,

[00:21:44] Mike Kaput: you know, what's interesting though, is like, I want to get kind of just your overall thoughts on this.

[00:21:49] Mike Kaput: 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 upscaling. And while [00:22:00] this is not directly related to that, this seems like one that they're attempting for infrastructure.

[00:22:05] Paul Roetzer: Yeah, definitely.

[00:22:05] Paul Roetzer: So I, 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.

[00:22:29] Paul Roetzer: how it happens is gonna, 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.

[00:22:49] Paul Roetzer: holding what seemed like a kind of an impromptu press conference with Altman, Larry Ellison, and Masa san? Who's the guy from the Yeah, Masa Hiyoshi san, [00:23:00] yeah. so, it's, it is, it is being formed as a new company, so that came out in an open AI, 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 percent equity or something.

[00:23:16] Paul Roetzer: 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.

[00:23:31] Paul Roetzer: They don't have 19 billion dollars 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 guys. And they had the CEO of Arm, who's actually heavily involved in this deal.

[00:23:49] Paul Roetzer: 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, [00:24:00] which is doubtful, they, they don't have the energy to run a two and a half gigawatt data center. So, like, nothing seems to actually add up for this, yeah, we're gonna spend 500 billion over the next year.

[00:24:12] Paul Roetzer: And so, Gerstner's analyst firm basically went through, like, They couldn't possibly even spend a hundred billion this year. Like there, 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?

[00:24:27] Paul Roetzer: 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. It is the 500 billion is not real yet. and there's all these other open questions.

[00:24:46] Paul Roetzer: 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 to build the data centers that Sam wanted to build this power, [00:25:00] and so Microsoft let Sam out of their exclusive deal so he could go do a deal with Oracle to bring this to life.

[00:25:09] Paul Roetzer: and it was for a facility that was already being built. So like, it's not even an opening ice 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.

[00:25:27] Paul Roetzer: But one of them, I think it was on Wednesday, so the day after this, 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 how they're spending it all.

[00:25:46] Paul Roetzer: 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 validity of this deal. And so he tweets, [00:26:00] let's see, so he said, okay, so I tweeted out, it was only a matter of time until Musk showed up, they don't actually have the money, was his tweet.

[00:26:10] Paul Roetzer: 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 Must 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.

[00:26:29] Paul Roetzer: 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 had, does have the money.

[00:26:50] Paul Roetzer: 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. That sure [00:27:00] seems like a shot at Sam. Right. 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.

[00:27:13] Paul Roetzer: 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, great, 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.

[00:27:37] Paul Roetzer: 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 fans of solar.

[00:27:58] Paul Roetzer: It is truly a soap [00:28:00] opera. Like it's, it's amazing to watch this all unfold.

[00:28:04] 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.

[00:28:20] Mike Kaput: Yeah.

[00:28:20] Paul Roetzer: 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.

[00:28:40] Paul Roetzer: 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 DeepSeek, but, yeah. Infrastructure and energy that we are fairly confident are going to keep being built.

[00:29:00] The AI Literacy Project

[00:29:00] Mike Kaput: All right. Our third big topic for this episode involves some news from you, Paul, and our team.

[00:29:05] Mike Kaput: So Paul on Friday, January 24th, SmarterX, your research and education firms, 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.

[00:29:44] Mike Kaput: So through it, SmarterX is setting out to drive AI understanding and across industries and professions through affordable courses in education. You're out to provide a path to AI mastery through content, events, and experiences, and also [00:30:00] personalize learning journeys to maximize the positive impact of AI on people's careers and lives.

[00:30:06] Mike Kaput: 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 percent of workers say they want to learn new skills to work with generative AI, only 5 percent of organizations currently provide AI training at scale.

[00:30:25] Mike Kaput: Similarly, in our 2024 State of Marketing AI report, we found that 67 percent of professionals cite a lack of education and training as a top barrier to AI adoption, and 75 percent 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.

[00:30:55] Paul Roetzer: as we're doing this, NVIDIA is down 12 percent to start [00:31:00] with. So one of the real important parts of AI literacy is like, why is NVIDIA down 12 percent 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.

[00:31:19] Paul Roetzer: 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 AI literacy project itself, and you go to literacyproject. ai and learn more about this. what, what happened is, I think that. What we do individually, so as our company, so the Institute and SmarterX are sister companies, it's, well, I own both these companies, like, it's kind of like a fundamental effort by these two entities, the Institute's focused on the marketing segment, SmarterX is focused on the story beyond marketing, so it's like all these other industries and personas, [00:32:00] 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.

[00:32:14] Paul Roetzer: it's in 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.

[00:32:33] Paul Roetzer: Like, this is fundamentally going to change everything and it, you know, we can say in the next five to ten 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 that, that AGI will have been achieved and surpassed.

[00:32:56] Paul Roetzer: We are either at or on the path to superintelligence where AI [00:33:00] 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.

[00:33:28] Paul Roetzer: 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.

[00:33:50] Paul Roetzer: 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 [00:34:00] 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.

[00:34:10] Paul Roetzer: 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.

[00:34:27] Paul Roetzer: This is an important one to me. Like, I don't know how this plays out. Like, 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.

[00:34:49] Paul Roetzer: 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. [00:35:00] 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.

[00:35:12] Paul Roetzer: We believe, and 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.

[00:35:29] Paul Roetzer: 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.

[00:35:48] Paul Roetzer: 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 [00:36:00] principles. So the phases 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.

[00:36:10] Paul Roetzer: 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.

[00:36:31] Paul Roetzer: Bye. 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.

[00:36:52] Paul Roetzer: 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 [00:37:00] 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 re skilled and up skilled fast enough.

[00:37:14] Paul Roetzer: So, I've been trying to kind of crack it, 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 3000 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.

[00:37:31] Paul Roetzer: 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.

[00:37:53] Paul Roetzer: The piloting and scaling courses, we're going to do, the thing I'm maybe most excited about, a new Gen [00:38:00] 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.

[00:38:18] Paul Roetzer: There's going to be an 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 of 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.

[00:38:51] Paul Roetzer: 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 [00:39:00] 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 so you can imagine this like truly personalized experience.

[00:39:14] Paul Roetzer: And then going beyond courses into like what newsletters 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.

[00:39:33] Paul Roetzer: And so I've already, like Friday afternoon after this webinar, I had like four conversations with people, different ideas of like bringing this to different audiences. Take care. 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.

[00:39:59] Paul Roetzer: It's like, what can we [00:40:00] do as, like, a society to, to really expand and focus on this vision? And so. It's, you know, obviously, like, hopefully you can hear my voice, like, I'm, I'm really excited about this. Like, 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.

[00:40:21] Paul Roetzer: That I think will, hopefully will help create a platform to really drive this change because I do believe urgency matters right now.

[00:40:32] Mike Kaput: Yeah. And if everything else is going to accelerate, I mean, AI literacy needs to accelerate with it. Yes.

[00:40:39] Paul Roetzer: 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.

[00:40:46] Mike Kaput: All right, Paul, let's dive into a bunch of rapid fire for this episode.

[00:40:50] Trump Actions on AI in First Week

[00:40:50] Mike Kaput: So first up, just days after returning to the White House, President Donald Trump has pretty dramatically shifted the direction of US AI [00:41:00] policy. In a new executive order that was signed last Thursday, Trump revoked the Biden administration's executive order on AI.

[00:41:08] Mike Kaput: 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.

[00:41:33] Mike Kaput: This effort will be led by a small group of tech and science 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.

[00:41:55] Mike Kaput: This includes revisiting guidelines that affect how government agencies [00:42:00] 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.

[00:42:28] Mike Kaput: Paul, we made some predictions about what to expect from the Trump administration on AI way back in episode 123, which feels like a lifetime ago, the week after the election. It seems like so far this is unfolding pretty much as we expected.

[00:42:46] Paul Roetzer: Yeah, no, no surprises at all. I think now we just wait, like see what 180 days from now, which I didn't do the math in my head.

[00:42:54] Paul Roetzer: Was that six months? so June ish, July ish this year [00:43:00] will, 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, these, action plans are being delivered to the president and we'll go from there. So, yeah. Yeah, I mean, like we've talked about many times, they're going to pull back on regulation.

[00:43:17] Paul Roetzer: 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 there, 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.

[00:43:39] Paul Roetzer: As we'll talk a little bit more about kind of the growing. AI war with China and some of that challenges 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.

[00:43:56] Mike Kaput: Yeah. It seems like maybe get a ready for maybe a little [00:44:00] bit of the wild west.

[00:44:01] Paul Roetzer: Yeah. Yeah. It's going to be wild. yeah. And then there's just new wrinkles. Um. You know, that technological advancements that are, are going to 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, you know, we need a couple of breakthroughs.

[00:44:26] Paul Roetzer: Based on the growing sentiment I'm getting from these different interviews that are happening, 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.

[00:44:47] Perplexity Assistant

[00:44:47] Mike Kaput: Next up, Perplexity has released Perplexity Assistant, which is a new tool that can actively perform tasks across multiple apps on your phone. Now Assistant can purportedly [00:45:00] 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.

[00:45:11] Mike Kaput: 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.

[00:45:36] Mike Kaput: 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 [00:46:00] permissions.

[00:46:01] Mike Kaput: 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?

[00:46:26] Mike Kaput: Like what is going on? I,

[00:46:28] Paul Roetzer: 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. It

[00:46:37] Mike Kaput: sounds like it is app use. Yeah.

[00:46:39] Paul Roetzer: Yeah. That sounds. Like it. I don't know. I, again, like I can be completely wrong here and perplexity could end up being, you know, IPO-ing in 18 months and end up being this massive, you know, 50 year company.

[00:46:53] Paul Roetzer: I just don't see it like so much of this is kind of like a me too and they don't have their own models, so they're Right. They're building this [00:47:00] on somebody else's models. This, this may be open eyes, APIt 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.

[00:47:09] Paul Roetzer: Um. They don't have their own models, so they're pulling through the API and they're building these, these things 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 you're not doing anything that isn't already done or someone else can't just do better because they're using their own models.

[00:47:34] Paul Roetzer: 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. 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, Really strong foundation in the future and that's super [00:48:00] differentiated.

[00:48:00] Paul Roetzer: 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. I think they did too, yeah. It was like, oh geez.

[00:48:11] Mike Kaput: Yeah.

[00:48:12] Paul Roetzer: Or like Claude introduced something last week, like citations or something. Yep. Like they were just in the middle of, it was the worst week.

[00:48:19] Mike Kaput: You're right. All right.

[00:48:22] Zapier Agents

[00:48:22] Mike Kaput: 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.

[00:48:44] Mike Kaput: So using it, you can create what 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 [00:49:00] different applications. And require no coding knowledge to set up.

[00:49:04] Mike Kaput: 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.

[00:49:29] Mike Kaput: 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.

[00:49:51] Mike Kaput: 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 [00:50:00] connections to current software.

[00:50:02] Paul Roetzer: Yeah, I would put Zapier in that category if they've got distribution. So we talk often about like differentiators can be data and distribution.

[00:50:09] Paul Roetzer: 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 used 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.

[00:50:28] Paul Roetzer: 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 CB Insights right away. 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.

[00:50:50] Paul Roetzer: They're doing something that, Other companies could emulate pretty quickly, you know, cause again, they're not building their own models here. So, but, but they're integrating it right [00:51:00] into an experience people are already familiar with that just increases the, I guess the experience you have using it.

[00:51:07] Paul Roetzer: 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. And so that's where I think like this unknown about the future of adoption of all these different things.

[00:51:23] Paul Roetzer: They're all building on the same six models. And now some are going to be building on DeepSeek 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.

[00:51:42] Paul Roetzer: 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.

[00:51:51] Mike Kaput: Right.

[00:51:52] Paul Roetzer: 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 [00:52:00] with access to my QuickBooks.

[00:52:01] Paul Roetzer: 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, we'll roll with the thing we already know and trust.

[00:52:20] Paul Roetzer: 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.

[00:52:36] Google Invests Another $1B in Anthropic

[00:52:36] Mike Kaput: Anthropic is making some waves with a couple major announcements.

[00:52:41] Mike Kaput: So first, Google has just said they are going to put an additional 1 billion investment into Anthropic that builds on their existing 2 billion dollar stake. It comes as anthropic is reportedly close to securing another 2 billion from other venture capital investors, potentially valuing them at about [00:53:00] $60 billion.

[00:53:01] Mike Kaput: Now, the company has grown very well, it sounds like, according to sources familiar with its finances. Andros 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 an interesting new technical feature called Citations for its Claude AI models.

[00:53:27] Mike Kaput: This allows Claude to ground its answers in source documents by providing detailed references to the exact sentences and passages it used. 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.

[00:53:50] Mike Kaput: Maybe they

[00:53:50] Paul Roetzer: are actually. As you were saying that, I started thinking like, hold on a second, who's really good at citations? That's what I was,

[00:53:57] Mike Kaput: I was kind of getting into like conspiracy theory in this [00:54:00] question here. I was like, well, this is something, A, Google would be super interested in, and B, I don't And B, I think even too, we talked about on our trends briefing, how much Apple's been struggling recently, with Apple intelligence.

[00:54:12] Mike Kaput: And 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?

[00:54:28] Paul Roetzer: Yeah, I don't know.

[00:54:29] Paul Roetzer: I do still think Anthropic gets acquired at some point, and I think that it's getting harder. so if you think about their valuation at 60 billion, 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.

[00:54:51] Mike Kaput: Yeah.

[00:54:51] Paul Roetzer: But Apple, Google, certainly still, you know, in the running there. yeah, I don't know. The citation thing is really interesting [00:55:00] 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 Hassabis, a couple of interviews he did last week.

[00:55:10] Paul Roetzer: 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 don't know, I do, I think Anthropic's 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 maybe they just haven't released them.

[00:55:40] Paul Roetzer: We'll talk in episode 133 about Dario Amodei's interviews. He was unusually high profile last week at Davos. He doesn't do a ton of interviews. He was all over the place. I'm doing interviews and panels and things. So I think something's coming from Anthropic. I wouldn't be shocked [00:56:00] if they don't have a new model in the next 30 to 60 days that jumps to the top of the leaderboard again.

[00:56:05] Paul Roetzer: I think they'll have more to talk about with AI agents. Like they're gonna 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, one more, you know, getting to a hundred billion.

[00:56:28] Paul Roetzer: 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, their valuation just gets too big. And they either have to IPO or, you know, 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.

[00:56:53] Davos Conversations with OpenAI CPO

[00:56:53] Mike Kaput: For our next few topics, we have a handful of conversations that came out of, the [00:57:00] 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.

[00:57:15] Mike Kaput: So, speaking at Davos, OpenAI CPO Kevin Whale outlined how OpenAI's products are rapidly advancing, with the costs of AI dropping by 99 percent over the last few years, while simultaneously becoming faster. 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.

[00:57:42] Mike Kaput: So we 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 [00:58:00] progressed from ranking as the millionth best coder in the world to just to the 175th best in just three months.

[00:58:08] Mike Kaput: He also talked about how open AI is rolling out early versions of AI agents. And he emphasized that they're taking a cautious approach, ensuring that users main 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.

[00:58:34] Mike Kaput: However, he pushed back against doomsday scenarios, arguing that like previous revolutions in 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.

[00:58:57] Mike Kaput: So Paul, there's plenty to unpack there, but that [00:59:00] 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?

[00:59:18] Paul Roetzer: Yeah, 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 Amodei's comment that it was going to be in like three to five years. Yeah, I think you're right. Yeah. Yeah. And then he said, or they asked him like by 2027, he goes, It could be sooner than that.

[00:59:37] Yeah.

[00:59:37] Paul Roetzer: so that was definitely noteworthy. Now, there are a lot of people in the AI space who do. I believe OpenAI is the number one culprit of overhyping, kind of, 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 [01:00:00] tens of billions of dollars if not trillions eventually and so they they need this hype to continue.

[01:00:08] Paul Roetzer: So, whether it's real or not, I don't know. 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 03, how quickly they went from 01 being like millionth best coder to like 175th best coder.

[01:00:27] Paul Roetzer: He did say in the interview that O4 is in training, so we don't even have full O3 yet, and they are in training in O4, 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 And they seem to be able to bring them to market way faster.

[01:00:53] Paul Roetzer: So that was of note. And then, you know, this idea of, I mean, it sounds like he's talking about superintelligence by 2027, not just [01:01:00] AGI, like where it's good at, like, most cognitive tasks are on par with human level, most cognitive tasks, but he's talking about, like, superhuman, like better than humans at everything.

[01:01:09] Paul Roetzer: So, yeah, I don't know. OpenAI's timelines definitely seem to be shrinking faster than most. And it is a, Concentrated effort on their part to get that message out. Cause 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.

[01:01:39] Paul Roetzer: so I don't know there's, there is a strategy behind what they're doing.

[01:01:45] Demis Hassabis on AI for Scientific Progress

[01:01:45] Mike Kaput: Another interview that came out of Davos was with Google 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 [01:02:00] that over 2. 5 million researchers worldwide now use AlphaFold to map proteins.

[01:02:06] Mike Kaput: 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 spin off company through DeepMind called Isomorphic Labs, that is now working to revolutionize drug discovery, combining AlphaFold with other AI models to design new medicines.

[01:02:36] Mike Kaput: He actually expects the first AI designed drugs to enter clinical trials by the end of this year. Looking ahead, Hassabis predicted we're 5 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 [01:03:00] likely requires one or two new breakthroughs that haven't happened yet.

[01:03:04] Mike Kaput: 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 overstated, not like a hype machine, but still communicating, this is going to be transformative.

[01:03:37] Mike Kaput: Like can you walk me through why he's so focused on AI for scientific progress?

[01:03:43] Paul Roetzer: 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.

[01:03:56] Paul Roetzer: there was the interview you're talking about and then I'll sprinkle in a [01:04:00] 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.

[01:04:11] Paul Roetzer: It's like literally the same exact line will come out and you find ways to say the same stuff. 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.

[01:04:28] Paul Roetzer: We lived in the PR world, so I kind of know how this game works a little bit. so yeah, a couple of notes here. I think he said a lot of interesting things built on some things we've talked about before, but a few noteworthy items. This idea of AlphaFold folded all 200 million proteins known to science.

[01:04:46] Paul Roetzer: It takes several years, on average to find the structure of a single protein. He often says, like, a PhD will spend their entire time in PhD figuring out how to fold a single protein. They figured out a full 200 million of them. It would have [01:05:00] taken a billion years of PhD time, and they just gave it free to the world.

[01:05:05] Paul Roetzer: 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, AGI? 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.

[01:05:30] Paul Roetzer: 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.

[01:05:56] Paul Roetzer: And that's the vision that DEMIS has for the world, [01:06:00] 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.

[01:06:19] Paul Roetzer: Like VO2, which again is the video generation model. Project Astra, he said, would likely 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.

[01:06:34] Paul Roetzer: 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.

[01:06:52] Paul Roetzer: That is not a reasonable solution. That's too, too hard and becomes too biased. Like, who's deciding? Like, what's misinformation? [01:07:00] 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.

[01:07:14] Paul Roetzer: AGI thought this was interesting because his definition of AGI, he said it's what they've always defined it as. Yeah, 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.

[01:07:30] Paul Roetzer: But he said we are maybe 5 to 10 years away, maybe 1 to 2 breakthroughs, but then in the next interview he said 3 to 5. 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. The open AIs of the world maybe are hyping too much, but Demis belief is five to ten years.

[01:07:54] Paul Roetzer: It's underrated and underappreciated how much society is going to change. And then in the Big [01:08:00] 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.

[01:08:16] Paul Roetzer: 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.

[01:08:35] Paul Roetzer: 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 them about scaling laws, which we talk about all the time.

[01:08:51] Paul Roetzer: 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 [01:09:00] these one to two breakthroughs gonna come from? Demis said, planning, memory, search, reasoning, creativity were the big ones. And then I thought he had this cool perspective on creativity.

[01:09:10] Paul Roetzer: It's like, 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.

[01:09:27] Paul Roetzer: 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.

[01:09:47] Paul Roetzer: 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 [01:10:00] so he said that's, we don't have that yet. 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.

[01:10:10] Paul Roetzer: 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.

[01:10:28] Paul Roetzer: 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.

[01:10:55] Paul Roetzer: We don't know yet what that looks like. I thought, oh man, like [01:11:00] 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.

[01:11:24] Paul Roetzer: 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 is kind of like, it's really impressive, probably had a bit of a headstart that they're not going to disclose in the research papers, but it is what it is.

[01:11:42] Paul Roetzer: 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 superintelligence? 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 have not, [01:12:00] as one of his favorite, books on, like, a possible future, where agents are everywhere and we've achieved superintelligence.

[01:12:08] Paul Roetzer: But he did say like, he's not going to figure this out. Like the, 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 going to be the ones that actually tell us what 20 years from now looks like.

[01:12:29] Paul Roetzer: You really need these people who can think deeply about society and humanity. And so I don't know. Yeah. I mean, obviously I'm a huge Demis fan. I listened 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.

[01:12:49] 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. Have you read them? [01:13:00] I've read a couple of them. Have you? Okay. So a really good accessible one to start with, which is one of the earlier ones.

[01:13:05] Mike Kaput: 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.

[01:13:23] Mike Kaput: What might really happen if you had limitless intelligence and abundance. It's like humans are not the main character in a lot of, a lot of things.

[01:13:32] Paul Roetzer: I may have to get a couple of the audio books. And yeah, for sure.

[01:13:35] LeCun Predicts New AI Architecture Paradigm in 5 Years

[01:13:35] Mike Kaput: All right. So one other big conversation with an AI leader that came out of Davos was with Yann LeCun, Sumedha's chief AI scientist.

[01:13:45] Mike Kaput: 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 [01:14:00] fundamental limitations that will drive the development of entirely new AI architectures.

[01:14:05] Mike Kaput: 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.

[01:14:25] Mike Kaput: 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, but points out that even our most advanced AI systems cannot even match a cat's understanding of the physical world.

[01:14:49] Mike Kaput: 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 Demis [01:15:00] 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 next.

[01:15:09] Paul Roetzer: Yeah, it definitely was echoing almost exactly what Demis said.

[01:15:13] Paul Roetzer: And Yann 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.

[01:15:39] Paul Roetzer: And I remember, I think it was in the fall. I remember listening to a Dario Amodei interview where he was talking about like the research directions at Anthropic, and 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.[01:16:00]

[01:16:00] Paul Roetzer: 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 superintelligence, Each lab has to figure out the recipe.

[01:16:22] Paul Roetzer: 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 into the multimodal aspect. And that's kind of, I think, where we're at.

[01:16:38] Paul Roetzer: 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, or 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 to see where each of [01:17:00] these, 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 DeepSeek, it's like, but how long of a lead did they really get when they figured out, is it three months?

[01:17:12] Paul Roetzer: Is it six months?

[01:17:16] AI Apps Saw $1B+ in Consumer Spending in 2024

[01:17:16] Mike Kaput: Alright, 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 percent increase from the previous year. So in this report, TechCrunch is citing research from the app intelligence provider, SensorTower.

[01:17:42] Mike Kaput: 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 [01:18:00] spikes around major releases like 01, whatever. Instead, consumer demand remained pretty consistently strong throughout the year.

[01:18:10] Mike Kaput: 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 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.

[01:18:40] Mike Kaput: So Paul, does this number surprise you at all? This rate of growth is pretty crazy.

[01:18:45] Paul Roetzer: Yeah, they're big numbers.

[01:18:46] Mike Kaput: I

[01:18:46] Paul Roetzer: mean, it's, it's going to get so hard to differentiate like AI app spending. Right. Every app is going to be AI. So, yeah. Yeah, it's it, I don't know, I always find this kind of data interesting [01:19:00] 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.

[01:19:19] Paul Roetzer: I was listening to a 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. We, I think we've touched on that at a podcast before, but like your kids are going to be interacting with AI agents in games and those agents are going to have basically 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.

[01:19:46] Paul Roetzer: 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 are. Roblox, like. Yeah, it's just going to be everywhere and we just need more people understanding that and like preparing for it. [01:20:00]

[01:20:00] 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 think we've talked about in the past.

[01:20:19] Mike Kaput: are much more targeted towards younger generations and are pretty eye opening.

[01:20:23] Paul Roetzer: 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, 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.

[01:20:41] Paul Roetzer: yeah, it's going to get a little weird.

[01:20:45] 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. we'll 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, [01:21:00] appreciate you breaking all this down for us.

[01:21:01] Paul Roetzer: 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 DeepSeek, 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.

[01:21:19] Paul Roetzer: Alright, 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. Thanks, Paul. Thanks for listening to The AI Show. Visit MarketingAIInstitute. com to continue your AI learning journey and join more than 60, 000 professionals and business leaders who have subscribed to the weekly newsletter, downloaded the AI blueprints, attended virtual and in person events, taken our online AI courses, and engaged in the Slack community.

[01:21:52] Paul Roetzer: Until next time, stay curious and explore [01:22:00] AI.

Claire Prudhomme

Claire Prudhomme is the Marketing Manager of Media and Content at the Marketing AI Institute. With a background in content marketing, video production and a deep interest in AI public policy, Claire brings a broad skill set to her role. Claire combines her skills, passion for storytelling, and dedication to lifelong learning to drive the Marketing AI Institute's mission forward.

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[The AI Show Episode 132]: OpenAI’s Operator, Stargate, The AI Literacy Project, Trump AI Executive Order, Perplexity Assistant & Zapier Agents

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Summary

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[00:05:57] Operator

[00:18:39] Stargate

[00:29:00] The AI Literacy Project

[00:40:50] Trump Actions on AI in First Week

[00:44:47] Perplexity Assistant

[00:48:22] Zapier Agents

[00:52:36] Google Invests Another $1B in Anthropic

[00:56:53] Davos Conversations with OpenAI CPO

[01:01:45] Demis Hassabis on AI for Scientific Progress

[01:13:35] LeCun Predicts New AI Architecture Paradigm in 5 Years

[01:17:16] AI Apps Saw $1B+ in Consumer Spending in 2024

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[The AI Show Episode 132]: OpenAI’s Operator, Stargate, The AI Literacy Project, Trump AI Executive Order, Perplexity Assistant & Zapier Agents

Listen Now

Watch the Video

Timestamps

Summary

Read the Transcription

[00:05:57] Operator

[00:18:39] Stargate

[00:29:00] The AI Literacy Project

[00:40:50] Trump Actions on AI in First Week

[00:44:47] Perplexity Assistant

[00:48:22] Zapier Agents

[00:52:36] Google Invests Another $1B in Anthropic

[00:56:53] Davos Conversations with OpenAI CPO

[01:01:45] Demis Hassabis on AI for Scientific Progress

[01:13:35] LeCun Predicts New AI Architecture Paradigm in 5 Years

[01:17:16] AI Apps Saw $1B+ in Consumer Spending in 2024

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