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[The AI Show Episode 151]: Anthropic CEO: AI Will Destroy 50% of Entry-Level Jobs, Veo 3’s Scary Lifelike Videos, Meta Aims to Fully Automate Ads & Perplexity’s Burning Cash

By Claire Prudhomme on June 3, 2025

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Anthropic’s CEO says AI could wipe out half of all entry-level white-collar jobs—and people are finally paying attention. We unpack why this moment feels like a tipping point, look at new data that backs it up, and talk about what needs to happen next. Plus: Meta’s AI shake-up, Miami schools go all-in on Gemini, the rise of grief bots, and AI videos that mess with your mind.

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

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Timestamps

00:00:00 — Intro

00:04:41 — Anthropic CEO: AI Could Wipe Out Half of Entry-Level White Collar Jobs

00:15:33 — How Seriously Should We Take Job Loss Warnings?

00:32:34 — We’re Not Prepared for Synthetic Content

00:39:52 — Prompt Theory

00:43:45 — Meta’s AI Restructuring

00:47:44 — Meta Plans to Automate Ads

00:50:32 — Third-Largest US School District Adopts AI

00:54:23 — Perplexity’s Financials

00:57:53 — Box State of AI Report

01:02:35 — Can AI Help Us Cope with Death?

01:08:59 — AI That Improves Itself

Summary:

AI’s Looming Threat to Entry-Level Jobs

Anthropic CEO Dario Amodei has told Axios that half of all entry-level white-collar roles could disappear within five years thanks to AI. And not just disappear — vanish nearly overnight. He says CEOs will quietly stop hiring and start replacing humans with AI agents the moment it makes business sense.

In his estimate, unemployment could spike to 10–20% as a result. And yet, few leaders are warning the public. Congress is largely uninformed. The White House is quiet about the possibility of job disruption. And workers? Mostly unaware.

Amodei, who’s helping build this tech, says companies have a “duty to be honest” about what’s coming, which is ostensibly why he decided to talk to Axios about this. 

Even so, the contradiction is jarring: in May, Anthropic unveiled Claude 4, which exhibits extremely powerful capabilities in white collar work like writing code and summarizing legal documents.

How Seriously Should We Take AI Job Loss Warnings?

We’ve heard the warnings: AI could decimate entry-level white-collar jobs within a few short years. But how seriously should we take the argument that this is happening right now? Is this really worth worrying about as urgently as some leaders would have us believe?

Recent 2025 data suggests the early stages of this disruption are underway. Unemployment for college grads has jumped to 5.8%, with technical fields like finance and computer science seeing the sharpest impacts—sectors where AI is advancing fastest. 

At the same time, companies are quietly shifting to AI-first hiring mindsets. Some are replacing entire teams of junior staff with a single AI-augmented expert. Others are skipping entry-level hires entirely, automating their tasks instead. 

But it’s not all doom and gloom. A new breed of AI-native and AI-forward companies is reimagining work from the ground up. These companies grow smarter with fewer people, enabling rapid scaling, lean teams, and creative experimentation. 

With AI in their repertoire, many young professionals are leapfrogging traditional roles—or choosing to build something entirely new. As part of our exploration into this topic, we look at the data behind these claims—and found some data of our own using OpenAI's Deep Research capabilities.

The Deep Research Prompt Paul ran: 

  • Dario Amodei, CEO of Anthropic, recently stated that AI could wipe out half of all entry-level white-collar jobs — and spike unemployment to 10-20% in the next one to five years. Can you create a research brief based on any 2025 data points that could be leading indicators that we are already entering this phase of job displacement and disruption (e.g. difficulty of recent graduates struggling to land jobs). Only use 2025 data.

We Are Not Prepared for Synthetic Content

We’re almost certainly not adequately prepared for synthetic content.

Google’s release of its incredible Veo 3 video generation model shows just how close we are to being unable to tell what’s real and what’s not online.

Released just a couple weeks ago, users are already flooding social media channels with hyper-realistic videos created using the tool.

And, while plenty of companies, notably TikTok and YouTube, are rolling out clearer labeling policies to tag content made with generative AI, the technology may be moving faster than efforts to flag it.

This episode is also brought to you by the AI for B2B Marketers Summit. Join us on Thursday, June 5th at 12 PM ET, and learn real-world strategies on how to use AI to grow better, create smarter content, build stronger customer relationships, and much more.

Thanks to our sponsors, there’s even a free ticket option. See the full lineup and register now at www.b2bsummit.ai.

Curious how AI is changing the future of work? Join SmarterX for a free, live webinar on June 25th — it’s called AI Deep Dive: Google Gemini Deep Research for Beginners. 

You’ll see a live demo of Google’s stunning Deep Research capabilities in action, learn how AI can supercharge your work, and walk away with real insights. It’s perfect for beginners and professionals alike. Register now here at this link!

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 think the class of 2025 is gonna face some different challenges in terms of these entry level jobs. I think by the time the class of 2026 merges gonna be a full blown, I don't wanna say crisis, but like is gonna be top of mind and cord economic discussions. Welcome to the Artificial Intelligence Show, the podcast that helps your business grow smarter by making AI approachable and actionable.

[00:00:26] My name is Paul Roetzer. I'm the founder and CEO of Smarter X and 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.

[00:00:48] Join us as we accelerate AI literacy for all.

[00:00:55] Welcome to episode 1 51 of the Artificial Intelligence Show. I'm your host, Paul [00:01:00] Roetzer, along with my co-host Mike Kaput, who is back with us after getting an episode off. You're right. So, just a reminder, we do the weekly drops every Tuesday, but last week we introduced the AI Answers series, which is, Cathy McPhillips and I, where we host and answer questions from our virtual events and summits.

[00:01:20] And so if you missed episode 1 51, we did have a Thursday episode last week, so you can go back and check that out. We went through, I think it was 19 or 20 questions from our audience that you can go listen to. And now Mike and I are back with our weekly edition. So, this week and not, I don't, it wasn't a crazy week of like model announcements and things like that, but man, the AI job stuff, just sort of.

[00:01:43] Took on a life of its own last week, I feel like. Yeah. so we're going to, we're gonna dig more into the impact of AI on jobs because it seems like it's really crossing over now into mainstream conversation as we're gonna, you know, get into a lot of that and some [00:02:00] really good recent articles that came up.

[00:02:02] So this episode is brought to us by a new webinar that we talked about actually, I don't know, a week or two ago, shared that we were gonna do an AI deep dive where I'm gonna go through Google Gemini Deep research for beginners. So this webinar is now live to register for, it's coming up June 25th.

[00:02:19] That is gonna be a free session through Smart Rx. You'll see a live demo of Google Google's deep research capabilities and action show you how you can supercharge your work and walk away with real insights. This is, ideal for beginners. So if you're, if you're really familiar with deep research from Google and or OpenAI, you know, you might learn a few things.

[00:02:40] might just be interested in the topic, how that, I'm gonna kinda walk through with the deep research project that, that I ran. But if you haven't used deep research yet, which, you know, having asked this question many times at conferences, there are very few executives and professionals who I've seen raise their hand say they're doing this.

[00:02:58] So that was the whole idea here is let's [00:03:00] show how to do this because Mike and I are both convinced this is an in, in incredible value multiplier for professionals who really know how to use these tools. So we're gonna go through that. Again, it's ai, deep dive, Google Gemini, deep research for beginners.

[00:03:14] You can go to smarter x.ai and click on education. And then, just click on the Google Deep Research webinar and we will also add the link to that in show notes. So again, that is coming up June 25th. I think at noon would, when is when it would be live? Let's usually when we do our webinars. Yeah.

[00:03:32] Alright. And then the second, big thing happening this week is the AI for B2B Marketer Summit presented by Intercept. So this is, one of marketing AI institutes it's virtual events. We do three virtual summits. as of right now, portfolio kind of keeps expanding, but this is coming up Thursday, June 5th, from 12 to 5:00 PM Eastern Time.

[00:03:53] It is packed with incredible sessions from top B2B marketing experts. You'll learn real world strategies to use AI to grow [00:04:00] better, create smarter content, build stronger customer relationships, and much more. And thanks to Intercept there is a free ticket option. You can see the full lineup. And register now at B2B summit.ai.

[00:04:13] Again, that is B, the number two B Summit ai. You can also under Marketing Institute, if you're on that site, just go under events and it's listed there as well. Okay. So let's dive into the topic that everyone seemed to be talking about, including when I was at like parties with friends in the last week.

[00:04:33] Yeah, right. Just like every, it was crazy. Like this is, this actually seemed to just hit the mainstream. I don't, I don't know. So yeah, let's dig into, Dario Am. 

[00:04:41] Anthropic CEO: AI Could Wipe Out Half of Entry-Level White Collar Jobs

[00:04:41] Mike Kaput: Alright, Paul. So yeah, the talk of the town is AI's impact on jobs. This is really kind of breaking containment here, and a big reason for that is that we just had a report this week that Anthropic, CEO, Dario Amedee, went and told Axios that half of all entry level white [00:05:00] collar roles could disappear within five years, thanks to ai and not just disappear, but basically he thinks vanish at some point overnight.

[00:05:10] He says CEOs will quietly stop hiring and start replacing humans with AI agents the moment it makes business sense. And in his estimate, unemployment could spike to 10 to 20% as a result. And yet he says, few leaders are warning the public. Congress is largely uninformed or unwilling to talk about this.

[00:05:33] And the White House is very quiet, not about ai, but about the possibility of job disruption. Not to mention many, many workers who are kind of outside the AI bubble seem to be pretty unaware that this could be happening. So Amadei, who is of course help building this technology says companies have a duty to be honest about what's coming, which is I guess why he decided to talk to Axios [00:06:00] about this in a very frank way.

[00:06:02] However, even so that contradiction is a bit jarring in just a couple weeks ago, we got Claude four, which exhibits very, very powerful capabilities in white collar work, like writing code or doing, summarization of legal documents. So Paul, maybe walk us through kind of what's going on here. AADE is building this stuff, but also saying that it could have this.

[00:06:26] Monumental negative impact on entry level work. It's not the only warning we're getting right now. There's two leaders at LinkedIn, they're head of economics in the Americas, and their Chief Economic Opportunity Officer, both of them published recent articles about AI's threat to entry level jobs.

[00:06:43] Specifically what do we need to be paying attention to here? 

[00:06:49] Paul Roetzer: So, as I was saying, kind of at the open, I do feel like this, for whatever reason him saying this just sort of caught the attention of everyone in, in mainly in the mainstream [00:07:00] media. I put this on LinkedIn, so we're recording this on Monday, June 2nd.

[00:07:05] This will drop on Tuesday, June 3rd. So I put this on LinkedIn five days ago, so it would've been like Wednesday or something I think when this came out. A a, a normal LinkedIn post for me will get five to 10,000 impressions. As of this morning, this post is at 151,000 impressions. Oh, wow. So, and like the comments within the thread are, are super productive.

[00:07:28] Like, I was actually super, like really impressed that people were being very levelheaded and having some disagreements, but really good dialogue. So there's, I don't know how many comments. There were two, two hundred and seventy six comments and 71 reposts. And so this is far beyond the usual like AI bubble of like my close network of people that always talk about ai.

[00:07:50] This superseded that. This was a lot of people that I don't usually see in the comment threads posting thoughts and questions and concerns. So it [00:08:00] just feels that for some reason him saying this, just sort of moved the dialogue forward, which I see is a very positive thing. Obviously on this show for a, a long time now, we've been kind of pushing.

[00:08:12] This says, something that needed to be talked about way more. when I, when I saw it, I'll come back to this research, but I like immediately went and like ran a deep research project to try and see what was going on. you know, if, if these things he was saying were actually starting to happen, because my personal theory, my hypothesis is that we will start to see data emerge through the summer and into the fall that shows AI is having a clear impact on jobs that the quiet AI layoffs we've been talking about are gonna start to compound and become more obvious what's actually happening.

[00:08:48] And I think that this will get accelerated because next generation models are coming. We will get GPT five at some point, likely this summer, I'm assuming, or early into the fall. We'll get Gemini three at some point this year. [00:09:00] Elon Musk is hyping up the next version of Grok, which is, I assume is gonna be Grok four.

[00:09:06] so these new models are gonna emerge. They're gonna start to accelerate the impact across different industries. as we discussed in episode 1 49, you can look at the total addressable market by salary of professions, and you can actually start to get a gauge of where the investments are gonna go.

[00:09:25] And then my hypothesis continues into next year, and I think that that's when we start to really see the disruption. So I think the class of 2025 is gonna face some different challenges in terms of these entry level jobs. I think by the time the class of 2026 emerges in May of 2026, it's gonna be a full-blown, I don't wanna say crisis, but like I.

[00:09:50] Is gonna be top of mind and core economic discussions. What we have to keep in mind is May of 2026 is right in the midst of [00:10:00] the start of midterm elections in the United States. . So for any international listeners we may have aren't familiar with how the US government works, US Congress is the leg legislative branch of the government.

[00:10:11] It's composed of the two chambers. The House of Representatives and the Senate Congressional elections determine, represents from representatives from the states and the federal government, and then which political party will hold majority in each chamber for the next two years. congressional elections happen every two years, at that time, one third of the Senate and every seat in the house is up for reelection.

[00:10:33] And so the midterm elections will take place November of 2026. So I think that this becomes a major topic for the midterms and as Mike, you and I talked about for this presidential election cycle in 2024 in the United States. It was not discussed at all. Like we just kept saying, where's, where's the conversation about ai?

[00:10:54] And then as soon as the new administration came in day one, it was now a topic. [00:11:00] So, I I think that it's still largely being ignored, but I don't think that that's gonna sustain for long. And I can just like qualitatively again, in the last week, I've been at multiple functions with family and friends where I have parents of high school and college aids kids asking me unprompted, like, what should we be doing?

[00:11:25] . What my, my son's majoring in computer science, is that viable? you know, they're thinking about going to business. What should they like? They're, you're now getting these way more educated questions about the impact this stuff is gonna have. And so I. I think that that started to cross over.

[00:11:44] And then if the economy keeps struggling, if tariffs and inflation continue to happen, and then you layer in an unanticipated unemployment number, or the bigger concern, I actually honestly have right now, and I haven't had a chance to dig into this data deeply, [00:12:00] is underemployment. So if you're not familiar with the concept of underemployment, that's when someone is working at a job that doesn't fully utilize their skills, education or experience.

[00:12:10] So maybe they're working part-time and they actually want full-time employment, or they're taking a job at, at a retail store when they came out with a computer science degree. So it doesn't show up in the unemployment numbers because they are employed, but they can't get the job that they want or they can't get the full employment that they want.

[00:12:30] And so my guess is that's gonna start to be a much bigger issue going into next year as well. And so, I don't know, I just feel like, We may have hit that tipping point where this really starts to become a concern for people, they start taking a far greater interest in it. . 

[00:12:48] Mike Kaput: And 

[00:12:48] Paul Roetzer: if constituents across, you know, United States start taking greater interest, then their Congress and Senate have to start taking a greater interest.

[00:12:56] And if, if jobs truly start being impacted [00:13:00] unemployment and underemployment going into the 2026 election cycle, it has to then become a major political issue. And I don't know what that means yet. Like, I, you know, I think, and I do think I mentioned this a couple, episodes ago. I think the church is gonna get involved.

[00:13:17] . I, I, I fully anticipate, 

[00:13:18] so I actually saw something this morning, about a, a sect of the church that, uh, sent a letter, I think it might've been to the Pope. no, actually it was to the Trump administration basically vocalizing that they wanna slow AI down. Oh, wow. So it's just, it's gonna.

[00:13:37] It's gonna cross over into a true societal issue very soon. And I, and that could go a couple different ways. 

[00:13:44] Mike Kaput: So we've talked about before that we need to have the conversation around AI's impact on jobs, part of AM day's thing. Whether you agree with it or not, was him kind of saying, we need to be a lot more frank about this.

[00:13:59] Axios [00:14:00] published a great follow up piece about leadership in the age of AI and what they're doing as a company and how they are having more frank conversations with their own employees about what AI could do and how they're going to move forward. But a lot of this is just people still saying like, let's talk more about it, which is great.

[00:14:19] But I guess the question that follows is, what should we actually do about it? 

[00:14:23] Paul Roetzer: Yeah. I, you know, I think, individually, we, we have to start looking at our own industries, looking at our own companies, being more proactive, thinking about. You know, think about our kids, what their schools are teaching, and if you need to take on more responsibility, prepare your kids, which again is like, I'm lucky.

[00:14:47] Our, our, my wife and I are lucky. Our, our kids go to an incredible school. but even they're not teaching ai, right? They're not, not allowing it, but they're not teaching it. And so I'm very much looking at this like, how do I be [00:15:00] proactive in actually preparing, you know, our kids. I was at a friend's house last night having a conversation.

[00:15:07] you know, the, his nephew is in, I think he's in his freshman year, maybe sophomore year. And it's just like straight up having this conversation, like, okay, like what is, what's the career path look like? What are the majors you're interested in? How would you layer a ar ai over those things? So I think it's a mix of being proactive, individually and then like as a community starting to, to focus on like more of what we can do.

[00:15:33] How Seriously Should We Take Job Loss Warnings?

[00:15:33] Mike Kaput: Okay, so we're kind of talking here about, you know, ADE's comments and some of the kind of things, you know, people at LinkedIn are saying about all this stuff. But our second big topic this week is kind of closely related to this first one because while we're seeing all these warnings come from AI leaders and others who are kind of employment experts, there's plenty of weight to those arguments.

[00:15:58] We're seeing it in our [00:16:00] own industry. But I guess the bigger question here is how seriously should we be taking the argument that all this is happening right now, like really urgently, like I think on a long enough timeline, we agree there's gonna be major changes to how jobs work in the age of ai, but.

[00:16:18] Is this really worth worrying about as urgently as some of these leaders would have us believe? That's kind of the next question that follows from this. And we wanted to look at a few different proof points that we're seeing at the moment in order to maybe stress test or kick the tires on the assumptions behind some of these job loss warnings.

[00:16:36] Because, you know, it gets headlines when AM day says half the entry level jobs are going away, but why do we believe that? So Paul, as this we get into the second topic, I wanted to ask you to give us maybe a sense of what we're seeing here that's supporting this idea. 

[00:16:52] Paul Roetzer: Yeah, so there was a couple of things that, articles that sort of surfaced right around this time that caught our attention.

[00:16:59] [00:17:00] So one was from the Chief Economic Opportunity Officer at LinkedIn, Anish Raman. And I'm just, I'll call it a couple excerpts from this and we'll put the link into the article. But it was a New York Times op-ed piece on, It says, I'm a LinkedIn executive. I see the bottom rung of the career ladder breaking.

[00:17:17] So in this one it says, breaking first is the bottom rung or the clear, clear career ladder. In tech, advanced coding tools are creeping into the tasks of writing simple code and debugging the way junior developers gain experience In law firms, junior paralegals and first year associates who once cut their teeth on document review are handing weeks of work over to AI tools to complete in a matter of hours.

[00:17:39] And across retailers, AI chat bots and automated customer service tools are taking on duties Once assigned to young associates continued these changes coincide with the shift appearing in the latest employment numbers. The unemployment rate for college grads has risen 30% since September, 2022, compared with an 18% for all workers.[00:18:00] 

[00:18:00] And while LinkedIn's Workforce Confidence Index a measure of job and career confidence across nearly 500,000 professionals is hitting new lows and general uncertainty. Members of gener, generation Z are more pessimistic about their futures than any other age group. Meanwhile, in the recent survey, over 3000 executives on LinkedIn at the VP level or higher, 63% agreed that AI will eventually take on some of the mundane tasks currently allocated to entry level employees continued.

[00:18:31] Their research suggests that professionals with more advanced degrees are more likely to see their jobs disrupted than those without. While the technology sector is feeling the first wave of change reflecting AI's mass adoption in this field. The erosion of traditional entry-level tasks is expected to play out in fields like finance, travel, food, and professional services.

[00:18:51] So that was the first one, Mike. 'cause like who has better data than LinkedIn when it comes to this stuff. And then Kevin Rus, had a, a great [00:19:00] article and I'll, I'll go, go through a couple excerpts of this one. So he wrote this month, millions of young people will graduate from college and look for work in industries that have little use for their skills, view them as expensive and expendable and are rapidly phasing out their jobs in favor of artificial intelligence.

[00:19:17] That is the troubling conclusion of my conversations over the past several months with economists, corporate executives and young job seekers, many of whom pointed to an emerging crisis for entry-level workers. That appears to be fueled at least in part by rapid advances in AI capabilities. I'll go through a couple more excerpts here, but I would highly recommend reading this whole article.

[00:19:38] It's, it's very good. he says, you can see hints of this in the economic data on unemployment for recent college graduates has jumped to an unusually high 5.8% in recent months. And the Federal Reserve Bank of New York recently warned that employment situation for these workers had deteriorated noticeably.

[00:19:56] he, he quotes, Oxford economics, report that [00:20:00] says there are signs that positions are being displaced by AI at higher rates. he goes on to say, but I'm convinced that what's showing up in the economic data is only the tip of the iceberg in an inter in interview after interview, I'm hearing that firms are making rapid progress toward automating entry level work.

[00:20:14] . 

[00:20:14] Paul Roetzer: And that AI companies are racing to build virtual workers that replace junior employees. One tech executive told him his company had stopped hiring anything below an L five software engineer. So just a grading level, mid-level. it goes on to say, this is, something, this is a quote from Molly Kinder at Brookings Institution.

[00:20:33] This is something I'm hearing about left and right. who this Molly studies the impact of AI on workers. Employers are saying these tools are so good that I no longer need marketing analysts, financial analysts, and research assistance. . now Kevin did say if there's a silver lining for recent grads, it's that it's, at least for some of them, the threat of AI replacements seems to be lighting a useful kind of fire.

[00:20:56] Some young workers that he spoke to are using their experience with the AI to vault [00:21:00] themselves ahead of their senior colleagues and others that are steering, more or clear of traditional ladder climbing. So that actually goes back to Mike on a recent podcast we talked about, how these, like young workers are gonna show up and be like, why are you, why are you doing it this way?

[00:21:15] Right? Like, why, right? Why are you like spending two weeks on that thing? and then I'll just share a quick anecdote. Like I put this on LinkedIn on Sunday morning. I just like woke up and I, like, we had, we had meetings on Friday at the company and we were talking about like our ideal customer profiles and customer journeys and you know, developing customer journey maps and personas and all these things.

[00:21:37] And it was like overwhelming amount of work that probably needed to happen and it's like, ah, who's got time to like do this? And so I literally just like pulled out my, I think I was using CO CEO and my, my custom GPTI built and I'm just like, cup of coffee. I'm like, ah, can you help me do this? And it just, because it already knows in its system instructions, our revenue model, it knows [00:22:00] our audiences, like it knows all those things.

[00:22:02] It's trained on it. It just started spitting out these ICPs and I was like, oh God, these are really good. And so I just kept like, so I gave it the list of the eight that I thought of and then it would just build these things out and then it build out customer journeys. And again, it was just this representation of.

[00:22:17] Once you understand what these things are capable of, you just look at work differently. And I think I said in the LinkedIn post, you know, I owned a marketing agency for 16 years. People paid us to do these exact things. And if a company had come to me and I was still running an agency, six months ago, a year ago, I, that would've been $25,000 minim I probably would've priced it on a per ICP basis.

[00:22:40] I would've probably said 2,500 to 3000 per ICP times eight. Like, that's how we would do pricing. and so it was easily that, and it was probably easily 50 plus hours of work. And if we were quoting it probably would've been like, you know, 2, 3, 4 weeks of work because some senior strategist gonna have to do the work.

[00:22:59] Some other [00:23:00] person above them was gonna probably have to review and approve it. So the whole thing just changed. And then under an hour I built eight ICPs that are now gonna be like the foundation of our team's conversation to take them and edit them and build on them. So I I don't know Mike, I think this goes like, yes, there's this disruption that's gonna happen, I think at the entry level for sure.

[00:23:19] I think, you know, this goes to how we talk about building companies. So anybody listening to the show heard me say like, AI Forward is sort of like how we define these companies. but Jeremiah o Yang was actually shared a post on LinkedIn last week where he was sort of, he had heard the AI Forward thing at an event in Silicon Valley.

[00:23:39] And so Jeremiah had tagged, I think you and I may be in that and tagged the podcast. Yeah. And so I was like adding some context for him to where like the origin of that came from. And so I thought I would add this to this 'cause I think this is an interesting part of the conversation. I. Y if you have an AI native company, which is what I consider like a startup, like we're just gonna build a smarter version of a company from the ground up, right?

[00:23:59] It's [00:24:00] gonna require fewer people. There's never been a better time to do that. It's like what we're doing at Smart Rx. It's, you know, we can just be really smart with like the people we bring in, in fusion of ai. We don't have to lay anybody off. We actually like can bring them in. We can pay them more than normal, we can do all these things, give 'em more vacation days because we're able to do that from the ground up.

[00:24:19] We're able to just build the company and my hope is we enter this sort of golden age of entrepreneurship and that offsets some of the job losses. So, you know, if we've double our team, the size of our team in the last like 30, 45 days, and we're still adding more people, so we're going to be a growth engine for the economy in a small way.

[00:24:37] Like we're gonna do our part to like build a company and make a difference, but we're gonna do it with a fraction of the total employees we would've needed. You know, years ago. But then what we're seeing happening, where these jobs start getting impacted is the AI emergent organization. . So these is like the traditional organizations that are trying to infuse ai.

[00:24:57] now they're gonna require fewer people to [00:25:00] grow. So if you've got an existing company, say it's a hundred people, a thousand people, 10,000 people, whatever, and you start infusing AI to build a smarter company, if the demand for their products and services remains flat or modest, they're gonna cut the workforce.

[00:25:13] Like, if, if you're not growing, even with ai, you don't need as many people. Like we know that equation, right? If you grow, then you can grow without having to hire as many people as you would have. So we had a quote from Financial Times, Janet Tru Ha, who's the global Chief executive of ey. she obviously said at a Milken Institute annual conference, that, her firm would not cut jobs in response to ai but could do more with less.

[00:25:40] She said, quote, I like to think we can double in size with the workforce we have today. So there you go. I mean, like, they're just telling you like, we're not gonna hire as many people. Yeah. So, and then I'll, you know, my, my other thought here was I did, before I read the Kevin Rus article, I actually wanted to see like, is this happening?

[00:25:57] Like, can we identify some [00:26:00] indicators that we are actually starting to already enter this job loss period. And so I gave a prompt, and we'll drop this in the show notes, but the prompt was, Daria Ade, CEO of philanthropic recently stated that AI could wipe out half of all entry white collar jobs and spike unemployment to 10 to 20% in the next one to five years.

[00:26:17] Can you re create a research brief based on any 2025 data points that could be leading indicators? We are already entering the phase of job displacement and disruption. For example, difficulty of recent graduates struggling to land jobs only use 2025 data. So that was the prompt I gave. I think I used open Eyes deep research for that one.

[00:26:38] I'm not gonna go into all the details, but here's, here's what the conclusion said. while de definitive pronouncements about the full realization of ADE's predictions are premature. The 2025 evidence strongly suggests the initial phase of this predicted disruption is underway. This underscores the urgency for all stakeholders, including educational institutions, policymakers, businesses, and [00:27:00] individuals preparing the intent of the workforce to acknowledge these early signals, which Mike goes back to your question about like, what do we do?

[00:27:05] Mike Kaput: Yep. 

[00:27:06] Paul Roetzer: proactive strategies for workforce adaptation, comprehensive reskilling and upskilling initiatives focused on AI literacy and human AI collaboration, and a fundamental rethinking of career paths for new entrants into an AI powered economy are becoming increasingly critical. The 2025 data does not offer a complete map of the future, but it does provide clear evidence-based call for proactive engagement with the transformative potential of AI on the world of work.

[00:27:34] So now Mike, this is like literally game time decision by Mike and I, So I've been working on this thing. Like I'm really frustrated honestly with the lack of, advancement being made to prepare for this. I've prepare for the future work, future of education. I am grateful for all the people, specifically in higher education who reach out to me every week asking what else can be done.

[00:27:59] there are a [00:28:00] lot of people who wanna make a difference and wanna think this thing through. So like a, about a year ago I started working on this idea to build these like AI impact summits where we would try and actually project out the impact we would bring in economists and philosophers and business leaders and educational leaders and government leaders, and kind of bring people together to start having like, think tanks around this stuff.

[00:28:22] And so I've been sitting on this idea for a while. and then I was kind of ready to just sort of punt it into 2026. 'cause there's a lot going on. And then honestly, like the last two weeks of this podcast has like, kind of pushed me to it, to a point where it's like, okay, we have to do something. We can't just keep talking about this stuff on this podcast with no, no hope of like, well, okay, we, we want to help.

[00:28:48] and I feel that from our audience. Like people are like, okay, we get it. Like job, we get messed up. Like what do we do? So what, what I decided to do this morning, I mean, literally like I, [00:29:00] you guys are okay with this. Like, I'm just gonna say this. So what we're gonna do is this idea I have for these sort of the smarter XI impact Summit on the future of work and education, we're gonna put up a, a, an interest list.

[00:29:13] So I'm not gonna make any promises that this event is coming, you know, this summer, this fall, I've got a million things we're working on, but I think this is incredibly important as part of our AI literacy project, as part of like our, our bigger mission to try and, you know, have AI have a positive impact on the economy and society.

[00:29:33] So we're gonna put up an interest list and what I would ask here is, it just provides a little bit of information about the event series. Like what we're thinking about is doing this series that would be geographically diverse. It would, it would be an ongoing series of one day events where we bring people together to sort of explore, discuss, and debate these pressing AI topics with a big focus on jobs and a big focus on education.

[00:29:56] and so there's gonna be a simple form you can [00:30:00] just express interest of, you know, kind of organization, job title, geographically, where you are, and then just your interest in attending it, sponsoring it, hosting, co-hosting, speaking, receiving updates. It's a super simple form that I literally threw together on Google this morning.

[00:30:16] and this information will help me kind of figure out how to prioritize this. And if the interest is high, we will, we will accelerate that, that planning. I wanna do this. I've wanted to do this for a while and I think it's really important. I haven't honestly like formalized the model exactly in my head.

[00:30:38] I have a vision of what this needs to be, but, we're just at the formative stage right now, so if it's something that's of interest to you. Check out the show notes, we will drop a link to that form. And then, like I said, just simple, we're not gonna market you. This is not like a marketing database thing.

[00:30:53] This is if you're interested in this. that's all we're gonna use this list for, is to [00:31:00] communicate with you specifically about this. If you choose to Optum to something else that's on you. But this is purely just to gather some interest and gauge. You know, if, when, where, those are all the things that I'm kind of thinking about, but I just feel like we have to do more, Mike, 

[00:31:14] Mike Kaput: honestly, that's, that's awesome.

[00:31:15] I couldn't agree more, especially, you know, I'm glad we're talking about it more, but yeah, I couldn't be more important to accelerate actually finding solutions because, you know, I've talked about, I just don't, anytime someone's like, well, okay, think about UBI or this other thing, or, you know, it's possible interesting stuff, but none, it just seems like way, way, way far in the future to me.

[00:31:35] Or illogical or implausible maybe. So real solutions are neat. 

[00:31:40] Paul Roetzer: Yeah. And like the qualitative stuff I was referring to earlier, like that's, you know, some, I'm with my high school buddies last night and we're just kind of catching up and I'm explaining what's going on. They're just like, a couple were like, I had no idea.

[00:31:51] Like, I didn't know it was this far along and, well, what's happening? Like, what are people gonna do? How does, how does it get solved if people don't work anymore? I was like, [00:32:00] UBI like that. That's the lab's answer to everything. They don't tell you what that is or how it works and. Yeah, it's just, I don't feel like anybody is presenting true ideas.

[00:32:09] And I'm not saying we're gonna be the one to figure it out, but if we have to be part of accelerating the conversation around it, then right then that's what we need to do. And I feel like right now, that's the best role we can play in this, is just try and get people together and drive this conversation forward and not like behind these closed doors.

[00:32:26] Like maybe these conversations are happening in government and we're just not being told about it, but we need to get this like kind of shine a light on this. 

[00:32:34] Synthetic Content

[00:32:34] Mike Kaput: Alright, for our third big topic this week, we are talking about synthetic content because we are almost certainly not adequately prepared for the flood of AI generated content that we're now seeing.

[00:32:49] Thanks to things like Google's release of its incredible VO three video generation model, which honestly shows us just how close we are to being unable to tell [00:33:00] what's real and what's not online. So not a new problem, but is definitely been accelerated by the fact that VO three, which was released just a couple of weeks ago, already has users using the tool to flood social media channels with hyper-realistic videos.

[00:33:16] They're incredible. We're gonna actually show examples of them in a later segment. you should definitely check them out. But while plenty of companies, notably TikTok and YouTube are rolling out some policies to tag content made with ai, the technology may be moving faster than efforts to flag it. Now, Paul, I know you posted the following on this topic.

[00:33:39] You said, I hope there is a plan for X, the social media platform as well as Facebook, Instagram, YouTube, et cetera. To clearly mark AI generated videos like those from vo, I assume there is a way to know through Google DeepMind synth id, it seems irresponsible at this point to not publicly tag them on social media.

[00:33:59] [00:34:00] So Paul, how bad is this problem right now thanks to VO three? 

[00:34:05] Paul Roetzer: I'm, I'm not sure how bad it is. I don't, so when I, when I started seeing the VO three videos, I was like, like, there, there's no way people are gonna have any clue. This is ai, right? Like, and so I live, I would say like the vast majority of my time on social media is spent on X, which is where I curate the vast majority of my AI news.

[00:34:26] And on LinkedIn, which is where I spend most of my time, like in engaging and sharing. I do not spend much time at all on like, Instagram, Facebook, TikTok, so I'm not sure what's happening there. I just know. From a Facebook and Instagram perspective, my guess is the audience who is spending a lot of time specifically on Facebook, is probably not the audience that, that largely comprehends what's happening in video generation [00:35:00] right now.

[00:35:00] Right. And that these mo models are capable of doing what we're seeing with vo. so I was just curious. So I just like started bouncing around. I was like, well, what are the different platforms doing? So like TikTok I went to, and we'll put the links and you can go research this yourself. they have auto labeling.

[00:35:16] So it says TikTok may automatically apply AI generate label. Because I was also seeing people saying things like, I think it was on X where it's like, yeah, I posted some on TikTok and they took it down and I can't even challenge it. . Like, like the, if TikTok decides it's AI generated, you're just cooked.

[00:35:30] Like you can't go back and change it. So they will automatically label something if it meets their criteria. Yeah. So this may happen when a creator uses TikTok AI effects or uploads ai, generate content that has content credentials attached to it, a technology from the Coalition for Content Providence and Authenticity, C two pa, which I think Mike, we talked about in 2024 when that came out.

[00:35:53] So that is one thing. except when you look into the, that organization, which was created by [00:36:00] Microsoft and Adobe in 2021, it doesn't appear to be very many companies participating in it. None of the AI labs are listed. It's just Adobe Arm, Intel, Microsoft, and True Pick. I don't, I dunno what a true pick is.

[00:36:12] So it was supposed to be something to like detect deep fakes and alert if it's synthetic media, but. Best I can tell it's not like widely adopted or it doesn't have a big impact here because again, the ones building these things are like, you know, runway and OpenAI and Google, and like, they're not, they're not listed here.

[00:36:31] so tiktoks, seems to have a, you know, you're supposed to tag it yourself, but if you don't tag it, they might. And if they're the ones that tag it, you're in trouble. YouTube, which I can't understand this one because they don't say anything about that I could find about using. So again, YouTube's owned by Google.

[00:36:48] You would think they would have the c ID technology from DeepMind baked right into YouTube, right? Maybe they do, but it's not obvious on their support pages. So again, YouTube sort of relies on [00:37:00] creators to tag the content. It goes through and explains to you how to do this. And the trouble you'll get in if you don't disclose it, they, they say a content of viewer could easily mistake.

[00:37:09] So the things you're supposed to tag as content of viewer could easily mistake for real person, place, scene, or event. That is made with altered or synthetic media, including generative ai. we're not requiring creators to disclose content that is clearly unrealistic, animated, or has these special effects.

[00:37:26] The one that I, again, I'm most familiar with would be like X 'cause that's where all these VO two or VO three videos are appearing. and it all there says is like they have an inauthentic content thing. You may not share it in inauthentic content on X, which is funny 'cause Elon Musk is probably like the biggest sharer of this stuff, which, so then they call like synthetic and manipulated media and it kind of goes in again, like you gotta tag this stuff.

[00:37:50] And then meta, I'll put the link in there as well. they rely on people to tag their stuff. They don't tag images or require you to tag images. They [00:38:00] basically say, examples would be like a video appears realistic of a group of people walking around an outdoor market. So they, you're not, they're all kind of saying the same things.

[00:38:07] And then I. The Google DeepMind sit id Mike, which we talked about on a recent episode, 'cause they released updated version of this. So Google has the ability to insert these watermarks in things created by DeepMind technology, but to have that widespread, you would need like a partnership with X to, to kind of pass that information through.

[00:38:28] Right now it looks like the solution on CTH ID is if you come across a video on X that you're not sure if it's real. You would have to like, take that video, give it to CTH id, and then it could then tell you whether it thinks it's real or not. Right. So it it just seems like we're just not there. Like the organizations are mentioning it in their, you know, their terms of use and their guidance for creators.

[00:38:54] But I. I don't know when, like, I'm gonna be on X and see a video and be like, I mean, [00:39:00] I like, I literally double check everything out, even from like verified sources because it's like, well, they might be feeling fooled, so I just assume everything's fake now. Like even we had the drone, you know, the Ukraine Russia drone attack this weekend.

[00:39:14] First time I saw that on XI was like, that's fake. Like, I just assumed it was right. And so I went and found like a legitimate media source. I'm like, oh man, that I actually did that. Like that wasn't, so yeah, I've kind of arrived at that point where I just doubt everything until I verify it's real. 

[00:39:30] Mike Kaput: And especially too when we've talked about this, for several years now, that your average person also is very ill-equipped to even understand what's possible.

[00:39:42] And that's never been more important or more true than today because VO three is just jaw dropping. It's wild.

[00:39:52] Prompt Theory

So on that point, as we dive into rapid fire, our first item is we actually wanted to show off a couple, viral videos that are [00:40:00] created using the VO three video generation tool. And they're kind of going viral because they also have a, a quirky little AI focused, story behind them, which is that these are very, very lifelike videos.

[00:40:14] They're being for shared in the form of some clips on X. And then there's some longer videos on YouTube, and they're all under this theme that they call it in the titles of the Prompt Theory. And what this is, is these videos are created through VO three prompts, and they tell these stories of. AI characters who basically are like refusing to believe that they're AI generated.

[00:40:38] So there's kind of a, a kind of blow your mind aspect to this as well, going down the rabbit hole of like what it means to be AI generated. And it's really, really eye-opening to see this put together in this way. So Paul, before I get your thoughts on this, we're gonna kind of take a real quick look at one of these clips.

[00:40:58] From the prompt [00:41:00] theory, 

[00:41:00] Video: a girl told me we're made of prompts. Like, seriously, dude, you're saying the only thing standing between me and a billion dollars is some random text? Honestly, the biggest red flag is when the guy believes in the prompt theory. Like, really? We came from prompts. Wake up man. You wanna convince me that this perfect creation behind me is the result of ones and zeros, a binary code and nothing more.

[00:41:23] It makes no sense. We're not bros. 

[00:41:25] Paul Roetzer: We're not bros. Yeah. The, I mean, this stuff is so crazy. When I first saw a short clip of this on Twitter, x, it was one of those like dystopian moments where you just, I watched it like three times and then the clips get like progressively more. I don't even know the right word here.

[00:41:48] disturbing. I guess like, right. Yeah. So if, if you're listening, to, to the podcast, it's hard to like understand the true impact of these things if you don't like, see the video. So either go click on the link or [00:42:00] flip over to our YouTube channel and watch it. they are indistinguishable from reality, so it truly looks like it's a comedian or it's a husband, you know, talking to his dying wife.

[00:42:12] Like, it's, all those things look completely real. And then, just this sort of bizarre, them being aware, they're just prompts and like asking the prompter to give. I don't know, like, it was, it just affected me in a weird way when I saw it and I was trying to like process it because it just, it's on multiple levels.

[00:42:36] You're trying to deal with this, that the video looks so real, the audio sounds so real. . And then that it's creating. This whole prompt theory with a prompter that's almost like a godlike figure that they're like asking for the prompter to prompt them something in their life. Like, yeah, it is.

[00:42:54] It's so messed up. Honestly. 

[00:42:57] Mike Kaput: It gets really unnerving. Yeah, that's a good way to [00:43:00] put it. It's like instead of praying, they're basically saying, Hey, can you prompt this for me to addressing kind of offscreen, you know? Yes. The viewer almost, right. 

[00:43:08] Paul Roetzer: Yeah, and when I mentioned earlier, like the church is gonna start to get much more involved, right?

[00:43:13] This is the kind of thing where if you're like the church, these are the kinds of things that are red flags where it's like, whoa, hold on a second. Like people are gonna start believing like crazy things and. I don't dunno. That's what I said. This is like a deep one. It goes multiple layers and you just kind of keep peeling it back and thinking about how messed up it is.

[00:43:32] But yeah, if you haven't watched 'em, we'll we'll drop the nine minute YouTube or the Yeah, the link to the nine minute video. It is it me with you? Yeah. Yeah. Yeah. 

[00:43:45] Meta’s AI Restructuring

[00:43:45] Mike Kaput: All right. Our next big topic in rapid fire, Paul, is that meta is shaking up its AI division to keep pace with rivals like OpenAI, Google and China's deep seek.

[00:43:57] So this past week meta split its [00:44:00] generative AI efforts into two new teams. One is focused on AI products like Meta Assistant and Instagram features the other on foundational research, including LAMA models and reasoning systems. So from some reporting by Axios, they said quote in an internal memo, sent Tuesday and seen by Axios chief product officer Chris Cro Cox laid out the new structure, which we'll see efforts divided into two AI teams, an AI products team, headed by Connor Hayes and an AI Founda AGI Foundations unit co-led by Ahmed Al and Amir Frankl.

[00:44:36] Now Meta's AI Research Unit fair apparently remains separate from this new structure. The Axios also said No executives are leaving as part of the changes, nor are any jobs being cut at the moment. This all comes after months of internal issues. At Meta related to ai, there are reports of burnout, infighting, lack of focus.

[00:44:58] They've been stumbling. [00:45:00] LAMA Four's release was delayed. There was a leaderboard controversy we talked about when they basically were trying to game the results of popular chatbot scoreboards and they've had some AI talent also begin to leave. So Paul, what does this actually mean for Meta? And I'm curious how, if at all, does this impact or reflect on Jan Koon, who is one of the godfathers of AI who works at Meta And we talked about a ton on the podcast.

[00:45:29] Paul Roetzer: Yeah, the if you wanna know the story of the founding of Fair, the Facebook AI research group and. Jan Koon, you know, going to work there. Read Genius Makers. It's like the best inside story I've seen of how it all kind of transpired. Zuckerberg tried to buy DeepMind before Google acquired them. he tells the story of how HASAs and Leg and Solomon, the three co-founders of DeepMind turned down more money from Zuckerberg to go to Google because they didn't understand Zuckerberg's vision [00:46:00] for ai, didn't align with the growth obsessed culture, kind of the move fast break things approach of Facebook.

[00:46:06] And, were convinced that Zuckerberg did not share their ethical concerns over the rise of ai. So they just saw it as like a pure, you know, capitalistic play by Zuckerberg and where they felt like at Google they could be treated more as a research lab, which ironically, you know, all these years later, general AI merges and they, they kinda get thrown into the commercialization side of it.

[00:46:28] But at the end of the day, I mean, I think they. It was probably a better fit for what DeepMind wanted to do, especially back at that time. So it is a fascinating story. Koon is a, a, a, a very, very important figure in the history of ai. Specifically the last, you know, 20 years. He's, been a key part of major breakthroughs.

[00:46:50] He's, controversial in his stance, sort of against large language models. Yeah. which I think sometimes he, you know, maybe just doesn't [00:47:00] vocalize exactly like his point, but he's, he's kind of been dismissive of large language models that they're not gonna get us to AGI and he doesn't even like that term.

[00:47:09] you know, the new breakthroughs are needed and, I dunno, he's been right a bunch in his career and so, we'll, we'll see it how Paul plays out. But I do wonder, like, I think, my understanding is he doesn't have direct reports there. Like I feel like Yeah. I saw an interview recently where they were talking about his, his work there.

[00:47:27] So, it's always been an interesting. Relationship and interesting working environment. it doesn't sound great. I mean, it sounds like there's quite a bit of chaos internally, and I don't know, reorgs are always interesting to see how they play out. 

[00:47:44] Meta Plans to Automate Ads

[00:47:44] Mike Kaput: So in some more meta news, the company wants to reinvent advertising by automating the entire thing.

[00:47:51] With ai, meta now plans to let brands generate complete ads from scratch using aIdeally by the end of next [00:48:00] year, according to a new report in the Wall Street Journal. So that means businesses could upload a product image, set a budget, and meta's AI would handle the rest, writing the copy, producing other images or video targeting the right users and optimizing spend.

[00:48:15] In fact, on the company's annual shareholder meeting last week. Mark Zuckerberg outlined the vision saying quote, in the not too distant future, we want to get to a world where any business will be able to just tell us what objective they're trying to achieve, like selling something or getting a new customer, how much they're willing to pay for each result and connect their bank account and we just do the rest for them.

[00:48:39] So Paul, this seems like a pretty big deal if Meta can pull it off. I mean, you know, since way back to the beginning of marketing AI Institute, we've seen vendors trying to go after this kind of golden goose, right? Which is fully autonomous AI advertising. 

[00:48:56] Paul Roetzer: Yeah. I mean, one of the ones you would remember, Mike, that we, 'cause you [00:49:00] know, back before generative ai, before chat GBT, we spent a lot of our time trying to educate people on use cases.

[00:49:05] Yeah. I actually built a tool that. Yeah, you could go through and rate the value of different use cases. It was largely using like machine learning and natural language processing and some other stuff. But we, we weren't at an age where you could just generate something with a prompt. 

[00:49:18] Mike Kaput: Right. 

[00:49:18] Paul Roetzer: And one of the companies that we spent some time with in those early days was trying to do something like this, but the human would create the different headlines, images, offers, and then you would upload all these variants and then the AI would run, you know, sometimes millions of variants mixing and matching, but it wasn't creating anything on its own.

[00:49:39] Right. So, yes, this has been around for a long time. It's been theorized. I mean, I would imagine Facebook just, you know, like Google and others, that these massive ad networks, they're gonna have the ability to do this now at a different scale. it's just, it's always funny when you're like, when you're relying on the [00:50:00] company that I.

[00:50:00] You're spending the money with. Right, right, right. To, to dictate what's gonna work and the efficiency of that spend. And, you know, they may have ulterior motives sometimes of, you know, how much your money to spend. But, yeah, I mean, I, again, I I would say like if your career right now or your company makes its money, creating ads on Facebook, I would maybe start thinking about what that looks like in six to 12 months.

[00:50:30] 'cause Yeah. It's not gonna look like it does today. 

[00:50:32] Third-Largest US School District Adopts AI

[00:50:32] Mike Kaput: So fair amount of, agencies that I believe do things like that. Yeah. Yeah. O so in. Other news. Just two years ago, schools in Miami Dade County had actually banned AI chatbots because they were afraid of students using them to cheat. But now they're actually doing an about face and kind of going all in, because we just got news that Miami Dade County, which is the third [00:51:00] largest school district in the US, is introducing Google's Gemini Chatbot to over a hundred thousand high schoolers.

[00:51:07] And this is the biggest rollout of classroom AI by any school district so far. So teachers are using AI to do everything from simulating historical figures to help grading essays and even co-designing lesson plans. There's a ton of anecdotes in a New York Times article reporting on this about students then kind of co-working with AI to learn better and to refine their essays and assignments with guardrails in the ai.

[00:51:32] So it won't actually help you, you know, do the assignment, but we'll actually prompt you to work better on the assignment. This shift kind of comes amid a national push that we've talked about a little bit. There's, you know, the Trump administration is actually called for AI literacy in K to 12. And Miami's approach is really interesting, not only for the scale, but because it is emphasizing both training their staff and putting guardrails in place for students [00:52:00] to do effective work with ai.

[00:52:03] Now, Paul, this kind of just our ongoing AI and education conversation. Yeah. there's a lot to like here and what jumped out to me, there was a line in the New York Times article that they, the co the school district actually rolled out AI tools in tandem with AI training workshops for its 17,000 teachers.

[00:52:22] They actually built something they called the AI Institute, which offers a bunch of like courses and training for teachers, which I thought was exactly kind of what you've always been saying on the podcast is the way to success. 

[00:52:34] Paul Roetzer: Yeah. Teach the teachers. That is what we always say. Yeah, this is phenomenal.

[00:52:40] Like, I would love to talk with whoever organized this, like, yes. I mean, it seems extremely well thought out. I'm not sure who was actually behind the whole program and devised it. obviously we have some connections at Google. We could maybe, talk with there. okay. I'm just, just like scanning these [00:53:00] notes, trying to see if you know what it is.

[00:53:01] But yeah, kudos. I mean, I think this is a, you know, potentially a great blueprint for educational institutions, but this is exactly what needs to happen in enterprises. Like, it's the same, it carries over for sure. So we'll definitely follow along with this story. And I could see, you know, revisiting this on future episodes.

[00:53:20] I would love to hear how this goes, and especially leading into next school year. Yeah. but yeah, I mean, this is a, a big leg up for these students. I mean, if you prepare kids like this and they go through this kind of training, they're gonna be so far ahead of their peers when they get into college. So this is great.

[00:53:35] Yeah. 

[00:53:36] Mike Kaput: And while it is a huge school district, and I realize maybe not every school district can mimic it perfectly, it is really interesting to see them threading that needle of, they're not just saying, throwing up their hands, okay, AI's here, it's gonna change everything. It's like they have guardrails in place with Google Gemini to be able to help the students actually learn and not just click a button and get an answer.

[00:53:57] Paul Roetzer: Yeah. I mean, I would love to see this at my kid's school. [00:54:00] Yeah. Like a, you know, a custom version of Gemini that, you know, functions as an advisor, a mentor, a tutor, not as a answer engine. 

[00:54:13] Mike Kaput: Wow. That's a good segue. 'cause speaking of answer engines, perplexity, the AI powered search startup is growing fast, but burning cash even faster.

[00:54:23] Perplexity’s Financials

[00:54:23] Mike Kaput: So according to some new reporting from the information I. Perplexity made $34 million last year, but burned about 65 million in cash as it spent heavily on cloud servers, AI models, from Anthropic and OpenAI, and those power, many of the search engines answers, and this is all according to financial documents that were seen by the information.

[00:54:47] Yet at the same time, it sounds like investors are still buying into perplexity. They're reportedly raising 500 million at a $14 billion valuation. Behind the scenes, it's trying to scale quickly. They've [00:55:00] got 200 employees. New product lines are being teased like a Comet browser, a budding ad business, and experiments in e-commerce.

[00:55:09] It's scooped up teams from other AI startups like Sidekick and Rhymes ai, but they're still not really making as much of a tent in search as the other giants in the space. Google still handles 900 times more surges daily according to the information. Chat. GPT handles at least 25 times more per day than perplexity.

[00:55:31] Paul, how do you rate perplexity prospects in the market right now? I mean, it's no doubt useful, but it seems like the value proposition is kind of being cannibalized by chat, GPT, which increasingly delivers accurate web results and Google, which is increasingly delivering AI powered search results, feels like they're getting squeezed on all sides.

[00:55:54] Paul Roetzer: I do not understand that valuation. 34 million last year [00:56:00] at a $14 billion valuation. That's crazy. 

[00:56:04] Mike Kaput: Yeah. Some AI math right there. 

[00:56:07] Paul Roetzer: Yeah, I I mean even if you assume a hundred million dollar run rate 2025, it's still just bonkers. the only thing I can come up with is I did see articles in the last couple days.

[00:56:18] I. That they're in talks with Samsung and Apple to integrate into those devices. So it sounds like the Samsung deal's pretty close. which it says two companies are talked to. Preload Perplexities, app and assistant on upcoming Samsung devices and integrate the startups search features into Samsung web browser.

[00:56:38] they've also discussed weaving perplexities technology to Samsung's Bigsby virtual assistant. So I don't know, maybe they have some multi-billion dollar deals sitting here with . Samsung and Apple that aren't publicly known yet, which then would make it a little bit more reasonable. but yeah, I mean, I have multiples nuts, but I mean, what is, what is open eyes at, [00:57:00] what are they thinking?

[00:57:01] Like $15 billion maybe this year? 15, 20 billion and they're valued at, yeah. 300 billion. Yep. I can't do that math in my head. Rolled. No. 

[00:57:11] Mike Kaput: Yeah. I mean, yeah, just doesn't 

[00:57:12] Paul Roetzer: add up to me. Especially, 

[00:57:14] Mike Kaput: but I said especially scale of perplexity compared to that. Right? 

[00:57:18] Paul Roetzer: Yeah. And I just, again, I've, I perplexed, I I love perplexity.

[00:57:22] Early on I was like a, I used it all the time. I know, Mike, you were a big, you were using it before I was, kind of convinced me to give it a go. I do just struggle to see it, how it differentiates Right. Moving forward, since it's just built on everybody else's models and those models are all gonna do a better job of the things that Perplexity is trying to do.

[00:57:39] And I feel like they're just scattering to all these different niches to try and like find somewhere to lock in and maybe it works out. or maybe they just get acquihire at some point, which I think is probably more realistic. 

[00:57:53] Box State of AI Report

[00:57:53] Mike Kaput: Our next rapid fire topic box has released a 2025 survey of over 1300 [00:58:00] IT leaders that were pulled between April and May of this year.

[00:58:04] They found some really interesting data around this. So, 94% of the organizations, where the people work that they survey are already using ai, but there's a pretty big gap between the dabblers and the doers. The highest proportion of respondents, 47% say they're in the early stages of AI adoption, which includes pilot projects and kind of limited deployments.

[00:58:28] But those who are further along are already seeing some pretty serious benefits. So the survey shows that companies that consider themselves on the quote, leading edge of AI adoption are seeing 37% productivity gains on average from ai. Now, the vast majority also measure the success of AI initiatives in things related to productivity.

[00:58:50] when they were asked like, how are you measuring the success of AI projects? Time savings was the highest proportion with 64% answering that, that was followed by [00:59:00] employee productivity metrics at 51% and cost reductions F 43%. Interestingly, the report also finds the most common use cases for AI at the company surveyed are things like writing emails and communications, doing document analysis and getting insights from those docs and general purpose AI chat and research.

[00:59:22] Now, what I found kind of interesting, and made me definitely double take is the report also asks how mature is your adoption of AI agents for your IT system? And 87% say they're at least piloting basic AI agents in some way, including 41% piloting, quote, fully autonomous operations in select domains.

[00:59:43] Last but not least, respondents were also asked about how they're addressing the AI skills gap in their companies with 58%, the highest proportion saying they're relying on upskilling the existing workforce. Now Paul, this is it focus, but definitely [01:00:00] interesting to see what some of these answers are. I was actually struck by some of the parallels to the 2025 state of marketing AI report we put out last month, because we also found companies are often measuring success in terms of time savings.

[01:00:14] We found that the majority of companies are still in that kind of piloting AI or experimenting with AI phase. So not apples to apples, but I did think it was interesting. So how some of this rhymed here? What did you think of some of the data here? 

[01:00:27] Paul Roetzer: I think it's a good just perspective. like we always talk with research.

[01:00:31] You have to understand the audience that was, polled, that was surveyed in, in, in the research and, what their roles are, what the industries they're in, the size of the companies they're at. Yeah. So there's no like right or wrong. I think the whole point we try and push on this show is be, be open to all the different perspectives with all the different data, and then you have to like, use that to draw your own conclusions at kind of where we are.

[01:00:56] So, I love these kinds of [01:01:00] reports that are, you know, done in a, a thorough way, and provide some perspectives on what that, that audience is looking at. So, yeah, I just, I thought it was good. I wanted to make sure we, you know, address this on the show. And whenever we see research worth sharing, we, you know, try and share it.

[01:01:15] It's great use for Notebook lm like, if you wanna dig into this, if you're interested in this topic. Go grab a report, throw it in notebook, LM from Google, and have a conversation with it, build a study guide, do those kinds of things. That's, I love doing that with research reports, especially the more dense ones.

[01:01:30] Mike Kaput: Yeah. and Box's, CEO, Aaron Levy is definitely worth following on XI think as well. He's got pretty good commentary, comes from, from a certain perspective as what I think to be useful commentary on. Yeah, we cite 

[01:01:42] Paul Roetzer: him. We've cited him quite a bit. Quite a bit. He, he is, yeah. He's one that I do get alerts from him.

[01:01:49] he is very optimistic about the future of work, like every once in a while for wanted to like leave a comment and I'm like, ah, it's not even worth it. He is very much in the camp of it's all gonna [01:02:00] work out and more jobs are gonna be created. And, I I'm not sure where the optimism comes from honestly.

[01:02:07] Like I've, I've tried to read and like fully understand his perspective. I wanna share that optimism. I'm just not there right now. 

[01:02:15] Mike Kaput: I feel that, you know, honestly too, I feel like his survey respondents were really optimistic. 'cause I've found this like 87% saying they're piloting basic AI agents to be a crazy high number.

[01:02:26] I don't, I don't work in it, so maybe that's it, but there's 

[01:02:29] Paul Roetzer: just a very generous definition of ai. That's what I agent is right now, I expect. 

[01:02:35] Can AI Help Us Cope with Death?

[01:02:35] Mike Kaput: Yeah. All right, next up, grief, love therapy. They're all going digital thanks to ai, and unfortunately, the consequences may be getting ready to pile up as well.

[01:02:47] According to a new report in psychology today, now they look at how AI companies are now offering simulated versions of platonic companions. Just like friendships, romantic [01:03:00] companions like boyfriends and girlfriends and AI companies are also offering simulated versions of the deceased promising comfort through avatars that mimic a loved one's voice in mannerisms.

[01:03:14] After they've passed away. And even if that sounds a little strange to you, users appear to be relying on AI companions more than ever according to this report. So the market for AI companionship was valued at 2.8 billion in 2024, and is projected hit 9.5 billion by 2028. Now the issue here, which Psychology Today points out, and its kind of the focus of this article, is that while AI girlfriends grief bots therapy apps, they're booming.

[01:03:44] There's not that much research research yet on what happens when we outsource emotional processing to AI chat bots. So some get a lot of affirmation from these AI companions, but while they can soothe you, they may [01:04:00] also have bad consequences like isolating you, interrupting, you know, very natural though painful mourning processes and even straining or replacing real relationships.

[01:04:13] So Paul, I feel like we've been dancing around this one for a while. Like it seems like we have to accept there's some type of real demand, whether we agree with it or not, from people for AI companionship. Now it's up for debate, like how far down the rabbit hole they're going with those companions. But on the other, this just seems like an obviously really slippery slope, especially when it comes to the stuff with the deceased.

[01:04:39] Paul Roetzer: So anybody who listens, listens regularly. episode 1 49. This is the topic I mentioned we had to cut because I just wasn't mentally there to discuss this one. So this is the I grieving one. I I alluded to, almost did make the cut again this week. So I, this is a rapid fire item. I'm, I'm just gonna address this kind of quickly and then we'll probably have to [01:05:00] come back around to this one again down the road.

[01:05:02] I, so when I owned my marketing agency, one of our largest clients for like a decade was a funeral home. And so I spent a lot of time in that industry, thinking about that industry. And when I created the Marketing Institute in 2016, it was one of the industries, like I would talk to them about it and say, Hey, listen, here's what I think's gonna happen in your industry.

[01:05:24] It's sort of an inevitability that will be able to sort digitize the dead. They, they, they're, you can train these models on video, audio. This is before Gen ai. This is before chat GBT, right? And that just accelerated it. so imagine being able to conduct interviews, take all these videos, all this audio, and be able to, to train in its simplest term, a custom GPT kind of thing in a more advanced firm, a digital avatar with like a VO engine behind it where it's like, you know, is, seems real and it's trained to like, behave and talk like the [01:06:00] deceased.

[01:06:01] And, I just always kind of assumed that it was inevitable because. We live in a capitalistic society and there's money to be made doing this. whether it should happen or not, that is, I think at the end of the day, it's gonna be for individuals to decide. I am convinced you will have that option at some point in the near future, that the commercial potential of this is far too great for venture capital firms to not fund this.

[01:06:31] So this is something I assume is coming and is probably already some forms of this that we're not, I haven't researched the market yet to like really understand deeply what's going on, but like, just to frame this, here's the opening to the article Mike mentioned, imagine this in the final months of her life, your mother, while in palliative care, paid an AI company to create a digital replica of herself.

[01:06:52] The pitch was simple. This AI avatar would ease your grief, allowing her to live on for you and your children. Now, [01:07:00] months after her death, you speak with to the simulation almost daily, the voice is 70% accurate. The video nearly lifelike and the illusion brings comfort. Yet your dependence on this digital ghost has trapped you in a state of suspended morning.

[01:07:13] So, like I said, this is a rapid fire topic. I could spend five hours on this one, like this is probably over the last 10 years. one of the applications of ai I've spent more time than most thinking about. and so I just want like people to start preparing for the fact that this will be a part of society and.

[01:07:37] I think that it's important that we start considering the perspectives around this and start, you know, understanding and If psychologists and, people like that aren't already proactively working on this, I think we need to, we need research in this area if it doesn't exist already about the impact it has when people can't go through the normal grieving process.

[01:07:58] Yeah. [01:08:00] And the decisions people are gonna have to make. 'cause I get it, like when you lose someone close, especially in a tragic way potentially, where you just wanna, you know, keep, and this is, that's what I'm saying. There's no right or wrong here. There's just gonna be, it is or is not. And I think it is, it will, it will exist.

[01:08:16] The technology will exist. Hmm. And we have as a society have to start preparing for that and what that means. And, I'm not qualified to be the one to, you know, say that I can express personally how I feel and things I've been through. But, I think at some point we'll probably have to pull in some experts and maybe have some like special spinoff episodes where we just talk about this kind of stuff.

[01:08:39] Because I just think it's gonna be really critical to society, to, to understand that this technology is going to be there and it's gonna get weird. Really weird. 

[01:08:51] Mike Kaput: Yeah. I mean, reading that article alone, I think it's already getting weird. Yeah. Yeah. All right. 

[01:08:59] AI That Improves Itself

[01:08:59] Mike Kaput: Our final topic this week is a project that researchers at Ana AI are building called the Darwin Godell Machine.

[01:09:07] And this is an AI system that rewrites its own code to improve itself. So this is an experimental agent they published about that evolves like a digital species. Each generation tweaks its own source code, then tests those changes on programming tasks. If the new version performs better, it survives and gets added to a growing archive of agents over 80 iterations.

[01:09:31] They say this loop led to really big performance gains. So the system boosted its score on SWE bench, which is a popular benchmark, for coding from 20% to 50%. And on a multi-language benchmark called polyglot, it went from 14% to over 30% accuracy. All without updating the foundation model that powered it.

[01:09:54] So in other words, it's AI that can learn indefinitely because it can update its [01:10:00] own code. And that's a really interesting development developing self-referential, open-ended, improving ai. Now Paul, the actual paper here related to this gets really technical, but the overall point seems to be that this could be a breakthrough that basically enables AI without updating that foundation model to get smarter.

[01:10:23] So what's important to be thinking about here and paying attention to? 

[01:10:27] Paul Roetzer: We just wanted to. Make sure we address this one on the show. in the Road to AGI series, the first episode I talked about, you know, one of the things that could drive like accelerate model development is self-improvement.

[01:10:40] . If these things can actually, like, improve themselves, and that's kind of the premise here. We talked about, Ana, I wanna say it was like toward the end of last year. I know we mentioned them on the podcast because I think they're backed by some pretty significant players in the AI space, which is what caught our attention.

[01:10:54] I would say, it may be a 

[01:10:57] Paul Roetzer: little while before you [01:11:00] hear more about this, in terms that would matter to you as like a, a business leader or practitioner, but this concept is one of the fundamental ways that the labs think they can rapidly advance these models to AGI and beyond. . And so I just wanted to make sure people were kind of aware of this progress.

[01:11:21] This is probably a topic I'll go further into in the Road GI series as I start, you know, building out those episodes. But, yeah, I would not try and digest this research before If you wanna try it in notebook dilemma and say, gimme this at like a fifth grade level. What does this mean? Right. You might have some success there.

[01:11:39] but overall this is pretty dense stuff and it's probably, you know, six to 12, 18 months away from finding its way into like major models. But progress is always being made on the research front and sometimes there's just research papers that surface and you're like, that one's gonna be important.

[01:11:57] Yeah. And I would put this in that category of like, you [01:12:00] just, as soon as you see it's like, okay, flag. That one is like one to come back to. 

[01:12:06] Mike Kaput: Alright, Paul, that's a wrap on another busy week in ai. I appreciate you breaking everything down for us and demystifying what's going on out there. 

[01:12:14] Paul Roetzer: Yeah. Good stuff.

[01:12:15] And then definitely check the, The show notes. There's a bunch of newsletter only stuff too that we had to cut, like Grammarly getting a billion dollars and going after an AI productivity platform. interviews with, you know, Google, Elon Musk doing some stuff with Sam Altman and trying to block his deal.

[01:12:32] There's all kinds of fascinating reads. So, yeah. As always, thanks everyone for joining us and thanks Mike for curating everything and pulling this together. Thanks for listening to the Artificial Intelligence Show. Visit smarter x.ai to continue on your AI learning journey and join more than 100,000 professionals and business leaders who have subscribed to our weekly newsletters, downloaded AI blueprints, attended virtual and in-person events, taken online AI [01:13:00] courses and earned professional certificates from our AI Academy, and engaged in the marketing AI Institute Slack community.

[01:13:06] Until next time, stay curious and explore 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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