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The Artificial Intelligence Show
#123: Trump AI Policies, Problems with OpenAI’s New Model, GenAI for Business Strategy & Visa’s 500 AI Use Cases
01:09:29
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- [00:00]
Paul Raitzer
Neither campaign really talked about AI much at all. My opinion was they didn't know how the public perceived AI, so there were no votes to be won by talking about AI on the campaign trails. But we knew it was gonna be fundamental to whatever happened once the administration, whichever one it was gonna be, came into office.
- [00:21]
Mike Kaput
Welcome to the Artificial Intelligence show, the podcast that helps your business grow smarter by making AI approachable and actionable. My name is Paul Raitzer. I'm the founder and CEO of Marketing AI Institute and I'm your host. Each week I'm joined by my co host and Marketing AI Institute Chief Content Officer, Mike 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. Join us as we accelerate AI literacy for all.
- [00:57]
Paul Raitzer
Welcome to episode 123 of the Artificial Intelligence Show. I'm your host Paul Raetzer, along with my co host Mike Kaput. So we had an election last week in the United States. Mike and I have a policy not to discuss politics on the show. No one cares about our political opinions. And too many tech podcasts went the way of political shows in my feeling over the last year. So Mike and I have a commitment to you not to do that. However, when it influences AI and the future of AI, we need to talk about it. So we will be discussing some early signs of what we think the new administration means to AI and technology more broadly. So that is going to be a main topic today. We're also going to get it in some rumors, I guess. I don't know. It's being reported that maybe the frontier models have plateaued in their training. So we're going to kind of unpack that because that's a very important thing. And then Mike and I are actually going to share a really cool internal use case that we used ChatGPT for, in particular for some planning that I think people could apply as they're doing their 2025 planning and then a whole bunch of rapid fire items. So we got a lot to cover. This week's episode is brought to us again by AI for Agency Summit. This is our virtual event, the second year it's happening. It is occurring Wednesday, November 20th from 12pm to 5pm Eastern Time. You cannot make that time zone. You can get on demand. So there will be an option to get the summit on demand. It's an incredible lineup. It's going to be packed with basically trying to figure out how to help you drive AI transformation in your own agency. And for your clients. If you're on the brand side, let your agencies know about the summit because you want agencies that are probably proactively seeking to drive AI literacy and capabilities within their own firms. And this is a great head start for them to do that. So you can go to aifor agencies.com, that's ai4agencies.com, check out the agenda, check out the speaker lineup, and then click register. Now you can use promo code AI forward 200 for $200 off. So again, that is ai4agencies.com and the promo code is AI4forward200 and that will get you 200 off the ticket. And again, if you can't make the live event, check out the on demand ticket options as well. All right, Mike, the topic you neither of us really wants to talk about that has to do with politics, we're going to talk about. So let's do this in our style is as objective and unbiased as we can humanly be when it comes to these things and just be report the facts as they appear to be. So that is our kind of promise to you, is we're going to do our very best anytime we talk about this topic related to politics to just give you the facts and let you all figure it out for yourselves from there.
- [03:57]
Guest Speaker
All right, Paul, so let's dive into it. According to a few reports we're starting to get, it seems like possibly President elect Donald Trump is potentially signaling some pretty significant changes to the nation's artificial intelligence strategy. So it sounds like at the center of his administration's plans might be a potential dismantling of President Biden's landmark AI Executive Order, which established safety and privacy standards for AI development. We know for a fact that the incoming administration is shaped in some ways by several key advisors, most notably Elon Musk, who contributed over $100 million to Trump's and has been outspoken about his views on how AI should be developed. We're kind of seeing among the most immediate changes expected is potentially the elimination of the AI Safety Institute that is created under Biden's executive order in order to evaluate advanced AI systems. However, as always, tech companies, think tanks are kind of racing to have their own influence. Some of them are trying to convince Congress to make the institute permanent before Trump takes office in January. And the new administration's AI agenda seems to be aligning around reducing regulatory barriers and promoting AI development. That, in their words, is kind of rooted in free speech. So this kind of pushes back against what some Trump allies kind of term, you know, quote, unquote like woke AI with like biased or politically skewed results. And then, of course, there's also going to be, what we've heard rumblings about is trade policies that could also impact AI development. Trump has proposed a 10% blanket tariff on US imports and 60% on Chinese products, all of which would affect some of the hardware and products that go into artificial intelligence. And we don't seem to have any real clarity on kind of what would replace this. Would it be just an unfettered set of policies? Would there be additional regulations? We're not sure yet. So, Paul, it kind of seems like we could see some swift, sudden changes to AI policy under the Trump administration. How are you seeing this playing out right now?
- [06:21]
Paul Raitzer
Yeah, I think there are breadcrumbs. You know, there's a couple articles that came out over the weekend. We'll put into the show, notes about this. But the way I, the way I kind of think about this is to follow the money is a good way to do it. So while the campaigns, neither campaign really talked about AI much at all, and we talked about this on the show, that my opinion was they didn't know how the public perceived AI. So there were no votes to be won by talking about AI on the campaign trails. But we knew it was going to be fundamental to whatever happened once the administration, whichever one it was going to be, came into office. So when we look at the Trump administration, you can look back over the last year, plus of who are the major technology organizations and individuals that backed the campaign. You mentioned Elon, obviously, but Andreessen Horowitz came out a few months back and kind of counter to their traditional views, they went all in on Trump. Now they published in fall 2023. We talked about this on the show, the Techno Optimist Manifesto. So if you want to understand why A16Z and Andreessen Horowitz would back Trump, you could probably go read the Techno Optimist Manifesto and that will give you a good sense. In essence, they are very, very pro startups. So they want to enable the startup ecosystem to innovate as much as possible with as little regulation as possible. And crypto, those are two, you know, two or three big areas. Startups, regulation, crypto. So they, they listed several reasons. They believe the Biden administration is stifling startups through over regulation and potentially needless taxation. The, I guess sort of like the tipping point for them was the Biden administration had proposed attacks on unrealized capital gains, meaning as state startups become higher and higher in value that they wanted to actually tax that increase in valuation before the money was actually realized by anybody. And that was the. What they claim was the. The big break for them. Another major player to look into is Peter Thiel. Peter Thiel is the kingmaker for J.D. vance. So when Vance was elected to Senate in 2022, it was Thiel who funded that campaign, who basically pushed for him to get into that position. And Thiel, along with David Sachs and some others, are the ones who basically pushed for JD Vance to get the ticket as the vice president. So Vance was put into power through his VC connections. You can go into Peter Thiel's history. He co founder of PayPal with Elon Musk, Palantir Technologies Founders Fund. So he's a VC as well. He was the first in Silicon Valley to publicly support Trump back in 2016. Gave a bunch of money, was very vocal, appeared at the Republican national convention in 2016, then pushed for Vance to be involved. He's a libertarian, which is someone who advocates for minimal government intervention in individuals, personal and economic lives. So again, get rid of the regulation, let technology do its thing, maximize personal freedoms while minimizing the role of the state. And then there's David Sachs, the All in podcast. I'm sure there's some of our listeners that are also all in podcast listeners, as you would be aware. David Sachs, who was a founding member and chief operating officer of PayPal, back with Peter Thiel and Elon Musk and all those guys. He was very, very vocal on the all in podcast and got Trump. I think Trump appeared on the all in podcast. If I'm not mistaken, he was also the founder. Sachs was of Yammer, which he sold to Microsoft in 2012, and he also has a VC firm. And then obviously Elon Musk. So, again, if you want to know the general technology agenda and where AI may go, you can look at some of those key players and what they have publicly stated about their beliefs. They're going to have an influence. Now, not all of Silicon Valley was supportive of the the Trump campaign and the next Trump administration, but they certainly all lined up over the weekend to congratulate. So you can go and look at Bezos and Bill Gates and Aiden Gomez of Cohere and Jack Clark of Anthropic and Sundar Pichai of Google and Mark Benioff of Salesforce and Greg Brockman of OpenAI. Every single one of them had the congratulatory tweets, and we're looking forward to working with your administration again, whether they supported that administration or not, you're going to have to work with them. So at the end of the day I kind of made my like scorecard like right away I was, I had this scorecard before I started looking into the rest of the stuff. And the losers in my opinion, climate, climate regulation done like they're, they're going to do anything in their power to not worry about climate change and they're certainly not going to care about whether or not advancing AI impacts the, the climate. So that is, that is a direct loser. The executive order as you called for is done. They will can that as soon as possible. So that is a loser, a dark horse loser. Here is OpenAI and Sam Altman and the reason for that is Elon Musk's influence. So as we have talked about many times on the show, Elon was a co founder of OpenAI. He put the first 40 million in, he created the name. He lost a power struggle in 2019 when he tried to roll OpenAI into Tesla. Sam came to power and Elon has a beef with Sam and it's very public and Elon like tends to hold grudges and so there's a, you know, maybe Sam and Elon kind of come to peace but if they don't like Elon could probably with his influence make Sam and OpenAI's life miserable if he chooses to. The other side to that is Xai, Elon Musk's startup AI company. You could imagine him getting way more support and power for his own AI startup because he's bought himself some pretty significant influence. And then open source is probably the other. And maybe the biggest winner is when you remove regulation you limit the, you know, the government's say in the downsides of open source and acceleration of technology. So the EAC movement that, that acceleration all costs, they're a winner too. And so open source probably by, is a byproduct of that and that's One of the A16Z plays is they want like kind of this freedom to innovate there the one big variable in all this and I, I don't know like how this plays out but the reality is Trump and, and Elon Musk both have very large egos, very large personalities and they are both alphas and, and how those two get along for four years is going to be really interesting because Elon, while he may not hold some official position in the administration, he is certainly going to have influence. And if he starts getting a lot of public credit for things that happen, you almost wonder if that doesn't create some friction. So I, I have no idea. But it'll be really interesting to watch how that power dynamic plays out and what kind of ends up happening. And, and again, keep in mind with Elon, he, he is historically a supporter of Democrats. Like he's very public about the fact that he voted for Hillary Clinton. It's rumored he voted for Biden when he took over Twitter in April 2022, he tweeted. For Twitter to deserve public trust, it must be politically neutral, which effectively means upsetting the far right and the far left equally. So Elon's move to support Trump wasn't, this isn't wasn't assumed all this time. I mean, Elon has, has tried to remain somewhat independent, but there was a shift and some believe the shift actually occurred when he got snubbed at the E. The electric vehicle event at the White House a couple years back when he wasn't invited there. And it ended up being because it was like a, in essence a union event and Tesla is not a union shop. But it seems like that may have played a role in him feeling burned by the current administration and shifting his support. But who knows? But yeah, it's a dynamic situation and like I said, Mike and I'll keep tabs on it and report the facts to you again as an unbiased and objective way as possible. Just observing the space. And so those are some of the things that I see early on. But I think we're going to learn a lot more in the months ahead leading up to the inauguration in January.
- [15:07]
Guest Speaker
Yeah, we'll definitely see how this all plays out in practice. But you mentioned this briefly. It just seems like at the moment I would not be betting on anything other than E ACC movement. The effect of accelerationism seems to be the order of the day here.
- [15:22]
Paul Raitzer
Yeah. And I think this probably also, you know, I hadn't thought about this one. It probably accelerates the states like California being way more aggressive. So if you remember when SB 1047. That's right, yep.
- [15:37]
Guest Speaker
Yeah.
- [15:37]
Paul Raitzer
When that, when Newsom did not sign that bill. What we said on that episode was that I thought the, the Biden administration and Nancy Pelosi told them to pump the brakes that that federal wanted to have a say in this and, and Newsom called like all hands in California legislation last week after the election. And so I would not be surprised at all if you don't see states like California race to put some state level legislation in place. Again. I hadn't really thought about that until now, but I could definitely see that being a major play to try and bypass some of the stuff that they're. That they know that this administration is going to do, too.
- [16:28]
Guest Speaker
Yeah. And while I don't, certainly don't expect Silicon Valley to go away anytime soon, you could see some really big moves depending on how regulation at the state level happens where some of these companies are built.
- [16:38]
Paul Raitzer
Yeah, for sure. And I mean, Elon's already made that pretty public with his efforts to build more in Texas. But again, like the SB 1047, the key to that legislation is it doesn't matter if you're in California or not, it's if you do business in California. And so, you know, California more than any other state can have an impact on the economy with their choices. So, yeah, I don't know. It's going to be fascinating.
- [17:06]
Guest Speaker
All right, so next up, we are seeing a bit of an unexpected challenge confronting OpenAI. The pace of improvement in their core AI technology might be slowing down. We got a report this past week from the Information that the company's upcoming flagship model, which is codenamed Orion, is kind of revealing the limitations of current AI development approaches. So the information is reporting that while Orion does appear to surpass previous models, the improvement is notably smaller than the big leap we saw between GPT3 and GPT4. And some OpenAI employees report that Orion just isn't consistently better at certain tasks, even particularly coding, despite higher operational costs. So this basically is starting to challenge one of the fundamental assumptions in AI that we've talked about a bunch, which is scaling laws. The systems will continue to improve at a consistent rate given more data in compute, and it seems like that data piece could be the bottleneck here. They are reporting that the amount of high quality training data is creating a real struggle for OpenAI. Apparently they have largely exhausted their publicly available text and data sources. They've started to experiment with AI generated training data. But this is creating complexity. The Information is reporting that Orion sometimes mimics the limitations of the older models used to generate its training data. So in response, OpenAI is trying a couple things. It sounds like they have established a dedicated foundations team led by Nick Ryder to address the data shortage and explore the future of AI scaling. They're also looking more at post training improvements like developing new reasoning models like O1 that take more time to think before providing answers. So, Paul, I guess my first and biggest question is are we actually slowing down here?
- [19:13]
Paul Raitzer
This is fascinating. So I don't feel like anything in this article was new, but this thing was Cooking on Twitter over the weekend, like everyone was reacting to this. There was a bunch of OpenAI employees responding to it. So the co founder and CTO at Writer, which is a, you know, a geni writing platform that we're very familiar with, he tweeted, we've been discussing this for some time. There's minimal improvement or return beyond a trillion parameters with only very small gains from around 150 billion to 1 trillion. We have publicly stated that our Palmera LLM achieves improvements by deepening the model architecture, not by increasing the number of parameters. But then you had other people. Clive Chan from OpenAI, he's like, what? It comes next as relatively little new science, but instead years of grinding engineering to try all the new obvious ideas. The new paradigm, scale it up, speed it up. Maybe there's another wall after this one, but for now there's 10X's as far as the eye can see. So he's like, you know, just the headlines misleading. Basically you had Dan Shipper, who's a co founder and CEO at every. The message that this headline conveys is at odds with what people inside the big labs are actually feeling, saying it's technically correct. But the takeaway for the casual reader, AI progress is slowing is exactly the opposite of what I'm hearing. We have Adam GPT, who's an OpenAI employee, said traditional scaling laws which focus on pre training larger models for longer is absolutely still a thing. That aspect of scale is still foundational. There now happens to be another scaling thing and together those two things are poised to unlock amazing capabilities. Noam Brown, who's fundamental to the O1 model, we've talked about Noem multiple times. He said there won't be a slowdown in AI progress anytime soon. Yeah. So. And then like ironically, Sam Altman did an interview with Gary Tan from Y Combinator and this is last week. We'll put the interview in the show notes. I was watching it on YouTube. I don't know if it's a podcast too or not, but it's definitely on YouTube. And Sam said these things are going to compound. We could hit some unexpected wall or we could be missing something. But it looks like there's a lot of compounding in front of us. We are not near the Satur point. The models are going to get so much better so quickly. And when Gary asked him what are you excited about in 2025? He said AGI. So I don't know. So I think like there was a couple of things I went back to on this because again the article, I, I guess maybe it was more explicitly saying that it thinks the labs have run into a plateau on the scaling laws. Yeah, but I, I don't, I don't know that that's new because like we talked recently about Ilya Sutskova and he was talking about the need to like how these labs all know to do like more data, more, more training time, but that there needs to be some new paths where you push hard and that the, the challenge a lot of these labs were facing was which new path to bet on, that there was different ways now to go about trying to drive like these leaps forward. But the thing we talked about, I can't remember what episode it was on. We'll have to go back and look. We'll put in the show notes. But what I said was it might have been we first talked about Orion, that the thing that to me was the trillion dollar question was could OpenAI create a new frontier model that stayed at the top of the leaderboard for another two years? Because when they introduced GPT4 in March of 23, everybody chased that model since then and, and it seems like everybody just sort of caught up to that. Like no one is, is clearly ahead of a GPT4, GPT4O model, but they're all sort of comparable. And so the question became, well, why hasn't someone taken a leap yet? Is it because that training in this way is just kind of like, this is it, this is the smartest models we get? The, the investments coming from big tech certainly didn't imply that. The demand for Nvidia chips certainly didn't imply that. So the unknown was, well, has OpenAI or is anybody else cracked the next breakthrough that allows them to create a model that is so far ahead of Everybody else like GPT4 was? And that's the part that seems up in the air at the moment. Now, as we talked about last week, OpenAI seems to think reasoning is the key that their series of O1 models. And again I'm, I'm a believer that we're going to get the full O1 sometime between November 21st when I think that there's a developer day, an OpenAI developer day and November 30th when we would be at the two year anniversary. Yeah, wait, did I get my numbers right? Yeah, two year anniversary of chat GPT coming out. So I think we're going to get the O1 full model now. What it's capable of doing beyond what we already see, I'm not sure, but I think that there, there is a real question here about whether or not these frontier models are sort of commoditized at this point, that they have somewhat plateaued in. They're just going to keep leapfrogging each other every three to six months. And there isn't a breakthrough really left at that model of text in and text out. But where I think this becomes interesting is like what are the things that are going to differentiate as we move forward? And the things that seem, because Demis Hassabas has done the same thing, that there's like two to three breakthroughs left before we just get to AGI. And reasoning seems to be a big one like that, that everybody's working on that. And so 01 is sort of the first one to market that has that clearly. But we know everybody else is working on it. Multimodal seems to be really critical. So again, keep in mind, a lot of these previous generation models were text in, text out. So they were trained on the text of the Internet. They were not trained on videos, audio, images as a single model. But we know that's what Google is trying to do at Gemini, that you train it on multimodal and then that opens up a whole new universe of data to train these models on. And maybe that's a path to go down, is pushing hard on the training there. The other one that comes to mind to me is the path and maybe these are some of the things Ilya is thinking about when he's saying like there needs to be, you got to pick which path to bet on. So you can bet on reasoning, you could bet on multimodal training, you could bet on symphony of models where the frontier model functions as the conductor. And then all the smaller models do their thing within specialized areas that don't require as much compute. And so you can imagine pushing hard on this sort of like central hub, which is the frontier model, and then all of this symphony that allows them to kind of work in collaboration together. And then the other one where, where Google has the massive advantage is self play and recursive self improvement. And that comes from reinforcement learning like alphas GO and Alpha 0 and things like that. And so those are 4. Again, I have no idea what the next breakthroughs are, but from everything I've heard in these interviews, they seem to think they know the collection of things it could be. And what they need to now do is push computer push different testing and see which of these things plays out to, to unlock these frontier models to maybe then take the leap. And maybe it's like a couple of these things in combination. But all that being said for our listeners, this is all fascinating. But for our listeners, here's the reality. It's irrelevant to you if they make a leap forward next year, like they probably will. But from what Mike and I see every day talking to big enterprises and small is the, the absorption of the current capabilities is so low. The, the value you can create in your company using today's models is so significant and so untapped that it doesn't really matter. Like do we get GPT 5 or Gemini 2 or Quad 4 or did their training runs not work? Like, it's all fun to talk about, but for you, focus on using what we have today to do your plans for next year to build a more efficient team to drive productivity and creativity and innovation. Like the next main topic, Mike and I are going to share a way we did this, but like that's my main message to you is don't get caught up worrying about all this stuff. Just go do things like take action. Because there's so much value sitting there to be created with the models we already have.
- [28:23]
Guest Speaker
And realistically we don't need that many more breakthroughs for there to be even more disruption. Right. I mean, even if it's not as big a leap next time forward, these are still improving. Are still improving. We're just debating like how much.
- [28:39]
Paul Raitzer
Yeah, I think the fusion of the current capabilities would be enough disruption to last us like five years.
- [28:48]
Guest Speaker
Yeah.
- [28:48]
Paul Raitzer
So they're going to get smarter, they're going to get more generally capable, they're going to be able to take actions, they're going to do all these things we talk about, have worldviews, things like that. But that, that stuff may not create value for your company for another year or two, but we have today can transform your company right now.
- [29:07]
Guest Speaker
So let's maybe then kind of ease into the third big topic and talk about a way to do that. Like we wanted to. You know, you and I had talked before this episode, Paul. We just kind of wanted to share like a practical use case of how even just using the latest capabilities of ChatGPT alone last week we dramatically accelerated planning and innovation for both Marketing AI Institute and Smarter X. So do you want to maybe walk us through what you and I had worked on?
- [29:35]
Paul Raitzer
Yeah. So basically the way this works is as the CEO, a lot of my work is on kind of the vision and the high level strategy for, for the organization. You know, thinking through our revenue channels, thinking through our current growth opportunities, future growth opportunities, Things like that. And so as I was going through building our 2025, like, growth matrix, I sort of landed on this idea that we'd had a couple years back, and it's related to, like, the media content side of our business. So Mike, as you're aware, is the chief content officer. So I go to Mike with this idea and I was like, listen, I think we have this opportunity to really scale what we're doing, but to create, like, tremendous value, like a high velocity of value creation across different industries and for different Personas. And so I kind of explained the concept to Mike and he's like, yeah, I love it. Like, we should do that. And it's like, okay, now what do we do? And so Mike and I spent, you know what, nine years at marketing agency together, and we've built plenty of strategies and campaigns. And there's always that, like, to go from idea to action is really hard because someone has to commit the time to build the brief, to go do the research, to do the initial planning so that you can then react to that together. So for me, I was like, okay, I got to put a forcing function in place. I got a bunch of travel coming up. Like, I'm just going to put a meeting for Mike and I. It was last Friday, I think we met. And so by putting that meeting on the calendar, it was like, okay, this will force us to now talk about it. But the Thursday, the day before, we had nothing. We had like, blank page. It's like, okay, we have this idea, but like, what do we do? And so what I, what I, what I then did is rather than Mike and I showing up to that meeting and, and spending two hours just kind of bouncing this idea around, I used ChatGPT to develop drafts of the plan, thinking through various planning, production, promotion, performance, like, kind of like the key areas we look at different ways. And I'm basically just giving some prompts to this thing that's saying like, okay, I've got this business idea. It's for our Smartr X brand. And this. I'm using my co CEO GPT that I built. And so it understands that brand and knows what we do and it knows our revenue channels. And I just said, help me think through this business model. And it's like, okay, great. Like, what do you, like, what do you want to do? And so I kind of like had a conversation around that. And then I, it was really good. And this is all happening over like three minutes. And then I said, okay, create a task list for the planning and production of the content that we're going to create without getting into all the details. And then I was like, okay, you know, we're going to do this for different industries and sometimes how do we identify and prioritize verticals and Personas, you know, to help drive our decision making? And it created an amazing brief on this thing. Now, as I said, Mike and I did this stuff for a living. Like, we have the ability to do this, but the reality is for us to do this would probably have taken 10, 20 hours to do the kind of planning that went into this. Now, there was nothing that ChatGPT output that we wouldn't have probably thought about if we had enough time. Like if Mike or I could go away for three days and just think deeply about this idea, we may have come up with 80, 90% of what ChatGPT. But the reality is ChatGPT did this in three minutes. And so my thinking here was, rather than Mike and I sitting staring at a blank page and ideating from zero, we now had, I don't know, it's probably like 2,000 words or so, structured really nicely in an outline and brief for us to react to. And so we get into the meeting on Friday and I said to Michael, I was like, let's just walk through what ChatGPT did and let's start talking through things we like, things we don't, if we have any other ideas. And there came a time, what, like 15 minutes into it, we're like, hold on a second, this is actually a really interesting idea. Let's lean into this for a couple minutes. And honestly, it ended up leading to a conversation that may change our whole go to market strategy for SmartRx next year. And if we hadn't had ChatGPT develop the brief, I don't know that we would have got there. And then I go away like this week and then we run into Agency Summit and then it's Thanksgiving and all of a sudden it's middle of December and Mike and I haven't made any progress. Instead we're going to spend the next 30 days pushing hard on the few things that came out of it that were actionable. So that to me is like a fundamental way to use these tools today, use them as planning assistance. And then the other thing we did is we traditionally use Zoom, but for this one, you know, I really wanted to try Google Meet. Now I had had a meeting last week where we did the video, the transcript in the summary with Google Meet, and I was pretty impressed. Like it was, it was really Solid. And so we have Google Workspace. So I said to Mike, like, let's try Google Meet for this one. And so we did Google Meet, and we used it. Did the video, the transcript, the summary, which was. Right. So the whole thing. Mike and I met for, like, two hours.
- [34:40]
Guest Speaker
Yeah.
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Paul Raitzer
And I feel like we made a month's worth of progress by just infusing ChatGPT and, like, that brainstorm process. So I don't know. How did you feel about it, Mike? I mean, you lived through the experience too.
- [34:54]
Guest Speaker
Yeah, no, I. I felt very similarly. What really struck me, too, is, like, everything you just described, it's like, if we had a really smart employee, like, brief us on initial ideas, which then gave us the bandwidth and the time to actually, I would argue, do what we should be doing and do best, which is actually exploring and operationalizing more ideas or creating our own based on that, we would never have gotten there. We would have spent all the time getting the initial brainstorming done. And like you said, nothing would have happened as fast as it happened.
- [35:27]
Paul Raitzer
Yep. Yeah. One other note I'll make here, and I. I mentioned this to Mike was. So I did all this in chat GPT then, because we're a Google Workspace shop. I copied and pasted everything because I wanted to share it with Mike. Now I can share the chat, but we wanted to be able to comment on it. We wanted to be able to, like, interact with it. So I needed that chat GPT output into Google Docs. So you copy and paste and unfortunately, all the formatting goes away. And I don't know, maybe there's something I'm doing wrong there, but I've tested multiple ways, and it just jacks up the formatting. It puts all the pound signs and everything in there. And so then as Mike and I are going through, I'm like, changing the format. It's kind of annoying. Now, that's a. That's an opportunity for Google, if you think about it, because direct integration into Google Docs would be brilliant. But I'm not saying chatgpt per se. Like, if you use Google Gems, you can export to Docs right away. There's actually a button to send it to Docs, like, share into the docs, and it does nice formatting. The problem is gems seems way behind custom GPTs at the moment. So, like, I went in and tried to do the same thing with a gem one. I can't find any information about the context window for the instructions. I don't know what the character limit is. Like, I know in ChatGPT it's 8,000. I can't find that anywhere. For gems there's no guide when you're in there. There's no ability to do conversation starters, which is like a really awesome feature of Chat GPT. I don't know how to do those. I think the gems are 100% private. They don't train on them. I think if I share them with you, only you can see them, but I have no idea. Like and so just a note to the Google team, like gems is a huge opportunity but I, I, I can't find anything other than like the blog post announcing that they exist in August. Yeah. And then like some user generated guides to it. But even those didn't answer the questions I had about character limits and conversation start and things like that. So I feel like if Google Docs had Gemini baked right in. Because if you go into Google Docs and just use the help me right thing, it does not do anything like what ChatGPT or Gemini are capable of doing. So like I just want the functionality to do my planning right in Google Docs.
- [37:43]
Guest Speaker
Yeah.
- [37:44]
Paul Raitzer
With Gemini without having to go through all this other stuff. And that does not exist. But because Google has Google Workspace, there's a big opportunity if they can crack actually making Gems highly functional and valuable and that integration with Google Docs right away. Now Microsoft obviously has the same capability with ChatGPT and Word, but that would be a great unlock in terms of value creation.
- [38:10]
Guest Speaker
Yeah. And you and I had even tested. Obviously there is Gemini within Docs, but even then I don't know if it's due to what information it pulls, what model is being used. But like we tried more sophisticated prompts right. In Google Docs and it's just not there. The same prompt works really well if you go open up your own instance of Gemini.
- [38:31]
Paul Raitzer
So yeah, it's very limited in capabilities in Docs. Right. It is not the same chat bot for sure. Which maybe that's the, maybe that's the need is like stop trying to be one thing in one doc and one in the other. It's just integrate the things. So yeah. So the moral story here is push on using these tools as a planning tool for next year. Like they're, there's a ton of value sitting there and it can really accelerate things. Like again I always use these examples of what would I pay to have that function. So forget 20 bucks a month for chat GPT. For Mike and I it's 40 bucks a month or whatever that number is. If I would have done that myself. We're talking 10 to 20 hours. What is 10 to 20 hours of my time worth? Right. A lot to me. So the fact that I didn't have to do that, if that was just like, hey, you can use it to help with this plan, what would you pay for it? I'm probably like, I don't know, one $2,000. Like if some, if a chatgpt is going to create this for me, that Mike and I could just spend two hours reacting to it. Instead I would have happily paid thousands of dollars as a business user for, for that one use case.
- [39:37]
Guest Speaker
Yeah, that's incredible. And like we've talked about a couple times, it's like whether you're trying to figure out more use cases or trying to figure out how to get started, go create a GPT that does helps you do your job like co CEO. Just think of it that way. Put your job description in and be working with it regularly.
- [39:54]
Paul Raitzer
Yep.
- [39:56]
Guest Speaker
All right, let's dive into our rapid fire topics this week. So first up, we have another interesting case study. Not ours this time around, but Visa. The credit card company has apparently deployed over 500 generative AI applications across its operations, according to a new report in the Wall Street Journal. So these applications span a ton of different functions, from security tools that detect bugs in code to specialized chatbots serving as subject matter experts. This initiative, led by the company's technology president, Rajat Taneja, reflects a deliberate kind of go fast approach designed to address two critical challenges. Staying ahead of increasingly sophisticated fraud attempts and maximizing AI's potential benefits before Visa's competitors do. So they've actually invested over $3 billion in AI and data infrastructure over the past decade to support this vision. One particularly notable implementation targets something called enumeration attacks, which currently cost the company over a billion dollars annually in fraud losses. Other tools they've developed help customers customize billing cycles and streamline various operational processes. And what's really interesting here is just kind of how all in the company has been on this. They establish really strong governance infrastructure and data protections first and then encourage their teams across all different business functions to participate in AI implementation. Looking ahead, Tanaja, who is the technology president in charge of this, envisions a future where human employees each oversee 8 to 10 different AI powered digital workers, creating kind of a hybrid workforce model. So Paul, this certainly seems like an enterprise succeeding with AI and getting real value out of it, which is a little contrary to some of the reports we've seen saying that nobody is Getting value out of this of stuff.
- [41:54]
Paul Raitzer
Yeah, it's. We're always on the lookout for brands that are telling their stories of success. They're hard to come by, honestly. So yeah, this is interesting and it makes sense like a lot on the fraud side that they would have a ton of use cases there. But simultaneously we, we came across a information exclusive for like their pro subscription with which Mike and I have out of the generative AI spending of 50 companies from Coke to Walmart. And so we were kind of scouring through that, looking at, seeing like which models they use, what are their use cases. And you know, I think similar to Visa, some of the things that Surface is customer support. Like everybody is building chatbots for customer support and success. That, that seemed almost universal. Marketing and content generation, which is no surprise. Operational efficiency, you know, companies like Goldman Sachs and Toyota deploying AI for internal tools, coding is obviously a big one. And then sales enablement, those are categorically like the big things that jumped out from these 50 companies. And again, they're big brands. So they were looking at IPG and DoorDash and at T and Coca Cola I mentioned. So, yeah, I think going into next year we're going to start seeing a lot more companies talking publicly. I did think it was interesting how he was sort of wording around the job part of this. You know, you mentioned, you know, the employees managing AI generated digital employees. Why 8 to 10 is a number? I don't know. I would be interested to see where that's coming from. But he also says we don't invest in AI to displace our talent. We invest in AI to help our employees be more productive, continue to protect consumers from fraud and to drive constant innovation and payments. That was a spokesperson actually from Visa that said that. So, you know, again, I think that the media, every time they're hearing these stories about all this efficiency and gains, they're going to ask the question about jobs. Yeah, and I think these are kind of like the boilerplate answers we're going to get for a while. That it's not meant to replace them. Like it's to give them tools to unlock things. And whether that actually because in that article they talked about layoffs at Visa. And so it's just they're trying to kind of head that that's not why the layoffs are happening, which may or may not be true.
- [44:08]
Guest Speaker
All right, so in some other news, we're seeing OpenAI taking steps to transform their corporate structure. They have entered into preliminary discussions with regular regulators to convert from a nonprofit to a for profit entity, which we knew was happening. And we're getting reports that they're currently engaged in early talks with both the California and Delaware attorney's general offices, marking the beginning of what is likely to be a complex regulatory review process. Now, this transition is not as straightforward as just changing your status. They have to figure out how to properly value and transfer the company's assets, including its AI technology portfolio. According to OpenAI's nonprofit board chairman Brett Taylor, any restructuring would ensure the nonprofit's continued existence and fair compensation for its current stake in the for profit entities. The company apparently plans to become a public benefit corporation, which allows it to, at least on paper, say, maintain its social mission while operating as a for profit business. And like we've talked about on past episodes, this timing here is a bit crucial because under their recent fundraising terms, the investments that they've raised could convert to debt if the restructuring doesn't occur within a couple of years. I believe within two years of the money being raised. So, Paul, we've talked about this being kind of one of the core near term challenges for OpenAI. Like how hard is this going to be for them to pull off?
- [45:40]
Paul Raitzer
Well, I'm kind of like laughing to myself at the moment because I'm thinking if Musk wants his vengeance, this is how you use your newfound influence and power, is you find a way for federal to throw a wrench in all of this. That would be the ultimate. Because this is why he was suing them. So this isn't me just like making up some drama. This is, Musk sued them over this thing that they, that they didn't function within this and they, you know, the money that was put in, they weren't functioning as this non profit. And so like there's, there's history here. Yeah. And if they can't do this, they're, they're in a whole heap of trouble if this process doesn't work. So, yeah, it'll be, it'll be fascinating to kind of follow this along. I mean, obviously they're not going to want information about this process to be leaked out because it's going to be challenging. But yeah, I feel like this got a lot more interesting now given Musk's influence on the incoming administration.
- [46:42]
Guest Speaker
Yeah, my guess is this week the timeline for this accelerated pretty quickly.
- [46:46]
Paul Raitzer
Yeah, they're going to try to, I don't think you can do this in a two month period, but they're gonna push every button possible, most likely.
- [46:54]
Guest Speaker
All right. And some other OpenAI news, they have acquired one of the Internet's oldest and most valuable domain names, chat.com. so this domain, which now redirects to chatgpt is, has kind of an interesting history because the domain was originally purchased last year by HubSpot co founder Dharmesh Shah, who we've talked about before, for over 15 million. That makes it one of the highest priced domain sales ever publicly reported. Now, Shah also revealed this past week that OpenAI was the unnamed buyer he had talked about selling the domain to. And he suggested that he may have received payment in the form of OpenAI shares. So chat.com is now totally in the hands of OpenAI. I mean, Paul, you know Dharmesh, given your Background, you own HubSpot's first ever partner agency. Like, seems like a bet for him that kind of paid off here.
- [47:49]
Paul Raitzer
Yeah, it was. I thought it was hilarious because Sam literally just tweeted chat.com and on November 6th and then like the tech world just like went crazy and Dharmesh posted the story of how it kind of happened on LinkedIn and, and on X. And yeah, he implied like, you know, he actually used the 01 reasoning model. He gave a prompt like, how much did Dharmesh sell it for? And then it was like he gave a prompt you could use and I wanted to try and figure it out. As far as I know, they didn't disclose anything. My guess is he didn't sell it for much of a profit, if any. He likely just exchanged it for OpenAI shares. Dharmesh is a notorious domain name collector. So, like, I have an issue with shoes. Like, I like to buy Nike shoes. I think Dharmesh buys domain names. Like, I don't know how many he owns, but my guess is it's in thousands. So, yeah, this is, I think for Dharmesh, like he said in his LinkedIn post, like, he doesn't need the money. Like, he's doing just fine. So I think this is just like fun for him. And, and I think the fact that OpenAI is using it, you know, gives Dharmesh some enjoyment and hopefully he, you know, made out with some OpenAI shares along the way. I mean, Dharmesh is one of my favorite people in the world. He's, he is one of those few people who lives up to your expectations when you actually get to meet someone in person. He has always been just a wonderful, wonderful person for me, for, for my business. I've known him going back to 2007. So yeah, if you don't know Dharmesh, it Couldn't happen to a better guy.
- [49:28]
Guest Speaker
And if you have a, an idea for a hot domain name you want to buy, maybe check with Dharmesh.
- [49:33]
Paul Raitzer
Yeah, you probably already got it.
- [49:37]
Guest Speaker
All right, so next up, Perplexity appears to be on the verge of securing a $500 million investment round led by Institutional Venture Partners IVP that potentially values the company at $9 billion. So this represents literally a tripling of the company's value from its previous funding round. Earlier this year. It would mark Perplexity's fourth funding round in 2024 alone. IVP was a significant backer. Already they led Perplexity Series B. Honestly, Perplexity's growth trajectory, Paul, seems kind of nothing short of explosive like we've talked about, you know, in comparison to Google. It's still very much a small fish in the search market, but this certainly seems like they're on the right trajectory.
- [50:22]
Paul Raitzer
Yeah, they gotta get out of their own way. They're still making a whole bunch of like PR missteps. And you know, I think Arvind has said he's, you know, learning lessons as a CEO. Like they've done some very questionable things from a business practice perspective, in my opinion. I love the technology. I'm not a huge user of Perplexity, but I feel like they're one of those like rocket ship startups that probably needs some. I don't know if this is the right way to say it, but like adults in the room, you know, in the early days of Google and things like that, when these huge explosions of growth happen, like you got to go get some people who know what the hell they're doing and don't have so many just self inflicted wounds. So I hope that they figure it out and they keep growing and they modernize the look and feel. As I mentioned last week, I think ChatGPT search sort of made Perplexity feel obsolete to me from a user experience. So, you know, I hope it keeps going and competition is good in the search market. I think it's, you know, pushing Google to, to think in a more innovative way and Microsoft and others. Yeah. So I, I would a couple things that would not Surprise me in 2025 is an adult like a seasoned leader is brought in to help, you know, keep, keep things moving in the right direction. If the regulatory stuff, this, this is the other thing is like I didn't think about this until this moment. Acquisitions might heat back up with the Trump administration because there, there's so many issues right now from a regulatory perspective that someone like Google or Microsoft, I don't think they could ever get an acquisition of Perplexity through in today's environment. Yeah, but come next summer, you know, maybe Perplexity starts becoming a really interesting acquisition target if, if things cool off from a regulatory perspective on acquisitions in the tech space. I know, interesting.
- [52:22]
Guest Speaker
Well, Perplexity is also in the news, not for as good stories we just covered. Exactly to your point, because Perplexity CEO Aravind Srinivas has stepped into also the middle of a labor dispute at the New York Times. So Times tech workers went on strike over wage increases and workplace policies. And at the same time, Srinivas publicly offered his company AI company services to the newspaper, which sparked some backlash. This was right around just days before the US presidential election. Times publisher A.G. sulzberg expressed concern about the strike's impact on election coverage. And Perplexity CEO responded directly on social media offering Perplexity services to ensure coverage remained available through the election period. Now, you know, this is, he kind of tried to later attempt to clarify this was an offer for merely technical infrastructure support, but some people pointed out that that's exactly what the striking workers were providing. So kind of put his foot in it a little bit. Like Paul, how seriously should we be taking this? Is it just like bad timing, bad communication? Is there more going on here?
- [53:38]
Paul Raitzer
Yeah, I mean I think it's just like I was saying, it's a tech CEO who isn't seasoned in this stuff.
- [53:43]
Guest Speaker
Yeah.
- [53:44]
Paul Raitzer
I don't think it was a strategic PR move to get the publicity like just to do it. I think he thought it was a clever idea and a way to get some attention and probably doesn't think through the, the ramifications to the brand and things like that. I, I again just, I don't know him, I don't know the company deeply but like from observing them for the last 12 to 18 months pretty closely, there's a lot of this stuff where it's just like if you had someone else in the room who's been through these things before, it could be a head of communications, it could be a president, it could be someone on the board. Like whatever it is, it's, there needs to just be somebody there that, that, that's helping along to avoid stuff like this. Right. It's just sometimes these self inflicted wounds are so obvious what the outcome is going to be. And again I, I don't think he wanted that backlash. Some people do this stuff for the backlash. Like Elon notoriously will do things just to cause the backlash. I, I don't think Aravind is, is that type of CEO yet. I don't know. I think he just thought it was a good idea and it ended up not being a great idea.
- [54:57]
Guest Speaker
Yeah, and clearly like we're also seeing that from a narrative perspective, people are extremely sensitive to anyone related to AI trying to be seen as potentially harming human workers. And that's a very real concern that people have.
- [55:14]
Paul Raitzer
Right.
- [55:16]
Guest Speaker
All right, so next up, Anthropic has unveiled Quad 3.5 Haiku, which is an upgrade to their fastest AI model. And it now matches the capabilities of large, larger models while maintaining its speed. It has very rapid response times and it turns out Claude 3.5 haiku surpasses Claude 3 opus on many intelligence benchmarks, even though it is optimized directly for speed. The model is being rolled out across multiple platforms, including Anthropic's API, Amazon Bedrock, Google Cloud's Vertex AI as well. So the pricing structure appears to reflect Anthropic's push for widespread adoption. It is a dollar per million input tokens, $5 per million output tokens, and there are potential cost savings of up to 90% through techniques like prompt caching and additional savings via Anthropic's message batches API. Now companies like Replit have noted substantial improvements in code related tasks, including tasks including reductions in errors and improved reasoning capabilities. So Paul, this is kind of related to one of our main topics like while there may be some issues with just how much progress we're seeing between each model generation, it sure seems like we're getting way better models for way cheaper still.
- [56:39]
Paul Raitzer
Yeah, and the implications to the average listener, the non developer, non technical listener here is the models are getting more powerful, they're getting way cheaper to build things on and to, to run. And so people are going to innovate and build more and more applications that you're going to be able to use in your industry. Or if you're at a bigger enterprise and you can go build things, it's getting cheaper and cheaper and it's going to continue to get cheaper for your developers. To build things for you is kind of again like, and this is just going to keep happening. So as these big frontier models were talking about, the reality is like your company may more likely to use like a 6 to 12 month old version of something or the smaller version of the current one. As confusing as all this is to build things to achieve what you want to achieve without having to pay for like the big model.
- [57:35]
Guest Speaker
So some other Anthropic news. Apparently Amazon is in discussions to make another massive investment in Anthropic. They that follows their initial $4 billion commitment last year. However, the new deal comes with some strings attached. Amazon wants Anthropic to use servers powered by its own Trainium chips, while Anthropic prefers Amazon servers that use Nvidia's AI chips. Now, for Amazon, getting Anthropic to adopt its chips could reduce dependency on Nvidia hardware, so it makes sense for them. For Anthropic, the decision could affect its flexibility to use multiple cloud providers or it operate its own data centers in the future. Now, Paul, can you kind of maybe unpack for us the dynamics here? On one hand, it kind of, you know, sounds a little bit like some inside baseball, but it does matter if certain companies are tying people into their ecosystems as part of their funding agreements.
- [58:36]
Paul Raitzer
Yeah, I don't know. On the surface, I feel like there's just gotta be a lot more to the story and like, how this partnership would work. I can't see Anthropic locking themselves in like 100% to something like this. And I'm sure there's again, it's, there's probably a whole bunch of other details, but more interesting thing is like Amazon's already put like 4 billion into anthropic as is, or 4 and a half billion, something we're talking about almost like 9 billion. And now we're, now we're starting to get into like the Microsoft open AI range where they've put like 13 or 14 billion into OpenAI. And again, like, go back to what I just said about regulation and acquisitions and stuff like that because, you know when, when I mentioned all the executives that were tweeting, you could throw Jeff Bezos in that group who tweeted, big congratulations to our 45th and now 47th president on an extraordinary political comeback and decisive victory. No nation has bigger opportunities wishing at real Donald Trump all success in leading and uniting the America we all love. So, you know, if regulations start to come down and Amazon sees an opportunity to make Alexa actually work again, and I don't know, like, I, that's one of the things I'm just really anxious to watch is like, how this all plays out. But they would be again, eight and a half billion dollars invested in a company that's supposedly valued at what, 40 billion is the rumor. So you're talking about a 20% equity stake in one of the frontier model companies. That's, that's not chump change.
- [60:07]
Guest Speaker
In other news, robotics software company is raising some eyebrows after securing a massive $400 million in early stage funding. So this company is called Physical Intelligence, and they just raised this money from some pretty significant tech industry heavyweights, including Jeff Bezos, OpenAI and prominent venture capital firms. So this investment actually values this startup at $2 billion. And basically what they're trying to do is create foundational software that can work across any robot platform. Their flagship software is called PI zero and it has already demonstrated some interesting capabilities, like it has successfully enabled robots to perform everyday tasks like folding laundry, bagging groceries and handling kitchen operations. So this is kind of coming as we get people like Elon Musk forecasting we're going to have literally billions of humanoid robots in the next couple decades. So ball, like, this is a pretty big early stage funding round. Like, how closely should we be paying attention to this company?
- [61:15]
Paul Raitzer
Well, I mean, obviously with the investors, they have that worth paying attention to. I think the bigger story here is just like robotics is, is going to be a major, major area of investment and progress. You're going to see probably a whole bunch of really cool demonstrations going into 2025. They're not going to be wide scale, it's not going to be mass market, but you're going to start to see really, really impressive stuff, especially as these multimodal language models are embedded in like, basically the brains of these robots. And the hardware keeps making progress from, you know, Nvidia to Boston Dynamics to, you know, Figure, which Antwerp or Amazon has a big investment in Figure, if I'm not mistaken. So I just. This is going to be a huge area to pay attention to. And sometime later this decade, you'll, you'll start to see these things really making an impression from a commercial perspective, like actually having commercial value and being productized. But we're a ways away from that still.
- [62:14]
Guest Speaker
So next up, OpenAI has secured kind of an interesting legal victory. A New York federal judge has dismissed a lawsuit filed by news outlets Raw Story and alternate that challenged OpenAI's use of their articles to train its AI models. Now, this case focused not on direct copyright infringement, but on the removal of copyright management information from articles used in AI training. So Judge Colleen McMahon, while dismissing this case, left the door open for the outlets to file an amended complaint, though she actually expressed skepticism about their ability to demonstrate sufficient legal injury. So this comes obviously as OpenAI has a number of open lawsuits, including one from the New York Times, which sued them in December 2023. And the judge's decision here actually highlighted a crucial distinction in the case that could have implications elsewhere. She noted that the real issue at stake isn't about copyright management information, but rather about compensation for the use of articles in AI development. So, Paul, when we're looking at this, obviously, as always, we are not lawyers, but how big a deal Is this for OpenAI?
- [63:30]
Paul Raitzer
Yeah, it seems like this is potentially a really important step. Again, like we got to talk to our IP attorney friends, but the one thread I was looking at said, you know, called out a few key points, facts on which LLMs train are not copyrightable. That seems like a really important distinction. Gen AI models synthesize, they don't copy, data sets they're trained on are vast. So no one one work is ever likely to be plagiarized and regurgitation is in quotes by an early LLM version is irrelevant if current versions won't do it. Those are four very interesting notes from the finding. So I. Yeah, I don't know. I mean, this is. We weren't expecting to see case law kind of like emerging this soon, and I wonder how much of an impact this one might have. And that's actually another area to consider with the next administration is what impact that has on the US Copyright Office review of, you know, these models and how they're used and how they're trained and if, if we don't maybe see some acceleration of changes to copyright law as a result of this, because that would allow more innovation and we know that's what they're going to want to do.
- [64:44]
Guest Speaker
And these four points you mentioned appear to me to be literally the foundational logic people like the New York Times are using, saying their stuff was stolen.
- [64:53]
Paul Raitzer
Yeah, again, I don't know how this stuff works, but it, it sure seems to imply that you could see some other cases thrown out if this holds up.
- [65:03]
Guest Speaker
All right, our last piece of news this week, Paul, is that Google accidentally, it appears, leaked details of its new AI assistant, which is called Jarvis.
- [65:12]
Paul Raitzer
Of course it's Jarvis. Of course, everybody names everything Jarvis.
- [65:18]
Guest Speaker
So this happened in the Chrome Web Store and there was like this premature reveal that kind of showed off a few things about what Google's thinking. For Jarvis, Jarvis is able to actually take direct control of web browsers to complete everyday tasks, at least according to the leaked description in the Chrome Web Store. So according to that description, which I believe is now taken down, the AI Assistant can independently handle activities like purchasing groceries, booking flights, and conducting research. Google appears to have removed the store page. This was originally planned to be unveiled in December, Paul. Regardless, it Sounds like we're about to get a possibly competent AI agent from Google.
- [66:02]
Paul Raitzer
My guess is you're about to get a impressive demo of an AI agent from Google. Like, I, I've said it many times on this, like I just, I, I, to, to use a tool like this. The computer used an anthropic, showed OpenAI's got the same thing that we're, everybody's working on this. They are not precise, they are not reliable, they have massive security concerns because you have to give them access to your credit card or your bank account or all these apps. I, I just don't see this being transformational technology in 2025. I, I think we're getting a ton of demos. There's gonna be a bunch of hype, there's gonna be a bunch of overreaction from media and influencers online who are like game changing and, and blah, blah, and this is the end of the world. Like it, it's just, it's just progress being made on an inevitable technology that may still take a year or two before it becomes mainstream. That's kind of like high level how I think about all this stuff.
- [67:00]
Guest Speaker
Gotcha. So maybe temper our expectations.
- [67:03]
Paul Raitzer
Yeah, they may show something and it may look amazing. And so did Sora eight months ago. Right. What do we now, as I say that they're probably going to release Sora in like the next three weeks. But like, you get my point. Like it's, and even, even though when they release it, we're going to have be able to get 10 seconds, not 60 seconds and things like that. So this is how this stuff works. Like you show these cool demos, you talk about it and then like, you know, maybe a year or two, like it's actually reality because Chat GPT changed how this stuff works. They dropped Chat GPT on the world and it changed everything. Now we're in this preview everything and then don't release it for 8 months, 12 months, 16 months, whatever it is, or release some early version of it. And that's kind of where we find ourselves in this AI timeline is everyone races to release demos of things that don't actually work or aren't really ready for us to use. So yeah, I think you just got to like have realistic expectations, but it's probably really impressive tech.
- [68:02]
Guest Speaker
All right, Paul, that's a wrap for this week. A lot of material to cover. Appreciate you as always. Demystifying everything for us, giving us all the context we need. As a couple quick housekeeping reminders, if you have not already, please go subscribe to our newsletter marketingaiinstitute.com Newsletter it's called this Week in AI. It gives you all the news you need to know each and every week in a very digestible format. Also, if you have not already and have the ability to please leave us a review. We really appreciate all the feedback and it helps us make the show better. Paul thanks so much.
- [68:39]
Paul Raitzer
Good stuff Mike. We will be back next week. We'll figure out if we're doing a Thanksgiving week episode after that, but next week we will be back. And final call ai4agencies.com if you are an agency or you use agencies, it'd be a great event for you to attend. All right. Thanks Mike.
- [68:57]
Guest Speaker
Thanks Paul.
- [68:59]
Mike Kaput
Thanks for listening to the AI show. Visit MarketingAI institute.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. Until next time, stay curious and explore AI.