164 | GPT-5 will change everything... again, Paris AI Summit - a missed opportunity, how companies are using AI right now, and more AI news you need to know for the week ending on February 14, 2025

0:00Hello and welcome to a business news episode of the Leveraging AI podcast. the podcast that shares practical, ethical ways to leverage AI, to improve efficiency, grow your business, and advance your career. This is Isar Maitis, your host. And like every week, we have a jam-packed week, but it's very different than previous weeks. In previous weeks, we focused mostly on releases and new transformation and innovation in AI. This week, we're going to talk a lot about the bigger picture. We're going to talk about three and a half big items, and then a lot of small rapid fire items. So in the big items, we have the Paris AI Action Summit that took place this past week, we have a glimpse to the future from Sam Altman and OpenAI, and we have two very interesting data sources to tell us what is AI used for right now.

0:43And the half deep dive is going to be the AI in the workplace report from McKinsey that was just released as well. So a lot to dive into. And then, as I mentioned, lots of rapid fire items, including some cool new releases from several different companies. So let's get started.

1:05As we mentioned last week, the AI Action Summit took place in Paris on February 10th through 11th, and a lot of leaders from multiple segments of both industry and government and so on showed up there, mostly Europeans, but also with support from all around the world, including the second sponsor that was India. So a big international summit to talk about multiple things. The previous two summits focused on AI safety, this one was dramatically different. So the key main topics they discussed, one was accelerating AI development, so understanding that it has a transformative potential and how can we push that in order to better humanity and the investment and technological that comes across.

1:46The first one is accelerating AI development. The second was managing AI transition. So basically, how do we ensure a smooth transition into an AI-powered future? And the third would be aligning AI with human values. All great topics to talk about. Now, multiple things came as an outcome of the summit. The first one is the AI Action Summit Declaration. The declaration was signed by 65 nations and organizations and focused on six key objectives. First one is promoting AI accessibility, basically making the digital divide smaller, which right now seems to be going in the wrong direction, ensuring responsible AI.

2:22So basically ensuring that open, inclusive, transparent, ethical, safe, secure, and trustworthy AI is what we deliver, which again, will be critical for our future. And it doesn't seem to be working that well right now. Fostering AI innovation. How do we enable conditions for AI development to avoid concentration in specific bodies and groups? Positive impact on labor. How do we encourage AI Diplomium to benefit the labor markets by positively shaping the future rather than by taking people jobs and trying to focus and foster sustainable economic opportunities, sustainability, so making sure that we don't burn the planet in the process of trying to build AI, and international cooperation.

3:02Now, while 61 countries and organizations signed this, there were two countries who declined to sign it, the US and the UK. So the US Vice President Vance, who was there, and we're going to talk in a minute about the keynote speech that he gave, he basically said that it includes too much regulation that could stifle innovation and hinders America's lead in the AI sector. And the UK mostly argued that there's no clear, practical solutions in it. And basically it's mostly fluff and hence there's no point. And they're calling for more clear implications and actions to be taken as part of this process.

3:38By the way, I 100 % agree with the UK statement. Also released the International AI Safety Report, which was the first one that was ever released. And the report was developed with inputs from 96 AI experts from 30 different countries, including some big organizations around the world. And they also announced a launch of two big European-based investments in AI. One is called Current AI with$400 million investment by the French government. the Invest AI Initiative, which the European Commission set up, and it's supposed to reach 200 billion euros in AI investments in Europe. Now, a lot of the conversations in the summit were how to balance the right regulation and safety measures and fair distribution of AI with allowing innovation to foster.

4:21Well, as I mentioned, US Vice President J.D. Vance gave a keynote address that was very, very clear in the direction that him and the current administration sees the right approach to AI. His opening sentence was, I'm not here this morning to talk about AI safety, which was the title of the conference a couple of years ago. I'm here to talk about AI opportunity. So that kind of set the tone. His speech focused on four different things. One is maintaining the US's global leadership in AI. So he basically said, we'll do everything we can to stay ahead in this process. His second point was creating pro-growth AI policies.

5:00So again, nothing that has to do with safety and security, everything that has to do with let's drive this forward as fast as we can. The third one was ensuring AI remains free from ideological bias. So that's actually a good one. The US government will work to ensure AI systems developed in America are free from ideological bias and are not used as tools for censorship or control. And the fourth one was maintaining a pro-worker growth path for AI. Again, that's a dream that they're all talking about. I don't see how that's happening definitely in the longer run, but I'm glad that this is a topic that everybody's focusing on, including the US.

5:35Now, he directly attacked the level of regulation in the European Union right now, and he claimed that while there's logical reasons behind it, it only leads to bad results while slowing down innovation. He also said that, and I'm quoting, when a massive incumbent comes to us asking for safety regulations, we ought to ask whether that safety regulation is for the benefits of our people or whether it's for the benefit of the incumbent. Or in other words, he's saying that when big companies support additional regulation, it's because they're already beyond that point. And all it is going to do is slow down new, faster moving companies who can develop innovative solutions from making us move forward.

6:16So the bottom line is very, very clear. The conversations in the AI Action Summit are important. All of them are really important. I would love to see this becoming an ongoing group of people from industry and academia and governments who meet regularly and define these subcommittees who will address each and every one of these issues and will actually come up with actionable things that we can agree on to move forward versus making these fluffy announcements and just talk because there's a real sense of urgency. And we're going to talk about the feedback from some big names who address the output of the Paris Action Summit.

6:52But as I mentioned, from my first personal perspective, it's a step in the right direction. And they just need to make it ongoing versus once in a blue moon. And to make it a lot more actionable with tactical steps that governments and countries and companies and organizations and our society can take to benefit from this amazing revolution while reducing the risks that come with it. One of the key people that addressed the output of this summit was Anthropic CEO Dario Amadei, who criticized it and basically labeled it as a missed opportunity. He's calling for a faster, swiffer, and clearer action from both industry and government, which aligns with what I believe as well.

7:29The exact quote is, the capabilities of AI systems will be best thought of as akin to an entirely new state populated by highly intelligent people appearing on the global stage. Dario outlined specific concerns about AI security across the board from the wrong types of governments, also to non-state actors, and also the development and deployment of military usages of AI by the wrong governments on the planet. Two additional points that he mentioned. One was that government should deploy resources to measure AI usage and impact across everything that's happening, and that policy should focus on ensuring equitable distribution of AI economic benefits.

8:10That's a huge point that a lot of people are talking about. We're going to talk about Sam Altman and his address of this in his blog post this week, but that's a big, big question. what is going to happen with the benefits that AI will generate and will only very few benefit from it and everybody else will suffer, or we will find ways to change more or less everything we know about the global economy and actually change that for the benefit of everyone. By the way, he's not pushing to slow down the development of AI. He's just saying that we need to invest as much in the development of processes and tools that will allow us to control the AI and make the best out of it.

8:46So he's saying, let's take a lot of the money that's invested today and just running forward and invest it in things like understanding how AI works, controlling it and distributing it equally. Now, he specifically called it a race against time, basically increasing the level of urgency. He's saying that by 2026 to 2027, he's expecting that AI will achieve a genius level, basically means it's going to be smarter than most people or all people on the planet. And that's around the corner. He's talking about next year. And then by 2030, it's his longest time estimate to achieving super intelligence, which is an AI entity that will be dramatically better than all humans at everything.

9:25So the bottom line is that current governance, both in means of current government, as well as controlling IT resources will become obsolete. And we need to develop more effective controls in order to benefit from this and reduce risks. And in parallel to the summit, Sam Altman has released several different interesting statements. The first one is called Three Observations. It's a blog post that he released on his personal blog post. I will share the link in the show notes, but I will quote a few sections and then I'll tell you what I think about it. So Sam says the following, over time in fits and starts, the steady march of human innovation has brought previously unimaginable levels of prosperity and improvements to almost every aspect of people's lives.

10:05I agree with that. Then he has his three observations, the intelligence of an AI model roughly equals the log of the resources used to train and run it. Basically, what he's saying is the more resources we're going to put into this, the more benefits we're going to get out of it as far as intelligence on the other side. So if you remember a couple of months ago, we talked about whether the curve of improvement is slowing down or not. And there was a lot of conversation because nobody was releasing new models. And that obviously has changed dramatically mostly with those thinking models. But Sam is saying the following.

10:36It appears that you can spend arbitrarily amounts of money and get continuous and predictable gains. The scaling laws that predict this are accurate over many orders of magnitude. So basically saying what he said all along, there is no wall, we pour more resources and we get more intelligence out of it. His second observation is the cost to use a given level of AI fall and lower prices lead to much more use. And then he's continuing to state the following. You can see this in the token cost of GPT-4 in early 2023 to GPT-4-0 in mid 2024, where the price per token dropped about 150x in that time period.

11:12Moore's law changed us about 10x every 12 months. And then he's stating that Moore's law has moved us forward about 2x every 18 months. And this is obviously 150x in the same amount of time, which shows you how quickly this innovation is moving, partially because costs of the same level of results is dramatically improving over time. And then his third observation is that socioeconomic value of linearly increasing intelligence is super exponential in nature. I know that sounds really confusing, so let's read it again. The socioeconomic value of linearly increasing intelligence is super exponential in value.

11:50What he basically means is that if you can create a worker that, let's say, writes code or does whatever specific admin work, and it now knows how to do that work, meaning it doesn't replace one person. You can now create thousands or millions of it. And so the more you increase the intelligence, there's a compounded output of that, A, because you can replicate it as many times as you want, and B, because that level of intelligence that can now help you write code faster can generate the next level of intelligence even faster than you could before. So that's two different levels why there is a super exponential in nature as Sam relates to that.

12:28And to make it very practical, I will use Sam's example. And now I'm quoting, let's imagine the case of a software engineering agent, which is an agent that we expect to be particularly important. Imagine that this agent will eventually be capable of doing most things a software engineer at a top company with a few years of experience could do for tasks up to a couple of days long. It will not have the biggest new ideas. It will require lots of human supervision and direction, and it will be great at some things, but surprisingly bad at others. Still, imagine it as real, but relatively junior virtual coworker.

13:02Now imagine a thousand of them or one million of them. Now imagine such agents at every field of knowledge work. Basically what he's telling us that every junior and mid-level position will be able to be replaced by these agents sometime in the relatively near future. That obviously changes everything we know about the workforce. And going back to what I said about the Paris summit, I think that's the biggest and scariest aspect in the near term of AI risk to our society. Those of you who've been listening to this podcast knows I've been saying this for a very, very long time. I do not see how we save jobs from this wave of AI.

13:42And I know people saying it's going to generate new jobs. First of I find it very hard to understand what kind of jobs because it's very, very different than previous revolutions. This time, AI is taking over the one thing that made us more adaptable and be able to come up with new jobs, which is our ability to think because it can outthink us in some cases already right now. And then the last thing he said is that ensuring that the benefits of AGI are broadly distributed is critical. The historical impact of technological process suggests that most of the metrics we care about, health outcomes, economic prosperity, etc., get better on average and over a long term.

14:16But increasing equality does not seem technologically determined, and getting this right may require new ideas. He's trying to paint this in a positive way, but what he's basically saying is that technology has driven broader and bigger inequality in our society, and there's a very serious risk that this will be an accelerator of that particular phenomena. And as I mentioned before about the Paris Summit and about the feedback from these people, I think that's a key thing that we have to figure out. And we have to figure it out very, very fast. But in parallel to dropping this blog post, Sam also tweeted an AI bomb on X.

14:53So again, I will read segments of his tweet and then we'll tell you what I think about it. So OpenAI roadmap update for GPT 4.5 and GPT 5. We want to do a better job of sharing our intended roadmap and a much better job at simplifying our product offerings. We want AI to just work for you. We realize how complicated our models and product offerings have gotten. We hate the model picker as much as you do and want to return to magic unified intelligence. We will next ship GPT 4.5, the model we called Orion internally, as our last non-chain-of-thought model. After that, a top goal of us is to unify O-series models and GPT series models by creating systems that can use all of our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks.

15:40In both ChatGPT and our API, we'll release GPT-5 as a system that integrates a lot of our technology, including O3. We will no longer ship O3 as a standalone model. The free tier of ChatGPT will get unlimited chat access to GPT-5 as a standard intelligence setting subject to abuse threshold plus subscribers will be able to run GPT at higher levels of intelligence. Okay, let's break this down. So surprisingly, a day before Sam wrote this, I recorded a video that I actually released this Friday of me bitching about AI complexity. And I started with OpenAI, ChatGPT, Dropdown menu, and all the different functions and what's available in one aspect of the product and not available in another.

16:25It's really entertaining and you should go and watch it. I will share a link to it in the show notes. If you have five minutes to see how frustrated I am, and probably you are, so you can relate to that, go and check out. You can literally open your phone right now and click on the link and watch that video. I'm sure you will enjoy it. But going back to Sam, what he's saying is that they understand that frustration. They understand that we have no clue which product we need to pick for specific tasks that we need to do. And people like me will try. I will actually experiment with it and try different things for different use cases.

16:53Most people just get confused and will either do nothing or will just pick, I don't know, a random one or the top one from the menu. That's not what this is supposed to be. This is supposed to be intelligent and supposed to understand our needs and supposed to work according to our needs. And that's exactly the direction that they're going, which is very, very exciting. From all the comments that we've seen around, GPT 4.5 will be released within the next few weeks. But then the other interesting thing is that they're planning to give more and more capabilities into the free tier with quote unquote standard intelligence settings.

17:24So it's probably going to be smarter than everything we have today. And still it's going to be free. Going back to his other statement about the dropping costs. This is obviously driven somewhat by the competition that is coming from other competitors, mostly open source models like DeepSeek. And now to our third big topic today, which is what is AI used for right now? And we have two interesting sources that provide us a glimpse into that information. The first one is Anthropic. Anthropic just released their economic index study. What they basically did is they anonymized Claude AI conversations, basically everything everybody's doing with Claude, and they looked at the data set and tried to compare it to specific tasks and jobs.

18:02And what they found is very interesting. So the first is that AI usage shows dramatic occupation-specific patterns. So 36 % of jobs using AI at least for a quarter of their tasks, while only 4 % of jobs use it for three quarters or more of their tasks. Now, even within these tasks, they found that 57 % are augmenting their work with AI versus 43 % that just automate specific parts of their work. So still most employees use it to help them do what they do versus to replace what they're doing. Now, while this sounds great, I'm like, okay, most people are using it for one quarter of their tasks, probably the tedious stuff they don't like to do anyway, and they're augmenting the work while they're replacing the work.

18:45Well, my problem with that statement or the positive aspect of that statement is that we are very, very, very early in the game. I teach AI courses. I do workshops for companies. I speak on large stages. I talk to a lot of CEOs and business leaders about AI. And still, most companies, most leadership teams are clueless about where AI is going and how to leverage it properly. And lack of training is the biggest and number one thing I hear again and again. And we're going to get more to that in a minute. But combine that with the fact that AI itself is getting better and AGI and ASI are coming sometime in the next few years.

19:20And this whole concept of it's doing only a quarter of our tasks and we're just augmenting what we're doing is going to change dramatically. Now, to dive a little more specific into some of the findings, computer and mathematical roles dominate in 37 % of usage of anthropic arts and media with 10%, education at 9.3 % and office and admin at 7.9%. That's not surprising to me, By the way, I think Claude 3.5 Sonnet is just really good at writing code, and it's really good at creative writing. And so that's the two things that show up in the Anthropic study. I'm sure if there was a study done by other tools, including video generation, image generation, other modalities, and so on, we will have a much broader and more accurate view of what AI is actually being used for versus this study.

20:04I'm not saying anything wrong about the study. I love the fact that Anthropic is sharing it. I'm just saying it's very, very biased. As an example, Anthropic 3.5 Sonnet is the number one pick tool in code generation tools, such as Cursor. And so a lot of people are using Cursor, are using Claude. And if they're using Claude in a code generation tool, then obviously that's the only thing they're using it for, which shifts the results of this particular survey. Another interesting finding in this survey is that the highest AI adoption happened in mid to high wage occupations. So very low usage on low-paying jobs and relatively low usage in very high-paying jobs.

20:42By the way, I'm not surprised by that one because very high-paying jobs are usually more strategic in nature. So the CEO and C-suite people of the world and very low-paying jobs, I think, are just not exposed to what's possible with these tools. And many of them are also manual labor, hence they're still not as impacted. So that makes perfect sense to me. Now, in parallel, Google released 50 use cases in 50 states as a follow-up to their ad in the Super Bowl. And they basically gave us 50 examples of companies on how they're using AI right now across multiple sectors. I love this particular information from Google.

21:15Again, I will share the link in the show notes so you can go and check it out yourself. But they have found multiple examples across multiple industries across the entire U.S. on how small to mid-sized companies are actually using AI in interesting ways just to give people ideas of what AI can be used for. The common threads are increased efficiency and productivity. So they're saying that AI tools that automate tasks bring employees to focus on more strategic and creative work, which is awesome, enhance communication and collaboration. So the fact that AI can analyze large emails or summarize meetings or translate things is another common usage of AI across all these different use cases.

21:49data-driven decision-making. Companies who did not have a big BI or data scientist capability can now analyze data and make better decisions. It's something I do with my clients all the time, and it's nothing short of magic. And improve content creation, which is usually the first thing that people go to, despite the fact it probably generates the least amount of value compared to all the other stuff you can do with AI. Now, the examples they gave come from across every aspect of businesses, from agriculture, where farmers leverage AI to analyze data and predict crop yields and optimize resource allocation.

22:17Education, where institutions are providing personalized learning experience and automate administrative tasks and helping teachers prepare and students work and so on. This is, by the way, from my perspective, maybe the biggest promises of AI right now that we should start using a lot more intensively. Food and beverage. So restaurants are using AI to manage inventory and predict demand and optimize pricing and stuff like that. And then there's healthcare and manufacturing and non-profit and retail and technology and travel and hospitality. So you can go and read these examples. They actually will give you great ideas on what you can do in your business, even if you're a small business and don't have a lot of resources and don't know a lot about IT.

22:53And so I think this is just a great quick read for you to go through and just brainstorm ideas on what you can do in your business. And as I mentioned, we have a half item today, which is AI in the Workplace, the report from McKinsey. And it explores the transformative potential of AI in the workplace and what leaders should do and have to do in order to harness the full potential. Now, the report was built based on surveying 3 ,600 employees and 238 C-suite executives from US, Australia, India, New Zealand, Singapore, and the United Kingdom. So a lot of Western-like economies. The findings are very interesting.

23:28Despite significant investment in AI in the last couple of years, only 1 % of companies consider themselves mature in their adoption of AI. That's not surprising to me at all. Again, I talk to companies all the time. Most people are still in very early stages, but only 1 % of companies say, yes, we figured it out. That being said, 92 % of companies are planning to increase their AI investment in the next three years. Another very interesting finding is that employee readiness are ahead of leadership strategy, and I see that all the time, more and more employees, standalone initiatives of people to embrace AI and they're trying stuff on their own without any leadership or direction from above.

24:09And in addition, employees are open and excited to see their company implementing AI despite the lack of action from their leadership. Now, they mentioned in the report the super agency concept. That's a concept that was coined by Reid Hoffman in his book called The Same Thing, Super Agency. And the idea here is that individuals empowered by AI can supercharge their creativity, productivity, positive impact, and so on, basically looking at the positive impacts that AI can have on people and companies in our society. But what they're saying is that part of the approach that we're seeing right now is the wrong approach.