215 | GPT 5 Massive backlash 🤯, AI pushes stock of a cliff (Gartner, Monday, SAP), Learning mode and connectors race, and more important AI news for the week ending on August 15, 2025

23:46It's the same exact thing. It has a name, and it has instructions, and you can connect files to it, and it will run exactly like your custom GPT, but you can pick the model it runs against. And now you can A, use it right there and then, but you can also connect it to anything external, like a user interface that you build with ChatUpt or an automation that you build on Make or NA10 or Zapier, et cetera. So it also provides a lot of additional flexibility doing it this way. I'm in the process of developing a course about it, and I will let you know as soon as it's ready, and I'm going to teach you how to build assistants and how to connect them to workflow automations because this is one of the most powerful capabilities that exists today.

24:20for almost free, you can completely revolutionize multiple aspects of how your business is running. So more on that in the next few weeks. Staying on the topic of ChatGPT, the verbatim GPT system prompt surfaced on GitHub. So you can actually see what is the system prompt that GPT-5 runs with. And there's a few interesting points. Again, you can go and find the whole thing and read the whole thing. It's not that long, but a few things I want to highlight. GPT-5 is mandated to use web searches for fresh, niche, or high stakes information. Basically, it needs to verify the answer that it's giving every time it's not mainstream or every time it touches a topic, it does not have a lot of information about.

24:57It is also using what they're calling recency need score from zero to five to reduce errors on stuff that is recent information, and it's defining how it should search the web to find such information. For more sensitive topics like finance, health, legal matters, etc., JudgeUPT must, and I'm quoting, always carefully check multiple reputable sources to ensure reliable responses. This is great for all of us because this is a way to reduce hallucinations. If it has to find more than one source and verify the information, it means it's going to provide us more accurate information. GPT-5 is also prohibited from storing creepy personal details, including race, ethnicity, religion, criminal records, precise geolocation, union membership, political views, or health information.

25:39So in its memory function that remembers things about you, which I find extremely helpful, it will not remember all these things about you, which is good news from all of us from a data security and privacy perspective. By the way, the exception to all of those instructions is if you explicitly request it to remember these things, it will remember them despite the fact that the rule is against it. Now, GPT-5 is also barred from reproducing copyrighted material such as song lyrics, even if prompted specifically by users. So there are cases that the system prompt tells it to override the system prompt by user request, and there are cases where it's saying exactly the opposite.

26:13Despite of anything the user says, don't do one, two, or three. All of these things make perfect sense. It just gives us a glimpse on how these models actually work under the hood. And if you want to read the entire system prompt, just sign up for our newsletter and there's going to be a link in there to read the entire thing or just Google it and you'll find it very quickly. Touching again on the accuracy of GPT-5 versus previous model, a company called Vectara tested chat GPT-5 against previous models on its hallucination level and it scores 1.4 % on its hallucination rate, which is relatively low.

26:44It is outperforming GPT-4 that had a 1.8 rate and GPT-4-0 at a 1.49, but not by a lot. Again, it's 1.49 down to 1.4%. It is still significantly less than people think it is, right? People think these models hallucinate a lot. We're talking about once every hundred things that it's saying. That's relatively low. That's probably better than most humans, to be fair. That being said, it is less accurate than O3 Mini. So O3 Mini high reasoning model scores an impressive 0.759 hallucination rate. So less than 1 % and significantly less than 1.4 % of GPT-5. The flip side, the model that is hallucinating the most out of the leading models right now is, I would say not surprisingly, Grok 4 with a 4.8 % hallucination rate.

27:29And in between that and GPT-5, there is Gemini 2.5 Pro with 2.6%. So now you kind of know where these models are right now when it comes to hallucination rates. Another interesting thing that came up this week is OpenAI revealed a comprehensive prompting guide for GPT-5. And if you're asking yourself, why the hell does GPT-5 need different prompting than the previous models? Is it prompting, just prompting? Well, the answer is this model is extremely good at following instructions, which means if you gave wishy-washy instructions previously, you could get away with it. The best model at that was O3.

28:02O3 was extremely good at understanding what you want and working with not perfectly defined prompts. That becomes a problem on GPT-5. Now, this is a blessing and a curse. The blessing is if you know how to write highly detailed, well-defined prompts, you are going to get significantly better results. I can tell you that in my personal experimentation in the past week, I'm able to do things that were practically impossible with previous models with the amount of details you can put and the amount of steps you can put in a single prompt. So previously things that I had to do in three, four, five prompts, I can do in a single prompt right now and the model follows it to the T.

28:34The problem with that is if you don't do that, you're not going to get as good results as you've gotten before, which means being a better prompter is actually going to serve you very well, even better today than it did before. The other thing that they shared in this guide, and again, this, I highly recommend you go and check it out. And we're going to put a link to that in the show notes. They're saying that any contradiction in the instructions is going to be problematic. So if you're saying one thing in the beginning, even if you're saying it vaguely, and then you into details, and one of the details contradicts what happens in the beginning, it is going to confuse the model.

29:06It's going to cause it to think a lot more and sometimes come out with the wrong conclusion. Now, on the API side, you can actually add additional parameters like the level of verbosity you want as one of the parameters, which will basically define how long and how detailed the answers of the API are going to be. And they added a few other capabilities to control the thinking aspect of GPT-5, which are now available also in the regular drop-down menu, but that wasn't available in the beginning. They also shared that GPT-5 is really good at what's called meta-prompting, which is basically asking GPT-5 how to improve your prompt for GPT-5.

29:42It actually generates very good results in either asking for more details or adding more details on its own. I use this all the time. I will write a prompt. I will explain what is the goal that I'm trying to achieve. I will give it enough context for it to understand what I'm trying to do. And I will ask it to ask me additional questions in order to provide it with better instructions. This delivers significantly better results from my testing in this past week. So bottom line from a prompting perspective for GPT-5, huge benefit for very detailed prompt, less effective results if you are not doing that, which means you have to start doing it.

30:15They also have a segment there about how to better use it for coding. So if you are using OpenAI for coding either in ChatGPT or in Cursor or in any other platform, it's worth reading that portion as well. Since I think most of you are not coding, I'm not going to dive into that segment. Another big news from OpenAI this week is they added a lot of new connectors. This is now a full-blown connector race between Claude and ChatGPT. It's actually surprising to me that Gemini is still not in this race, but now you can connect ChatGPT to Box, Canva, Dropbox, HubSpot, Notion, Microsoft SharePoint, and Microsoft Teams without leaving the app, basically just by going to the connector section, adding these connectors, and then you can pick them when you're running specific queries, which is obviously very helpful.

30:56Now, people with the Pro account, with a$200 a month account, gain additional connectors for Microsoft Teams, GitHub, Gmail, Google Calendar, Google Contacts, and so on and so forth. I would assume that all of these will roll down to everybody else, or at least to the other paid users that are paying 20 bucks a month. But for now, there are some benefits of using the Pro account when it comes to connectors. I've been using these connectors on Claude previously, and they provide huge benefits because they allow you to search your data and your information across multiple platforms and connect the dots.

31:26Basically, the biggest promise of AI is allowing us to connect the dots across siloed data from different platforms. And is it going to do it perfectly well? I don't know yet. From my test of using Gemini to collect information across multiple Google platforms and trying to do the same thing with Cloud, Gemini did a better job than Cloud. So Cloud missed more stuff in collecting that information, but Gemini also missed stuff. So I think these tools are not perfectly there yet. I think it's definitely a step in the right direction that will give us a lot more functionality and value when using these models.

31:58Now, if you want to test it out in ChatGPT, you got to go to settings and then in settings, go to connectors and then define the connections that you want to set up and give it permissions. And then you can start using them and turn them on and off for specific chats. This could have been an entire episode on its own on OpenAI, the rollout of ChatGPT. And I'm going to switch to the impact on jobs and industries overall. And there's a few interesting data points that I want to share with you. This week, Gartner's stock took a nosedive. It basically went down this month from$363 to$238. That is a 30 % drop in Gartner's valuation.

32:33And the main reason for that is there is no need for Gartner anymore. It should not exist because right now, using tools like Deep Research and Code Interpreter and the ability to create visualization, you can get the same data that you're getting from Gartner, only perfectly personalized to your particular need, your particular niche, your particular situation, the things that you're trying to figure out. So what used to take a very large company for decades to collect that information, synthesize that information and create a report for the masses, you can now do for yourself for 20 bucks a month.

33:06So if you are going to use Chachupiti or Claude or Grok or Gemini, it doesn't matter, and use its deep research to do the research that you want, and then allow yourself to fine-tune the information by asking additional follow-up questions, and then ask it to create whatever visualization you want while analyzing the data, you can get two results that will be as good, and in many cases better just because they're better customized, not because you're a better researcher, than what you can get from Gartner or Forrester. And you can do this without paying them the crazy amount of money that you need to pay them in order to get access to their information.

33:39Now, their CEO's explanation was that they lost major revenue from government contracts and stalled deals. But I think the reality is, exactly what I said, is more and more contracts are going to get canceled because less and less companies will find this valuable because they'll be able to do this on their own without paying Gartner. Or like Mary Shia, who's a PhD and a co-founder of Meerkat, said, we are in the final chapters of Gartner and Forrester. But if you think they're the only sector that is getting hit very, very hard by AI, another example is Monday.com. Monday.com is a highly successful startup from Israel that builds project and teams management solutions that are used by millions of people around the world.

34:19And its stock took a 26.5 % nosedive after issuing its Q3 revenue forecast. And that's despite the fact they were beating Q2 earnings. Now, the real reason is investors are scared that people will use AI to do some of the things and over time, maybe all the things that Monday can do. And I shared with you on this podcast many times before, the fact that Monday has 347 different features, I don't know the exact number, I made it up, but many, many features doesn't mean most companies use most of these features. Most companies probably use 10 or 20. And you can now vibe code many of these capabilities on your own, tailoring it to your needs, connecting it to your applications without having to pay a monthly subscription fee to Monday for every seat for every person in your company.

35:04The same is true across other businesses as well. You want a different one? SAP. SAP went down from 308 to 277. Again, more than a 10 % decrease in its valuation. Why? Same exact reasons. Many, many things that SAP does, even though it's a big infrastructure layer for many different companies, more and more things that SAP deliver can be now done with AI without paying SAP. Does that take away the need to use them? No, or the answer is not yet. But investors look at the far future to get long-term returns. And these returns are at risk right now with many software companies. Now, the other thing that is happening that is impacting companies in the job market is shifting funding internally in companies from employees to AI.

35:47Another example this week is Amdox. Amdox is another giant company from Israel that generates billions of dollars of revenue every single year. and they're just announced another layoff round that might get to thousands across their 29 ,000 global workforce. The company has been investing heavily in developing an AI layer to their product and that funding needs to come from somewhere. And so they're laying off employees despite the fact that the company is doing very well financially. Now, this is not the first time Amdocs is doing a layoff round. It's the fourth time in three years. So basically since the launch of ChatGPT 2023, and then into 2024.

36:25And now in 2025, they are laying off employees while they're pouring more and more money into developing their AI solutions. Another company that is doing the same thing is Oracle. Oracle is eliminating hundreds of jobs globally in its cloud unit, one of its most successful units in the company that has seen huge growth in this past year or two. Now, some reductions are tied to performance issues, but the primary driver is a strategic shift to investing in AI infrastructure instead of investing in employees. And again, they're laying off people while their cloud revenue grew 27 % this past quarter.

37:01And very similar to what we see from Microsoft and from Amdocs and from other giants, this is not their first round of layoffs. So they laid off people in 2024 and in 2025 for approximately 11 ,000 jobs that were cut. Now, these are just the canaries in the coal mine, if you want, because this is going to go way beyond the tech industry. A new study from Sanford that is titled Future of Work with AI Agents has surveyed 1 ,500 workers across 104 occupations to map the impact of AI and AI agents on their workforce. Based on the results of this research are saying that 70 million US workers face major transitions due to AI agents.

37:42Making it a little more specific, they're estimating that 80 % of employees may see AI affect at least 10 % of the tasks that they're doing, and 19 % of employees are facing disruption to over half of the tasks that they're doing. So one in every five employees in the US will have half the things they're doing during their job, doing as part of their job today, will be disrupted by AI. Now, despite that, most workers express positive attitude towards AI automation, with 46.1 % rating their desire to use AI in specific tasks as three or higher out of five in a five-point scale. And that's despite their concerns or potentially losing their jobs.

38:19The top motivations for automations are freeing time for high value work. That's in 69 % of the surveyors from the people surveyed, repetitive, so eliminating the need to do repetitive tasks with 46%, stressfulness, 25%, and quality improvements with 46%. This is a huge one, right? We tend to think that most people want to use AI to reduce exactly what we said before, tedious work. But the reality is about half the people saying it's actually improving the work that they're doing. I definitely see that every time I use AI across multiple aspects I use it. I actually get better results than I would have done it myself, definitely when you compare it to the amount of time that I'm putting into it.

38:55But even in an objective way to compare the actual output, regardless of the amount of time put into it, as an example, the proposals that I'm writing are all written by AI. I go through them, I make final changes and do stuff like that. But the majority of the proposal is written by AI. And because it knows how to capture the actual language from the customer, it writes better proposals than I ever did. And it does it in seconds instead of the two hours that it would take me. And on the flip side, the key fears of resisting automation come from lack of trust with 45%, job replacement with 23%, and absence of human touch with 16%.

39:27The interesting and not surprising thing is that the lack of trust is getting reduced significantly after the employees actually start using AI automation. So seeing what AI can do, going back to my example with my CEO girlfriend is a great way to increase trust in how these systems work. Because once you use it for a specific use case in which it's actually working well, you gain trust and then you're willing to use it for more things. This again comes to education and picking the right use cases as your initial test cases for yourself, for your team, for your company, etc. A different survey was done by Workday.

40:00They surveyed over 3 ,000 business leaders, found some interesting additional insights when it comes to AI adoption. The first one is three quarters, 75 % of workers are comfortable working alongside AI agents, but only 30 % would agree to take orders from AI agents, which is interesting. I think that is going to change over time, mostly because many people are not going to have a choice. Same findings here, direct experience with agents builds confidence as familiarity increases employee trust in AI systems. So almost the same exact finding as in the other survey. 90 % of responders to this survey see AI boosting productivity, but fear that it will increase the demands from their bosses.

40:40And they fear it's going to erode critical thinking and reduce human interaction. So on the one side, people definitely see the benefits. On the other side, they have lots of fears, which has been the world of AI since the launch of ChatGPT in November of 2022. I've been on this roller coaster of, oh my God, this is amazing too. Holy crap, what is going to happen to the world and what my kids are going to do. And I go through that every single day. And this is the feeling across the board. Now, if you think that the leaders that are pushing this industry forward, like Sam Altman, Dario Amede, and so on, have answers, the answer is they don't.

41:11And a very big proof of that came from an interview with Sam Altman this week, who admitted in an interview that AI will eliminate many jobs, but he insists that it will create a lot of thrilling opportunities. And he was saying, and I'm quoting, in 2035, that graduating college student could very well be leaving on a mission to explore the solar system. Now, I want to give you three thoughts on this statement by Sam. One, there is no way that from a capital investment perspective, there are going to be jobs from graduates of colleges in the next seven years, enough for all of them to be exploring the solar system.

41:44Can one or two do it? Yes, but they can do it right now, right? There's enough space agencies right now that send people to space for exploration or for tourism or for many other things. And that is definitely going to grow between now and 2035, I do not see this as a real job opportunity, especially when you're comparing to the amount of jobs that are at risk, as we've seen from the previous surveys. So that's number two, is even if this is a really exciting and thrilling opportunity to explore new things, how many people will actually get access to that versus how many jobs are going to be lost?

42:16And the third thing is, which none of them is addressing, is how is this transition going to happen? Like what is actually going to happen to the workforce? how will that impact the needs from an education perspective? And how will the education system adapt in order to allow us to do this? All based on Sam Altman in the next eight years, I see many, many, many question marks, and I see very few answers coming from anyone. So going back to my personal roller coaster, this is one of the things that really troubles me when not a single person seems to have answers to those particular questions. Now, since we touched on education, there was a very interesting and disturbing article on the New York Times this week.

42:52It was an opinion piece that was called What AI Really Means for Learning, AI Role in College Classrooms and Critical Thinking. This was an interview done by a New York Times columnist together with two people. One of them did interviews with relevant people from academia and students and so on. And the other teaches psychology at UNC Chapel Hill. And they basically said that AI has no value and it's just a disturbance in the classroom. They rated it two out of 10 with its ability to benefit higher education. The professor at Chapel Hill called Chachupiti a mid-tech, basically an average hyperinflated tool, a long line with other ed tools and promises like TVs and Chromebooks that were promising to improve education and actually didn't.

43:36Now they're saying that the students are fear-fueled into embracing AI because of the current job market issues, especially for entry jobs that we talked about many times on this podcast. and that Gen Zers are now developing and creating LinkedIn profiles as early as middle school. So they have something to talk about when they try to get job interviews and that's driving them to use AI across the board because they fear that otherwise they're not going to get a job. Both of them have given examples, which I don't know if are true or not, on how bad hallucinations can be and why it's not a tool that can actually be trusted for anything in education.

44:08And they were calling for a lot more government intervention and they're saying, and I'm quoting, if AI causes some great harm, who do we call? Basically, what they stated is that there are no real federal level guardrails. And if anything, it's the other way around. They're pushing very, very hard because of the competition with China. So where do I sit on this particular thing? I think this is a horrific piece that a publication like the New York Times cannot put out there without getting people to show the other side. I can guarantee you that these two ladies have no clue how AI can be used in general and definitely how can it be used for education.

44:40I think in general, our education system, instead of finding ways to leverage AI, to use it to provide potentially the best education we ever had the opportunity to give, where you can provide personalized education paths to each student that will be adapting in real time to their current level of knowledge, to their real time level of being able to focus at this moment in time, to the path that will make it easiest for them to learn, whether it's through games, through reading, through exercises, through testing, through communication. communication, any style of education is available through AI on a personal level that can be literally the best gift education has ever gotten.

45:18And interviewing people who have no clue how to leverage AI effectively to give an opinion on how AI can be used in education and putting it as a story on the New York Times is, from my perspective, an embarrassment to the New York Times. Now, I'm not saying there's no risk. I think there are huge problems with the way AI is handled right now in the education system. But it is because, again, because they're not investing time and money and resources in educating the educators, educating the system, the people who make decisions for our education system on how AI will change the world and how the education system should change in order to adapt to that.

45:54And that is a very scary thought, especially for me on a personal perspective when my daughter is going to college in the next few months. Staying on the topic of education, I shared with you a couple of weeks ago that OpenAI Revealed Study Mode that is available in ChatGPT. Well, Anthropic, and we're going to talk a lot about the releases in the next few segments, have just released their learning option as part of the options that you can pick. And you can pick it. It's kind of weird, but it's in the style drop down menu in Claude. So if you're in Claude and you go to styles, there's a different styles that there.

46:22There's the styles that you can create. And one of the styles is learning. And very similar to the option in ChatGPT, instead of giving you answers, it's going to use a Socratic approach and ask you questions and push you to understand on your own and help you to figure out the answers in a way that will be very supportive and exploratory, which I find brilliant. Drew Brent, Anthropics Education Lead, was discussing this topic and sharing that students themselves, and now I quote, they themselves realize that when they just copy and paste something directly from the chatbot is not so good for their long-term learning.

46:54I think that's very obvious to students. One of the things that is happening in universities and high schools around the nation right now is that more and more the testing are now in person, on paper, without any computers, because of the fear of the students using AI. So the students understand they cannot use AI in the test, which means they actually have to learn, which means they cannot just do their homework with AI because then they will fail the test. So providing solutions for that in ChatGPT, Claude, and now Gemini as well is very, very helpful, which leads me to the next thing that Gemini just introduced the same thing.

47:21In Gemini, it's called guided learning, and it follows the same exact concept as ChatGPT and Claude. You can select it and then tell it what you're trying to figure out. And then instead of giving you the answer, it is going to help you learn it and understanding on your own. One of the cool things in Gemini that is from what I tested shortly is more advanced than the other ones, is that it will create and bring images, diagrams, videos, and interactive quizzes on its own in order to help you do this when you have to prompt for that in Claude and Chachapiti. And I think most people don't know that they can prompt for that, so they're not going to benefit from that.

47:51But on Gemini, it does it on its own. I think this direction from the three main providers is fantastic. And I would like to see more and more of that and find ways to integrate it into our education system. From a very personal perspective, my son loves math. And when they went on summer break earlier this summer, he came to me after a few days and said, hey, dad, can you give me math problems? Because he loves solving math problems and there were no more homework. I know, a weird kid. But anyways, I said, you know what, I have a better idea for you. Let's build a math game. He's like, oh, what kind of a math game?

48:19He said, I don't know. You tell me what kind of games you like playing right now. And he really likes this very low graphics soccer penalty shootout game that he found online that he played a lot. I said, I want to turn this into a math game. I said, okay, this is a great idea. Let's do that. So we use that as a template, kind of like the look and feel and shooting penalties. And we turn it into a one V one game where the game will give a question in math for his level to the goalie. And then a question in the same level to the kicker. And depending on how accurate their answers are, it will change the chances of the ball going into the goal.

48:50And then we added more and more functionality and we made the questions more random and we added more levels to the game with tougher questions. And we showed on the side the actual questions and the answers that were given and the correct answers. It was a great thing. And for about three days, everybody in the family, including myself, my wife and his siblings, played this game, everybody solving math problems. Every teacher and every student can do the same thing right now. Find something that excites them, that they actually enjoy doing and build a learning application around it in minutes.

49:19So they will learn AI because they will learn how to build applications and they will then use the application to actually learn the thing that they're trying to learn. Everybody wins. This is where we should be going instead of giving it a two out of 10 on the scale of how supportive it is in education. Staying on Anthropic and Claude, they just introduced a really cool functionality, which is the ability to prompt Claude in a conversation to look for previous conversations and find relevant information and use them as reference in a new conversation. So different than the chat GPT persistent memory that just remembers things about you, Claude took a different approach.

49:55You can basically said, find all the conversation in which we talked about topic X, you will find them, and then you can pick the ones you want to reference as context in this new conversation, basically continuing from where you stopped or even combining several conversations into one piece of context for this new conversation. I find this brilliant. I think it's very, very helpful. It has obviously pros and cons compared to the ChatGPT setup. I actually love the ChatGPT setup. I teach ChatGPT everything about me and I ask it to remember that because it gives me significantly better and more accurate results over time.

50:26But in this particular case, I think it could be combined with the ability to pull in specific conversations in order to use them as context for a new conversation. So kudos for Claude 2 including that. This feature is currently only available to Macs and Teams at Enterprise tiers, but it will roll out to everybody else sometime in the near future. Staying on Claude, another big and helpful update is that Claude Sonnet 4 now has a million tokens context window. So those of you who are not aware, all these models have what's called a context window, which is the amount of memory they basically have for a single chat.

50:58And once they're getting to the end of that context window, and definitely when you pass it, it starts getting cuckoo and forgetting things and look a little drunk and doing weird stuff. And Claude just upgrades Sonnet 4 from 200 ,000 tokens to a million tokens. That is very significant. Those of you who don't know, tokens are basically parts of words. So a million tokens is about 750 ,000 words, which is a lot of words. This is way more than GPT-5's 256 ,000 tokens if you're using the chat or 400 ,000 if you're using the API. So it definitely surpasses both of them by a big spread. This particular move from Claude is aiming mostly for developers.

51:33I think the average person is not going to use such a big context window, definitely not on the day-to-day. But if you want to run a large chunk of code or an entire code base through your AI to get feedback, to get responses, or to write code that connects to it, having a large context window is very significant. And this is a great step in the right direction. As we know, ChatGPT is now, as we've seen in the launch of GPT-5, GPT-5 is now the default model in Cursor, despite the fact the vast majority of Cursor users like to use Cloud, and this is part of Cloud's way to fight back and just provide a much larger context window that allows you to do a lot more with a lot more code.

52:07Putting things in perspective, the only two models that have a larger context window is Gemini 2.5 Pro with 2 million tokens context window, which is 1.5 million words-ish, and Meta's Lama 4 with 10 million tokens context window, at least so they claim, but I don't think Metal Llama 4 is nearly at the level of Gemini or Claude or Chachapiti right now. So from a scale perspective, you're getting the scale, but you're not necessarily getting the same quality if you're going down that path. I go to Gemini 2.5 Pro every time I need to do anything big and it always works. And it's definitely still a go-to, even though now Claude has a much bigger limit than he did before.

52:43That being said, it comes at a price. So Prompt that has over 200 ,000 tokens see a price hike to$6 per million input tokens and$22.50 for output tokens compared with 3 and 15. So it doubles the cost of the input and it adds about 50 % to the cost of the output if you're using the longer context window. Anthropic also published a very interesting study this week that found what they call persona vectors. Basically, it's a methodology that while you are training an AI, allows you to see where and how it stores information about its personality, which allows you to A, see what kind of personality it has, and B, be able to steer it effectively in the training phase.

53:22This is obviously extremely important, especially for companies who are going to take open source models and want to build their own models on top of that. It will allow them to A, eliminate issues that the role model had when they took it and started training it, and B, allow them to create personas that are aligned with what the company needs and wants. And I think this is a very, very important step in the future development of AI models that will be safe and supporting of society versus the other way around. Now, staying on topics of new interesting releases, Google just released another family member for the Gemma open source models that they have.

53:56It is called Gemma 3 270 million with a 270 billion parameter, which is a very small model that apparently is really, really good at following robust instructions while being very energy efficient and can run on edge devices. It is also very good at being ready for training. So it's optimal if you want to take and build a very specific use case for a model that doesn't require a very big model. So a small, effective model that is easy to train is a perfect solution for that. And they've developed this model exactly for this purpose. Per multiple benchmarks, it is the best model to its size in instruction following and the best in being energy efficient across multiple models in the open source universe today.

54:38And with this release, Google also is celebrating over 200 million downloads of their different Gemma models, which is definitely showing trust in the developer community. Now I want to switch and talk about two interesting, one is a research and one is an opinion about some of the big issues in the AI world and how it's maybe not as incredible as we feel or think it is. So researchers from Arizona State University have done a research trying to check how much reasoning can the reasoning models actually do. And what they basically did is they took very small models that are trained on chain of thought processes, which is how these models reason, and they tested their reasoning capability on topics they had in the training data.

55:18Then they gave them examples of reasoning problems where just some of the information was in their training data. And then they also asked them to reason on stuff that wasn't in their training data at all. And the results were very, very clear. These models cannot reason or do a really poor and, in some cases, catastrophic job in reasoning across things that were not in their training data, and they struggle with stuff that was partially in their training data, which basically tells you that these models do not really have reasoning capabilities. They can simulate reasoning capabilities based on past experience, which takes us to two separate conclusions.

55:51Conclusion number one, the bigger the model, the better its reasoning is going to be, right? So these massive, gigantic training runs that the really big labs are doing right now are going to pay off on that particular perspective because we'll have significantly more reference materials to reason across a wide variety of things. The flip side is we are very far from AGI. If the idea of AGI is these models can reason like humans, meaning they can see a problem they've never seen before and they can apply their knowledge on how to solve problems to something new, just doesn't exist, at least with the current technology.

56:23Staying on the same topic, Demis Asabes, the CEO of Google's DeepMind, was speaking on the Google for Developers podcast, and he said that he sees inconsistencies in AI performance as a critical hurdle in the quest for AGI. Those inconsistencies are between similar runs on the same topics, but even bigger when you compare the AI ability to sometimes do really complex things and then fail in very, very basic stuff. Asabes mentioned that the top models from Google, Gemini, and Chachipiti just won gold at the International Mathematical Olympiad, but it sometimes struggles with basic high school math, which is showcasing a big inconsistency on the AI performance.

57:02he thinks that this lack of consistency is a barrier in the path to AGI. And he thinks that just scaling data and compute alone is not going to solve this problem, which means technological breakthroughs are required in order to go beyond the current issues with AI. And that's why he thinks the path to AGI is longer than some other people in the industry are suggesting. There was also a recent interview on the Lex Friedman podcast, which I'm not going to dive into, but I highly recommend listening to. I love listening to Demis Asabes. He's an incredibly smart individual, but he also is really good at taking very complex topics and making it easy for idiots like me to understand.

57:40And so if you want to learn more about where AI is right now, where is it going, and what Demis thinks about all these topics, I highly recommend listening to this interview with Lex Friedman. And we also had a big week when it comes to AI celebrities bashing heads with our favorites Elon Musk and Sam Altman exchanging some blows on X and beyond on more than one topic. So the first one was Elon, as you know, the founder of XAI, has claimed that Apple has favorism in its app store towards ChatGPT that makes it impossible for other AI companies to reach number one. The specific tweet was, Apple is behaving in a manner that makes it impossible for any AI companies beside OpenAI to reach number one in the app store, which is an unequivocal antitrust violation.

58:22XAI will take immediate legal action. Now, several different people added the following facts. In January 2025, DeepSeek reached number one overall in the App Store. Just one month ago, on July 18th, Perplexity also reached number one overall in India App Store, which is kind of like contradicting what Elon is saying. But Sam Altman copied Elon Musk's tweet and said, this is a remarkable claim given what I've heard alleged that Elon does to manipulate X to benefit himself and his own companies and harm his competitors and people he doesn't like. He then added another tweet that says, a lot has been said about this.

58:56Here is one thing. And he added a video that says, yes, Elon Musk created a special system for showing you all his tweets first. And then Sam added, I hope someone will get counter discovery on this. I and many others would love to know what has been happening, but OpenAI will just stay focused on making great products. Basically, what he's saying is we're number one because we're just better and you are a crybaby. Other companies are able to reach number one. You're not reaching number one because you're not just good enough. and at the same time, you are manipulating X in order to get your stuff ahead of other people, so stop whining.

59:27But that wasn't the end of it because somebody on X asked Grok to decide which one of them is right. And Grok sided with Sam Altman, stating Musk has a history of directing X algorithm changes to boost his post and favor his interests. Musk was obviously not happy with those results from Grok, which is XAI's model that his company is developing, and he said that this is not correct and that they're going to fix the model in order to get the truth out there. But definitely a fun exchange from these two if you're sitting on the sideline just looking. In addition, a US federal judge has just ruled against Elon Musk attempt to dismiss OpenAI's allegations of prolonged harassment campaign.

1:00:08We talked a lot about this situation last year when Elon was doing everything he could to slow OpenAI down and suing them across multiple things. And they sued him back saying it's just harassment and that there's no real substance. Elon was trying to dismiss this and the judge said there's no reason to dismiss this because there's enough evidence for it to move forward to trial. And to pour some more gasoline into the fire Sam Altman just launched another company called Merge Labs which is a brain-computer interface also known as BCI which is a startup that will compete with Elon Musk's Neuralink.

1:00:40So this is, by the way, not a new idea by Sam even the name of the company is related to Sam's blog post from 2017 where he said that by 2025, humans will merge with machines. This is not happening, thank God, at least not yet. But he definitely predicted that and he wants to go in that direction. But that puts him on another collusion path with Elon Musk. And I promised you some great news in the end as I try to finish every episode. So MIT researchers has harnessed AI to design novel antibiotics that is targeting drug-resistant bacteria. They're suggesting that they will be able to fight the global antimicrobial resistance crisis that is currently killing nearly 5 million people every single year.

1:01:21So 5 million people die every year from bacterial infections in which antibiotics doesn't help them. And there's been very few new antibiotics approved by the FDA in the last 45 years. Most of them are variants of existing drugs. Now, the AI was able to generate 29 million new types of compounds that could be potentially solutions. And out of those researchers, we're able to find a few that are actually helpful and impactful in fighting those bacteria. So these are some of the things that actually really excite me when it comes to AI usage. Our ability to improve healthcare, hopefully for everybody, is something that is already happening and hopefully will happen at a much bigger scale.

1:02:03That's it for this week. This Tuesday, we are going to share a really amazing episode that is going to share the five different levels of potential AI implementation from basic chat to assistance to business flow automation to agents and to vibe coding and explain the pros and cons on each one and how to get started with each and every one of them. It's a really great episode that can help you understand where to get started or how to solve your particular use case. If you find this podcast or this episode valuable, I would really appreciate it if you open your phone right now and click on the share button and share it with a few people who can benefit from it.

1:02:36There's tens of thousands of people already listening every single week, but it will be awesome to get it to a lot more people because there's millions of people in the world who need this knowledge and you can help. And I would really appreciate if you do that while you're at it and you have your phone in your hand and you open the app, you can also provide us a review on either Spotify or Apple podcast. And I would really appreciate that as well. Until then, keep experimenting, keep learning AI. Come join us on the Friday Hangouts. It's a really great group of people that gets together every single week at 1 p.m.

1:03:06Eastern, and we just talk AI, and we solve tactical problems, and we talk about big issues, and we look at examples of successful things and failed things, and we just learn AI together. It's really fun, it's unscripted, and it's highly educational. So if you want to join, just send me a message on LinkedIn, and I will gladly add you to the group. And until then, have an awesome rest of your weekend.