OpenAI and Google Just Beat the World's Smartest Mathematicians

Ejaaz: All right josh the ai nerds are Ejaaz: fighting again this past weekend there was Ejaaz: a very prestigious competition called the international math olympiad which Ejaaz: hosts some of the brightest smartest mathematicians of our time and they're Ejaaz: typically high schoolers and basically they come together and they take a really Ejaaz: hard math test this is like four to five hours and those that score the highest, get medals.

Ejaaz: You can get bronze, silver, and the highest scorers get gold medals. Ejaaz: So what's this going to do with AI? Ejaaz: Well, recently, over the last couple of years, the organizers of this International Ejaaz: Math Olympiad decided to start inviting AI models to participate as contestants. Ejaaz: And they did terribly. Like, no one's come even near the human geniuses.

Ejaaz: Except this year, Josh, where they came to play and not one, Ejaaz: but two AI models achieved not silver, but gold medals, which is just an insane thing, right? Ejaaz: So it should be all fun and games, right? What a fairytale story. Ejaaz: Well, unfortunately, OpenAI and Google got into an online spat where they started Ejaaz: accusing each other of cheating.

Ejaaz: Now, remember, these are trillion dollar companies. So essentially, Ejaaz: Josh, I was teleported this weekend back to my high school days where I felt Ejaaz: like the teacher had to come in, separate the kids from arguing over some kind Ejaaz: of random homework problem and get them to chill out. Josh: We will look back at this episode and laugh at it like it's a joke because these Josh: AIs, they're competing against high schoolers. That's so lame.

Josh: Only high schoolers? Like, come on, and you're just barely getting gold. Ejaaz: Well, in their defense, Josh, these are some pretty smart high schoolers, Ejaaz: man. Like I was looking at some of these math problems. Ejaaz: I don't know if you can see my screen here. I'm sharing the official site. Ejaaz: And if you look at some of these problems, here we go. Ejaaz: And then like, okay, so they have basically, they host this competition in a Ejaaz: different country each year.

Ejaaz: And you can kind of like download the test yourselves after the fact to see Ejaaz: how well you could do it. I had a look at this one, Josh from the Afrikaans. Ejaaz: I basically don't understand anything. One second. All right, Ejaaz: take a look at that. Take a look at this. Josh: That looks like quite a bit of squiggly lines on a page. Ejaaz: You know what? That could be mistaken for a piece of art in a gallery if you Ejaaz: didn't peer too closely at it. This looks insane.

Josh: Okay, so I take it back. So the high schoolers are probably pretty smart then. Josh: And I guess the AI performing as well as the high schoolers is probably a pretty big deal, right? Josh: Because that looks like very complicated math problems that I'm assuming most Josh: of the smartest people in the world cannot solve.

Ejaaz: Exactly. Yeah. This is like something that is technically set for high schoolers Ejaaz: and sometimes college kids, but is meant to demonstrate prowess in the field. Ejaaz: So there's a lot of university academics, which obviously do math degrees and Ejaaz: they do PhDs, but those are in very specific problems. So you kind of like in Ejaaz: science, you just need to kind of pick and choose your lane and then dedicate your life to it.

Ejaaz: High schoolers is kind of college kids are kind of like the last point before Ejaaz: you jump into your specialization. Ejaaz: So really, if you're the best at generalized maths, you're going to compete in this competition. Ejaaz: And what's so interesting is typically AI models haven't been able to perform Ejaaz: very well because they needed a lot of context beforehand about the problem, Josh.

Ejaaz: So they needed to know that, you know, there was certain, you know, Ejaaz: X equals something and Y equals something. Ejaaz: And they had to have defined parameters to kind of figure out the problem. Ejaaz: But this was the first time that AI models basically were just given a blank Ejaaz: sheet of paper or not a blank sheet of paper.

Ejaaz: But they stared at the problem just as we just looked at it just now and had Ejaaz: to read the words, read the characters, interpret what that meant in the context Ejaaz: of that situation and the way that the question was framed and then figure it out themselves. Ejaaz: So it's as if the AI models had a camera that looked at a paper, Ejaaz: similar way that we look at test papers as kids through our eyes and figure it out themselves.

Josh: So what changed? What happened in the last year that made it so much better? Josh: Because it went from, what, basically zero of six to now six or five of six questions answered.

Josh: Now it's a gold medalist. So what happened? Ejaaz: So listen, I'm not going to try and explain it, but maybe you and I can decipher Ejaaz: it through the legends themselves that built these models, right? Ejaaz: Okay, so let me paint the scene for you, Josh. Ejaaz: It is Saturday evening. Ejaaz: You know, normal people are usually out and about. They're having fun. Ejaaz: They're probably having dinner, catching up with friends or chilling at home, watching a movie.

Ejaaz: And this guy called Alexander Wei, who is OpenAI's head of reasoning. Ejaaz: Reasoning is basically this new fancy technique that AI models have typically Ejaaz: demonstrated, which has brought them up to like the frontier level of AI models. Ejaaz: Basically, if your model can do reasoning, it's typically a pretty smart model, right?

Ejaaz: And he posts this tweet saying, I'm excited to share that our latest OpenAI Ejaaz: Experimental Reasoning LLM has achieved a longstanding grand challenge in AI, Ejaaz: a gold medal level performance on the world's most prestigious math competition, Ejaaz: the International Math Olympiad.

Ejaaz: And he goes on to describe, you know, how the model basically took on each problem Ejaaz: in its own regard and solved it and how this is a massive success and win for Ejaaz: AI models and how, most importantly. Ejaaz: OpenAI was the first ever model to complete this. Ejaaz: And not too long after he posts that tweet, Josh, Sam Altman jumps in here, right?

Ejaaz: And he goes, again, he kind of echoes similar thoughts. We achieved gold medal Ejaaz: level performance on the 2025 IMO competition with general purpose reasoning. Ejaaz: And then he kind of like shells GPT-5 at the end. Basically, Ejaaz: it's like a promotive thing for OpenAI. Ejaaz: And I will say that this is really cool because what they've achieved is something Ejaaz: that hasn't been done before, right? So very impressive feat.

Ejaaz: And in terms of how this works specifically, Cheryl Su here gives a really good breakdown. Ejaaz: She says, the model solves these problems without tools like coding or Lean, Ejaaz: which is another coding tool. Ejaaz: It just uses natural language. So as I said earlier, It kind of reads the paper Ejaaz: and just kind of interprets what it thinks it means. Ejaaz: And it also has the same amount of time to do the test as other kits, so 4.5 hours.

Ejaaz: And she says, we see the model reason at a very high level, trying out different Ejaaz: strategies, making observations from examples, and testing different hypotheses out. Ejaaz: And she says, it's crazy how we've gone from 12% on the AIME test, Ejaaz: which is what GPT-4O, which is OpenAI's early model, got to IMO gold, Ejaaz: International Math Olympiad gold medal in 15 months. Ejaaz: So just to set that in context, Josh, that is a crazy leap in 15 months.

Ejaaz: Imagine going from eighth grade level math to the best. Ejaaz: Mathematician in the world in 15 months. It's a pretty insane thing.

Ejaaz: Yeah, I'd say so. So essentially the breakthrough that Cheryl is highlighting Ejaaz: here is number one, the model didn't need any context. Ejaaz: Number two, it used really high level reasoning to figure out the problems from first principles. Ejaaz: And number three, it was able to test out multiple hypotheses at the same time Ejaaz: instead of trying to one shot the problem.

Ejaaz: Typically in the past when AI models have been given a prompt or a problem, Ejaaz: it tries to just like give it its best shot and give you one solution, Josh. Ejaaz: Whereas what these models, these reasoning models do really well is they are Ejaaz: able to hypothetically entertain many different scenarios and then pick the Ejaaz: best one of which it thought it was an answer. Ejaaz: And it ended up with the gold medal, which is insane, right?

Ejaaz: But it wasn't entirely without a few glitches here and there, Josh. Ejaaz: So if you look at this post from Jasper, he read through the entire kind of Ejaaz: like problem set that OpenAI's model went through. and he points out that some weird anomalies. Ejaaz: So he kind of like talks about like how it kind of like analyzed and a bunch of things. Ejaaz: And he goes, however, the write-up is kind of messy. He goes, Ejaaz: it overuses shorthand and sentence fragments.

Ejaaz: It introduces new terms without definitions, for example, forbidden and sunny partners. Ejaaz: I have no idea what either of those terms could mean, but it was just apparently Ejaaz: just interspersing these phrases during its analysis. Ejaaz: And so as a reviewer, or as an examiner, they were reading this, Ejaaz: they were like, sorry, wait, what is it talking about? Ejaaz: It got to the right answer, but what is it talking about, right?

Ejaaz: The other key point from this post is it was unable to solve one problem, problem six. Ejaaz: And I'm not even gonna try and get into why it failed on that problem, Ejaaz: but it was just particularly hard for it to figure out. Ejaaz: But it still scored a high enough percentage that it got a gold medal.

Ejaaz: So it's basically a win for OpenAI, but that's when the drama starts unfolding. Ejaaz: So I've got this post up from Mikhail Samin, which kind of like sparks this entire fight, Josh. Ejaaz: He goes, according to a friend, the IMO, which is the International Math Olympiad. Ejaaz: Asked AI companies not to steal the spotlight from kids and to wait a week after Ejaaz: the closing ceremony to announce the results. Ejaaz: OpenAI instead announced the results before the closing ceremony. Yeah.

Ejaaz: And then he goes on to basically say how this is essentially like some kind Ejaaz: of clout chasing move from OpenAI. Ejaaz: And OK, I tried to evaluate this, Josh, from OpenAI's kind of perspective, Ejaaz: which is they basically want to steal the limelight, Ejaaz: but also say that they were the first AI model to ever achieve gold on this Ejaaz: competition, which puts them in a good light and makes users want to choose

Ejaaz: OpenAI and solidify the branding that OpenAI is the best. right? Ejaaz: But on the other side, you know, they're kind of like stealing the spotlight Ejaaz: from the kids, as this post says. But that's not actually the main trope. Ejaaz: The main trope here, Josh, is OpenAI wasn't the only model to achieve a goal, right? Ejaaz: At the same time, during the same testing period, you had Google achieving the exact same score.

Ejaaz: So then the question becomes, okay, well, it was whoever was ethical about announcing their own result. Ejaaz: This post from Demis Hassabis, which is Google's head of AI, Ejaaz: basically posts, and I'll note two days later, Official results are in. Ejaaz: Gemini, which is their flagship model, achieved gold medal level in the International Math Olympiad. Ejaaz: An advanced version was able to solve five out of six problems.

Ejaaz: So same as OpenAI, same thing, struggled on the sixth problem. Ejaaz: Incredible progress. Huge congrats to the team. Ejaaz: And a tweet here says that Google Ejaaz: basically had to wait for marketing to approve the tweet until Monday. Ejaaz: But OpenAI shared theirs first at 1 a.m. Ejaaz: On Saturday and stole the spotlight.

Ejaaz: And we see the screenshot from Demis Hassabis, which, you know, Ejaaz: he further clarifies this, basically saying, Ejaaz: by the way, as an aside, we didn't announce on Friday because we respected the Ejaaz: IMO's board's original request that all AI labs share the results only after Ejaaz: the official results have been verified. Ejaaz: Now that we've been given permission to share, blah, blah, blah, Ejaaz: he shares. So Demis is playing the like good Samaritan here.

Ejaaz: He's like, ah, you know, we also have the good model, but we, Ejaaz: you know, we have some pride and some manners about how we deal with these things. Ejaaz: That's where it starts to get a little uglier, Josh, because we have OpenAI Ejaaz: chiming in to this tweet, which basically says, and this is some random commenting Ejaaz: on OpenAI and this entire situation.

Ejaaz: So OpenAI basically has zero advantages except the size of the team, Ejaaz: aka the OpenAI team was claimed to be smaller than Google Gemini's team. Ejaaz: So what he's inferring here is there's no real difference between OpenAI's models Ejaaz: and Google Gemini's models. You can pretty much use either or. Ejaaz: OpenAI maybe has a smaller team to build that model, but who the hell cares?

Ejaaz: And then one of the AI model researchers at OpenAI basically comes in and says, Ejaaz: well, I think it's also interesting that they they Ejaaz: being google curated and provided useful context Ejaaz: to the model which we did not feels like Ejaaz: taking your tutor's cheat sheet with you into the exam so shots basically being Ejaaz: fired from open ai saying hey um you cheated you gave context to your model

Ejaaz: and that was why it was able to achieve gold we open ai didn't provide any of Ejaaz: that context and it was able to reason from first principles, there you have it. Ejaaz: But then directly beneath it, Vinay Rameshes, who is a Google DeepMind AI researcher, responds, Ejaaz: it's worth noting actually that a deep think system, which is Google's AI system Ejaaz: with no access to this corpus, so no context, also got gold.

Ejaaz: Again, according to the official graders, and he puts this in brackets because Ejaaz: OpenAI didn't wait for the official graders to mark their score, Ejaaz: with exactly the same score. Ejaaz: So basically, this is like a pissing contest between two of the top AI model providers.

Ejaaz: Here's my take, Josh. And then I really want to kind of lean into what you think Ejaaz: about this whole debacle. Ejaaz: Number one, this seems so childish to me. Ejaaz: Like, eventually, AI models were eventually going to get smarter or smart enough Ejaaz: to solve these mathematical problems. Ejaaz: And I think you said this earlier on. Ejaaz: This is something that they're going to probably laugh about 10 years from now,

Ejaaz: right? that they were able to solve whatever, the most complex mathematic problems Ejaaz: for humans, mere humans. Ejaaz: And now AI is off creating wonderful scientific discoveries for us that we would Ejaaz: have never comprehended or figured out ourselves, right? Ejaaz: So firstly, you're arguing over something that's so silly. Ejaaz: But number two, this kind of seems desperate on the open AI side. Ejaaz: And maybe I'm being biased, but I'm just going to give you my take.

Ejaaz: Open AI has kind of had a series of stumbles recently.

Ejaaz: They claimed that they were going to release gpt5 which Ejaaz: is their brand new frontier model but they've delayed it many months Ejaaz: now um they got outperformed by Ejaaz: grok 4 from xai uh so now Ejaaz: they have a new benchmark that they need to beat a new model that they basically Ejaaz: need to outcompete uh they claimed that they were going to release a new open Ejaaz: source model and then delayed it after a chinese open source model was released

Ejaaz: and had one trillion parameters and outperformed not just their model, Ejaaz: but any other open source model out there. Ejaaz: And so I feel like they're looking Ejaaz: for a win, right? They released their agent this week or last week. Ejaaz: And so, you know, that had mixed review, mixed feedback. Ejaaz: So I feel like Sam is desperate for a win. Ejaaz: People are criticizing consistently their moat, asking what has OpenAI got?

Ejaaz: They've lost a ton of researchers to Meta and other companies. Ejaaz: I feel like their back's against the wall. Ejaaz: Sam's scared and he basically needs to grab any kind of win. Ejaaz: So it reeks of desperation. Ejaaz: What's your take, Josh? Josh: I do empathize with the team. They've been coming under fire from every single angle. Josh: I mean, you have Zuck poaching all of their talent, and then all of the other Josh: open-source AI models are beating them at their own game.

Josh: And they're just kind of, they're really getting beat up now. Josh: And I think that they're looking to get some footing. I'm sure this probably plays a role in it. Josh: But I'm sure behind the scenes, they're really trying to fight hard to put their Josh: feet back on stable ground, to get GPT-5 out the door, to build Project Stargate Josh: and make this big infrastructure network.

Josh: They need some wins. So sure, this was probably an attempt to get ahead, Josh: make them look good, win over some more hearts and minds.

Josh: But I think the most interesting part of the whole story is less the drama and Josh: more the fact that these models were able to accomplish a really impressive Josh: feat over such a short period of time. Josh: From what I understand, previously when they attempted to solve these problems, Josh: they used a custom training data set. Josh: They used custom tool sets. It was mostly a model trained on solving mathematical problems.

Josh: And with this version, both the OpenAI version and the Gemini models, Josh: they were both general purpose models. Josh: They were not trained specifically with the intention of solving mathematical problems. Josh: These are the general models that people day to day are using. Josh: They're just now able to solve these math problems using this new general intelligence.

Josh: So it's a really interesting breakthrough that I think we get from reinforcement Josh: learning that now there is not so much of an advantage to training a model specific Josh: to one's skill set when you could just make it great at everything. Josh: There was one thing that I noticed that some people call it cheating, other people don't.

Josh: But so with the mathematical, with the actual test that high school was had Josh: to take, they're not allowed to use tools and they have a limited amount of Josh: time per question to answer. Josh: The models that, the OpenAI model and the Gemini model, they had infinite amount Josh: of time to answer and they were allowed to use tools. Josh: So there still are small differences in these. Ejaaz: Were they allowed to like use the internet?

Josh: I don't know the specifics. I would imagine at least calculators, Josh: at most probably the full repertoire of what we have currently available to Josh: us, which is full internet search, code writing abilities. They could do their Josh: own mathematical checks. Josh: So I would just assume the minimum amount of constraints possible. Josh: So there was much less constraints on the models, But they did solve the questions.

Josh: And I think that's super impressive. They got five out of six right. Josh: Which was gold and better than almost every student, if I'm not mistaken. Josh: Only a few students got the six out of six completely correct. Josh: It's just cool to see the rate of progress of these models getting better. Josh: That over the course of the last 15 months or so, they went from horrible and Josh: narrowly trained to incredible and generally trained.

Josh: And as long as that trend keeps going, I think the drama matters less than the Josh: output, which is models are getting really good at solving really hard math problems. Josh: And original ones too, that the world has never seen before. Ejaaz: Yeah, well, that last point is actually the main takeaway that I had, Ejaaz: Josh, which is it's original, never-before-seen problems.

Ejaaz: Typically, these AI models are trained on things that they've seen before, as you said, right? Ejaaz: They're trained on data sets. So they've already seen the problem, Ejaaz: and then they have to work out, they know the answer, and they have to work Ejaaz: out how to get there, right? So they kind of have a leading factor. Ejaaz: Here, it's just kind of like completely unknown.

Ejaaz: The other thing is, this is kind of like the culmination of a trend, Ejaaz: Josh, which is these AI models are really good at doing kind of binary tasks. Ejaaz: And I don't want to reduce mathematics to binary tasks, but technically it's Ejaaz: numbers, sequential formulas, that kind of stuff, right? Ejaaz: So if you can run enough compute at a thing, and if you can get that AI model Ejaaz: to consider all different decision parts, It's going to eventually get to the answer, right?

Ejaaz: But it's always a specific answer at the end of that, right? Ejaaz: Whereas when it comes to more subjective things, more human experiential things, Ejaaz: AI has typically struggled to...

Ejaaz: Improve at the same rate that it has for like all these different scientific Ejaaz: and math problems so i'm glad that we've reached this pinnacle feat i think Ejaaz: ai models have are really good at one thing and not so great at other things Ejaaz: and i'm excited to see how like they kind of like try to start leapfrogging Ejaaz: each other over the next couple of years.

Josh: Yeah it's it's that directional progress that we like Josh: math is clearly the first because you can write down Josh: proofs and you could check your work and there is an actual verifiable solution Josh: and i think that's why we're seeing a lot of the progress start early Josh: in math and then hopefully go on to these other places but Josh: what we are seeing is these first signs of Josh: new knowledge breakthroughs where it's solving a Josh: new and novel problem that hasn't been

Josh: released before based on its previous data set Josh: so it's not just pattern matching like you mentioned earlier where it has Josh: this data set of questions it's kind of finding the right examples and Josh: then applying that logic to the question it's actually Josh: reasoning and it's it's reasoning in many instances and Josh: then it's comparing its work and it's it's coming to a conclusion Josh: and we saw this with the grok heavy model last week too when

Josh: it released um where i think the the new Josh: meta is many instances solving hard Josh: problems and then comparing so you lower that error rate more Josh: and more and more each time and what we're seeing is great progress so Josh: i mean although open ai and google are fighting again they're both they're both Josh: fighting over over exciting progress and sure maybe one tried to sweep in and Josh: steal the valor but they both did an excellent job in actually completing these

Josh: problems and placing gold in a test that was previously not possible to do from an ai model you Ejaaz: Know who the real winners are here out of this josh. Josh: Who's that high school kids Ejaaz: Who now have an AI model that can do all their math homework for them. Josh: Isn't that incredible? Like, man, think about it. Ejaaz: I wish I had that. Josh: You have an AI model that is as smart as the smartest people on planet Earth

Josh: in high school. If it could solve those math problems, it could solve anything. Ejaaz: It sounds human as well, Josh. So, like, your teacher is going to struggle unless Ejaaz: they use AI themselves to figure out whether you just did that yourself or completely Ejaaz: just ran that through GPT, your mom's GPT subscription. Josh: It really forces you to re-evaluate the school model, right?

Josh: Because now that this information is so readily accessible, it's so easy to solve these problems. Josh: Is that the actual thing worth learning? Or is it how to use these tools that's Josh: more important to get to the answer?

Josh: And there's this there's this dual pronged approach and we see we see Josh: developers and programmers talk about this a lot where as soon Josh: as they start to rely too heavily on the tools they start Josh: to lose their touch they start to lose their ability to to deeply Josh: understand how it reaches conclusions um but Josh: is that worth it in exchange for getting to the answer much quicker and then Josh: being able to seek many more answers i don't know it's weird dynamic if i was

Josh: a teacher i'd be worried because i mean similar to what we saw with the calculator Josh: it just replace the thinking process and just yield you an answer and Ejaaz: The thing with the calculator is like you you're Ejaaz: using the calculator so it figures out the answer for you but you kind of Ejaaz: loosely understand how it is working right you Ejaaz: know what numbers it's crunching to get to that answer and then typically you

Ejaaz: do a few things on a calculator and then you get to your eventual answer for Ejaaz: whatever the original question was the issue with or the concern that you're Ejaaz: highlighting here with AI is it's doing really complex problems, Ejaaz: which kids don't even need to understand in the first place just to get an answer, Ejaaz: which they can then give to their teacher, get a grade and then go to university. Ejaaz: But the kids don't actually learn actively in that process.

Ejaaz: And it's going to be a concerning trend if we see kids just trying to go from Ejaaz: zero to 100% without understanding anything in between. Ejaaz: A trend to watch. Josh: This is our episode from a few weeks ago. Is AI making you dumber? Josh: Yes. And I think that's just going to continue to be the question. Josh: Oh, God. And I think the answer is it's all dependent on how you choose to use Josh: the tools that you're given.

Josh: And if you use these tools as further leverage. So I'm sure these math olympiads Josh: who can actually complete the problems would love to have this model to check Josh: the problems and to work through the problems and to figure out shortcuts on Josh: solving these problems. Josh: Where if you deeply understand it, then this becomes an amazing tool to check Josh: your work, to generate new questions for you.

Josh: It's a great study, buddy. or if you are not an olympiad and you still want Josh: to get to the answer well you just kind of cheat your way through and you just Josh: ask it for exactly what you want so it's that it's that split again and it's Josh: up to the person to take their own agency solve their own problems and try to Josh: use these for for tools of leverage instead of just problem solving machines that

Ejaaz: Actually reminds me of this tweet i saw yesterday josh um so what you're looking Ejaaz: at here is a tweet from dave white dave White is a very prestigious investment Ejaaz: slash research advisor at this fund called Paradigm, Ejaaz: which basically it's a crypto fund, but it is one of the wealthiest funds out there. Ejaaz: So a lot of the investments they made were massive wins. And a lot of the reasoning Ejaaz: of those wins was from Dave White's analysis.

Ejaaz: He is a deeply thoughtful mathematician at his core, and he is famed for doing Ejaaz: a lot of analyses on companies, mathematical analyses that have ended up, you know. Ejaaz: Determining whether a fund puts $100 million in a company or zero, right? Ejaaz: So a very important job worth hundreds of millions of dollars, right? Ejaaz: And what he says here, basically, is him having an identity crisis, Ejaaz: because he has looked up to the IMO, the International Math Olympiad.

Ejaaz: And he goes on to say in this tweet that subconsciously, whenever he's met a Ejaaz: gold medalist IMO champion, he's always subconsciously thought that they were Ejaaz: smarter than him, that he is more respecting of them. Ejaaz: And now with this news that AI models basically can do his job for him, Ejaaz: can reason better than him at some of these math problems, he now has an identity crisis.

Ejaaz: He doesn't know kind of where to go from this. And if people like Dave White Ejaaz: is having this kind of like disillusioned sentiment from how smart AI is, Ejaaz: you can imagine how this is going to happen for everyone else in all of the Ejaaz: other sectors, Josh, right?

Ejaaz: It doesn't matter if you're a mathematician or an investment research advisor, Ejaaz: you could be a technician in some kind of engineering industrial role, Ejaaz: or you could be a teacher, or you could be a kid or a high schooler. Ejaaz: I think this disillusionment is going to spread. And I think it's super important Ejaaz: for people to kind of like evolve their thinking, like you said, Ejaaz: Josh, and learn how to leverage these tools versus just consume.

Josh: Yeah, this is, I mean, this is crazy. There's a lot of people that are going Josh: to have to adapt to this new world order of intelligence, where if you build Josh: up your entire identity around being intelligent, well, perhaps you're going to have to alter the way Josh: present yourself as intelligent because the meaning of intelligence is becoming Josh: commoditized among these tools that are now reduced down to a single chat box.

Ejaaz: Yep. Benchmarks are going to have to reset themselves completely.

Ejaaz: But folks, that is the end of this episode. Thank you so much for tuning in again. Ejaaz: Josh and I are going hammer and tong at Limitless. Ejaaz: Our goal is to get you the hottest and trending topics and news fresh out the Ejaaz: door, give you our commentary, our thoughts, and hopefully some useful insights for you.

Ejaaz: If you enjoyed this episode if you enjoyed any of our previous episodes please Ejaaz: continue to share and spread them with all your friends and family and whoever Ejaaz: you think might be interested in this we are getting tons of feedback from you Ejaaz: guys and with every episode that we release we're getting better so please remember Ejaaz: to like subscribe follow us it's hugely appreciative and helpful for us and Ejaaz: we'll see you on the next one.