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
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