AGI is Back! Google Gemini 3.0 Crushed Our Expectations

Josh: If I had a crown in my hands, I would place it on the heads of Google because they have done it again. Josh: They have the world's best AI model ever in history by a shockingly large margin. Josh: Gemini 3.0 just got released. Josh: It's available now to anybody in the world to go use it. And the benchmarks Josh: are kind of blowing everyone's expectations out of the water, myself included.

Josh: And most importantly, it places another data point on the chart that shows we Josh: are continuing to ascend up this exponential curve towards AGI. Josh: And the roadmap is still intact and we are very quickly moving through it. Josh: This, EJs, I was just, I was going through the benchmarks before recording this Josh: and I, it's, it's shocking because we live in this world and yet somehow I'm

Josh: still continually blown away by the progress that's made by these models. So let's get into it. Josh: Please walk everyone through, tell me, what did Gemini and the Google team just Josh: release with this 3.0 update? Ejaaz: People probably think we say the world's best model every week, Ejaaz: but this time we really, really mean it. Ejaaz: Like they have blown every single other model provider out the water.

Ejaaz: The things that this thing can do. Well, how about how about I just show you? Ejaaz: How about I show you, Josh? Josh: Please, let's see some examples. Ejaaz: We have a thread here. And Sundar basically says, you can give Gemini 3 anything, Ejaaz: images, PDFs, scribbles on a napkin, and it'll create whatever you like. Ejaaz: For example, an image becomes a board game. Ejaaz: A napkin sketch transforms into a full website.

Ejaaz: And a diagram could turn into an interactive lesson, right? So there's two examples Ejaaz: I want to show you, Josh. I want to get your opinion on this. Ejaaz: So number one, there's a short video of someone playing pickleball here and Ejaaz: he or she rather uploads it into Gemini and says, hey, can you tell me how well Ejaaz: I've done here and how I can improve my game? Ejaaz: And it analyzes the entire video.

Ejaaz: It knows that she's wearing a knee brace. It analyzes her positions, Ejaaz: telling her where she can move to better position herself to score the point. Ejaaz: That's pretty nuts. But before I get your reaction to that, because Josh, Ejaaz: I know you're an athlete. I know you're very competitive when it comes to these Ejaaz: things. So this is a tool you could definitely use. Ejaaz: The second thing is probably applicable to a lot of listeners on this show.

Ejaaz: They've embedded Gemini 3 into Google search and into new generative UI experiences. Ejaaz: The way I would summarize this is it basically is very intuitive, Josh. Ejaaz: It understands what you're asking for without you needing to really kind of explain yourself. Ejaaz: The example they're showing on the video here is, can you explain the three body problem to me?

Ejaaz: And rather than just give you kind of like this simplistic text, Ejaaz: which explains the concept, it decides to create a video diagram from scratch Ejaaz: to show you a visual depiction of how this works. Ejaaz: Right. Give me your reaction in order from one to two. So starting with the sports. Josh: Okay, let's go. The first example. Ejaaz: Yes, sir.

Josh: So this is really cool, the napkin example, where you can scribble something Josh: down on a piece of paper, it'll generate it in the real world. Josh: What all these examples are kind of showing me is what we always talk about Josh: with Google, where it has this awareness of physics, reality, Josh: and visuals and understanding what it's seeing.

Josh: And all three of these examples are leaning into that. So it leads me to believe Josh: Gemini really is a multimodal first model, where it's meant to ingest, Josh: meant to understand the world around us. This example of the chessboard and Josh: the napkin is amazing because a lot of people oftentimes have sketches. Josh: You just draw it down on paper and it intuitively understands it. Josh: But the one that was most surprising to me is the video example.

Josh: Because as far as I'm concerned. Josh: As far as I'm aware, there has never been a model that can ingest video and Josh: understand the video that it sees. And if it does exist, I've never tried it before. Josh: So the idea that you can, I mean, I play baseball growing up. Josh: I, if I could take a video of myself swinging and get a corrective coach to Josh: walk me through exactly what was wrong. Josh: A lot of people play golf. I'm sure who are watching this.

Josh: If you could have a phone recording of you playing golf and it can actually Josh: critique it and then critique me as if you are a tiger woods, Josh: critique me as if you are whoever else is good that plays golf. Josh: I don't know, Rory McIlroy, whatever they are, but like critique Critique me Josh: as if you are an expert who is really good at golf and can give me some feedback Josh: on how I can better my swing.

Josh: And what this offers in this one just narrow case example is now you have this Josh: personal tutor that can do anything. If you're dancing, if you're doing anything Josh: physical, if you're whatever it is, it can evaluate things for you. Josh: Even if you have a video, a podcast, EJS, we uploaded to Gemini 3.0, Josh: it could critique us. What did we do well? What did we not?

Josh: What did the visuals look like? How can we improve them? And that awareness Josh: of video is like really cool. Ejaaz: Yeah, I just want to say, I think the closest we got to this was with GPT, Ejaaz: where you can upload an image, like what's under my car bonnet and say, Ejaaz: hey, what's wrong? My car stopped working. Ejaaz: And it can kind of like identify the point that you need to kind of like change, Ejaaz: change the oil, blah, blah, blah.

Ejaaz: But that's just a static image. To go from that to live video and for it to Ejaaz: analyze all the frames in that video and then give you a response on that is Ejaaz: a massive leap upwards. We just haven't seen that anyway. So yeah, you're right. Josh: It's amazing. And every example we go through, it kind of breaks the mold of Josh: what I believe should be possible. Josh: And I find that it's going to be difficult to use Gemini 3.0 because there are

Josh: so many possibilities now that have not existed previously. You kind of need Josh: to relearn how to engage with AI because it's so capable. Josh: And there's a fourth example here that I just want to touch on briefly, Josh: which was also cool, is that it works just as well for the other things. Josh: The example is a trip planning one where it starts to plan a trip and a vacation. Josh: And it shows you a full list that is fully interactive of all the places broken up day by day.

Josh: And there's an option that you could just choose visual layout. Josh: And you see on the screen here, it'll take every single day of your trip, Josh: break it into images, section it out into this really nice visual grid. Josh: So what I'm seeing the themes here are, okay, real world understanding, Josh: video first, and really nice presentation, which I think a lot of models sometimes struggle on. Josh: Demo's out of control. I'm excited to use it. Everyone else can use it now.

Josh: It's live. Now I want to get to benchmarks, EJS, because this is where things Josh: get kind of crazy, where we could actually compare one to another and see exactly Josh: how impressive this is relative to everybody else. So please, we have the card here. Josh: Walk us through what we're seeing in this model card and all the specs that we need to know. Ejaaz: As you guys probably know by now, benchmarks is typically how we evaluate any Ejaaz: typical AI model against each other.

Ejaaz: And they're measured against a range of different benchmarks. Ejaaz: A benchmark can be considered as sort of like a test. Ejaaz: Now, right at the top, you've got humanity's last exam. This is by default, Ejaaz: the hardest exam that an AI model is tested against. Ejaaz: And it's kind of like an academic reasoning test with no tools accessible to it. Ejaaz: It scored a very impressive 37.5%, which is more than I think is about a 15% Ejaaz: increase from its previous model.

Ejaaz: Very, very impressive. But what really blew my mind was the second stat listed Ejaaz: here, which is the ARK AGI 2 benchmark. Ejaaz: Josh, when I say this 2x'd the previous state-of-the-art model, I absolutely mean it. Ejaaz: In fact, let me just show you this chart here. Ejaaz: Now, you may notice a couple of bustly specs here. Ejaaz: GPT-5 Pro, Grok 4 Thinking. And then can you see that outlier right at the top Ejaaz: right. Do you see that, Josh? Josh: That's insane. The two outliers.

Ejaaz: The two outliers. So these are the Gemini 3 Pro and the Gemini 3 deep thinking model. Ejaaz: Deep thinking being like, you know, a large number that can like kind of give Ejaaz: you a more research response. They are a... Ejaaz: Stand out from every single other model. And the reason why this is so crazy, Ejaaz: well, there's a few reasons. Ejaaz: Number one, all the other model progressions, as you can see over time, Ejaaz: has been kind of impressive, but kind of small.

Ejaaz: Like they've been a good jump. It's been impressive, but it hasn't been as impressive Ejaaz: to be like, oh, you know, another model provider couldn't catch up. Ejaaz: These results from Google literally put it miles ahead of every other model. Ejaaz: So when I sat at this chart, I think, wow, Google probably has the lead for Ejaaz: another six months and in six months time, they're going to have a more impressive model by then.

Ejaaz: So at this point, I'm kind of thinking, can anyone catch up to Google? Ejaaz: Josh, do you have any reactions to this benchmark? Josh: This is the chart that like the first thing I said to myself when I saw this Josh: is like, oh, my God, there is no wall there. Josh: We are not going to stop scaling. The scaling will still apply because these Josh: two new data points that we have blow everything else out of the water. Josh: And this is how exponential growth happens.

Josh: It seems like a really small cluster down there in the bottom, Josh: but the reality is that was the top just a couple hours ago. Josh: And Gemini kind of refactored this entire chart to make it seem like it's so Josh: small because the progress is so high.

Josh: And although Gemini 3.0 thinking is seemingly the most impressive, Josh: the really anomaly chart is the Gemini 3.0 Pro, which is basically a vertical Josh: line up from these other models, where the score is higher, but the cost is Josh: actually slightly lower. Josh: And if you connect a dot between these averages, you start to see literal vertical Josh: line in terms of improvement and acceleration in these models.

Josh: And that to me shows that there is no scaling wall that we're hitting. Josh: Like we can continue to scale resources, energy, compute, and we could continue Josh: along this path towards AGI in a world where some people were saying, Josh: we don't know if it continues. The answer to me is very clearly, it continues. Josh: This is a step much closer to AGI. Josh: And again, that real world understanding makes it feel much closer to AGI than it ever has before.

Josh: Because now it really like intuitively understands the world through video, Josh: through photo, through audio, through basically every sensory input we have Josh: outside of what taste and feel. Josh: So this to me, I saw this chart. I was like, oh, my God, Gemini, Josh: you really outdid yourselves. Ejaaz: I'm just going to be honest. I think over the last couple of months, Ejaaz: I've been getting a little bored with the models that have been released by other model providers.

Ejaaz: And it led me to think that we're not going to make many breakthroughs until Ejaaz: some model provider figures out a new, unique way to train their model. Ejaaz: Gemini or Google has convinced me otherwise with this release. Ejaaz: But I know you guys are probably like fed up with listening to us hop on about benchmarks. Ejaaz: So how about I materialize that for you in a much more easy to understand way, right?

Ejaaz: So here are the four big takeaways that you need to learn about Gemini 3. Ejaaz: Number one, for its intelligence, for the intelligence that you're getting, Ejaaz: it is not that super expensive. Ejaaz: Google trained this from scratch, as this tweet says, using their own GPU infrastructure. Ejaaz: And it used this kind of like layout called a mixture of experts, Ejaaz: which basically means that whenever you prompt the model, it's not going to use the entire model.

Ejaaz: So it actually ends up being cheaper than what it could eventually become. Ejaaz: One million token context input, 64K token output. We'll get to the costs in Ejaaz: a bit of a second, But the point that I'm making here is that it's not as expensive Ejaaz: as you would expect for the intelligence that you're getting. Ejaaz: Now, if you compared Gemini 3 to GPT 5.1 from OpenAI, on a relative basis, Ejaaz: it is more expensive. But for the jump in intelligence that you're getting,

Ejaaz: it's way better. So it's, in my opinion, worth it. Ejaaz: Number two, when it comes to computer use, so that means letting the AI model Ejaaz: control your computer and do tasks for you whilst you go do something else. Ejaaz: It is state of the art. It is the best here. They measured it against a benchmark Ejaaz: called ScreenSpot Pro, which is a benchmark which kind of like analyzes its Ejaaz: ability to understand images and visuals on a desktop. It just absolutely crushes it.

Ejaaz: Number three, it is the best AI for math by far. Ejaaz: So again, the point I'm making here or the theme that we're seeing here is it's Ejaaz: not just good at one thing, it's good at many things, which makes it the best Ejaaz: generalist AI model in the world right now, by far. Ejaaz: And the final thing, Josh, and this is where it might slip up. Ejaaz: I'm curious to get your take on this. Ejaaz: It is insanely good at coding, but we don't quite know if it is the best at coding yet.

Ejaaz: What I mean by that is it completely crushed everyone else on one coding benchmark, Ejaaz: but the coding benchmark that matters, which is the software engineering, Ejaaz: SWE, it didn't do as well as its competitor, Claude 4.5 from Anthropic. Ejaaz: So those are the four main takeaways. Josh: I would much prefer a model that understands the world than understands how to code.

Josh: And I think we're starting to see these subset niches where if Anthropic has Josh: the best coding model, that's great. Josh: Let them focus on code. Let them narrowly make that the best model. Josh: Let Google handle everything else. And I think that's what Gemini is focusing Josh: on. So the code thing doesn't really bother me because I don't care to use Gemini for code. Josh: I'm happy to be in Claude Camp for code and then use Gemini for everything else.

Josh: And then one of the points earlier that you mentioned on the pricing is. Josh: I find it a little interesting because it's a little bit more than just a little bit more expensive. Josh: The pricing, I was looking through it and it's for over 200,000 tokens. Josh: They're charging $4 for inputs and $18 for outputs. Josh: Now, relative to GPT 5.1, which just got released, they're charging for a million Josh: tokens, $1.25 in, $10 out.

Josh: So you're talking about, what is that? that's about $20 versus $1.25 on inputs. Josh: And that is a fairly significant margin that you're paying for this quality. Josh: So we're starting to see the trade-offs happening on that Pareto curve that Josh: we talked about in a few episodes earlier, where there are trade-offs coming Josh: in terms of cost and quality.

Josh: And it's clear that while OpenAI may have optimized for cost, Josh: Google is kind of optimizing for a little further up the cost curve in exchange for super high quality. Josh: And it seems like this is kind of a balanced data point for now because unless Josh: you are using this via API and you're requiring a ton of tokens, Josh: a $20 a month Google membership will get you all of the use that you need. And that is just fine.

Josh: So in terms of a usability perspective, I think that's okay. Josh: But it's just an interesting thing to know is that this is a better model.

Josh: It is also more expensive. Josh: And that is a trade-off that was made. And in the case that OpenAI decides to Josh: make this trade-off with GPT-6 or Grok decides to make this with Grok-5, Josh: or Grok 6. I'm losing track of all these models now. I think we're going to Josh: start to see the dynamic shift in terms of that Pareto curve and what model Josh: architects decide to remove and add.

Josh: And in this case, it looks like Google added quality, but they also did add Josh: quite a significant cost increase. Ejaaz: I personally don't think it matters. I think it's a nothing burger. Ejaaz: I think that if Google wanted to make it affordable for everyone, Ejaaz: including the developers that want to get API access, that think it might be Ejaaz: too expensive, they could subsidize it. Ejaaz: They are a cash flow giant. They have enough money to do that.

Ejaaz: OpenAI has been doing that for so long now that it doesn't even matter. Ejaaz: I don't see any reason why Google couldn't do that. Ejaaz: The other reason is Google just released their latest TPU, which is their GPU Ejaaz: that they use to train their models and inference their models. Ejaaz: And typically with every generation, we get a much cheaper cost of inference.

Ejaaz: I think by the time that they release their next generation model, Ejaaz: which might be, you know, Gemini 3.1, we're going to see a considerable reduction Ejaaz: in the cost for using Gemini 3 Pro and Gemini Pro deep research. Ejaaz: So I'm not too worried about that. I think it's kind of like a short-term problem Ejaaz: and not a long-term problem.

Ejaaz: But kind of speaking of TPUs, I just want to take a moment to really kind of Ejaaz: belay the point that using their own TPUs to train a state-of-the-art model Ejaaz: that is 2x better than the previous state-of-the-art model and probably puts Ejaaz: them in a six-month lead after Google started off on the back foot, Ejaaz: creating probably the worst model I've ever seen and Ejaaz: changing that all around in what's it under two years is Ejaaz: nothing short of insanity tpus is

Ejaaz: uh google's kind of version of the gpu gpu is Ejaaz: kind of like what nvidia controls the monopoly over this is the hardware that Ejaaz: you use to train your ai and inference your ai the uh unique part here is that Ejaaz: google's never used an nvidia gpu uh or in any considerable way to train their Ejaaz: models they've always trained it in-house and that's such a difficult and tricky Ejaaz: thing to do because designing and building these

Ejaaz: TPUs at scale, these GPUs at scale is a super hard and complex thing. Ejaaz: You need so much talent, you need so much expertise and insight to be able to do that. Ejaaz: The unique thing about Google's TPUs, well, there's two main takeaways. Ejaaz: Number one, it's cheaper to train the same amount of intelligence that an NVIDIA Ejaaz: GPU is. So it's more cost efficient.

Ejaaz: And the second way is, and this is their secret sauce, you can stack those TPUs Ejaaz: on top of each other in a really scalable way that you can start training really, really large models.

Ejaaz: If you wanted to train the same size model with nvidia Ejaaz: gpus it would cost way more and it would take way Ejaaz: longer so google made a really risky and big bet about a decade ago saying we're Ejaaz: going to build our infrastructure in-house and we're not going to rely on nvidia Ejaaz: and we're going to benefit from the full stack experience and this model is Ejaaz: a prime example of that bet paying off so i just want to call them out like

Ejaaz: it's not like google has gotten lucky here they've been planning it for a while now The Josh: Interesting thing to me is that this is the first number one model in the world Josh: built on something other than an NVIDIA GPU. Josh: And that's fairly significant because every company in the world is trying, Josh: but this is proof that it's actually possible.

Josh: And I think when we talk about Tesla and AI5 and the XAI team, Josh: when we talk about OpenAI working with whoever they're working with to build Josh: their own in-house GPUs, I think this sets a precedent that it is possible. Josh: And I suspect that will result in more companies putting their foot on the gas. Josh: When it comes to kind of destructing part of NVIDIA's monopoly that it holds Josh: over GPUs. So that to me is the interesting takeaway of this.

Josh: And hearing that it was fully done, trained on these TPUs, that's very high Josh: signal to me saying, okay, there is an architecture chips happening. Josh: There is a real benefit to vertical integration if you could figure out manufacturing Josh: these compute units at scale. Josh: And now the race is on for everyone to do this. Josh: Because again, using the Apple example, the M series chips, unbelievable, Josh: and they unlocked the best computers in the world.

Josh: And if companies can really start to refine this vertical integration of their Josh: own chips, you're going to see that exponential curve go vertical times 10. Josh: Like it is going to, I suspect that is very... Josh: Obviously now how we reach AGI faster than people previously thought, Josh: because the efficiency improvements from those vertical integrations, Josh: once they're able to manufacture these at scale, are going to be unbelievable.

Josh: And I'm so excited for that to happen in the near future. Google has a big head Josh: start, but let me tell you, the other companies are not far behind.

Ejaaz: Well, let me introduce you to another big advantage of being the big dog, Google. Ejaaz: You thought you were going to come on to this episode and listen to us hopping Ejaaz: on about a generalized model? No. Ejaaz: You're forgetting Google has many other products in their arsenal, Ejaaz: and you're forgetting that they can plug in their new state-of-the-art model into all of them. Ejaaz: So Google not only today announced Gemini 3, but they also announced a different product.

Ejaaz: It's called Google Anti-Gravity, which is basically a new software environment Ejaaz: for you to code up AI agents, except this time these AI agents are going to Ejaaz: be super, super smart because they get plugged in with Gemini 3. Ejaaz: Now, if you remember earlier, I mentioned that one of the cool benchmarks that Ejaaz: this new model sets is in computer use, which means that it can control your Ejaaz: computer, it can do things autonomously for you.

Ejaaz: Now, typically, the reason why we haven't really spoken about that on the show Ejaaz: is that they've been kind of lame. Ejaaz: Like they can book you a dinner reservation and do different kinds of stuff.

Ejaaz: With this model, it's way more intuitive. It can do way more intelligent tasks Ejaaz: and it can take a lot more complex work off of your hands such that the value Ejaaz: that it produces to you over like the eight hours that you take to sleep overnight Ejaaz: would be considerable for you to actually be serious to use in your enterprise, Ejaaz: in your business, or just at your at-home lifestyle, right?

Ejaaz: So the point I want to make around here is Google's moat is not just its intelligence Ejaaz: or ability to create new models. It's not its TPUs. Ejaaz: It's its distribution. It's the entire product suite that it has that regular Ejaaz: users like you and I that use Gmail, that use Google Suite can now kind of benefit Ejaaz: from simply by plugging in that model.

Ejaaz: And I think like products like this, anti-gravity, I bet you, Ejaaz: Josh, we're going to see a slew of new Google product releases over the next Ejaaz: couple of weeks simply because they created this model. Josh: I hope so. I guess the contrarian take is like, okay, how many people are actually Josh: going to want to use them? Josh: We just spoke about how Claude is the superior code model. Everyone loves Cursor.

Josh: No one really uses the mobile applications of these. A lot of people are engaging Josh: with AI on their phone. So maybe it works for the right type of person. Josh: But Google still does have that product problem where they kind of have a tough time. Josh: They have the amazing intelligence. They just have a tough time using it. Josh: I mean, I don't have the Gemini app on my phone. I mostly use Grok and ChatGPT.

Josh: And there is this bar that they Josh: still need to cross that I think they're trying with Google AI Studio. Josh: And we had Logan Kilpatrick on, who was the head of that, to talk about it when Nano Banana came out. Josh: But there is still a bit of a long shot for them to get good at products to actually develop this. Josh: But what we saw this week is that there was a resounding, overwhelming amount Josh: of support, to your point, you guys, where the market just believes in Google.

Josh: And in a week where all of the stocks, all of the Mag7 was down, Josh: Google was the one anomaly. Google was up this week. Josh: And I think it's because the market is starting to realize, one, Josh: vertical integration through these TPUs is a huge deal. Josh: Two, Google has an existing business that is not reliant on AI. Josh: And sure, AI places a huge hand on that scale, but it is not everything.

Josh: And they are cashflow positive in the absence of AI. So all of this innovation Josh: that they're doing is really just applying later fluid on top of an already Josh: great business. And the market's starting to evaluate that properly. Josh: So Google is positioned very strongly. Josh: They have very high intelligence. Gemini 3 rocks. Josh: And I mean, again, we continue on the bull train for Google. Josh: I am a believer. I am a supporter.

Josh: I am stoked that they have the crown. I assumed it was only a matter of time. Josh: And now the question is, who's next? Josh: Who is the next competitor? Who's going to set the next plot on that chart and Josh: set the vertical trajectory on the exponential curve we're on? Josh: Do you have any guesses who you think it's going to be? Ejaaz: Yeah, well, I don't because I don't think it's going to be anyone for a while.

Ejaaz: I said this earlier in the show and I'm going to say it again. I think there's going Ejaaz: to be a six month period now where either the other model providers don't release Ejaaz: the model because it's not as good as Google's or they just kind of release Ejaaz: these kind of mediocre kind of like consumer products that kind of maybe benefit Ejaaz: certain consumers in one way or another, Ejaaz: but doesn't really kind of break the generalized model

Ejaaz: standard that Google has just set. Ejaaz: Just a last point on the kind of Google bull case thesis, they may not just Ejaaz: play in the same ring as cursor does. Ejaaz: Like I was critiquing Microsoft on another episode, Josh, do you remember? Ejaaz: And then I got off that episode and I was just like, Microsoft like dominates Ejaaz: the enterprise environment. Ejaaz: All the boomer companies and institutions love Microsoft and they have all their data and memory.

Ejaaz: And just because you and I don't use it or just I'll speak for myself, Ejaaz: just because I don't use it and I think it's doesn't mean that they're not absolutely crushing. Ejaaz: Google just came off a hundred billion dollar quarter of revenue. Ejaaz: That's like the highest they've ever had. So I don't want to be too hasty to Ejaaz: say that like Google's not going to make it because they can't make a sick consumer Ejaaz: product like OpenAI can maybe.

Ejaaz: I just think they're maybe playing in different fields. Ejaaz: But to the point around like I don't think anyone else is going to catch up. Ejaaz: Look at these comments. I want to show you two comments all right one is from sam altman Ejaaz: He goes, congrats to Google and Gemini 3. This looks like a great model. Ejaaz: The other is from the almighty being, Elon Musk, saying, I can't wait to try this out.

Ejaaz: And this is just one of a series of tweets that he's been putting out this week Ejaaz: saying, can you guys just drop Gemini 3? Because I need to see how good this thing is. Ejaaz: And the reason why I bring up these two people is both Sam Altman and Elon Musk Ejaaz: have released new versions of their models, GPT and Grok respectively, Ejaaz: but it's been the 0.1 upgrade. Ejaaz: It's GPT 5.1. It is Grok 4.1. and they are almost identical updates.

Ejaaz: You want to know what the biggest and coolest thing about their model updates were? Ejaaz: Personality traits, which don't get me wrong, is cool. Like I would like my Ejaaz: model to kind of respond in a very intuitive manner and get me, Ejaaz: but it's nowhere near the state of the art standard that we've just seen broken by Gemini. Ejaaz: So the point I'm making is, I think these two companies might have run out of fuel for the near term.

Josh: Grok is going to be next. You think? They're the next one. By the end of Q1, Josh: Grok will have the crown. Josh: Why? And I assume by a fairly large margin. But I assume it will be a different type of crown. Josh: And this is where I'm really excited to see how these models progress. Josh: We spoke a little bit earlier about how Cursor is kind of the coding model. Josh: Google has a very deep understanding of the real world and physics and video Josh: and understanding how that works.

Josh: Grok and the XAI team are very focused on the pursuit of truth and information. Josh: And I think that's kind of the alley that we'll see them going down. Josh: So they have the real-time data with X. They have the pursuit of truth. Josh: And where Google and OpenAI and all these other companies are trained on an Josh: existing data set, the XAI team and the Grok team are developing an entirely Josh: new synthetic data set that is maximally truth-seeking.

Josh: And we saw that early version with Grokopedia that should provide the most accurate Josh: and I guess thoughtful information. It should be the best of thinking because Josh: it's the closest to source truth. So while I think, Josh: Gemini will probably be better at physics and video and understanding the real Josh: world for quite some time. Josh: I suspect Grok will be really good at just communicating via text.

Josh: If text is a modality in which we interface from, Grok should be really good. Josh: And again, the rate of acceleration, Grok has been around for the least amount Josh: of time. They're accelerating the fastest. Josh: And I'm very, very, very excited for a Grok 6, Grok 5, whatever we're at announcement, Josh: hopefully early next year. So that's the predictions.

Josh: That's the episode. That's Gemini 3.1. It is an unbelievable new model. Josh: Everyone could try it out. So here's how you try it out. Josh: I believe you need to be a Google premium plus subscriber, whatever it's called. It's $20 a month. Josh: You can go on the Gemini website and it's just a text box and you can play around Josh: with it. They also have a mobile application. Josh: It's very easy to download on your phone, play around with it.

Josh: I'd love to see examples of cool things because I think one of the problems Josh: for me and one of the things I'd love help with from anyone who's listening Josh: is how do you use this thing to test it? Josh: What do I ask it? And how are you interfacing with it to get the maximum amount of results from it? Josh: Because intuitively, I would never think to record myself and ask for feedback, Josh: but that's a new possibility.

Josh: So I guess the challenge to anyone who's listening is figuring out how to get Josh: the most out of these new models as these new features get released. Josh: And Gemini 3 has just opened up the gates to a gazillion new use cases. Ejaaz: Yeah, I mean, this is a super cool release for Google. Ejaaz: And weirdly enough, it's not the only release over the last week. Ejaaz: I mean, I've got a list pulled up here. They've released new Android iOS updates.

Ejaaz: They've got a new search AI mode. They've released anti-gravity that we mentioned earlier. Ejaaz: We've got CIMA2 research, which we demoed on a previous episode. Ejaaz: You should definitely go check that out. Ejaaz: I mean, they are just not stopping and they're a force to reckon with. Ejaaz: And kind of similar to them, Josh, just to kind of round this episode out and Ejaaz: thank you guys for listening. Ejaaz: We are here in Argentina, in

Ejaaz: Buenos Aires. We are kind of meeting some of the fans that are out here. Ejaaz: And we spoke to one just this afternoon, Josh. And you know what he said to me? Have a guess. Josh: What's that? Ejaaz: He said, your podcast Limitless is like the state-of-the-art AI podcast. Ejaaz: In fact, it is 2X better than any other AI podcast that I've ever heard. And you know what? Ejaaz: That sounds very similar to Ejaaz: the Gemini 3. So you could potentially call us the Gemini 3 of AI podcast.

Ejaaz: And so if you're a listener to this, if you are a non-subscriber on our YouTube, Ejaaz: you should probably click that subscriber button. Ejaaz: You should probably click that notification button because guess what? Ejaaz: We've got more episodes coming this week. And guess what? the five star ratings help us out massively.

Ejaaz: So if you enjoyed this episode and if you want to hear more episodes of this Ejaaz: nature and of cutting edge news in AI, you should give us a follow and we will see