Marc Andreessen on AI, Geopolitics, and the Regulatory Landscape | Ray Summit 2024

Multimodal capabilities are important for robotics and real-world applications because unlike software-only AI, robots must perceive and act in the real world through multiple modalities (vision, manipulation, etc.).

“It's interesting to see how important all the multimodal capabilities are for robotics and real world stuff”

ChatGPT, Claude, and similar AI systems have high usage numbers, allowing ordinary people in regular jobs and professions to use them for asking questions, getting guidance, dealing with complex situations, navigating government, understanding laws, and accessing an AI to help them through various challenges.

“you know and this is one of the great things about technology is like you know by the way the usage numbers are like you know on fire and so that the number of just ordinary people in regular jobs in regular professions um you know who are able to use chat GPT or any of these systems today and are able to you know ask questions and get guidance and figure out how to like deal with complex situations or deal with the government or navigate you know laws or you know figure out like you all of a sudden everybody has like a an AI they can talk to to kind of help help them through all these things”

The Ukraine battlefield is demonstrating the contrast between 20th century versus 21st century warfare: Russian military using traditional tanks versus Ukrainian forces using first-person-view professional video game players piloting autonomous drones and shoulder-mounted AI-guided weapons (like Javelins with fly-by-wire homing) that automatically target and attack, resulting in devastating losses for Russia.

“what's happening on the Ukrainian battlefield is shaping a lot of thinking around national security...It's like it's like 20th century versus 21st century...the Red Army, you know, the the Russian military basically is, you know, driving tanks down. Um, and the Ukrainians are responding with, you know, first-p person, you know, basically literally professional video game players piloting in VR, you know, piloting autonomous drones...these shoulder-mounted, you know, weapons like javelins, um, that again are kind of, you know, they call them fly by wire. They sort of, you know, they sense where the the thing is...you fire it and it automatically homes in on the tank and then drops down through the hatch. Um and so you know the Russians have taken devastating losses”

A longshoreman strike kicked off today based on opposition to automation—specifically, the workers' position is flat-out no more automation, no more machines, we're done, representing pure anti-automation sentiment in response to automation concerns.

“There's a long shoreman strike actually that's that kicked off today, you know, where the the guys, you know, basically people who load and unload boats on docks and it's just like it's like a flatout just anti-ext. It's just flat out no more automation, like we're done. Literally, that's the strike is no more automation, no more machines, we're done”

Evidence for LLM commoditization includes that price per token of LLM output has dropped 100x in the last year, which is much faster than Moore's Law and opposite of what you'd expect if someone was going to profit from LLM businesses.

“the price per token, right, of generated LLM output has dropped 100x in the last year, right? Which is like much faster than Moore's law, which is the exact opposite of what you'd expect if somebody was going to, you know, get a lot of profit out of that business”

Google leaked memo said 'we have no moat and neither does anybody else' because if you have the same data, you get the same results, everybody has the same data, so LLMs are commoditizing.

“There was a famous Google memo that leaked called, you know, we have no moat and neither does anybody else where they kind of articulate basically saying if you have the same data, you get the same results. Everybody has the same data”

Humanoid robots are currently struggling with low-level physical tasks (cracking an egg without destroying everything) but are capable of teaching quantum physics in a plummy British accent through LLM interfaces, showing a gap between reasoning/language capabilities and embodied manipulation.

“these robots, as you see, the demo is like so the these humanoid robots like they've got their like they've got their like control system, which is like the the state-of-the-art. like this reinforcement learning algorithm to try to get it to like crack an egg without destroying everything on the table or whatever. Um, but then they've got they've all got like LLM user interfaces with like voice voice now. And so it's like struggling to crack an egg, but it's like teaching you quantum physics, right? Like like in like a plumby British accent like at the same time, right?”

Biotech faces a real challenge with data access: the ideal would be getting everybody's health data and genome data together, which would be completely illegal in the US and result in jail time, but is apparently acceptable in China—creating an opportunity for China to potentially leap frog on biotech progress.

“it's a real challenge. Um, it's a real challenge. And I would say it's a real challenge in particular because access, you know, what you really want, like if you wanted the perfect biotech industry. What you would want is you would want to basically get, you know, get everybody's health data, you know, pull it all together. You know, you'd want to get everybody's genome data, pull it all together. You know, that in the US that would all be completely illegal. You know, you would never be allowed to do that. You would go straight to jail. Um, you know, interestingly, in China, that's actually just fine”

What triggered the shift to AI-based military systems was the realization that autonomous systems work: self-driving cars demonstrated autonomous ground operation (DARPA grand challenge 2005), airplane autopilots showed autonomous air operation, and taking pilots out of aircraft enables different, faster, more maneuverable designs without humans to protect.

“they started well one is they they you know self-driving cars self-driving cars started to work you know the the original DARPA grand challenge for self-driving cars was back in 2005. And then so you started to see those basic systems started to work. And then they you started, you know, obviously autopilots on on airplanes started to get really good. And they started thinking about taking the pilot out of the airplane. And if you take the pilot out of the airplane, all of a sudden you can build very different kinds of aircraft that, you know, maybe are like much more maneuverable, much faster because they don't need keep a pilot alive”

The US military views current dynamics as requiring complete reinvention of its force structure: from aircraft to submarines, everything from how things are fueled to how they operate is going to completely change because the economics and strategic implications of AI-enabled autonomy are incompatible with existing platform design.

“If you talk to people in the US military, they're like, 'Okay, now we need to basically reinvent the whole thing.' Like the the way that we feel everything from aircraft to submarines, like all these things is is is just going to is going to completely change”

There is a fine line between hallucination and creation in AI systems—as demonstrated by Runway's ability to create spectacular videos. AI can now literally create art, giving users another application of the same underlying computational capability.

“there's this like fine line between hallucination and creation you know so we we have literal you know literally computers now that can create so it could be a feature or actually create art. And so we we basically have sort of another bite of the apple, right? The the sort of magic apple. Um you know, we have all the traditional computers and now we have this new kind of computer”

There is a huge advantage for startups in the AI era because they can start from scratch, while incumbent tech companies adding AI to existing products face limitations—like adding flour to a cake after it's already baked instead of building from the recipe foundation up.

“of course that means it's kind of it's going to be prime time for startups right that that have the huge advantage of being able to uh you know to start from scratch...if you have an existing product and you add AI to it, it's a little bit like, you know, adding flour into a cake, like after the cake's already been baked. like it doesn't like doesn't work well. You you if if if there's a really transformative technology, you have to like get you have to get the flour into the recipe from the very beginning”

AI systems are a new kind of computer—probabilistic computers that give different outputs for the same input, unlike deterministic computers which give identical results. This probabilistic nature means AI systems can hallucinate (make things up when they don't know answers), which mirrors how people behave.

“at our firm the way the way that we think about AI systems is they're new kinds of computers. Um and the way we describe it kind of traditional computers are so-called deterministic computers which is you know they they give you the same answer every time...AI systems, we view them as as computers also, but probabilistic computers. You give them the same input twice, they give you two different outputs...they hallucinate, right? you know, they like people describe it's like people describe to me it's like is AI skeptical say things like well you know AI AI you know is not useful because like when it doesn't know the answer it it just makes something up and I'm like well have you met people”

There is an asymmetry in the Ukraine conflict: for Russians, there's always a guy in the tank, but for Ukrainians, there's no guy in the drone—an asymmetry that enables Ukraine to punch way above its expected weight and inflict devastating losses on Russia through aggressive in-field innovation.

“there's always a guy in the tank. For the Ukrainians, you know, there's there's no guy in the drone. So so there there's an there's an asymmetry to it. Um and so you know Ukraine has punched way above the weight that all of the planners expected when this whole thing first started because they've been able and they've been very aggressively innovating in the field you know for how this stuff works”

Historically, warfare was about mass: Napoleon's principle 'God is on the side of the big battalions' captures that success depended on numbers of soldiers and material. Projecting forward, future military success will shift to being based on who has the best technology and most money, because those factors determine who can develop or buy the most advanced technology.

“defense historically like you know, sort of warfare has been an issue sort of of mass and you know, sort of number of men, amount of material, right? So, how many how many soldiers do you have? And then like how how many tanks do you have, you know, sort of it's Napoleon, I think once said, God is on the side of the big battalions, right? And so, it's like, you know, just just like massive force. Um, and you know, argu if you project this forward enough, what you kind of see a picture emerging is actually in the future success will be based on who has the best technology and the most money, right?”

Technology becoming politically loaded is the tech industry's own fault. Tech people who grew up believing their work was really important wanted the rest of the world to understand, and now that it does, they're like a dog that caught the bus—they have the world's attention but don't know what to do with it, and the bus (world attention) just keeps going while they get dragged along.

“I think basically so I so start by saying I think it's our fault. Um so I I blame us and by us I mean myself and my firm and my companies and all I think it's all your fault. uh everybody here uh shares the blame. So um look like a lot of us who kind of grew up you know in technology grew up you know engineering you know I you know my degree is in in computer science um you know we we sort of were like wow like we think the stuff that we're working on is like really important and like we wish the rest of the world would understand how important it is and and now they do right like they didn't for a long time and now they do. And so I I use the metaphor of the dog that caught the bus, right? Which is, you know, the dog chases the bus, you know, never expecting to catch it, and then, god forbid, you know, the dog ends up with a tailpipe in its mouth. Like, what does it do with the bus, right?”

One of the great things about AI is it's rolling out in a very democratic way: unlike computers 50 years ago (which started as $20 million mainframes and took 30 years to reach personal computers), the best AI systems are rolling out to consumers first.

“One of the great things about AI is it's rolling out in actually a very democratic way, right? So, so and if you think about this, like the way the computer technology rolled out like 50 years ago, it showed up in the form of like, you know, $20 million mainframe computers and then it trickled its way down over 30 years to personal computers and then smartphones. One of the most amazing things about AI today is the best AI systems are rolling out to consumers first, right?”

There is prospect for a general uplift in intelligence when everyone has access to AI systems: people will have a level of intelligence available at their fingertips that hasn't been historically available, including politicians, policymakers, and military planners—creating a 'decision support system' available to everybody.

“I think there's the prospect for sort of a general uplift of in of of intelligence, you know, basically of of of people having, you know, a level of intelligence available to them at their fingertips that we we haven't historically had. You know, that that certainly includes, you know, politicians, policy makers, you know, um that certainly includes, you know, people like military planners, like everybody's going to have this sort of additional level u we used to call decision support systems”

The speaker experiences two conflicting conversations in DC about technology: the 'Tuesday conversation' frames it as US versus China competition requiring US technological dominance for national security and democracy, while the 'Thursday conversation' focuses on US internal concerns about technology being weird, scary, and AI requiring regulation and slowdown.

“I've been spending a lot more time in DC than I used to and I sort of have these two very different conversations in DC um I call it's called the Tuesday conversation Tuesday conversation is it's it's US versus China and then you know Iran Russia and so forth and we and this this revolution is here and the US needs to be the dominant technology global superpower because that's what's going to lead to us, you know, being being strong and pro protecting democracy and protecting our allies and all these other things...And then on Thursday I go back and they forgot about the China topic. Um, instead they're just focused on the US and they're like technology is like weird and scary. um and like it's like freaking us out and like AI is really scary and like we think we ought to stop this whole thing”

The tech industry must ensure that AI technology stays democratic and open. Open source is important because it would be bad if AI technology were centralized in the hands of a handful of companies—society needs cultural access to this technology.

“and really help people understand this and and and by the way also make sure that this technology stays democratic and stays open. One of the reasons like I think open source is so important is like I think it'd be very bad if this technology is centralized in the hands of a handful of companies. I think you know it's very important society culturally that this is something that everybody has access to”

Both emotional impulses underlying the tension—fear of losing a war with China and fear of AI disrupting jobs and society—are emotionally valid, because losing a war is devastating and AI disrupting everyone's jobs and changing society is also scary. The tech industry must increasingly explain itself and engage in policy process.

“both of these impulses are very emotional right these are very emotional topics because if you picture us losing a war with China you know that's just devastating emotionally. If you picture AI you know completely revolutionizing everybody's jobs and you know changing society that's also very scary. Um and so you know we we do we we as an industry are going to have to increasingly step up and explain ourselves and articulate what we're trying to do and you know engage in the policy process”

AI will be transformative in biotech, finance, and defense sectors. The firm is investing across all of these domains and believes AI will reinvent almost every product category people currently understand, with examples like video editing being replaced by talking to computers that do image generation and editing.

“one is we think it's going to be transformative in in actually every single one of those sectors, and we're we're investing across all of those...I think there's a really good chance that it you know it really reinvents almost every product category that we think we understand today. And again, take runway as an example, like are people in the future really going to be doing video editing or photo editing like you know using like Photoshop or Final Cut Pro or these things or are they going to are you going to be talking to the computer and the computer does does the does the image generation editing”

When the speaker tries to reconcile the Tuesday and Thursday conversations by repeating the Tuesday arguments on Thursday, policymakers say 'no, that's your job' to reconcile them—creating a real tension where the tech industry must navigate between emotional concerns about job displacement and existential risk versus geopolitical competition requirements.

“I kind of say well like you know I I repeat the Tuesday conversation on Thursday and I'm like you know could you please reconcile you know these two points of view for me and they say no that's your job. Um so there's a real tension underway right now”

Humanoid robots when rolled out to consumers could cost $10,000-$20,000, enabling subscription models for robotics and making mass deployment economically feasible, with costs looking to come in at those price points based on current Unitree humanoid hardware advancement rates.

“So, there's a chance that the um humanoid roll out will look more like a $20 subscription democratized versus a $20 million mainframe. Yeah. Look, so this company Unitry has um they have a I think it's a it's a I think it's a 60 $50,000 humanoid now. Um hardware and you know, if you if you just watch on their website, like they're advancing the the the sort of hardware capabilities like super quickly. Um and so, you know, it looks like the humanoid robots when they roll out, I don't know, mass market. You're talking about to consumers 20. Yeah. To consumers. Well, the the hardware cost looks like it's going to come in at I don't know, $20,000, $10,000”

Many startups pitch with a 'bullet point number six' phenomenon where their existing product feature list includes AI as the sixth bullet point, indicating they added it after the fact, while smarter companies redo their slides to show AI-first design.

“we have this phenomenon we call bullet point number six. um or we'll get a sort of a you know 5-year-old company or whatever will come in and pitch and and they'll have their product slide and it'll have you know the five kind of things their product does and it'll have bullet point number six is oh it also does AI right and it's always bullet point number six because of course they added it after the fact right that you know they couldn't quite you know the smart ones go in and redo the slide”

A fair number of people in the US and California want to adopt the EU regulatory model and are lobbying hard to do so, while some are true believers who genuinely believe there's a profound societal or existential threat, and others have commercial self-interest in establishing monopolies or cartels and want government protection for their business.

“we have a fair number of people in the US and in California which is amazing uh who basically want to adopt the EU model and they're you know they're lobbying very hard to do that some some of those people by the way are true believers you know they they really believe that there's like a profound societal threat or you know existential threat or various other kinds of threats you know they they really believe it and you you kind of see it in their eyes. Um and then um you know there's a bunch of other people that have commercial self-interest, right? And you know they want to establish monopolies or cartels of different kinds and and they want uh there to be um you know basically government protection uh for their business and so there's this like unholy alliance that's sort of formed up between these two groups”

The bits version of the AI revolution may be followed almost immediately by the atoms version (robotics), where we could have a convergence of software AI and hardware robotics nearly simultaneously, driven by Elon and other entrepreneurs working on robot software.

“And so, it may be that we have the sort of bits version of AI revolution. It may be followed like almost immediately by the Adams version...there's all these questions around how to actually build all the software for robots. And, you know, Elon and others are and lots of startups are working on that. And so, it may be that we have the sort of bits version of AI revolution. It may be followed like almost immediately by the Adams version. That's incredible”

In the web-to-mobile transition, big incumbent companies like Google and Facebook actually did fine, suggesting that while startups have an advantage in AI, established tech companies that adapt successfully can still thrive—making the future genuinely competitive.

“in the mobile to web you know in the in the web to mobile wave a lot of the big actually incumbent companies like Google and Facebook actually did just fine Right. Um, you know, I tend to think that startups have a have a have a really uh great run here, but you know, it's going to be a real fight, you know, kind of in the industry and we we'll see”

AI and engineering platforms in biotech will converge: once you have an engineering platform, you can bring AI to bear, enabling rational design of drugs and biological systems using computational methods.

“the minute you have an engineering platform you could you can bring AI to bear”

There is a connection between having the most money and having the best technology: with the most money, a nation can either develop the best technology or buy it, meaning military dominance will require being the strongest economy with the most advanced technology.

“there's some connection between the best technology and the most money because if you have the most money, you can either develop the best technology or buy the most technology. Um, and so it it sort of changes the the N and by the way, it means like if you want to then be the strongest military force, you then want to be the strongest economy with the most advanced technology”

AI might help arguments become more rational (through better access to information and analysis), but it won't dampen emotion at all—there will be tremendous amounts of emotion as AI rolls out, and the industry must increasingly explain itself and engage in the policy process.

“But you know that I would say that what that what hopefully that means arguments can get a little bit more rational. But what that doesn't do is it I don't think that dampens emotion at all. Right. And and I think that I think there's going to be just like just tremendous amounts of emotion as this as this technology rolls out as as is already happening. Um, and so I just think like we as an industry are going to have to increasingly step up and explain ourselves and articulate what we're trying to do and you know engage in the policy process”

AI represents an 80-year overnight revolution—an overnight in terms of the sudden visible progress from 2012 onward, but overnight in the making because 80 years of ideas from neural network research now work and will get used in all kinds of ways.

“the way I think about this, this is like an overnight revolution that's been like 80 years in the making, right? And so, and so it turns out it's it's incredible because it turns out we have this incredibly rich, you know, kind of history of 80 years of ideas now that that turn out to work”

Technology has become politically loaded over the past decade for multiple reasons, causing the speaker and his firm to be much more engaged in politics now and spending more time in DC than previously.

“technology has become a very politically loaded topic over the last you know decade for a bunch of reasons and so I've been at our firm we're much more engaged now in politics than we used to be and I've been spending a lot more time in DC than I used to”

There is a real fight underway about open source AI: there's a real move to ban open source and specifically open source AI, including attempts to ban the underlying math (linear algebra, gradient descent) which the speaker finds mindboggling because these are fairly basic algorithms taught in schools and learned by nine-year-olds.

“there's a real fight. So there there's a real move underway to ban open source and that and specifically open source AI and specifically the math um under under under AI which you know is is fairly mindboggling for me as an as an engineer you know just in the talking about linear algebra. It's not that complicated, right? Like it's it's right. It's linear algebra. It's it's you know gradient descent. These are fairly basic algorithms. They're taught, you know, broadly in schools today. My nine-year-old is starting to you know, learn this stuff. Um, uh, there are videos on YouTube that teach you how to do this. There's textbooks”

We might soon have a billion humanoid robots in the field gathering data and feeding it back for continuous improvement, creating one of the largest scale technical systems ever built—compounding feedback from massive deployment.

“But like we might be in a world within a few years where we've got a billion humanoid robots that are also gathering all that data and feeding it back and getting better. And so it may be one of the largest scale technical systems that we've ever built. It might be very close”

Discussions in Washington about banning open source AI and the underlying mathematics are disconcerting, and there is potential for a stifling blanket of regulation similar to what happened in the EU.

“but like there there are serious like the discussions in Washington are like disconcerting on this topic because they they seriously uh, you know, talk about this. Um, and then you know there there's like outright bans and then there's also just like sort of what I call sort of the potential for like a this sort of stifling blanket of regulation”

For people building AI infrastructure at an infrastructure conference, this is prime time. The industry is just starting, and what exists today will look like it belongs in a museum in 5-10 years compared to what's coming. All participants will play a big role in building this out.

“I mean look like it's it's going to be prime time. Like you guys are in the right field. Um because you know this is it like this is going to be the big buildout. Um and it's just starting and you know it's going to be one of those things where we look at the stuff that we have today. You know we look at you know 5 years from now 10 years ago and it's it's going to look like it was you know belongs in a museum as compared to what's coming. Um and so and you know all all of us here are going to play play a big role in in building that”

Drones provide a precedent for how China could saturate the world with robots: China swamped the world with drones, and they may similarly saturate the world with robots at least on the hardware side, while there remain questions about building the software for robots.

“drones drones were kind of an example of that, you know, where China just like swamped the world with drones. And I think, you know, they may well swap the world with robots, at least on the hardware side”

A major open question is whether large language models are a race to monopoly (biggest company has best model, charges premium prices, huge margins) or a race to the bottom (commodity intelligence, anyone can build LLMs, price per token dropped 100x in last year).

“are the large language models like OpenAI. Are those businesses basically a race to monopoly and infinite profits because of scale, right? The the biggest company's going to have the best model. It's going to answer all the questions better and then they're going to charge whatever they want for it...Or the answer is actually are all those companies actually in a race to the bottom, right? in which it actually turns out, you know, selling, you know, intelligence is like selling rice”

One possible outcome is 'profitless prosperity' where LLM companies have lots of revenue but very low margins, like selling rice or any commodity—high volume but thin profits.

“And the term sometimes used there is a profitless prosperity, which is, you know, like like selling rice or any commodity. These companies will have a lot of revenue. They'll just have very very low margins”

Large questions about value capture in AI (where will profits go? who will win?) mean the investment firm is trying hard not to prejudge the outcome, because they actually don't know yet which approach will succeed.

“there's really big questions around where the value capture is going to happen. And we're we're we're actually trying very hard to not prejudge that because I think we actually don't know yet”

It is uncertain whether human soldiers will be at risk in military roles (field, aircraft, submarines) in 20 years, but the speaker expects probably not—suggesting near-complete autonomy is a plausible future for military operations.

“Will you even have human soldiers, you know, at risk in the field or in planes or in submarines in 20 years? Like maybe, but I think probably not”

There is an unlimited number of technical issues to solve in AI infrastructure, and the industry is on an incredible voyage of discovery determining which domains of AI will progress the fastest.

“Um yeah and so this is going to be like absolutely prime time. Um you know there's an unlimited number of of technical issues issues to solve obviously. uh you know but look on top of that we're on this incredible voyage of discovery I think as an industry and of a world of you know which which of these domains of AI are going to be the ones that really take the fastest”

The 'Peter Thiel thing' is that VCs should just invest in Nvidia instead of AI startups, because Nvidia will capture all the venture capital invested in AI startups plus all revenues those startups generate—and this has been a good strategy for the last 10 years.

“The Peter Teal thing is, um, you know, we're all wasting time with all these software companies, right? We should just put all of our money into Nvidia. Um, you know, and just and call it. And by the way, for the last like, you know, 10 years, that would have been a very good, you know, very good strategy”

The outcome of chip competition is uncertain and depends on decisions by large companies and startups, and by customers and users—a collective voyage of discovery where choices made by all parties determine whether Nvidia maintains dominance or loses market share to competitors.

“these are none of these things or one of the things that's hard to forecast these things is it it depends on what people do right and so you know what decisions are made today at the big at the other big companies and what decisions are made by the startups and VCs and you know by the way customers and users um you know and all the people building around this you know what what do they all want and so we're we're we're kind of on a on a collective mission of discovery to figure that out”

It is strategically important for a country to win in technology, which is something that's hotly controversial today, and the shift from mass-based warfare to technology-based warfare changes the nature of national competition.

“It means it's like really strategically important for your country to actually win in technology, which is, you know, something that's sort of hotly controversial these days”

Runway demos showing spectacular AI-generated video content are causing Hollywood to be freaked out about a future where movies can be rendered by AI and classic actors' images can be used to generate films for thousands of years, raising questions about whether there will ever be new actors or if the future is just Tom Cruise movies rendered endlessly by AI.

“the runways you know you know the spectacular runway demos like you know people in Hollywood are like freaked out right because like you know what does it mean to be entering a world in which movies can be rendered by AI right um and what does it mean you know for example give you an example like you know movie actors like if you know the you know great movie actors of the past can can have their images, you know, being rendered in AI, you know, for the next thousand years, you know, literally is the future of the movie industry going to be Tom Cruz movies for the next thousand years, you know, kind of rendered over and over again in AI. Like, will there ever be any new actors, right?”

Nobody quite knows the answer to whether LLMs will be monopolistic or commoditized, and it depends on what happens in the ecosystem, such as Meta's release of Llama and open source models which could really change how the future unfolds.

“I think sitting here today, nobody quite knows the answer to that. You know, it also depends on things that happen, you know, in the ecosystem. I think like, you know, Meta, you know, where I'm on the board, the the release of the llama, I think open source models has really I think it's really changed how the future's going to unfold, you know, because having fully competitive open source, I think, really changes things”

Cerebras is going public this week, illustrating the startup competition in AI chip design, suggesting that in five years, Nvidia may be part of the ecosystem with multiple big companies and 10 startups offering alternative approaches.

“Cerebras, I think, is going public this week. Um um and so you have lots of startups and and you just have like lots of people who are like, 'Wow, I want a piece of that pie.' Uh and and by the way, another argument on that would be GPUs...And so, you know, it may be in, you know, in five years from now, Nvidia is still a great company, but they just they, you know, they're part of the ecosystem. And it turns out there's, you know, five other big companies and 10 other startups and a whole bunch of other approaches”

There is a software wave happening to merge AI approaches by creating multimodal models capable of reasoning, planning, and potentially powering robots—OpenAI's 01 is a reasoning engine, Llama release has open source multimodal capabilities, and within a year a single multimodal model could power robot reasoning and planning.

“There's this software kind of wave happening right now to try to like merge those approaches together, right? uh and have you know sort of multimodal models that are capable of reasoning and planning and and you know that you know the new llama release just dropped I think last week that has multimodal open source um and then you know open AAI just released their 01 you know the planning the reasoning and planning engine which they you know they say is going to get a lot better from here and so like it may be that in a year we actually have a sort of single multimodal model that can do reasoning and planning that can power a robot and then we're off to the races”