Educational Technology and Change Journal

By Jim Shimabukuro
Editor

Introduction: The following informal transcript was grabbed off a YouTube video this afternoon, Nov 19, 2025. I relied on the audio and CC. I focused on Elon Musk’s and Jensen Huang’s talks. I omitted the introductions, host’s comments, and small talk. I didn’t have the time or resources to review and edit, so expect typos and possible errors. -js

Elon Musk: It’s mostly not disruption, it’s creation…. There are no useful humanoid robots at this point. There are sort of gimmicks…. I think Tesla is going to make the first actually useful humanoid robots. This will be quite a revolution, and I think something that everyone will want. Who wouldn’t want their own personal C3PO R2-D2. Everyone would want one, right?… Humanoid robots will be the biggest industry or the biggest product ever. Bigger than cell phones or anything else because everyone’s going to want one or maybe more than one. And there will be many in [the] industry. A humanoid robot would be better than R2D2 and C3PO combined…. AI and humanoid robots will actually eliminate poverty. Tesla won’t be the only one that makes them. I think Tesla will pioneer this, but there will be many other companies that make humanoid robots. There is only basically one way to make everyone wealthy, and that is AI and robotics.

Jensen Huang: I’ve said that AI is an infrastructure and the reason for that of course we understand AI from the perspective of the technology and how it’s revolutionizing every industry. Digital intelligence of course has applications into every field. So it’s going to be used by every company, every industry, every country. In that way, it’s foundational and therefore it’s part of the infrastructure. What is new about AI from a computer science perspective is that the way computing was done in the past was largely retrieval-based computing. Somebody typed in a story or created a piece of art or came up with four versions of a digital ad. It’s all pre-built by somebody which is then using a system to retrieve the appropriate version for you. It’s a retrieval-based computing model. Many of the frameworks and operating systems of the past all were designed to retrieve the appropriate information for you. But today, software is going to be generated in real time. It’s generative, based on the context, based on the circumstance, based on who you are, based on the problem you ask that’s based on your prompt. It will generate unique content for you every single time for everybody. It’s unique. When you use Grok, every time you use it, it’s different. Just based on the prompt that you give it and based on the circumstance. Therefore, it used to be retrieval-based, [but] today it’s generative. And if it’s generative then and every time is different, then you need AI factories all over the world to generate the content in real time, which is the reason why you need AI factories, and this is a unique way of doing computation but the benefit of course is that everything isn’t preconceived and pre-documented and it’s contextually sensible and therefore intelligent.

Musk: In the long term where will things end up? I don’t know what long term is. Maybe it’s 10-20 years, something like that. For me that’s long term. My prediction is that work will be optional. It’ll be like playing sports or a video game or something like that. If you want to work — in the same way like you can go to the store and just buy some vegetables or you could grow vegetables in your backyard. It’s much harder to grow vegetables… but some people still do it because they like growing vegetables. That will be what work is like — optional. Between now and then there’s actually a lot of work to get to that point. I always recommend people read Iain Banks’s culture books to get a sense for what a probable positive AI future is like. And interestingly in those books, money no longer exists. My guess is if you go out long enough, assuming there’s a continued improvement in AI and robotics, which there seems likely, the money will stop being relevant at some point in the future. Now there will still be constraints on power like electricity and mass. The fundamental physics elements will still be constraints. But I think at some point currency becomes irrelevant.

Huang: I would say there’s different horizons you could look at. Everybody’s jobs will be different. I think that’s for sure. How the students learn will be different. How people do their work will be different obviously because a lot of the things that we do mundanely or arduously or very difficultly are going to be done very simply. So we’re going to be more productive from that sense. One of the things that I will say is that for most people or companies, if your life becomes more productive and if the things that you’re doing with great difficulty becomes simpler it is very likely because you have so many ideas, you’ll have more time to go pursue things. It is my guess that Elon will be busier as a result of AI. I’m going to be busier as a result of AI. And the reason for that is because we have so many ideas we want to puruse, so many things we have in our backlog inside our company that we can go pursue. If we were more productive, we can get to those things faster. So in the near term, I would say that there’s every evidence that we will be more productive and yet still be busier because we have so many ideas. One thing that I will say, give you some evidence, is, and I was telling Elon about this earlier, radiology for example, has largely been converted to AI-driven radiology, and there’s some really great companies doing that, and the surprising thing is the prediction that all radiologists would be the first jobs to go was exactly the opposite. The trend shows that there are more radiologists being hired now as a result of AI, and the reason for that, if you take a step back, it’s because the goal of a radiologist is not to study the images. The goal of a radiologist is to diagnose a disease. Now, the studying of the images became so productive, they could study more images, study more modalities, spend more time with the patients. And as a result, they were actually accepting more patients. We’re doing more radiology all around the world. We’re doing a better job with diagnosing disease. And so that’s kind of the near-term outcome of AI and productivity. And we’ll see what happens long term. When currency doesn’t matter anymore, let me know right before.

Musk: You’ll see it coming.

Huang: We text often.

Musk: Yeah we do.

Musk: We’re excited to announce that we’re doing a 500 megawatt….

Huang: We’re announcing all kinds of things. We’re working with Humane on Omniverse digital twins. AI is not just agentic AI and chatbots and cognitive AI is incredibly important to the world. But AI applies to everything, chemicals and proteins and genes and physics and fluid dynamics and particles and of course robotics and activation, and we created this world called Onniverse where robots can learn how to be good robots, and it’s physically based. It obeys the laws of physics. And so robots can learn in these environments, and we’re working with Humane to apply omniverse to all kinds of digital factories and robotics and warehouses and things like that. We’re also working in Saudi Arabia to build supercomputers to simulate quantum computers and using our computers to be the controller and the error correction. Quantum error correction requires an enormous amount of computation, and so we’re doing a lot of great work there, too. So a big partnership with Humane. They’re off the charts, off the ground and off the charts at the same time.

Musk:  If civilisation continues, which it probably will, then AI in space is inevitable. I always have to preface, we shouldn’t take civilization for granted. We need to ensure that civilization has an upward arc. Any student of history knows that civilizations have life cycles. Hopefully we are in a strong upward arc, I think we are for now, but we don’t want to take that for granted or be complacent. The way to think of AI in space is that in order to achieve any meaningful percentage of a Kardashev 2-scale civilization, where you’re using even a millionth of the sun’s energy, you must have solar-powered AI satellites in deep space. Once you think in terms of a Kardashev 2-scale civilization, which is what percentage of the sun’s energy are you turning into useful work, then it becomes obvious that space is overwhelmingly what matters. The Earth only receives roughly one or two billionth of the sun’s energy. So if you want to have something that is, say, a million times more energy than earth could possibly produce, you must go into space. This is where it’s kind of handy to have a space company, I guess.

Huang: Easier to cool chips in space, too.

Musk. Yes, easier to cool chips in space. Yeah, there’s definitely no water in space. So you’re going to have to do something. We’re gonna do something that doesn’t involve water, just hang out. Well, it’s just gonna radiate. The cost effectiveness of electricity like the cost effectiveness of AI in space will be overwhelmingly better than AI on the ground. So far long before you exhaust potential energy sources on Earth, I think even perhaps in the four or five year time frame, the lowest cost way to do AI compute will be with solar-powered AI satellites. So I’d say not more than five years from now.

Huang: And just look at the supercomputers we’re building together. Let’s say each one of the racks is two tons. Out of that two tons, 1.95 of it is probably for cooling.

Musk: Right.

Huang: Just imagine how tiny that little supercomputer is, right? Each one of these GB300 racks will just be a little tiny thing.

Musk: And just electricity generation is already becoming a challenge. So if you start doing any kind of scaling for both electricity generation and cooling, you realize, okay, space is incredibly compelling. Let’s say you wanted to do, I don’t know, two or 300 gigawatt per year of AI compute. It’s very difficult to do that on Earth. The US average electricity usage, last time I checked, was around 460 gigawatts per year average usage. So something like say 300 gigawatts a year, that would be like 2/3 of US electricity production per year. There’s no way you’re building power plants at that level. And if you take it up to say a terawatt per year? Impossible. You have to do that in space. There just is no way to do a terawatt per year on Earth. In space you’ve got continuous solar. You actually don’t need batteries because it’s always sunny in space. And the solar panels actually become cheaper because you don’t need glass or framing. And the cooling is just radiative. So that’s why I think that’s the dream.

Huang: I think it’s really important when you look at what’s happening around the world and go back to first principles of what’s happening in computer science and computing. There are three things that’s happening. The first thing is that we all know that Moore’s Law has run its course, and the ability that the amount of demand for computing versus the amount of computation we can get out of general purpose computing is really challenging, and so the world’s been moving to accelerated computing for some time. We’ve been pushing this now for some over 20 years…. Six years ago CPUs were 90% of the world’s supercomputers, top 500 supercomputers six years ago. This year less than 15%. Went from 90% to 10%. And meanwhile accelerated [computing] went from the other way, 10% to now 90%…. The second thing is …. the last 15 years is called Rexes [RecSys], recommender systems, how do we know what information to recommend to us in a social feed…. The world is, the internet is so gigantic without a recommender system that little tiny phone of ours will have no chance of ever seeing the right information. That Rexes is the engine of the internet today. That’s going generative AI. It used to be running on CPUs, now runs on GPUs. Which then says the third thing when if you just look at those two applications many of the internet companies can build enormous number of GPU supercomputers just doing that. Of course, then it creates the third opportunity on top of it, which is agentic AI. This is Grok and this is OpenAI, this is Anthropic, you know, this is Gemini. Agentic AI sits on top of that, but don’t forget to think about what is happening above, underneath, what everybody sees as AI today. There’s a whole movement of computing from general purpose computing to accelerated computing, and if you just take that into consideration, you’ll come to the conclusion that in fact what is left over to fuel that revolutionary agentic AI is not only substantially less than you thought, and all of it is justified.

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