Andrej Karpathy

“I think there's going to be a lot of people who are going to try to do to do the obvious things, which is like, oh, have an LLM and ask it questions and get, you know, do all the basic things that you would do via prompting right now.”

Expects: Andrej Karpathy expects many people to try using LLMs for basic educational tasks, such as asking questions through prompting. · no date given · not yet resolved

“I will hire faculty, I think, because there are domains in which I'm not an expert. And I think that's the only way to offer the state of the art experience for the student ultimately.”

Expects: Karpathy expects to hire faculty in fields outside his expertise, believing this is necessary to provide students with a state-of-the-art educational experience. · no date given · not yet resolved

“The digital offering is, yeah, a bunch of stuff on the internet and maybe some LLM assistant and it's a bit more gimmicky and a tier below, but at least it's accessible to like 8 billion people.”

Expects: Karpathy envisions that a lower-tier digital education offering, with online materials and possibly an LLM assistant, could become accessible to roughly 8 billion people. · no date given · not yet resolved

“I don't actually think that, I think there will be transitionary period where we are going to be able to be in the loop and, you know, advance things if we actually understand a lot of stuff.”

Expects: The speaker expects a transitional period during which people can remain involved in advancing technology, provided they understand a great deal. · no date given · not yet resolved

“It's going to start making up its own language. It's going to start using words that are extremely rare,”

Expects: Excessive entropy encouragement could cause a model to invent its own language and use extremely rare words. · no date given · not yet resolved

“I think it will. I mean, it is fundamentally automation, but I mean, it will be like extremely foreign. I do think it will look really strange because,”

Expects: A civilization containing advanced AI will probably feel extremely foreign and look strange. · no date given · not yet resolved

“I think that there's going to be, we're going to be able to gobble up what, in my understanding, is being built because I do think that, for example, cloth code or OpenAI codecs and stuff like that, they didn't even exist a year ago,”

Expects: The speaker expects demand to absorb the compute infrastructure being built, citing AI coding tools that, in their understanding, did not exist a year earlier. · no date given · not yet resolved

“If I had a turtle like that for any arbitrary piece of like knowledge I think it's gonna be so much easier to learn anything”

Expects: A capable tutor will probably make learning arbitrary subjects much easier. · no date given · not yet resolved

“And I do think it's possible that in context learning actually runs a small gradient descent loop internally in the layers of the neural network.”

Expects: In-context learning may run a small gradient-descent loop internally within neural-network layers. · no date given · not yet resolved

“maybe it's a Lora, it's not a full weight neural network that's... So it's just small, some of the small sparse subset of the weights are changed.”

Expects: Person-specific model adaptation could modify only a small, sparse subset of weights. · no date given · not yet resolved

“Like maybe we have some very elaborate sparse attention over it.”

Expects: Elaborate sparse attention could support very long context windows. · no date given · not yet resolved

“And the model can also discover solutions that the human might never come up with.”

Expects: Models may discover solutions that humans would not think of. · no date given · not yet resolved

“And if you reinforce my learning with respect to them, you will find adversarial examples for your LM judges, almost guaranteed.”

Expects: Optimizing with reinforcement learning against an LLM judge will almost certainly produce adversarial examples that exploit the judge. · no date given · not yet resolved

“but I do think that you could probably regularize the entropy to be higher.”

Expects: It may be possible to encourage higher entropy in models through regularization. · no date given · not yet resolved

“But some of the jobs maybe that I would be looking for have some features that I think make it very amenable to automation earlier than later.”

Expects: The speaker expects that some jobs have characteristics that make them suitable for automation earlier than other jobs. · no date given · not yet resolved

“and humans are supervising teams of five AIs doing the call center work that's more rote.”

Expects: Human workers will supervise teams of five AI systems performing rote call-center tasks. · no date given · not yet resolved

“So I would be looking for new interfaces or new companies that provide some kind of a layer that allows you to manage some of these AIs that are not yet perfect.”

Expects: The speaker expects that there will be a need for interfaces or companies that help people manage imperfect AI systems. · no date given · not yet resolved

“And then I would expect that across the economy, and a lot of jobs are a lot harder. harder than call center employee.”

Expects: Many jobs across the economy will be more difficult to automate than call-center jobs. · no date given · not yet resolved

“for example, because I would expect a lot of the road stuff to be automatable today.”

Expects: Much of the routine work in call centers may be automatable today. · no date given · not yet resolved

“for example, because I would expect a lot of the road stuff to be automatable today.”

Expects: Much of the rote work in call centers is automatable with current technology. · no date given · not yet resolved

“I just feel like there will be a gradual automation of a lot of things and superintelligence will be sort of like the extrapolation of that.”

Expects: Many activities will probably be gradually automated, with superintelligence representing an extrapolation of that automation trend. · no date given · not yet resolved · In a shared prediction of 16 →

“So I do think we expect more and more autonomous entities over time that are doing a lot of the digital work and then eventually even the physical work, probably some amount of time later.”

Expects: Autonomous entities will perform an increasing amount of digital work over time and probably some physical work at a later point. · no date given · not yet resolved · In a shared prediction of 16 →

“going to be able to do some of the things. It's going to fail at some other things. It's going to be gradually put into society and basically we'll end up with the same pattern is my prediction.”

Expects: AI will have uneven capabilities, fail at some tasks, and be gradually integrated into society, resulting in the same broad economic growth pattern as before. · no date given · not yet resolved

“Because this assumption of suddenly having a completely intelligent, fully flexible, fully general human in a box and we can dispense it at arbitrary problems in society. I don't think that we will have this like discrete change.”

Expects: The speaker does not expect a sudden, discrete transition to fully general, human-like AI that can be deployed on arbitrary societal problems. · no date given · not yet resolved

“Because this assumption of suddenly having a completely intelligent, fully flexible, fully general human in a box and we can dispense it at arbitrary problems in society. I don't think that we will have this like discrete change.”

Expects: Karpathy does not expect a discrete economic or societal shift caused by a fully general, flexible, human-like AI that can be deployed on arbitrary problems. · no date given · not yet resolved

“So in the simplest case, it would be a giant scratchpad that the LLM can edit, and as it's reading stuff, or as it's helping out with work, it's editing the scratchpad for itself.”

Expects: A basic form of LLM culture could be a shared or persistent scratchpad that an LLM edits while reading or doing work. · no date given · not yet resolved

“But I do think Tesla is taking the more scalable strategy and is going to look a lot more like that.”

Expects: Tesla’s self-driving strategy will prove more scalable and become the more prevalent approach. · no date given · not yet resolved

“So you would expect a lot more faster adaptation also in the industry and so on.”

Expects: The speaker expects the changeability of digital bits to enable faster adaptation in industry. · no date given · not yet resolved

“But I'm still like overall very bullish on technology. I think we're going to work through all this stuff.”

Expects: The speaker expects people to work through the issues associated with technology. · no date given · not yet resolved

“there's going to be a huge amount of demand as we see the demand in ChatGPT already and so on.”

Expects: The speaker expects substantial demand for AI, citing existing demand for ChatGPT as evidence. · no date given · not yet resolved

“But I think like my personal big fear is that a lot of this stuff happens on the side of humanity and that humanity gets disempowered by it.”

Expects: AI developments may proceed independently of humanity and leave humans disempowered. · no date given · not yet resolved

“And so I guess I'm most afraid of something maybe like depicted in movies like WALL-E or Idiocracy or something like that where humanity is sort of on the side of this stuff.”

Expects: The speaker fears that the future may resemble WALL-E or Idiocracy, with humanity sidelined by technological developments. · no date given · not yet resolved

“And I think a lot of people are going to pursue like, oh, just ask chat GPT, etc.”

Expects: Many people will try using ChatGPT by simply asking it for help, as Karpathy expects. · no date given · not yet resolved

“So I think it would change over time. So I think right now it would be hiring faculty to help work hand in hand with AI and a team of people probably to build a state of the art courses.”

Expects: Karpathy thinks that, at present, creating state-of-the-art courses would require faculty working alongside AI and probably a team of other people. · no date given · not yet resolved

“But I think you'll need faculty for the overall architecture of a course and making sure that it fits.”

Expects: Karpathy believes faculty will remain necessary to design a course’s overall structure and ensure its coherence. · no date given · not yet resolved

“And maybe at some future point, you know, I'm not even that useful and AI is doing most of the design much better than I could. But I still think that that's going to take some time to play out.”

Expects: AI may eventually design most courses better than Karpathy can, though he expects this transition to take time. · no date given · not yet resolved

“Yeah, I do expect that I would hire faculty, but I will probably stick around in AI for some time.”

Expects: Karpathy expects to hire faculty while probably continuing to work in AI for some time. · no date given · not yet resolved

“And when I'm building Starfleet Academy, I do probably imagine a physical institution and maybe a tier below that a digital offering that is not the state of the art experience you would get when someone comes in physically full time.”

Expects: Karpathy probably envisions Starfleet Academy as a physical institution offering a higher-quality experience than its lower-tier digital option. · no date given · not yet resolved

“Yeah, and I think there's going to have to be a lot of not just education, but also re-education, and I would love to help out there because I think the jobs will probably change quite a bit.”

Expects: Jobs will probably change substantially, creating a need for both education and re-education. · no date given · not yet resolved

“And so I kind of think that education will kind of play out in the same way. Like you'll go to school, like you go to gym and you'll and I think that right now, I think not that many people learn because learning is hard.”

Expects: Education will become more like gym-going, with people attending school for reasons beyond practical necessity. · no date given · not yet resolved

“But maybe it's going to even become a sport. But right now you have powerlifters who go extreme on this direction. So what is powerlifting in a cognitive era? Maybe it's people who are really trying to make Olympics out of knowing stuff.”

Expects: Cognitive achievement could become a sport, potentially involving competitions that treat knowledge like an Olympic discipline. · no date given · not yet resolved

“And if you have a perfect AI tutor, maybe you can get extremely far.”

Expects: People might achieve very high levels of learning with the help of a perfect AI tutor. · no date given · not yet resolved

“And I think for a while it's going to be AI plus human collab and at some point maybe it's just AI, I don't know.”

Expects: Learning will involve AI-human collaboration for a while and may eventually be handled by AI alone; the speaker is uncertain about whether this will happen. · no date given · not yet resolved

“Like if they can see the dumb questions I had, it might help them explain better in the future or something like that.”

Expects: Authors may explain their work better in the future if they see the basic questions learners ask about it. · no date given · not yet resolved

“evolve and i think um i was triggered by that because i feel like there's some over predictions going on in the industry and uh in my mind this is really a lot more accurately described as the decade of agents and we have some very early agents that are actually like extremely impressive and that i use daily uh you know cloud and codecs and so on but i still feel like there's uh so much work to be done and so i think my like my reaction is like we'll be working with these things for decades they're gonna get better”

Expects: AI agents will continue to improve over the coming decades, though they still require substantial work. · no date given · not yet resolved

“like they don't have enough intelligence they're not multimodal enough they can't do computer use and all this kind of stuff and they don't do a lot of the things that you've alluded to earlier you know they don't have continual learning you can't just tell them something and they'll remember Yeah, it and they're just cognitively lacking and it's just not working and i just think that it will take about a decade to work through all those issues”

Expects: Resolving the problems that keep AI agents from working well will take about a decade, according to Andrej Karpathy. · no date given · not yet resolved

“stuff that happened I mean AI is actually like so wonderful because there have been a number of I would say seismic shifts That were like the entire field has sort of like suddenly looks a different way Right and I guess I've maybe lived through two or three of those and I still think there will continue to be some because they come with some kind of like almost surprising regularity Well my when my career began of course like when I started to work on deep learning when I became interested in deep learning This was just kind of like by chance of being right next to Jeff Hinton at University of Toronto”

Expects: Andrej Karpathy expects further major shifts in AI that rapidly change the field, given how surprisingly regularly such shifts have occurred. · no date given · not yet resolved

“basically doing some kind of a synthetic data generation process and distilling it back into the weights and maybe having a specific neural net per person, maybe it's a Lora, it's not a full weight neural network that's... So it's just small, some of the small sparse subset of the weights are changed.”

Expects: A model's experience could be processed through synthetic-data generation and distilled into its weights, potentially using a person-specific neural network. · no date given · not yet resolved

“So I almost feel like we are redoing a lot of the cognitive tricks that evolution came up with through a very different process but where i think can converge on a similar architecture cognitively well”

Expects: Andrej Karpathy believes AI development is recreating many cognitive strategies evolved by humans through a different process and may converge on a similar cognitive architecture. · no date given · not yet resolved

“So maybe some of the things that we can bet on, I think, in 10 years by translational sort of covariance is we're still training giant neural networks with forward backward pass and update through gradient descent. but maybe it looks a little bit different and”

Expects: Andrej Karpathy predicts that in ten years, giant neural networks will likely still be trained using forward and backward passes and gradient-descent updates, although the approach may look somewhat different. · 17 Oct 2035 – 17 Oct 2035 · not yet resolved

“All these things have to improve simultaneously. So, you know, we're probably going to have a lot more data, we're probably going to have a lot better hardware, probably going to have a lot better kernels and software, we're probably going to have better algorithms. And all of those, it's almost like no one of them is winning too much. All of them are surprisingly equal.”

Expects: Andrej Karpathy expects AI progress to come from simultaneous improvements in data, hardware, kernels and software, and algorithms, with no single factor dominating and their contributions being surprisingly equal. · no date given · not yet resolved

“that part is not there yet i would love to actually like add that probably later this week or something in some way like either it's a it's probably a video or something like that but um but maybe roughly speaking that's what i would try to do is build the stuff yourself uh but don't allow yourself copy paste i do think that there's two types of knowledge almost like there's the high level surface knowledge but the thing is that when you actually build something from scratch you're forced to come to terms”

Expects: Andrej Karpathy would like to add an explanation of how the repository was built, probably later that week and possibly in video form. · 17 Oct 2025 – 24 Oct 2025 · not yet resolved

“And so I saw a paper from Google yesterday that tried to have this reflect and review page. idea in mind what was the memory bank paper or something i don't know i've actually seen a few papers along these lines so i expect there to be some kind of a major update to how we do algorithms for llms coming in that realm and then i think we need three or four or five more something like that”

Expects: The speaker expects a major update to LLM algorithms involving approaches such as reflection, review, or memory. · no date given · not yet resolved

“You can't do this for too long. You do maybe 10 steps or 20 steps, maybe it will work, but you can't do 100 or 1000 because it's not obvious because I know I understand it's not obvious, but basically the model will find. little cracks it will find all these like spurious things in the nooks and crannies of the giant model and find a way to cheat it so one example that's prominently in my mind is i think this i think this was probably public but basically if you're using an lm judge for a reward so you just give it a solution from a student and ask it if the student will or not we were training with reinforcement learning against that reward function”

Expects: The speaker thinks reinforcement learning against an LLM judge may work for around 10–20 steps, but not for 100–1,000 steps, because the optimized model will discover exploitable weaknesses in the judge. · no date given · not yet resolved

“can do this but every time you do this you get a new llm and it still has adversarial examples there's infinity adversarial examples and i think probably if you iterate this a few times it will probably be harder and harder to find adversarial examples but i'm not 100% sure because this thing has a trillion parameters or whatnot um”

Expects: The speaker thinks that iterating on adversarial examples may make them progressively harder to find, but is uncertain; the model has roughly a trillion parameters. · no date given · not yet resolved

“too much so you always have to like seek entropy in your life so talking to other people is a great source of entropy and things like that so maybe the brain has also built some internal mechanisms for increasing the amount of entropy in that process but yeah maybe that's an interesting idea”

Expects: The brain may have internal mechanisms that increase entropy during internal thought or learning. · no date given · not yet resolved

“say their morals are smaller and even then i actually think they memorized way too much um so i think i had a prediction a while back that i almost feel like we can get cognitive course that are very good at even like a billion”

Expects: A cognitive core of around one billion parameters could perform very well. · no date given · not yet resolved

“building parameters it should be already like like if you talk to a building parameter model i think in 20 years you can actually have a very productive conversation it thinks um and it's a lot more like a human but if you ask it some factual question might have to look it up but it knows that it doesn't know and it might have to look it up and it will just do all the reasonable things”

Expects: The speaker thinks that in 20 years, a billion-parameter model could converse productively, behave more like a human, and recognize when it should look up a factual answer it does not know. · 17 Oct 2045 – 17 Oct 2045 · not yet resolved

“memory and then so like what i'm saying is like we need intelligent models to help us refine even the pre-training set to just narrow it down to the cognitive components and then i think get away with a much smaller model because it's a much better data set and you could train it on it but probably it's not trained directly on it's probably distilled for a much better model still but i”

Expects: Intelligent models could filter pre-training data for cognitive content, enabling a much smaller model to be trained on better data, probably through distillation from a stronger model. · no date given · not yet resolved

“I expect the data sets to get much, much better because when you look at the average data sets, they're extremely terrible, like so bad that I don't even know how anything works, to be honest, like look at the average example in the training set. It like factual mistakes, errors, nonsensical things.”

Expects: Andrej Karpathy expects AI training datasets to improve substantially from their current state, which he considers extremely poor and full of factual mistakes, errors, and nonsensical examples. · no date given · not yet resolved

“our hardware um our old kernels um older kernels for running the hardware maximizing what you get with the hardware you know so nvidia slowly tuning the actual hardware itself tensor course and so on all that needs to happen and will continue to happen uh all the kernels will get better and utilize the chip to the max extent all the algorithms will probably improve over optimization architecture and um just all the modeling components of how everything is done and what the algorithms are that we're even training with so i do i do kind of expect like a”

Expects: AI hardware and its software kernels will keep improving, including through improvements that maximize hardware utilization. · no date given · not yet resolved

“our hardware um our old kernels um older kernels for running the hardware maximizing what you get with the hardware you know so nvidia slowly tuning the actual hardware itself tensor course and so on all that needs to happen and will continue to happen uh all the kernels will get better and utilize the chip to the max extent all the algorithms will probably improve over optimization architecture and um just all the modeling components of how everything is done and what the algorithms are that we're even training with so i do i do kind of expect like a”

Expects: Karpathy expects NVIDIA to continue gradually tuning its hardware, including Tensor Cores. · no date given · not yet resolved

“our hardware um our old kernels um older kernels for running the hardware maximizing what you get with the hardware you know so nvidia slowly tuning the actual hardware itself tensor course and so on all that needs to happen and will continue to happen uh all the kernels will get better and utilize the chip to the max extent all the algorithms will probably improve over optimization architecture and um just all the modeling components of how everything is done and what the algorithms are that we're even training with so i do i do kind of expect like a”

Expects: AI algorithms, model components, and training algorithms will probably improve through optimization and architectural changes. · no date given · not yet resolved

“instantly replace people. We're going to be swapping in AIs that do 80% of the volume. They delegate 20% of volume to humans,”

Expects: Call centers will gradually transition to a model in which AI handles about 80% of the work volume and humans handle the remaining 20%, rather than people being replaced instantly. · no date given · not yet resolved

“with respect with respect to when the world looks like that is this kind of like gradual loss of control and understanding of what's happening and i think that's actually the most likely outcome probably is that there will be a gradual loss of understanding of and we'll gradually layer all this stuff everywhere and there'll be fewer and fewer people who understand it and then there will be a sort of this like scenario of gradual loss of control and understanding of what's happening That to me seems most likely outcome of how all the stuff will go down.”

Expects: Gradual societal loss of understanding of what is happening, amid widespread deployment of technology and fewer people who understand it, is the most likely outcome. · no date given · not yet resolved

“I think like, I guess I expect the loss of both.”

Expects: Society will lose both understanding of and control over increasingly autonomous systems. · no date given · not yet resolved

“so we're really far into a territory of i don't know what this looks like but if i was to write sci-fi novels they would look along the lines of not even a single like entity or something like that so that just sort of like takes over everything uh but actually like multiple competing entities that gradually become more and more autonomous and uh some of them go rogue and the others like fight them off and all this kind of stuff and it's like this this hot pot of completely autonomous activity that we've delegated to i”

Expects: A future scenario could involve multiple increasingly autonomous entities competing within a large body of autonomous activity delegated by people, with some entities going rogue and others opposing them. · no date given · not yet resolved

“I mean, there will be tools to people and the people could some of the population is like. they're acting on behalf of people or something like that. So maybe those people are in control, but maybe it's a loss of control overall for society in the sense of like outcomes we want or something like that, where you have entities acting on behalf of individuals that are still kind of roughly seen as out of control.”

Expects: Some entities will act on behalf of individuals, while society may still lose control over whether outcomes align with what people want. · no date given · not yet resolved

“Yeah, my expectation is that it stays the same pattern.”

Expects: The existing pattern of economic growth will probably continue rather than change because of AI. · no date given · not yet resolved

“going to be able to do some of the things. It's going to fail at some other things. It's going to be gradually put into society and basically we'll end up with the same pattern is my prediction. I don't think that we will have this like discrete change. At the same kind of gradual diffusion of this across the industry.”

Expects: AI will perform some tasks but fail at others, and will be gradually adopted across society and industry rather than arriving as a sudden, complete transformation. · no date given · not yet resolved · In a shared prediction of 16 →

“but I still think that you're presupposing some discrete jump, some unlock that we're waiting to claim. And I still think you're presupposing some discrete jump that I think has basically no historical precedent that I can't find in any of the statistics and that I think probably won't happen.”

Expects: A discrete jump of the kind being proposed probably will not occur, according to the speaker. · no date given · not yet resolved

“existence so maybe that's a slight event of there's a slight indication of maybe intelligence springing up a few times and so in that case you'd maybe expect it more frequently or something”

Expects: Distinct forms of intelligence may indicate that intelligence evolved independently several times, which could mean intelligence is more frequent than expected. · no date given · not yet resolved

“and evolution um and for in alpha go more algorithmically like alpha go is playing against itself and that's how it learns to get really good at go and there's no equivalent of self-playing llms but i would expect that to also exist but no one has done it yet like why can't an llm for example create a bunch of problems that another llm is learning to solve and then the the llm is always trying to like serve more and more difficult problems stuff like that you know so like”

Expects: Systems equivalent to AlphaGo’s self-play approach will emerge for LLMs, which the speaker says do not yet have such a system. · no date given · not yet resolved

“and evolution um and for in alpha go more algorithmically like alpha go is playing against itself and that's how it learns to get really good at go and there's no equivalent of self-playing llms but i would expect that to also exist but no one has done it yet like why can't an llm for example create a bunch of problems that another llm is learning to solve and then the the llm is always trying to like serve more and more difficult problems stuff like that you know so like”

Expects: A possible LLM self-play method would involve one LLM generating progressively harder problems for another LLM to solve. · no date given · not yet resolved

“right so even Waymo and so on has very few cars and they're doing that roughly speaking because they're not economical right because they've built something that that lives in the future and so they had to like pull back future but they had to make it uneconomical so they have all these like you know there's all these costs not just marginal costs for those cars and their operation maintenance but also the capex of the entire thing so making economical is still going to be a slog I think”

Expects: Making Waymo’s service economical will remain a difficult, prolonged process, according to the speaker. · no date given · not yet resolved

“the times they are but they're certainly involved and there are people and in some sense we haven't actually removed the person we've like moved them to somewhere we can't see them i still think there will be some work as you mentioned going from environment to environment and so i think like there's still challenges to to make self-driving real but i i do agree that it's definitely across a threshold where it kind of feels real unless it's like really teleoperated for example waymo can't go to all the different parts of the city my suspicion is it's like parts of city where we don't get good signal”

Expects: The speaker expects further work to be done to adapt self-driving systems across environments, with significant challenges remaining before self-driving is fully realized at scale. · no date given · not yet resolved

“I mean, I also think that if we are talking about knowledge work at scale, there will be some latency requirements practically speaking because we,”

Expects: The speaker expects large-scale knowledge work to impose practical latency requirements. · no date given · not yet resolved

“You know, there's going to be equivalents of all that.”

Expects: The speaker expects AI deployment to have counterparts to people obstructing a Waymo vehicle with a cone. · no date given · not yet resolved

“a very good question about the current capability you don't but I do think that with as and that's why I think it's not actually the right right time to actually build this kind of an AI tutor I still think it's a useful product and lots of people will build it but I still feel like the bar is so high and the capability is not there”

Expects: Many people will build AI tutors, although current AI capabilities are insufficient for Andrej Karpathy’s desired version. · no date given · not yet resolved

“So I guess I'm waiting for that capability.”

Expects: AI capabilities will advance enough to support the tutor experience Andrej Karpathy wants to build. · no date given · not yet resolved

“And I feel like it's in the same in education right now where I kind of feel like for what I have in mind, it's not yet the time, but the time will come. But for now, I'm building something that looks maybe a bit more conventional, that has a physical and digital component and so on.”

Expects: Andrej Karpathy thinks his envisioned AI tutor will come, though the time is not yet right for it. · no date given · not yet resolved

“And then I think over time it can maybe some of the TAs can actually become AIs because some of the TAs like, okay, you just take all the course materials. And then I think you could serve a very good automated TA for the student when they have more basic questions or something like that, right?”

Expects: AI systems may eventually serve as automated teaching assistants that answer students’ basic questions using course materials. · no date given · not yet resolved

“really good course to teach in this in this respect um and yeah i think the motivation wise uh before agi uh motivation is very simple to solve because people want to make money and this is how you make money in the industry today i think post agi is a lot more interesting um possibly because yeah if everything is automated and there's nothing to do for anyone why would anyone go to a school etc um”

Expects: After AGI, if everything is automated and people have nothing to do, it may be unclear why people would attend school. · no date given · not yet resolved

“but I do think that we should it's a technical problem to solve it's a technical problem to do what my tutor did for me when I was learning Korean I think it's tractable and buildable and someone should build it and I think it's going to make learning anything like trivial and desirable and people will do it for fun because it's trivial”

Expects: The speaker believes it is technically feasible to build a tutor that makes learning any subject easy and appealing, and says someone should build it. · no date given · not yet resolved

“that I think this, so I do definitely feel like people will be, I do think like eventually it's a bit of a losing game. if that makes sense i do think that it is in long term long term which i think is longer than i think maybe most people in the industry it's a losing game i i do think that people can go so far and that we barely scratch the surface of much person can can go and that's just because people are bouncing off of material that's too easy or too hard and they and and i i actually kind of feel that people will be able to go much further like anyone speaks five languages because why not because it's so trivial”

Expects: In the long term, human efforts to influence technological progress through individual labor or cognition will probably become a losing game. · no date given · not yet resolved

“long term which i think is longer than i think maybe most people in the industry it's a losing game i i do think that people can go so far and that we barely scratch the surface of much person can can go and that's just because people are bouncing off of material that's too easy or too hard and they and and i i actually kind of feel that people will be able to go much further like anyone speaks five languages because why not because it's so trivial anyone knows, you know, all the basic curriculum of undergrad, etc.”

Expects: The speaker imagines that if learning became trivial, people could learn five languages and the basic undergraduate curriculum. · no date given · not yet resolved

“And I kind of feel like I am betting a little bit implicitly on some of the timelessness of human nature. And I think it will be desirable to be. to do all these things. And I think people will look up to it as they have for millennia because and I think this will continue to be true.”

Expects: People will continue to value physical and cognitive pursuits, reflecting aspects of human nature that are timeless. · no date given · not yet resolved

“I do think that long term. That probably goes away, right?”

Expects: Human involvement in advancing technology will probably disappear in the long term. · no date given · not yet resolved