[karimf]

I've always thought about the best way to contribute to humanity: number of people you help x how much you help them. I think what Karpathy is doing is one of the highest leverage ways to achieve that.

Our current world is build on top of open source projects. This is possible because there are a lot of free resources to learn to code so anyone from anywhere in the world can learn and make a great piece of software.

I just hope the same will happen with the AI/LLM wave.

[bkettle]

This free tradition in software is I think one of the things that I love so much, but I don't see how it can continue with LLMs due to the extremely high training costs and the powerful hardware required for inference. It just seems like writing software will necessarily require paying rent to the LLM hosts to keep up. I guess it's possible that we'll figure out a way to do local inference in a way that is accessible to everyone in the way that most other modern software tools are, but the high training costs make that seem unlikely to me.

I also worry that as we rely on LLMs more and more, we will stop producing the kind of tutorials and other content aimed at beginners that makes it so easy to pick up programming the manual way.

[levocardia]

There's a Stephen Boyd quote that's something like "if your optimization problem is too computationally expensive, just go on vacation to Greece for a few weeks and by the time you get back, computers might be fast enough to solve it." With LLMs there's sort of an equivalent situation with cost: how mindblowing would it be able to train this kind of LLM at all even just 4 years ago? And today you can get a kindergartener level chat model for about $100. Not hard to imagine the same model costing $10 of compute in a few years.

There's also a reasonable way to "leapfrog" the training cost with a pre-trained model. So if you were doing nanochat as a learning exercise and had no money, the idea would be to code it up, run one or two very slow gradient descent iterations on your slow machine to make sure it is working, then download a pre-trained version from someone who could spare the compute.

[hodgesrm]

This. It looks like one of the keys to maintaining open source is to ensure OSS developers have access to capable models. In the best of worlds, LLM vendors would recognize that open source software is the commons that feeds their models and ensure it flourishes.

In the real world...

[DennisP]

Maybe this isn't possible for LLMs yet, but open source versions of AlphaZero have been trained on peer-to-peer networks.

https://zero.sjeng.org/

https://katagotraining.org/

[Lerc]

(This is a bit ranty, but due to a sincere desire for a better world, and being the recipient of personal attacks for believing a better world is achievable by a different path to others)

I feel like this point of view is an ideal not shared by one of the main branches of anti-AI sentiment.

The idea of intellectual property works against this. Rather than contributing to humanity directly, ownership of information is accumulated by individuals and then rented to humanity.

At the same time I agree that people should be able to have a livelihood that affords them the ability to create new intellectual contributions.

The service Karpathy is providing is also being provided by thousands of YouTube creators in a huge variety of topics. It's a little sad that so many must support their efforts with support their efforts with sponsorships from sources with varying degrees of ethical behaviour. Patreon is better but still not ideal. I sincerely believe this _is_ one of the best ways to contribute to society.

A recent Daily Show had Jon Stewart describe training AI as strip mining human knowledge. Training AI is regularly described as theft as if this position is a given without any counter argument possible. It is opinion masquerading as fact. This saddens me because it suggests to me that the war to control the narrative is being won by people who want to entrench a hypercapitalistic vision of ownership where not only is a particular expression of an idea ownable but also stakes a claim to own some of any ideas that come from viewing that expression.

I cannot see any way that this viewpoint would aid humanity as a whole, but instead assign benefits to a collection of individuals. The ability to trade intellectual property means that ownership inevitably gets passed to a smaller and smaller pool of individuals over time.

I think we really do need a new way to consider these issues in light of the modern world. When mentioning these thoughts to others a common refrain is that it doesn't matter because the powers that be (and their lobbyists) will prevent any fix from happening. I have never been fond of that particular fatalism, especially when it inhibits discussion of what would be better.

[oblio]

Awesome approach.

I'm all for abolishing IP if all AIs are owned communally. I.e. ideally they're utilities or flat out co-ops like some Spanish businesses.

https://en.wikipedia.org/wiki/Mondragon_Corporation

Consum (Spanish supermarket).

They don't get to use everything communally and then capitalism their way forward.

[viccis]

I recommend his ANN/LLM from scratch videos to people a lot because not only is he a clear instructor, but his code tends to be very Pythonic and just the right balance of terse but readable (not counting the Pytorch vectorization stuff, but that's not his fault, it's just complex). So I think people benefit just from watching and imitating his code style.

[epolanski]

Then a single person whose learned those skills decide to poison all of us thanks to the skills acquired.

[shafyy]

If it only were so easy

[carlcortright]

strong +1 - developers like him are heros

[martin-t]

As noble as the goal sounds, I think it's wrong.

Software is just a tool. Much like a hammer, a knife, or ammonium nitrate, it can be used for both good or bad.

I say this as someone who has spent almost 15 years writing software in my free time and publishing it as open source: building software and allowing anyone to use it does not automatically make other people's lives better.

A lot of my work has been used for bad purposes or what some people would consider bad purposes - cheating on tests, cheating in games, accessing personal information without permission, and in one case my work contributed to someone's doxxing. That's because as soon as you publish it, you lose control over it.

But at least with open source software, every person can use it to the same extent so if the majority of people are good, the result is likely to be more positive than negative.

With what is called AI today, only the largest corporations can afford to train the models which means they are controlled by people who have entirely different incentives from the general working population and many of whom have quite obvious antisocial personality traits.

At least 2 billion people live in dictatorships. AI has the potential to become a tool of mass surveillance and total oppression from which those countries will never recover because just like the models can detect a woman is pregnant before she knows it, it will detect a dissenter long before dissent turns into resistance.

I don't have high hopes for AI to be a force for good and teaching people how toy models work, as fun as it is, is not gonna change it.

[simonw]

"With what is called AI today, only the largest corporations can afford to train the models"

I take it you're very positive about Andrej's new project which allows anyone to train a model for a few hundred dollars which is comparable to the state-of-the-art from just 5 years ago then.

[oliveiracwb]

I would genuinely love to think otherwise. But I've seen and grown up seeing good things being used in stupid ways (not necessarily for malice)

[isaacremuant]

> At least 2 billion people live in dictatorships. AI has the potential to become a tool of mass surveillance and total oppression from which those countries will never recover because just like the models can detect a woman is pregnant before she knows it, it will detect a dissenter long before dissent turns into resistance.

It already works like this in your precious western democracies and they didn't need AI to be authoritarian total surveillance states in spirit, with quite a lot of support from a propagandized populace that begged for or pretended to agree with the infringement of their civil rights because of terrorism, drugs, covid or protecting the poor poor children.

You can combat tech with legislation and culture but the legislation and culture were way beyond the tech in being extremely authoritian in the first place.

[croes]

I‘m afraid the technology will do more damage because many people will abuse it for fake news and misinformation.

[IntrepidPig]

Yeah it feels similar to inventing the nuke. Or it’s even more insidious because the harmful effects of the tech are not nearly as obvious or immediate as the good effects, so less restraint is applied. But also, similar to the nuke, once the knowledge on how to do it is out there, someone’s going to use it, which obligates everyone else to use it to keep up.

[contingencies]

While documenting a build path is nice, IMHO renting hardware nobody can afford from VC-backed cloud providers using cold hard cash to produce clones of legacy tech using toy datasets under the guise of education is propping up the AI bubble and primarily helping institutional shareholders in those AI bubble companies, particularly their hardware supplier NVidia. Personally I do not see this as helping people or humanity.

This would sit better with me if the repo included a first tier use case for local execution, non-NVidia hardware reference, etc.

[simonw]

"This would sit better with me if the repo included a first tier use case for local execution, non-NVidia hardware reference, etc."

This is a pretty disheartening way to respond to something like this. Someone puts a great deal of effort into giving something interesting away for free, and is told "you should have also done THIS work for free as well in order for me to value your contribution".

[CamperBob2]

If you can't afford $100 or learn how to train it locally with more time and less money, then this isn't something you should be focusing on at all.

[wordpad]

Tinkering with something is what inspires next generation of innovators, in this space or another.

Think back to your first experience with tech, something you just erenstly thought was cool...

[jstummbillig]

I think you got your proportions slightly wrong there. This will be contributing as much to an AI bubble as a kid tinkering around with combustion is contribution to global warming.

[bgwalter]

He is the GOAT of LLM MVPs. That is educational and useful, especially because he uses a minimal and clean style, but I don't see how it even compares with kernels, operating systems etc.

So I appreciate his work in an academic and educational sense, but large scale applications with stolen training material are still theft.

[Yizahi]

I would adjust your formula to the:

number of people you help x how much you help them x number of people you harm x how much you harm them

For example - harming a little bit all content creators of the world, by stealing their work without compensation or permission. How much does that cost globally every year after year? How do we even quantify long term consequences of that? Stuff like that.

[wordpad]

If you consider the cost of hiring a human professional to over using multimodal AI for something, its very realize literally thousands of dollars of value per chat.

Multiply that by many billions of chats per day.

Lawyers and other professionals charge a lot. So do artists, especially when you want to do a million revisions. LLMs hand it out for free, making many knowledge and art professions affordable and accessible to the masses.

Stable owners were upset when cars replaced horses, but you can't stop progress, especially when value proposition is undenyable.