Regardless of who is right here, I think the enormous egos at play make OpenAI the last company I’d want to develop AGI. First Sam vs. the board, now Elon vs. everyone … it’s pretty clear this company is not in any way being run for the greater good. It’s all ego and money with some good science trapped underneath.
Yes and no. Elon has ego, but I also take him at his word when he says he wants to open source AI. He did the same thing with Tesla's patents.
Did you read the article? According to it, Elon Musk agreed with AGI being closed source, but he wanted controlling interest.
Regardless of who is right here, I think the enormous egos at play make OpenAI the last company I’d want to develop AGI. First Sam vs. the board, now Elon vs. everyone … it’s pretty clear this company is not in any way being run for the greater good. It’s all ego and money with some good science trapped underneath.
Yes and no. Elon has ego, but I also take him at his word when he says he wants to open source AI. He did the same thing with Tesla's patents.
Did you also take him at his word when he said 5+ years ago that Teslas can drive themselves safer than a human "today"? Or that Cybertruck has nuclear explosion proof glass (which was immediately shattered by a metal ball thrown lightly at it)?
Musk has a long history of shamelessly lying when it suits his interest, so you should really really not take him at his word.
Regardless of who is right here, I think the enormous egos at play make OpenAI the last company I’d want to develop AGI. First Sam vs. the board, now Elon vs. everyone … it’s pretty clear this company is not in any way being run for the greater good. It’s all ego and money with some good science trapped underneath.
If AGI is as transformative as its proponents make it out to be, would it both attract and create those enormous egos though?
Which is why one might create a mechanism, say a non-profit, that has an established, codified mission to combat such obviously foreseeable efforts.
Regardless of who is right here, I think the enormous egos at play make OpenAI the last company I’d want to develop AGI. First Sam vs. the board, now Elon vs. everyone … it’s pretty clear this company is not in any way being run for the greater good. It’s all ego and money with some good science trapped underneath.
Yes and no. Elon has ego, but I also take him at his word when he says he wants to open source AI. He did the same thing with Tesla's patents.
I seem to remember that being only partially true? Or the license was weird and deceptive? Also as other replies have stated why isnt "Grok" open source? Musk loves to throw around terms like open source to generate good will but when it comes time to back those claims up it never happens. I wouldnt take Musk at his word for literally anything.
You are advocating here for an unresolvable set of ethics, which just happens to be one that conveniently leaves abuse of AI on the table. You take as an axiom of your ethical system the absolute right to create and propagate in public these AI technologies regardless of any externalities and social pressures created. It is of course an ethical system primarily and exclusively interested in advancing the individual a…
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Ok, but please don't post generic ideological battle comments to HN. They're repetitive and tedious, and usually turn nasty. We're trying to avoid that on this site.
I'm not defending the GP comment (I don't even know what it's saying) but at least it wasn't completely unmoored from the specific topic.
Edit: your account has been breaking the site guidelines in quite a few other places too—e.g.
Regardless of who is right here, I think the enormous egos at play make OpenAI the last company I’d want to develop AGI. First Sam vs. the board, now Elon vs. everyone … it’s pretty clear this company is not in any way being run for the greater good. It’s all ego and money with some good science trapped underneath.
I was with them, sort of, until they had this bit of Comms-major corporate BS:
> We’re making our technology broadly usable in ways that empower people and improve their daily lives, including via open-source contributions.
Their evidence does a nice job of making Musk seem duplicitous, but it doesn't really refute any of his core assertions: they still have the appearance of abandoning their core mission to focus more on profits, even if they've elaborated a decent justification of why that's necessary to do. Or to put it more simply: here they explain why they had to betray their core mission. But they don't refute that they did betra…
Elon is suing OpenAI for breach of contract but doesn't have a contract with OpenAI. Most legals experts are concluding that this is a commercial for Elon Musk, not much more. Missions change, yawn...
It's not just the volume of original data that matters here. From empirics we know performance scales roughly like (model parameters)*(training data)*(epochs). If you increase any one of those, you can be certain to improve your model. In the short term, training data volume and quality has given a lot of improvements (especially recently), but in the long run it was always model size and total time spent training th…
In smaller models, not having enough training data for the model size leads to overfitting. The model predicts the training data better than ever, but generalizes poorly and performs worse on new inputs. Is there any reason to think the same thing wouldn't happen in billion parameter LLMs?
This happens in smaller models because you reach parameter saturation very quickly. In modern LLMs and with current datasets, it is very hard to even reach this point, because the total compute time boils down to just a handful of epochs (sometimes even less than one). It would take tremendous resources and time to overtrain GPT4 in the same way you would overtrain convnets from the last decade.
Could you please stop posting unsubstantive comments and flamebait? You've unfortunately been doing it repeatedly. It's not what this site is for, and destroys what it is for.
There is very little in terms of rigorous mathematics on the theoretical side of this. All we have are empirics, but everything we have seen so far points to the fact that more compute equals more capabilities. That's what they are referring to in the blog post. This is particularly true for the current generation of models, but if you look at the whole history of modern computing, the law roughly holds up over the l…
True but also from general theory you should expect any function approximator to exhibit intelligence when exposed to enough data points from humans, the only question is the speed of convergence. In that sense we do have a guarantee that it will reach human ability
It's a bit more complicated than that. Your argument is essentially the universal approximation theorem applied to perceptrons with one hidden layer. Yes, such a model can approximate any algorithm to arbitrary precision (which by extension includes the human mind), but it is not computationally efficient. That's why people came up with things like convolution or the transformer. For these architectures it is much harder to say where the limits are, because the mathematical analysis of their basic properties is infinitely more complex.