neonbjb

5 ms·

1.
by neonbjb 2mo ago
I actually think people who are great at understanding problems, coming up with requirements and designing solutions (all things I would expect someone who is good at churning out MVPs would be good at) are exactly the people most empowered
2.
by neonbjb 9mo ago
> So it made me wonder. Is Brainf*ck the ultimate test for AGI? Absolutely not. Id bet a lot of money this could be solved with a decent amount of RL compute. None of the stated problems are actually issues with LLMs after on policy trai
3.
by neonbjb 1y ago
Yes we do. If you worked at Google you know moma. Our moma is an internal version of chat. It is very good.
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by neonbjb 1y ago
Also work at OpenAI. Every tender offer has made full payouts to previous employees. Sorry to ruin your witch hunt..
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by neonbjb 1y ago
I work for openai. o4-mini gets much closer (but I'm pretty sure it fumbles at the last moment): https://chatgpt.com/share/680031fb-2bd0-8013-87ac-941fa91cea... We're pretty bad at model naming and communicat
6.
by neonbjb 2y ago
You're missing the fact that requests are batched. It's 70 tokens per second for you, but also for 10s-100s of other paying customers at the same time.
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by neonbjb 2y ago
You wouldn't do that to this model. It finds its own mistakes and corrects them as it is thinking through things.
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by neonbjb 2y ago
I'm James Betker. Of course architecture matters in this regard lol. Comparing a CNN to a transformer is like comparing two children brought up in the same household but one has a severe disability. What I meant in this blog post was t
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by neonbjb 3y ago
As an employee of OpenAI: fuck you and your condescending conclusions about my peers and my motivations.
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by neonbjb 3y ago
I don't think the plan is an occasionally rocket launch long term. I think the plan is to launch rockets as fast as humanly possible.
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by neonbjb 3y ago
Its cool that this is starting to approach real time video territory (30 images per second, this claims close to 1 image/sec).
12.
by neonbjb 3y ago
@dooraven - I also work in ML (including recently working at Google) and I agree with @whimsicalism. You seem to be under the mistaken belief that: 1. Google has competent high-level organization that effectively sets and pursues long term
13.
by neonbjb 3y ago
You can make almost anything work in DL if you try hard enough, that doesn't mean it is the correct thing to do. Convolutions have inductive biases which are the cause of many of the problems associated with deep learning over the last
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by neonbjb 4y ago
I theorize (but cannot prove) that the processes underpinning creativity in the human mind are exactly the same statistical processes that ML models use. Think about it: you live your life. You experience things. You experience art, and exp
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by neonbjb 5y ago
AGI consists of a set of problems: 1. Finding an algorithm which is capable of learning anything. 2. Building the computers that can run said algorithm. 3. Collecting, sorting and filtering the data that the algorithm learns from. DeepMind
16.
by neonbjb 5y ago
This is wrong IMO - the fed has NO tools in its hands. Its last tool was inflation rates, and it burned that during the great recession. It is now caught in a pickle: raise interest rates, causing a mass exodus of wealth from securities to
17.
by neonbjb 6y ago
There are other reasons to farm indoors (or in vertical farms) than electricity and water too. Pests are one such reason. They are extremely difficult to control outdoors, but far simpler to do so inside. Both fertilizer and pesticide treat