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Comment by MacsHeadroom | Hacker News Reader

It's not remotely intellectually challenging to replicate GPT-4. It just takes a lot of GPUs, something plenty of people all around the world have access to.

GPT-2 and GPT-3 are the same algorithm based on the same open source library. GPT-4 most likely is as well. You can literally fork the repo and if you have enough VRAM, cuda cores, and time, you will get GPT-4. High Schoolers could do it. Amateurs are already replicating LLaMA, which is more complex than GPT and not even a month old. (it's just smaller = fewer GPUs required)

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Engineering such a system is a harder challenge than many types of research. Even the mighty Google, the leader in AI research by many metrics, is catching up.

Another example is Meta only finishing OPT-175B, a near equivalent of GPT-3, two years after it.

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GPT-4 got much better results on many benchmarks than PaLM, Google's largest published model [1]. PaLM itself is probably quite a bit better than LamDa in several tasks, according to a chart and a couple of tables here: https://arxiv.org/abs/2204.02311

It's unclear that Google currently has an internal LLM as good as GPT-4. If they do, they are keeping quiet about it, which seems quite unlikely given the repercussions.

[1] GPT-4's benchmark results vs PaLM: https://openai.com/research/gpt-4

> Even the mighty Google

Since the release of the Attention paper, they havent come up with any groundbreaking idea, that was five years ago. Where is their research? All they seem to have are technical descriptions with scarce details, deceiving tactics, fiddling with parameters, and an abundance of pointless ethical debates. Can we even call this "research"?

Including DeepMind, they published Gato, Chinchilla, PaLM, Imagen, and PaLM-E, among others. They may not be as fundamental as transformers, but important nonetheless.

Can you list 1-2 research organizations, in any field, with more important output in 5 years? Bonus points if outside the US/UK/the west per context above.

You didn’t mention how to gather high quality data. OpenAI has never and will never release that.

You are way over simplifying.

It is not remotely intellectually challenging to go to the moon. It just takes rocket fuel. Newton solved motion hundreds of years ago, and now high schoolers compute it in physics class.

There is theory, and then there is practice. Followed by experience.

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