How did new large language models come out so quickly after chatgpt was unveiled?

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How does ‘cutting edge’ technology suddenly get implemented by other parties soon after new technology is unveiled…for example. chatgpt came out as an amazing new technology that was like nothing we ever saw, and then right after, we hear that other parties are coming up with their own version of chatgpt…If the technology was so secret, then how come everyone else just started coming up with their own version so soon?

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Anonymous 0 Comments

This is a really common phenomenon.

Someone invented a telephone? Great! Turns out a dozen people were all inventing the telephone at the same time. Same as most other breakthroughs, they are just the *final* piece of the puzzle. The inventor gets the credit, but they are standing on the shoulders of ever growing giants. That giant grows & suddenly anyone looking can see something new on the horizon.

It’s truly rare for anything revolutionary to come out of left field, what generally happens is lots pieces fall into place & something that was impossible (or impossibly expensive) suddenly becomes viable.

For LLM it was a lot of factors, of which an important one was GPUs. They were designed for games & that industry funded them for 30 years. They do lots of small operations in parallel with insane throughput & eventually it reached critical mass which enabled lots of new technology.

Once we had this cheap, fast & specialized compute we found lots of cool things to do with it.

… The thing that bums me out is that the math used for raytracing doesn’t seem to have any useful applications outside of ray & wavetracing. There is a rumor AMD has an algorithm that uses massive multiplication matrixes which *is* useful math & *may* build out silicon to perform them.

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