The recent deep learning AI efforts only started around 2012 with AlexNet. They were based on ideas that were around since the 1980s, but they had been previously abandoned as they just didn’t produce any usable results with the hardware available at the time. Once programmable consumer GPUs came around that changed.

Most of the other AI research that has been happening since the 1950s was a dead end, as it relied on hand crafted feature detection, symbol logic and the like written by humans, which as the last 10 years have shown performs substantially worse than techniques that learn from the data directly without a human in the loop.

That’s the beauty of it. Most of this AI stuff is quite simple on the software side of things, all the magic happens in the data, which also means that it can rapidly expand into all areas were you have data available for training.

You smug idiots are proud of yourself that you can find a hand with an additional finger in an AI image, completely overlooking that three years of AI image generation just made 50 years of computer graphics research obsolete. And even ChatGPT is already capable of holding more insightful conversations than you AI haters are capable of.

(it’s not, il the underlying tech is much older than that).

ChatGPT was released Nov 2022. Plain GPT1/2/3 neither had the chat interface nor the level of training data and fine tuning that ChatGPT/GPT-3.5 had and in turn were much less capable. They literally couldn’t function in the way ChatGPT does. Even the original Google paper this is all based on only goes back to 2017.

LLMs are physically incapable

Yeah, LLM won’t ever improve, because technology improving has never happened before in history… The stupid in your argument hurts.

Beside GPT-4 can already handle 32768 tokens, that’s enough for your average movie, even without any special tricks (of which there are plenty).