LLM Discussion

[Niya]

Thinking we're close to a radical shift in AI is like thinking routine space travel to other star systems was on the horizon after we landed on the moon. There's a ceiling for the current underlying technology... it will advance, but not to the point of revolution.

I see what you're trying to say but there is something you didn't consider: we have no non-theoretical models for advanced space travel. We don't know of anything that could surpass the cosmic speed limit. All we have are theories, most of which tell us that there is a ceiling. However, we do have numerous examples of what neural networks are capable of all around us. The ants in your backyard are constantly solving problems of ventilation, defense, construction, acquiring energy, and reproduction, all of which are powered by neural networks that could fit in the palm of your hand. The neural network in a dragonfly’s head controls an exceptionally advanced flight system, coordinating four independently moving wings while simultaneously processing complex data on air pressure, currents, angles of attack, speed, distance, and timing. The end result is a hunting success rate of 90%, the highest in the animal kingdom. We haven't even mentioned humans yet.

My point is, nature has already given us countless examples, not even counting humans, of what neural nets are capable of. We haven't tapped into that yet, but we know it is possible. We also have 2 major advantages over nature: energy and storage capacity. The human brain can only hold so many neurons, and the body can only provide so much energy. Our artificial neural nets have no such constraints. Imagine how potent AI will become when we do unlock the remaining secrets of neural networks.

Another example with just the last thing I did:

> I need to get the total amount of video RAM for each adapter, from a 32bit application, where the total can exceed 4GB. On Windows, with C++. How can I do that?

Since it has no actual reasoning ability, even an amateur human would catch the issue here... a SIZE_T or UINT32 can't store numbers above 4GB. But since a language model is a technology without any actual understanding, it gives me the standard methods: DXGI_ADAPTER_DESC (SIZE_T, wrong), and WMI (uint_32, wrong).

Asking for corrections only gets the same or worse results; it changed to using DXGI_ADAPTER_DESC1, falsely claiming that worked when it's the same size_t. It doesn't even understand the same problem exists. Another solution actually does support the proper 8-byte types, but only provides information about available to the current app/allocated to the current app memory (which is more useful, but not the right answer).

Well, like I said, our current models aren't ready for this level of cognition, but I wouldn't bet on this being the case indefinitely, after all, the neural net in your head can do it. I see no reason why we can't build an artificial one to do the same. The only valid point of contention I can see in all this is time. When will it happen? Two years from now or thirty? But I am sure it will happen.