zlacker

>>Jimmc4+(OP)
It is easy to point to loopy theories around superalignment, p(doom), etc. But you don't have to be hopped up on sci-fi to oppose something like GPT-4o. Low-latency response time is fine. The faking of emotions and overt references to Her (along with the suspiciously-timed relaxation of pornographic generations) are not fine. I suspect Altman/Brockman/Murati intended for this thing to be dangerous for mentally unwell users, using the exact same logic as tobacco companies.

>>nickle+491
Realistically its all just probabilistic word generation. People "feel" like an LLM understands them but it doesn't, its just guessing the next token. You could say all our brains are doing are just guessing the next token but thats a little too deep for this morning

All these companies are doing now is taking an existing inferencing engine, making it 3% faster, 3% more accurate, etc. per quarter, fighting over the $20/month users

One can imagine product is now taking the wheel from engineering and are building ideas on how to monetize the existing engine. Thats essentially what GPT-4o is, and who knows what else is in the 1,2,3 year roadmaps for any of these $20 companies

To reach true AGI we need to get past guessing, and that doesn't seem close at all. Even if one of these companies gets better at making you "feel" like its understanding and not guessing, if it isnt actually happening, its not a breakthrough

Now with product leading the way, its really interesting to see where these engineers head

>>shmatt+1o1
> People "feel" like an LLM understands them but it doesn't, its just guessing the next token. You could say all our brains are doing are just guessing the next token but thats a little too deep for this morning

"Just" guessing the next token requires understanding. The fact that LLMs are able to respond so intelligently to such a wide range of novel prompts means that they have a very effective internal representation of the outside world. That's what we colloquially call "understanding."

>>Diogen+Gq1
I've seen this idea that "LLMs are just guessing the next token" repeated everywhere. It is true that accuracy in that task is what the training algorithms aim at. That is not however, what the output of the model represents in use, in my opinion. I suspect the process is better understood as predicting the next concept, not the next token. As the procedure passes from one level to the next, this concept morphs from a simple token to an ever more abstract representation of an idea. That representation (and all the others being created elsewhere from the text) interact to form the next, even more abstract concept. In this way ideas "close" to each other become combined and can fuse into each other, until an "intelligent" final output is generated. It is true that the present configuration doesn't offer the LLM a very good way to look back to see what its output has been doing, and I suspect that kind of feedback will be necessary for big improvements in performance. Clearly, there is an integration of information occurring, and it is interesting to contemplate how that plays into G. Tononi's definition of consciousness in his "information integration theory".

>>8crazy+so2
Also, as far as hallucinations go, no symbolic representation of a set of concepts can distinguish reality from fantasy. Disconnect a human from their senses and they will hallucinate too. For progress in this, the LLM will have to be connected in some way to the reality of the world, like our senses and physical body connect us. Only then they can compare their "thoughts" and "beliefs" to reality. Insisting they at least check their output against facts as recorded by what we already consider reliable sources is the obvious first step. For example, I made a GPT called "Medicine in Context" to educate users; I wanted to call it "Reliable Knowledge: Medicine" because of the desperate need for ordinary people to get reliable medical information, but of course I wouldn't dare. It would be very irresponsible. It is clear that the GPT would have to be built to check every substantive fact against reality, and ideally to remember such established facts going into the future. Over time, it would accumulate true expertise.