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1. nickle+491[view] [source] 2024-05-15 14:48:28
>>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.
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2. shmatt+1o1[view] [source] 2024-05-15 15:55:31
>>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

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3. Diogen+Gq1[view] [source] 2024-05-15 16:05:41
>>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."

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4. carom+os1[view] [source] 2024-05-15 16:12:35
>>Diogen+Gq1
I disagree. I use ChatGPT daily as a replacement for Google. It doesn't understand or have logic, it can spit out information very well though. It has a broad knowledge base. There is no entity there to have an understanding of the topic.

This becomes pretty clear when you get to more complex algorithms or low level details like drawing a stack frame. There is not logic there.

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5. root_a+lH1[view] [source] 2024-05-15 17:22:25
>>carom+os1
Indeed. It's also obvious when the "hallucinations" create contradictory responses that a conceptual understanding would always preclude. For example, "In a vacuum, 100g of feathers and 100g of iron would fall at the same rate due to the constant force of gravity, thus the iron would hit the ground first". Only a language model makes this type of mistake because its output is statistical, not conceptual.
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