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128 points ArmageddonIt | 2 comments | | HN request time: 0.721s | source
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danbruc ◴[] No.44500955[source]
Let us see how this will age. The current generation of AI models will turn out to be essentially a dead end. I have no doubt that AI will eventually fundamentally change a lot of things, but it will not be large language models [1]. And I think there is no path of gradual improvement, we still need some fundamental new ideas. Integration with external tools will help but not overcome fundamental limitations. Once the hype is over, I think large language models will have a place as simpler and more accessible user interface just like graphical user interfaces displaced a lot of text based interfaces and they will be a powerful tool for language processing that is hard or impossible to do with more traditional tools like statistical analysis and so on.

[1] Large language models may become an important component in whatever comes next, but I think we still need a component that can do proper reasoning and has proper memory not susceptible to hallucinating facts.

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Davidzheng ◴[] No.44501079[source]
Sorry but to say current LLMs are a "dead end" is kind of insane if you compare with the previous records at general AI before LLMs. The earlier language models would be happy to be SOTA in 5 random benchmarks (like sentiment or some types of multiple choice questions) and SOTA otherwise consisted of some AIs that could play like 50 Atari games. And out of nowhere we have AI models that can do tasks which are not in training set, pass turing tests, tell jokes, and work out of box on robots. It's literally insane level of progress and even if current techniques don't get to full human-level, it will not have been a dead end in any sense.
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jayd16 ◴[] No.44501260[source]
Something can be much better than before but still be a dead end. Literally a dead end road can take you closer but never get you there.
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Davidzheng ◴[] No.44502034[source]
But dead end to what? All progress eventually plateaus somewhere? It's clearly insanely useful in practice. And do you think there will be any future AGI whose development is not helped by current LLM technology? Even if the architecture is completely different the ability of LLMs to understand humans data automatically is unparalleled.
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1. danbruc ◴[] No.44502497[source]
To reaching AI that can reason. And sure, as I wrote, large language models might become a relevant component for processing natural language inputs and outputs, but I do not see a path towards large language models becoming able to reason without some fundamentally new ideas. At the moment we try to paper over this deficit by giving large language model access to all kind of external tools like search engines, compilers, theorem provers, and so on.
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2. Davidzheng ◴[] No.44506019[source]
When LLMs attempt to some novel problems (I'm thinking of pure mathematics here) they can try possible approaches and examine by themselves which approaches are working and not and then come to conclusions. That is enough for me to conclude they are reasoning.