A year or two ago, I wasted over a month on side projects that I thought were novel. Now, another LLM scrutinizes any idea in an area I don't know well ("I have just received this from a junior researcher on my team. Scrutinize it very critically. Don't hold back. This early stage is the best time for honest, harsh feedback. Don't forget to include the analysis of X, Y, Z in your report.").
replyI go through this process at the very start, after planning, and at least once a week afterward. With AI, the landscape can change dramatically during one week. I am not being hyperbolic.
Asking an LLM for criticism is like asking a yes-man to punch you in the face. he'll always swing, but hitting a straw man he built himself.
replyA fancy autocomplete still. Said with no intent to disparage. If the prior art hasn’t been pulled into the context window, it’s not surprising for the completion to not take it into consideration.
replySometimes I feel like a fancy autocomplete myself.
replyMost LLMs these days can use tools (such as web searching), so depending on how strictly you define "autocomplete" this alone could disqualify it from being an autocomplete, fancy or otherwise.
For sure yeah! What I’m pointing out is that I see people mistaking LLMs for “truth engines”, when they’re not. I find the “autocomplete” mental model really useful for when I work with LLMs myself. E.g., always keep in mind what’s in context, what’s not, where to get context.
replyGoes without saying - humans are no truth engines either lol.
Yes, "predictors" or "completers" are a far more accurate metal model for what they actually do and it pays to understand how they "use tools" and what RL, SFT, etc. is and how it makes LLMs seem like much more than what they still, ultimately, are.
replyPeople latched onto the bs marketing terms like "thinking" way too easily. I don't know where all the classic hacker skepticism and desire to know how things actually work went the past four years.
I enjoy the contrite rationalizations and turns of phrase LLMs use when encountering a discrepancy.
reply"Prior art has reduced the novelty of the discovery" is a great one
Maybe LLMs are getting a little too good at emulating humans.
replyIt’s like a shell game. It’s likely overfitting on its training data.
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