#Llms

The other day, I saw a viral tweet saying that people talking about how LLMs are causing slow, bloated, code are going to eat crow once they re-write everything in super-optimized assembly.…

I came across a GH thread related to chess engine development that made me think of why hobby programming communities are increasingly hostile toward LLM development.…

Large language models (LLMs) have become the default tool for a remarkable range of tasks, yet they have had conspicuously little success at one of the most common machine learning workloads: predictive analytics over tabular data.…

In the 2010s, if you had technical gaps (say, you couldn’t write CSS), you had to either rely on a skilled colleague or just hope that the answer to your exact problem was out there on the internet.…

I almost agree with all of the LLM critics, yet I still use LLMs a lot. I know this sounds like I am delusional, but I don't think I am alone with it.

Google answered a question about LLMs-Author.txt and whether it helps people become easier to identify online.

Given the exceptional performance of proprietary large language models (LLMs) like GPT-4, recent research has increasingly focused on boosting the capabilities of smaller models through knowledge distillation (KD) from these powerful yet black-box…

Implying chatbots have some kind of consciousness may just be a good marketing ploy by the companies involved.

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Google's John Mueller dismisses LLMs.txt as speculative for now and says he likes WebMCP, a Google-backed alternative.

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