There has been a lot of excitement recently about how using lower precision floats only slightly degrades LLM performance. I am wondering if Google took those results at face value to offer a low-cost mass-use transformer LLM, but didn’t test it since according to the benchmarks (lol) the lower precision shouldn’t matter very much.

But there is a more general problem: Big Tech is high on their own supply when it comes to LLMs, and AI generally. Microsoft and Google didn’t fact-check their AI even in high-profile public demos; that strongly suggests they sincerely believed it could answer “simple” factual questions with high reliability. Another example: I don’t think Sundar Pichai was lying when he said Gemini taught itself Sanskrit, I think he was given bad info and didn’t question it because motivated reasoning gives him no incentive to be skeptical.

The adversarial surface to the LLM remains enormous, manual cannot handle it.