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The value is showing how confidently is presents incorrect results. Especially the lack of nuance or uncertainty in the language they use. They extremely conf
by xnorswap 3y ago
The value is showing how confidently is presents incorrect results.
Especially the lack of nuance or uncertainty in the language they use.
They extremely confidently present the incorrect information, and prime generation is interesting because it's information that isn't easy to spot as obviously incorrect to the user while being information that's possible to determine is wrong at small numbers and difficult to verify for large numbers.
It's my favourite test because it's a good demonstration of the lack of nuance or uncertainty in LLMs. They have no sense of how wrong the information they're giving out might be.
If they could give confidence intervals for any information then they could provide the context by how likely they think they might be correct, but they actually double-down on their incorrectness instead.
- tveita 3y agoMixtral is a pre-existing model that was released by Mistral AI in December: https://mistral.ai/news/mixtral-of-experts/ https://mistral.ai/news/mixtral-of-experts/ It was discussed on HN at the time: https://news.ycombinator.com/item?id=38598559 https://news.ycombinator.com/item?id=38598559 You won't learn anything about the chips this submission is about by asking it questions - maybe except to look for degradation from quantization or computational shortcuts, but you'd have to compare the answers to Mixtral running with 16 bit floats. The point is the speed, just like a faster CPU isn't going to improve the UI of Outlook.
- spacecadet 3y agoAsk a proper code gen llm, I bet you get a better response.