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In a bid to enhance the reasoning capabilities of large language models (LLMs), researchers from Google Deepmind and University of Southern California have proposed a new ‘self-discover’ prompting framework. Published on arXiV and Hugging Face this morning, the approach goes beyond existing prompting techniques used by LLMs and has been found capable of improving the performance of known models out there, including OpenAI’s GPT-4 and Google’s PaLM.

Fans of virtual currencies congregate in some places and not in others. There’s now a way to pinpoint crypto intensity in the U.S. From circumstantial evidence, you can conclude that if you’re in an area that shows up on a crypto heat map, you’re probably surrounded by taxpayers who are young, rich or employed as coders. Not surprisingly, California leads in the number of locales where a high percentage of the population owns bitcoin or one of its competitors. But in a state-by-state ranking, Washington beats California.