Opinion | Apple’s Cheap AI Bet Could Pay Off Big - WSJ
Opinion | Apple’s Cheap AI Bet Could Pay Off Big WSJ
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Contra Nina Panickssery on advice for children
I recently read this post by Nina Panickssery on advice for children. I felt that several of the recommendations are actively harmful the children they are aimed at. I am going to assume that this advice is targeted at children who are significantly more intelligent than average and maybe 7-12 years of age? It may be worth reading the original post beforehand, or maybe having it open in another tab while you read through this one. We'll go through the points one by one: "Don't be a sheep" . There's a difference between noticing when other people are wrong and actively assuming everyone else is dumb. This leans towards the second. There is a huge amount of evolutionary pressure that has gone into designing kids' behaviour; survival past childhood is pretty important if you want to have kids
Qwen 4B/9B and Gemma E4B/26B A4B for multilingual entity extraction, summarisation and classification?
Hi, LLM newbie here. Has anyone benchmarked these smaller models on multilingual entity extraction, summarisation and classification? I'm particularly interested in your opinion when it comes to finetuning them to reach higher success rates and reliability. What is your general feeling of the performance and capabilities? I saw plenty posts here but rarely the ones that mention multilingual entity extraction, summarisation or classification submitted by /u/Creative-Fuel-2222 [link] [comments]
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