Posted by admin

The first model set to be opensourced that actually comes close to ChatGPT, and is just 13B (that's small enough for a laptop). The 51 page report from Microsoft was released just 48 hours ago but I have gone through it all, and bring relevant insights from 5 other papers. By imitating the logic and explanations of GPT 4 (and using GPT 3.5 as an assistant), as well as by training on diverse tasks and an order of magnitude more examples, we have Orca. I will showcase it on a dozen benchmarks and go through in detail how it works and why. I will also end on comments from Sam Altman and Ilya Sutskever on whether Opensource will catch-up... Orca Paper: https://arxiv.org/pdf/2306.02707.pdf False Promise Paper: https://arxiv.org/pdf/2305.15717.pdf https://sharegpt.com/ FLAN: https://arxiv.org/pdf/2301.13688.pdf Vicuna: https://lmsys.org/blog/2023-03-30-vicuna/ No Moat memo: https://www.semianalysis.com/p/google-we-have-no-moat-and-neither LLM Leaderboard: https://chat.lmsys.org/?leaderboard AGIEval: https://arxiv.org/pdf/2304.06364.pdf BIG-Bench Hard: https://arxiv.org/pdf/2210.09261.pdf Language Models as Tool Makers: https://arxiv.org/pdf/2305.17126.pdf Altman Interview: https://www.youtube.com/watch?v=VWUhASix9ws DERA Paper: https://arxiv.org/abs/2303.17071 Let's Verify Step by Step: https://arxiv.org/abs/2305.20050 https://www.patreon.com/AIExplained