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โ† thesingularity ๊ฒŒ์‹œํŒ

[๐Ÿ“ช์ •๋ณด] ai ์ „์œ ๋ฌผ ๋ถˆ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋งŒ๋“œ๋Š” ๋…ผ๋ฌธ๋‚˜์˜ด

๋ฉœ๋ฃจ(gustn1914) 2024-03-12 16:42 ์ถ”์ฒœ 10
AI ์ด๋ฏธ์ง€1


7fe98120e0813da023ec8fe44f9c703cc1187a508f2f4266cc4ad99a58883a734a12705eaede2da91056ee6c9c110dab52ad6e4f508dbda79fbb7cc809





https://www.semianalysis.com/p/google-we-have-no-moat-and-neither

Google "We Have No Moat, And Neither Does OpenAI"Leaked Internal Google Document Claims Open Source AI Will Outcompete Google and OpenAIwww.semianalysis.com

๋ฌธ๋‹ซ์€ close ai

๊ฐ•์ œ๋กœ open ์‹œ์ผœ๋ฒ„๋ฆฌ๋Š” ๋…ผ๋ฌธ ๋‚˜์˜ดย ย ใ…‹ใ…‹


https://arxiv.org/abs/2403.06634

Stealing Part of a Production Language ModelWe introduce the first model-stealing attack that extracts precise, nontrivial information from black-box production language models like OpenAI's ChatGPT or Google's PaLM-2. Specifically, our attack recovers the embedding projection layer (up to symmetries) of a transformer model, given typical API access. For under $20 USD, our attack extracts the entire projection matrix of OpenAI's Ada and Babbage language models. We thereby confirm, for the first time, that these black-box models have a hidden dimension of 1024 and 2048, respectively. We also recover the exact hidden dimension size of the gpt-3.5-turbo model, and estimate it would cost under $2,000 in queries to recover the entire projection matrix. We conclude with potential defenses and mitigations, and discuss the implications of possible future work that could extend our attack.arxiv.org

๋Œ“๊ธ€ 5

  • ์•„ ์ด๊ฑฐ ๋‚ด๊ฐ€ ์˜ฌ๋ฆด๋ ค๊ณ  ํ–ˆ๋Š”๋ฐ ์ด์ œ ์ „์œ ๋ฌผ ๋ชปํ•˜๋‹ค ์–ด์ฉŒ๋ฉด ํ† ๋ ŒํŠธ์— ๋–  ๋Œ์•„๋‹์ˆ˜ ์žˆ๋‹ค๋Š”๋ฐ ใ„ทใ„ทใ„ท

    ์ต๋ช…(studio0168) 2024-03-12 16:56
  • ์ด๋ฏธ ๋ ˆ๋“œํŒ€์—์„œ ์˜จ๊ฐ– ํƒˆ์ทจ์‹œ๋„๋ฅผ ๋‹ค ํ•˜๊ณ  ์žˆ์„ํ…๋ฐ, ๋…ผ๋ฌธ๋‚˜์˜จ๊ฒŒ ๋ญ

    ์ต๋ช…(112.220) 2024-03-12 17:05
  • dccon
    ํฌ์ŠคํŠธํœด๋จผ.(ysoo75430) 2024-03-12 17:21
  • ํ—‰

    ๋ถ€ํŒจํ•˜๋Š”์œ ์ „์ž!!!(sansss2015) 2024-03-12 18:08
  • dccon
    ์ต๋ช…(211.41) 2024-03-12 18:25

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