๐Ÿ“ข ๊ฒ€์ƒ‰ ๊ธฐ๋Šฅ ์ถ”๊ฐ€ ์˜ˆ์ •

์ฃผ๋ฏผ๊ฑด

๊ธฐ๋ก = ์„ฑ์žฅ

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23.06.18 (Sun)

๋ชจ๋ธ์„ ๋ฐ”๋ผ๋ณด๋Š” ๊ด€์ ์„ ํ•จ์ˆ˜ํ˜• ํ”„๋กœ๊ทธ๋ž˜๋ฐ์„ ํ•˜๋“ฏ, ํ•˜๋‚˜์˜ ๋ชจ๋ธ์€ ํ•˜๋‚˜์˜ ์—ญํ• ์„ ๋งก๊ฒŒ ๋งŒ๋“  ๋Š๋‚Œ์ด๋‹ค. ์˜ˆ๋ฅผ ๋“ค๋ฉด, ํŠธ๋žœ์Šคํฌ๋จธ๋Š” ์ถ”๋ก ์„ ๋ชปํ•œ๋‹ค๋Š” ๋…ผ๋ฌธ์€ ๋ง์„ ํ•˜๋Š” ๋ชจ๋ธ์— ์ˆ˜ํ•™์  ์ถ”๋ก ๊นŒ์ง€ ํ•˜๋ผ๊ณ  ํ–ˆ๊ณ , OpenAI๊ฐ€ ๋งŒ๋“  ๋ชจ๋ธ ๊ตฌ์กฐ๋Š” GPT๋Š” ๋ง๋งŒ ํ•˜๋„๋กํ•˜๊ณ  ๋ณด์ƒ ๋ชจ๋ธ์„ ๋‘ฌ์„œ ์ถ”๋ก  ๊ณผ์ •์„ ๊ฒ€ํ† ํ•˜๋„๋ก ํ–ˆ๋‹ค. / ์‚ฌ๋žŒ์˜ ํ”ผ๋“œ๋ฐฑ์„ ๋ชจ๋ธ์˜ ํ•™์Šต ๋ฐ์ดํ„ฐ๋กœ ์ œ๊ณตํ•˜๋Š” ์ธก๋ฉด์—์„œ ๊ฐ•ํ™”ํ•™์Šต, ์•กํ‹ฐ๋ธŒ๋Ÿฌ๋‹์€ ํ•„์ˆ˜๋ถˆ๊ฐ€๊ฒฐํ•˜๋‹ค. / ์ˆ˜ํ•™์ด ์•„๋‹Œ ๋‹ค๋ฅธ ๋ถ„์•ผ์˜ ๊ณผ์ • ๊ฐ๋…์„ํ•˜๋ ค๋ฉด ์–ด๋–ป๊ฒŒ ๋ณด์ƒ ๋ชจ๋ธ์„ ๊ตฌ์„ฑํ•ด์•ผ๋ ๊นŒ?

23.06.17 (Sat)

์‹œ์žฅ์—์„œ ์‚ด์•„๋‚จ๋Š” ์‚ฌ๋žŒ์ด ๋˜๊ธฐ
์ด๋ฒˆ ํฌ์ŠคํŒ…์—์„œ๋Š” ์‹œ์žฅ ๊ฒฝ์ œ์— ์ฐธ์—ฌํ•˜๋Š” ํ•œ ๋ช…์˜ ํ”Œ๋ ˆ์ด์–ด๋กœ์จ ํ•„์ž๊ฐ€ ์ƒ๊ฐํ•ด์˜จ ๊ณ ๋ฏผ๋“ค์— ๋Œ€ํ•ด ํ•œ๋ฒˆ ๋‹ด๋‹ดํžˆ ํ’€์–ด๋ณด๋ ค๊ณ  ํ•œ๋‹ค. ์ง€๊ธˆ๊นŒ์ง€ ํ•„์ž๋Š” ๊ฐœ์ธ์˜ ์„ฑ์žฅ๊ณผ ๋ชจํ‹ฐ๋ฒ ์ด์…˜ ๊ทธ๋ฆฌ๊ณ  ์ฒ ํ•™์— ๋Œ€ํ•œ ์ด์•ผ๊ธฐ๋ฅผ ๋งŽ์ด ํ•ด์™”์ง€๋งŒ, ์ด๋ฒˆ ํฌ์ŠคํŒ…์—์„œ๋Š” ์ง€๊ธˆ๊นŒ์ง€์™€๋Š” ์กฐ๊ธˆ ๋‹ค๋ฅธ ํ˜„์‹ค์ ์ธ ์ด์•ผ๊ธฐ๋ฅผ ํ•ด๋ณด๋ ค๊ณ  ํ•œ๋‹ค. ๊ทธ์ € ์—ด์‹ฌํžˆ ํ•˜๋‹ค๋ณด๋ฉด ์–ธ์  ๊ฐ€ ์ž˜ ๋  ๊ฒƒ์ด๋ผ๋Š” ๋ง๋ณด๋‹ค๋Š” ์ •๋ง ํ˜„์‹ค์ ์œผ๋กœ ๋„์›€์ด ๋  ๋งŒํ•œ ๊ณ ๋ฏผ์„ ํ•ด๋ณผ ์ˆ˜ ์žˆ๋Š” ์•„์  ๋‹ค๋ฅผ ๋˜์ ธ๋ณธ๋‹ค.
์ž์‹ ์˜ ๋…ธ๋™๋ ฅ์— ๊ฐ๊ด€์  ๊ฐ€์น˜๋ฅผ ๋งค๊ธธ ์ค„ ์•Œ์•„์•ผ ์‹œ์žฅ์—์„œ ์‚ด์•„๋‚จ์„ ์ˆ˜ ์žˆ๋‹ค

23.06.16 (Fri)

Data-Centric AI ๊ด€์ ์œผ๋กœ ์žฌํ•ด์„ํ•˜๋Š” ์ž์—ฐ์–ธ์–ด์ฒ˜๋ฆฌ ๊ธฐ๋ฐ˜ History of AI โ€” Upstage
์ธ๊ณต์ง€๋Šฅ 70๋…„ ์—ญ์‚ฌ์˜ ์ฃผ์š” ๋ถ„์•ผ ์ค‘ ํ•˜๋‚˜์ธ ์ž์—ฐ์–ธ์–ด์ฒ˜๋ฆฌ(NLP)๋ฅผ Data-Centric AI ๊ด€์ ์œผ๋กœ ์žฌํ•ด์„ํ•ด ๋ณด๋ฉด ์–ด๋–ค ์ธ์‚ฌ์ดํŠธ๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ์„๊นŒ์š”? ๊ทœ์น™ ๊ธฐ๋ฐ˜, ํ†ต๊ณ„ ๊ธฐ๋ฐ˜, ๊ธฐ๊ณ„ํ•™์Šต ๊ธฐ๋ฐ˜, ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜์„ ๊ฑฐ์ณ Large Language Model(LLM)์˜ ์‹œ๋Œ€์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ AI์˜ ํ๋ฆ„์„ ๋˜์งš์–ด๋ณด์„ธ์š”.
"ChatGPT์˜ ํ•ต์‹ฌ์€ Human feed back data, ์ฆ‰ ์–‘์งˆ์˜ ๋ฐ์ดํ„ฐ์ž…๋‹ˆ๋‹ค. ์•ž์œผ๋กœ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ์—…์˜ ํ•ต์‹ฌ ์—ญ๋Ÿ‰์€ ๊ฒฐ๊ตญ ์–‘์งˆ์˜ ๋ฐ์ดํ„ฐ๋ฅผ ํ™•๋ณดํ–ˆ๋Š๋ƒ ์•ˆํ–ˆ๋Š”๋ƒ๋กœ ๊ฐˆ๋ฆฌ๊ฒŒ ๋  ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค. ๊ธฐ์—…์—์„œ AI ๋น„์ฆˆ๋‹ˆ์Šค๋ฅผ ํ•  ๋•Œ์—๋„ ๋ฐ์ดํ„ฐ๋ฅผ ์ž˜ ํ™•๋ณดํ•  ์ˆ˜ ์žˆ๋Š” ๊ตฌ์กฐ์ธ์ง€, ๋” ๋‚˜์•„๊ฐ€์„œ ์–‘์งˆ์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋งŒ๋“ค์–ด ๋‚ผ ์ˆ˜ ์žˆ๋Š” ํ”„๋กœ์„ธ์Šค๊ฐ€ ๊ฐ–์ถฐ์ ธ ์žˆ๋Š”์ง€๋ฅผ ๊ณ ๋ฏผํ•ด์•ผํ•  ๊ฒƒ ์ž…๋‹ˆ๋‹ค."

23.06.15 (Thu)

์ง€๊ธˆ์€ ๋ฐ์‹œ๋ฒจ ๊ธฐ์ค€์ด๋ผ๋“ ์ง€ ์‚ฌ๋žŒ์˜ ํ‘œ์ • ๊ธฐ๋ฐ˜์œผ๋กœ ์˜์ƒ์„ ํŽธ์ง‘ํ•ด์ฃผ๋Š”๋ฐ ๋‹ค์Œ ๋ฒ„์ „์€ ์ธ๊ฐ„์˜ ํฅ๋ฏธ ํ˜น์€ ๊ด€์‹ฌ ๊ธฐ์ค€์œผ๋กœํŽธ์ง‘ํ•ด์ค„ ์ˆ˜ ์žˆ์ง€ ์•Š์„๊นŒ? ์ด๋ฏธ ๊ตฌํ˜„ ๊ฐ€๋Šฅํ•œ ๊ธฐ๋Šฅ์ด๊ธดํ•˜๋‹ค RLHF๋กœ / ์•„๋ฌดํŠผ ๋ฏธ๋ž˜๋Š” ๋ฉ€ํ‹ฐ๋ชจ๋‹ฌ

23.06.14 (Wed)

Open LLM Leaderboard - a Hugging Face Space by HuggingFaceH4
Discover amazing ML apps made by the community
I-JEPA: The first AI model based on Yann LeCunโ€™s vision for more human-like AI
I-JEPA learns by creating an internal model of the outside world, which compares abstract representations of images (rather than comparing the pixels themselves).
without having the model fill in pixel-level details, which tend to result in learning less semantically meaningful representations.
Segment Anything: TorchServe๋กœ ๋ฐฐํฌํ•˜๊ธฐ - code ํฌํ•จ
Segment Anything model์„ TorchServe๋ฅผ ํ†ตํ•ด ๋ฐฐํฌํ•˜๋Š” ๊ณผ์ •์„ Code๋ฅผ ํ†ตํ•ด์„œ ์ƒ์„ธํ•˜๊ฒŒ ์•Œ๋ ค๋“œ๋ฆฝ๋‹ˆ๋‹ค. python code์™€ docker๋ฅผ ์‚ฌ์šฉํ•ด ์ถ”๋ก  ํ™˜๊ฒฝ์„ ๋งŒ๋“œ๋Š” ๊ณผ์ •์ด ํฌํ•จ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
๋…ผ๋ฌธ๋ฆฌ๋ทฐ Segment Anything | SAM
Segment Anything Model์€ SAM์€ ๊ฐ์ฒด ์‹๋ณ„ ์„ฑ๋Šฅ, ํด๋ž˜์Šค(=๊ฐ์ฒด ์นดํ…Œ๊ณ ๋ฆฌ) ์ž์œ ๋„, ์ž‘๊ฑฐ๋‚˜ ๋ณต์žกํ•œ ๊ฐ์ฒด์— ๋Œ€ํ•œ ์„ธ๋ถ„ํ™”๋œ ๋ถ„ํ• , ์‹ค์‹œ๊ฐ„ ์ฒ˜๋ฆฌ, ์‰ฌ์šด ์„œ๋น„์Šค ํ†ตํ•ฉ ๋ฐ ์‚ฌ์šฉ ๋“ฑ ๋‹ค์–‘ํ•œ ์ธก๋ฉด์—์„œ ์ด์ ์„ ๊ฐ–๋Š” ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค.
Comparing current and prior imaging studies in radiology AI
Todayโ€™s AI radiology solutions donโ€™t effectively account for past imaging findings despite their routine use by radiologists. BioViL-T jointly trains text and image encoders that can ground radiology text across longitudinal images:

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