[B! AI] Oooã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

Ooo id:Ooo

AIã«é–¢ã™ã‚‹Oooã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (27)

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Retentive Network: A Successor to Transformer for Large Language Models
In this work, we propose Retentive Network (RetNet) as a foundation architecture for large language models, simultaneously achieving training parallelism, low-cost inference, and good performance. We theoretically derive the connection between recurrence and attention. Then we propose the retention mechanism for sequence modeling, which supports three computation paradigms, i.e., parallel, recurre
Ooo 2023/07/24
performance

ai
ãƒªãƒ³ã‚¯
å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«(LLM)ã®ä½œã‚Šæ–¹ GPT-NeoXç·¨ Part 1
ã¯ã˜ã‚ã« Turing æ ªå¼ä¼šç¤¾ã®ãƒªã‚µãƒ¼ãƒãƒãƒ¼ãƒ ã§ã‚¤ãƒ³ã‚¿ãƒ¼ãƒ³ã‚’ã—ã¦ã„ã‚‹æ±äº¬å·¥æ¥å¤§å¦ B4 ã®è—¤äº•(@okoge_kaz)ã§ã™ã€‚ å¤§è¦æ¨¡ãƒ¢ãƒ‡ãƒ«ã¸ã®æ³¨ç›®ã®é«˜ã•ã‚’è‚Œã§æ„Ÿã˜ã‚‹ä»Šæ—¥ã“ã®ã”ã‚ã§ã™ãŒã€äº‹å‰å¦ç¿’ã®çŸ¥è¦‹ã«ã¤ã„ã¦ã¯ä¾ç„¶ã¨ã—ã¦ååˆ†ã«å…±æœ‰ã•ã‚Œã¦ã„ã‚‹ã¨ã¯è¨€ã„é›£ã„ã¨å€‹äººçš„ã«æ„Ÿã˜ã¦ã„ã¾ã™ã€‚ Turingæ ªå¼ä¼šç¤¾ã§ã¯ã€æ¬¡ä¸–ä»£ã®è‡ªå‹•é‹è»¢æŠ€è¡“ã‚’æ”¯ãˆã‚‹æŠ€è¡“ã®1ã¤ã¨ã—ã¦å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«ã«æ³¨ç›®ã—ã¦ãŠã‚Šã€ç‹¬è‡ªã«ç ”ç©¶é–‹ç™ºã‚’è¡Œã£ã¦ã„ã¾ã™ã€‚ä»Šå›žã¯å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«ã‚’å¦ç¿’ã™ã‚‹éš›ã€ç”¨ã„ã‚‹ãƒ©ã‚¤ãƒ–ãƒ©ãƒªå€™è£œã®ï¼‘ã¤ã«ä¸ŠãŒã‚‹ã§ã‚ã‚ã†GPT-NeoXã«ã¤ã„ã¦è§£èª¬ã—ã¾ã™ã€‚ ä»¥ä¸‹ã§ç’°å¢ƒæ§‹ç¯‰æ–¹æ³•ã€å¦ç¿’ã‚’è¡Œã†æ–¹æ³•ãªã©ã«ã¤ã„ã¦è©³ã—ãè§£èª¬ã—ã¾ã™ã€‚ GPT-NeoXã¨ã¯ EleutherAIãŒç®¡ç†ã—ã¦ã„ã‚‹NIDIA/Megatron-LM ãƒ™ãƒ¼ã‚¹ã®å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«(Large Language Model: LLM)ã‚’å¦ç¿’ã™ã‚‹ãŸã‚ã®ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã§ã™ã€‚ Mi
Ooo 2023/07/19
python

llm

ai

gpt

transformers
ãƒªãƒ³ã‚¯
CTOã®è¦–ç‚¹ã‹ã‚‰è¦‹ãŸAzure OpenAI Serviceã¨OpenAIã®ChatGPT APIã®æ·±å €ã‚Šæ¯”è¼ƒ - Qiita
â€» ã“ã®è¨˜äº‹ã®å†…å®¹ã¯å…ˆæ—¥ã®Qiita Nightã§ãŠè©±ã—ã—ãŸã“ã¨ã¨ä¸€éƒ¨é‡è¤‡ã—ã¾ã™ã€‚ Qiita Nightã§ã¯LTã®åˆ¶é™æ™‚é–“(10åˆ†)ã«åŽã‚ã‚‹ãŸã‚ã€çµæ§‹ç«¯æŠ˜ã‚Šã¾ã—ãŸã€‚ ã¯ã˜ã‚ã« ChatGPTãŒç™»å ´ã—ã¦ã‹ã‚‰æ•°ãƒ¶æœˆãŒçµŒã¡ã¾ã—ãŸã€‚ ChatGPTã‚’ã¯ã˜ã‚ã¨ã—ãŸGenerative AIã¯å®Œå…¨ã«ç¾åœ¨ã®ITæ¥ç•Œã®ãƒˆãƒ¬ãƒ³ãƒ‰ã¨ãªã£ã¦ã„ã¾ã™ã€‚ ä»Šã‚„å¤šãã®ä¼æ¥ã§ChatGPT APIã‚’ã‚µãƒ¼ãƒ“ã‚¹ã«çµ„ã¿è¾¼ã‚“ã§é¡§å®¢æä¾›ã‚’é–‹å§‹ã—ãŸã‚Šã€è‡ªç¤¾ã®ç¤¾å†…ã‚·ã‚¹ãƒ†ãƒ ã«çµ„ã¿è¾¼ã‚“ã ã‚Šã¨ç©æ¥µçš„ã«åˆ©ç”¨ã™ã‚‹ã‚ˆã†ã«ãªã‚Šã¾ã—ãŸã€‚ ç§ã‚‚Generative AIãŒç„¡ããªã‚‹ã¨æ¥å‹™ã«æ”¯éšœãŒå‡ºã‚‹ãƒ¬ãƒ™ãƒ«ã§åˆ©ç”¨ã—ã¦ã„ã¾ã™ã€‚ ãã—ã¦ã€2023å¹´5æœˆæ™‚ç‚¹ã§ã¯ChatGPTã®APIã‚’åˆ©ç”¨ã™ã‚‹æ–¹æ³•ã¨ã—ã¦ã€æœ¬å®¶OpenAIç¤¾ãŒæä¾›ã—ã¦ã„ã‚‹APIã‚’åˆ©ç”¨ã™ã‚‹æ–¹æ³•ã¨Microsoftç¤¾ãŒæä¾›ã—ã¦ã„ã‚‹Azure OpenAI Serviceã®APIã‚’åˆ©ç”¨ã™ã‚‹æ–¹æ³•ã®2ã¤ãŒ
Ooo 2023/05/16
azure

AI

gpt
ãƒªãƒ³ã‚¯
methexis-inc/img2prompt â€“ Run with an API on Replicate
Run time and cost This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 32 seconds. The predict time for this model varies significantly based on the inputs. Model description Provides approximate text prompts that can be used with stable diffusion to re-create similar looking versions of the image/painting. Try it by copying the text prompts to stable diffusion! A sligh
Ooo 2022/08/29
text

api

image

AI

stable diffusion
ãƒªãƒ³ã‚¯
Stable Diffusionã‚’ã„ã‚‰ã™ã¨ã‚„ã§ãƒ•ã‚¡ã‚¤ãƒ³ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°ã™ã‚‹
å··ã§è©±é¡Œã®Stable Diffusionï¼ˆä»¥ä¸‹SDï¼‰ã‚’ãƒ•ã‚¡ã‚¤ãƒ³ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°ã™ã‚‹æ–¹æ³•ãŒå…¬é–‹ã•ã‚ŒãŸã®ã§ã€æ—©é€Ÿã‚„ã‚Šã¾ã™ã€‚
Ooo 2022/08/28
stable diffusion

ai
ãƒªãƒ³ã‚¯
PlayTorch is a framework for rapidly creating mobile AI experiences.
This project has been archived and is no longer actively maintained.
Ooo 2022/08/25
pytorch

ai

expo

react

react native

playtorch

mobile

ios

android
ãƒªãƒ³ã‚¯
Stable Diffusion Public Release â€” Stability AI
It is our pleasure to announce the public release of stable diffusion following our release for researchers [https://stability.ai/stablediffusion] Over the last few weeks, we all have been overwhelmed by the response and have been working hard to ensure a safe and ethical release, incorporating data from our beta model tests and community for the developers to act on. In cooperation with the tirel
Ooo 2022/08/23
AI
ãƒªãƒ³ã‚¯
Googleã€â€œãƒãƒ¼ã‚«ãƒ«AIâ€æ§‹ç¯‰ç”¨ãƒ¯ãƒ³ãƒœãƒ¼ãƒ‰ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿ã‚„ã‚«ãƒ¡ãƒ©ã‚’ã€ŒCoralã€ãƒ–ãƒ©ãƒ³ãƒ‰ã§ç™ºå£²
ç±³Googleã¯3æœˆ6æ—¥ï¼ˆç¾åœ°æ™‚é–“ï¼‰ã€â€œãƒãƒ¼ã‚«ãƒ«AIâ€ã§IoTç«¯æœ«ã‚’æ§‹ç¯‰ã™ã‚‹ãŸã‚ã®ãƒ—ãƒ©ãƒƒãƒˆãƒ•ã‚©ãƒ¼ãƒ ã€ŒCoralã€ï¼ˆÎ²ï¼‰ã‚’ç™ºè¡¨ã—ãŸã€‚ã‚«ãƒ¡ãƒ©ãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã‚„é–‹ç™ºãƒœãƒ¼ãƒ‰ãªã©ã€5ç¨®é¡žã®ãƒãƒ¼ãƒ‰ã‚¦ã‚§ã‚¢ã‚‚æŠ«éœ²ã—ãŸã€‚ ãƒãƒ¼ã‚«ãƒ«AIã‚ã‚‹ã„ã¯ã€Œã‚ªãƒ³ãƒ‡ãƒã‚¤ã‚¹AIã€ã¨ã¯ã€ã‚¯ãƒ©ã‚¦ãƒ‰ã§ã¯ãªãã‚¨ãƒƒã‚¸ã‚ã‚‹ã„ã¯ãƒãƒ¼ã‚«ãƒ«ã‚ã‚‹ã„ã¯ãƒ‡ãƒã‚¤ã‚¹ä¸Šã§AIå‡¦ç†ã‚’è¡Œã†ã“ã¨ã€‚Coralã¯ã€Œå®Œå…¨ãªãƒãƒ¼ã‚«ãƒ«AIãƒ„ãƒ¼ãƒ«ã‚ãƒƒãƒˆã‚’æä¾›ã™ã‚‹ã€ã¨ã„ã†ã€‚ãƒãƒ¼ãƒ‰ã‚¦ã‚§ã‚¢ã‚³ãƒ³ãƒãƒ¼ãƒãƒ³ãƒˆã€ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ãƒ„ãƒ¼ãƒ«ã€ãƒãƒ¼ã‚«ãƒ«ã§ãƒ‹ãƒ¥ãƒ¼ãƒ©ãƒ«ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã‚’æ§‹ç¯‰ã™ã‚‹ãŸã‚ã«å¿…è¦ãªã‚³ãƒ³ãƒ†ãƒ³ãƒ„ã§æ§‹æˆã•ã‚Œã‚‹ã€‚ ã„ãšã‚Œã‚‚åŒæ—¥å…¬å¼ç‰ˆã«ãªã£ãŸãƒ•ãƒ¬ãƒ¼ãƒ ãƒ¯ãƒ¼ã‚¯ã€ŒTensorFlow Liteã€ã‚’ã‚µãƒãƒ¼ãƒˆã™ã‚‹ã€‚ ã€ŒCoral Dev Boardã€ã¯ã€SoMï¼ˆã‚·ã‚¹ãƒ†ãƒ ã‚ªãƒ³ãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ï¼‰ã¨ã—ã¦è¨è¨ˆã•ã‚ŒãŸã‚·ãƒ³ã‚°ãƒ«ãƒœãƒ¼ãƒ‰ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿ã€‚åŒç¤¾ãŒæ˜¨å¹´10æœˆã«ç™ºè¡¨ã—ãŸã‚¨ãƒƒã‚¸ãƒ‡ãƒã‚¤ã‚¹å‘ã‘ASICã€ŒEdge TPUã€ã€NXP
Ooo 2019/03/07
AI

google
ãƒªãƒ³ã‚¯
nni | An open source AutoML toolkit for neural architecture search and hyper-parameter tuning.
Who should consider using NNI Those who want to try different AutoML algorithms in their training code (model) at their local machine. Those who want to run AutoML trial jobs in different environments to speed up search (e.g. remote servers and cloud). Researchers and data scientists who want to implement their own AutoML algorithms and compare it with other algorithms. ML Platform owners who want
Ooo 2018/12/25
microsoft

ml

ai

automl

machinelearning
ãƒªãƒ³ã‚¯
GitHub - microsoft/nni: An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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Ooo 2018/12/25
microsoft

MachineLearning

AI

automl
ãƒªãƒ³ã‚¯
Autonomous Tidying-up Robot System - Preferred Networks
Overview æ ªå¼ä¼šç¤¾Preferred Networksã¯ã€ãƒãƒœãƒƒãƒˆãŒèº«è¿‘ãªå ´æ‰€ã§æ´»èºã™ã‚‹ç¤¾ä¼šã®å®Ÿç¾ã«å‘ã‘ã¦ã€ãƒ‘ãƒ¼ã‚½ãƒŠãƒ«ãƒãƒœãƒƒãƒˆã®ç ”ç©¶é–‹ç™ºã‚’è¡Œã£ã¦ã„ã¾ã™ã€‚ CEATEC JAPAN 2018ã§ã¯, ãƒˆãƒ¨ã‚¿è‡ªå‹•è»Šæ ªå¼ä¼šç¤¾ãŒé–‹ç™ºã™ã‚‹ "ç”Ÿæ´»æ”¯æ´ãƒãƒœãƒƒãƒˆHSRï¼ˆHuman Support Robot)" ã‚’ä½¿ã„â€»ã€æœ€å…ˆç«¯ã®æ·±å±¤å¦ç¿’æŠ€è¡“ã‚’å¿œç”¨ã—ãŸã€Œå…¨è‡ªå‹•ãŠç‰‡ä»˜ã‘ãƒãƒœãƒƒãƒˆã‚·ã‚¹ãƒ†ãƒ ã€ã‚’å±•ç¤ºã—ã¾ã™ã€‚ ã“ã®ã‚·ã‚¹ãƒ†ãƒ ã¯ã€CEATEC JAPAN 2018ã«å±•ç¤ºã•ã‚Œã‚‹ã‚¤ãƒŽãƒ™ãƒ¼ã‚·ãƒ§ãƒ³æ€§ãŒé«˜ãå„ªã‚Œã¦ã„ã‚‹æŠ€è¡“ãƒ»è£½å“ãƒ»ã‚µãƒ¼ãƒ“ã‚¹ç‰ã‚’è¡¨å½°ã™ã‚‹ã€ŒCEATEC AWARD 2018ã€ ã«ãŠã„ã¦ã€ã‚¤ãƒ³ãƒ€ã‚¹ãƒˆãƒªï¼ãƒžãƒ¼ã‚±ãƒƒãƒˆéƒ¨é–€ æº–ã‚°ãƒ©ãƒ³ãƒ—ãƒª ã‚’å—è³žã—ã¾ã—ãŸã€‚ éƒ¨å±‹ã®å…¨è‡ªå‹•ç‰‡ä»˜ã‘ã¯ã€å¾“æ¥ã®ãƒãƒœãƒƒãƒˆã‚·ã‚¹ãƒ†ãƒ ã§ã¯å®Ÿç¾å›°é›£ã§ã—ãŸãŒã€è¿‘å¹´ã®æ·±å±¤å¦ç¿’ã®ç™ºå±•ã«ã‚ˆã£ã¦åˆã‚ã¦å®Ÿç”¨çš„ãªãƒ¬ãƒ™ãƒ«ã§å®Ÿç¾ã§ãã¾ã—ãŸã€‚ ç‰©ã‚’ã¤ã‹ã‚€ã€ç‰©ã‚’ç½®ãã€å‹•ä½œè¨ˆç”»ã‚’
Ooo 2018/10/15
robot

deeplearning

AI

machinelearning
ãƒªãƒ³ã‚¯
MicrosoftãŒã€ŒSketch 2 Codeã€ã‚’å…¬é–‹ï¼AIãŒã€æ‰‹æ›¸ãã®ãƒ¯ã‚¤ãƒ¤ãƒ¼ãƒ•ãƒ¬ãƒ¼ãƒ ã‚’HTMLã«è‡ªå‹•å¤‰æ›ã—ã¦ãã‚Œã‚‹æ–°æ™‚ä»£ã«ã€‚ã“ã‚Œã¯ã™ã”ã„ï¼ï¼ï½œæ¦ŠåŽŸæ˜Œå½¦
MicrosoftãŒã€ŒSketch 2 Codeã€ã‚’å…¬é–‹ï¼AIãŒã€æ‰‹æ›¸ãã®ãƒ¯ã‚¤ãƒ¤ãƒ¼ãƒ•ãƒ¬ãƒ¼ãƒ ã‚’HTMLã«è‡ªå‹•å¤‰æ›ã—ã¦ãã‚Œã‚‹æ–°æ™‚ä»£ã«ã€‚ã“ã‚Œã¯ã™ã”ã„ï¼ï¼ æµã‚Œã¦ããŸãƒ„ã‚¤ãƒ¼ãƒˆã‚’ã¿ã¦ã€Œãªã‚“ã ã“ã®ãƒ‡ãƒ¢ã¯ã€ã¨ã„ã‚ã„ã‚è¦‹ã¦ã¿ãŸã¨ã“ã‚ã€Microsoft AI labãŒã™ã”ã„æŠ€è¡“ã‚’å…¬é–‹ã—ã¦ã„ãŸã®ã§ç°¡å˜ã«ã¾ã¨ã‚ã¾ã™ã€‚ã©ã†ã„ã†æŠ€è¡“ã‹ã¨ã„ã†ã¨ã€Œæ‰‹æ›¸ãã®ãƒ¯ã‚¤ãƒ¤ãƒ¼ãƒ•ãƒ¬ãƒ¼ãƒ ã‚’é©åˆ‡ã«ä¿®æ£ã—ã¦HTMLã«è‡ªå‹•å¤‰æ›ã€ã—ã¦ãã‚Œã¾ã™ã€‚ Kabel, Spike Techniques, MicrosoftãŒ2018å¹´8æœˆæœ«ã«å…¬é–‹ã—ãŸSketch 2 Codeã¨ã„ã†ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã§ã™ã€‚GitHubï¼ˆÂ https://github.com/Microsoft/ailab/tree/master/Sketch2Code ï¼‰ã§å…¬é–‹ã•ã‚Œã¦ã„ã‚‹ã®ã§ã€ç¢ºèªã™ã‚‹ã“ã¨ãŒã§ãã¾ã™ã€‚è¡Œã£ã¦ã„ã‚‹å‡¦ç†ã¯ä»¥ä¸‹ã®é€šã‚Šã€‚ 1. ãƒ¦ãƒ¼ã‚¶ã¯Webã«ç”»åƒï¼ˆæ‰‹æ›¸ããƒ¯ã‚¤ãƒ¤ãƒ¼ãƒ•ãƒ¬
Ooo 2018/09/01
microsoft

code

AI

html
ãƒªãƒ³ã‚¯
Nippon Telegraph and Telephone Corporation corevo APIãƒãƒ¼ã‚¿ãƒ«
Ooo 2018/03/17
corevo

ai
ãƒªãƒ³ã‚¯
How to build your own AlphaZero AI using Python and Keras
Update! (2nd December 2019)Iâ€™ve just released a series on MuZero â€” AlphaZeroâ€™s younger and cooler brother. Check it out ðŸ‘‡ How to Build Your Own MuZero Using Python (Part 1/3) How to Build Your Own MuZero Using Python (Part 2/3) How to Build Your Own MuZero Using Python (Part 3/3) In this article Iâ€™ll attempt to cover three things: Two reasons why AlphaZero is a massive step forward for Artificial
Ooo 2018/01/27
AI

game

Deep Learning
ãƒªãƒ³ã‚¯
IBMã«è©°ã‚å¯„ã‚‹Watsonãƒ¦ãƒ¼ã‚¶ãƒ¼ã€APIã®ç›¸æ¬¡ãå¤‰æ›´ã§æ··ä¹±ã‚‚
2015å¹´ã«ç±³å›½ã§é–‹å‚¬ã•ã‚ŒãŸç±³IBMã®äººå·¥çŸ¥èƒ½ï¼ˆAIï¼‰ã‚·ã‚¹ãƒ†ãƒ ã€ŒWatsonã€é–¢é€£ã®ã‚¤ãƒ™ãƒ³ãƒˆã§ã€æ—¥æœ¬ã®Watsonãƒ¦ãƒ¼ã‚¶ãƒ¼ãŒIBMã®æ‹…å½“è€…ã«è©°ã‚å¯„ã‚‹ã‚·ãƒ¼ãƒ³ãŒã‚ã£ãŸã€‚ãƒ¦ãƒ¼ã‚¶ãƒ¼ãŒåˆ©ç”¨ã—ã¦ã„ã‚‹ã€ŒWatson APIã€ã®1ã¤ãŒ2016å¹´ã«ã€Œã‚µãƒ³ã‚»ãƒƒãƒˆã€ã«ãªã‚‹ã¨èžã„ãŸã‹ã‚‰ã ã€‚ã‚µãƒ³ã‚»ãƒƒãƒˆã¯ã‚µãƒ¼ãƒ“ã‚¹ãŒçµ‚äº†ã™ã‚‹ã“ã¨ã‚’æŒ‡ã™ã€‚ ã“ã®æ§˜åã‚’ç›®æ’ƒã—ãŸã¨ã„ã†å‚åŠ è€…ã¯ã€Œãƒ¦ãƒ¼ã‚¶ãƒ¼ãŒä¸æº€ã‚’æŒã¤ã®ã‚‚ç„¡ç†ã¯ãªã„ã€ã¨è©±ã™ã€‚Watsonæ—¥æœ¬èªžç‰ˆã®æ£å¼ç™ºè¡¨ã¯2016å¹´2æœˆã ãŒã€ä¸€éƒ¨ãƒ¦ãƒ¼ã‚¶ãƒ¼ã¯2015å¹´ã‹ã‚‰å°Žå…¥ã‚’é€²ã‚ã¦ã„ãŸã€‚APIã®çµ‚äº†ã§å½±éŸ¿ã‚’å—ã‘ãŸã®ã¯ã€è©¦è¡ŒéŒ¯èª¤ã—ã¤ã¤Watsonã®å°Žå…¥ã‚’é€²ã‚ã¦ã„ãŸã“ã‚Œã‚‰ã®å…ˆè¡Œãƒ¦ãƒ¼ã‚¶ãƒ¼ã ã€‚ åŒã˜å½¹å‰²ã‚’æžœãŸã™å¾Œç¶™APIã¯ã€æ©Ÿèƒ½ã‚„ä½¿ã„å‹æ‰‹ã«é–¢ã—ã¦å¤§å¹…ã«å¼·åŒ–ã•ã‚ŒãŸä¸€æ–¹ã§ã€äº’æ›æ€§ã¯ãªããƒ‡ãƒ¼ã‚¿ã‚’ãã®ã¾ã¾å¼•ãç¶™ãã“ã¨ã¯ã§ããªã„ã€‚ ã—ã‹ã—APIãŒä½¿ãˆãªããªã‚‹ä»¥ä¸Šã€å…ˆè¡Œãƒ¦ãƒ¼ã‚¶ãƒ¼ã¯å¾Œç¶™APIã‚’ä½¿ã‚ã–ã‚‹ã‚’å¾—ãªã„ã€‚å¾“æ¥ã®
Ooo 2018/01/24
api

ibm

AI

watson
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Ooo 2017/11/02
AI
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Ooo 2017/10/20
adobe

AI

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Ooo 2017/10/11
AI

Machine Learning
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Ooo 2017/09/14
AI
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Secondmind
The race is on to re-imagine every aspect of the design, development and experience of driving. Engineering organizations that define this future through software will compete. Those with the optimization tools to crush mounting software complexity and accelerate development productivity will win. From reducing design simulation time and calibration overhead, to continuously improving energy effic
Ooo 2017/09/06
ai

decision
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