GeminiTechnologies Gemini breaks new ground: a faster model, longer context and AI agents
Text-to-Speech AI: Lifelike Speech Synthesis | Google Cloud
Google ã®æœ€å…ˆç«¯ AI テクノãƒã‚¸ãƒ¼ã‚’活用ã—㟠API を利用ã—ã¦ã€ãƒ†ã‚ストを自然ãªéŸ³å£°ã«å¤‰æ›ã§ãã¾ã™ã€‚ æ–°è¦ã®ãŠå®¢æ§˜ã«ã¯ã€Text-to-Speech ã‚„ä»–ã® Google Cloud プãƒãƒ€ã‚¯ãƒˆã‚’ãŠè©¦ã—ã„ãŸã ã‘る無料クレジットを最大 $300 分差ã—上ã’ã¾ã™ã€‚
WaveNet launches in the Google Assistant
To understand why WaveNet improves on the current state of the art, it is useful to understand how text-to-speech (TTS) - or speech synthesis - systems work today. The majority of these are based on so-called concatenative TTS, which uses a large database of high-quality recordings, collected from a single voice actor over many hours. These recordings are split into tiny chunks that can then be co
33122
Google「DeepMindã€ã€ã‚³ãƒ³ãƒ”ュータãŒäººåž‹ãƒ™ãƒ¼ã‚¹ã§B地点ã«ãŸã©ã‚Šç€ã最善ã®æ–¹æ³•ï¼ˆæŸ”軟ãªå‹•ã）を独å¦ã§ç”Ÿæˆã™ã‚‹å¼·åŒ–å¦ç¿’を用ã„ãŸã‚¢ãƒ—ãƒãƒ¼ãƒã‚’æ案ã—ãŸè«–文を発表 2017-07-11 Googleã®AIã‚’ç ”ç©¶ã™ã‚‹å会社「DeepMindã€ã¯ã€å¼·åŒ–å¦ç¿’ã§äººåž‹å«ã‚シミュレートã•ã‚ŒãŸç’°å¢ƒã®ä¸ã§è¤‡é›‘ã§æŸ”軟ãªå‹•ãを生æˆã™ã‚‹ã‚¢ãƒ—ãƒãƒ¼ãƒã‚’æ案ã—ãŸè«–文を公開ã—ã¾ã—ãŸã€‚ Emergence of Locomotion Behaviours in Rich Environments（PDF） ã“れら動ãã¯ã€ã‚³ãƒ³ãƒ”ュータãŒç‹¬å¦ã§æœ€å–„ã®æ–¹æ³•ã¨ã—ã¦è€ƒæ¡ˆã—ãŸè¡Œå‹•ã§ã™ã€‚ ç ”ç©¶è€…ã¯ã€ã‚¨ãƒ¼ã‚¸ã‚§ãƒ³ãƒˆã«å‹•ãã®ã‚»ãƒƒãƒˆã¨å‰é€²ã™ã‚‹ã‚¤ãƒ³ã‚»ãƒ³ãƒ†ã‚£ãƒ–を与ãˆã€Aã‹ã‚‰B地点ã«ãŸã©ã‚Šç€ã最善ã®æ–¹æ³•ã‚’生ã¿å‡ºã™ãŸã‚ã®å¼·åŒ–å¦ç¿’を仕込ã¿ã¾ã™ã€‚ コンピュータã¯ã€ä»Šã‚る動作を使ã£ã¦è©¦è¡ŒéŒ¯èª¤ã‚’ç¹°ã‚Šè¿”ã—ã€ã•ã¾ã–ã¾ãªå‹•ã方をæ€ã„ã¤ãä¸ã§æ¬¡ã€…ã¨æœ€å–„ã¸è¿‘ã¥ã‘ã¦ã„
Publications
Explore our research on some of the most complex and interesting challenges in AI. Latest research news Discover our latest AI breakthroughs and updates from the lab Research FermiNet: Quantum physics and chemistry from first principles Using deep learning to solve fundamental problems in computational quantum chemistry and explore how matter interacts with light
Open-sourcing DeepMind Lab
Research Open-sourcing DeepMind Lab Published 3 December 2016 Authors Charlie Beattie, Joel Leibo, Stig Petersen, Shane Legg DeepMind's scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how. To achieve this, we work from the premise that AI needs to be general. Agents should operate across a wide range of
グーグルã®DeepMindã€AI訓練プラットフォームをオープンソース化
Alphabetã®äººå·¥çŸ¥èƒ½éƒ¨é–€ã§ã‚ã‚‹DeepMindã¯ç±³å›½æ™‚é–“12月5æ—¥ã€ã€ŒDeepMind Labã€ã‚’オープンソース化ã™ã‚‹ã“ã¨ã‚’発表ã—ãŸã€‚DeepMind Labã¯ã€ã‚¨ãƒ¼ã‚¸ã‚§ãƒ³ãƒˆãƒ™ãƒ¼ã‚¹ã®AIç ”ç©¶ã®ãŸã‚ã®3Dゲームã®ã‚ˆã†ãªãƒ—ラットフォームã 。 一人称視点ã‹ã‚‰è¦³å¯Ÿã•ã‚Œã‚‹ï¼ˆDeepMind Labã®ã‚ˆã†ãªï¼‰3D世界ã§ã¯ã€æ±Žç”¨ã®äººå·¥çŸ¥èƒ½ã€ã¤ã¾ã‚Šäº‹å‰ã«ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ã—ãªãã¦ã‚‚ã€å¤‰åŒ–ã™ã‚‹ç’°å¢ƒã«é©å¿œã—ã¦ç¨¼åƒã§ãる能力ã®é–‹ç™ºãŒå®¹æ˜“ã«ãªã‚‹ã¯ãšã ã¨DeepMindã®ãƒãƒ¼ãƒ ã¯ãƒ–ãƒã‚°ã§èª¬æ˜Žã—ã¦ã„る。 DeepMind Labã®ã‚¨ãƒ¼ã‚¸ã‚§ãƒ³ãƒˆã¯æµ®éŠã™ã‚‹çƒä½“ã®å½¢ã®ã€Œèº«ä½“ã€ã‚’æŒã¡ã€ã‚¹ãƒ©ã‚¹ã‚¿ãƒ¼ã«ã‚ˆã£ã¦æµ®æšã—ãŸã‚Šã€å‹•ã„ãŸã‚Šã™ã‚‹ã€‚åŒãƒ—ラットフォームã§è¡Œã‚ã‚Œã‚‹ç ”ç©¶ã®ç„¦ç‚¹ã¯ãƒŠãƒ“ゲーションã€ãƒ¡ãƒ¢ãƒªã€ä¸€äººç§°è¦–点ã‹ã‚‰ã®3Dビジョンã€é‹å‹•åˆ¶å¾¡ã€ãƒ—ランニングã€æˆ¦ç•¥ã€æ™‚é–“ã 。ユーザーã¯GitHubを介ã—ã¦ã€æ–°ã—ã„レベルをDeepMind L
LipNet: End-to-End Sentence-level Lipreading
Lipreading is the task of decoding text from the movement of a speaker's mouth. Traditional approaches separated the problem into two stages: designing or learning visual features, and prediction. More recent deep lipreading approaches are end-to-end trainable (Wand et al., 2016; Chung & Zisserman, 2016a). However, existing work on models trained end-to-end perform only word classification, rather
Blizzardã¨DeepMindãŒã€ŽStarCraft IIã€ã®AIç ”ç©¶ã§ææºã€‚人工知能ãŒãƒ—ãƒã‚²ãƒ¼ãƒžãƒ¼ã‚’超ãˆã‚‹æ—¥ã¯è¿‘ã„？ - AUTOMATON
ホームニュース Blizzardã¨DeepMindãŒã€ŽStarCraft IIã€ã®AIç ”ç©¶ã§ææºã€‚人工知能ãŒãƒ—ãƒã‚²ãƒ¼ãƒžãƒ¼ã‚’超ãˆã‚‹æ—¥ã¯è¿‘ã„？ 日本時間ã®11月5æ—¥ãŠã‚ˆã³11月6æ—¥ã«é–‹å‚¬ã•ã‚ŒãŸBlizzard Entertainment（以下ã€Blizzard）ã«ã‚ˆã‚‹ãƒ•ã‚¡ãƒ³ã‚¤ãƒ™ãƒ³ãƒˆBlizzCon 2016ã«ã¦ã€Google傘下ã§AIç ”ç©¶ã‚’è¡Œã£ã¦ã„ã‚‹DeepMind Technologies（以下ã€DeepMind）ã¨BlizzardãŒã€ŽStarCraft IIã€ã®AIç ”ç©¶åˆ†é‡Žã§ææºã™ã‚‹ã“ã¨ãŒåˆ†ã‹ã£ãŸã€‚ 両社ãŒé–‹ç™ºã‚’å…±ã«ã™ã‚‹AIç ”ç©¶ç”¨ã®ã€ŒStarCraft II APIã€ã¯2017å¹´åˆæ—¬ã«å…¬é–‹ã•ã‚Œã‚‹ã€‚ AI技術分野ã§èºé€²ã™ã‚‹DeepMind DeepMindãŒã“ã‚Œã¾ã§ã«é–‹ç™ºã—ã¦ããŸäººå£çŸ¥èƒ½ã¨ã—ã¦ã¯ã€å¦ç¿’アルゴリズムã®ã€ŒDQN（Deep Q-Network）ã€ã¨å›²ç¢AI「Alpha Goã€ãŒæœ‰
DeepMind and Blizzard to release StarCraft II as an AI research environment | DeepMind
Research DeepMind and Blizzard to release StarCraft II as an AI research environment Published 4 November 2016 Authors Oriol Vinyals Today at BlizzCon 2016 in Anaheim, California, we announced our collaboration with Blizzard Entertainment to open up StarCraft II to AI and Machine Learning researchers around the world. For almost 20 years, the StarCraft game series has been widely recognised as the
グーグルDeepMindã€æ¬¡ä¸–代人工知能技術「ディファレンシャブル・ニューラル・コンピューターã€ã‚’発表
ディープマインド（DeepMind）ã¯10月12æ—¥ã€æ¬¡ä¸–代ã®äººå·¥çŸ¥èƒ½æŠ€è¡“ã¨ã—ã¦ã€Œãƒ‡ã‚£ãƒ•ã‚¡ãƒ¬ãƒ³ã‚·ãƒ£ãƒ–ル・ニューラル・コンピューター（Differentiable Neural Computers：DNC)ã€ã‚’発表ã—ãŸã€‚ ディープマインドã¯äººå·¥çŸ¥èƒ½AlphaGoã«ã‚ˆã£ã¦å›²ç¢ä¸–ç•Œãƒãƒ£ãƒ³ãƒ”オンを打ã¡è² ã‹ã—ãŸã“ã¨ãŒè¨˜æ†¶ã«æ–°ã—ã„グーグルã®AIç ”ç©¶ãƒãƒ¼ãƒ 。近年ã§ã¯ã‚³ãƒ³ãƒ”ューター・ゲームã®ãƒ«ãƒ¼ãƒ«ã‚’自分ã§å¦ã³ã‚¯ãƒªã‚¢ã™ã‚‹ã€ŒDQN（Deep Q-Network）ã€ã‚’発表ã—ã¦ã„る。新AI技術ã®DNC（機械å¼è¨ˆç®—æ©Ÿã¨ã—ã¦å高ã„ãƒãƒ™ãƒƒã‚¸ã®ãƒ‡ã‚£ãƒ•ã‚¡ãƒ¬ãƒ³ã‚·ãƒ£ãƒ«ãƒ»ã‚¨ãƒ³ã‚¸ãƒ³ã‚’連想ã•ã›ã‚‹åå‰ï¼‰ã¯ã€DQNã®æŠ€è¡“ã‚’æ›´ã«é€²åŒ–ã•ã›ãŸã‚¢ãƒ¼ã‚テクãƒãƒ£ã‚’採用ã—ã€æ—¢å˜ãƒ‡ã‚£ãƒ¼ãƒ—ラーニングよりもå¦ç¿’精度や汎用性ãŒé«˜ã„AI技術ã®ã‚ˆã†ã 。
Engadget | Technology News & Reviews
How to watch Polaris Dawn astronauts attempt the first commercial spacewalk
1
リリースã€éšœå®³æƒ…å ±ãªã©ã®ã‚µãƒ¼ãƒ“スã®ãŠçŸ¥ã‚‰ã›
最新ã®äººæ°—エントリーã®é…ä¿¡
j次ã®ãƒ–ックマーク
kå‰ã®ãƒ–ックマーク
lã‚ã¨ã§èªã‚€
eコメント一覧を開ã
oページを開ã
Unity and DeepMind partner to advance AI research – Unity Blog
Engadget | Technology News & Reviews
「AlphaGoã€ã¨ã„ã†â€œç¥žâ€ã®å¼•é€€ã¨ã€äººé¡žæœ€å¼·ã®19æ³ãŒè¦‹ã›ãŸæ¶™ã®æ„味：ç¾åœ°ãƒ¬ãƒãƒ¼ãƒˆ
https://jp.techcrunch.com/2017/04/08/20170407google-deepmind-open-sources-sonnet-so-you-can-build-neural-networks-in-tensorflow-even-quicker/
グーグル傘下ã®DeepMindã€ã€Œäººé–“ã®ã‚ˆã†ã«è¨˜æ†¶ã™ã‚‹ã€æ¬¡ä¸–代AIを発表
äººé–“ã‚’ç ´ã£ãŸäººå·¥çŸ¥èƒ½ã‚’ã¤ãã£ãŸDeepMindã¨ã¯ä½•è€…ã‹ï¼Ÿ
{{#tags}}- {{label}}
{{/tags}}