Open Data

Govtech 創業者シリーズ: OpenGov の CEO に送信パフォーマンス管理クラウド|Govtech Founder Series: OpenGov’s CEO Sends Performance Management to the Cloud

by opendata • 2017年4月5日

オープンデータ関連のニュースです。

• Govtech 創業者シリーズ: OpenGov の CEO に送信パフォーマンス管理クラウド|Govtech Founder Series: OpenGov’s CEO Sends Performance Management to the Cloud

日本語

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Welcome to the second installment of the Govtech Founder Series. This interview is with Zac Bookman, the CEO and co-founder of OpenGov. OpenGov is a leading gov tech company, with close to 1,500 public agency customers. Additionally, it has attracted significant investment from some of the world’s best venture capitalists. Zac is one of my favorite CEOs in the space and has great insight into what it takes to be an effective leader inside a fast-growing company. Enjoy. The interview has been condensed for clarity. Nick: How did you get into entrepreneurship, specifically govtech? Zac: I grew up near “government” in Maryland. My father worked at the National Academy of Sciences in Washington. I was an entrepreneur from a young age, but growing up in D.C.
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Open Data

キネマ システムは、産業用ロボット世界初の 深い学習 3 D ビジョン システムを発表します。|Kinema Systems Announces World’s First Deep Learning 3D Vision System for Industrial Robots

by opendata • 2017年4月5日

オープンデータ関連のニュースです。

• キネマ システムは、産業用ロボット世界初の 深い学習 3 D ビジョン システムを発表します。|Kinema Systems Announces World’s First Deep Learning 3D Vision System for Industrial Robots

日本語

世界の商業の大きい部分をパレット上に配置のボックスに移動します。物流センターの倉庫内のボックスをデパレタイズ工場、人口統計と製品ミックスの増加を変更すると難しくなっている困難な作業です。キネマのピックは、世界の最初深い学習 3 D ビジョン システム産業用ロボットです。混合 SKU のシングル SKU パレット depalletization を対応しています。 このスマートのニュース リリースでは、マルチ メディアを備えています。ここで、完全なリリースを表示: http://www.businesswire.com/news/home/20170404005626/en/ キネマ ピック KS1000、複雑なパレットのボックスを見つけることの深い学習・ 3 D ビジョンの高解像度 3次元/2次元センサーを統合します。
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English

A large part of the world’s commerce moves in boxes arranged on pallets. Depalletizing boxes in warehouses, distribution centers and factories is a difficult task that has become more challenging with changing demographics and an increase in product mix. Kinema Pick is the world’s first Deep Learning 3D Vision system for industrial robots. It addresses the depalletization of both mixed SKU and single SKU pallets. This Smart News Release features multimedia. View the full release here: http://www.businesswire.com/news/home/20170404005626/en/ Kinema Pick integrates the KS1000, a high-resolution 3D/2D sensor with deep-learning and 3D Vision to find and locate boxes on complex pallets.
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Open Data

NVIDIA GPU 技術会議を正式に発表|NVIDIA GPU Technology Conference Officially Announced

by opendata • 2017年4月5日

オープンデータ関連のニュースです。

• NVIDIA GPU 技術会議を正式に発表|NVIDIA GPU Technology Conference Officially Announced

日本語

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With the conference being over a month away, NVIDIA sent out a press release announcing the conference. The conference starts on Monday, May 8th, and lasts until Thursday, May 11th. This year, NVIDIA reshuffled the conference format in a bid to ensure continuous coverage of the conference. What used to be opening keynote with Jensen Huang, co-founder and the CEO is now being shifted to the penultimate day. The expectations for the conference are quite big, with the focus on A.I. and deep learning, virtual reality and self driving vehicles. We will cover the conference extensively. NVIDIA (NASDAQ: NVDA), a world leader in AI computing technology, will host its eighth annual GPU Technology Conference (GTC) on May 8-11, at the San Jose McEnery Convention Center.
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Open Data

創がワンショット学習に役立つことがあります。|One-shot learning may help with drug design

by opendata • 2017年4月5日

オープンデータ関連のニュースです。

• 創がワンショット学習に役立つことがあります。|One-shot learning may help with drug design

日本語

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Researchers in the lab of Vijay Pande, PhD, have developed an algorithm to help make predictions about the properties of molecules. This algorithm could be beneficial in the early stages of drug design when a researcher is trying to choose what molecule to study from a group of molecules that each show some potential. Customarily, researchers need to train algorithms using thousands to trillions of data points. This new algorithm was able to produce fairly accurate predictions about toxicity and side effects of molecules using fewer than 30 data points. The study was published this week in ACS Central Science. The researchers describe this type of deep learning, called one-shot learning, as analogous to how toddlers can identify giraffes after seeing a picture of a giraffe only once.
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Open Data

マイクロソフトはバージョン 2.0 のもたらす多くの新しい特徴に 深い学習 ツールキットを更新します。|Microsoft updates Deep Learning Toolkit to version 2.0 bringing lots of new features

by opendata • 2017年4月5日

オープンデータ関連のニュースです。

• マイクロソフトはバージョン 2.0 のもたらす多くの新しい特徴に 深い学習 ツールキットを更新します。|Microsoft updates Deep Learning Toolkit to version 2.0 bringing lots of new features

日本語

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English

Microsoft is bringing its Cognitive Toolkit version 2.0 out of beta today and should be helping out a ton of companies who depend on tools to deploy deep learning at scale. The Cognitive Toolkit or CNTK to some is a deep learning tool that helps companies speed up the process of image and speech recognition. Thanks to today’s update, CNTK can now be used by companies either on-premises or in the cloud combined with Azure GPUs. Cognitive Toolkit is being used extensively by a wide variety of Microsoft products, by companies worldwide with a need to deploy deep learning at scale, and by students interested in the very latest algorithms and techniques. The latest version of the toolkit is available on GitHub via an open source license.
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Open Data

LinkedIn: 機械学習 酸素のようなものですが、人間の要素はいつでもすぐになくなっていません。|LinkedIn: Machine learning is like oxygen, but the human element is not going away anytime soon

by opendata • 2017年4月4日

オープンデータ関連のニュースです。

• LinkedIn: 機械学習 酸素のようなものですが、人間の要素はいつでもすぐになくなっていません。|LinkedIn: Machine learning is like oxygen, but the human element is not going away anytime soon

日本語

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English

Recently LinkedIn revamped its newsfeed and rolled out a new feature called Trending Storylines. Coupled with the acquisition by Microsoft, this is a move with far-reaching implications. Social media and their newsfeeds have come to play a key role in our lives. To a large extent, they shape our perceptions, the way we get our information and connect with each other and the world at large. LinkedIn is a professional network, but its size and ambition mean that its newsfeed can be hugely important in its own way. Leveraging data to offer its users a relevant experience is at the core of LinkedIn’s operation. As Igor Perisic, LinkedIn’s CDO, VP of Engineering and head of machine learning (ML) puts it, “machine learning is like oxygen for LinkedIn’s organism.
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Open Data

AI は日食 Hadoop、Forrester を言うは、ので、Cloudera は機械学習プラットフォームとして IPO のファイル|AI Will Eclipse Hadoop, Says Forrester, So Cloudera Files For IPO As A Machine Learning Platform

by opendata • 2017年4月4日

オープンデータ関連のニュースです。

• AI は日食 Hadoop、Forrester を言うは、ので、Cloudera は機械学習プラットフォームとして IPO のファイル|AI Will Eclipse Hadoop, Says Forrester, So Cloudera Files For IPO As A Machine Learning Platform

日本語

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When you start a revolution, you need to go public before the next revolution starts. Hadoop used to be the “revolutionary” technology behind the “big data” revolution but it has now been buried deep by deep learning, at least as far as the tech hype is concerned. One Hadoop distribution vendor, Hortonworks, sensed the passing of the “revolution” baton early, and went public in 2014.
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Open Data

BriefCam は、NVIDIA GPU 搭載のインテリジェント ビデオ解析ソリューションを提供します。|BriefCam Delivers NVIDIA GPU-powered Intelligent Video Analytics Solutions

by opendata • 2017年4月4日

オープンデータ関連のニュースです。

• BriefCam は、NVIDIA GPU 搭載のインテリジェント ビデオ解析ソリューションを提供します。|BriefCam Delivers NVIDIA GPU-powered Intelligent Video Analytics Solutions

日本語

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LAS VEGAS, ISC West, April 3, 2017 /PRNewswire/ — BriefCam®, the Video Synopsis® company, today announced that it is bringing video analytics to the next level by delivering solutions powered by NVIDIA GPUs and deep learning. BriefCam’s Syndex Pro, running on NVIDIA technology, will accelerate video processing performance and enable richer metadata extraction at a reduced cost. “We’re committed to delivering value from video and taking a giant leap with NVIDIA to provide the industry with video analytics solutions that will perform faster, deliver better results and cost less,” said Tom Edlund, Chief Technology Officer of BriefCam.
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Open Data

誰かは最後に以上の悪夢を作成する 深い学習 技術をハイジャック|Someone Finally Hijacked Deep Learning Tech to Create More Than Nightmares

by opendata • 2017年4月4日

オープンデータ関連のニュースです。

• 誰かは最後に以上の悪夢を作成する 深い学習 技術をハイジャック|Someone Finally Hijacked Deep Learning Tech to Create More Than Nightmares

日本語

Google は、その深い夢ニューラル ネットワークと技術が作成された悪夢を誘発するイメージで私たちの脳を液化、ほぼ 2 年が経ちました。今、カリフォルニア大学バークレー校からのチームは逆のことのようなものが、「一種の」に重点を置いて バークレー校のチームは、印象派の絵画を写実的な画像に変換できる CycleGAN と呼ばれる、深い学習ソフトウェアの新しい型を構築しました。いくつかの調整とツールがシマウマ、オレンジにリンゴと夏に冬馬を回転することもできます。なぜこれまでたいトリックのこれらの種類を行う?誰にもわかりません。非常には、少なくとも、CycleGAN のコンセプトの興味深い証拠であります。 他の深い学習技術のようなバークレー ソフトウェアは、一般的なイメージの 2 つのセット間のリレーションシップを描画することによって動作します。
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It’s been almost two years since Google liquefied our brains with its Deep Dream neural network and the nightmare-inducing images the technology created. But now, a team from the University of California, Berkeley is sort of doing the opposite—emphasis on “sort of.” The Berkeley team built a new type of deep learning software, dubbed CycleGAN, that can convert impressionist paintings into photorealistic images. With a few tweaks, the tool can also turn horses into zebras, apples into oranges, and winter into summer. Why would you ever want to do these kinds of tricks? Who knows. At the very least, CycleGAN is an interesting proof of concept. Like other deep learning techniques, the Berkeley software works by drawing relationships between two sets of common images.
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Open Data

ORNL の研究量子、HPC、深い 学習ニューラルネットワークコンピューティング|ORNL Studies Quantum, HPC, and Neuromorphic Computing for Deep Learning

by opendata • 2017年4月4日

オープンデータ関連のニュースです。

• ORNL の研究量子、HPC、深い 学習ニューラルネットワークコンピューティング|ORNL Studies Quantum, HPC, and Neuromorphic Computing for Deep Learning

日本語

深い学習は、多くの機会と課題を提示します。トレーニングは、後者の良い例-ヶ月以上かかることができます。オークリッジ国立研究所主導のチームは、量子コンピューティング、伝統的な HPC とニューラルネットワークコンピューティングは、深い学習と彼らの初期の作品を改善するためにされる可能性がありますがそれぞれが単独で、あるいはとき他の人とコンサートで使用される活用できる強みを示唆する方法を勉強しています。 仕事の論文 (A 研究の複雑な深い学習ネットワーク、高性能、ニューロ、量子コンピューター) で、arxiv.org に投稿、短い記事にもまとめて (コンピューター-量子深い) オークリッジ国立研究所の web サイト。
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Deep learning presents many opportunities and challenges. Training is a good example of the latter – it can take months or longer. An Oak Ridge National Laboratory-led team is studying how quantum computing, traditional HPC, and neuromorphic computing might be used to improve deep learning and their early work suggests each has strengths that could be leveraged independently or when used in concert with the others. The work is presented in a paper (A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers), posted on arxiv.org and also summarized in a short article (Computing – Quantum deep) on the ORNL web site.
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