机器之心海外团队作者

Synced Global AI Weekly | 2018.9.1—9.7

Collaborations of This Week

Huawei Guns for Nvidia With Potential Microsoft AI Chip Deal in China

Microsoft and Huawei Technologies are discussing the possibility of the U.S. company using Huawei’s newly developed artificial intelligence chips for data centers in China, people familiar with the matter said.

(The Information)


Baidu Cloud Collaborates with Intel AI to Advance Financial Services, Shipping and Video Processing

At the Baidu 2018 ABC Summit in Shanghai, Baidu and Intel outlined new artificial intelligence collaborations showcasing applications ranging from financial services and shipping to video content detection.

(Intel)


IBM collaborated with the NYPD on an AI system that can search for people by race

Three months after Amazon provided facial recognition technology to local law enforcement, a new report shows that IBM collaborated with the NYPD to develop a system that allowed officials to search for people by skin color, hair color, gender, age, and various facial features.

(VentureBeat)


Technology

Making It Easier to Discover Datasets

"To enable easy access to this data, we launched Dataset Search, so that scientists, data journalists, data geeks, or anyone else can find the data required for their work and their stories, or simply to satisfy their intellectual curiosity."

(Google AI)


Detecting Depression with Audio/Text Sequence Modeling of Interviews

We utilized data of 142 individuals undergoing depression screening, and modeled the interactions with audio and text features in a Long-Short Term Memory (LSTM) neural network model to detect depression.

(MIT CSAIL)


NERSC, Intel, Cray Harness the Power of Deep Learning to Better Understand the Universe 

A Big Data Center collaboration between computational scientists at Berkeley Lab's NERSC and engineers at Intel and Cray has yielded another first in the quest to apply deep learning to data-intensive science: CosmoFlow, the first large-scale science application to use the TensorFlow framework on a CPU-based high performance computing platform with synchronous training.

(NERSC)


You May Also Like

OpenAI's Long Pursuit of Dota 2 Mastery

OpenAI’s first Dota 2 effort was a scripted computer with hard-coded rules. It could improve its tactics only by acquiring additional expert input: How to buy items? What was the last hit? How do we deny? How do we best take towers?

(Synced)


NIPS Tickets Sell Out in Less Than 12 Minutes

Registration opened at 8:00 a.m. PDT today for December’s NIPS 2018 (Conference on Neural Information Processing Systems) in Montreal. The early birds were the fortunate ones this year — as tickets for the main conference were all snapped up less than a dozen minutes later.

(Synced)


Global AI Events

8–14 Sep
ECCV
Munich, Germany.
10–11 Sep
Robots and Deep Learning
Singapore
11–12 Sep
Big Data Innovation Summit
Boston, USA
13–16 Sep
LOD 2018
Volterra, Italy
11–13 Sep
AI & Machine Learning Summit.
Sydney, Australia
11–14 Sep
O’Reilly Strata Data Conference New York
New York, USA
17–18 Sep
ICHRI
Rome, Italy
NewsLetter
相关数据
英特尔机构

英特尔是计算创新领域的全球领先厂商,致力于拓展科技疆界,让最精彩体验成为可能。英特尔创始于1968年,已拥有近半个世纪产品创新和引领市场的经验。英特尔1971年推出了世界上第一个微处理器,后来又促进了计算机和互联网的革命,改变了整个世界的进程。如今,英特尔正转型成为一家数据公司,制定了清晰的数据战略,凭借云和数据中心、物联网、存储、FPGA以及5G构成的增长良性循环,提供独到价值,驱动日益发展的智能互联世界。英特尔专注于技术创新,同时也积极支持中国的自主创新,与产业伙伴携手推动智能互联的发展。基于明确的数据战略和智能互联全栈实力,英特尔瞄准人工智能、无人驾驶、5G、精准医疗、体育等关键领域,与中国深度合作。面向未来,英特尔致力于做中国高价值合作伙伴,在新科技、新经济、新消费三个方面,着力驱动产业协同创新,为实体经济增值,促进消费升级。

https://www.intel.com/content/www/us/en/company-overview/company-overview.html
相关技术
机器学习技术

机器学习是人工智能的一个分支,是一门多领域交叉学科,涉及概率论、统计学、逼近论、凸分析、计算复杂性理论等多门学科。机器学习理论主要是设计和分析一些让计算机可以自动“学习”的算法。因为学习算法中涉及了大量的统计学理论,机器学习与推断统计学联系尤为密切,也被称为统计学习理论。算法设计方面,机器学习理论关注可以实现的,行之有效的学习算法。

TensorFlow技术

TensorFlow是一个开源软件库,用于各种感知和语言理解任务的机器学习。目前被50个团队用于研究和生产许多Google商业产品,如语音识别、Gmail、Google 相册和搜索,其中许多产品曾使用过其前任软件DistBelief。

张量技术

张量是一个可用来表示在一些矢量、标量和其他张量之间的线性关系的多线性函数,这些线性关系的基本例子有内积、外积、线性映射以及笛卡儿积。其坐标在 维空间内,有 个分量的一种量,其中每个分量都是坐标的函数,而在坐标变换时,这些分量也依照某些规则作线性变换。称为该张量的秩或阶(与矩阵的秩和阶均无关系)。 在数学里,张量是一种几何实体,或者说广义上的“数量”。张量概念包括标量、矢量和线性算子。张量可以用坐标系统来表达,记作标量的数组,但它是定义为“不依赖于参照系的选择的”。张量在物理和工程学中很重要。例如在扩散张量成像中,表达器官对于水的在各个方向的微分透性的张量可以用来产生大脑的扫描图。工程上最重要的例子可能就是应力张量和应变张量了,它们都是二阶张量,对于一般线性材料他们之间的关系由一个四阶弹性张量来决定。

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