Synced Global AI Weekly | 2018.9.8—9.14

2018-09-18 15:47:00
刘大牛
转自文章
230

Synceds Favourite Tech News of This Week

Tencent Open-Sources Its Massive Multi-Labeled Image Dataset

Tencent AI Lab has announced that it will open source its multi-label image dataset ML-Images and deep residual network ResNet-101 by the end of September. ML-Images contains 18 million images and more than 11,000 common object categories; while ResNet-101 has reached the highest precision level in the industry.

(Synced)


AMC: AutoML for Model Compression and Acceleration on Mobile Devices 

Researchers from MIT, Google, and Xian Jiaotong University recently published a paper proposing AutoML for Model Compression (AMC), which leverages reinforcement learning to shorten model compression processing time and improve results.

(MIT & Google)


Is It Real or Is It Gibson? A New Virtual Environment for AI Training

Researchers from Stanford University and University of California Berkeley have introduced Gibson Environment, a real-world-based virtual environment for training and testing active perception agents.

(Synced)


ECCV 2018 Announces Best Papers

Taking top honours in the Best Paper category is Implicit 3D Orientation Learning for 6D Object Detection from RGB Images from researchers at the German Aerospace Center andTechnical University of Munich.  

(Synced)


Technology

Preserving Outputs Precisely while Adaptively Rescaling Targets

"PopArt: a single agent that can play 57 diverse Atari video games, with above-human median performance across the set"

(DeepMind)


Finding And Fixing Software Bugs Automatically with SapFix and Sapienz

Debugging code is drudgery. But SapFix, a new AI hybrid tool created by Facebook engineers, can significantly reduce the amount of time engineers spend on debugging, while also speeding up the process of rolling out new software. SapFix can automatically generate fixes for specific bugs, and then propose them to engineers for approval and deployment to production.

(Facebook)


The What-If Tool: Code-Free Probing of Machine Learning Models

"Today, we are launching the What-If Tool, a new feature of the open-source Tensor Board web application, which let users analyze and better understand an ML model without writing code. We look forward to people using, and contributing to, the What-If Tool."

(Google AI)


You May Also Like

AI Chip Duel: Apple A12 Bionic VS Huawei Kirin 980

Apple has unveiled the latest iteration of its smartphone chip: the A12 Bionic SoC (system-on-a-chip). The company made the announcement yesterday at its annual product showcase event in Cupertino, California, hailing the A12 as the industry’s first ever 7nm chip (the smallest current transistor scale). It will be embedded in Apples new XR, XS, and XS Max iPhones.

(Synced


Jeff Deans 1990 Senior Thesis Is Better Than Yours

Google AI lead Jeff Dean recently posted a link to his 1990 senior thesis on Twitter, which set off a wave of nostalgia for the early days of machine learning in the AI community. The thesis may be almost 30 years old and only eight pages long, but the paper does a remarkable job of explaining the methods behind neural network training and the modern development of AI.

( Synced )


Global AI Events

17–18 Sep

ICHRI

Rome,  Italy.

17–18 Sep

AI Innovation Summit.

San Francisco,  USA.

17–19 Sep

AIPR 2018

 Lodz,  Poland.

18–20 Sept

IJCCI

Seville,  Spain.

18–20 Sep

AI Summit

San Francisco,  USA.

19–21 Sep

CHIRA

Seville,  Spain

NewsLetter
发表评论
评论通过审核后显示。
文章分类
联系我们
联系人: 透明七彩巨人
Email: weok168@gmail.com