Computers are now excellent at recognizing images of human faces, cats and dogs — but struggle when it comes to detecting continuous actions, for example determining if a character in a video might be “dancing the tango.” Computers also fall short in detecting nuanced expressions of human emotions.
Benjamin Sanchez-Lengeling from Harvard University and Alán Aspuru-Guzik from the University of Toronto have successfully applied machine learning models to speed up the materials discovery process. Their paper Inverse molecular design using machine learning: Generative models for matter engineering was published July 27 in Science Vol. 361.
Neural networks can be notoriously difficult to debug, but a Google Brain research team believes it may have come up with a novel solution. A paper by Augustus Odena and Ian Goodfellow introduces Coverage-Guided Fuzzing (CGF) methods for neural networks. The team also announced an open source software library for CGF, TensorFuzz 1.
Since 2010, the annual ImageNet Large-Scale Visual Recognition Challenge has been the most widely recognized benchmark for testing image recognition algorithms. Tencent Machine Learning picks up the challenge with its new paper Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes.
At the annual Google Cloud Next conference which kicked off July 24 in San Francisco the company unveiled a series of AI-based product releases and enhancements for its analytics and machine learning tools, additional applications on G Suite, and new IoT products.
On July 10th, with German Chancellor Angela Merkel and Chinese Premier Li Keqiang looking on, Siemens AG signed a partnership agreement with Alibaba Cloud — the cloud-computing arm of Internet conglomerate Alibaba — to bring an Industrial Internet of Things (IIoT) upgrade to China’s manufacturing industry.
Over the past three months, criticism and protests have been mounting over Google’s participation in Project Maven, a Pentagon pilot program to build machine learning models to detect and categorize objects in drone footage provided by the US Department of Defense.
NIPS’ peer reviewer selection process came under question in the AI community last week, when a Reddit user who identified as a predoctoral student posted that they had been selected as a NIPS reviewer, and needed advice on how to properly write paper reviews…
Google I/O 2018 kicked off today with an uptempo keynote from CEO Sundar Pichai. The tech giant’s annual developer conference is always a platform for big announcements, and this was no exception, with Google gearing up for what promises to be an especially busy year.
The McKinsey Global Institute this month released the report “Notes From the AI Frontier Insights From Hundreds of Use Cases”. The 36-page discussion paper surveys cutting-edge machine learning algorithms, and discusses how they can be integrated or transformed into practical applications across 19 selected industries.
Leading machine learning conference International Conference on Learning Representations (ICLR) has named its best research papers of the last year: On the convergence of Adam and Beyond, Spherical CNNs, and Continuous Adaptation via Meta-learning in Nonstationary and Competitive Environments.
The Age of Discovery began in the 15th century, when Europeans built their first oceangoing vessels and set out to explore the world. Whether motivated by political, economic or cultural factors, human exploration has traditionally been driven by technological progress.
As Facebook struggles with fallout from the Cambridge Analytica scandal, its research arm today delivered a welcome bit of good news in deep learning. Research Engineer Dr. Yuxin Wu and Research Scientist Dr. Kaiming He proposed a new Group Normalization (GN) technique they say can accelerate deep neural network training with small batch sizes.
Founded in 2014 by international business lawyer Noory Bechor and machine learning guru Ilan Admon, LawGeex is a Tel Aviv-based legal tech startup focused on contract review. It closed US$7 million in Series A funding last March, principally from Indeed.com owner Recruit Holdings, Lool Ventures, and LionBird.
Google has announced the release of MusicVAE, a machine learning model that makes composing musical scores as easy as mixing paint on a palette. A breakthrough from Google Brain’s Magenta Project, MusicVAE generates and morphs melodies to output multi-instrumental passages optimized for expression, realism and smoothness which sound convincingly like human-composed music.
Microsoft researchers in the US and Asia sent a shockwave through the AI community today with their paper Achieving Human Parity on Automatic Chinese to English News Translation, which introduces a neural machine translation system they say equals the performance of human experts in Chinese-to-English translation.
I purchased a Tmall Genie X1 — Alibaba’s flagship smart speaker — at the discounted price of US$15 during China’s November 11 “Singles Day” shopping festival. I was given order number 560,000-ish, and received the product a month later. The speaker is regularly priced at US$79, about the same as its American counterpart Google Mini.
Paige.AI is a New York-based startup that fights cancer with AI. Launched last month as a spinoff from the Memorial Sloan Kettering Cancer Center (MSK) — the largest cancer research institute in the US — Paige.AI has exclusive access to MSK’s IP in the field of computational pathology as well as its dataset of 25 million pathology cancer images (“slides”).