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.
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.
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.
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”).