Category: Technology

Technical review of the newest machine intelligence research.

AI Technology

Stanford Open-Sources Neural Network Verification Project

A Stanford Intelligent Systems Laboratory (SISL) research group has announced it is open-sourcing its NeuralVerification.jl project, which helps verify deep neural networks’ training, robustness and safety results.

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AI China Technology

Alibaba Open-Sources Mars to Complement NumPy

Alibaba Cloud recently announced that it has open sourced Mars — its tensor-based framework for large-scale data computation — on Github. Mars can be regarded as “a parallel and distributed NumPy.” Mars can tile a large tensor into small chunks and describe the inner computation with a directed graph, enabling the running of parallel computation on a wide range of distributed environments, from a single machine to a cluster comprising thousands of machines.

AI Technology

White Hats Vs CAPTCHAs

Text-based CAPTCHA remain one of the most visible and commonly used mechanisms for website security. As a sort of online gatekeeper that distinguishes between humans and bots, the little solvable image fields have critical commercial applications in blocking automatic spam and preventing e-transfer fraud; and can also stop bots from spreading fraudulent information, etc.

AI Technology

Using Machine Learning to Synthesize Peptides

Synthesizing peptides — the chains of amino acids that conduct various functions within cells — has long been a research area of interest for scientists and engineers. There has however been little success thus far, as existing methods for synthesizing peptides have been prohibitively expensive and time-consuming.

AI Technology

AI Brush: New GAN Tool Paints Worlds

The digital painting tool GANpaint has gone viral on social media. The product of a team of high-profile researchers from MIT, IBM, Google, and the Chinese University of Hong Kong, GAPpaint allows anyone — even those with little knowledge of digital painting or photoshop — to “paint” incredibly complex and detailed photorealistic scenes.

AI Technology

Uber AI Beats Montezuma’s Revenge (Video Game)

Another video game has succumbed to the strength of artificial intelligence. Uber researchers announced yesterday that their AI has completely solved Atari’s Montezuma’s Revenge, a classic game that involves moving a character from one room to another while killing enemies and collecting jewels in a 16th century Aztec-like pyramid.

AI Technology

Global Minima Solution for Neural Networks?

New research from Carnegie Mellon University, Peking University and the Massachusetts Institute of Technology shows that global minima of deep neural networks can been achieved via gradient descent under certain conditions. The paper Gradient Descent Finds Global Minima of Deep Neural Networks was published November 12 on arXiv.

AI China Technology

New HotpotQA Dataset Has the Answers for Multi-Hop Queries

If you’ve ever wondered whether Dota 2 or League of Legends is the most popular multiplayer online battle arena game, or how long you’d need to spend on a treadmill to burn off that party size bag of chips you just ate, you know that you can probably find the answer by accessing a couple of relevant information sources and then applying what seems like a natural and straightforward reasoning process.

AI Technology

Facebook Open-Sources QNNPACK Kernel Library

Facebook announced today that it is open-sourcing QNNPACK, a high-performance kernel library optimized for mobile AI. The computing power of mobile devices is but a tiny fraction of that of data center servers. As such it is essential to find ways to optimize mobile devices’ hardware performance in order to run today’s compute-hungry AI applications.

AI Technology

Google Cloud TPUs Now Speak Julia

A new paper from Julia Computing Co-Founder and CTO Keno Fischer and Senior Research Engineer Elliot Saba introduces a method and implementation for offloading sections of Machine Learning models written in Julia programming language to TPUs.

AI Technology

Get a Grip! Berkeley Targets Dexterous Manipulation Using Deep RL

UC Berkeley researchers have published a paper demonstrating how Deep Reinforcement Learning can be used to control dexterous robot hands for complicated tasks. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations proposes a low-cost and high-efficiency control method that uses demonstration and simulation techniques to accelerate the learning process.