Boston Dynamics’ Robot Dog Is Now Available for Select Customers
Boston Dynamics has begun commercialization of its robodog Spot. The company released a video on Tuesday that shows Spot navigating challenging terrain, picking up construction objects, moving through bad weather, and picking itself up after a fall.
(CNN) / (Watch the video)
Boston Dynamics’ Atlas Can Now Do An Impressive Gymnastics Routine
Alongside the news that Boston Dynamics is letting robot dog Spot out of its laboratory for the first time, the company has released a new video of Atlas, a spectacular bipedal robot that’s previously been seen doing everything from parkour to backflips.
(The Verge) / (Watch the video)
Contributing Data to Deepfake Detection Research
In collaboration with Jigsaw, Google has announced the release of a large dataset of visual deepfakes they have produced. The data has been incorporated into the Technical University of Munich and the University Federico II of Naples’ new FaceForensics benchmark, an effort that Google co-sponsors.
High Fidelity Speech Synthesis With Adversarial Networks
Researchers have introduced GAN-TTS, a Generative Adversarial Network for Text-to-Speech. The architecture is composed of a conditional feed-forward generator producing raw speech audio, and an ensemble of discriminators which operate on random windows of different sizes.
(Imperial College London & DeepMind)
Rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch
Rlpyt is designed as a high-throughput code base for small- to medium-scale research in deep RL. This blog post briefly introduces its features and relation to prior work. Notably, rlpyt reproduces the recent record-setting results in the Atari domain from “R2D2″–except without requiring distributed compute infrastructure to gather the 10’s of billions of frames of gameplay needed.
(Berkeley Artificial Intelligence Research)
Automation via Reinforcement Learning
What does it mean to automate a task with reinforcement learning? The basic process can be decomposed into two steps: first reduce the problem to RL by writing it as an MDP or POMDP, and then solve for the optimal policy of the MDP or POMDP2. The optimal policy then allows us to fully automate the task, completing it any number of times with no further human effort.
(Jacob Buckman from Johns Hopkins)
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Reproducibility Challenges in Machine Learning for Health
A team of researchers from MIT, University of Toronto, New York University, and Evidation Health have proposed a number of “recommendations to data providers, academic publishers, and the ML4H research community in order to promote reproducible research moving forward” in their new paper Reproducibility in Machine Learning for Health.
Alibaba’s New AI Chip Can Process Nearly 80K Images Per Second
The 12-nm Hanguang 800 contains 17 billion transistors. Given an inference image classification benchmark test on ResNet-50, Hanguang 800’s peak performance is 78,563 images per second (IPS). Zhang says the Hanguang 800 is 15 times more powerful than the NVIDIA T4 GPU, and 46 times more powerful than the NVIDIA P4 GPU. The chip’s peak efficiency is 500 IPS/W.
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