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Waymo Teams Up With DeepMind; Lyft Shares Large-Scale Dataset

Synced Global AI Weekly July 28th

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Waymo and DeepMind Mimic Evolution to Develop A New, Better Way to Train Self-Driving AI
Alphabet’s autonomous driving and robotaxi company Waymo teamed up with fellow Alphabet company and AI specialist DeepMind to develop new training methods that would help make its training better and more efficient. DeepMind says in a blog postthat using PBT decreased by 24% false positives in a network that identifies and places boxes around pedestrians, bicyclists and motorcyclists spotted by a Waymo vehicle’s many sensors.
(TechCrunch) / (DeepMind)

Moving Autonomous Vehicles Forward, Together
Lyft shares a comprehensive, large-scale dataset featuring the raw sensor camera and LiDAR inputs as perceived by a fleet of multiple, high-end, autonomous vehicles in a bounded geographic area. This dataset also includes high quality, human-labelled 3D bounding boxes of traffic agents, an underlying HD spatial semantic map.

GM Cruise to Delay Commercial Launch of Self-Driving Cars to Beyond 2019
General Motors Co’s self-driving unit, Cruise, said on Wednesday it was delaying the commercial deployment of cars past its target of 2019 as more testing of the vehicles was required. Cruise Chief Executive Officer Dan Ammann said the company would expand testing in San Francisco.


Lookahead Optimizer: K Steps Forward, 1 Step Back
Researchers propose a new optimization algorithm, Lookahead, that is orthogonal to these previous approaches and iteratively updates two sets of weights. Intuitively, the algorithm chooses a search direction by \emph{looking ahead} at the sequence of “fast weights” generated by another optimizer.
(Vector Institute)

Introducing EvoGrad: A Lightweight Library for Gradient-Based Evolution
Uber AI researchers built EvoGrad, a Python library that gives researchers the ability to differentiate through expectations (and nested expectations) of random variables, which is key for estimating NES gradients. The idea is to enable more rapid exploration of variants of NES, similar to how TensorFlow enables deep learning research.
(Uber Engineering)

Learning Better Simulation Methods for Partial Differential Equations
Researchers explore a potential path for how ML can offer continued improvements in high-performance computing, both for solving PDEs and, more broadly, for solving hard computational problems in every area of science.
(Google AI)

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1 comment on “Waymo Teams Up With DeepMind; Lyft Shares Large-Scale Dataset

  1. Pingback: Waymo Teams Up With DeepMind; Lyft Shares Large-Scale Dataset – NewsChest Technology

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