Sidewalk Labs’ $900 Million Plan to Remake Toronto’s Waterfront Has Finally Been Unveiled.
It’s been almost two years since Alphabet subsidiary Sidewalk Labs announced its plan to build a high-tech neighborhood in Toronto, and the company is finally ready to put some major questions to rest. Earlier this week, Sidewalk Labs released a 1,500-page master document detailing an expansive vision to create “the most innovative district in the world” along Toronto’s Eastern Waterfront.
(Business Insider) /(Sidewalk Toronto Proposal)
Apple Acquires Self-Driving Startup Drive.ai on The Brink of Closure
Drive.ai, the autonomous vehicle tech startup once valued at US$200 million, has been acquired by Apple as it prepared to shut down after four years. Drive.ai was founded in 2015 by former graduate students working in Stanford University’s Artificial Intelligence Lab run by Andrew Ng, the renowned artificial intelligence expert.
Waymo Hires Engineers from Shuttered Robot Startup Anki to Work on Its Self-Driving Trucks
Waymo is hiring 13 engineers from shuttered robot toy startup Anki, including former Anki CEO Boris Sofman who will lead the Alphabet unit’s self-driving trucking project. Anki launched in 2013 with a smartphone-controlled toy racecar set called Anki Drive. It raised more than US$200 million in venture capital funding and sold 1.5 million robot units.
Argo AI Is Investing $15 Million Into A Self-Driving Car Research Center at CMU
Argo AI will invest US$15 million over five years to create a center for autonomous vehicle research at Carnegie Mellon University, one of the latest efforts by the Ford-backed company to accelerate the development of self-driving cars.
Uber Acquires Seattle Startup Mighty AI to Fuel Its Push into Self-Driving Cars
Uber has made its first acquisition of a Seattle startup, swooping up Mighty AI, which develops training data for computer vision models. The deal has been confirmed by both companies. Terms were not disclosed.
ORRB – OpenAI Remote Rendering Backend
OpenAI researchers present the OpenAI Remote Rendering Backend (ORRB), a system that allows fast and customizable rendering of robotics environments. It is based on the Unity3d game engine and interfaces with the MuJoCo physics simulation library. ORRB was designed with visual domain randomization in mind.
When to Trust Your Model: Model-Based Policy Optimization
Designing effective model-based reinforcement learning algorithms is difficult because the ease of data generation must be weighed against the bias of model-generated data. In this paper, researchers study the role of model usage in policy optimization both theoretically and empirically.
Regularized Hierarchical Policies for Compositional Transfer in Robotics
DeepMind researchers develop and investigate simple hierarchical inductive biases — in the form of structured policies — as a mechanism for knowledge transfer across tasks in reinforcement learning (RL). To leverage the power of these structured policies they design an RL algorithm that enables stable and fast learning.
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The Staggering Cost of Training SOTA AI Models
While it is exhilarating to see AI researchers pushing the performance of cutting-edge models to new heights, the costs of such processes are also rising at a dizzying rate. Synced took a look at cost estimates for training large AI models.
Facebook Model Pretrained on Billions of Instagram Hashtags Achieves SOTA Results on Top-1 ImageNet
Facebook is leveraging its massive social media data to improve its machine learning algorithms, and the results look excellent. In the paper Exploring the Limits of Weakly Supervised Pretraining, the Facebook AI research team show how they trained a large convolutional network to predict hashtags on some 3.5 billion social media images.
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