AI lab DeepMind becomes profitable and bolsters relationship with Google
Reinforcement learning improves game testing, AI team finds
Amazon’s Astro robot: A feat of science or a successful product?
Nvidia, University of Toronto are making robotics research available to small firms
A developer’s guide to machine learning security
Abductive inference is a major blind spot for AI
Boston Dynamics’ Spot robot is securing its position in a niche market
Google’s new deep learning system can give a boost to radiologists
Computer vision and deep learning provide new ways to detect cyber threats
What Databricks’ $1.6B funding round means for the enterprise AI market
Demystifying deep reinforcement learning
Unsupervised learning can detect unknown adversarial attacks
Inside Boston Dynamics’ project to create humanoid robots
The dos and don’ts of machine learning research
What AI researchers can learn from the self-assembling brain
What to expect from OpenAI’s Codex API
What is federated learning?
To create AGI, we need a new theory of intelligence
Is DeepMind’s new reinforcement learning system a step toward general AI?
Can you teach AI common sense?
Aurora’s SPAC merger comes amid self-driving car delays
OpenAI Codex shows the limits of large language models
Natural language understanding tough for neural networks
What OpenAI and GitHub’s ‘AI pair programmer’ means for the software industry
The future of deep learning, according to its pioneers
Tesla AI chief explains why self-driving cars don’t need lidar
Overview of deep learning architectures computers use to detect objects
Evolution, rewards, and artificial intelligence
What Google’s AI-designed chip tells us about the nature of intelligence
What Waabi’s launch means for the self-driving car industry
DeepMind says reinforcement learning is ‘enough’ to reach general AI
Machine learning security needs new perspectives and incentives
A simple model of the brain provides new directions for AI research
Microsoft, GPT-3, and the future of OpenAI
Intel’s image-enhancing AI is a step forward for photorealistic game engines
IBM’s Project CodeNet will test how far you can push AI to write software
Understanding dimensionality reduction in machine learning models
Understanding the differences between biological and computer vision
