Lead author Matthew Lai, a PhD researcher at UCL and Google DeepMind, said, “RoboBallet transforms industrial robotics into a ...

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of ...

Google DeepMind and Intrinsic developed AI that uses graph neural networks and reinforcement learning to automate multi-robot ...

Instead of retraining the LLM, the agent consults a dynamic store of past outcomes to make smarter decisions for new tasks.

Deep reinforcement learning leverages the learning capacity of deep neural networks to tackle problems that were too complex for classic RL techniques.

Robots that plan in seconds, adapt on the fly and work in sync. This AI could change how factories run. Read more!

Deep learning can be applied to different learning paradigms, LeCun added, including supervised learning, reinforcement learning, as well as unsupervised or self-supervised learning.

Through reinforcement learning that has a rigorous, formal system and that supports modularity, Trivedi's CAREER award opens a new path for complex artificial intelligence alongside neural networks, ...

Neural networks can better model high-level abstractions during the learning process, and combining the two techniques together has yielded state-of-the-art results across many problem areas.

Deep neural networks will move past their shortcomings without help from symbolic artificial intelligence, three pioneers of deep learning argue in a paper published in the July issue of the ...