Gathering Human Feedback
RL-Teacher is an open-source implementation of our interface to train AIs via occasional human feedback rather than hand-crafted reward functions. The underlying technique was developed as a step towards safe AI systems, but also applies to reinforcement learning problems with rewards that are hard to specify.
This simulated
Gathering Human Feedback
RL-Teacher is an open-source implementation of our interface to train AIs via occasional human feedback rather than hand-crafted reward functions. The underlying technique was developed as a step towards safe AI systems, but also applies to reinforcement learning problems with rewards that are hard to specify.
This simulated
Automatic image retouching on your phone
System can apply a range of styles in real-time, so that the viewfinder displays the enhanced image.
AI and Neuroscience: A virtuous circle
Recent progress in AI has been remarkable.Artificial systems now outperform expert humans at Atari video games, the ancient board game Go, and high-stakes matches of heads-up poker. They can also produce handwriting and speech indistinguishable from th…
Musk vs Zuck vs Trump
Who knows less about AI and wants more than they should. Recently a nice
little “row” emerged over who can beat the other at AI know-how in order to
have or have-not get politicians involved in AI regulation.
DeepMind Makes AI Walk & Run (Serious & Funny)
The agility and flexibility of a monkey swinging through the trees or a
football player dodging opponents and scoring a goal can be breathtaking.
Mastering this kind of sophisticated motor control is a hallmark of
physical intelligence, and is a crucial part of AI research.
Better Exploration with Parameter Noise
We’ve found that adding adaptive noise to the parameters of reinforcement learning algorithms frequently boosts performance. This exploration method is simple to implement and very rarely decreases performance, so it’s worth trying on any problem.
| Action Space Noise | Parameter Space Noise |
Parameter