The reinforcement gap — or why some AI skills improve faster than others

AI tasks that work well with reinforcement learning are getting better fast — and threatening to leave the rest of the industry behind.
Communications of the ACM

Shields for Safe Reinforcement Learning

Evaluating the advantages and potential drawbacks of shielding as a method for safe RL. Bettina Könighofer is an assistant ...

AI Agents, LLMs & Economic Growth : Karpathy’s Surprising Predictions

Discover Andrej Karpathy's insights on AI agents, LLMs, and economic growth. Insights on memory, education, and economic ...

Nvidia researchers boost LLMs reasoning skills by getting them to 'think' during pre-training

By teaching models to reason during foundational training, the verifier-free method aims to reduce logical errors and boost ...

Inside Ring-1T: Ant engineers solve reinforcement learning bottlenecks at trillion scale

Ant Group, an affiliate of Alibaba, released Ring-1T which it says is the first trillion parameter open-source model.
Nature

Reinforcement learning improves behaviour from evaluative feedback

Reinforcement-learning algorithms 1,2 are inspired by our understanding of decision making in humans and other animals in which learning is supervised through the use of reward signals in response to ...

The challenge of creating brains in a lab

They’re growing miniature 3D brains from stem cells. These aren’t your fictional mad scientists’ brains in a vat; they’re ...

This Startup Wants to Spark a US DeepSeek Moment

With the US falling behind on open source models, one startup has a bold idea for democratizing AI: let anyone run ...
Forbes

Artificial Intelligence: What Is Reinforcement Learning - A Simple Explanation & Practical Examples

At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the ...