This ensures learning effectiveness while minimizing overall transaction costs. By applying reinforcement learning algorithms to optimize model aggregation strategies, not only does it significantly ...
The self-play framework uses a 'Challenger' and a 'Reasoner' to create a self-improving loop, pushing the boundaries of AI ...
Having spent the last two years building generative AI (GenAI) products for finance, I've noticed that AI teams often struggle to filter useful feedback from users to improve AI responses.
Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. It can be used to teach a robot new tricks, for ...
AI coding tools are getting better fast. If you don’t work in code, it can be hard to notice how much things are changing, but GPT-5 and Gemini 2.5 have made a whole new set of developer tricks ...
It was not long ago that the world watched World Chess Champion Garry Kasparov lose a decisive match against a supercomputer. IBM’s Deep Blue embodied the state of the art in the late 1990s, when a ...
Ambuj Tewari receives funding from NSF and NIH. Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a ...