Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

Rebecca Qian is the Co-Founder and CTO of Patronus AI, with nearly a decade of experience building production machine ...

AI"s inability to continually learn remains one of the biggest problems standing in the way to truly general purpose models.

HybridLeg robots Olaf and Snogie use impact-safe design and self-recovery to enable scalable, real-world hardware ...

Q/C Technologies, Inc. (Nasdaq: QCLS) (“Q/C Technologies” or “the Company”), a pioneer of quantum-class computing at the speed of light, today announced the appointment of Chelsea Voss to its Board of ...

Hosted by the Wu Tsai Neurosciences Institute, professor Dani Bassett’s talk explored how neurological approaches to human behavior can allow us to modify our real-world information systems.

Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

Top AI graduate programs at schools like Carnegie Mellon and Stanford are feeding a field where salaries average over $150,000—with job growth outpacing the broader market.

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...