Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...

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

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial intelligence (AI) to address a ...

Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...

A Fortune 500 retailer cut robot idle time by 15%, replenishment cycles by 12%, and costs by 8% in two months. Most ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

Most current autonomous driving systems rely on single-agent deep learning models or end-to-end neural networks. While ...

V3.2, a family of open-source reasoning and agentic AI models. The high compute version, DeepSeek-V3.2-Speciale, performs ...

Connect X9 (1.6 TB/s bandwidth), Bluefield 4 DPU (offloads storage/security), NVLink 6 switch (scales 72 GPUs as one), Spectrum X Ethernet Photonix (512 lanes, 200 Gbit optics for AI factories).

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Researchers in China have reportedly developed a smart electromagnetic surface capable of converting ambient electromagnetic waves into electrical power. This development represents an integration of ...