Achieving high reliability in AI systems—such as autonomous vehicles that stay on course even in snowstorms or medical AI ...
The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
Artificial reinforcement learning is just one lens to evaluate organizations. However, this thought experiment taught me that ...
Google has released TranslateGemma, a set of open translation models based on the Gemma 3 architecture, offering 4B, 12B, and ...
One of the most pressing challenges to the continued deployment of nuclear energy systems is in the ultimate management and disposition of discharged fuel assemblies. While reprocessing and recovery ...
Researchers have developed a new artificial intelligence approach that exposes critical weaknesses in multi-agent reinforcement learning systems, enabling stronger coordinated attacks with broad ...
As organizations plan for 2026, a clear structural shift is emerging in how technical talent is valued and deployed. Amid this shift, Interview Kickstart has introduced an advanced machine learning ...
Abstract: This paper proposes a hybrid actor-critic framework for the optimal operation of a phase-changing soft open point (PCSOP) in an unbalanced distribution network. The framework combines ...
Researchers at Meta, the University of Chicago, and UC Berkeley have developed a new framework that addresses the high costs, infrastructure complexity, and unreliable feedback associated with using ...
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