In this modern era, Reinforcement Learning (RL) has evolved from theoretical research to a transformative force driving significant changes in industrial applications. Debu Sinha, a recognized ...

In today's fractured online landscape, it is harder than ever to identify harmful actors such as trolls and misinformation ...

Alibaba’s analysis found that training with about 64,000 Google search queries would cost roughly $586.70 via SerpAPI. In ...

Alibaba’s ZeroSearch trains large language models to beat Google Search and slash API costs by 88%, redefining how AI learns ...

AI visionaries predict an 'Era of Experience' where AI learns autonomously, and it will have important implications for ...

In today’s digital transformation era, the growing demand for scalable, intelligent, and cost-efficient data storage has accelerated the shift toward artificial intelligence-enhanced architectures.

Researchers from Nanjing University and Carnegie Mellon University have introduced an AI approach that improves how machines learn from past data—a process known as offline reinforcement learning.

Self-motivated AI agents expands the boundaries of what AI can achieve and provides more efficient, adaptive, and intelligent ...

Y Combinator-backed startup Theta Software, which builds self-learning and real-time adaptation for AI agents, has recently ...

If there's one thing that characterizes driving in any major city, it's the constant stop-and-go as traffic lights change and ...