7 Agentic AI Trends to Watch in 2026
The agentic AI field is moving from experimental prototypes to production-ready autonomous systems.
The agentic AI field is moving from experimental prototypes to production-ready autonomous systems.
NVIDIA founder and CEO Jensen Huang took the stage at the Fontainebleau Las Vegas today to open CES 2026, declaring that AI is scaling into every domain and every device. “Computing has been fundamentally reshaped as a result of accelerated computing, as a result of artificial intelligence,” Huang said. “What that means is some $10 …
When the creator of the world’s most advanced coding agent speaks, Silicon Valley doesn’t just listen — it takes notes. For the past week, the engineering community has been dissecting a thread on X from Boris Cherny, the creator and head of Claude Code at Anthropic. What began as a casual sharing of his personal …
The chip giant says Vera Rubin will sharply cut the cost of training and running AI models, strengthening the appeal of its integrated computing platform.
New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers redesigned AI systems to better resemble biological brains, some models produced brain-like activity without any training at all. This challenges today’s data-hungry approach to AI development. The work suggests smarter design could dramatically speed up …
Okay guys, I think we all know that bringing up training on Reddit is always a total fustercluck. It’s an art more than it is a science. To that end I’m proposing something slightly different… Put your steps, dataset image count and anything else you think is relevant in a quick, clear comment. If you …
The administration has made it clear that Nicolás Maduro’s capture was tied to Venezuela’s vast oil reserves. Much less certain is how US companies will actually access them—or if they even want to.
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Donald Trump says that Venezuela’s governance will remain in the hands of senior US officials until a “proper and judicious transition” can take place. The rest of the region is on notice.
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive optical networks, in particular, enable large-scale parallel computation through the use of passive structured phase masks and the propagation of light. However, one major challenge remains: systems trained in model-based simulations often fail to perform optimally in real experimental settings, …
Read more “Reinforcement learning accelerates model-free training of optical AI systems”