Large language models have moved out of the research lab and into engineers’ daily workflow. LLMs serve as reasoning engines ...

LFM2.5-230M proves that while 3-billion-parameter models like VibeThinker are solving advanced calculus, a ...

Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well? Contrary to expectations, a ...

Lium today emerged from stealth and announced the launch of its platform designed to help organizations make sense of complex, hard-to-use data. Lium takes datasets that are most challenging for AI ...

OpenAI published a new paper called "Monitoring Monitorability." It offers methods for detecting red flags in a model's reasoning. Those shouldn't be mistaken for silver bullet solutions, though. In ...

Is it possible for an AI to be trained just on data generated by another AI? It might sound like a harebrained idea. But it’s one that’s been around for quite some time — and as new, real data is ...

A new study by Google suggests that advanced reasoning models achieve high performance by simulating multi-agent-like debates involving diverse perspectives, personality traits, and domain expertise.

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

As PV projects move into more complex terrain, hybrid configurations and grid-supporting roles, Solargis sees higher-resolution meteorological data, physical modelling and quality-controlled AI as ...