LLM
4 published articles
Artificial Intelligence
Ai2's EMO makes modular AI emerge from data, not human rules
Ai2's new MoE model, EMO, uses a novel training method that lets expert modules emerge naturally from data, enabling selective expert use with minimal performance loss. The model matches standard MoE performance on benchmarks while offering vastly improved modularity.
2026-07-07
Media & AI
AI-written news saves money and loses readers. The math doesn't work.
News outlets have embraced AI to churn out vast volumes of content, but early returns point to diminishing quality, reader distrust, and a looming feedback loop where AI text pollutes the data future models will train on.
2026-07-06
Artificial Intelligence
Microsoft's Phi-4 Model Redefines Efficiency in Breakthrough Research
Microsoft's Phi-4 model achieves state-of-the-art efficiency, matching larger models in reasoning tasks with significantly fewer parameters. Published on May 15, 2025, the research paper reexamines assumptions about scaling laws in AI.
2026-07-03
Artificial Intelligence
DeepSeek's new model makes efficiency the AI arms race front line
DeepSeek has released a new LLM that sharpens its competition with major AI labs by betting on efficiency over brute force. The model aims to offer strong performance with optimized resource usage, reflecting a broader industry pivot toward cost-effective AI.
2026-06-30