MoE's Dirty Secret Is Load Balancing
Every frontier lab now ships a sparse Mixture-of-Experts model. Google's Switch Transformer started the trend. DeepSeek-V3 proved it could scale....
Clear, practical breakdowns of the AI papers and ideas that matter: agents, reasoning, safety, multi-agent systems. Written for practitioners, not academics.
Every frontier lab now ships a sparse Mixture-of-Experts model. Google's Switch Transformer started the trend. DeepSeek-V3 proved it could scale....
Stanford researchers found LLM teams fail to match their expert agents by up to 37.6%. Independent multi-agent systems amplify errors 17.2 times. The evidence for single agents over swarms is stronger than the industry admits.
NVIDIA just released a video foundation model that can simulate physical worlds with startling accuracy. A team at Oak Ridge National Laboratory built an...
Retrieval-augmented generation was supposed to solve the hallucination problem. It didn't. Most RAG systems still return the wrong chunk, miss the...
When an AI agent causes harm, who pays? Current law can't answer that clearly.
Microsoft's Phi-4 trained on more than 50% synthetic data and beat GPT-4o on graduate science benchmarks. The old rules about training data are changing fast.
Computer-use agents jumped from 12% to 72% on OSWorld in 18 months. The scores look like progress. The latency and efficiency numbers tell a different story.
MCP and A2A solved the plumbing. The hard part — agents actually communicating meaning — remains wide open.
Long-context LLMs now hit a million tokens, but a persistent 10% accuracy gap and punishing costs keep RAG very much in the fight.
Obsidian 1.12 ships an official CLI with 100+ commands. Here's what works, what breaks, and why AI developers should care.
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