#mixture-of-experts-moe

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Artificial intelligence
fromComputerworld
7 hours ago

Nvidia bets on open infrastructure for the agentic AI era with Nemotron 3

Nemotron 3 enables enterprises to build domain-specific AI agents without creating foundation models by providing open models, training data, and reinforcement-learning libraries.
Artificial intelligence
fromInfoWorld
8 hours ago

Nvidia bets on open infrastructure for the agentic AI era with Nemotron 3

Nvidia releases Nemotron 3 open models enabling enterprises to build domain-specific AI agents without creating foundation models, while releasing training data and RL libraries.
Artificial intelligence
fromTheregister
1 month ago

Baidu teases next-gen AI training, inference accelerators

Baidu unveiled M100 (inference) and M300 (training) chips and will deploy Tianchi256/512 clusters to lower inference costs and support larger MoE models.
Artificial intelligence
fromZDNET
1 month ago

A new Chinese AI model claims to outperform GPT-5 and Sonnet 4.5 - and it's free

Moonshot's open-source Kimi K2 Thinking claims superior reasoning performance to GPT-5 and Sonnet 4.5 on several benchmarks while offering tool use and MoE architecture.
fromTheregister
1 month ago

How Perplexity optimized 1T parameter AI models for AWS EFA

AI search provider Perplexity's research wing has developed a new set of software optimizations that allows for trillion parameter or large models to run efficiently across older, cheaper hardware using a variety of existing network technologies, including Amazon's proprietary Elastic Fabric Adapter. These innovations, detailed in a paper published this week and released on GitHub for further scrutiny, present a novel approach to addressing one of the biggest challenges in serving large-scale mixture of experts models (MoE) at scale: memory and network latency.
Artificial intelligence
Artificial intelligence
fromLogRocket Blog
3 months ago

Agentic AI for 5x less: Why Kimi K2 is a frontend game-changer - LogRocket Blog

Kimi K2 is an open-source, agentic mixture-of-experts model that activates 32B of 1T parameters to execute tasks efficiently and rapidly.
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