Na Zhang

1/ today we're releasing muse spark, the first model from MSL. nine months ago we rebuilt our ai stack from scratch. new infrastructure, new architecture, new data pipelines. muse spark is the result of that work, and now it powers meta ai. 🧵

1/5 🤔 LLMs can solve olympiad math and write production code. But can they hold a conversation that's actually fun — one that people want to keep coming back to? 💬✨ We present CharacterFlywheel— an iterative process optimizing LLMs for real human engagement and character steerability, while maintaining rigorous safety protocols 🔒. Tested across Instagram, WhatsApp & Messenger 📱with millions of users — where they can create, share, and chat with their own AI characters 🤖. 📄 paper: arxiv.org/abs/2603.01973 huggingface.co/papers/2603.01…

People are putting lots of efforts into building diverse RL environments. But what kinds of environments are more useful for building **generalist** agents that are able to solve tasks beyond their training tasks? 🚀 Instead of optimizing one single benchmark, we look for drivers of transfer in our latest paper: huggingface.co/papers/2601.18… Joint work with MSL @MetaAI (@ZhihanLiu21628 @GuanSuns @EasonNie @KaiZhang_CS @nazzhang) where @ZhihanLiu21628 interned. (1/n)

Three Extreme Performance Talks from the Office of the CTO at VMworld USA octo.vmware.com/three-extreme-… #VMworld17

Great post by @nazzhang! Virtualized HPC Performance with VMware vSphere 6.5 on a Dell PowerEdge C6320 Cluster en.community.dell.com/techcenter/hig…

Performance of RDMA and HPC Applications in VMs using FDR InfiniBand on VMware vSphere bit.ly/24TLhuv