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Latest AI news, models and releases from Meta. ['Astryx', 'Business Agent', 'BYT5', 'CodeLlama', 'expressive voice AI', 'FAIRChem v2 UMA', 'Gemma 4', 'Gemma4:e2b', 'HuBERT', 'llama', 'Llama', 'LLaMA', 'Llama-2 70B', 'LLaMA2-chat-70B', 'Llama 3', 'Llama 3.1', 'Llama 3.1-405B', 'Llama-3.1-405B', 'LLaMA-3.1 405B', 'Llama 3.1-70B', 'Llama 3.1 8B', 'Llama 3.1-8B', 'Llama-3.1-8B', 'Llama 3.2', 'LLaMA 3.2', 'Llama-3.2-1B-Instruct', 'Llama 3.3', 'llama-3.3-70b', 'Llama 3 8B', 'Llama3-8B-Instruct', 'Llama 4', 'Llama 4 Maverick', 'LLaMA 65B', 'Llama 70B', 'M2M100', 'M**a AI', 'mBART', 'Meta AI', 'Meta AI model (model name not specified)', 'Meta Muse Spark']

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Threads users can now chat with Meta AI in direct messages

Meta has started rolling out the Meta AI chatbot within Threads direct messages, allowing users to interact with the AI assistant privately. The feature is already available on Facebook, Instagram, and WhatsApp, and aims to keep users within Meta's ecosystem.

New DeepSeek-V3 technical report: how hardware-software co-design enables low-cost training of large models

A new technical paper from the DeepSeek team, with CEO Wenfeng Liang as co-author, explores hardware-aware model co-design to reduce LLM training costs. Using DeepSeek-V3 trained on 2048 NVIDIA H800 GPUs as a case study, the paper details innovations in memory efficiency (MLA), sparse computation (DeepSeekMoE), FP8 training, and interconnect-aware routing.

DeepSeek

NVIDIA

Alibaba/Qwen