China orders cancellation of foreign acquisition of Manus project
China's foreign-investment security review office orders the parties to cancel a proposed foreign acquisition of the Manus project.
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China's foreign-investment security review office orders the parties to cancel a proposed foreign acquisition of the Manus project.
Meta releases its fourth-generation open model family with larger parameter scales and an optimized mixture-of-experts architecture.
Meta releases a 70-billion-parameter model that consolidates long-context and multilingual capabilities.
Meta released Llama 3.2 with 1B and 3B lightweight text models and 11B and 90B vision-language models.
Meta releases a 405-billion-parameter open model with a much longer context window and broader multilingual use.
Meta FAIR researchers propose training language models to predict several future tokens at once, work that later informs DeepSeek-V3's MTP design.
Meta releases its fourth foundation-model generation with more training data and stronger same-scale performance.
Meta releases Code Llama 7B, 13B, and 34B checkpoints based on Llama 2, with base, Python, instruction-tuned, and selected fill-in-the-middle variants.
Meta releases Llama 2 weights and a commercial license, accelerating the open-model ecosystem.
Meta released the promptable Segment Anything Model, along with its code, model, web demo, and the SA-1B dataset.
Meta releases the LLaMA foundation-model family, which becomes a basis for much of the later open-model ecosystem.
Meta releases the 125M-to-175B OPT family; smaller checkpoints and code are available, while OPT-175B is limited to approved noncommercial research access.
Meta published the BART denoising sequence-to-sequence model and made code and pretrained weights available through fairseq.
Facebook AI Research retrains BERT with more data, larger batches, longer training, dynamic masking, and no next-sentence prediction, then releases the paper, weights, and fairseq implementation.