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MiniMax AI discusses sparse attention and multimodal training

By PulseAugur Editorial · [1 sources] ·

MiniMax AI's research lead, Olive Song, discussed the company's advancements in sparse attention and native multimodal training during a conversation at the AI Engineer conference. The discussion highlighted the importance of open-weights models for the future of AI. Song expressed gratitude to the AI Engineer team for facilitating such technical exchanges. AI

IMPACT Highlights the ongoing research and development in AI, particularly concerning open-weight models and multimodal training.

RANK_REASON The cluster consists of a social media post discussing AI research topics, not a primary announcement or release.

Read on X — MiniMax AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MiniMax AI discusses sparse attention and multimodal training

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The cluster consists of a social media post discussing AI research topics, not a primary announcement or release.
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COVERAGE [1]

  1. X — MiniMax AI TIER_1 English(EN) · MiniMax_AI ·

    Day two of @aiDotEngineer started with a conversation anyone serious about open weights should be paying attention to.

    Day two of @aiDotEngineer started with a conversation anyone serious about open weights should be paying attention to. @olive_jy_song, research lead RL, joined @Thom_Wolf to dig into sparse attention, native multimodal training from day zero, and why open-weights matter for

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