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Multimodal models can now achieve state-of-the-art performance in real-world tasks like document understanding and audio-video comprehension with significantly reduced inference latency thanks to novel token-reduction techniques.
Current multimodal LLMs choke on long-form video understanding, either forgetting details or getting lost in the timeline, but a new agentic architecture with dynamic memory management offers a promising fix.
