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AI agents enhanced with multi-modal inputs reduce correction loops

Omar Sanseviero discusses how adding more modalities to AI agents can enhance their understanding and reduce correction loops. He introduces the concept of a 'task' which bundles various inputs like voice notes, screen context, and text to allow agents to reconstruct user intent more effectively and handle larger work assignments. AI

IMPACT Multi-modal inputs and bundled 'tasks' could significantly improve AI agent efficiency and user experience by reducing the need for iterative corrections.

RANK_REASON Commentary on AI agent capabilities based on a point made by Karpathy.

Read on X — Omar Sanseviero (HF research) →

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

AI agents enhanced with multi-modal inputs reduce correction loops

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  1. X — Omar Sanseviero (HF research) TIER_1 English(EN) · omarsar0 ·

    Karpathy's point about long voice rambles goes further when you add more modalities.

    Karpathy's point about long voice rambles goes further when you add more modalities. My favorite way to prompt agents lately is a bigger unit I've been calling a task. A task bundles a long voice note, the current screen, annotations, and exact text into a single turn. The …