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  "text": "NEW paper from Meta.\n\n(bookmark this one)\n\nWhat if the model wasn't just using the computer, but became the computer?\n\nNew research from Meta AI and KAUST makes a serious case for Neural Computers (NCs).\n\nThe paper proposes NCs as learned runtimes where computation, memory, and I/O live inside a single latent state. Their first prototypes use video models to roll out terminal and GUI interfaces from prompts, pixels, and user actions.\n\nWhy does it matter?\n\nToday's agents still depend on external computers to store state, execute actions, and enforce system contracts. Neural Computers point to a different machine form: one where interface dynamics, working memory, and execution are learned together.\n\nThe early results are promising but grounded. CLI rendering improves, GUI cursor control reaches 98.7% with explicit visual supervision, and reprompting boosts arithmetic-probe accuracy from 4% to 83%. But symbolic reliability, stable reuse, and runtime governance remain open.\n\nThis is less \"agents got better\" and more \"what comes after agents as a computing substrate?\"\n\nPaper: https://t.co/CKdclokmer\n\nLearn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX",
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