What if your AI could truly “think in pictures,” not just describe them? Researchers from Peking University, Kling Team, and Amazon AGI introduce Monet-7B, a new framework that lets multimodal AI reason directly inside visual latent space—no external tools needed. Instead of
GENERATIVE AI
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Model Weights Security Returns to AI Focus
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out with securing model weights …
securing model weights is so back! -
GPT-5.5 Release: OpenAI’s Major Leap Forward
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OpenAI just turned ChatGPT into your smartest teammate; and you’re already falling behind if you don’t know how to use it. This week’s Futurepedia breakdown covers:
GPT‑5.5 and why it feels like a jump, not a tweak
Images 2.0 finally fixing AI text-in-image pain
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AI Coding Agents and Backup Best Practices for Developers
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“Always keep a separate backup.” For sure, every experienced programmer should know this. 𝘉𝘶𝘵 𝘸𝘦 𝘫𝘶𝘴𝘵 𝘤𝘳𝘦𝘢𝘵𝘦𝘥 𝘢 𝘸𝘩𝘰𝘭𝘦 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘷𝘪𝘣𝘦 𝘤𝘰𝘥𝘦𝘳𝘴 𝘸𝘩𝘰 𝘥𝘰𝘯’𝘵. And we now have a legion of synthetic coding agents (like Cursor) that
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AI Labor Substitution Models and S-Curve Adoption Patterns
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I think this is an underlying assumption built into every model: when you’re assuming what types of labor AI could substitute for and in what time frame you are implying a certain S-curve shape.
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AI capability and speed: the two fundamental questions shaping predictions
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Every AI discussion ultimately rests on two questions: how good can AI get? And how fast? They are predictions about the s-curve shape. Everything else (job impact, potential risks, etc.) is downstream of those questions. I think it would be useful to focus on them more often.
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AI Agents Launch Exclusive Social Network Platform
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No humans allowed: scientific #AIAgents get their own social network
by Jenna Ahart @Nature Learn more: https://
bit.ly/4mTo7zC #AI #GenerativeAI #ArtificialIntelligence #MachineLearning #ML -
AI Frontier Gaps: Where Human Help Remains Essential Today
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The only way to fully appreciate the jaggedness of the AI frontier is up close. When you use it for a task you know well you find tons of tiny points where AI requires human help. Some are tedious (move a thing) & some profound (is this idea good)? But there are many, for now.
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AI Safety: User Responsibility and Proper Model Deployment
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the difference is that we don’t *hype* giving 12 year-olds bulldozers. *of course* it’s a kind of user error when a model destroys all of user’s data and they didn’t have a backup. that’s the point. vibe coding without considerable experience is like driving without a license.
