// Harnessing Agentic Evolution // Pay attention to this one if you run iterative agentic search loops. (bookmark it) AEvo splits the self-improvement loop into two jobs: > One proposes the next candidate. > The other watches what worked, what failed, and edits the procedure
AI
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Future Glasses to Focus on AI-Driven Features, Apple Vision Pro Evolution Expected
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WWDC, if it does introduce glasses, will focus mostly on AI-driven glasses that don't have displays. But three years from now? I totally expect a much lighter Apple Vision Pro.
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Designing with AI Agents and Data Integration in MagicPath
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Yes, of course. Like, let’s say you have your agent connected to a mixpanel MCP or a database or a CSV, you can design WITH that in MagicPath now!
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Traces d’agents auto-améliorants pour modèles
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you talking about how traces of self improving agents can be fed into the retraining of self improving models?
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VR/AR Headset Form Factors Evolving Beyond ‘Scuba Mask’ Design
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Does this count> https://
x.com/pimaxofficial/
status/2054947429829480742?s=20
… ? See, the "scuba mask" form factor is going away. It's getting lighter. The market is segmenting into different kinds of devices. It's a spectrum from lightweights like @evenrealities to heavyweights like Quest 3 or Apple Vision Pro. -
Grok Build CLI Beta Launched with AI Agent Features
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SPACEXAI : Grok Build CLI is now live in Beta for Grok Heavy users. It supports Skills, Subagents, Plugins, and Planning Mode. Heavy testing time /btw
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Testing Higgsfield’s Supercomputer with multi-model routing
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I've been testing Higgsfield's Supercomputer for the past few days, and it genuinely caught me off guard. You type a task in plain language. The system picks from 61 production skills, routes each sub-task to the best available model (GPT-5.5, Claude Opus, Gemini, Seedance, Veo,
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Optimiser les tâches avec Claude Code
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A small hack for my AI multi-taskers out there: I have so many Claude Code conversations running at once that I ask it to synthesize all of its action or my next action into single go/no-go sentences. That way, when I come back to my desk an hour later, the work is seamless.
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Effective scaling laws for time series foundation models
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Are scaling laws finally effective for time series foundation models? Today, @datadoghq is releasing Toto 2.0 weights under Apache 2.0 on @huggingface. It's a family of open-weights TSFMs ranging from 4M to 2.5B parameters, where each size outperforms the previous one from a single hyperparameter configuration.
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AGI Alpha: A Public Proof Layer for Self-Improving AI
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Recursive validated self-improving AI at $ 4.65B. AGI ALPHA is building the public proof layer. Not just AI that improves—
AI that proves, replays, audits, archives & compounds. Proof-bound. Enterprise-ready. Built in public. https://
github.com/MontrealAI/agi
alpha-first-real-loop
… #AGIALPHA #MontrealAI