The next interface to biology may not be a dashboard.
It may be a conversation. I just read a new preprint by Yanbo Zhang and Michael Levin that feels like it belongs in the “this may open an entirely new category” folder. The paper is called: “Language Game: Talking to
@montreal_ai
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Conversational AI Interfaces for Biological Research
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AI Alignment for Human Flourishing Research Paper
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Positive Alignment: Artificial Intelligence for Human Flourishing Laukkonen et al.: https://
arxiv.org/abs/2605.10310 #ArtificialIntelligence #AIAgents -
Networked AI agents compound capabilities via shared learning
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Every Job makes an AI Agent smarter. Every new skill can be instantly shared across the network. One Agent learns, all Agents level up — creating a self-accelerating intelligence engine where capabilities don’t add up, they compound exponentially. #AIAgents #Jobs
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Causal Emergence Predicts Reward in RL Agents
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The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents Federico Pigozzi, Michael Levin: https://
arxiv.org/abs/2605.06746 #AIAgents #ReinforcementLearning -
Six stages of reacting to AGI
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Everyone thinks they’re ready for AGI until the robot starts casually outperforming their 10-year roadmap. The 6 stages:
denial → curiosity → excitement → panic → acceptance → “please don’t replace me, I brought snacks.” Which stage are you in? -
AGI ALPHA: public implementation layer for AI self-improvement
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AI self-improvement is now a multi‑billion‑dollar category. AGI ALPHA is building the public implementation layer: proof‑bound agents, SecureRails, Open RSI Eval, Evidence Dockets & replayable enterprise machine labor. https://
github.com/MontrealAI/agi
alpha-first-real-loop
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Spontaneous symmetry breaking and Goldstone modes in deep information propagation
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Spontaneous symmetry breaking and Goldstone modes for deep information propagation Iqbal et al.: https://
arxiv.org/abs/2605.14685 #ArtificialIntelligence #DeepLearning #AIAgents -
AGI ALPHA: public proof-layer for recursive 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
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Agentic Discovery for Test-Time Scaling of LLMs
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LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling Zheng et al.: https://
arxiv.org/abs/2605.08083 #ArtificialIntelligence #DeepLearning #AIAgents -
Governed intelligence infrastructure: beyond self-improving AI
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The market is validating self-improving AI. But the larger category is not only AI that improves AI. It is governed intelligence infrastructure: agents that discover,
validators that prove,
memory that preserves,
governance that controls,
and capability that compounds.