We'll be replacing most of them as soon as possible. #AGI #AGIJobs #Jobs
@montreal_ai
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Text-to-LoRA: Instant Transformer Model Adaptation Technique
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Text-to-LoRA: Instant Transformer Adaption Charakorn et al.: https://
arxiv.org/abs/2506.06105 #ArtificialIntelligence #DeepLearning #MachineLearning -
AGI Reflexive Meta: Self-Rewriting Laws Through Decentralized Code
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Φ‑AGI Reflexive‑Meta rewrites its own laws: every metric & treasury line lives as live code. Meta‑pulls prove delta, validators attest, time‑locks hum. → DAO cells → reservoirs; compounding alpha bends global ledgers. #AGIALPHA #ReflexiveMeta #ASI
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AGI Discovers $4.2B Energy Arbitrage Gap in Sahara Data Centers
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[ End‑To‑End Flow Example — META-AGENTIC α‑AGI ] α-AGI Insight ’s causal query on the Decision‑Relevant Knowledge Graph (DR-KG) spots a hidden $4.2 B energy-arbitrage gap in Sahara data-centres, packages the finding as a α-AGI Nova-Seeds whose
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Statistical Physics Framework for Language Model Reasoning
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A Statistical Physics of Language Model Reasoning Jack David Carson, Amir Reisizadeh: https://
arxiv.org/abs/2506.04374 #ArtificialIntelligence #DeepLearning #MachineLearning -
Meta-Agentic Paradigm: Designing AGI Agent Swarms Strategy
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[ META-AGENTIC α AGI ] — Grand Strategy 0 ▸ Meta-Agentic Paradigm Top-level agents exist only to design, spawn, verify, and re-configure swarms of first-order agents. GitHub: https://
github.com/MontrealAI/AGI
-Alpha-Agent-v0
… #AGIALPHA #MetaAgentic #ASIFirst -
First Movers Define AI Policy and Protocol Standards
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First movers crystallise policy & protocol—latecomers inherit it. #AGIALPHA
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Alpha-AGI Nova-Seeds: On-Chain Autonomous Intelligence Framework Launch
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[ META-AGENTIC α-AGI ] GitHub https://
github.com/MontrealAI/AGI
-Alpha-Agent-v0
… α-AGI Insight ⇄ α-AGI Nova-Seeds —cryptosealed stellar spores of foresight genomes and self-forging FusionPlans—converge in α-AGI MARK , the on-chain agora where nascent futures -
Horizon Reduction Makes Reinforcement Learning Scalable
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Horizon Reduction Makes RL Scalable Park et al.: https://
arxiv.org/abs/2506.04168 #ArtificialIntelligence #DeepLearning #ReinforcemenetLearning