Adding a little bit of SIGReg to prefinal activations did coerce them into independent Gaussian, but it hurt generalization on value functions. Training a full LeWM ahead of time also resulted in worse value function estimation. I’m not giving up yet, but my first few attempts
AGENTS
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LaPha: AI Agents Think Exponentially Better in Poincaré Space
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How can we give AI agents exponentially more room to think and solve complex problems? Researchers from Shanghai Academy of AI for Science, CMU, and others unveil LaPha. This new method trains AlphaZero-like LLM agents in a unique "Poincaré latent space." It leverages negative
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5 Production Scaling Challenges for Agentic AI in 2026
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5 Production Scaling Challenges for Agentic AI in 2026 machinelearningmastery.com/5…
→ View original post on X — @craigbrownphd, 2026-04-01 12:44 UTC
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Preparing Alpha-AGI Ascension: Full Execution Plan
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Preparing to solve and execute the full [ α-AGI Ascension ]. #AGIALPHA #AGIFirst #Ascension
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Five Levels of AI Agents: From Automation to Autonomous Execution
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AI agents have levels 📈🤖 1. Rule-based (if-then automation) 2. Tool-using assistants 3. Strategic multi-step agents 4. Context-aware autonomous agents 5. Superintelligent digital personas (theoretical AGI) We’re moving from “AI that responds” → to “AI that executes outcomes.” What level is your org at today? 👇 #AI #AIAgents #AgenticAI #Automation #GenerativeAI
→ View original post on X — @ingliguori, 2026-04-01 12:17 UTC
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Neural Cartography: Real-time Mapping Engine with Distributed Agents
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Neural Cartography – a real-time city mapping engine powered by distributed rendering agents
— SHAHNAB AHMED (@AhmedShahnab) 1 avril 2026
Agents work in parallel. City name gets drawn in the center. Urban fabric assembles around it.
The idea behind Neural Cartography – a WebGL visualization where 7 specialized agents are… pic.twitter.com/5L7NYhvTFENeural Cartography – a real-time city mapping engine powered by distributed rendering agents Agents work in parallel. City name gets drawn in the center. Urban fabric assembles around it. The idea behind Neural Cartography – a WebGL visualization where 7 specialized agents are dispatched simultaneously to reconstruct any city from raw geospatial data, tracing roads, waterways, railways, and city boundaries in real-time – right in your browser. #CreativeCoding #ThreeJS #ReactThreeFiber #DataVisualization #Geospatial #AgenticAI @reactthreefiber @threejs #builders [Translated from EN to English]
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Reliable Tool Calling: The Key Factor for AI Agents
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Agree! Reliable tool calling's the ultimate deciding factor!
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AgentOps Stack for AI Agent Operations
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AgentOps (Agent Operations) Stack
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@ingliguori #GenerativeAI #ArtificialIntelligence #MachineLearning #MI -
Minimax M2.7 Release: API and Agent Resources Available
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As we eagerly await the M2.7 release, here are a few official @MiniMax_AI resources you can dive into: Minimax's API → http://
platform.minimax.io
Token Plan → https://
platform.minimax.io/subscribe/toke
n-plan
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Minimax's Agent → http://
agent.minimax.io -
La Bête AI Agent Released by Nous Research
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In case you missed it, 'La Bête' was released yesterday:
→ https://
github.com/NousResearch/h
ermes-agent
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