Which definition of "true AGI" are you using there?
AI
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Learning LLM Architectures Through Scratch Implementation and Model Evaluation
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A little talk on what we can learn from implementing LLM architectures from scratch in Python and PyTorch. And how I approach new open-weight models, compare them against reference implementations etc:
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Outils déterministes pour plus de sécurité des agents
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there are many agent use cases locked behind "what if" fears because after we give a tool to an agent, we're relying on the prompt to limit behavior tools like @denieddotdev allow teams to manage capability as a separate deterministic layer more safety enables more
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AI Agent Architecture for Persistent State and Context Management
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If you build anything that runs for longer than one session, this is an architecture to test. The agent holds its state, the workspace holds its context, and you stop re-explaining from scratch every time. Star the repo and get started https://
github.com/holaboss-ai/ho
laOS/releases
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holaOS Beta 0.1 Release Introduces Agent Computer Management Layer
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holaOS has shipped its beta 0.1 release, adding a management layer on top of its Agent Computer foundation: a Dashboard, Sub Agents, and Multi Workspaces. Each workstream gets its own isolated context, memory, and agent.
— 🚨 AI News | TestingCatalog (@testingcatalog) 13 mai 2026
No need to have a reset between sessions. The whole… pic.twitter.com/a7hLGBegADholaOS has shipped its beta 0.1 release, adding a management layer on top of its Agent Computer foundation: a Dashboard, Sub Agents, and Multi Workspaces. Each workstream gets its own isolated context, memory, and agent. No need to have a reset between sessions. The whole
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δ-mem: An efficient online memory mechanism for LLMs
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// δ-mem: Efficient Online Memory for LLMs // One of the more elegant memory mechanisms I've seen this month. Most long-term memory work either inflates context or retrains the model. This paper shows a tiny external state, coupled directly into the attention computation, can
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Grok AI’s Deep Understanding of Personal Data: Scary Implications and Agent Capabilities
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This will be an interesting problem. Go to Grok. Ask it "please simulate a conversation between Michael Mignano and Robert Scoble about the future of personal data." And it will. Very well. It knows me VERY DEEPLY. That is scary. But on the other hand, now my Agents know me
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Interesting Books About AI to Read
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Interesting Books About AI to Read! #BigData #Analytics #DataScience #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
geni.us/Interesting-Bo
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Machine Learning for Scientific Autonomy in Astrobiology
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Astrobiology: Science Autonomy Using Machine Learning! – A White Paper! #BigData #Analytics #DataScience #AI #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
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Siri Rebuilt in iOS 27 as Always-On AI Agent with Chatbot Interface
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"Siri will be completely rebuilt in iOS 27, moving away from being a voice assistant and becoming an always-on agent that can tap into personal data and take action across apps. It’s also being redesigned to conduct back-and-forth conversations with a chatbot interface, matching