try it out now: https://
alphaxiv.org/assistant
LLMS
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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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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
… @Holabossai -
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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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
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UK AI Institute: Mythos and GPT-5.5 show rapid cyber growth
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The UK’s state AI Security iIstitute findings:
1) Mythos is a big gain in cyber capabilities. But so is GPT-5.5
2) It is hard to establish an upper bound on Mythos/GPT-5.5, which appear to be limited by tokens used, rather than ability.
3) Capability doubling time is 4.5 months -
User surprised by GPT-5.6’s rapid arrival
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GPT-5.6 arriving *that quick* was not on my bingo card.
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Cline SDK Revolutionizes AI Development
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The new Cline SDK just dropped and it changes everything 🔥
— Charly Wargnier (@DataChaz) 13 mai 2026
→ Rebuilt agent harness
→ Fully open SDK (npm i @cline/sdk)
→ Beats Claude Code on tbench
→ Hub-backed persistent sessions
→ Cron automations
best part?
they just open-sourced the SDK so you can build on it too👀 https://t.co/3Rg0xBBnPSThe new Cline SDK just dropped and it changes everything → Rebuilt agent harness
→ Fully open SDK (npm i @cline/sdk)
→ Beats Claude Code on tbench
→ Hub-backed persistent sessions
→ Cron automations best part? they just open-sourced the SDK so you can build on it too