Gated DeltaNet has been one of my favorite "hybrid attention" newcomers in the good old transformer stack.
Excited to see Gated DeltaNet-2. Adding it to my reading stack. In the meantime, I have a primer on Gated DeltaNet here: https://
magazine.sebastianraschka.com/i/177848019/26
-gated-deltanet
…
TECHNOLOGY
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Gated DeltaNet-2: Hybrid Attention Architecture Advancement
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Codex enhances engineers’ focus
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6/ The thread beneath all five. Codex isn’t used to write code faster. It’s used to handle the work that disrupts focus. Reading. Refactoring. Testing. Scaffolding. Background tasks.
The engineer stays in the flow. The agent takes care of the rest. -
Scaffolding a New Project with Codex
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4/ Scaffolding new work. The initial setup of folders, modules, and API stubs for a feature. The boilerplate phase. Engineers use Codex to generate runnable code in minutes, then begin the actual problem-solving work.
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Reading unfamiliar code with AI assistance
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1/ Reading unfamiliar code. When engineers get pulled into a part of the codebase they have never touched, they point Codex at it first. For onboarding. For debugging. For incidents where you need to understand a system in minutes. This is the most common one in the report.
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Feedback sought on latest Gemini model
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why is the model bad? Would love feedback! It’s the most capable Gemini model we have ever shipped
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Agent Swarms for Apps and Automations
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🚨 AGENT SWARMS – BUILD COMPLEX APPS AND AUTOMATIONS WITH ONE PROMPT
— Abacus.AI (@abacusai) 21 mai 2026
Combine Gemini 3.1 Pro, Opus 4.7 and GPT 5.5 to create complex multi-agent systems
Each agent excels at a particular task – coding, testing, mobile app, research and monitoring
Master agent orchestrates… pic.twitter.com/QGfgUPNT84AGENT SWARMS – BUILD COMPLEX APPS AND AUTOMATIONS WITH A SINGLE PROMPT Combine Gemini 3.1 Pro, Opus 4.7, and GPT 5.5 to create advanced multi-agent systems. Each agent specializes in a specific task—coding, testing, mobile app development, research, and monitoring. A master agent orchestrates the workflow.
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Modèles de transcription leaders du secteur
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Industry-leading transcription. Our transcription models are optimized for conversational use cases, delivering ultra-low latency and built to handle messy, real-world environments.
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Training Major AI Model with 10x Compute on Colossus 2
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> Together with SpaceXAI, we're training a significantly larger model from scratch, using 10x more total compute. With Colossus 2's million H100-equivalents and our combined data and training techniques, we expect this to be a major leap in model capability. That's double
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Moving Beyond Traditional Statistics in the Age of AI
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If You’re Still Worshipping Pearson Correlation, You’re Not a Data Scientist — You’re Driving a Horse Cart in the Age of AI: https://
valeman.medium.com/if-youre-still
-worshipping-pearson-correlation-you-re-not-a-data-scientist-you-re-driving-a-831dc0590de6
… My summary: Don’t just plug your data into some formula to find the answers to the questions you started with. Real Data -
Project GAIUS: Gesture Control Without the Cloud
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Point at a lamp. It turns on. Point at the TV. It changes the channel. No remote, no voice, no cloud. Project GAIUS by @KatusDavid: multi-camera 3D triangulation, arm raycasting, gesture recognition on Metis M.2. Fully offline, fully open source. Code + docs:
https://eu1.hubs.ly/H0vmv_j0