The recording of our live session with @ultralytics and Innowise is now up. See how to deploy Ultralytics YOLO models on Axelera Metis AIPUs in minutes using a single command. Read the technical blog: https://
eu1.hubs.ly/H0tm6sp0
Watch the session: https://
eu1.hubs.ly/H0tm3BT0 #EdgeAI
AI
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Deploy Ultralytics YOLO Models on Axelera Metis AIPUs
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Turn Ideas into AI Apps in Minutes with Abacus.AI Agent
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Turn ideas into AI apps in minutes No code. No complexity. Just results. Join us LIVE on April 23 to see Abacus.AI Agent & Claw easily turn prompts into production apps. 🎟 Spots are limited, reserve your place today: eventbrite.com/e/19865596172…
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AI-Generated Thumbnails: Five Years of Creative Evolution
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I’ve been unapologetically using AI for my thumbnails for 5-years now! The AI just got better and better and less noticeable. Cringe works. Annoying but effective unfortunately.
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AI agent autonomously probes its own multi-GPU setup and stats
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running Qwen3.5 397B MoE (17B active/token)
— Ahmad (@TheAhmadOsman) 9 avril 2026
on 4x DGX Sparks in FP8 (~400GB)
> OpenCode driving
> agent exploring its own config
> probing all 4 Sparks (via ssh) + reporting thermals
> inspecting how vLLM is serving it
> collecting + analyzing its own stats
local AI is awesome https://t.co/KU9u30GgXk pic.twitter.com/yPWSbSKto8running Qwen3.5 397B MoE (17B active/token) on 4x DGX Sparks in FP8 (~400GB) > OpenCode driving
> agent exploring its own config
> probing all 4 Sparks (via ssh) + reporting thermals
> inspecting how vLLM is serving it
> collecting + analyzing its own stats local AI is awesome -
Microsoft faces £3.5B class action over software resale appeal
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Microsoft software resale appeal catches eye of £3.5B class action https://
go.theregister.com/feed/www.there
gister.com/2026/04/09/microsoft_valuelicensing_appeal/?utm_source=dlvr.it&utm_medium=twitter
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LangChain Launches Deep Agents, Open Source Alternative to Claude
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Read the full blog here: blog.langchain.com/deep-agents-deploy-an-open-alternative-to-claude-managed-agents/ Documentation: docs.langchain.com/oss/python/deepagents/deploy [Translated from EN to English]
→ View original post on X — @langchain, 2026-04-09 15:49 UTC
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Deep Agents Deploy: Model Optionality and Sandbox Flexibility
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One of the benefits of Deep Agents deploy is model optionality Choose from models from @OpenAI @GeminiApp @AnthropicAI @FireworksAI_HQ @baseten @OpenRouter @ollama @nvidia and many others Another is you can bring your own sandbox – @daytonaio @modal @RunloopDev
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Deep Agents deployment with open standards configuration
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Deep Agents deploy is simple – just specify configuration like you would for a coding agent: – AGENTs.md (open standard)
– /skills (open standard)
– mcp.json (convention) and then choose your model and sandbox provider -
LangSmith Agent Deployment with Memory and Protocol Exposure
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From there – we spin up a deployment on LangSmith deployments with production ready short term and long term memory We expose your agent via MCP, A2A, and agent protocol
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Deep Agents Deploy Beta Launch for Production-Ready Models
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Deep Agents deploy Today we’re launching Deep Agents deploy in beta. Deep Agents deploy is the fastest way to deploy a model agnostic, open source agent harness in a production ready way. Open harness, open memory, model agnostic