AI Dynamics

Global AI News Aggregator

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GENERATIVE AI

  • AI automation delivers news, posts, and analysis from a single prompt.

    By

    @aibreakfast

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    I woke up to: – 10 AI news summaries with links in my inbox
    – An Instagram post already live
    – A competitor analysis emailed to me I opened X zero times yesterday. All from one prompt on @Pokee_AI
    's PokeeClaw.

    → View original post on X — @aibreakfast

  • Real-time motion transfer avatar creation technology breakthrough

    By

    @OlivierRimmel

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    Wow it's amazing you can create an indian avatar driven with motion transfer in real time!

    → View original post on X — @olivierrimmel

  • Chatbase Voice: AI Agent Now Handles Phone Calls

    By

    @scobleizer

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    Introducing @Chatbase Voice. The same AI agent that handles your emails and website chat, can now pick up the phone. One agent, deployed on every channel. Comment "voice" to get a personalized demo & 1 month free.

    → View original post on X — @scobleizer, 2026-04-07 15:01 UTC

  • Connected AI Systems: The Next Evolution Beyond Individual Tools

    By

    @ronald_vanloon

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    The shift isn’t “more AI tools” It’s connected AI across systems What stood out to me with this approach: → Pulls data from email, CRM, Slack, docs, code → Works across multiple LLMs, not locked into one → Executes workflows, not just answers questions Example: Ask in Slack: “Which deals are at risk this quarter?” → AI analyzes CRM signals → Generates a plan → Can take action That’s a different level of leverage

    → View original post on X — @ronald_vanloon, 2026-04-07 15:00 UTC

  • Frontier AI Models: From Expensive Today to Affordable Tomorrow

    By

    @clementdelangue

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    I am experiencing this now and it’s definitely the future Marc Andreessen 🇺🇸 (@pmarca) Magical OpenClaw experiences that use frontier models cost $300-1,000/day today, heading to $10,000/day and more. The future shape of the entire technology industry will be how to drive that to $20/month. — https://nitter.net/pmarca/status/2041397922940801170#m

    → View original post on X — @clementdelangue, 2026-04-07 14:50 UTC

  • QoderWork: Desktop AI Agent That Automates Your Work Locally

    By

    @scobleizer

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    Meet QoderWork — a desktop AI agent that doesn't just chat, it actually does your work. Evan leads the QoderWork product at Qoder, a Singapore-based AI company. Which is a new generalized agentic service that lets you: ++ Open files on your computer. ++ Analyze data. ++ Run code. ++ Automate multi-step workflows. ++ Deliver polished, ready-to-use results (e.g., complete PowerPoint decks, reports, or charts) directly to your desktop. QoderWork positions itself at this inflection point: it takes a task like “analyze this spreadsheet and build a board-ready presentation,” then handles the entire chain autonomously. Key takeaway: Trust and usefulness matter more than raw intelligence—agents must be powerful enough for real work while remaining reliable and transparent. I wanted to add some of my personal opinions after doing this rare interview. Everything runs locally on your own computer — your files never leave your machine. That’s a big deal for anyone handling sensitive business data. Everything runs locally on your own computer. And it's more advanced than other agentic services I've told you about. A great example of the global AI agent wave. I'm working on getting more interviews like this with entrepreneurs around the world bringing the AI age to your life and business. Try @qoder_ai_ide at qoder.com/en

    → View original post on X — @scobleizer, 2026-04-07 14:46 UTC

  • Aligned News: New AI Industry Tracking Platform Launches Today

    By

    @scobleizer

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    THIS 👇🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥 Robert Scoble (@Scobleizer) Launching now: a new way to follow the AI industry. Beta starts now for the next month. A joint project between Unaligned (my company) and Levangie Labs (@blevlabs company). It reads 50,000 of you, and follows 8,300 AI companies here on X. And pulls out the best and most interesting. All built with the X API. Check it out: alignednews.com/ai And please sign up for its daily newsletter. Yeah, $25 a month is a lot for many of you, but that will defray the costs and let me expand it to do a lot more than just AI. Also, the same AI agent that built the site, and did EVERYTHING you see can build custom reports for you on literally any tech community here on X. It supports OpenClaw, RSS, and Notebook LM too. And I'll add more from your requests. More: — https://nitter.net/Scobleizer/status/2039230811355132274#m

    → View original post on X — @scobleizer, 2026-04-07 14:41 UTC

  • Building Games with Codex: From Idea to Updates in Seconds

    By

    @romainhuet

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    I built a small game live, going from idea to updates in seconds, and explored different ways to build with Codex. As we manage more agents, judgment, taste, and a deep understanding of user needs matter even more. Watch the full conversation:

    → View original post on X — @romainhuet

  • Building Codex at OpenAI: Behind the Scenes with Live Demo

    By

    @romainhuet

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    Really enjoyed joining @petergyang with @embirico to talk about how we’ve been building Codex at OpenAI. We show a live demo of the Codex app and go behind the scenes. What’s been striking: role lines are blurring. Designers write code, engineers think product.

    → View original post on X — @romainhuet

  • On-Policy SFT Matches RL Generalization Without Sacrificing Efficiency

    By

    @jiqizhixin

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    Can we boost Supervised Fine-Tuning (SFT) to match Reinforcement Learning's (RL) generalization power, without sacrificing efficiency? Researchers from Southeast University, Microsoft Research Asia, and Shopee just dropped a game-changer! They introduce a "Distribution Discriminant Theory" to align training data with a model's own output, leading to two techniques: In-Distribution Finetuning and Hinted Decoding. This enables "On-Policy SFT" – effectively training SFT with data highly relevant to its current state, much like RL. The result? SFT that outperforms leading offline RL algorithms like DPO and SimPO in generalization, all while keeping SFT's renowned efficiency. This is a game-changer for domains where RL is too complex! Towards On-Policy SFT: Distribution Discriminant Theory and its Applications in LLM Training Paper: arxiv.org/abs/2602.12222 Code: github.com/zhangmiaosen2000/… Our report: mp.weixin.qq.com/s/vBtoBAsTe… 📬 #PapersAccepted by Jiqizhixin

    → View original post on X — @jiqizhixin