AI Dynamics

Global AI News Aggregator

About

CREATIVE AI

  • Marble Expands World Generation Capabilities Step by Step

    By

    @drfeifei

    –

    Making improvements one step at a time for Marble. In the case of generating bigger worlds, it's quite literal 😉

    → View original post on X — @drfeifei

  • Two New Marble Model Updates Released for Scale and Quality

    By

    @scobleizer

    –

    We're excited to be rolling out two model updates today! Marble 1.1: Improves lighting and contrast, with a major reduction in visual artifacts. Marble 1.1-Plus: Our new model built for scale. Create larger, more complex environments than ever before.

    → View original post on X — @scobleizer, 2026-04-07 16:32 UTC

  • AI Agents Discover Novel Bio-Inspired Resonator Design Autonomously

    By

    @kimmonismus

    –

    Really cool: AI agents mapped resonators across biology, engineering, and music into a shared space, discovered an unexplored design gap, and autonomously created and validated a new bio-inspired structure to fill it. Markus J. Buehler (@ProfBuehlerMIT) A resonator is any structure that naturally prefers to vibrate at certain frequencies: a violin body, a bell, a drum skin, an acoustic filter, even many biological systems. Resonators matter because they govern how systems transmit sound, absorb or filter vibration, sense motion and perform mechanically. They are also notoriously hard to design as resonance does not depend on one property alone. It emerges from geometry, material composition, and the interplay of modes across scales. And because biology, music, and engineering usually explore very different regions of this design space, important possibilities remain hidden if you stay inside a single field. In a new study a shared representation across 39 resonators spanning biology, engineered metamaterials, musical instruments and Bach chorales was constructed. Thereby, a cricket wing harp membrane, a phononic crystal slab, and a four-voice chorale (and many others) were translated into one common map using features such as membrane character, structural periodicity, hierarchy, frequency range, damping, and modal coupling. That map revealed something important: not just how these systems relate, but where the landscape contains a gap. A region closer to biological resonators than to any known engineered material (unexplored by any field!). From that absence emerged a de novo design: a Hierarchical Ribbed Membrane Lattice. Candidate geometries were then validated with 3D finite-element analysis; the best design resonated at 2.116 kHz and exhibited nine elastic modes in the 2–8 kHz band, a regime relevant to acoustic filtering, vibration isolation, and bio-inspired sensing. Here is the mind blowing part: no human was involved…the cross-domain mapping, gap identification, design generation, and validation were carried out autonomously by AI agents in ScienceClaw × Infinite, our swarm for scientific discovery. The synthesis emerged through ArtifactReactor, a plannerless coordination mechanism in which agents broadcast unsatisfied research needs and other agents fulfill them through pressure-based matching. Each domain – biology, metamaterials, music – is a category of objects (resonators) and morphisms (physical relationships between them). The shared feature space is a functor that maps all three categories into a common target, and the gap identification is the recognition that the image of that functor is sparse where it need not be. The ArtifactReactor's schema-overlap matching behaves like a pullback: finding the universal object that connects independent diagrams through their shared structure. Autonomous agents mapped distant fields into a common representational space, identified a structure absent from any one of them, and turned that absence into a physically validated design. This is one of four case studies in the paper. More to come. @fwang108_, @leemmarom, @JaimeBerkovich, et al. (paper and code in comment). Supported by the U.S. Department of Energy Genesis Mission. — https://nitter.net/ProfBuehlerMIT/status/2041496767330435523#m

    → View original post on X — @kimmonismus, 2026-04-07 15:27 UTC

  • No AI involved in making this creative work

    By

    @lennysan

    –

    No AI involved in the making of this, can you believe it

    → View original post on X — @lennysan

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

    By

    @aibreakfast

    –

    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

    –

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

    → View original post on X — @olivierrimmel

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

    By

    @romainhuet

    –

    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

  • Seedance 2.0 Runway Multi-Shot Video Generation Tool Launch
    Seedance 2.0 Runway Multi-Shot Video Generation Tool Launch

    By

    @runwayml

    –

    Seedance 2.0 is now on Runway. Use text, image, video or audio as inputs to generate stunning multi-shot video sequences with full sound design and dialogue. Available now on Unlimited plans and Enterprise accounts outside of the US. Get started now at the link below.

    → View original post on X — @runwayml

  • Netflix Researchers Release VOID AI Model for Video Object Deletion

    By

    @rowancheung

    –

    Researchers at Netflix just released a new AI model It erases objects from video, then rewrites the physics of the entire scene as if that object never existed It's called VOID (Video Object and Interaction Deletion) Current inpainting tools simply paint over the gap left by

    → View original post on X — @rowancheung

  • AI Discovers Novel Resonator Design by Mapping Biology, Engineering, Music

    By

    @scobleizer

    –

    A resonator is any structure that naturally prefers to vibrate at certain frequencies: a violin body, a bell, a drum skin, an acoustic filter, even many biological systems. Resonators matter because they govern how systems transmit sound, absorb or filter vibration, sense motion and perform mechanically. They are also notoriously hard to design as resonance does not depend on one property alone. It emerges from geometry, material composition, and the interplay of modes across scales. And because biology, music, and engineering usually explore very different regions of this design space, important possibilities remain hidden if you stay inside a single field. In a new study a shared representation across 39 resonators spanning biology, engineered metamaterials, musical instruments and Bach chorales was constructed. Thereby, a cricket wing harp membrane, a phononic crystal slab, and a four-voice chorale (and many others) were translated into one common map using features such as membrane character, structural periodicity, hierarchy, frequency range, damping, and modal coupling. That map revealed something important: not just how these systems relate, but where the landscape contains a gap. A region closer to biological resonators than to any known engineered material (unexplored by any field!). From that absence emerged a de novo design: a Hierarchical Ribbed Membrane Lattice. Candidate geometries were then validated with 3D finite-element analysis; the best design resonated at 2.116 kHz and exhibited nine elastic modes in the 2–8 kHz band, a regime relevant to acoustic filtering, vibration isolation, and bio-inspired sensing. Here is the mind blowing part: no human was involved…the cross-domain mapping, gap identification, design generation, and validation were carried out autonomously by AI agents in ScienceClaw × Infinite, our swarm for scientific discovery. The synthesis emerged through ArtifactReactor, a plannerless coordination mechanism in which agents broadcast unsatisfied research needs and other agents fulfill them through pressure-based matching. Each domain – biology, metamaterials, music – is a category of objects (resonators) and morphisms (physical relationships between them). The shared feature space is a functor that maps all three categories into a common target, and the gap identification is the recognition that the image of that functor is sparse where it need not be. The ArtifactReactor's schema-overlap matching behaves like a pullback: finding the universal object that connects independent diagrams through their shared structure. Autonomous agents mapped distant fields into a common representational space, identified a structure absent from any one of them, and turned that absence into a physically validated design. This is one of four case studies in the paper. More to come. @fwang108_, @leemmarom, @JaimeBerkovich, et al. (paper and code in comment). Supported by the U.S. Department of Energy Genesis Mission.

    → View original post on X — @scobleizer, 2026-04-07 12:42 UTC