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Crazy project: DOMStream Compile React components into UTXOs that form valid transactions👀 Support privacy & batching sessions into a single tx. Powered by Starstream Goal: decentralized frontends!

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Sebastien Guillemot

43,859 subscribers

40,910 Aufrufe • vor 1 Jahr •via X (Twitter)

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Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

React is a way to programmatically create and manage a DOM (html) using Javascipt You can add/remove elementg dynamically based on program state (ex: remove an item from the page after it's bought)

Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

The key insight is that UTXOs can model object lifetimes (keep creating new utxos to represent program contiuations) So you can represent the lifetime of DOM elements as utxos as well!

Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

For example, <button> is added -> create a utxo <button> is removed -> consume utxo props -> constructor state -> datum

Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

Since Starstream supports privacy (via ZK) it means you can run the UI locally and prove statements about your UI without revealing any information (ex: data you entered or navigation history)

Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

Since Starstream supports compression (via ZK) It means any proof about the state of your UI is small! (〜16kbs!)

Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

This means you can easily use DOMStream to create decentralized frontends And do so using tools you know (react) powerered by the same VM as your smart contracts!

Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

It's a crazy idea, but I feel it's a huge improvement over other solutions that require you to learn whole new tools and paradigms here, it's all just react and utxos!

Profilbild von Sebastien Guillemot
Sebastien Guillemotvor 1 Jahr

Starstream is still in active development, and DOMStream is a crazy extension of the concept Want to contribute thoughts or learn more? Join the Starstream Working Group below!

Profilbild von Etherspot 🐞
Etherspot 🐞vor 2 Jahren

Want to build a Web3 app without all the overhead costs? Try TransactionKit, a React toolkit that makes building dApps easy. Integrate cutting-edge account abstraction features in just a few clicks. Try it today 👇

Profilbild von John Santi (johnny5i)
John Santi (johnny5i)vor 1 Jahr

This sounds so brilliant. Returned custom components based on the state of the utxo. My mind is soaring towards RWA registration tokenization referring to specific react modules (a location of memory) I wonder if that could be a thing. Immutable ledger referenc8ng a react object that would only pass if unmodified (validator)

Profilbild von John Santi (johnny5i)
John Santi (johnny5i)vor 1 Jahr

I wonder if a good initial use case might be to build a voting website that uses ZK proofs UTXOs everything is recorded and yet privacy is maintained

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Introducing Batch Bridge, powered by Relay A tool that allow users to bridge or swaps multiple tokens across Ethereum, Base and Arbitrum in a single batch transaction using EIP5792 and EIP7702 🔗 Tool Link : 🔗 Code : Batching very small value tokens may cause issues, so it is best to batch tokens worth at least $1. This rool uses EIP-5792 for batching when supported. Wallets that do not support wallet_sendCalls fall back to sequential transactions. For the true batch transaction experience, use ambire.eth wallet or OKX wallet, they fully support EIP-5792 batch calls, allowing all swaps and approvals to execute in a single transaction.
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Shibarium | SHIB.IO

15,688 Aufrufe • vor 1 Jahr

Can we compile matter - for instance, a pine cone - and derive new active materials, end-to-end from observation to manufacturing? If physical systems can be formalized as composable mathematics, we can point AI that has been shown to resolve long-open mathematical problems at matter itself. Our new work turns bioinspired engineering from analogy into formal compilation: biology and mechanics become explicit, checkable, and executable, so AI reasoning can produce physical designs. This is the first end-to-end demonstration in which a formally compositional multiscale model is carried from a biological hierarchy, through engineered design and fabrication specification, to executable manufacturing code - and then to a physically tested artifact. Background: Humans have long been inspired by biology to advance technology, but this has usually been an ad hoc process rather than a mathematically rigorous one. Natural materials such as pinecones achieve adaptive behavior through mechanisms organized across many scales. Engineering typically translates those mechanisms by analogy: identify a biological principle, build something inspired by it, and validate each new design as a separate case. This can produce remarkable results, but the knowledge does not readily compound. Instead, we represent each scale as a dynamical module with explicit states, stimuli, governing laws, and interfaces. Every scale-to-scale map must preserve the stimulus - response dynamics: evolve the fine-scale system and then map upward, or map upward first and then evolve. The two paths must agree. Because this condition is preserved under composition, locally valid interfaces remain consistent when assembled into the full hierarchy. We then carry that structure into an engineered system, translate the target behavior into a verified fabrication specification, and compile it into G-code: the toolpaths, deposition sequence, temperatures, speeds, and other commands executed by a 3D printer. The intermediate translations are explicit, checkable, and executable rather than completed through an ad hoc handoff. The formal guarantee is that given valid local models and interfaces, their composition remains valid. Whether those models and manufacturing assumptions accurately capture physical reality remains an empirical question. That is why we fabricated and tested the results. We generated four actuator classes by crossing two stimuli - humidity and heat - with two responses: bending and twisting. The fourth, thermal twisting, required no new pipeline and no separate derivation within the framework. It emerged by composing a thermal stimulus module already validated in one case with a twisting module validated in another. The generated G-code produced the intended motion without manual redesign, and all four predictions fell within one experimental standard deviation of the measured response. Why this matters: 1⃣For AI in science, this provides a physics-aware type system against which generative proposals can be checked - and rejected at the interface - before expensive simulation, fabrication, or experiment. It is roughly analogous to proof checking, but for the composition of physical mechanisms. 2⃣For engineering, the accessible design space can scale with a library of validated components rather than with the number of individually derived cases. 3⃣The mathematics, category theory, carries all the way into a physical object on a print bed. This points toward scientific knowledge as executable infrastructure: models that are not only described in papers, but typed, composable, verifiable, and able to compile into experiments. Excellent work led by my student Lee Marom with Skylar Tibbits & Gioele Zardini. Paper published in J. Mech. Phys. Solids along with code, Grasshopper scripts, and manufacturing G-code below.
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Can we compile matter - for instance, a pine cone - and derive new active materials, end-to-end from observation to manufacturing? If physical systems can be formalized as composable mathematics, we can point AI that has been shown to resolve long-open mathematical problems at matter itself. Our new work turns bioinspired engineering from analogy into formal compilation: biology and mechanics become explicit, checkable, and executable, so AI reasoning can produce physical designs. This is the first end-to-end demonstration in which a formally compositional multiscale model is carried from a biological hierarchy, through engineered design and fabrication specification, to executable manufacturing code - and then to a physically tested artifact. Background: Humans have long been inspired by biology to advance technology, but this has usually been an ad hoc process rather than a mathematically rigorous one. Natural materials such as pinecones achieve adaptive behavior through mechanisms organized across many scales. Engineering typically translates those mechanisms by analogy: identify a biological principle, build something inspired by it, and validate each new design as a separate case. This can produce remarkable results, but the knowledge does not readily compound. Instead, we represent each scale as a dynamical module with explicit states, stimuli, governing laws, and interfaces. Every scale-to-scale map must preserve the stimulus - response dynamics: evolve the fine-scale system and then map upward, or map upward first and then evolve. The two paths must agree. Because this condition is preserved under composition, locally valid interfaces remain consistent when assembled into the full hierarchy. We then carry that structure into an engineered system, translate the target behavior into a verified fabrication specification, and compile it into G-code: the toolpaths, deposition sequence, temperatures, speeds, and other commands executed by a 3D printer. The intermediate translations are explicit, checkable, and executable rather than completed through an ad hoc handoff. The formal guarantee is that given valid local models and interfaces, their composition remains valid. Whether those models and manufacturing assumptions accurately capture physical reality remains an empirical question. That is why we fabricated and tested the results. We generated four actuator classes by crossing two stimuli - humidity and heat - with two responses: bending and twisting. The fourth, thermal twisting, required no new pipeline and no separate derivation within the framework. It emerged by composing a thermal stimulus module already validated in one case with a twisting module validated in another. The generated G-code produced the intended motion without manual redesign, and all four predictions fell within one experimental standard deviation of the measured response. Why this matters: 1⃣For AI in science, this provides a physics-aware type system against which generative proposals can be checked - and rejected at the interface - before expensive simulation, fabrication, or experiment. It is roughly analogous to proof checking, but for the composition of physical mechanisms. 2⃣For engineering, the accessible design space can scale with a library of validated components rather than with the number of individually derived cases. 3⃣The mathematics, category theory, carries all the way into a physical object on a print bed. This points toward scientific knowledge as executable infrastructure: models that are not only described in papers, but typed, composable, verifiable, and able to compile into experiments. Excellent work led by my student Lee Marom with Skylar Tibbits & Gioele Zardini. Paper published in J. Mech. Phys. Solids along with code, Grasshopper scripts, and manufacturing G-code below.

Markus J. Buehler

128,390 Aufrufe • vor 1 Monat

Introducing Wan2.6 - A native multimodal model that turns your ideas into breathtaking videos and images! · Starring: Cast characters from reference videos into new scenes. Support human or human-like figures, enabling complex multi-person and human-object interactions with appearance and voice consistency. · Intelligent Multi-shot Narrative: Turn simple prompts into auto-storyboarded, multi-shot videos. Maintain visual consistency and upgrade storytelling from single shots to rich narratives. · Native A/V Sync: Generate multi-speaker dialogue with natural lip-sync and studio-quality audio. It doesn’t just look real - it sounds real. · Cinematic Quality: 15s 1080p HD generation with comprehensive upgrades to instruction adherence, motion physics, and aesthetic control. · Advanced Image Synthesis and Editing: Deliver cinematic photorealism with precise control over lens and lighting. Support multi-image referencing for commercial-grade consistency and faithful aesthetic transfer. · Storytelling with Structure: Generate interleaved texts and images powered by real-world knowledge and reasoning capabilities, enabling hierarchical and structured visual narratives.
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Introducing Wan2.6 - A native multimodal model that turns your ideas into breathtaking videos and images! · Starring: Cast characters from reference videos into new scenes. Support human or human-like figures, enabling complex multi-person and human-object interactions with appearance and voice consistency. · Intelligent Multi-shot Narrative: Turn simple prompts into auto-storyboarded, multi-shot videos. Maintain visual consistency and upgrade storytelling from single shots to rich narratives. · Native A/V Sync: Generate multi-speaker dialogue with natural lip-sync and studio-quality audio. It doesn’t just look real - it sounds real. · Cinematic Quality: 15s 1080p HD generation with comprehensive upgrades to instruction adherence, motion physics, and aesthetic control. · Advanced Image Synthesis and Editing: Deliver cinematic photorealism with precise control over lens and lighting. Support multi-image referencing for commercial-grade consistency and faithful aesthetic transfer. · Storytelling with Structure: Generate interleaved texts and images powered by real-world knowledge and reasoning capabilities, enabling hierarchical and structured visual narratives.

Wan

3,847,954 Aufrufe • vor 8 Monaten

Welcome to Scalia Infrastructure! At the heart of our mission is to democratize and scale decentralized infrastructure, ensuring that censorship resistance, enhanced security, and the eradication of single points of failure are not privileges but rights accessible to all. Imagine a world where your digital life is safeguarded by the collective power of a community, not by the confines of centralized entities. With Scalia, not only do you tap into a world of decentralized resources, but you also unlock a treasure trove of rewards: - Earn and claim rewards based on $SCALE holdings - Enjoy exclusive discounts and hardware giveaways - Become a vital part of a thriving DePIN ecosystem $SCALE isn't just a token; it's the lifeblood of the DePIN sector, accelerating growth and fostering a thriving community. Our robust rewards system ensures that as we grow, you grow. Integrate your resources with Scalia, earn rewards, and claim them based on your $SCALE holdings. Enjoy exclusive discounts, hardware giveaways, and more, as we continually boost our network, empowering the most crucial element of any decentralized project – our community. Join Scalia, Join the DePIN revolution, Stay Empowered. TG:
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Welcome to Scalia Infrastructure! At the heart of our mission is to democratize and scale decentralized infrastructure, ensuring that censorship resistance, enhanced security, and the eradication of single points of failure are not privileges but rights accessible to all. Imagine a world where your digital life is safeguarded by the collective power of a community, not by the confines of centralized entities. With Scalia, not only do you tap into a world of decentralized resources, but you also unlock a treasure trove of rewards: - Earn and claim rewards based on $SCALE holdings - Enjoy exclusive discounts and hardware giveaways - Become a vital part of a thriving DePIN ecosystem $SCALE isn't just a token; it's the lifeblood of the DePIN sector, accelerating growth and fostering a thriving community. Our robust rewards system ensures that as we grow, you grow. Integrate your resources with Scalia, earn rewards, and claim them based on your $SCALE holdings. Enjoy exclusive discounts, hardware giveaways, and more, as we continually boost our network, empowering the most crucial element of any decentralized project – our community. Join Scalia, Join the DePIN revolution, Stay Empowered. TG:

Scalia

42,575 Aufrufe • vor 2 Jahren