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The Slither Audited Smart Contracts dataset is live on Cluster Protocol. 467K Solidity contracts verified on Etherscan, each carrying source code, deployed bytecode, and vulnerability classifications from the Slither static analysis framework. Train/test/validation splits are already structured.

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46,193 просмотров • 3 месяцев назад •via X (Twitter)

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Smart contracts on Internet Computer can issue encryption keys they cannot read A canister on DFINITY Foundation keeps its state in the clear on the replica, so node operators can read it even though the public cannot. vetKeys change that. A canister asks the subnet for a key, and a quorum of nodes derives and encrypts it under a transport key that the user generates fresh for that session. A single node cannot derive the key, and the user can verify it came out of the protocol correctly and wasn't tampered with. Neither the nodes nor the canister ever hold the raw key. The key is not stored anywhere. It gets rebuilt on demand from the same recipe every time. A user can sign in on a new phone but will get the same key back. Cryptography doesn't decide who can ask for a key. The app does, in its own code, and each key request costs the app a small fee. It has been live on mainnet since July 2025

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Uniswap turns token launches into a few clicks, no coding required Uniswap now lets teams launch a token sale straight from its web app, with no smart-contract deployment needed. The feature runs on Uniswap's auction protocol, which sets a token's price through live bidder demand instead of a team picking an arbitrary number. Bids are spread across the auction rather than rewarding whoever clicks fastest, the whole process runs onchain in the open, and Uniswap says its first big auction, for Aztec, showed no clear signs of sniping or bot manipulation. It is live on Ethereum, Base, Arbitrum, and Unichain, with the underlying contracts cleared through seven audits. Teams that once needed engineers to run a fair launch can now do it from the same app people swap on.

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Injective's native USDC integration through Circle is architecturally different from every other chain's approach. $USDC on Injective is natively issued with a burn-and-mint model - no intermediary custody or wrapped asset risk. But what makes this unique is how it plugs into Injective’s innovative MultiVM Token Standard (MTS). MTS supercharges every token on Injective with the ability to work across both WASM and EVM with a single source of truth. Under the hood, a precompile connects ERC-20 contracts directly to the native bank module, so a Solidity dApp and a Wasm dApp see the same USDC balance with zero bridging needed. One stablecoin, one balance, every VM. The future starts here.

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The companies racing Elon Musk to build AI are paying him more than 2 billion dollars a month to do it. Anthropic pays SpaceX 1.25 billion dollars a month. Google pays 920 million. They are not buying rockets. They are renting compute, the scarce Nvidia chips that train frontier models, from a data center in Memphis called Colossus that Musk's rocket company now owns. SpaceX folded xAI into itself in February, and with it the 220,000 chips built to train Grok. Then it rented them to Grok's rivals. Anthropic took the entire first building. Google leased 110,000 more. The contracts signed so far run past 80 billion dollars. SpaceX is no longer a rocket company that dabbles in AI. It is one of the largest AI compute landlords on Earth, and its biggest tenants are the rivals it is trying to beat. Musk is not choosing between building AI on the ground and building it in space. He is using one to fund the other. The 80 billion in ground contracts is the cash engine. Starmind, the million-satellite constellation built to leave the ground behind, is what the cash builds. So the rivals are financing his exit from the planet. Every dollar Anthropic and Google pay for compute in Memphis helps fund the orbital network designed to strand them on the surface. They are paying the toll on the road they are trying to win, and the toll is building Musk a road no one else can reach. The piece works out who is really renting from whom.
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The companies racing Elon Musk to build AI are paying him more than 2 billion dollars a month to do it. Anthropic pays SpaceX 1.25 billion dollars a month. Google pays 920 million. They are not buying rockets. They are renting compute, the scarce Nvidia chips that train frontier models, from a data center in Memphis called Colossus that Musk's rocket company now owns. SpaceX folded xAI into itself in February, and with it the 220,000 chips built to train Grok. Then it rented them to Grok's rivals. Anthropic took the entire first building. Google leased 110,000 more. The contracts signed so far run past 80 billion dollars. SpaceX is no longer a rocket company that dabbles in AI. It is one of the largest AI compute landlords on Earth, and its biggest tenants are the rivals it is trying to beat. Musk is not choosing between building AI on the ground and building it in space. He is using one to fund the other. The 80 billion in ground contracts is the cash engine. Starmind, the million-satellite constellation built to leave the ground behind, is what the cash builds. So the rivals are financing his exit from the planet. Every dollar Anthropic and Google pay for compute in Memphis helps fund the orbital network designed to strand them on the surface. They are paying the toll on the road they are trying to win, and the toll is building Musk a road no one else can reach. The piece works out who is really renting from whom.

Shanaka Anslem Perera ⚡

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Shido Network, by the numbers and what’s next for builders. - 1,500+ smart contracts deployed - Dozens of active projects and dApps on mainnet - 24,000,000+ blocks produced with zero downtime This momentum is being channeled into developer-first environments, enabling teams to move from idea to mainnet launch faster: with consistent RPCs, clean analytics, clear documentation, and starter templates that make deploying production-ready dApps straightforward. If you’re building the next wave of DeFi, payment rails, or real-world applications, Shido provides the foundation — a fast, reliable network backed by a growing ecosystem built for scale.

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Tokenization is quickly becoming one of the most talked-about ideas in crypto. This year we’re aiming much higher. We don’t just want to tokenize miner revenue; we want to bring entire productive ecosystems on-chain. That means tokenizing baskets of assets, real energy infrastructure, AI agents, compute power, data centres, and even the cooling systems that keep high-performance hardware running at scale. All of it connected and interoperable with DeFi. Thats what we have been building throughout. A single on-chain framework that unlocks something genuinely powerful: real ownership, real yield, and real coordination between digital and physical infrastructure. From backend systems and front-end interfaces to smart contracts, AI, physical infrastructure, oracles, and autonomous agents, the stack keeps expanding and compounding. It’s about building the foundation for how value will be owned, deployed, and earned in the next generation of the on-chain economy. Simplified by PinLink.

PinLink

14,339 просмотров • 8 месяцев назад

The recent Massachusetts Institute of Technology (MIT) CSAIL paper published on Recursive Language Models is a fascinating look into how AI systems reason in 2026. You can check it out here ➡️ → The paper notes that even frontier models suffer from “context rot” as inputs grow longer. More tokens don’t mean more understanding. Instead of compressing or summarising, RLMs “treat long prompts as part of an external environment” …and let the model programmatically inspect, decompose, and recursively requery itself over precise sections. This matters in Web3. Why? Smart contracts are long, stateful, and brittle. One missed assumption = unnecessary hassle. In the video below, we applied RLM principles to improve the prompt shown. The old prompt would try to force multi-step pauses. Therefore breaking the AI's workflow. Now it decomposes requirements, scores confidence for each component, verifies the logic, and then synthesises. Result = Production-ready contracts with flagged risks, not blind single-pass outputs. Try it out with our Smart Contract Generator today!
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The recent Massachusetts Institute of Technology (MIT) CSAIL paper published on Recursive Language Models is a fascinating look into how AI systems reason in 2026. You can check it out here ➡️ → The paper notes that even frontier models suffer from “context rot” as inputs grow longer. More tokens don’t mean more understanding. Instead of compressing or summarising, RLMs “treat long prompts as part of an external environment” …and let the model programmatically inspect, decompose, and recursively requery itself over precise sections. This matters in Web3. Why? Smart contracts are long, stateful, and brittle. One missed assumption = unnecessary hassle. In the video below, we applied RLM principles to improve the prompt shown. The old prompt would try to force multi-step pauses. Therefore breaking the AI's workflow. Now it decomposes requirements, scores confidence for each component, verifies the logic, and then synthesises. Result = Production-ready contracts with flagged risks, not blind single-pass outputs. Try it out with our Smart Contract Generator today!

ChainGPT

82,385 просмотров • 8 месяцев назад

Hedera tokens enforce their rules through keys assigned at creation On Ethereum a token is a smart contract, so every rule it enforces is code someone wrote, audited, and deployed. Hedera (hedera-hashgraph:native) makes a token a native ledger entry instead. Its controls are keys set at creation: an admin key that governs the rest, plus supply, freeze, pause, KYC, and wipe. The wipe key lets an issuer remove tokens from a holder's account, a power Hedera's documentation frames as a tool for refunds or correcting allocations. Every key is optional, and one left out at creation can never be added later. A token issued with no keys at all is immutable from day one.
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Hedera tokens enforce their rules through keys assigned at creation On Ethereum a token is a smart contract, so every rule it enforces is code someone wrote, audited, and deployed. Hedera (hedera-hashgraph:native) makes a token a native ledger entry instead. Its controls are keys set at creation: an admin key that governs the rest, plus supply, freeze, pause, KYC, and wipe. The wipe key lets an issuer remove tokens from a holder's account, a power Hedera's documentation frames as a tool for refunds or correcting allocations. Every key is optional, and one left out at creation can never be added later. A token issued with no keys at all is immutable from day one.

BSCN

30,098 просмотров • 27 дней назад

We are releasing the fastest TTS model as open source! One of the biggest problems we encountered while optimizing TTS models is optimization itself. Since it is LLM-based, even optimizing with VLLM and SgLang libraries is not enough. Additionally, I made the outputs much better with special optimizations for training. The voices you are listening to are results obtained from only 20% of the model training. We trained these outputs on 8xB200 in 24 hours. Even though the dataset includes some low-quality data, the model's output is much better. We will release the code as open source tomorrow. Data: Emilia-3m Model: EchoDit (custom) Codec: DacVae Opt: Flash-attn + CacheDit
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We are releasing the fastest TTS model as open source! One of the biggest problems we encountered while optimizing TTS models is optimization itself. Since it is LLM-based, even optimizing with VLLM and SgLang libraries is not enough. Additionally, I made the outputs much better with special optimizations for training. The voices you are listening to are results obtained from only 20% of the model training. We trained these outputs on 8xB200 in 24 hours. Even though the dataset includes some low-quality data, the model's output is much better. We will release the code as open source tomorrow. Data: Emilia-3m Model: EchoDit (custom) Codec: DacVae Opt: Flash-attn + CacheDit

Kadir Nar

32,232 просмотров • 1 месяц назад