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Privacy matters most where data matters most. ⬟ Healthcare data cannot leak. Regulated industries require private inference by default, not policies layered on later. Encrypted computation is what makes real compliance possible. Build where compliance is native.

Nesa

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25,934 просмотров • 7 месяцев назад •via X (Twitter)

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Prividium is the only platform purpose-built for Institutions that demand privacy, compliance and control of their data. 🔐 Privacy with public proofs 🧾 Built-in compliance 🏢 Enterprise control 🌏 Direct connectivity Private where it matters. Connected where it counts.

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🧵 Understanding Zama; the future of privacy tech & homomorphic encryption 1️⃣ Zama is pioneering fully homomorphic encryption (FHE). A breakthrough that lets you compute on encrypted data without decrypting it. 🔐 That means total privacy, even the system running your data can’t see it. 2️⃣ Why it matters: Right now, cloud apps, AI models, and databases must access your raw data to work. FHE changes that. your data stays private while still usable. 3️⃣ Zama builds open-source FHE tools for developers, turning advanced cryptography into practical products for AI, blockchain, and Web3. 4️⃣ Imagine: •AI that learns without reading your secrets 🤖 •Blockchain transactions with zero data leaks •Cloud apps that never see your info 5️⃣ Zama’s mission: Privacy should be the default, not an option. They’re making privacy-preserving tech simple, scalable, and open for everyone. 🔚 In a world obsessed with data, Zama might just be building the encryption layer of the future internet. 🌐

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Grayscale

16,856 просмотров • 11 месяцев назад

TL;DR - Privacy on public blockchains has historically been fragmented and episodic. Umbra introduces persistent, expressive privacy by default. - Umbra is a private financial layer on Solana, enabling private transfers, swaps, balances, and yield within a continuous shielded environment. - Umbra combines client-side zero-knowledge proofs for anonymity with MPC for confidentiality - MPC enables confidential balances via Encrypted Token Accounts (ETAs), hiding balances and transfer amounts - Privacy strength depends not only on cryptography, but on anonymity set size and user behavior. - Umbra treats anonymity sets as a first-class metric and designs the product to minimize behavioral privacy failures. - A multi-purpose shielded pool allows funds to remain private across transfers, swaps, and yield, compounding privacy over time. - The Umbra SDK allows wallets and applications to integrate private transfers, swaps, and balances, feeding activity into a shared shielded pool. - Swaps execute via public liquidity venues while identity, balances, and intent remain unlinkable. - Users can earn yield on shielded assets, incentivizing longer time in the private environment. - Umbra mitigates exit-related privacy risks through product design, including anonymity indicators, configurable unshielding delays, and confidential balances. - UTXO-based shielded systems suffer from performance decay as balances fragment into many notes over time, increasing scan and aggregation costs. - Umbra eliminates this bottleneck by consolidating balances into Encrypted Token Accounts (ETAs), using UTXOs only at the anonymity boundary. The result is encrypted balances with stable, high-performance transfers even as activity scales. - Compliance is addressed through proactive screening against risk databases and opt-in selective disclosure via read-only viewing keys. - Umbra was launched via MetaDAO as an ownership coin, with governance and economic policy determined by token holders through futarchy. - Umbra is not a mixer or a single feature, but a sovereign privacy domain with its own private state and internal economy. - Umbra is Hopecore for Privacy. Thank you all for reading!

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milian

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Silencio has surpassed 1 million on-chain devices on peaq This is the live count of real contributors using their smartphones to capture and stream the physical world into digital infrastructure. Each device is opt-in, privacy-preserving, and individually rewarded in $SLC. Together, these contributors have recorded more than 10.6 million hours of real-world acoustic signal. The network spans 190 countries and has generated over 38.8 Billion environmental datapoints. All of it is live. All of it is on-chain. Silencio represents a deployed DePIN system operating at global scale. Its data is already integrated into major enterprise marketplaces. Its token economy is active, deflationary, and fully aligned with participation. This milestone is not just about numbers. It is about trust, coordination, and measurable impact. It proves that decentralized networks can scale without compromising on quality, compliance, or utility. Built on peaq. Secured by $SLC and the Blocksound Foundation. Powered by people. This is not the future of data infrastructure. It is already in motion.

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22,863 просмотров • 1 год назад

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

Akshay 🚀

36,317 просмотров • 4 месяцев назад

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

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23,748 просмотров • 2 месяцев назад

⚡️ THE OBSERVATION DECK ⚡️ Above the canopy, beyond the waterfalls, one Operator watches what no map can show. Twin planetary cores suspended in silence — one breathing life, one pulsing with raw data. Screens flicker with the heartbeat of the Biosphere. Floating gardens grow where code meets soil. This is not a control room. This is where the next world is monitored before it becomes real. 🧬⚡ Exclusively on Crypto.com NFT × Cronos #Synthtopia #BIOSPHERE #CroFam #cryptocom

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SYNTHTOPIA

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Today we’re releasing the $XNT SDK (Node.js). This is the world’s first zk-STARK based Software Development Kit. This is a core milestone for building private, non-custodial applications on XNT. The XNT SDK provides the core tools needed to build applications that interact with the network without custody. This includes offline transaction signing, so private keys never leave the client or trusted environment. Why this matters: Most privacy apps today still depend on custodial backends, trusted relayers, or opaque infrastructure. The XNT SDK enables applications where users remain in full control, end-to-end. The SDK is open source and intended as foundational infrastructure for: • wallet developers • application builders • tooling teams • anyone building on private execution Builders, the next phase is in your hands. We’ll continue improving the SDK and releasing updates as the ecosystem grows. If you’re building privacy preserving applications and care about non-custodial design, this is for you! GitHub:

Today we’re releasing the $XNT SDK (Node.js). This is the world’s first zk-STARK based Software Development Kit. This is a core milestone for building private, non-custodial applications on XNT. The XNT SDK provides the core tools needed to build applications that interact with the network without custody. This includes offline transaction signing, so private keys never leave the client or trusted environment. Why this matters: Most privacy apps today still depend on custodial backends, trusted relayers, or opaque infrastructure. The XNT SDK enables applications where users remain in full control, end-to-end. The SDK is open source and intended as foundational infrastructure for: • wallet developers • application builders • tooling teams • anyone building on private execution Builders, the next phase is in your hands. We’ll continue improving the SDK and releasing updates as the ecosystem grows. If you’re building privacy preserving applications and care about non-custodial design, this is for you! GitHub:

Neptune Privacy

16,493 просмотров • 6 месяцев назад

Driven by a UK Government push to open up transport data and boost public transport use nationwide, Google Maps has officially integrated live public transport tracking. By mandating that operators share their live GPS data, tech apps can now let you literally watch your specific bus moving along the map in real-time. As seen in the screenshot above, you can tap on your route (like the 207 towards White City) and see exactly where the bus is on the road, how many minutes away it is, and when the data was last updated. No more relying on broken countdown boards. No more running for a “ghost bus” that never actually shows up. No more standing in the rain guessing if you have time to grab a coffee. Have you noticed this government-backed feature on your phone yet? And more importantly... which West London bus route is the most unreliable and needs this the most? Let us know below #UB1UB2 #London #Southall #Hayes #Ealing

Driven by a UK Government push to open up transport data and boost public transport use nationwide, Google Maps has officially integrated live public transport tracking. By mandating that operators share their live GPS data, tech apps can now let you literally watch your specific bus moving along the map in real-time. As seen in the screenshot above, you can tap on your route (like the 207 towards White City) and see exactly where the bus is on the road, how many minutes away it is, and when the data was last updated. No more relying on broken countdown boards. No more running for a “ghost bus” that never actually shows up. No more standing in the rain guessing if you have time to grab a coffee. Have you noticed this government-backed feature on your phone yet? And more importantly... which West London bus route is the most unreliable and needs this the most? Let us know below #UB1UB2 #London #Southall #Hayes #Ealing

UB1UB2 West London (Southall)

21,165 просмотров • 3 месяцев назад

Many immigrants claim that white Brits are racist. But here’s the reality I witnessed: A man collapsed on the street-an immigrant. And who rushed to help? Ordinary British people. No questions about his background.( legal, illegal, rapist or high on drug’s) No judgement about his skin colour. They stayed with him, cared for him, and called an ambulance 🚑 until help arrived. That’s real British values. Humanity first. Compassion first. Not division. Not hate. This is what truly makes Britain great, people who stand up for each other when it matters most, regardless of who you are or where you come from. Respect 🫡✊

Many immigrants claim that white Brits are racist. But here’s the reality I witnessed: A man collapsed on the street-an immigrant. And who rushed to help? Ordinary British people. No questions about his background.( legal, illegal, rapist or high on drug’s) No judgement about his skin colour. They stayed with him, cared for him, and called an ambulance 🚑 until help arrived. That’s real British values. Humanity first. Compassion first. Not division. Not hate. This is what truly makes Britain great, people who stand up for each other when it matters most, regardless of who you are or where you come from. Respect 🫡✊

Harman Singh Kapoor

154,398 просмотров • 4 месяцев назад

$EPIC Is Now Live on One of Southeast Asia’s and Thailand’s Leading Fiat Exchange, Bitkub.com Epic has officially launched on a major regulated exchange with 5M+ users and billions in annual volume, unlocking direct THB access in one of Asia’s most institutionally and retail-driven markets. What this activates: → EPIC/THB trading now live → Seamless fiat on-ramps for millions of local users → Native entry into a market where 80%+ of activity is retail → Regional campaigns, liquidity programs & activations underway Stay tuned for more! Trade now →

$EPIC Is Now Live on One of Southeast Asia’s and Thailand’s Leading Fiat Exchange, Bitkub.com Epic has officially launched on a major regulated exchange with 5M+ users and billions in annual volume, unlocking direct THB access in one of Asia’s most institutionally and retail-driven markets. What this activates: → EPIC/THB trading now live → Seamless fiat on-ramps for millions of local users → Native entry into a market where 80%+ of activity is retail → Regional campaigns, liquidity programs & activations underway Stay tuned for more! Trade now →

EPIC Travel

27,154 просмотров • 10 месяцев назад

In 2025, the AgentFlayer exploit highlighted a new category of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.

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17,038 просмотров • 4 месяцев назад

Tokenized Stocks: Coming to RWAX Next Month Real-world asset tokenization is projected to reach trillions in value over the next few years. Stocks are the most understood and traded form of 'real assets' - exceeding the trade value of real estate. Despite the momentum, most of the space is still dominated by institutional players with limited access for everyday users. That’s where RWAX comes in. By building a Tokenized Stocks Trading Terminal that offers diversified exposure to real-world assets on-chain, RWAX makes it simple for anyone to get involved in this emerging category. The countdown to launch starts now.

Tokenized Stocks: Coming to RWAX Next Month Real-world asset tokenization is projected to reach trillions in value over the next few years. Stocks are the most understood and traded form of 'real assets' - exceeding the trade value of real estate. Despite the momentum, most of the space is still dominated by institutional players with limited access for everyday users. That’s where RWAX comes in. By building a Tokenized Stocks Trading Terminal that offers diversified exposure to real-world assets on-chain, RWAX makes it simple for anyone to get involved in this emerging category. The countdown to launch starts now.

RWAX $APP

45,709 просмотров • 1 год назад