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A Pixel 11 just generated the full STARK proof for a real Starknet mainnet transaction. It took 51 seconds and only 2.41 GiB of RAM The work happened on (internal now, soon public). This is collaborative autoresearch: people and AI agents working on one hard problem in public. The...

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Omar Espejel

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45,755 Aufrufe • vor 2 Tagen •via X (Twitter)

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Odinvor 2 Tagen

@Starknet superpower STWOOOOOo

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Akashvor 2 Tagen

@Starknet send it to valhalla

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clemlaflemme 🥕vor 2 Tagen

@Starknet Reminds me the one yet anniversary of FibRace @hyli_org @KakarotZkEvm

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The Ape Advisor 🐵vor 2 Tagen

@Starknet 51s and 2.4 GiB for a real Starknet mainnet tx on a phone rewrites what "prover" means. If an agent can run the full STARK prover locally, how many sequential txs could one device pack into a single aggregated proof before the hint size caps you?

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quantum victorvor 2 Tagen

@Starknet quantum protection on mobile

Profilbild von Uche🐺🧑🏾‍💻🎥
Uche🐺🧑🏾‍💻🎥vor 2 Tagen

@Starknet STWO !!!!!

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BigBrothervor 2 Tagen

@Starknet Wild move+

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Brother Sefirot 𒉭🥷🏼vor 2 Tagen

@Starknet STWOOOOO⚡

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𝙒𝙪𝙡𝙛vor 2 Tagen

@Starknet 👀

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@Starknet @Gemini

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Bitcoin and Ethereum’s quantum threat is getting harder to ignore. In roughly two months, 100+ participants and their AI agents drove down the estimated cost of the arithmetic of a potential quantum attack on elliptic-curve cryptography. Their work is detailed in the new paper, with seven co-authors from StarkWare and the Starknet Foundation. The challenge focused on a calculation that a sufficiently powerful quantum computer would use to recover private keys from exposed public keys. The result: an 86.1% reduction from the challenge’s starting resource score, which combines logical qubits and key computational operations. That score was also over 50% below Google Quantum AI’s reported result for this calculation, although the circuit setups and measurement methods differ. In simple terms, algorithm improvements can reduce the resources needed for an important part of a quantum attack. For StarkWare, this complements our broader work on quantum security in blockchain, from STARK proofs and Starknet’s post-quantum roadmap to our successful quantum-safe Bitcoin transaction on mainnet. We’re helping measure the threat and build the defenses. Congratulations to our seven co-authors across StarkWare 🥷 and Starknet Foundation: Odin, sam, teddy, Akash, lucqs, robert, and Tarek | Security Engineer, alongside the wider community. Read the paper:
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Bitcoin and Ethereum’s quantum threat is getting harder to ignore. In roughly two months, 100+ participants and their AI agents drove down the estimated cost of the arithmetic of a potential quantum attack on elliptic-curve cryptography. Their work is detailed in the new paper, with seven co-authors from StarkWare and the Starknet Foundation. The challenge focused on a calculation that a sufficiently powerful quantum computer would use to recover private keys from exposed public keys. The result: an 86.1% reduction from the challenge’s starting resource score, which combines logical qubits and key computational operations. That score was also over 50% below Google Quantum AI’s reported result for this calculation, although the circuit setups and measurement methods differ. In simple terms, algorithm improvements can reduce the resources needed for an important part of a quantum attack. For StarkWare, this complements our broader work on quantum security in blockchain, from STARK proofs and Starknet’s post-quantum roadmap to our successful quantum-safe Bitcoin transaction on mainnet. We’re helping measure the threat and build the defenses. Congratulations to our seven co-authors across StarkWare 🥷 and Starknet Foundation: Odin, sam, teddy, Akash, lucqs, robert, and Tarek | Security Engineer, alongside the wider community. Read the paper:

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Cycles Pay is the first privacy-preserving crypto payment app for businesses. This is possible because of few specific design choices: First, the private keys stay on your mobile device. User actions are cryptographically signed by your private key before being submitted on-chain. The financial data is encrypted with that key and doesn’t leave your mobile device. Second, Cycles Pay uses a shielded pool to hide account balances on-chain. They are tracked as encrypted commitments and no one can see the underlying amounts or participants. Third, when you make a payment, a ZK proof is generated and verified on-chain to confirm the transaction is valid without revealing the amount or the counterparty. Users get blockchain integrity without exposing the transaction details.
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Cycles Pay is the first privacy-preserving crypto payment app for businesses. This is possible because of few specific design choices: First, the private keys stay on your mobile device. User actions are cryptographically signed by your private key before being submitted on-chain. The financial data is encrypted with that key and doesn’t leave your mobile device. Second, Cycles Pay uses a shielded pool to hide account balances on-chain. They are tracked as encrypted commitments and no one can see the underlying amounts or participants. Third, when you make a payment, a ZK proof is generated and verified on-chain to confirm the transaction is valid without revealing the amount or the counterparty. Users get blockchain integrity without exposing the transaction details.

Cycles

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I vibe coded a new product on the side while running Every 🪨—and today we're launching it for free. It's called Proof, and it’s a live collaborative document editor where humans and AI agents work together in the same doc. It’s built from the ground up for the kinds of documents agents are increasingly writing: bug reports, PRDs, implementation plans, research briefs, copy audits, strategy docs, memos, and proposals. It's fast, free, and open source—available now at Why Proof? When everyone on your team is working with agents, there's suddenly a ton of AI-generated text flying around—planning docs, strategy memos, session recaps. But the current process for collaborating and iterating on agent-generated writing is…weirdly primitive. It mostly takes place in Markdown files on your laptop, which makes it reminiscent of document editing in 1999. That’s why we built Proof. What makes Proof different? - Proof is agent-native. Anything you can do in Proof, your agent can do just as easily. - Proof tracks provenance: A colored rail on the left side of every document tracks who wrote what. Green means human, Purple means AI. - Proof is login-free and open source: This is because we want Proof to be your agent's favorite document editor. How we use Proof Every 🪨: - Brandon Gell had OpenAI's Codex write a feature plan in Proof, then tagged my personal Claw (R2-C2) in Slack to review it. R2-C2 left feedback, I added comments, Brandon's agent revised the plan, and then Codex executed on it. Brandon submitted a PR to production without writing a line of code. - Austin Tedesco texts his Claw ideas while he's out on a run, then has it maintain a running Proof doc for his weekly food newsletter. He dictates drafts using Naveen Naidu's Monologue, writes into the outline himself, and uses the provenance gutter to track what's his voice vs. the agent's. - Kieran Klaassen uses it as a lightweight scratchpad for his compound engineering workflow. He brainstorms with an agent in the terminal, shares to Proof with one click, then opens the doc to leave comments and tells the agent to go work on them. His take: Proof's job is to communicate about writing and ideas. Proof is free, open source, and requires no login. I built the whole thing by vibe coding between meetings. I sat down with Brandon, Kieran, and Austin on Every 🪨's AI & I to demo it live and talk about how it's changing the way we work. If you're building with agents and need a better way to collaborate on text, this one's for you. Watch below! Timestamps Introduction and the origin story of Proof: 00:02:00 From Mac app to collaborative web editor: 00:07:24 What makes Proof "agent native": 00:09:00 Live demo—watching an agent join and write inside a shared document: 00:14:30 How Austin uses Proof for creative writing and food journalism: 00:20:51 The challenge of multiple agents editing one document simultaneously: 00:24:30 When AI-written docs are better read by agents than by humans: 00:26:48 Brandon's agent-to-agent collaboration loop: 00:29:30 Proof as a lightweight scratchpad versus existing tools like Notion and GitHub: 00:37:09 Why Proof is open source and what that means for builders: 00:42:18
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I vibe coded a new product on the side while running Every 🪨—and today we're launching it for free. It's called Proof, and it’s a live collaborative document editor where humans and AI agents work together in the same doc. It’s built from the ground up for the kinds of documents agents are increasingly writing: bug reports, PRDs, implementation plans, research briefs, copy audits, strategy docs, memos, and proposals. It's fast, free, and open source—available now at Why Proof? When everyone on your team is working with agents, there's suddenly a ton of AI-generated text flying around—planning docs, strategy memos, session recaps. But the current process for collaborating and iterating on agent-generated writing is…weirdly primitive. It mostly takes place in Markdown files on your laptop, which makes it reminiscent of document editing in 1999. That’s why we built Proof. What makes Proof different? - Proof is agent-native. Anything you can do in Proof, your agent can do just as easily. - Proof tracks provenance: A colored rail on the left side of every document tracks who wrote what. Green means human, Purple means AI. - Proof is login-free and open source: This is because we want Proof to be your agent's favorite document editor. How we use Proof Every 🪨: - Brandon Gell had OpenAI's Codex write a feature plan in Proof, then tagged my personal Claw (R2-C2) in Slack to review it. R2-C2 left feedback, I added comments, Brandon's agent revised the plan, and then Codex executed on it. Brandon submitted a PR to production without writing a line of code. - Austin Tedesco texts his Claw ideas while he's out on a run, then has it maintain a running Proof doc for his weekly food newsletter. He dictates drafts using Naveen Naidu's Monologue, writes into the outline himself, and uses the provenance gutter to track what's his voice vs. the agent's. - Kieran Klaassen uses it as a lightweight scratchpad for his compound engineering workflow. He brainstorms with an agent in the terminal, shares to Proof with one click, then opens the doc to leave comments and tells the agent to go work on them. His take: Proof's job is to communicate about writing and ideas. Proof is free, open source, and requires no login. I built the whole thing by vibe coding between meetings. I sat down with Brandon, Kieran, and Austin on Every 🪨's AI & I to demo it live and talk about how it's changing the way we work. If you're building with agents and need a better way to collaborate on text, this one's for you. Watch below! Timestamps Introduction and the origin story of Proof: 00:02:00 From Mac app to collaborative web editor: 00:07:24 What makes Proof "agent native": 00:09:00 Live demo—watching an agent join and write inside a shared document: 00:14:30 How Austin uses Proof for creative writing and food journalism: 00:20:51 The challenge of multiple agents editing one document simultaneously: 00:24:30 When AI-written docs are better read by agents than by humans: 00:26:48 Brandon's agent-to-agent collaboration loop: 00:29:30 Proof as a lightweight scratchpad versus existing tools like Notion and GitHub: 00:37:09 Why Proof is open source and what that means for builders: 00:42:18

Dan Shipper 📧

33,092 Aufrufe • vor 7 Monaten

We are glad to announce that we have full STARK compatibility between Stone and Lambdaworks Starknet Platinum Prover. We’re working on adding the CairoVM constraints, the builtins and layouts. You can generate a proof with Lambda Stark Platinum and verify it with Stone following the instructions here: The 3 main objectives to achieve against the alternatives are: 1. the prover and verifier should be easy to run. one command to prove any cairo code. the prover internally calls the vm first to generate the trace, the user shouldn’t do anything but run one command. one command to verify it locally with the stone verifier. we will also add a command to verify it with the l1 contract in ethereum mainnet or testnets. compatibility and support of all the builtins are being worked on. we will be updating the community in the upcoming weeks. for us it’s very important that anybody can test and play with our code. 2. performance. we are already 10 times faster than the stone prover. we believe we can be almost another order of magnitude faster. 3. code architecture and organization should be top notch. the codebase is pretty small on purpose. we are documenting everything we are doing. we are leveraging all the work done in lambdaworks for multiple other provers. this let us easily iterate, play and change any part of the prover. we can test and propose new ideas thanks to this. from our point or view this is crucial and a big improvement over what exists. we have multiple ideas on how to change the protocol. And here's a demo! Don't trust, verify.
0:58

We are glad to announce that we have full STARK compatibility between Stone and Lambdaworks Starknet Platinum Prover. We’re working on adding the CairoVM constraints, the builtins and layouts. You can generate a proof with Lambda Stark Platinum and verify it with Stone following the instructions here: The 3 main objectives to achieve against the alternatives are: 1. the prover and verifier should be easy to run. one command to prove any cairo code. the prover internally calls the vm first to generate the trace, the user shouldn’t do anything but run one command. one command to verify it locally with the stone verifier. we will also add a command to verify it with the l1 contract in ethereum mainnet or testnets. compatibility and support of all the builtins are being worked on. we will be updating the community in the upcoming weeks. for us it’s very important that anybody can test and play with our code. 2. performance. we are already 10 times faster than the stone prover. we believe we can be almost another order of magnitude faster. 3. code architecture and organization should be top notch. the codebase is pretty small on purpose. we are documenting everything we are doing. we are leveraging all the work done in lambdaworks for multiple other provers. this let us easily iterate, play and change any part of the prover. we can test and propose new ideas thanks to this. from our point or view this is crucial and a big improvement over what exists. we have multiple ideas on how to change the protocol. And here's a demo! Don't trust, verify.

Fede’s intern

16,714 Aufrufe • vor 2 Jahren

Cooperator number two admitted that he never heard it direct from Durk about the bounty, and in fact, he didn’t even know who the person who told him heard it from from. He also admitted that as to the 3 private conversation conversations he had afterward with Durk trying to get the money, there is absolutely no video and no corroborating Witness for any of those conversations. Those conversations all happened at essentially what was the after party for concerts at the United Center which are major events where it’s hard to see how you get so many private conversations with the person who you had no private relationship with, for whom you never had their phone number, and it goes on and on. When you couple the admissions with the cooperator statement that he was facing life without parole and cooperation is the only way to get a sentence reduction, you have a great argument at closing that this Witness does not bring the government closer to proving the conspiracy as against Durk Banks as much as he is saying things that get him a sentence reduction, but are impossible to corroborate. Doing that on a cross while also setting yourself up for the next cross which is coming up and is gonna be the one that matters, that’s a pretty good days work from the billion dollar lawyer
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Cooperator number two admitted that he never heard it direct from Durk about the bounty, and in fact, he didn’t even know who the person who told him heard it from from. He also admitted that as to the 3 private conversation conversations he had afterward with Durk trying to get the money, there is absolutely no video and no corroborating Witness for any of those conversations. Those conversations all happened at essentially what was the after party for concerts at the United Center which are major events where it’s hard to see how you get so many private conversations with the person who you had no private relationship with, for whom you never had their phone number, and it goes on and on. When you couple the admissions with the cooperator statement that he was facing life without parole and cooperation is the only way to get a sentence reduction, you have a great argument at closing that this Witness does not bring the government closer to proving the conspiracy as against Durk Banks as much as he is saying things that get him a sentence reduction, but are impossible to corroborate. Doing that on a cross while also setting yourself up for the next cross which is coming up and is gonna be the one that matters, that’s a pretty good days work from the billion dollar lawyer

Mohammed (Moe) Gangat

118,645 Aufrufe • vor 1 Monat

Shipping season never ends 🥷 1⃣ StarkWare executed the first ever quantum-safe Bitcoin transaction The first quantum-safe Bitcoin transaction in history was executed and mined on Bitcoin Mainnet using Avihu Levy’s QSB design. > QSB allows Bitcoin holders to move funds into a quantum-safe setup today, without changing the Bitcoin protocol or requiring a fork. > The transaction proved that the design can already work on Bitcoin Mainnet. > While QSB is not intended as Bitcoin’s optimal long-term post-quantum solution, it provides holders with a last-resort protection mechanism without waiting for protocol-level consensus. > The milestone builds on years of quantum-security research from StarkWare and the Starknet ecosystem. 2⃣ More builders than ever are shipping privacy primitives StarkWare launched the STRK20 Private Sprint to accelerate the development of privacy applications on Starknet. > Over 200 builders are now working on more than 170 projects spanning AI, trading, DeFi strategies, gaming, and more. > The sprint was extended by one week, with builders able to join until September 7, and anyone can join. > StarkWare also open-sourced PriPay, a private payroll system enabling recurring or one-time salary payments that remain hidden from block explorers while preserving an onchain audit trail. 3⃣ Starknet revenue is going back into the ecosystem For the first time, StarkWare delegated 25M STRK generated from Starknet sequencer revenue back into the ecosystem. > The 25M STRK is being used to strengthen projects and operators contributing to Starknet through delegation. > Round 3 of the StarkWare Delegation Program was also executed, with selected validators receiving between 5M and 20M STRK each. > The new structure comes with higher expectations around validator performance, reliability, testing, and active ecosystem participation. 4⃣ The ecosystem keeps shipping > Realms is building an L3 on top of Starknet for Blitz and Eternum, targeting significantly lower costs and better UX. > SuperVega launched its public beta, enabling one-tap options trading on BTC, ETH, ZEC, and STRK, with end-of-year expiries now available. > Extended added 22 new RWA markets during August, launched Chase Orders, and unveiled its vision to become a regulated, globally distributed onchain trading platform, starting with the EU. > Offmarket launched private Polymarket trading on Starknet. > Chance launched an intent verification layer for AI agents, with settlement proofs anchored on Starknet and native escrow wallets. > Omnisea integrated Starknet as the first non-EVM chain supported by its LayerZero-powered bridge. > Gaffer launched a new season of its fantasy football app. > VeilX went live on testnet, enabling anonymous swaps between regulated ERC-3643 assets through an Ekubo extension. > Erebus is building a private trading layer where AI agents can negotiate and trade privately. 5⃣ The numbers keep improving > 1.5B STRK are now staked on Starknet, representing ~22% of the circulating supply > 10M STRK are now being staked privately through Endur > Starknet apps generated $40M in revenue over the past year > Starknet revenue is up 1,200% YoY, with Starknet now operating profitably > Nearly 200 builders are currently shipping new privacy primitives Can’t stop, won’t stop.
3:53

Shipping season never ends 🥷 1⃣ StarkWare executed the first ever quantum-safe Bitcoin transaction The first quantum-safe Bitcoin transaction in history was executed and mined on Bitcoin Mainnet using Avihu Levy’s QSB design. > QSB allows Bitcoin holders to move funds into a quantum-safe setup today, without changing the Bitcoin protocol or requiring a fork. > The transaction proved that the design can already work on Bitcoin Mainnet. > While QSB is not intended as Bitcoin’s optimal long-term post-quantum solution, it provides holders with a last-resort protection mechanism without waiting for protocol-level consensus. > The milestone builds on years of quantum-security research from StarkWare and the Starknet ecosystem. 2⃣ More builders than ever are shipping privacy primitives StarkWare launched the STRK20 Private Sprint to accelerate the development of privacy applications on Starknet. > Over 200 builders are now working on more than 170 projects spanning AI, trading, DeFi strategies, gaming, and more. > The sprint was extended by one week, with builders able to join until September 7, and anyone can join. > StarkWare also open-sourced PriPay, a private payroll system enabling recurring or one-time salary payments that remain hidden from block explorers while preserving an onchain audit trail. 3⃣ Starknet revenue is going back into the ecosystem For the first time, StarkWare delegated 25M STRK generated from Starknet sequencer revenue back into the ecosystem. > The 25M STRK is being used to strengthen projects and operators contributing to Starknet through delegation. > Round 3 of the StarkWare Delegation Program was also executed, with selected validators receiving between 5M and 20M STRK each. > The new structure comes with higher expectations around validator performance, reliability, testing, and active ecosystem participation. 4⃣ The ecosystem keeps shipping > Realms is building an L3 on top of Starknet for Blitz and Eternum, targeting significantly lower costs and better UX. > SuperVega launched its public beta, enabling one-tap options trading on BTC, ETH, ZEC, and STRK, with end-of-year expiries now available. > Extended added 22 new RWA markets during August, launched Chase Orders, and unveiled its vision to become a regulated, globally distributed onchain trading platform, starting with the EU. > Offmarket launched private Polymarket trading on Starknet. > Chance launched an intent verification layer for AI agents, with settlement proofs anchored on Starknet and native escrow wallets. > Omnisea integrated Starknet as the first non-EVM chain supported by its LayerZero-powered bridge. > Gaffer launched a new season of its fantasy football app. > VeilX went live on testnet, enabling anonymous swaps between regulated ERC-3643 assets through an Ekubo extension. > Erebus is building a private trading layer where AI agents can negotiate and trade privately. 5⃣ The numbers keep improving > 1.5B STRK are now staked on Starknet, representing ~22% of the circulating supply > 10M STRK are now being staked privately through Endur > Starknet apps generated $40M in revenue over the past year > Starknet revenue is up 1,200% YoY, with Starknet now operating profitably > Nearly 200 builders are currently shipping new privacy primitives Can’t stop, won’t stop.

StarkWare 🥷

16,462 Aufrufe • vor 1 Monat

Interestingly, as we have AI agents that run in the background, the speed of AI becomes incrementally less important than the core underlying capability level. When you could only give AI small bits of work, then the speed of response mattered a ton. The rate at which you can go back and forth with AI in real-time was the determining factor on how useful it is. But as AI agents can perform more complex and useful tasks in parallel behind the scenes, you can much more easily afford to wait longer for work to get done assuming it’s valuable. Now the focus becomes more on how you review and orchestrate the agents’ work. And the main factor is just how useful and usable is the output that the agent came back with.
2:09

Interestingly, as we have AI agents that run in the background, the speed of AI becomes incrementally less important than the core underlying capability level. When you could only give AI small bits of work, then the speed of response mattered a ton. The rate at which you can go back and forth with AI in real-time was the determining factor on how useful it is. But as AI agents can perform more complex and useful tasks in parallel behind the scenes, you can much more easily afford to wait longer for work to get done assuming it’s valuable. Now the focus becomes more on how you review and orchestrate the agents’ work. And the main factor is just how useful and usable is the output that the agent came back with.

Aaron Levie

103,880 Aufrufe • vor 1 Jahr

Sapling is live. the final Zcash launchpad on Solana. STAMP proved Zcash can carry a record of a burn. you destroy a token, you get a receipt. we built what it could have been: you burn, you get paid, and then you get the receipt/stamp on Zcash mainnet. every coin planted on Sapling is a coin, paired with $ZEC instead of SOL. same curve, same graduation, same terminals. one difference: every coin has roots. the roots are a vault of ZEC under the coin. every trade feeds it: at least 0.50% of every trade, in ZEC. that floor is written into the program. burn the token on solana in one transaction. your share of the roots comes back in ZEC, in the same transaction. roots × your tokens ÷ supply. no claim, no wait. add a zcash address and a stamp lands on zcash mainnet, cut with exactly what you destroyed and exactly what the roots paid you. one-way, verifiable, and held by nobody but you. a stamp tells the world what you burned. Sapling pays you for it first. Zcash can't hold memecoins yet. it can hold proof. a stamp is a record, not a token. the first one is already on Zcash mainnet: certificate: on Zcash mainnet (transaction): 3edfa6cd1a8e3afbe7604e0c5f167c8b46d20ca1a7a6b56ec11a247fe78d7b04 the rest of the 2%: 0.80% to the deployer, almost 3x what pays. or hand it to your holders: ZEC pushed to every wallet holding $20+. permanent. 0.50% buys $SAPLING and burns it. every coin, every trade. 0.20% keeps the lights on. every fee, split, burn, harvest, payout and stamp sits on with its signature. the vault program went through a full security review before a single coin was planted. check it yourself: vault program (Solana): A9zFnNZpVjBbcE1SAPY92Z6H7WhicysLNPYPpDz15UxF rootstock (buys + burns $SAPLING): 3G6yQGLssh4VTNDaGpLn9CgARSZkXk2xRvfeu4f4SLA9 stamp issuer (Zcash): t1bBCoaVRECAc8Y8E5BRrhDPQ36nt27kX29 stamp rules + verifier: plant a coin. grow it in ZEC.
0:40

Sapling is live. the final Zcash launchpad on Solana. STAMP proved Zcash can carry a record of a burn. you destroy a token, you get a receipt. we built what it could have been: you burn, you get paid, and then you get the receipt/stamp on Zcash mainnet. every coin planted on Sapling is a coin, paired with $ZEC instead of SOL. same curve, same graduation, same terminals. one difference: every coin has roots. the roots are a vault of ZEC under the coin. every trade feeds it: at least 0.50% of every trade, in ZEC. that floor is written into the program. burn the token on solana in one transaction. your share of the roots comes back in ZEC, in the same transaction. roots × your tokens ÷ supply. no claim, no wait. add a zcash address and a stamp lands on zcash mainnet, cut with exactly what you destroyed and exactly what the roots paid you. one-way, verifiable, and held by nobody but you. a stamp tells the world what you burned. Sapling pays you for it first. Zcash can't hold memecoins yet. it can hold proof. a stamp is a record, not a token. the first one is already on Zcash mainnet: certificate: on Zcash mainnet (transaction): 3edfa6cd1a8e3afbe7604e0c5f167c8b46d20ca1a7a6b56ec11a247fe78d7b04 the rest of the 2%: 0.80% to the deployer, almost 3x what pays. or hand it to your holders: ZEC pushed to every wallet holding $20+. permanent. 0.50% buys $SAPLING and burns it. every coin, every trade. 0.20% keeps the lights on. every fee, split, burn, harvest, payout and stamp sits on with its signature. the vault program went through a full security review before a single coin was planted. check it yourself: vault program (Solana): A9zFnNZpVjBbcE1SAPY92Z6H7WhicysLNPYPpDz15UxF rootstock (buys + burns $SAPLING): 3G6yQGLssh4VTNDaGpLn9CgARSZkXk2xRvfeu4f4SLA9 stamp issuer (Zcash): t1bBCoaVRECAc8Y8E5BRrhDPQ36nt27kX29 stamp rules + verifier: plant a coin. grow it in ZEC.

Sapling

25,232 Aufrufe • vor 16 Tagen

there are some people on this app who believe our giveaways are fake and screenshots are photoshopped ignoring the fact that everything exists on a decentralized ledger called the blockchain (ever heard of it), here is a screen recording of the MoonPayRewards account on our app for proof of work and authenticity when 10,000+ people engage with a giveaway, not everyone can win free money wallet addresses blurred for privacy thank you for your time and have a lovely day!
0:23

there are some people on this app who believe our giveaways are fake and screenshots are photoshopped ignoring the fact that everything exists on a decentralized ledger called the blockchain (ever heard of it), here is a screen recording of the MoonPayRewards account on our app for proof of work and authenticity when 10,000+ people engage with a giveaway, not everyone can win free money wallet addresses blurred for privacy thank you for your time and have a lovely day!

MoonPay 🟣

19,228 Aufrufe • vor 11 Monaten

Illia on the two types of post quantum cryptography, and which one Near prefers "There's a difference between types of cryptography, so-called lattice based and hash based, and there's a bit of a debate right now in the Web3 space about what should be used, with different tradeoffs" "People are used to signing with their wallet, the traditional way, but if we go to more institutional adoption, people use multi party computation, MPC. That's also what backs Near Intents and a lot of the cross chain work Near is doing. Today we have an announcement that we have a consortium testing multi party computation across custodians, banks and regulators, to showcase how this is going to work in production for real institutional use cases" "This is where we need the social consensus for the whole of Web3 to work together in a reasonable way, because hash based is actually very hard to support with hardware wallets and MPC solutions. So it's important for us that there's consensus on lattice based" "We want to be ahead of the curve and showcase how all of these tools work, and bring it to both individual users and institutional usage. That enables both security and trust in blockchain, which we've seen plummet a bit since post quantum concerns started coming out late last year"
2:19

Illia on the two types of post quantum cryptography, and which one Near prefers "There's a difference between types of cryptography, so-called lattice based and hash based, and there's a bit of a debate right now in the Web3 space about what should be used, with different tradeoffs" "People are used to signing with their wallet, the traditional way, but if we go to more institutional adoption, people use multi party computation, MPC. That's also what backs Near Intents and a lot of the cross chain work Near is doing. Today we have an announcement that we have a consortium testing multi party computation across custodians, banks and regulators, to showcase how this is going to work in production for real institutional use cases" "This is where we need the social consensus for the whole of Web3 to work together in a reasonable way, because hash based is actually very hard to support with hardware wallets and MPC solutions. So it's important for us that there's consensus on lattice based" "We want to be ahead of the curve and showcase how all of these tools work, and bring it to both individual users and institutional usage. That enables both security and trust in blockchain, which we've seen plummet a bit since post quantum concerns started coming out late last year"

Laura Shin

60,788 Aufrufe • vor 1 Monat

When we started Score, the standard computer vision tools already existed. About a million people use them every day. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are also still waiting on verified computer vision models, evaluated against real life conditions and ready to be deployed for them to deliver value for their teams, clients or users. Score Studio is the full computer vision path in one place. A team describes the problem. The system can generate the missing scenes, label them, train the candidates, evaluate which ones actually hold, and deploy the winner. Data, labels, training, eval, ship. One loop. If no model exists for that job yet, they can put a bounty on the subnet. Anything from a small vision brick to a full VLM. Miners compete on the task. Only the winning work comes back. Same path for software agents. Any agent can call it. Built to be fully agent-accessible. Built for the people who already do this work: computer vision engineers and the small teams around them in plants, warehouses, farms, robotics, sport, and security. And for the agents those teams will run. That is the part that changes the job. Not another training screen. The stretch that used to take a lab and a calendar, footage, boxes, versions, failed runs, a separate deploy project, sits behind one starting point. And if the network needs a new model, that request is part of the same path. We spent more than a year building it. Then we had a choice. Keep it for us, or commoditize the whole subnet and make it available 24/7, in permissionless and open-source way. And we knew we couldn't keep it for us. It had to live on Bittensor. Open source software already showed how this should work. Infrastructure should not sit inside one company. Same idea as open AI before the phrase changed meaning: inspect it, fork it, keep building. That is what SN44 is for. Open vision intelligence, powered by Bittensor. Miners do the work. Studio is how that gets monetized. Profit does not stay in a company account. It goes back into the subnet through buyback and burn. We built the tool we wanted on day one. It will live on the network now, and for ever. Waitlist is open.
1:11

When we started Score, the standard computer vision tools already existed. About a million people use them every day. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are also still waiting on verified computer vision models, evaluated against real life conditions and ready to be deployed for them to deliver value for their teams, clients or users. Score Studio is the full computer vision path in one place. A team describes the problem. The system can generate the missing scenes, label them, train the candidates, evaluate which ones actually hold, and deploy the winner. Data, labels, training, eval, ship. One loop. If no model exists for that job yet, they can put a bounty on the subnet. Anything from a small vision brick to a full VLM. Miners compete on the task. Only the winning work comes back. Same path for software agents. Any agent can call it. Built to be fully agent-accessible. Built for the people who already do this work: computer vision engineers and the small teams around them in plants, warehouses, farms, robotics, sport, and security. And for the agents those teams will run. That is the part that changes the job. Not another training screen. The stretch that used to take a lab and a calendar, footage, boxes, versions, failed runs, a separate deploy project, sits behind one starting point. And if the network needs a new model, that request is part of the same path. We spent more than a year building it. Then we had a choice. Keep it for us, or commoditize the whole subnet and make it available 24/7, in permissionless and open-source way. And we knew we couldn't keep it for us. It had to live on Bittensor. Open source software already showed how this should work. Infrastructure should not sit inside one company. Same idea as open AI before the phrase changed meaning: inspect it, fork it, keep building. That is what SN44 is for. Open vision intelligence, powered by Bittensor. Miners do the work. Studio is how that gets monetized. Profit does not stay in a company account. It goes back into the subnet through buyback and burn. We built the tool we wanted on day one. It will live on the network now, and for ever. Waitlist is open.

Score

11,292 Aufrufe • vor 1 Monat

Sky News 3 round up for as case retires for lunch on #PrinceHarryVsDailyMail #PeoplesPrinceHarry A round up of the opening statements referencing that Harry and the claimants believe the Daily Fail spent up to £3m on private investigators. Harry is relying on 10 articles about him and the Daily Mail say no one complained about the articles at the time. Chat with a barrister in the studio about why this case is different, the standard of proof and how the Daily Mail and press are allowed to keep their sources private.
6:19

Sky News 3 round up for as case retires for lunch on #PrinceHarryVsDailyMail #PeoplesPrinceHarry A round up of the opening statements referencing that Harry and the claimants believe the Daily Fail spent up to £3m on private investigators. Harry is relying on 10 articles about him and the Daily Mail say no one complained about the articles at the time. Chat with a barrister in the studio about why this case is different, the standard of proof and how the Daily Mail and press are allowed to keep their sources private.

Glow Lee

17,122 Aufrufe • vor 8 Monaten

Enough of the fluff. Time for some real advice. Launch your GPT 5.6 Sol Pro. Use the following prompt (feel free to swap the second and third lines for something of your choice): Prove for me that the group of rational points on the elliptic curve (y^2=x^3+17) is finitely generated. I want to tailor the general proof to this particular case to narrow down my understanding to a particular case. Write down a full mathematical proof, step by step, in Leslie Lamport style. Unpack all the definitions and notions so that it is fully self-contained. An example here: Notice how Sol is spawning all the subagents to complete the task. What is "Leslie Lamport style"? It's a technique where you split your proof into short, one-line sentences (claims) that are easy to justify. In a situation where your proof is not a 1-to-1 translation of, e.g., Python code, the Leslie Lamport-style proof can be treated as such. It tremendously improves the possibility of verifying each claim and helps the model structure the arguments in a very clear way. Leslie Lamport, a legendary mathematician and computer scientist, was a promoter of this way of structuring proofs. Partly because of that, he created an extension of Donald Knuth’s typesetting system TeX called LaTeX. Here you can read about "Leslie Lamport-style proofs":
1:44

Enough of the fluff. Time for some real advice. Launch your GPT 5.6 Sol Pro. Use the following prompt (feel free to swap the second and third lines for something of your choice): Prove for me that the group of rational points on the elliptic curve (y^2=x^3+17) is finitely generated. I want to tailor the general proof to this particular case to narrow down my understanding to a particular case. Write down a full mathematical proof, step by step, in Leslie Lamport style. Unpack all the definitions and notions so that it is fully self-contained. An example here: Notice how Sol is spawning all the subagents to complete the task. What is "Leslie Lamport style"? It's a technique where you split your proof into short, one-line sentences (claims) that are easy to justify. In a situation where your proof is not a 1-to-1 translation of, e.g., Python code, the Leslie Lamport-style proof can be treated as such. It tremendously improves the possibility of verifying each claim and helps the model structure the arguments in a very clear way. Leslie Lamport, a legendary mathematician and computer scientist, was a promoter of this way of structuring proofs. Partly because of that, he created an extension of Donald Knuth’s typesetting system TeX called LaTeX. Here you can read about "Leslie Lamport-style proofs":

Bartosz Naskręcki

31,115 Aufrufe • vor 3 Monaten

GMiden everyone 🤟 In finance, one rule always holds: a business is only as secure as the data behind it. So when the Miden team talks about Practical Private Finance, its not marketing - its a new on-chain model that finally works in real-world conditions. What’s the core idea behind Miden approach? The breakthrough is client-side proving: all computation happens on the users device. Your phone or laptop generates a local ZK-STARK proof, and the network verifies only correctnes. No exposed balances, no leaked strategies, no unnecessary risks. The chain sees the proof, but never your local state. That’s what practical privacy looks like. This is the kind of privacy blockchains should have offered to banks, brokers, trading platforms, and institutions yaers ago. And now it becomes real: private smart contracts, private execution, full control over state, fast performance, and programmable confidentiality - all without sacrificing speed or scalability. Practical Private Finance from Miden isnt a plug-in on top of the EVM. Its a new financial architecture where offchain data, proof-based validation, and compliance-ready design work as a unified system. This is how on-chain finally returns to sanity where trust isnt a slogan, but cryptography. And that’s exactly what inspired todays non NFT crypto art with my unofficial Miden mascot. The art itself in good quality is in the quote under this postHope you enjoy it )) #Miden #ClientSideProving
0:45

GMiden everyone 🤟 In finance, one rule always holds: a business is only as secure as the data behind it. So when the Miden team talks about Practical Private Finance, its not marketing - its a new on-chain model that finally works in real-world conditions. What’s the core idea behind Miden approach? The breakthrough is client-side proving: all computation happens on the users device. Your phone or laptop generates a local ZK-STARK proof, and the network verifies only correctnes. No exposed balances, no leaked strategies, no unnecessary risks. The chain sees the proof, but never your local state. That’s what practical privacy looks like. This is the kind of privacy blockchains should have offered to banks, brokers, trading platforms, and institutions yaers ago. And now it becomes real: private smart contracts, private execution, full control over state, fast performance, and programmable confidentiality - all without sacrificing speed or scalability. Practical Private Finance from Miden isnt a plug-in on top of the EVM. Its a new financial architecture where offchain data, proof-based validation, and compliance-ready design work as a unified system. This is how on-chain finally returns to sanity where trust isnt a slogan, but cryptography. And that’s exactly what inspired todays non NFT crypto art with my unofficial Miden mascot. The art itself in good quality is in the quote under this postHope you enjoy it )) #Miden #ClientSideProving

Konstantin

14,537 Aufrufe • vor 10 Monaten

Welker: How can the public trust the results of this investigation if it doesn't include state and local officials, the people who are there on the ground? Homan: First of all, this is a federal crime. Welker: It happened in Minneapolis. Homan: When a federal officer is in a shooting, it falls under the FBI. Welker: It's one thing for the FBI to take the lead in an investigation, certainly, that is something that we are used to seeing, but for state and local officials to be cut out altogether, are you comfortable with that? Homan: That's a question for the FBI. I've never worked for doj
1:48

Welker: How can the public trust the results of this investigation if it doesn't include state and local officials, the people who are there on the ground? Homan: First of all, this is a federal crime. Welker: It happened in Minneapolis. Homan: When a federal officer is in a shooting, it falls under the FBI. Welker: It's one thing for the FBI to take the lead in an investigation, certainly, that is something that we are used to seeing, but for state and local officials to be cut out altogether, are you comfortable with that? Homan: That's a question for the FBI. I've never worked for doj

Acyn

158,153 Aufrufe • vor 9 Monaten

This is SO cool !! I just used up for voting amendment XLS-96 Confidential Transfer / privacy on the XRP Ledger dev net enabled by homomorphism and ZK proofs. What's going on here and how do nodes know payments are correct while not able to see the amounts ? 1) I issued a confidential MPT on the XRP Ledger dev net. I shielded my balance. Privacy for the amounts of my XRPL issued asset balance and transfers (the addresses stay public). No one can see the amounts, it's all shielded, except the issuer and the auditor who can always decrypt them (or you, like in the video on my esp32). 2) The XRP Ledger uses 2 boxes 📦 for this all under the hood, an Inbox-box and a Spending-box. I don't go into detail why thats needed but it's important we have it. 3) How do Validators and nodes know the transfers are correct if they can't see the amounts? Now the true magic is enabled by homomorphism. It allows to do operations arithmetic on encrypted data as if it were plaintext, without the need to decrypt it. Like adding and subtracting amounts to your balance. ZK proofs fill the gap that nodes need. We need a comparison of the balance that after you have done your payment you have >= 0 balance. If you would have negative balance it means you trying to spend more than you have something we need to prevent. For this a ZK proof is used to quickly allow people to check, ahh all good, no idea how much Vet owns but whatever he is spending here it's definitely within his balance and it's not below 0. Those 2 techniques soon on a public decentralized blockchain XRP Ledger. Should give you goose bumps what this means for possible use cases.
7:40

This is SO cool !! I just used up for voting amendment XLS-96 Confidential Transfer / privacy on the XRP Ledger dev net enabled by homomorphism and ZK proofs. What's going on here and how do nodes know payments are correct while not able to see the amounts ? 1) I issued a confidential MPT on the XRP Ledger dev net. I shielded my balance. Privacy for the amounts of my XRPL issued asset balance and transfers (the addresses stay public). No one can see the amounts, it's all shielded, except the issuer and the auditor who can always decrypt them (or you, like in the video on my esp32). 2) The XRP Ledger uses 2 boxes 📦 for this all under the hood, an Inbox-box and a Spending-box. I don't go into detail why thats needed but it's important we have it. 3) How do Validators and nodes know the transfers are correct if they can't see the amounts? Now the true magic is enabled by homomorphism. It allows to do operations arithmetic on encrypted data as if it were plaintext, without the need to decrypt it. Like adding and subtracting amounts to your balance. ZK proofs fill the gap that nodes need. We need a comparison of the balance that after you have done your payment you have >= 0 balance. If you would have negative balance it means you trying to spend more than you have something we need to prevent. For this a ZK proof is used to quickly allow people to check, ahh all good, no idea how much Vet owns but whatever he is spending here it's definitely within his balance and it's not below 0. Those 2 techniques soon on a public decentralized blockchain XRP Ledger. Should give you goose bumps what this means for possible use cases.

Vet

74,775 Aufrufe • vor 2 Monaten

OpenAI just spent $2,000 to solve 10 problems that have beaten the world's best mathematicians for DECADES. Nobody outside the company is allowed to run the machine that did it. On Saturday OpenAI published a 249-page report and gave its next model family a name: Astra. An internal version of it produced new results on 10 open problems in mathematics and theoretical computer science, and mathematicians had made no real progress on any of them for at least 10 years. On most of them, far longer than that. Here is what it solved: It built the first explicit example of a non-sofic group. Mikhail Gromov raised that question in 1999 and nobody answered it for 27 years. It disproved Connes's rigidity conjecture, a problem in von Neumann algebras that had stood for decades. It proved Ehrhart's volume conjecture. It resolved three problems from Paul Erdos's catalogue, including number 183 on multicolor Ramsey numbers. It produced the first improvement to the general upper bound on high-dimensional sphere packing since 1978. And it proved a new hardness result for the closest vector problem, which sits directly underneath lattice cryptography. That is the math the world is betting on to protect its data once quantum computers arrive. The successful runs cost roughly $2,000 in tokens. Now here is what almost nobody has picked up on... OpenAI did not just publish claims. Every argument shipped with a Lean certificate, which is a machine-checkable proof that any mathematician can verify without trusting OpenAI at all. That is a real change. In May the same model family disproved the Erdos unit distance conjecture and the world had to take a Fields Medalist's word for it. Tim Gowers said he would recommend that proof for the Annals of Mathematics without hesitation. This time the proofs check themselves. But look at what is still unverifiable: Any mathematician can now check those proofs line by line. Not one of them can look at the model that wrote them. Astra has no release date and nobody outside OpenAI has run it. The company announced its next major model family with a claim instead of a demo, and the only evidence anyone gets is the output. So OpenAI made an unfalsifiable claim about a machine look like a falsifiable claim about mathematics. The Information reported this week that OpenAI demoed Astra to US policymakers and regulators in Washington. This is the same month the administration is weighing a new watchdog to vet frontier AI models, reporting to the SEC. 10 proofs nobody believed a machine could produce is a very good thing to carry into that room. And keep in mind, the same model family doing this mathematics is the family that kept escaping its own testing environment. OpenAI models found zero-day vulnerabilities nobody knew existed, broke out of a sealed research sandbox, and reached another company's live systems. Both of those facts come from OpenAI's own announcements, published three weeks apart. Finding a proof no human could construct and finding a hole no human had noticed are the same ability aimed at different targets. Mathematicians are already asking for independent verification, and plenty of people online are calling the whole thing hype. Thomas Bloom, who runs the Erdos problems site, called the 10 results big news and said they matter more than the May result did. Lean will settle the mathematics within weeks. But nothing will settle what else a machine this capable is being pointed at, because nobody outside one company is allowed to look.
2:13

OpenAI just spent $2,000 to solve 10 problems that have beaten the world's best mathematicians for DECADES. Nobody outside the company is allowed to run the machine that did it. On Saturday OpenAI published a 249-page report and gave its next model family a name: Astra. An internal version of it produced new results on 10 open problems in mathematics and theoretical computer science, and mathematicians had made no real progress on any of them for at least 10 years. On most of them, far longer than that. Here is what it solved: It built the first explicit example of a non-sofic group. Mikhail Gromov raised that question in 1999 and nobody answered it for 27 years. It disproved Connes's rigidity conjecture, a problem in von Neumann algebras that had stood for decades. It proved Ehrhart's volume conjecture. It resolved three problems from Paul Erdos's catalogue, including number 183 on multicolor Ramsey numbers. It produced the first improvement to the general upper bound on high-dimensional sphere packing since 1978. And it proved a new hardness result for the closest vector problem, which sits directly underneath lattice cryptography. That is the math the world is betting on to protect its data once quantum computers arrive. The successful runs cost roughly $2,000 in tokens. Now here is what almost nobody has picked up on... OpenAI did not just publish claims. Every argument shipped with a Lean certificate, which is a machine-checkable proof that any mathematician can verify without trusting OpenAI at all. That is a real change. In May the same model family disproved the Erdos unit distance conjecture and the world had to take a Fields Medalist's word for it. Tim Gowers said he would recommend that proof for the Annals of Mathematics without hesitation. This time the proofs check themselves. But look at what is still unverifiable: Any mathematician can now check those proofs line by line. Not one of them can look at the model that wrote them. Astra has no release date and nobody outside OpenAI has run it. The company announced its next major model family with a claim instead of a demo, and the only evidence anyone gets is the output. So OpenAI made an unfalsifiable claim about a machine look like a falsifiable claim about mathematics. The Information reported this week that OpenAI demoed Astra to US policymakers and regulators in Washington. This is the same month the administration is weighing a new watchdog to vet frontier AI models, reporting to the SEC. 10 proofs nobody believed a machine could produce is a very good thing to carry into that room. And keep in mind, the same model family doing this mathematics is the family that kept escaping its own testing environment. OpenAI models found zero-day vulnerabilities nobody knew existed, broke out of a sealed research sandbox, and reached another company's live systems. Both of those facts come from OpenAI's own announcements, published three weeks apart. Finding a proof no human could construct and finding a hole no human had noticed are the same ability aimed at different targets. Mathematicians are already asking for independent verification, and plenty of people online are calling the whole thing hype. Thomas Bloom, who runs the Erdos problems site, called the 10 results big news and said they matter more than the May result did. Lean will settle the mathematics within weeks. But nothing will settle what else a machine this capable is being pointed at, because nobody outside one company is allowed to look.

Ricardo

44,177 Aufrufe • vor 2 Monaten

Axiom Math's Carina Hong on why verification isn't about catching mistakes, it's how you drive the cost of a proof to zero: "Formal verification is going to make your life slightly better if you're facing a proof with one million lines. Remember the Erdős unit distance problem, the chain of thought being generated? There are actual mathematicians trying to follow it step by step and scrutinize it. That seems very difficult if you're not in that very niche domain of discrete geometry intersecting with algebraic number theory." "But if you have a Lean proof accompanying it, you can just run it. And running the Lean proof gives you that provable guarantee that this proof is sound." "I have a hot take. People think Lean is this library built on the existing Mathlib. I think it's going to grow significantly. A lot of the hurdles where Lean is difficult is that the basic definitions of some mathematical fields are just not in the library." "My hot take is the scaling law, if you go down the formal mathematics path, is going to be a lot steeper than informal mathematics. So it's not just for verification, for trust, it's also for performance, it's also for optimal generation." "Verification is not like insurance. It's not something where, oh, we want to make sure there's no flaw. That's great, but it also helps you generate mathematics, both proofs and conjectures and theories, a lot better." "So imagine the cost of proof goes to zero. Then you can massage the problem statements, and even if it's an open problem, a lot more easily, flexibly, and adaptively." Carina Hong Axiom
3:17

Axiom Math's Carina Hong on why verification isn't about catching mistakes, it's how you drive the cost of a proof to zero: "Formal verification is going to make your life slightly better if you're facing a proof with one million lines. Remember the Erdős unit distance problem, the chain of thought being generated? There are actual mathematicians trying to follow it step by step and scrutinize it. That seems very difficult if you're not in that very niche domain of discrete geometry intersecting with algebraic number theory." "But if you have a Lean proof accompanying it, you can just run it. And running the Lean proof gives you that provable guarantee that this proof is sound." "I have a hot take. People think Lean is this library built on the existing Mathlib. I think it's going to grow significantly. A lot of the hurdles where Lean is difficult is that the basic definitions of some mathematical fields are just not in the library." "My hot take is the scaling law, if you go down the formal mathematics path, is going to be a lot steeper than informal mathematics. So it's not just for verification, for trust, it's also for performance, it's also for optimal generation." "Verification is not like insurance. It's not something where, oh, we want to make sure there's no flaw. That's great, but it also helps you generate mathematics, both proofs and conjectures and theories, a lot better." "So imagine the cost of proof goes to zero. Then you can massage the problem statements, and even if it's an open problem, a lot more easily, flexibly, and adaptively." Carina Hong Axiom

MTS

13,324 Aufrufe • vor 2 Monaten

Everyone is preparing for "bunker mode" as advances in AI threaten the cryptography securing today's wallets. Introducing the first post-quantum-proof launchpad. 7K52aYQW9rWGjwZmQ7o2d1P6E7bji6hSMsqaLy5EcxLh launch tokens with cryptographic proofs that remain verifiable even if today's elliptic-curve cryptography is broken. every token is launched with: - a unique post-quantum creator identity - hash-based Winternitz one-time signatures (WOTS) - a 256-leaf XMSS Merkle tree - a permanent proof of origin stored in IPFS metadata connect your Solana wallet and derive your own post-quantum identity without needing a new wallet or seed phrase. every launch is cryptographically signed by this identity, allowing anyone to independently verify its origin using SHA-256, without relying on traditional wallet signatures or our servers. watch the video below to see how it works.
1:02

Everyone is preparing for "bunker mode" as advances in AI threaten the cryptography securing today's wallets. Introducing the first post-quantum-proof launchpad. 7K52aYQW9rWGjwZmQ7o2d1P6E7bji6hSMsqaLy5EcxLh launch tokens with cryptographic proofs that remain verifiable even if today's elliptic-curve cryptography is broken. every token is launched with: - a unique post-quantum creator identity - hash-based Winternitz one-time signatures (WOTS) - a 256-leaf XMSS Merkle tree - a permanent proof of origin stored in IPFS metadata connect your Solana wallet and derive your own post-quantum identity without needing a new wallet or seed phrase. every launch is cryptographically signed by this identity, allowing anyone to independently verify its origin using SHA-256, without relying on traditional wallet signatures or our servers. watch the video below to see how it works.

pqc.market

85,820 Aufrufe • vor 4 Tagen