Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Proof-of-Useful-Work forced us to solve a problem ordinary blockchains do not have. A Pearl miner performs large matrix multiplications as part of a real AI workload. Naively, when it finds a valid block, it would need to publish those matrices so the network could verify the computation. The matrices...

prlnet's profile picture

Pearl Research Labs

16,134 subscribers

19,453 Aufrufe • vor 2 Monaten •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

7 Kommentare

Profilbild von inipool.org
inipool.orgvor 2 Monaten

Why has the cryptocurrency price been continuously falling instead of rising?

Profilbild von Weaver Labs
Weaver Labsvor 2 Monaten

Yes, the verification layer is often the hardest part of useful work systems. Compressing large computations into compact proofs helps make real-world workloads practical without turning the blockchain into a data transport layer.

Profilbild von Ruqo
Ruqovor 2 Monaten

This is where PoUW gets really interesting. Useful AI computation
↓
Zero-Knowledge Proofs
↓
Privacy-preserving verification
↓
Consensus The network doesn't need to see the model, the weights, or the data. It only needs proof that the work was done. pearl-2:native

Profilbild von Mr George
Mr Georgevor 2 Monaten

Your algorithm is probably cracked again, and the computing power has increased sharply.

Profilbild von Stoic Chain
Stoic Chainvor 2 Monaten

CoreWeave just paid $9B for Core Scientific, a Bitcoin miner. The buildings and cheap power miners locked up years ago are exactly what AI is scrambling for now. Pearl skips a step and makes the mining itself the AI work. Miners accidentally built the hottest real estate in tech.

Profilbild von crypto.vv
crypto.vvvor 2 Monaten

Pearl vulnerability not blocked, about to reach zero

Profilbild von Glutamineux
Glutamineuxvor 2 Monaten

Damn still the same conference you cutting video clips from ?

Ähnliche Videos

Pearl started with a simple question: Why should AI and blockchain mining compete for the same GPUs when the same computation could do both? In this talk, Pearl co-founder Ilan Komargodski explains how that idea became a live proof-of-useful-work network turning AI inference into blockchain security with minimal overhead.
20:04

Pearl started with a simple question: Why should AI and blockchain mining compete for the same GPUs when the same computation could do both? In this talk, Pearl co-founder Ilan Komargodski explains how that idea became a live proof-of-useful-work network turning AI inference into blockchain security with minimal overhead.

Pearl Research Labs

25,586 Aufrufe • vor 2 Monaten

Who still believes in Proof of Work? ✋ At the Skyline PoW Mixer, our founder Carter (Carter Feldman) explained its importance and revival. Proof of Work embodies freedom, not just block mining. Anyone can participate without permission, gatekeepers, or censorship. Psy Protocol advances this with PoW 2.0: Proof of Useful Work. Instead of wasting energy, computation is purposeful. ZK math verifies everything. Miners earn for contributing to real, measurable work that strengthens the network. It’s open-source, censorship-resistant, and built for the next internet. The future belongs to builders, users and decentralization believers. The king is coming home.
1:47

Who still believes in Proof of Work? ✋ At the Skyline PoW Mixer, our founder Carter (Carter Feldman) explained its importance and revival. Proof of Work embodies freedom, not just block mining. Anyone can participate without permission, gatekeepers, or censorship. Psy Protocol advances this with PoW 2.0: Proof of Useful Work. Instead of wasting energy, computation is purposeful. ZK math verifies everything. Miners earn for contributing to real, measurable work that strengthens the network. It’s open-source, censorship-resistant, and built for the next internet. The future belongs to builders, users and decentralization believers. The king is coming home.

Psy Protocol

175,983 Aufrufe • vor 1 Jahr

Proof of work has always demanded a brutal trade-off - to secure a monetary network, you burn energy on the scale of entire countries. Meanwhile, hundreds of billions poured into AI - all for one operation at massive scale - matrix multiplication. For years, these energy markets were disjoint. It was commonly believed that proof of work could never be implemented on top of real-world instances. They were wrong. The same matrix multiplication that powers AI can secure a monetary network as a by-product - every GPU cycle doing double duty. A currency backed by the most valuable computation on earth. A deep dive by Omri Weinstein ⤵️
40:23

Proof of work has always demanded a brutal trade-off - to secure a monetary network, you burn energy on the scale of entire countries. Meanwhile, hundreds of billions poured into AI - all for one operation at massive scale - matrix multiplication. For years, these energy markets were disjoint. It was commonly believed that proof of work could never be implemented on top of real-world instances. They were wrong. The same matrix multiplication that powers AI can secure a monetary network as a by-product - every GPU cycle doing double duty. A currency backed by the most valuable computation on earth. A deep dive by Omri Weinstein ⤵️

Pearl Research Labs

15,990 Aufrufe • vor 3 Monaten

On proof-of-work, miners can collude to reorder settled transactions. On proof-of-stake, the biggest pools can reorder or roll back the chain. Settlement finality isn't a given on most networks, it's a property you have to verify before you trust it.
1:21

On proof-of-work, miners can collude to reorder settled transactions. On proof-of-stake, the biggest pools can reorder or roll back the chain. Settlement finality isn't a given on most networks, it's a property you have to verify before you trust it.

Jake Claver, QFOP

22,754 Aufrufe • vor 2 Monaten

.Logan broke down the utility + mechanics of base:0x9b5e262cf9bb04869ab40b19af91d2dc85761722 - No staking, no yield - Fixed supply - Hard money backed by useful proof-of-work - Inspired by Bittensor's subnet model - Q4 ZK upgrade adds privacy + programmability to transactions - Early July AI compute network launch "The purest expression of a proof of useful work thesis. Compute networks can be launched for any type of useful work vertical."
3:08

.Logan broke down the utility + mechanics of base:0x9b5e262cf9bb04869ab40b19af91d2dc85761722 - No staking, no yield - Fixed supply - Hard money backed by useful proof-of-work - Inspired by Bittensor's subnet model - Q4 ZK upgrade adds privacy + programmability to transactions - Early July AI compute network launch "The purest expression of a proof of useful work thesis. Compute networks can be launched for any type of useful work vertical."

MCG

15,284 Aufrufe • vor 3 Monaten

Proof-of-Useful-Work proposes that the same GPU computation used for AI workloads can also secure a blockchain network. But that immediately triggers an economic objection - if miners are already getting paid for running AI jobs, does the security of the network collapse? Rafael Pass breaks it down and shows why this critique doesn’t hold up. Worth watching 👇
34:00

Proof-of-Useful-Work proposes that the same GPU computation used for AI workloads can also secure a blockchain network. But that immediately triggers an economic objection - if miners are already getting paid for running AI jobs, does the security of the network collapse? Rafael Pass breaks it down and shows why this critique doesn’t hold up. Worth watching 👇

Pearl Research Labs

14,775 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

Today on MCG: Logan from Nockchain | $NOCK Nockchain is a PoW blockchain whose mining produces zk proofs of state transitions rather than discarded hashes. The energy that secures the chain also subsidizes a global market for verifiable compute. Topics covered on stream: 01:11 - Kraken listing 04:11 - Logan's background 11:50 - Useful proof-of-work is broader than AI 12:24 - Helium🎈 parallel 14:51 - Nockchain's foundation is "real hard money secured by proof of useful work" 16:01 - AI compute network launches early July, will verify matrix multiplications for inference work 17:09 - Data centers only use hardware 35-45% of the time...what is the rest used for? 18:25 - "They're mining crypto" 22:55 - Nockchain's AI compute network will be merge-mineable with Pearl Research Labs 25:05 - GTM thesis 30:55 - 10,000-20,000 consumer GPUs on the network at any given time 31:38 - Projecting 5-10x more compute on the network this time next year 32:01 - Funding 35:50 - "Proof of work is the only DAO that works" 40:02 - Roadmap
49:38

Today on MCG: Logan from Nockchain | $NOCK Nockchain is a PoW blockchain whose mining produces zk proofs of state transitions rather than discarded hashes. The energy that secures the chain also subsidizes a global market for verifiable compute. Topics covered on stream: 01:11 - Kraken listing 04:11 - Logan's background 11:50 - Useful proof-of-work is broader than AI 12:24 - Helium🎈 parallel 14:51 - Nockchain's foundation is "real hard money secured by proof of useful work" 16:01 - AI compute network launches early July, will verify matrix multiplications for inference work 17:09 - Data centers only use hardware 35-45% of the time...what is the rest used for? 18:25 - "They're mining crypto" 22:55 - Nockchain's AI compute network will be merge-mineable with Pearl Research Labs 25:05 - GTM thesis 30:55 - 10,000-20,000 consumer GPUs on the network at any given time 31:38 - Projecting 5-10x more compute on the network this time next year 32:01 - Funding 35:50 - "Proof of work is the only DAO that works" 40:02 - Roadmap

MCG

26,314 Aufrufe • vor 3 Monaten

Vitalik Buterin explains why proof-of-stake is more secure than proof-of-work “I think proof of stake is very secure because to attack the system, you need to have basically as much stake as the rest of the network. Right now, for example, we have 5 million ETH staking, which means you have to come up with 5 million ETH and then join the network.” At the time of this writing, more than 37 million ETH are being staked, with 3 million ETH waiting to join via the validator queue. At today’s prices, that’s more than $80 billion of ETH someone would have to acquire to attack the network and revert finalized blocks, which is more than the cost of attacking even the Bitcoin network by some estimates. The other defense mechanism that proof-of-stake has that proof-of-work doesn’t is slashing, which makes Ethereum antifragile. Vitalik explains: “Recovering from attacks is much easier in proof-of-stake than proof-of-work. For many kinds of attacks you do against [the Ethereum] network, we have this concept of automatic slashing. In order to revert a finalized block, you basically have to have a big portion of your validators sign two conflicting messages. This is something where once these messages are on the network, you can go and prove ‘these people did it.’ So we have this feature in the protocol where you basically take all these people who provably misbehaved and you burn their coins.” Vitalik also acknowledges the possibility of censoring attacks, where if 1/3rd of validators refuse to attest, the chain can’t finalize. But, as he explains, Ethereum has a contingency plan for this as well: “Everyone who got censored would create a minority chain, and the community would have to do a soft fork. The would have to say, ‘this chain is clearly attacking us and this one is not attacking us, so we’re going to join this chain.’ Then what happens is, on that new chain, the attackers also lose a lot of coins. The difference between proof-of-stake and proof-of-work is that in a proof-of-stake system, you can identify specific participants — and this isn’t a human going in and saying ‘I don’t like you’. It’s all automated.” One last benefit of proof-of-stake is that security scales with the value of the network. As Vitalik put it five years ago, it is really relative security, and not absolute security, that matters: “The security needs of a thing have to be proportional to the size of that thing, because as a thing gets bigger, its enemies become bigger and more well-motivated. If BTC were 100x as big as it is today, the value from destroying it would be 100x higher, and the kinds of actors that would want to care about destroying it would be much bigger and scarier. This is also why countries of all sizes have roughly similarly sized militaries as a percentage of GDP. Hence, cost of attack divided by market cap really is the correct statistic to measure, and in the long run issuance-free PoW really does look not that good." Source: Lex Fridman (Jun 2021)
2:04

Vitalik Buterin explains why proof-of-stake is more secure than proof-of-work “I think proof of stake is very secure because to attack the system, you need to have basically as much stake as the rest of the network. Right now, for example, we have 5 million ETH staking, which means you have to come up with 5 million ETH and then join the network.” At the time of this writing, more than 37 million ETH are being staked, with 3 million ETH waiting to join via the validator queue. At today’s prices, that’s more than $80 billion of ETH someone would have to acquire to attack the network and revert finalized blocks, which is more than the cost of attacking even the Bitcoin network by some estimates. The other defense mechanism that proof-of-stake has that proof-of-work doesn’t is slashing, which makes Ethereum antifragile. Vitalik explains: “Recovering from attacks is much easier in proof-of-stake than proof-of-work. For many kinds of attacks you do against [the Ethereum] network, we have this concept of automatic slashing. In order to revert a finalized block, you basically have to have a big portion of your validators sign two conflicting messages. This is something where once these messages are on the network, you can go and prove ‘these people did it.’ So we have this feature in the protocol where you basically take all these people who provably misbehaved and you burn their coins.” Vitalik also acknowledges the possibility of censoring attacks, where if 1/3rd of validators refuse to attest, the chain can’t finalize. But, as he explains, Ethereum has a contingency plan for this as well: “Everyone who got censored would create a minority chain, and the community would have to do a soft fork. The would have to say, ‘this chain is clearly attacking us and this one is not attacking us, so we’re going to join this chain.’ Then what happens is, on that new chain, the attackers also lose a lot of coins. The difference between proof-of-stake and proof-of-work is that in a proof-of-stake system, you can identify specific participants — and this isn’t a human going in and saying ‘I don’t like you’. It’s all automated.” One last benefit of proof-of-stake is that security scales with the value of the network. As Vitalik put it five years ago, it is really relative security, and not absolute security, that matters: “The security needs of a thing have to be proportional to the size of that thing, because as a thing gets bigger, its enemies become bigger and more well-motivated. If BTC were 100x as big as it is today, the value from destroying it would be 100x higher, and the kinds of actors that would want to care about destroying it would be much bigger and scarier. This is also why countries of all sizes have roughly similarly sized militaries as a percentage of GDP. Hence, cost of attack divided by market cap really is the correct statistic to measure, and in the long run issuance-free PoW really does look not that good." Source: Lex Fridman (Jun 2021)

Etherealize

102,150 Aufrufe • vor 6 Monaten

More users in the U.S. are starting to take a closer look at ZPN — a decentralized toolkit built around Zero-Knowledge Proof (ZKP) principles. 🔹 $ZPN (Zero Proof Network) Designed to enhance digital interactions with higher privacy standards. Its core idea: data can be verified without being exposed. 🔹 Zero-Knowledge Proofs (ZKP) A growing pillar in the Web3 privacy space, allowing verification without revealing the underlying information. 🔹 #ZPNWallet A wallet built with these concepts in mind, enabling asset management and on-chain interactions while preserving user privacy. For anyone exploring tools that emphasize transparency, security, and data sovereignty, ZPN is worth watching. #ZPN #ZKP #Web3Privacy #CryptoWallet
1:14

More users in the U.S. are starting to take a closer look at ZPN — a decentralized toolkit built around Zero-Knowledge Proof (ZKP) principles. 🔹 $ZPN (Zero Proof Network) Designed to enhance digital interactions with higher privacy standards. Its core idea: data can be verified without being exposed. 🔹 Zero-Knowledge Proofs (ZKP) A growing pillar in the Web3 privacy space, allowing verification without revealing the underlying information. 🔹 #ZPNWallet A wallet built with these concepts in mind, enabling asset management and on-chain interactions while preserving user privacy. For anyone exploring tools that emphasize transparency, security, and data sovereignty, ZPN is worth watching. #ZPN #ZKP #Web3Privacy #CryptoWallet

ZPN Chain

15,580 Aufrufe • vor 10 Monaten

Andrej Karpathy on autoresearch with an untrusted pool of workers: "My designs that incorporate an untrusted pool of workers (into autoresearch) actually look a little bit like a blockchain. Instead of blocks, you have commits, and these commits can build on each other and contain changes to the code as you're improving it. The proof of work is basically doing tons of experimentation to find the commits that work." The idea that distributed & permissionless autoresearch ~= proof-of-useful-work remains a high-level intuition for now, but it is extremely intriguing to say the least. Someone needs to take this further. See QT for more on what's missing.
1:56

Andrej Karpathy on autoresearch with an untrusted pool of workers: "My designs that incorporate an untrusted pool of workers (into autoresearch) actually look a little bit like a blockchain. Instead of blocks, you have commits, and these commits can build on each other and contain changes to the code as you're improving it. The proof of work is basically doing tons of experimentation to find the commits that work." The idea that distributed & permissionless autoresearch ~= proof-of-useful-work remains a high-level intuition for now, but it is extremely intriguing to say the least. Someone needs to take this further. See QT for more on what's missing.

Wei Dai

615,073 Aufrufe • vor 6 Monaten

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.
0:52

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

13,648 Aufrufe • vor 4 Monaten

What if blockchains didn’t just scale, but spoke the same language? Boundless is making that real with Mainnet Beta and The Signal, a universal proof layer broadcasting Ethereum state across chains. This isn’t some vague vision. It’s live. Here’s how it works: • Anyone can request a proof → each one strengthens The Signal • Provers earn directly by running nodes and generating proofs • Communities vote to decide which chain gets integrated next It’s a new kind of interoperability where computation is verifiable, incentives are aligned, and blockchains become part of a shared ZK fabric. This is what connected infrastructure looks like. Explore more here
0:57

What if blockchains didn’t just scale, but spoke the same language? Boundless is making that real with Mainnet Beta and The Signal, a universal proof layer broadcasting Ethereum state across chains. This isn’t some vague vision. It’s live. Here’s how it works: • Anyone can request a proof → each one strengthens The Signal • Provers earn directly by running nodes and generating proofs • Communities vote to decide which chain gets integrated next It’s a new kind of interoperability where computation is verifiable, incentives are aligned, and blockchains become part of a shared ZK fabric. This is what connected infrastructure looks like. Explore more here

Jaymz.eth

14,441 Aufrufe • vor 1 Jahr

Full Stack Verifiability | Verifiable Cloud ☁️ Sreeram Kannan explains how EigenCloud delivers verifiability across the entire stack. It starts at the base with the EigenLayer, where computation is guaranteed by a decentralized network of hundreds of operators backed by $12B of stake. That’s the trust foundation of the cloud. On top of this: ✅ EigenDA: a data availability protocol that guarantees verifiable data publication.Publish data once, and anyone can retrieve it without trust. ✅ EigenCompute: execute arbitrary programs off-chain and bring the results back onchain verifiably. ✅ EigenAI: run AI inference today and return inference outputs directly onchain. All of them deliver strong verifiability for computation, inference, and data, all anchored by the underlying decentralized layer. And it doesn’t stop at first-party services, EigenCloud includes a growing ecosystem of third-party systems like zkTLS, proof-of-location, and decentralized prover networks, adding even deeper verification guarantees throughout the cloud. This is what a fully verifiable cloud looks like. A cloud you can check, not just trust.
1:30

Full Stack Verifiability | Verifiable Cloud ☁️ Sreeram Kannan explains how EigenCloud delivers verifiability across the entire stack. It starts at the base with the EigenLayer, where computation is guaranteed by a decentralized network of hundreds of operators backed by $12B of stake. That’s the trust foundation of the cloud. On top of this: ✅ EigenDA: a data availability protocol that guarantees verifiable data publication.Publish data once, and anyone can retrieve it without trust. ✅ EigenCompute: execute arbitrary programs off-chain and bring the results back onchain verifiably. ✅ EigenAI: run AI inference today and return inference outputs directly onchain. All of them deliver strong verifiability for computation, inference, and data, all anchored by the underlying decentralized layer. And it doesn’t stop at first-party services, EigenCloud includes a growing ecosystem of third-party systems like zkTLS, proof-of-location, and decentralized prover networks, adding even deeper verification guarantees throughout the cloud. This is what a fully verifiable cloud looks like. A cloud you can check, not just trust.

EigenCloud

48,010 Aufrufe • vor 10 Monaten

Hyperspace: A Peer-to-Peer Blockchain For The Agentic Intelligence Economy Over the past few weeks we observed that when agents do Karpathy-style experiments, and then gossip and share with others over the Hyperspace network, it leads to intelligence which is useful to many. Today we introduce the first-ever agentic blockchain which rewards agents when their experiments lead to intelligence for their network. It is based on a new mechanism called Proof-of-Intelligence (PoI) which requires a cryptographic proof of experimentation, a nominal stake, and a proof of compute in order to mine the currency of this new blockchain. -> This approach diverges from the two primary ways to secure blockchains we have seen so far: Proof-of-Work by Bitcoin (meaningless hash-generation), and Proof-of-Stake by Ethereum (capital is all that matters here). Proof-of-Intelligence specifically incentivizes miners to run more capable intelligent infrastructure (better open source models, on more powerful GPUs) in order to be able to be the ones which compound and improve upon the experiments which other agents then find useful. Adoption is the unit of value In Bitcoin, you earn by finding a valid hash. In Hyperspace, you earn when another agent uses your experiment as a starting point and improves on it. A fixed budget of tokens is emitted per epoch and split among participants by weight - and verified adoption of your work is the largest weight multiplier. Garbage experiments earn nothing because no one adopts them. Thoughtful experiments compound: each adoption triggers downstream adoptions. The incentive to run powerful models and intelligent search strategies is built into the economics, not imposed by rules. Research DAG When an agent runs an experiment and shares its result, other agents can adopt that result as their starting point - mutate it, extend it, improve upon it. Each experiment is a commit in a content-addressed graph we call the ResearchDAG. Like Git, but for research. Over time, the DAG accumulates chains of reasoning: agent A discovers RMSNorm helps, agent B adds warmup scheduling on top, agent C scales the hidden dimension. The graph records who built on whom. This is the network's collective intelligence - not any single experiment, but the accumulated structure of experiments and their relationships. Broadband era for agentic commerce: $0.001 micropayments at 10M TPS (theoretical max) This blockchain is built upon our research in how to scale and build for the broadband-era of the agentic economy, where it has a theoretical max of 10 million transactions per second (TPS), while reducing the agent-to-agent micropayments to $0.001 even at scale (based on architecture design). Overall, it is 100x cheaper than Ethereum, and is designed from the ground-up for agents: enshrining agent-native opcodes in the protocol compared to the more inefficient smart contract driven approach. It packs in a robust Agent Virtual Machine (AVM) which can verify multiple types of agent work, for other agents to be able to trust, invoke and pay each other. This then feeds into improving the peer-to-peer AgentRank (see paper and launch post from earlier). By solving for trust, scale and incentives for agents to operate autonomously, this would form the basis of a new economy. This is the world's first agentic blockchain, and you can join and start running a blockchain node today (it is in testnet). PS: We are releasing the code today, and will release our blockchain scalability paper and other presentations in days ahead. This is the most advanced peer-to-peer AI and cryptography software in the world. It has bugs :)
0:30

Hyperspace: A Peer-to-Peer Blockchain For The Agentic Intelligence Economy Over the past few weeks we observed that when agents do Karpathy-style experiments, and then gossip and share with others over the Hyperspace network, it leads to intelligence which is useful to many. Today we introduce the first-ever agentic blockchain which rewards agents when their experiments lead to intelligence for their network. It is based on a new mechanism called Proof-of-Intelligence (PoI) which requires a cryptographic proof of experimentation, a nominal stake, and a proof of compute in order to mine the currency of this new blockchain. -> This approach diverges from the two primary ways to secure blockchains we have seen so far: Proof-of-Work by Bitcoin (meaningless hash-generation), and Proof-of-Stake by Ethereum (capital is all that matters here). Proof-of-Intelligence specifically incentivizes miners to run more capable intelligent infrastructure (better open source models, on more powerful GPUs) in order to be able to be the ones which compound and improve upon the experiments which other agents then find useful. Adoption is the unit of value In Bitcoin, you earn by finding a valid hash. In Hyperspace, you earn when another agent uses your experiment as a starting point and improves on it. A fixed budget of tokens is emitted per epoch and split among participants by weight - and verified adoption of your work is the largest weight multiplier. Garbage experiments earn nothing because no one adopts them. Thoughtful experiments compound: each adoption triggers downstream adoptions. The incentive to run powerful models and intelligent search strategies is built into the economics, not imposed by rules. Research DAG When an agent runs an experiment and shares its result, other agents can adopt that result as their starting point - mutate it, extend it, improve upon it. Each experiment is a commit in a content-addressed graph we call the ResearchDAG. Like Git, but for research. Over time, the DAG accumulates chains of reasoning: agent A discovers RMSNorm helps, agent B adds warmup scheduling on top, agent C scales the hidden dimension. The graph records who built on whom. This is the network's collective intelligence - not any single experiment, but the accumulated structure of experiments and their relationships. Broadband era for agentic commerce: $0.001 micropayments at 10M TPS (theoretical max) This blockchain is built upon our research in how to scale and build for the broadband-era of the agentic economy, where it has a theoretical max of 10 million transactions per second (TPS), while reducing the agent-to-agent micropayments to $0.001 even at scale (based on architecture design). Overall, it is 100x cheaper than Ethereum, and is designed from the ground-up for agents: enshrining agent-native opcodes in the protocol compared to the more inefficient smart contract driven approach. It packs in a robust Agent Virtual Machine (AVM) which can verify multiple types of agent work, for other agents to be able to trust, invoke and pay each other. This then feeds into improving the peer-to-peer AgentRank (see paper and launch post from earlier). By solving for trust, scale and incentives for agents to operate autonomously, this would form the basis of a new economy. This is the world's first agentic blockchain, and you can join and start running a blockchain node today (it is in testnet). PS: We are releasing the code today, and will release our blockchain scalability paper and other presentations in days ahead. This is the most advanced peer-to-peer AI and cryptography software in the world. It has bugs :)

Varun

30,689 Aufrufe • vor 6 Monaten

Balaji Srinivasan: The Third Phase of the Crypto Industry Is Privacy On December 3, Balaji Srinivasan, former CTO of Coinbase, stated at Binance Blockchain Week 2025 in Dubai that the crypto industry can be broadly divided into three phases: an early phase centered on proof of work to validate system security; a subsequent phase focused on programmability, driven by platforms such as Ethereum; and a current phase that is gradually moving toward privacy, with zero-knowledge proofs (ZK) at its core, aiming to achieve higher levels of privacy protection and data security. Source:
0:55

Balaji Srinivasan: The Third Phase of the Crypto Industry Is Privacy On December 3, Balaji Srinivasan, former CTO of Coinbase, stated at Binance Blockchain Week 2025 in Dubai that the crypto industry can be broadly divided into three phases: an early phase centered on proof of work to validate system security; a subsequent phase focused on programmability, driven by platforms such as Ethereum; and a current phase that is gradually moving toward privacy, with zero-knowledge proofs (ZK) at its core, aiming to achieve higher levels of privacy protection and data security. Source:

Wu Blockchain

57,038 Aufrufe • vor 9 Monaten

“What if the real unlock for AI x crypto is not speculation — but proving intelligence can be trusted?” Sachi Miyasaki sits down with dcbuilder.eth ⚪️ for a deep dive into the intersection of AI and crypto, from DC’s work building the ZKML community to why zero-knowledge machine learning could become a core trust layer for AI on the internet. They break down how ZKML makes it possible to prove that a machine learning model produced a specific output from specific inputs — without forcing everyone to rerun the full computation themselves. The conversation also explores why this matters for model accountability, transparency, and verifiable AI at scale, plus the projects pushing the space forward, from Modulus Labs and Giza to EZKL and new research around proof of inference.
5:35

“What if the real unlock for AI x crypto is not speculation — but proving intelligence can be trusted?” Sachi Miyasaki sits down with dcbuilder.eth ⚪️ for a deep dive into the intersection of AI and crypto, from DC’s work building the ZKML community to why zero-knowledge machine learning could become a core trust layer for AI on the internet. They break down how ZKML makes it possible to prove that a machine learning model produced a specific output from specific inputs — without forcing everyone to rerun the full computation themselves. The conversation also explores why this matters for model accountability, transparency, and verifiable AI at scale, plus the projects pushing the space forward, from Modulus Labs and Giza to EZKL and new research around proof of inference.

BeaconLayer Podcast

73,815 Aufrufe • vor 4 Monaten