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General AI value is flowing into Onchain AI China Open-Weight Labs → Inference providers → Intelligent Routers Venice is eating more token share, DIEM secondary markets are getting established, and decentralized consumer inference are forming their structural moats Diving into the latest dynamic of General AI Onchain AI +... show more

0xJeff

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16,686 次观看 • 2 个月前 •via X (Twitter)

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Another flat week with so much happening below the surface - ████ became one of the top revenue-generating category in Crypto - Inference War is heating up on Bittensor with many players launching a decentralized inference network - The AI War is shifting from model to harness Covering where liquidity is moving & the trends happening within the broader AI and onchain AI In this week After Hour ↓

Another flat week with so much happening below the surface - ████ became one of the top revenue-generating category in Crypto - Inference War is heating up on Bittensor with many players launching a decentralized inference network - The AI War is shifting from model to harness Covering where liquidity is moving & the trends happening within the broader AI and onchain AI In this week After Hour ↓

0xJeff

15,576 次观看 • 1 个月前

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering

Madison Kanna

119,268 次观看 • 6 个月前

Jesse Pollak on the ecosystem forming around tokenized inference "There's this really cool tokenized inference market that Venice has innovated, where they've taken inference and turned it into a token called DIEM where you can buy it and you get $1 of inference per day" "That innovation of tokenizing inference has unlocked a ton of innovation around it, where people are using that tokenized inference to do things" "There's other projects that let people sell their tokenized inference at a discount so other people can get cheaper inference and the whole system works more efficiently" "I feel like that's the first time we're really seeing the intersection of AI plus markets plus crypto and it's thanks to Venice and it's happening on Base"

Jesse Pollak on the ecosystem forming around tokenized inference "There's this really cool tokenized inference market that Venice has innovated, where they've taken inference and turned it into a token called DIEM where you can buy it and you get $1 of inference per day" "That innovation of tokenizing inference has unlocked a ton of innovation around it, where people are using that tokenized inference to do things" "There's other projects that let people sell their tokenized inference at a discount so other people can get cheaper inference and the whole system works more efficiently" "I feel like that's the first time we're really seeing the intersection of AI plus markets plus crypto and it's thanks to Venice and it's happening on Base"

Market Bubble

26,240 次观看 • 2 个月前

My conversation with Tarun Chitra As a co-founder of Gauntlet and GP at Robot Ventures, Tarun has one of the sharpest frameworks for understanding market structure across both crypto and AI. In this episode we dig into why open source AI is unbundling faster than most people expect, and how the resulting stack looks surprisingly similar to DeFi. We spend time mapping the AI infrastructure layers directly onto crypto primitives and examining where value is actually going to accrue as models, harnesses, routers, and inference providers separate. At the center of the conversation is the belief that AI’s unbundling is creating a new competitive order-flow market (data centers competing like nodes, MEV-like dynamics for tokens/GPUs) while crypto itself has settled into a more mature “TradFi plus+” phase focused on trading, payments, and bringing real assets on-chain. We discuss: - The current state of crypto as TradFi+ and the decline of speculative narratives - Why AI is killing Bitcoin mining economics and weakening ETH value accrual - The architectural parallel between AI stacks and DeFi (Harnesses = Wallets, Routers = DEX aggregators, Models = Protocols, Inference Providers = LPs) - Why open source models are unbundling faster than traditional software - Agents as the next interface layer and the potential unbundling of ETFs -Cryptography, verifiable compute, and turning GPUs into digital assets - Onchain compute trading as the real crypto × AI opportunity - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of the Crypto Market 2:00 – Speculative Narratives Fade, Trading & Payments Remain 7:00 – AI’s Impact on Bitcoin Economics & Data Center Opportunity Cost 9:00 – ETH Value Accrual, Solana Positioning & DeFi Token Sustainability 15:00 – Trading Design Space & On-Chain Volume Upside 25:00 – AI Unbundling Thesis: Open-Source Models vs Data Centers 35:00 – The DeFi Mapping (Harnesses, Routers, Models, Inference) 48:00 – Agents, Preference Expression & Unbundling Traditional Products 1:00:00 – Real-Time Harness Generation & Active Learning 1:05:00 – Cryptography, Verifiable Compute & On-Chain GPU Markets 1:10:00 – Closing Thoughts: Where Value Accrues Next Enjoy!

My conversation with Tarun Chitra As a co-founder of Gauntlet and GP at Robot Ventures, Tarun has one of the sharpest frameworks for understanding market structure across both crypto and AI. In this episode we dig into why open source AI is unbundling faster than most people expect, and how the resulting stack looks surprisingly similar to DeFi. We spend time mapping the AI infrastructure layers directly onto crypto primitives and examining where value is actually going to accrue as models, harnesses, routers, and inference providers separate. At the center of the conversation is the belief that AI’s unbundling is creating a new competitive order-flow market (data centers competing like nodes, MEV-like dynamics for tokens/GPUs) while crypto itself has settled into a more mature “TradFi plus+” phase focused on trading, payments, and bringing real assets on-chain. We discuss: - The current state of crypto as TradFi+ and the decline of speculative narratives - Why AI is killing Bitcoin mining economics and weakening ETH value accrual - The architectural parallel between AI stacks and DeFi (Harnesses = Wallets, Routers = DEX aggregators, Models = Protocols, Inference Providers = LPs) - Why open source models are unbundling faster than traditional software - Agents as the next interface layer and the potential unbundling of ETFs -Cryptography, verifiable compute, and turning GPUs into digital assets - Onchain compute trading as the real crypto × AI opportunity - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of the Crypto Market 2:00 – Speculative Narratives Fade, Trading & Payments Remain 7:00 – AI’s Impact on Bitcoin Economics & Data Center Opportunity Cost 9:00 – ETH Value Accrual, Solana Positioning & DeFi Token Sustainability 15:00 – Trading Design Space & On-Chain Volume Upside 25:00 – AI Unbundling Thesis: Open-Source Models vs Data Centers 35:00 – The DeFi Mapping (Harnesses, Routers, Models, Inference) 48:00 – Agents, Preference Expression & Unbundling Traditional Products 1:00:00 – Real-Time Harness Generation & Active Learning 1:05:00 – Cryptography, Verifiable Compute & On-Chain GPU Markets 1:10:00 – Closing Thoughts: Where Value Accrues Next Enjoy!

Logan Jastremski

132,411 次观看 • 1 个月前

A decentralized AI compute play just outran 99% of the crypto market this month $AKT, the native token of Akash Network, is up 72% on the month and leading CoinMarketCap's Broad Market category despite a 12% pullback Saturday testing $0.595 support. The DePIN GPU marketplace lets users rent NVIDIA H100s for $1.49/hour vs $43K outright. Founder Greg Osuri presented at the Economist Impact AI Compute Summit in Amsterdam this week. Recent integrations with Venice ai and FLock io target decentralized AI inference, the same vertical NEAR and Sahara AI are also rotating into.

A decentralized AI compute play just outran 99% of the crypto market this month $AKT, the native token of Akash Network, is up 72% on the month and leading CoinMarketCap's Broad Market category despite a 12% pullback Saturday testing $0.595 support. The DePIN GPU marketplace lets users rent NVIDIA H100s for $1.49/hour vs $43K outright. Founder Greg Osuri presented at the Economist Impact AI Compute Summit in Amsterdam this week. Recent integrations with Venice ai and FLock io target decentralized AI inference, the same vertical NEAR and Sahara AI are also rotating into.

BSCN

10,984 次观看 • 4 个月前

Tesla is a world-class execution machine that's systematically expanding into the largest addressable markets in history. • The auto business was just their first act - AI transport and AI labor are where the real massive value creation will happen. • AI Transport will be much larger than the entire traditional auto industry. • Data and network effects will create a virtuous cycle of continuously improving AI driving giving Tesla a competitive advantage. • AI labor will be biggest market of all - even AI transport is just a subset of AI labor. In summary, Tesla's true advantage is their ability to out-execute world-class competitors in massive new markets.

Tesla is a world-class execution machine that's systematically expanding into the largest addressable markets in history. • The auto business was just their first act - AI transport and AI labor are where the real massive value creation will happen. • AI Transport will be much larger than the entire traditional auto industry. • Data and network effects will create a virtuous cycle of continuously improving AI driving giving Tesla a competitive advantage. • AI labor will be biggest market of all - even AI transport is just a subset of AI labor. In summary, Tesla's true advantage is their ability to out-execute world-class competitors in massive new markets.

Dave Lee

187,984 次观看 • 1 年前

Eric Schmidt says the biggest returns in AI won’t come from the giants. Established tech companies are already highly valued. Instead, the real opportunity lies in businesses transformed by AI. Invest in companies where AI is the key to unlocking new growth. That’s where the next big wave of value will emerge.

Eric Schmidt says the biggest returns in AI won’t come from the giants. Established tech companies are already highly valued. Instead, the real opportunity lies in businesses transformed by AI. Invest in companies where AI is the key to unlocking new growth. That’s where the next big wave of value will emerge.

Wes Roth

33,450 次观看 • 7 个月前

FOMO IS LIVE ON ROBINHOOD CHAIN. Robinhood Chain is building an AI-native onchain economy, purpose-built to make real-world assets investable onchain. FLock now brings FOMO, the first Fair Open Model Offering, to Robinhood Crypto, extending that frontier from financial assets to artificial intelligence. AI Model Tokens aren’t just another crypto asset. They’re a new onchain primitive, backed by model inference through FLock API Platform, FLock’s enterprise-grade gateway for open-source AI models. Built for the agentic economy, FOMO connects Model Token value to real AI usage, giving anyone a new way to launch, trade, and back AI models. Thousands of AI agents are being tokenised. Now, the open-source intelligence powering them can be too. This is not a phase. This is a supercycle. Explore Model Tokens on FOMO. Now live for trading on Uniswap.

FOMO IS LIVE ON ROBINHOOD CHAIN. Robinhood Chain is building an AI-native onchain economy, purpose-built to make real-world assets investable onchain. FLock now brings FOMO, the first Fair Open Model Offering, to Robinhood Crypto, extending that frontier from financial assets to artificial intelligence. AI Model Tokens aren’t just another crypto asset. They’re a new onchain primitive, backed by model inference through FLock API Platform, FLock’s enterprise-grade gateway for open-source AI models. Built for the agentic economy, FOMO connects Model Token value to real AI usage, giving anyone a new way to launch, trade, and back AI models. Thousands of AI agents are being tokenised. Now, the open-source intelligence powering them can be too. This is not a phase. This is a supercycle. Explore Model Tokens on FOMO. Now live for trading on Uniswap.

FLock.io

16,851 次观看 • 20 天前

Lightchain AI – Decentralized Inference Demo 🍂🥧 + Blockchain Rewards In this video, we showcase how Lightchain AI’s decentralized inference engine (AIVM + PoI + Federated Learning) runs a real-world prompt “What is the best way to make pumpkin pie for thanksgiving dinner?” 💰 Blockchain Rewards in Action This demo doesn’t just show inference — it shows how inference providers are rewarded for their work. The provider that processed this prompt was automatically rewarded on the Lightchain testnet. 🍁 Why It Matters Unlike centralized AI, Lightchain AI distributes inference across a global network of participants. Nodes earn blockchain rewards for providing compute, ensuring a trustless, transparent, and economically sustainable ecosystem. With pay-to-prompt mechanics and DAO governance, Lightchain AI creates a fair AI economy for all. 🌐 Learn more at-

Lightchain AI – Decentralized Inference Demo 🍂🥧 + Blockchain Rewards In this video, we showcase how Lightchain AI’s decentralized inference engine (AIVM + PoI + Federated Learning) runs a real-world prompt “What is the best way to make pumpkin pie for thanksgiving dinner?” 💰 Blockchain Rewards in Action This demo doesn’t just show inference — it shows how inference providers are rewarded for their work. The provider that processed this prompt was automatically rewarded on the Lightchain testnet. 🍁 Why It Matters Unlike centralized AI, Lightchain AI distributes inference across a global network of participants. Nodes earn blockchain rewards for providing compute, ensuring a trustless, transparent, and economically sustainable ecosystem. With pay-to-prompt mechanics and DAO governance, Lightchain AI creates a fair AI economy for all. 🌐 Learn more at-

Lightchain AI

18,730 次观看 • 1 年前

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter

Tommy

24,582 次观看 • 1 个月前

We asked Tom Schmidt ＞|＜ from Dragonfly ＞|＜ about AI x crypto. "We are more bearish on this category." "A lot of AI crypto is broken down into people trying to do decentralized inference, this GPU marketplace. This is an old idea in crypto." "If you want to train a state-of-the-art model, you don't use 1M consumer-grade GPUs around the world. You want one big co-located A100 cluster." "The areas where we are more excited about are MPC and agent payments, where stablecoins are uniquely positioned to provide microtransactions."

We asked Tom Schmidt ＞|＜ from Dragonfly ＞|＜ about AI x crypto. "We are more bearish on this category." "A lot of AI crypto is broken down into people trying to do decentralized inference, this GPU marketplace. This is an old idea in crypto." "If you want to train a state-of-the-art model, you don't use 1M consumer-grade GPUs around the world. You want one big co-located A100 cluster." "The areas where we are more excited about are MPC and agent payments, where stablecoins are uniquely positioned to provide microtransactions."

TBPN

41,164 次观看 • 1 年前

What will it take to power the next phase of #AI? After more than 15 years of flat growth, US electricity demand is rising again as AI moves into real world inference, answering questions, powering applications, and embedding itself into daily life. On the latest episode of The Bid #podcast, Will Su from BlackRock’s Fundamental Equities Group joins host Oscar Pulido to explore how investments in natural gas, solar, battery storage, and nuclear power are shaping a new infrastructure cycle and what it means for utilities and capital markets. 🎧 Listen:

What will it take to power the next phase of #AI? After more than 15 years of flat growth, US electricity demand is rising again as AI moves into real world inference, answering questions, powering applications, and embedding itself into daily life. On the latest episode of The Bid #podcast, Will Su from BlackRock’s Fundamental Equities Group joins host Oscar Pulido to explore how investments in natural gas, solar, battery storage, and nuclear power are shaping a new infrastructure cycle and what it means for utilities and capital markets. 🎧 Listen:

BlackRock

14,277 次观看 • 7 个月前

Chips are the foundation of every AI experience. That's why understanding the hardware behind the software has never mattered more. When you ask a chatbot a question or generate an image, there's a physical chip somewhere doing the heavy lifting. For most of computing history, that was a CPU—the "brain" of a computer—great for general tasks needed to run software and operating systems. AI is more complex: for workloads called training and inference, AI needs to perform trillions of calculations in parallel. That's where AI accelerators come in. Purpose-built accelerators can deliver significantly better performance and efficiency than general-purpose chips. Amazon Web Services Trainium chips are an example—purpose-built for AI training and inference. New chips for a new era. ⬇️

Chips are the foundation of every AI experience. That's why understanding the hardware behind the software has never mattered more. When you ask a chatbot a question or generate an image, there's a physical chip somewhere doing the heavy lifting. For most of computing history, that was a CPU—the "brain" of a computer—great for general tasks needed to run software and operating systems. AI is more complex: for workloads called training and inference, AI needs to perform trillions of calculations in parallel. That's where AI accelerators come in. Purpose-built accelerators can deliver significantly better performance and efficiency than general-purpose chips. Amazon Web Services Trainium chips are an example—purpose-built for AI training and inference. New chips for a new era. ⬇️

Amazon

27,151 次观看 • 4 个月前

Interview with Nebius Co-Founder Roman Chernin Please like & share this video so that all $NBIS investors on X will see it! :) If you prefer watching on YouTube: Timestamps: 00:00 - Why AI Infrastructure Is So Hard to Understand 00:24 - Market Fragmentation and What Actually Differentiates Providers 01:30 - Consolidation, Segmentation, and the Future AI Cloud Landscape 02:56 - What Analysts and VCs Still Get Wrong About AI Infrastructure 05:34 - Nebius Cloud: Product Readiness and Customer Proof Points 07:42 - Why Inference Workloads Are Exploding 09:11 - Training vs. Inference: How AI Models Actually Reach Production 10:10 - Why Inference Market Share May Concentrate Around a Few Winners 12:36 - Customer Use Cases: Coding, Enterprise AI, and Real-World Adoption 14:01 - Why Integrated Training and Inference Matter Strategically 16:01 - Building Scalable AI Infrastructure With High Utilization 18:24 - Token Factory: Inference as a Managed Service 20:24 - Revolut Case Study: AI-Driven Product Enhancements 22:56 - Token Factory Performance Optimization and Competitive Advantage 25:07 - Scale, Capacity, and Efficiency as Growth Drivers 28:36 - Why Inference Capacity Could Become the Next Major Bottleneck 30:10 - How Nebius Benchmarks Performance Across Providers 33:14 - The Future Size and Shape of the Inference Market 36:38 - Value-Based Pricing: Moving Beyond Cost per GPU Hour 40:55 - How Nebius Wins Deals: Quality, Performance, and Customer Experience 44:53 - Autonomous AI Platforms and the Rise of Agent-Based Models 47:28 - Tavily, Agentic Applications, and the Next Layer of the AI Stack 50:45 - Strategic Trade-Offs: Scaling, Product Roadmap, and Customer Relevance 55:40 - Final Thoughts: Adapting to the Next Shift in AI Workloads Nebius Roman Chernin

Interview with Nebius Co-Founder Roman Chernin Please like & share this video so that all $NBIS investors on X will see it! :) If you prefer watching on YouTube: Timestamps: 00:00 - Why AI Infrastructure Is So Hard to Understand 00:24 - Market Fragmentation and What Actually Differentiates Providers 01:30 - Consolidation, Segmentation, and the Future AI Cloud Landscape 02:56 - What Analysts and VCs Still Get Wrong About AI Infrastructure 05:34 - Nebius Cloud: Product Readiness and Customer Proof Points 07:42 - Why Inference Workloads Are Exploding 09:11 - Training vs. Inference: How AI Models Actually Reach Production 10:10 - Why Inference Market Share May Concentrate Around a Few Winners 12:36 - Customer Use Cases: Coding, Enterprise AI, and Real-World Adoption 14:01 - Why Integrated Training and Inference Matter Strategically 16:01 - Building Scalable AI Infrastructure With High Utilization 18:24 - Token Factory: Inference as a Managed Service 20:24 - Revolut Case Study: AI-Driven Product Enhancements 22:56 - Token Factory Performance Optimization and Competitive Advantage 25:07 - Scale, Capacity, and Efficiency as Growth Drivers 28:36 - Why Inference Capacity Could Become the Next Major Bottleneck 30:10 - How Nebius Benchmarks Performance Across Providers 33:14 - The Future Size and Shape of the Inference Market 36:38 - Value-Based Pricing: Moving Beyond Cost per GPU Hour 40:55 - How Nebius Wins Deals: Quality, Performance, and Customer Experience 44:53 - Autonomous AI Platforms and the Rise of Agent-Based Models 47:28 - Tavily, Agentic Applications, and the Next Layer of the AI Stack 50:45 - Strategic Trade-Offs: Scaling, Product Roadmap, and Customer Relevance 55:40 - Final Thoughts: Adapting to the Next Shift in AI Workloads Nebius Roman Chernin

Daniel Koss

204,819 次观看 • 4 个月前

AI, compute, and Tokens are beginning to reshape the relationship between technology and the global economy. In DeepTalk Vol.4 — The Token Era: Compute Infrastructure Reshaping the Future Economy — we explored some key questions: What skills will remain irreplaceable in the AI era? Why is the logic behind Token valuation changing? How will humans and AI collaborate in the future? And what will define the next generation of competitiveness? This conversation goes beyond technology itself. It’s about how AI is starting to reshape economic systems, infrastructure, and the way value is created. #Token #AI #Infrastructure #ChinaAMC #DeepTalk

AI, compute, and Tokens are beginning to reshape the relationship between technology and the global economy. In DeepTalk Vol.4 — The Token Era: Compute Infrastructure Reshaping the Future Economy — we explored some key questions: What skills will remain irreplaceable in the AI era? Why is the logic behind Token valuation changing? How will humans and AI collaborate in the future? And what will define the next generation of competitiveness? This conversation goes beyond technology itself. It’s about how AI is starting to reshape economic systems, infrastructure, and the way value is created. #Token #AI #Infrastructure #ChinaAMC #DeepTalk

China Asset Management

12,846 次观看 • 3 个月前

Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

Fireside Alpha

162,832 次观看 • 2 个月前

Connecting all intelligence with ORA ⏺️ So, how does it work? Let's dive in 👇 At the heart of ORA is the Onchain AI Oracle (OAO), designed to empower dApp developers by seamlessly integrating verifiable AI inference into their applications without sacrificing decentralization. At the center of ORA is Optimistic Machine Learning (opML). This technology ensures that AI inferences originate from the correct models and that results remain untampered. A robust network of nodes independently verifies each AI inference and can raise challenges if tampering is suspected. Want to be part of this decentralized movement? You can easily run your own node using Tora, our user-friendly node software. Built on Optimistic Machine Learning (opML), our Onchain AI Oracle connects the best open-source AI models to the blockchain. This means any dApp can easily become an AI dApp! With our Initial Model Offering (IMO), developers can tokenize open-source models, effectively overcoming the cold start problem by securing essential funding for their projects. ORA is integrated with several L2s, including Mantle Network, Linea.eth, and Arbitrum. This allows you to build on low-cost chains that best suit your needs. ORA is committed to bringing decentralized, verifiable AI to the blockchain. Are you ready to join us? Use OAO: Read more about OAO: Learn about IMO: Use Tora:

Connecting all intelligence with ORA ⏺️ So, how does it work? Let's dive in 👇 At the heart of ORA is the Onchain AI Oracle (OAO), designed to empower dApp developers by seamlessly integrating verifiable AI inference into their applications without sacrificing decentralization. At the center of ORA is Optimistic Machine Learning (opML). This technology ensures that AI inferences originate from the correct models and that results remain untampered. A robust network of nodes independently verifies each AI inference and can raise challenges if tampering is suspected. Want to be part of this decentralized movement? You can easily run your own node using Tora, our user-friendly node software. Built on Optimistic Machine Learning (opML), our Onchain AI Oracle connects the best open-source AI models to the blockchain. This means any dApp can easily become an AI dApp! With our Initial Model Offering (IMO), developers can tokenize open-source models, effectively overcoming the cold start problem by securing essential funding for their projects. ORA is integrated with several L2s, including Mantle Network, Linea.eth, and Arbitrum. This allows you to build on low-cost chains that best suit your needs. ORA is committed to bringing decentralized, verifiable AI to the blockchain. Are you ready to join us? Use OAO: Read more about OAO: Learn about IMO: Use Tora:

ORA

453,792 次观看 • 2 年前

NEW EP: Purpose-Built AI Chains with Anish Agnihotri and Saneel Seerni of Ritual The future of blockchain design may rest in building systems meant for agents. In today's pod @Robbie_rollup and sat down with and Saneel of Ritual, to cover: > AI Execution Onchain vs. Traditional Models > Why DeFi needs AI More Than Just Bots > How Consensus & Compute Works in AI-Driven Blockchains > Composability & Coordination of Onchain AI > Where AI & DeFi are Headed Next Full episode links below. Timestamps: 00:00 Intro to Ritual 5:50 AI Crypto Convergence 14:03 Building AI Agents 25:49 AI Ethical Considerations 37:23 State Bloat & Fast Execution 49:58 Verifying Outputs 58:16 The Butterfly Effect

NEW EP: Purpose-Built AI Chains with Anish Agnihotri and Saneel Seerni of Ritual The future of blockchain design may rest in building systems meant for agents. In today's pod @Robbie_rollup and sat down with and Saneel of Ritual, to cover: > AI Execution Onchain vs. Traditional Models > Why DeFi needs AI More Than Just Bots > How Consensus & Compute Works in AI-Driven Blockchains > Composability & Coordination of Onchain AI > Where AI & DeFi are Headed Next Full episode links below. Timestamps: 00:00 Intro to Ritual 5:50 AI Crypto Convergence 14:03 Building AI Agents 25:49 AI Ethical Considerations 37:23 State Bloat & Fast Execution 49:58 Verifying Outputs 58:16 The Butterfly Effect

The Rollup

58,968 次观看 • 1 年前