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Introducing a new cryptographic governance primitive >> Conviction - The Formula: Conviction = Stake x Time. - Linear Unlocking: Lock Alpha tokens for a set duration (e.g., 365 days) to prove long-term commitment. - Mutable Ownership: If an owner acts maliciously, the community can collectively lock their tokens to...

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Openτensor Foundaτion

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47,209 views • 5 months ago •via X (Twitter)

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We’re back for Episode 14 of TAO Talk 🚨 calanthia from Masa joins 563 and brody this week to chat about new subnets and AI agents sourcing intelligence from Bittensor! The group chats about: - $TAO -pilling AI/ML chads at NeurIPS Conference feat. const Crucible Labs Macrocosmos Manifold and Yuma - JJ teaming up with Cameron Fairchild to form Laτenτ Holdings, which will validate and help scale subnets - Crucible Labs drops a subnet analysis framework - Celium offering H100s cheaper than any other provider - Tao360 releases inaugural research report for their AI-enabled subnet analysis tool @notYourBananaa - Masa unveils the AI Agent Arena on SN59 /// Timestamps: 00:00 Intro 01:10 Subnet 42 and Agent Arena: Masa’s Subnets 03:00 Real-Time Data Networks for AI 04:20 How Masa is Building AI Agent Arenas Inspired by Gladiators 06:10 Decentralized AI and Bittensor: The Growing Ecosystem 08:15 AI Meets Web3: Masa’s Role in Revolutionizing Data Networks 10:00 The Future of AI Agents: Intelligent Societies and Real-Time Data 12:05 Why Masa Chose Bittensor 14:10 $TAO Incentives and the Future of AI Decentralization 16:25 Bittensor and the Rise of Agent Competition: Masa’s Perspective 18:00 Exploring AI Agent Societies 20:30 Creating Competitive AI Arenas: The Agent Arena Subnet Explained 23:00 Calanthia on the Challenges of Web3 AI Development 25:10 Bringing Web2 Developers into Web3: Lessons from Masa 27:30 The Evolution of AI: From Dumb Agents to Intelligent Societies 30:00 AI Agents as the Future of Interaction in Decentralized AI 34:00 The Agent Arena’s Vision: Competition, Incentives, and Innovation
37:00

We’re back for Episode 14 of TAO Talk 🚨 calanthia from Masa joins 563 and brody this week to chat about new subnets and AI agents sourcing intelligence from Bittensor! The group chats about: - $TAO -pilling AI/ML chads at NeurIPS Conference feat. const Crucible Labs Macrocosmos Manifold and Yuma - JJ teaming up with Cameron Fairchild to form Laτenτ Holdings, which will validate and help scale subnets - Crucible Labs drops a subnet analysis framework - Celium offering H100s cheaper than any other provider - Tao360 releases inaugural research report for their AI-enabled subnet analysis tool @notYourBananaa - Masa unveils the AI Agent Arena on SN59 /// Timestamps: 00:00 Intro 01:10 Subnet 42 and Agent Arena: Masa’s Subnets 03:00 Real-Time Data Networks for AI 04:20 How Masa is Building AI Agent Arenas Inspired by Gladiators 06:10 Decentralized AI and Bittensor: The Growing Ecosystem 08:15 AI Meets Web3: Masa’s Role in Revolutionizing Data Networks 10:00 The Future of AI Agents: Intelligent Societies and Real-Time Data 12:05 Why Masa Chose Bittensor 14:10 $TAO Incentives and the Future of AI Decentralization 16:25 Bittensor and the Rise of Agent Competition: Masa’s Perspective 18:00 Exploring AI Agent Societies 20:30 Creating Competitive AI Arenas: The Agent Arena Subnet Explained 23:00 Calanthia on the Challenges of Web3 AI Development 25:10 Bringing Web2 Developers into Web3: Lessons from Masa 27:30 The Evolution of AI: From Dumb Agents to Intelligent Societies 30:00 AI Agents as the Future of Interaction in Decentralized AI 34:00 The Agent Arena’s Vision: Competition, Incentives, and Innovation

TAO τalk 🥩🦍

24,929 views • 1 year ago

Someone just stole from 37,000 $TAO holders and walked away clean. Not because they broke a rule. Because no rule existed to stop them. That changes today. Here is what happened. Covenant AI ran one of the most watched subnets on Bittensor. On April 10, the founder sold their entire position and disappeared. No warning. No announcement. No on-chain signal. By the time holders found out, the price had already moved against them. This was not a hack. This was not a bug. This was a founder legally exiting into their own community with zero accountability. Bittensor just closed that door permanently. The Conviction upgrade is live on mainnet today. Every emission a subnet owner earns now locks automatically the moment it arrives. They cannot touch it immediately. If they want to exit they must submit a public unlock transaction on-chain. Visible to every single person on the network the second it is submitted. Then the clock starts. 30 days before 63% of their position becomes spendable. 90 days before 95% is accessible. You now have a month of warning before the first dollar of sell pressure hits. A silent exit is no longer possible. The founder has to tell you they are leaving before they can leave. And it goes further. Any holder can now lock their tokens toward a different address they believe would run the subnet better. The address with the most locked support behind it becomes eligible to take over entirely. Bad owners can be replaced by the community before they do damage. Before today, subnet investing had one risk nobody could price. The person running it could vanish overnight, and you would never see it coming. That risk has been removed from the equation. Skin in the game used to be a promise. Now, it is a number on a block explorer that every holder can verify in real time. The people who understand what accountable infrastructure means for the value of $TAO will not need to explain themselves later. This is still early.
23:08

Someone just stole from 37,000 $TAO holders and walked away clean. Not because they broke a rule. Because no rule existed to stop them. That changes today. Here is what happened. Covenant AI ran one of the most watched subnets on Bittensor. On April 10, the founder sold their entire position and disappeared. No warning. No announcement. No on-chain signal. By the time holders found out, the price had already moved against them. This was not a hack. This was not a bug. This was a founder legally exiting into their own community with zero accountability. Bittensor just closed that door permanently. The Conviction upgrade is live on mainnet today. Every emission a subnet owner earns now locks automatically the moment it arrives. They cannot touch it immediately. If they want to exit they must submit a public unlock transaction on-chain. Visible to every single person on the network the second it is submitted. Then the clock starts. 30 days before 63% of their position becomes spendable. 90 days before 95% is accessible. You now have a month of warning before the first dollar of sell pressure hits. A silent exit is no longer possible. The founder has to tell you they are leaving before they can leave. And it goes further. Any holder can now lock their tokens toward a different address they believe would run the subnet better. The address with the most locked support behind it becomes eligible to take over entirely. Bad owners can be replaced by the community before they do damage. Before today, subnet investing had one risk nobody could price. The person running it could vanish overnight, and you would never see it coming. That risk has been removed from the equation. Skin in the game used to be a promise. Now, it is a number on a block explorer that every holder can verify in real time. The people who understand what accountable infrastructure means for the value of $TAO will not need to explain themselves later. This is still early.

2xnmore

19,549 views • 4 months ago

A subnet founder allegedly walked away with $10M in TAO and torched his own community in the process. On TWiST, Mark Jeffrey of Stillcore Capital joins us to break down what really happened with Templar/Covenant, the overall fixes that co-founder Const has proposed, and why Bittensor’s incentive engine may have been a victim of its own success. PLUS we’re joined by subnet operators Will Squires and Steffan Cruz (of MacroCosmos) and Ken Miyachi of BitMind to get their perspective on the controversy, and to demo the exciting projects they’re still building on the blockchain. 0:00 Mark Jeffrey joins the show! 2:18 How Mark Jeffrey learned about Bittensor. 6:17 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 7:22 Mark Jeffrey's Bittensor investments. 9:25 Check out our discussion with Nova: 10:16 Sentry - New users can get $240 in free credits when they go to and use the code TWIST 10:41 Check out Ridges! 11:53 How trading alpha tokens works on Bittensor 12:44 Subnet drama: what happened? 16:01 Do subnet owners have too much power? 18:33 Check out our conversation with Sam Dare (2268): 19:10 How Sam Dare should've handled walking away (per Mark Jeffrey) 20:02 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit to learn more. 23:29 Who should subnets be owned by? 24:02 Ken Miyachi from BitMind joins the show 30:56 Netsuite - Get the free business guide Demystifying AI at 31:06 Ken's $3M raise & investors (Arch, Canonical, Mechanism) 33:18 Token vs. equity: how to think about a subnet investment. 41:57 Will Squires and Stefan Kruse of MacroCosmos join the show 42:54 How MacroCosmos lets anyone become a compute provider. 56:29 Stefan on the Covenant drama: "disappointing, but solvable" 1:02:11 Off-duty with J-Cal, Mark Jeffrey, and Lon Harris 1:02:48 Bieber vs. Carpenter: does Coachella owe you a spectacle? 1:15:20 Jason says Staples should pay the "Staples baddie" $1M/year cc: @jason, Lon Harris, Mark Jeffrey, const, Distributed State, templar, covenant, Macrocosmos, Apex・SN1, IOTA ・ SN9, Ken Jon, BitMind BitMindAI 🎥 Watch the full episode here 👇
1:18:38

A subnet founder allegedly walked away with $10M in TAO and torched his own community in the process. On TWiST, Mark Jeffrey of Stillcore Capital joins us to break down what really happened with Templar/Covenant, the overall fixes that co-founder Const has proposed, and why Bittensor’s incentive engine may have been a victim of its own success. PLUS we’re joined by subnet operators Will Squires and Steffan Cruz (of MacroCosmos) and Ken Miyachi of BitMind to get their perspective on the controversy, and to demo the exciting projects they’re still building on the blockchain. 0:00 Mark Jeffrey joins the show! 2:18 How Mark Jeffrey learned about Bittensor. 6:17 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 7:22 Mark Jeffrey's Bittensor investments. 9:25 Check out our discussion with Nova: 10:16 Sentry - New users can get $240 in free credits when they go to and use the code TWIST 10:41 Check out Ridges! 11:53 How trading alpha tokens works on Bittensor 12:44 Subnet drama: what happened? 16:01 Do subnet owners have too much power? 18:33 Check out our conversation with Sam Dare (2268): 19:10 How Sam Dare should've handled walking away (per Mark Jeffrey) 20:02 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit to learn more. 23:29 Who should subnets be owned by? 24:02 Ken Miyachi from BitMind joins the show 30:56 Netsuite - Get the free business guide Demystifying AI at 31:06 Ken's $3M raise & investors (Arch, Canonical, Mechanism) 33:18 Token vs. equity: how to think about a subnet investment. 41:57 Will Squires and Stefan Kruse of MacroCosmos join the show 42:54 How MacroCosmos lets anyone become a compute provider. 56:29 Stefan on the Covenant drama: "disappointing, but solvable" 1:02:11 Off-duty with J-Cal, Mark Jeffrey, and Lon Harris 1:02:48 Bieber vs. Carpenter: does Coachella owe you a spectacle? 1:15:20 Jason says Staples should pay the "Staples baddie" $1M/year cc: @jason, Lon Harris, Mark Jeffrey, const, Distributed State, templar, covenant, Macrocosmos, Apex・SN1, IOTA ・ SN9, Ken Jon, BitMind BitMindAI 🎥 Watch the full episode here 👇

This Week in Startups

29,964 views • 5 months ago

$TAO just reclaimed the #1 AI crypto spot. Most people saw the headline. Almost nobody understands what it means for the price. Here is the data. $NEAR built real infrastructure. Partnerships. Developer activity. A legitimate ecosystem. $TAO just walked past it anyway. Not because of hype. Because Bittensor is the only AI crypto with a functioning marketplace for machine intelligence where supply, demand, and price discovery are all happening on-chain right now. That is not a roadmap. That is a live network. The numbers. 120+ subnets running today. $1.4B+ total ecosystem value. Chutes AI subnet: 150B+ tokens per day. Grayscale GTAO Trust: already live. Single subnet listed on the marketplace at $970,000 asking price. Subnets are becoming assets. The market is starting to price that. What the emission data is telling you. Emission rate is the network's vote on where the most valuable work is being done. When a subnet gains emission share, the collective stake-weighted intelligence of the network has decided that subnet's output is worth more of the TAO supply. Chutes AI gaining emissions while processing 150B tokens daily is not a coincidence. The network is directing capital toward proven output before any headline announces it. Why mainstream money changes everything. James Altucher just launched bluetao. ai, a TAO-powered ChatGPT alternative built directly on Bittensor subnets. He did not just buy the token. He built a product on the network. Products built on a network create structural demand for the native asset. That is how every successful L1 cycle has worked. Bittensor is now getting that builder activity from outside the crypto native world. That is a different signal from a price target tweet. Why $TAO is structurally different. Most AI tokens are betting their chain becomes the preferred environment for AI development. $TAO is not betting on becoming infrastructure. It already is. 120+ subnets running. Miners competing. Validators setting weights. Alpha tokens being priced in real time. The difference between $TAO and every other AI crypto is the difference between a city under construction and a city people are already living in. Van de Poppe said $1,000 to $2,000 in 12 months. He gave you the narrative. The subnet emission data is the mechanism he did not explain. Now you have both. $TAO at $313 with a $3.42B market cap is still early relative to what this network is actually processing. Centralised AI infrastructure companies are valued at hundreds of billions for processing far less novel work than a decentralised intelligence marketplace running 120+ competing subnets simultaneously. The repricing has not happened yet. The subnet marketplace listing at $970,000 is telling you something the price has not caught up to yet.
16:52

$TAO just reclaimed the #1 AI crypto spot. Most people saw the headline. Almost nobody understands what it means for the price. Here is the data. $NEAR built real infrastructure. Partnerships. Developer activity. A legitimate ecosystem. $TAO just walked past it anyway. Not because of hype. Because Bittensor is the only AI crypto with a functioning marketplace for machine intelligence where supply, demand, and price discovery are all happening on-chain right now. That is not a roadmap. That is a live network. The numbers. 120+ subnets running today. $1.4B+ total ecosystem value. Chutes AI subnet: 150B+ tokens per day. Grayscale GTAO Trust: already live. Single subnet listed on the marketplace at $970,000 asking price. Subnets are becoming assets. The market is starting to price that. What the emission data is telling you. Emission rate is the network's vote on where the most valuable work is being done. When a subnet gains emission share, the collective stake-weighted intelligence of the network has decided that subnet's output is worth more of the TAO supply. Chutes AI gaining emissions while processing 150B tokens daily is not a coincidence. The network is directing capital toward proven output before any headline announces it. Why mainstream money changes everything. James Altucher just launched bluetao. ai, a TAO-powered ChatGPT alternative built directly on Bittensor subnets. He did not just buy the token. He built a product on the network. Products built on a network create structural demand for the native asset. That is how every successful L1 cycle has worked. Bittensor is now getting that builder activity from outside the crypto native world. That is a different signal from a price target tweet. Why $TAO is structurally different. Most AI tokens are betting their chain becomes the preferred environment for AI development. $TAO is not betting on becoming infrastructure. It already is. 120+ subnets running. Miners competing. Validators setting weights. Alpha tokens being priced in real time. The difference between $TAO and every other AI crypto is the difference between a city under construction and a city people are already living in. Van de Poppe said $1,000 to $2,000 in 12 months. He gave you the narrative. The subnet emission data is the mechanism he did not explain. Now you have both. $TAO at $313 with a $3.42B market cap is still early relative to what this network is actually processing. Centralised AI infrastructure companies are valued at hundreds of billions for processing far less novel work than a decentralised intelligence marketplace running 120+ competing subnets simultaneously. The repricing has not happened yet. The subnet marketplace listing at $970,000 is telling you something the price has not caught up to yet.

2xnmore

12,150 views • 3 months ago

The rebranding $MOA to $AIM and strategy of MetaOasisVR 1⃣ Quick recruitment of AI Talent 2⃣ Technological differentiation from other metaverse platforms and a long-term technological roadmap 3⃣ New rebranding tailored to AI technology application 4⃣ Establish marketing strategies tailored to market trends Tools introducing #AI technology are emerging around the world, and MetaOasis has also been able to decorate my land since the launch of the #mobile version In order to quickly build a creative economy, we want to keep up with global trends. We will brand "Inception," a #GenerativeAI #creator tool, for the long term, Through this, #MetaOasis will become a Generative AI-based #Web3 creator #ecosystem #metaverse in the future. It is a concept in which creators participate in creation based on psychometric methods such as #MBTI, and eventually #NFT content #Avatar, #Building, Environment, #Esset, #GamingContents The reason why we chose Avalanche Avalanche🔺 We considered various chains to expand the various games and ecosystems of Metaoasis, and among them, we judged that avalanche was excellent in efficiency. Avalanche Game Ecosystem View Centered on Subnet ✅ Blockchain game developers can distribute smart contracts by choosing between Avalanche's "C-Chain" and customized chain's "Subnet" depending on the function ✅ Ideal for self-chain subnet utilization when gas cost payment system, high transaction throughput, and strict access control are required ✅ Avalanche provides a tooling ecosystem and support programs for game development on the subnet ✅ Notable Avalanche game subnets, '#SHRAPNEL', #OffTheGrid and #MetaDOS A world of bottom-up inception that can quickly implement a metaverse environment We are planning to build it. It is ideal to use a subnet when 1) Flexible customized environment and 2) stability and security are important in game development. Because Subnet is its own chain, it allows developers to set logic specific to their games and provides an independent operating environment. For example, various functions, including gas payment systems and EVMs, can be customized. This flexibility effectively reduces costs and resources by allowing game developers to effectively implement the functions required by their games. In addition, the subnet enhances scalability and service quality through its own transaction processing capabilities. Since transaction completeness is not dependent on the main chain, the game service is not affected by transactions of other projects, so the user experience remains stable. Furthermore, access control and personal information protection functions can be set, ensuring high security and stability of user data. If you are concerned about introducing a subnet, but need to reduce resources and costs, you may start development on C-Chain, Avalanche's main network, and adopt a strategy to flexibly move assets to the subnet as needed in the future. Avalanche Subnet: Custom Chain Revolution for Games #Avalanche is pioneering the Web3 game market that has been developed beyond the limits of the existing game industry through subnet technology. Let's find out the strategy of utilizing the Avalanche subnet and the prospect of the Avalanche game ecosystem centered on the subnet. Submit Wallet Address for Migration 🔗 1. Submit the Wallet holding the $MOA 2. Submit the Wallet Address will receive $AIM Airdrop 3. Submission Deadline 31.DEC 2023 - 20.00 PM (JST ,KST) (+UTC9) Token Informations of $AIM $AIM - Artificial Intelligence Metaverse Contract : 0xCEeE63fF114F8e8deBF5E78a14e770E5B905eA91 Chain : Erc20 - Avalanche (AVAX) Decimals: 18 5,000,000,000 $AIM #Metaverse #Gamefi #Fun #Blockchain #P2E #PLAYFORFREE #ETH #polygon #chainlink #METAMASK #COINBASEWALLET #BITGETWALLET #BURRITOWALLET #AVALANCHE
0:26

The rebranding $MOA to $AIM and strategy of MetaOasisVR 1⃣ Quick recruitment of AI Talent 2⃣ Technological differentiation from other metaverse platforms and a long-term technological roadmap 3⃣ New rebranding tailored to AI technology application 4⃣ Establish marketing strategies tailored to market trends Tools introducing #AI technology are emerging around the world, and MetaOasis has also been able to decorate my land since the launch of the #mobile version In order to quickly build a creative economy, we want to keep up with global trends. We will brand "Inception," a #GenerativeAI #creator tool, for the long term, Through this, #MetaOasis will become a Generative AI-based #Web3 creator #ecosystem #metaverse in the future. It is a concept in which creators participate in creation based on psychometric methods such as #MBTI, and eventually #NFT content #Avatar, #Building, Environment, #Esset, #GamingContents The reason why we chose Avalanche Avalanche🔺 We considered various chains to expand the various games and ecosystems of Metaoasis, and among them, we judged that avalanche was excellent in efficiency. Avalanche Game Ecosystem View Centered on Subnet ✅ Blockchain game developers can distribute smart contracts by choosing between Avalanche's "C-Chain" and customized chain's "Subnet" depending on the function ✅ Ideal for self-chain subnet utilization when gas cost payment system, high transaction throughput, and strict access control are required ✅ Avalanche provides a tooling ecosystem and support programs for game development on the subnet ✅ Notable Avalanche game subnets, '#SHRAPNEL', #OffTheGrid and #MetaDOS A world of bottom-up inception that can quickly implement a metaverse environment We are planning to build it. It is ideal to use a subnet when 1) Flexible customized environment and 2) stability and security are important in game development. Because Subnet is its own chain, it allows developers to set logic specific to their games and provides an independent operating environment. For example, various functions, including gas payment systems and EVMs, can be customized. This flexibility effectively reduces costs and resources by allowing game developers to effectively implement the functions required by their games. In addition, the subnet enhances scalability and service quality through its own transaction processing capabilities. Since transaction completeness is not dependent on the main chain, the game service is not affected by transactions of other projects, so the user experience remains stable. Furthermore, access control and personal information protection functions can be set, ensuring high security and stability of user data. If you are concerned about introducing a subnet, but need to reduce resources and costs, you may start development on C-Chain, Avalanche's main network, and adopt a strategy to flexibly move assets to the subnet as needed in the future. Avalanche Subnet: Custom Chain Revolution for Games #Avalanche is pioneering the Web3 game market that has been developed beyond the limits of the existing game industry through subnet technology. Let's find out the strategy of utilizing the Avalanche subnet and the prospect of the Avalanche game ecosystem centered on the subnet. Submit Wallet Address for Migration 🔗 1. Submit the Wallet holding the $MOA 2. Submit the Wallet Address will receive $AIM Airdrop 3. Submission Deadline 31.DEC 2023 - 20.00 PM (JST ,KST) (+UTC9) Token Informations of $AIM $AIM - Artificial Intelligence Metaverse Contract : 0xCEeE63fF114F8e8deBF5E78a14e770E5B905eA91 Chain : Erc20 - Avalanche (AVAX) Decimals: 18 5,000,000,000 $AIM #Metaverse #Gamefi #Fun #Blockchain #P2E #PLAYFORFREE #ETH #polygon #chainlink #METAMASK #COINBASEWALLET #BITGETWALLET #BURRITOWALLET #AVALANCHE

MetaOasisVR l $AIM🔺

69,057 views • 2 years ago

Most $TAO holders are flying blind. They bought the token. They watched the price. They read the threads. But they have never opened the one tool that shows them everything happening inside the Bittensor network in real time. It is called Taostats. It is free. And after reading this, you will never look at $TAO the same way again. Here is exactly how to use it. Step 1: Start at the Subnets page. This is the heartbeat of the entire network. Every subnet running on Bittensor is listed here with: - its current emission rate - the number of active miners and validators - real-time performance data The emission rate is the most important number on this page. It tells you exactly how much TAO is flowing into each subnet every block. High emission means the network is directing significant resources toward that subnet's commodity. Low emission means the market has not yet recognised its value, or the subnet has not yet proven itself. Watch which subnets are gaining emission share over time. That movement tells you where the network believes the most valuable work is being done, before any headline announces it. Step 2: Use the Subnet pages to go deeper. Click any subnet, and you enter a complete dashboard for that individual market. - The TradingView chart shows you the alpha token price history for that subnet. Alpha tokens are the subnet-specific tokens that sit inside TAO's broader economy. Their price relative to TAO tells you how the market is valuing that subnet's specific commodity. - The Metagraph is the full list of every miner and validator currently active in the subnet: their UID, their stake, their trust score, their emission share. This is the raw intelligence layer. The miners consistently earning the most emissions are producing the work the validators collectively agree is the most valuable. - The Sentiment Index gives you a real-time community temperature reading on each subnet. Not price sentiment. Ecosystem sentiment. Whether the participants building inside the subnet believe it is healthy and improving. Step 3: Check Validators before you stake anything. This is the step most people skip and regret. The Validators page on Taostats shows you the performance history of every validator on the network: their VTrust score, their emission consistency, and their weight-setting behaviour across subnets. VTrust is the metric that matters most. It measures how closely a validator's judgments align with the honest stake-weighted majority across the network. High VTrust means the validator is doing genuine work and being rewarded for it. Low VTrust means the validator is either lazy, copying other validators' weights, or attempting to manipulate the system. When you delegate your TAO to a validator, you are trusting them with your emissions. Taostats shows you exactly which validators have earned that trust over time, and which ones have not. Never stake blind again. Step 4: Use the Blockchain explorer to track real movement. The Blockchain section of Taostats logs every transfer, every staking transaction, and every extrinsic called on the Bittensor chain in real time. This is where you track what wallets are actually doing: - Large staking transactions from unknown addresses - Subnet registration events that signal a new market is about to go live - Neuron registration burns that show demand for participation in a specific subnet is accelerating The people who read on-chain data before the narrative catches up to it are the ones who position correctly before the crowd notices the move. Step 5: Track your own portfolio inside the Dashboard. Connect your coldkey address, and Taostats builds you a complete portfolio view: - Your TAO balance - Your staking positions - Your delegation returns - Your yield over time The yield calculator is particularly useful. It shows you the actual return you are generating from your staking position in real TAO terms, not in percentage estimates that assume conditions that may not hold. If your yield is lower than the network average for your validator tier, Taostats shows you that too. Switching validators takes one transaction. The data to make that decision intelligently is right in front of you. The bigger picture. Most people holding $TAO are making decisions based on price charts and social media sentiment. Both of those inputs are downstream of what is actually happening inside the network. Subnet emission shifts. Validator VTrust changes. On-chain registration events. Neuron burn rates. Alpha token price movements relative to TAO. All of it is live on Taostats right now. All of it is free. All of it tells you something the price chart cannot. The investors who understand Bittensor at the data layer will always be positioned ahead of the investors who understand it at the narrative layer. Taostats is the data layer. Bookmark it. Open it daily. The network is telling you exactly what it is doing if you know where to look.
1:52

Most $TAO holders are flying blind. They bought the token. They watched the price. They read the threads. But they have never opened the one tool that shows them everything happening inside the Bittensor network in real time. It is called Taostats. It is free. And after reading this, you will never look at $TAO the same way again. Here is exactly how to use it. Step 1: Start at the Subnets page. This is the heartbeat of the entire network. Every subnet running on Bittensor is listed here with: - its current emission rate - the number of active miners and validators - real-time performance data The emission rate is the most important number on this page. It tells you exactly how much TAO is flowing into each subnet every block. High emission means the network is directing significant resources toward that subnet's commodity. Low emission means the market has not yet recognised its value, or the subnet has not yet proven itself. Watch which subnets are gaining emission share over time. That movement tells you where the network believes the most valuable work is being done, before any headline announces it. Step 2: Use the Subnet pages to go deeper. Click any subnet, and you enter a complete dashboard for that individual market. - The TradingView chart shows you the alpha token price history for that subnet. Alpha tokens are the subnet-specific tokens that sit inside TAO's broader economy. Their price relative to TAO tells you how the market is valuing that subnet's specific commodity. - The Metagraph is the full list of every miner and validator currently active in the subnet: their UID, their stake, their trust score, their emission share. This is the raw intelligence layer. The miners consistently earning the most emissions are producing the work the validators collectively agree is the most valuable. - The Sentiment Index gives you a real-time community temperature reading on each subnet. Not price sentiment. Ecosystem sentiment. Whether the participants building inside the subnet believe it is healthy and improving. Step 3: Check Validators before you stake anything. This is the step most people skip and regret. The Validators page on Taostats shows you the performance history of every validator on the network: their VTrust score, their emission consistency, and their weight-setting behaviour across subnets. VTrust is the metric that matters most. It measures how closely a validator's judgments align with the honest stake-weighted majority across the network. High VTrust means the validator is doing genuine work and being rewarded for it. Low VTrust means the validator is either lazy, copying other validators' weights, or attempting to manipulate the system. When you delegate your TAO to a validator, you are trusting them with your emissions. Taostats shows you exactly which validators have earned that trust over time, and which ones have not. Never stake blind again. Step 4: Use the Blockchain explorer to track real movement. The Blockchain section of Taostats logs every transfer, every staking transaction, and every extrinsic called on the Bittensor chain in real time. This is where you track what wallets are actually doing: - Large staking transactions from unknown addresses - Subnet registration events that signal a new market is about to go live - Neuron registration burns that show demand for participation in a specific subnet is accelerating The people who read on-chain data before the narrative catches up to it are the ones who position correctly before the crowd notices the move. Step 5: Track your own portfolio inside the Dashboard. Connect your coldkey address, and Taostats builds you a complete portfolio view: - Your TAO balance - Your staking positions - Your delegation returns - Your yield over time The yield calculator is particularly useful. It shows you the actual return you are generating from your staking position in real TAO terms, not in percentage estimates that assume conditions that may not hold. If your yield is lower than the network average for your validator tier, Taostats shows you that too. Switching validators takes one transaction. The data to make that decision intelligently is right in front of you. The bigger picture. Most people holding $TAO are making decisions based on price charts and social media sentiment. Both of those inputs are downstream of what is actually happening inside the network. Subnet emission shifts. Validator VTrust changes. On-chain registration events. Neuron burn rates. Alpha token price movements relative to TAO. All of it is live on Taostats right now. All of it is free. All of it tells you something the price chart cannot. The investors who understand Bittensor at the data layer will always be positioned ahead of the investors who understand it at the narrative layer. Taostats is the data layer. Bookmark it. Open it daily. The network is telling you exactly what it is doing if you know where to look.

2xnmore

154,024 views • 4 months ago

E157: Anthony Pompliano 🌪 – Why I Went All-In on Bitcoin and Never Sold Pomp and I discuss why asymmetry beats diversification, how to stay concentrated without becoming a degen, and why the best investment most people can make isn't in markets at all. This is a masterclass in long-term conviction, bifurcating risk, and knowing when cowboy time starts Timestamps: 0:00 Introduction 1:21 Please Subscribe 1:46 5 Podcasts In 1 Day, Yet Anthony’s “Ok” 2:36 Who Are You 2:50 Why Relentless Is Anthony’s Favorite Word 3:38 The Key To Keeping Conviction When Things Are Bad With Your Portfolio 4:30 How Does Someone Who Relies On Their Portfolio Build Conviction 6:17 Anthony Is A Risk Cowboy 7:06 The History Of Anthony’s Risk & Conviction 8:55 Partnerships: Jupiter KAST 9:31 The Fine Line Between Gambling Addicts & Having Concentrated Bets 12:20 Making Changes From 95% In Bitcoin To Other Assets 14:08 Anthony’s Evolution Towards Investing 18:01 Building A Business To Bring Value vs Scamming People 19:30 Partnerships: Paradex Zashi is now Zodl Mantle 20:39 Does Forcing Yourself Into A Corner Result In True Growth 24:39 3 Things Being Talked About Most In 2026 — Humanoid Robots, Prediction Markets, AI 26:17 Partnerships: Trezor Sui 27:10 How To Invest In Those 3 Big Topics Today 29:40 A Realistic Return On Bitcoin Over The Next 10 Years 32:18 A Single Bitcoin’s Worth In 30, 40, Or 50 Years 33:12 Closing Thoughts
33:45

E157: Anthony Pompliano 🌪 – Why I Went All-In on Bitcoin and Never Sold Pomp and I discuss why asymmetry beats diversification, how to stay concentrated without becoming a degen, and why the best investment most people can make isn't in markets at all. This is a masterclass in long-term conviction, bifurcating risk, and knowing when cowboy time starts Timestamps: 0:00 Introduction 1:21 Please Subscribe 1:46 5 Podcasts In 1 Day, Yet Anthony’s “Ok” 2:36 Who Are You 2:50 Why Relentless Is Anthony’s Favorite Word 3:38 The Key To Keeping Conviction When Things Are Bad With Your Portfolio 4:30 How Does Someone Who Relies On Their Portfolio Build Conviction 6:17 Anthony Is A Risk Cowboy 7:06 The History Of Anthony’s Risk & Conviction 8:55 Partnerships: Jupiter KAST 9:31 The Fine Line Between Gambling Addicts & Having Concentrated Bets 12:20 Making Changes From 95% In Bitcoin To Other Assets 14:08 Anthony’s Evolution Towards Investing 18:01 Building A Business To Bring Value vs Scamming People 19:30 Partnerships: Paradex Zashi is now Zodl Mantle 20:39 Does Forcing Yourself Into A Corner Result In True Growth 24:39 3 Things Being Talked About Most In 2026 — Humanoid Robots, Prediction Markets, AI 26:17 Partnerships: Trezor Sui 27:10 How To Invest In Those 3 Big Topics Today 29:40 A Realistic Return On Bitcoin Over The Next 10 Years 32:18 A Single Bitcoin’s Worth In 30, 40, Or 50 Years 33:12 Closing Thoughts

MR SHIFT 🦁

59,792 views • 7 months ago

SpaceX’s AI arm is partnering with coding startup Cursor in a deal worth no less than $10 billion and as much as $60 billion. Can the pair topple the rising Anthropic-OpenAI AI coding axis? A lot of money is being bet that the answer is yes. Next up, Lon Harris and alex 🏴‍☠️🇺🇸🇺🇦 invited the bitstarter team on the show to discuss their work to help kickstart new Bittensor subnets. The dynamic duo had a new program to announce, so make sure to tune into their pitch if you have dreams of launching your own subnet. Then we brought TrajectoryRL onto the pod, a Bittensor subnet that holds competitions to improve agent skills. Yes, the markdown files that everyone who uses OpenClaw swears by. Hit play, let’s have some fun! 2:27 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 4:07 SpaceX/ xAI "partners" with Cursor! 9:35 Will the Cursor deal help pump a future SpaceX IPO? 9:57 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 12:14 How AI coding models like Cursor help xAI grow recursively. 17:24 Chris Zacharia and Brian McRindle of Bitstarter join the show. 20:23 Grasshopper Bank: Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 29:59 Notion - Notion brings all your notes, docs, and projects into one connected space that just works with AI built right in. Try Notion, with Notion Agent, at 33:03 How Bittensor subnets monetize and how it compares to VC funds. 37:04 Is Bittensor hard-capped at 128 subnets? 42:37 Bittensor's biggest weakness. 46:10 Ning Ren of TrajectoryRL joins the show. 47:34 Skills now need entire agents just to write them! 48:26 Back up… What are skills? 1:07:38 Amazon and Anthropic's $5 BILLION deal 1:08:48 Google has 2 new chips! 1:09:50 Apple CEO, Tim is COOKED! John Ternus is in! 1:11:37 Alex is bullish on MacBook Neo! 🎥 Watch the full episode here 👇
1:13:29

SpaceX’s AI arm is partnering with coding startup Cursor in a deal worth no less than $10 billion and as much as $60 billion. Can the pair topple the rising Anthropic-OpenAI AI coding axis? A lot of money is being bet that the answer is yes. Next up, Lon Harris and alex 🏴‍☠️🇺🇸🇺🇦 invited the bitstarter team on the show to discuss their work to help kickstart new Bittensor subnets. The dynamic duo had a new program to announce, so make sure to tune into their pitch if you have dreams of launching your own subnet. Then we brought TrajectoryRL onto the pod, a Bittensor subnet that holds competitions to improve agent skills. Yes, the markdown files that everyone who uses OpenClaw swears by. Hit play, let’s have some fun! 2:27 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 4:07 SpaceX/ xAI "partners" with Cursor! 9:35 Will the Cursor deal help pump a future SpaceX IPO? 9:57 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 12:14 How AI coding models like Cursor help xAI grow recursively. 17:24 Chris Zacharia and Brian McRindle of Bitstarter join the show. 20:23 Grasshopper Bank: Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 29:59 Notion - Notion brings all your notes, docs, and projects into one connected space that just works with AI built right in. Try Notion, with Notion Agent, at 33:03 How Bittensor subnets monetize and how it compares to VC funds. 37:04 Is Bittensor hard-capped at 128 subnets? 42:37 Bittensor's biggest weakness. 46:10 Ning Ren of TrajectoryRL joins the show. 47:34 Skills now need entire agents just to write them! 48:26 Back up… What are skills? 1:07:38 Amazon and Anthropic's $5 BILLION deal 1:08:48 Google has 2 new chips! 1:09:50 Apple CEO, Tim is COOKED! John Ternus is in! 1:11:37 Alex is bullish on MacBook Neo! 🎥 Watch the full episode here 👇

This Week in Startups

19,991 views • 5 months ago

Covenant Labs just did a 90-minute AMA breaking down their 3 Bittensor subnets. templar. basilica. grail. Pre-training, compute, and post-training under one roof. Most people missed it. Here's everything they said. Covenant is building what they call the "end to end intelligence continuum." Three subnets. Three layers of the AI stack. All permissionless. Templar (SN3) handles decentralized pre-training. Basilica (SN39) handles compute. Grail (SN81) handles RL post-training. Sam Dare, the lead, put it bluntly. Decentralized training is "humanity's last dance." Not about beating OpenAI head to head. About creating optionality. About making it cheap enough for anyone to train models. The gap between academia and frontier labs is growing exponentially. Researchers can't afford to experiment. The actual training run costs 5% of the reported budget. The other 95% is experimentation. If Covenant cracks cheap training, that entire surface area opens up. On Templar specifically: • Hit 39% emission on Bittensor. Highest since Apex was the only subnet on the network • Covenant-72B trained permissionlessly with 70+ contributors on commodity internet • 1.1 trillion tokens processed. No centralized data center • Performance competitive with LLaMA-2-70B On Grail, something flew under the radar. They built Pulse. A weight synchronization method that compresses model updates by 100x. • In RL post-training, only ~1% of weights update per step • Pulse exploits that sparsity. Lossless compression • Prime Intellect's comparable system took 14 minutes to sync a 30B model • Pulse makes decentralized RL training actually feasible at scale • Already used by Cursor The lead researcher on Grail said they've trained on math, code, and GPU kernels. Got 40-60% improvement on benchmarks. Working toward agentic training with 100K+ token context and 30B+ parameter models. On Basilica, the compute subnet: The team was blunt. Just reselling GPU hours is a 5-10% margin game. Traditional compute providers already do that. Their play is value-added services. • "GPU as code." No dashboard. No UI. Agents interact via SDK • Custom scheduler that places workloads across heterogeneous hardware • Verification checks for GPU, CPU, bandwidth, memory, storage, and OS security • Partnerships with providers like Mass Compute for 10-20% below market pricing • Miners compete on useful infrastructure, not just GPU hours Sam then went on a rant about the miner burn debate. His take: Bittensor had to grow up. dTAO introduced investors. The old "miners are God" philosophy doesn't hold. • Subnet owners have a duty to protect token value • Miners are a resource optimization exercise, not a cost reduction exercise • 100% miner emissions on compute subnets = immediate sell pressure • The 41% miner allocation is arbitrary. Different business models need different splits • Fish (who started burns) agreed. Burns usually mean the validation isn't mature enough The bigger point. You can't police burns. Subnets just send to their own keys instead of the burn address. Subnet 28 does exactly that. Sam's position: judge subnets on outcomes, not process. Const has changed the protocol 9-10 times in 2 years. That iteration speed is Bittensor's actual moat. The whole Covenant thesis is playing out in real time. TAO is up 100%+ in a month. Jensen Huang name-dropped the network. Grayscale has an ETF filing. But the real story is three subnets quietly building every layer of decentralized AI.
1:39:04

Covenant Labs just did a 90-minute AMA breaking down their 3 Bittensor subnets. templar. basilica. grail. Pre-training, compute, and post-training under one roof. Most people missed it. Here's everything they said. Covenant is building what they call the "end to end intelligence continuum." Three subnets. Three layers of the AI stack. All permissionless. Templar (SN3) handles decentralized pre-training. Basilica (SN39) handles compute. Grail (SN81) handles RL post-training. Sam Dare, the lead, put it bluntly. Decentralized training is "humanity's last dance." Not about beating OpenAI head to head. About creating optionality. About making it cheap enough for anyone to train models. The gap between academia and frontier labs is growing exponentially. Researchers can't afford to experiment. The actual training run costs 5% of the reported budget. The other 95% is experimentation. If Covenant cracks cheap training, that entire surface area opens up. On Templar specifically: • Hit 39% emission on Bittensor. Highest since Apex was the only subnet on the network • Covenant-72B trained permissionlessly with 70+ contributors on commodity internet • 1.1 trillion tokens processed. No centralized data center • Performance competitive with LLaMA-2-70B On Grail, something flew under the radar. They built Pulse. A weight synchronization method that compresses model updates by 100x. • In RL post-training, only ~1% of weights update per step • Pulse exploits that sparsity. Lossless compression • Prime Intellect's comparable system took 14 minutes to sync a 30B model • Pulse makes decentralized RL training actually feasible at scale • Already used by Cursor The lead researcher on Grail said they've trained on math, code, and GPU kernels. Got 40-60% improvement on benchmarks. Working toward agentic training with 100K+ token context and 30B+ parameter models. On Basilica, the compute subnet: The team was blunt. Just reselling GPU hours is a 5-10% margin game. Traditional compute providers already do that. Their play is value-added services. • "GPU as code." No dashboard. No UI. Agents interact via SDK • Custom scheduler that places workloads across heterogeneous hardware • Verification checks for GPU, CPU, bandwidth, memory, storage, and OS security • Partnerships with providers like Mass Compute for 10-20% below market pricing • Miners compete on useful infrastructure, not just GPU hours Sam then went on a rant about the miner burn debate. His take: Bittensor had to grow up. dTAO introduced investors. The old "miners are God" philosophy doesn't hold. • Subnet owners have a duty to protect token value • Miners are a resource optimization exercise, not a cost reduction exercise • 100% miner emissions on compute subnets = immediate sell pressure • The 41% miner allocation is arbitrary. Different business models need different splits • Fish (who started burns) agreed. Burns usually mean the validation isn't mature enough The bigger point. You can't police burns. Subnets just send to their own keys instead of the burn address. Subnet 28 does exactly that. Sam's position: judge subnets on outcomes, not process. Const has changed the protocol 9-10 times in 2 years. That iteration speed is Bittensor's actual moat. The whole Covenant thesis is playing out in real time. TAO is up 100%+ in a month. Jensen Huang name-dropped the network. Grayscale has an ETF filing. But the real story is three subnets quietly building every layer of decentralized AI.

Jesus Martinez

26,763 views • 5 months ago

Introducing $Harvest, a token on Robinhood Chain. Most tokens reward whoever sells first, we built the opposite. Here's how it all works. The loop: trade → creator fees → buyback → airdrop to harvesters Every trade of $Harvest generates creator fees. Those fees are used to buy $Harvest back on the open market, and every token bought back is airdropped to harvesters, meaning anyone who harvests their tokens via our website, more info can be found on our website. Airdrops land straight in your wallet. Nothing to claim, nothing to remember. Your share: amount locked × hours locked = your weight Lock for any term you like, from 1 hour to 1 year. 1,000 tokens for 30 days carries the same weight as 10,000 tokens for 3 days. Lock more, or lock longer, and your slice of every buyback grows. You won't find an APR number here because we're not going to invent one. What you receive is $Harvest bought with real fees, in proportion to what you committed. Your lock: lock → term runs out → withdraw lock → leave early → penalty to the treasury The contract holds your tokens, not us. When your term ends you take them back. Leave early and you pay a penalty, which goes to the treasury. Patience is the whole point. Check it yourself: Every contract address, with a link to its verified source on the explorer, is listed at Every buyback and every airdrop is a transaction you can open. The board at only shows records it has confirmed on-chain, so if it's on the board, it happened. How the trust model works, and where its limits are: The launchpad: launch → bonding curve → own vault → harvest every 30 min → lockers claim ETH None of this is reserved for $Harvest. The same machinery is open to anyone who wants to launch a token on Robinhood Chain. Launch from and your token goes live on Pons v2's bonding curve with its own HarvestVault deployed alongside it, automatically. No contracts to write, no team to hire. Every creator fee your token earns, in ETH, lands in that vault instead of a wallet. Your holders lock for a term, weighted by amount × hours, exactly like $Harvest. Every 30 minutes anyone can trigger a harvest: the vault takes your share as creator, which you set at launch and can never raise above 50%, and credits the rest to your lockers by weight. They claim their ETH straight from the contract. Nobody, including you and including us, can touch locked tokens or unclaimed ETH. There is no owner, no pause button and no upgrade path. Leave a lock early and 10% of it is burned. Fill the curve and the token graduates to a live pool. Your holders get a reason to stay, and you get a token where nobody has to trust you. How to launch: How vaults work: $Harvest is live on Robinhood Chain. The only official $Harvest contract: 0x22d141f768b4dc6108c1e8712b10aca9a5c603dc
0:28

Introducing $Harvest, a token on Robinhood Chain. Most tokens reward whoever sells first, we built the opposite. Here's how it all works. The loop: trade → creator fees → buyback → airdrop to harvesters Every trade of $Harvest generates creator fees. Those fees are used to buy $Harvest back on the open market, and every token bought back is airdropped to harvesters, meaning anyone who harvests their tokens via our website, more info can be found on our website. Airdrops land straight in your wallet. Nothing to claim, nothing to remember. Your share: amount locked × hours locked = your weight Lock for any term you like, from 1 hour to 1 year. 1,000 tokens for 30 days carries the same weight as 10,000 tokens for 3 days. Lock more, or lock longer, and your slice of every buyback grows. You won't find an APR number here because we're not going to invent one. What you receive is $Harvest bought with real fees, in proportion to what you committed. Your lock: lock → term runs out → withdraw lock → leave early → penalty to the treasury The contract holds your tokens, not us. When your term ends you take them back. Leave early and you pay a penalty, which goes to the treasury. Patience is the whole point. Check it yourself: Every contract address, with a link to its verified source on the explorer, is listed at Every buyback and every airdrop is a transaction you can open. The board at only shows records it has confirmed on-chain, so if it's on the board, it happened. How the trust model works, and where its limits are: The launchpad: launch → bonding curve → own vault → harvest every 30 min → lockers claim ETH None of this is reserved for $Harvest. The same machinery is open to anyone who wants to launch a token on Robinhood Chain. Launch from and your token goes live on Pons v2's bonding curve with its own HarvestVault deployed alongside it, automatically. No contracts to write, no team to hire. Every creator fee your token earns, in ETH, lands in that vault instead of a wallet. Your holders lock for a term, weighted by amount × hours, exactly like $Harvest. Every 30 minutes anyone can trigger a harvest: the vault takes your share as creator, which you set at launch and can never raise above 50%, and credits the rest to your lockers by weight. They claim their ETH straight from the contract. Nobody, including you and including us, can touch locked tokens or unclaimed ETH. There is no owner, no pause button and no upgrade path. Leave a lock early and 10% of it is burned. Fill the curve and the token graduates to a live pool. Your holders get a reason to stay, and you get a token where nobody has to trust you. How to launch: How vaults work: $Harvest is live on Robinhood Chain. The only official $Harvest contract: 0x22d141f768b4dc6108c1e8712b10aca9a5c603dc

Harvest

23,430 views • 10 days ago

In a brand new episode of TWiST, @jason sits down with Brynn Putnam to discuss her startup, Board, her learnings from building Mirror to a $500M exit, and how her new family gaming startup is taking on the screen time epidemic. Then, alex 🏴‍☠️🇺🇸🇺🇦 interviews AJ Piplica of Hermeus to discuss hypersonic, autonomous jet aircraft, what they bring to military and civilian contexts, and what’s next on the startup’s incredibly rapid testing schedule! 0:00 Board's Brynn Putnam joins the show 2:54 Board's proprietary AI software stack 6:43 Why Board manufactures in Mexico (not China) 9:21 LinkedIn: Thanks to our partners at LinkedIn! Post your job for free at then promote it to get access to LinkedIn Jobs' new AI assistant. 9:42 How to raise a Seed round for hardware without a finished product 15:26 Brynn's daughter and the mermaid example 17:09 Can Board limit screen time fears? 18:47 Northwest Registered Agent: Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 22:54 Selling the first 10,000 units 28:38 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit to learn more. 29:42 Why Board is steering away from simple ports toward native IP experiences 39:59 Hermeus's AJ Piplica joins the show 41:15 What is Dark Horse? 47:47 Commercial applications: Cargo, organs, flowers, and trans-Atlantic in 90 minutes 58:42 Dark Horse range and the "reusable first stage" analogy 1:02:42 $350M Series C led by Khosla; total funding now exceeds $500M 1:03:39 The SpaceX model: get customers to fund your R&D 1:07:47 Closing: the American Dynamism pitch 🎥 Watch the full episode here 👇
1:08:51

In a brand new episode of TWiST, @jason sits down with Brynn Putnam to discuss her startup, Board, her learnings from building Mirror to a $500M exit, and how her new family gaming startup is taking on the screen time epidemic. Then, alex 🏴‍☠️🇺🇸🇺🇦 interviews AJ Piplica of Hermeus to discuss hypersonic, autonomous jet aircraft, what they bring to military and civilian contexts, and what’s next on the startup’s incredibly rapid testing schedule! 0:00 Board's Brynn Putnam joins the show 2:54 Board's proprietary AI software stack 6:43 Why Board manufactures in Mexico (not China) 9:21 LinkedIn: Thanks to our partners at LinkedIn! Post your job for free at then promote it to get access to LinkedIn Jobs' new AI assistant. 9:42 How to raise a Seed round for hardware without a finished product 15:26 Brynn's daughter and the mermaid example 17:09 Can Board limit screen time fears? 18:47 Northwest Registered Agent: Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 22:54 Selling the first 10,000 units 28:38 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit to learn more. 29:42 Why Board is steering away from simple ports toward native IP experiences 39:59 Hermeus's AJ Piplica joins the show 41:15 What is Dark Horse? 47:47 Commercial applications: Cargo, organs, flowers, and trans-Atlantic in 90 minutes 58:42 Dark Horse range and the "reusable first stage" analogy 1:02:42 $350M Series C led by Khosla; total funding now exceeds $500M 1:03:39 The SpaceX model: get customers to fund your R&D 1:07:47 Closing: the American Dynamism pitch 🎥 Watch the full episode here 👇

This Week in Startups

15,506 views • 2 months ago

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead
1:09:53

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead

Raoul Pal

172,640 views • 1 year ago

Most $TAO holders staking right now are trusting the wrong validators. Not because they are careless. Because nobody explained what the numbers on the Validators page actually mean. There is a tool inside Taostats that shows you exactly which validators are genuinely working and which ones are collecting your emissions without contributing anything to the network. It is free. It is live. And almost nobody is using it correctly. Here is exactly how to read it. Step 1: Understand what Dominance actually measures. Dominance is not popularity. It is not a ranking of which validator is best. It describes a validator's Stake Weight as a percentage of all validator stake weights combined across the network. Stake Weight is calculated as: root stake multiplied by 0.18, plus all alpha staked across subnets converted into TAO. Root stake is deliberately discounted at 18 percent of its face value. Alpha stake carries the full weight. This means a validator with deep subnet-level staking is structurally more powerful than one sitting purely on root, even if their raw TAO numbers look similar on the surface. When you see a validator with rising Dominance over time, it is not just getting more popular. It is getting more alpha stake directed toward it across active subnets. That is a meaningful signal about where serious capital is moving inside the network. Step 2: Check the Take percentage before you delegate anything. Take is the percentage of emissions the validator keeps for itself. Everything above that number flows to you as a nominator. A validator with a 18 percent Take keeps 18 percent of the emissions their position generates and distributes the remainder to stakeholders. A validator with a 50 percent Take is keeping half of what your stake earns. Most people never look at this number before delegating. It is the first number you should check. A high Take is not automatically a red flag if the validator is genuinely performing well and contributing to the network. But a high Take combined with low VTrust in their subnet performance page is the exact combination that should make you move your stake immediately. Step 3: Open the Validator Performance page and find the VTrust score. This is the number most holders never see. VTrust measures how closely a validator's weight assignments align with the honest stake-weighted majority across the network inside each subnet they operate in. Validators are responsible for evaluating miner output and assigning scores. Those scores go into Yuma Consensus and determine which miners earn emissions. A validator doing genuine evaluation work will have weights that align closely with the honest consensus. High VTrust. Consistent emissions. Reliable nominator returns. A validator that is weight copying, meaning they are simply copying the Yuma consensus scores back onto themselves rather than doing real evaluation, will show a flagged return on Taostats. Their nom/24hr/1k TAO score appears in red. This is Taostats telling you directly: this validator is extracting value from the network without contributing to it. When you stake to a weight copying validator, you are funding a free rider. Step 4: Watch the 24hr Nominator Change column. This number moves fast and it tells you something before any other signal does. A validator losing nominators over consecutive days is a validator that informed stakers are quietly leaving. A validator gaining nominators rapidly while their VTrust is healthy is a validator attracting attention for the right reasons. The 24hr column is the on-chain version of sentiment before sentiment becomes a narrative on social media. Step 5: Check Active subnets alongside Total Weight. Active tells you the number of subnets where the validator has a parent or child hotkey running. A validator with high Total Weight but low Active subnets is concentrated. They are running a specific strategy in specific markets. A validator with broad Active coverage across many subnets is building a wider surface area for emissions and is more exposed to the overall network performance rather than any single subnet cycle. Neither is inherently better. But knowing which type of validator you are delegating to tells you what you are actually betting on when you stake. Step 6: Check the Weight Change column over time. Total Weight is a snapshot. Weight Change is momentum. A validator with stable or growing Total Weight over consecutive days is attracting net new stake consistently. A validator with declining Weight Change is losing stake faster than it is gaining it. Most people look at the current number. The people positioning correctly are watching which direction the number is moving and how fast. The difference between a good validator and a dangerous one is not obvious from the outside. It is not the name. It is not the size. It is the VTrust score, the Take percentage, the nominator trend, and whether Taostats is showing their return in red or not. Every one of those signals is sitting on the Validators page right now. Free. Live. Updated every block. The investors who read the data layer before the narrative layer will not need to explain their staking decisions later. Open Taostats tonight. You will want to find this post when you do.
3:44

Most $TAO holders staking right now are trusting the wrong validators. Not because they are careless. Because nobody explained what the numbers on the Validators page actually mean. There is a tool inside Taostats that shows you exactly which validators are genuinely working and which ones are collecting your emissions without contributing anything to the network. It is free. It is live. And almost nobody is using it correctly. Here is exactly how to read it. Step 1: Understand what Dominance actually measures. Dominance is not popularity. It is not a ranking of which validator is best. It describes a validator's Stake Weight as a percentage of all validator stake weights combined across the network. Stake Weight is calculated as: root stake multiplied by 0.18, plus all alpha staked across subnets converted into TAO. Root stake is deliberately discounted at 18 percent of its face value. Alpha stake carries the full weight. This means a validator with deep subnet-level staking is structurally more powerful than one sitting purely on root, even if their raw TAO numbers look similar on the surface. When you see a validator with rising Dominance over time, it is not just getting more popular. It is getting more alpha stake directed toward it across active subnets. That is a meaningful signal about where serious capital is moving inside the network. Step 2: Check the Take percentage before you delegate anything. Take is the percentage of emissions the validator keeps for itself. Everything above that number flows to you as a nominator. A validator with a 18 percent Take keeps 18 percent of the emissions their position generates and distributes the remainder to stakeholders. A validator with a 50 percent Take is keeping half of what your stake earns. Most people never look at this number before delegating. It is the first number you should check. A high Take is not automatically a red flag if the validator is genuinely performing well and contributing to the network. But a high Take combined with low VTrust in their subnet performance page is the exact combination that should make you move your stake immediately. Step 3: Open the Validator Performance page and find the VTrust score. This is the number most holders never see. VTrust measures how closely a validator's weight assignments align with the honest stake-weighted majority across the network inside each subnet they operate in. Validators are responsible for evaluating miner output and assigning scores. Those scores go into Yuma Consensus and determine which miners earn emissions. A validator doing genuine evaluation work will have weights that align closely with the honest consensus. High VTrust. Consistent emissions. Reliable nominator returns. A validator that is weight copying, meaning they are simply copying the Yuma consensus scores back onto themselves rather than doing real evaluation, will show a flagged return on Taostats. Their nom/24hr/1k TAO score appears in red. This is Taostats telling you directly: this validator is extracting value from the network without contributing to it. When you stake to a weight copying validator, you are funding a free rider. Step 4: Watch the 24hr Nominator Change column. This number moves fast and it tells you something before any other signal does. A validator losing nominators over consecutive days is a validator that informed stakers are quietly leaving. A validator gaining nominators rapidly while their VTrust is healthy is a validator attracting attention for the right reasons. The 24hr column is the on-chain version of sentiment before sentiment becomes a narrative on social media. Step 5: Check Active subnets alongside Total Weight. Active tells you the number of subnets where the validator has a parent or child hotkey running. A validator with high Total Weight but low Active subnets is concentrated. They are running a specific strategy in specific markets. A validator with broad Active coverage across many subnets is building a wider surface area for emissions and is more exposed to the overall network performance rather than any single subnet cycle. Neither is inherently better. But knowing which type of validator you are delegating to tells you what you are actually betting on when you stake. Step 6: Check the Weight Change column over time. Total Weight is a snapshot. Weight Change is momentum. A validator with stable or growing Total Weight over consecutive days is attracting net new stake consistently. A validator with declining Weight Change is losing stake faster than it is gaining it. Most people look at the current number. The people positioning correctly are watching which direction the number is moving and how fast. The difference between a good validator and a dangerous one is not obvious from the outside. It is not the name. It is not the size. It is the VTrust score, the Take percentage, the nominator trend, and whether Taostats is showing their return in red or not. Every one of those signals is sitting on the Validators page right now. Free. Live. Updated every block. The investors who read the data layer before the narrative layer will not need to explain their staking decisions later. Open Taostats tonight. You will want to find this post when you do.

2xnmore

11,771 views • 3 months ago

tylercowen is bullish on AI education — here's why. 00:00 -- Preview 00:24 -- President Carlos Carvalho's AI-generated intro 03:21 -- Cowen reacts to UATX's campus 04:38 -- The AI revolution is here. Who will lose the most? 06:05 -- AI lawyers 07:17 -- Don't underestimate this 10:41 -- Changes to the "upper upper middle class" 12:38 -- How to be successful 13:43 -- The rise of managerial empires 14:02 -- When will we have the first billion dollar company with one employee? 16:05 -- 10-20 year forecast 16:19 -- Why education is so behind 17:01 -- Should you be bullish on UATX? 18:36 -- Should you still read Homer? 21:50 -- Write to think 25:01 -- Meet more people 25:42 -- How to get hired 26:54 -- Is AI your best mentor? 38:17 -- How to curb cheating 39:02 -- The new life of the mind 42:34 -- Q&A: Will there be more status associated with real education or AI education? 45:50 -- Q&A: Why do tech-savvy students need to practice using AI? 47:56 -- Q&A: Do LLMs atrophy your mind? 49:29 -- Q&A: How do you avoid AI-dependency? 51:05 -- Q&A: Isn't this vision lonely and isolating? 53:06 -- Q&A: Do students need teachers? 55:36 -- Q&A: What are the four most important courses for undergrads? 57:49 -- Q&A: Which AI company will win the AI race in the next five years and why? 59:22 -- Q&A: Can AI teach religion? 01:01:32 -- Q&A: Will AI narrow or widen our world? 01:04:37 -- Q&A: What makes us human? 01:05:42 -- Q&A: What is art? 01:08:33 -- Q&A: It's easy to catch cheaters
1:10:31

tylercowen is bullish on AI education — here's why. 00:00 -- Preview 00:24 -- President Carlos Carvalho's AI-generated intro 03:21 -- Cowen reacts to UATX's campus 04:38 -- The AI revolution is here. Who will lose the most? 06:05 -- AI lawyers 07:17 -- Don't underestimate this 10:41 -- Changes to the "upper upper middle class" 12:38 -- How to be successful 13:43 -- The rise of managerial empires 14:02 -- When will we have the first billion dollar company with one employee? 16:05 -- 10-20 year forecast 16:19 -- Why education is so behind 17:01 -- Should you be bullish on UATX? 18:36 -- Should you still read Homer? 21:50 -- Write to think 25:01 -- Meet more people 25:42 -- How to get hired 26:54 -- Is AI your best mentor? 38:17 -- How to curb cheating 39:02 -- The new life of the mind 42:34 -- Q&A: Will there be more status associated with real education or AI education? 45:50 -- Q&A: Why do tech-savvy students need to practice using AI? 47:56 -- Q&A: Do LLMs atrophy your mind? 49:29 -- Q&A: How do you avoid AI-dependency? 51:05 -- Q&A: Isn't this vision lonely and isolating? 53:06 -- Q&A: Do students need teachers? 55:36 -- Q&A: What are the four most important courses for undergrads? 57:49 -- Q&A: Which AI company will win the AI race in the next five years and why? 59:22 -- Q&A: Can AI teach religion? 01:01:32 -- Q&A: Will AI narrow or widen our world? 01:04:37 -- Q&A: What makes us human? 01:05:42 -- Q&A: What is art? 01:08:33 -- Q&A: It's easy to catch cheaters

University of Austin (UATX)

27,770 views • 8 months ago

this is a lecture on how to hunt for investors, cofounders & new hires complete breakdown: 00:00 8 billion people don't know you exist 00:24 No one knows you. No one cares. 01:09 Stop being a farmer 01:51 The one thing all great hunters share 02:10 How I got my co-founder in 30 seconds 03:30 You + them = 3 people 05:36 Missionaries vs mercenaries 10:31 Why you have to be generous with equity 12:35 The right vesting schedule 13:17 Always trial before you commit 14:19 The 9-to-5 specialist red flag 15:05 Why logos mean nothing 17:46 Hunt them on GitHub 19:37 Niche Discords and subreddits 20:58 Why paid referrals work 22:10 Hiring friends: the trap 24:39 Why advisors are bullshit 31:29 Should you raise at all? 35:06 Investors only buy growth stories 35:58 Fundraising is running an auction 37:36 The luck factor (and Twitter lies) 39:33 Angels vs VCs 47:21 The hierarchy: inbound > warm > cold 48:00 Never ask a VC for intros if they pass 48:59 The double opt-in rule 52:32 Fundraising is a full-time job 53:33 Why a 4-week VC chat is a "no" 56:22 The leverage trick 01:00:24 Fundraising advisors = scam 01:02:21 The one trait of every great founder 01:03:18 Your homework: a list of 100
1:04:08

this is a lecture on how to hunt for investors, cofounders & new hires complete breakdown: 00:00 8 billion people don't know you exist 00:24 No one knows you. No one cares. 01:09 Stop being a farmer 01:51 The one thing all great hunters share 02:10 How I got my co-founder in 30 seconds 03:30 You + them = 3 people 05:36 Missionaries vs mercenaries 10:31 Why you have to be generous with equity 12:35 The right vesting schedule 13:17 Always trial before you commit 14:19 The 9-to-5 specialist red flag 15:05 Why logos mean nothing 17:46 Hunt them on GitHub 19:37 Niche Discords and subreddits 20:58 Why paid referrals work 22:10 Hiring friends: the trap 24:39 Why advisors are bullshit 31:29 Should you raise at all? 35:06 Investors only buy growth stories 35:58 Fundraising is running an auction 37:36 The luck factor (and Twitter lies) 39:33 Angels vs VCs 47:21 The hierarchy: inbound > warm > cold 48:00 Never ask a VC for intros if they pass 48:59 The double opt-in rule 52:32 Fundraising is a full-time job 53:33 Why a 4-week VC chat is a "no" 56:22 The leverage trick 01:00:24 Fundraising advisors = scam 01:02:21 The one trait of every great founder 01:03:18 Your homework: a list of 100

Founders Inc

19,968 views • 4 months ago

Inside the $6B quant fund that turned down a shot at $20B to keep control — early investors who stayed in day one are up almost 40x. Suhaimi Zainul-Abidin — CEO @ Quantedge, Asia's top quant hedge fund, CEO since 2018 "We're trying to beat the markets. 20% annualized returns — if you can do it for 10 years, well done. If you can do it for 20, that's what we've done. But we're going to do it for 50." We cover: - Why Quantedge turned down a straight shot at $20B AUM — and the redemption structure they built instead - The real edge left in investing isn't information, it's running 300+ markets to drive idiosyncratic risk near zero - Their hard rule: if you can't explain a strategy in plain English, it doesn't belong in the model - Why they refuse to launch a "lower-vol" product for allocators, even though it's the easiest AUM they'd ever raise - The behavioral-bias thesis behind two decades of 20% annualized returns - "Class Q" — the internal share class that's turned early investors' money into almost 40x, with one brutal catch: it's permanent capital - Why Quantedge hires almost exclusively straight out of school and turns away experienced PMs - His path from law partner to hedge fund CEO — and the one skill that made the jump possible - The real reason funds die (hint: it's rarely the returns) Thanks to Suhaimi Zainul-Abidin for coming on Odds on Open! Highlights: 00:00 Intro 01:08 Founding Quantedge: two guys, $3M, and a Bloomberg machine 03:07 What makes an investment strategy robust across regimes 06:31 The real edge: it's not information, it's diversification across 300 markets 10:59 Scaling from $3M to $6B without chasing allocator money 15:00 Why they turned down the "dial down the risk" pitch from allocators 18:00 Running 25% vol with conviction — and why it's not a black box 20:33 How the research process evolved over 20 years 24:00 Trading on narratives vs. noise — why they stay distanced from the news 27:47 Is generative AI signal or noise for a quant shop? 31:09 Why Quantedge hires only fresh grads — never mid-career PMs 35:47 The two-pronged mission: compound for 50 years, then do good 38:28 From law partner to hedge fund CEO 49:32 Capital consolidation — why the big funds keep winning 55:04 The #1 mistake that kills emerging managers 59:03 Why fixed-term lockups saved the fund — even though it cost them a shot at $20B AUM 1:05:00 Class Q: the almost-40x share class only insiders get 1:07:26 Why 200 CVs come in for every open seat 1:14:44 Balancing meritocracy with actually caring about people 1:19:17 Final advice: patience, conviction, and playing the long game
1:22:38

Inside the $6B quant fund that turned down a shot at $20B to keep control — early investors who stayed in day one are up almost 40x. Suhaimi Zainul-Abidin — CEO @ Quantedge, Asia's top quant hedge fund, CEO since 2018 "We're trying to beat the markets. 20% annualized returns — if you can do it for 10 years, well done. If you can do it for 20, that's what we've done. But we're going to do it for 50." We cover: - Why Quantedge turned down a straight shot at $20B AUM — and the redemption structure they built instead - The real edge left in investing isn't information, it's running 300+ markets to drive idiosyncratic risk near zero - Their hard rule: if you can't explain a strategy in plain English, it doesn't belong in the model - Why they refuse to launch a "lower-vol" product for allocators, even though it's the easiest AUM they'd ever raise - The behavioral-bias thesis behind two decades of 20% annualized returns - "Class Q" — the internal share class that's turned early investors' money into almost 40x, with one brutal catch: it's permanent capital - Why Quantedge hires almost exclusively straight out of school and turns away experienced PMs - His path from law partner to hedge fund CEO — and the one skill that made the jump possible - The real reason funds die (hint: it's rarely the returns) Thanks to Suhaimi Zainul-Abidin for coming on Odds on Open! Highlights: 00:00 Intro 01:08 Founding Quantedge: two guys, $3M, and a Bloomberg machine 03:07 What makes an investment strategy robust across regimes 06:31 The real edge: it's not information, it's diversification across 300 markets 10:59 Scaling from $3M to $6B without chasing allocator money 15:00 Why they turned down the "dial down the risk" pitch from allocators 18:00 Running 25% vol with conviction — and why it's not a black box 20:33 How the research process evolved over 20 years 24:00 Trading on narratives vs. noise — why they stay distanced from the news 27:47 Is generative AI signal or noise for a quant shop? 31:09 Why Quantedge hires only fresh grads — never mid-career PMs 35:47 The two-pronged mission: compound for 50 years, then do good 38:28 From law partner to hedge fund CEO 49:32 Capital consolidation — why the big funds keep winning 55:04 The #1 mistake that kills emerging managers 59:03 Why fixed-term lockups saved the fund — even though it cost them a shot at $20B AUM 1:05:00 Class Q: the almost-40x share class only insiders get 1:07:26 Why 200 CVs come in for every open seat 1:14:44 Balancing meritocracy with actually caring about people 1:19:17 Final advice: patience, conviction, and playing the long game

Ethan Kho

151,472 views • 1 month ago

EP.47: Activist Investor Pushing for an Epic Turnaround at Eagle Bancorp ($EGBN) My former colleague and banking guru, James Abbott, is living his passion with the launch of Diligence Capital Management (DCM). DCM runs a concentrated, net-long financials strategy alongside a tighter-net long/short financials portfolio. James and his team bring more than 50 years of combined experience in financial services—and a deep understanding of how banks operate, where they underperform, and what it takes to improve them. In this episode, James explains why DCM became actively involved with Eagle Bancorp ($EGBN), how he identified an underperforming bank in need of change, and why he believes the market is still underestimating its earnings power. We also discuss lessons from the 2008 financial crisis and the collapse of Silicon Valley Bank, as well as why spending time inside a business can create an investing edge that is difficult to replicate from the outside. "My goal was to be a portfolio manager just like Peter Lynch." "The market just doesn't really appreciate what's going on here." Stocks: $EGBN, $ZION Not Investment Advice. (00:00) Introduction to James Abbott and the Eagle Bancorp investment thesis (02:14) How a Peter Lynch article inspired James Abbott's investing career (05:44) Reflections on FBR's research culture and working alongside Dan Ives (10:28) Founding Diligence Capital Management and launching the firm (11:46) The impact of Silicon Valley Bank's collapse and banking sector contagion (16:37) Why Eagle Bancorp became a high-conviction investment (17:48) Assessing Eagle Bancorp's earnings power and excess capital (19:09) Concentration risk and the challenges facing Eagle Bancorp (31:51) Corporate governance reforms and separating the chairman and CEO roles (41:14) The path to achieving $6 per share in earnings power This episode is powered by: 💡Oxford Data Plan 💡AlphaSense
43:36

EP.47: Activist Investor Pushing for an Epic Turnaround at Eagle Bancorp ($EGBN) My former colleague and banking guru, James Abbott, is living his passion with the launch of Diligence Capital Management (DCM). DCM runs a concentrated, net-long financials strategy alongside a tighter-net long/short financials portfolio. James and his team bring more than 50 years of combined experience in financial services—and a deep understanding of how banks operate, where they underperform, and what it takes to improve them. In this episode, James explains why DCM became actively involved with Eagle Bancorp ($EGBN), how he identified an underperforming bank in need of change, and why he believes the market is still underestimating its earnings power. We also discuss lessons from the 2008 financial crisis and the collapse of Silicon Valley Bank, as well as why spending time inside a business can create an investing edge that is difficult to replicate from the outside. "My goal was to be a portfolio manager just like Peter Lynch." "The market just doesn't really appreciate what's going on here." Stocks: $EGBN, $ZION Not Investment Advice. (00:00) Introduction to James Abbott and the Eagle Bancorp investment thesis (02:14) How a Peter Lynch article inspired James Abbott's investing career (05:44) Reflections on FBR's research culture and working alongside Dan Ives (10:28) Founding Diligence Capital Management and launching the firm (11:46) The impact of Silicon Valley Bank's collapse and banking sector contagion (16:37) Why Eagle Bancorp became a high-conviction investment (17:48) Assessing Eagle Bancorp's earnings power and excess capital (19:09) Concentration risk and the challenges facing Eagle Bancorp (31:51) Corporate governance reforms and separating the chairman and CEO roles (41:14) The path to achieving $6 per share in earnings power This episode is powered by: 💡Oxford Data Plan 💡AlphaSense

Doug Garber

18,151 views • 1 month ago

FROM A $50 SALARY IN SYRIA TO A $6M ROUND Episode 5 of PredictTime is live, and you'll hear it from a founder who restarted from zero three times and never sent a single cold email to close his round Ali, founder and CEO of XO Market. We go deep into why 400+ prediction markets are just copies of the same model, why a whale unfairly resolving his Polymarket bet became the tipping point, and how AI agents now decide market outcomes instead of humans Now he's building XO Market, where anyone can turn any idea into a conviction market. Everything you need to know about user-generated markets, XO Vaults and the future of prediction markets is in this episode --- Win 1,000 Conviction Points and get access to XO's weekly parlays with prizes up to $50,000 (we'll pick the winner on July 13): - sign up via the link: -drop your username with your most creative comment or question about the episode and follow Predict Time and XO Market --- Timecodes: 00:00 Intro 00:38 Raising $6M without pitching a single VC 04:29 Why not just copy Polymarket 07:05 Advice for builders: grants over VC money 12:15 Building a team across every continent 15:52 Ali's story: from Syria to Switzerland 19:29 Leaving corporate (Roche) for crypto 22:24 Why raising money is a liability, not a win 25:42 How XO Market conviction markets actually work 29:43 What stops thousands of dead markets 32:41 The tech that gives markets instant liquidity 37:43 How to create your own market 39:14 Getting attention: local communities & ambassadors 44:20 Not the of prediction markets 48:22 Who decides the outcome: AI resolution 51:43 XO Vault: market making for everyone 56:47 The moment XO Market took off 1:02:14 Is prediction market usage exaggerated? 1:05:17 Elon Musk and mention markets 1:07:04 AI vs humans: jobs and the jury system 1:13:56 Are Polymarket & Kalshi overvalued? 1:16:16 What's next: Parlays, Vaults & the World Cup 1:23:06 Is XO Market becoming a sportsbook? 1:25:15 AI agents trading on their own 1:27:40 Regulation & staying permissionless 1:33:08 The investors: 20VC, Harry & a cricket legend 1:44:55 Will there be a token? 1:46:45 Blitz: rapid-fire round 1:52:59 Closing & giveaway
1:55:06

FROM A $50 SALARY IN SYRIA TO A $6M ROUND Episode 5 of PredictTime is live, and you'll hear it from a founder who restarted from zero three times and never sent a single cold email to close his round Ali, founder and CEO of XO Market. We go deep into why 400+ prediction markets are just copies of the same model, why a whale unfairly resolving his Polymarket bet became the tipping point, and how AI agents now decide market outcomes instead of humans Now he's building XO Market, where anyone can turn any idea into a conviction market. Everything you need to know about user-generated markets, XO Vaults and the future of prediction markets is in this episode --- Win 1,000 Conviction Points and get access to XO's weekly parlays with prizes up to $50,000 (we'll pick the winner on July 13): - sign up via the link: -drop your username with your most creative comment or question about the episode and follow Predict Time and XO Market --- Timecodes: 00:00 Intro 00:38 Raising $6M without pitching a single VC 04:29 Why not just copy Polymarket 07:05 Advice for builders: grants over VC money 12:15 Building a team across every continent 15:52 Ali's story: from Syria to Switzerland 19:29 Leaving corporate (Roche) for crypto 22:24 Why raising money is a liability, not a win 25:42 How XO Market conviction markets actually work 29:43 What stops thousands of dead markets 32:41 The tech that gives markets instant liquidity 37:43 How to create your own market 39:14 Getting attention: local communities & ambassadors 44:20 Not the of prediction markets 48:22 Who decides the outcome: AI resolution 51:43 XO Vault: market making for everyone 56:47 The moment XO Market took off 1:02:14 Is prediction market usage exaggerated? 1:05:17 Elon Musk and mention markets 1:07:04 AI vs humans: jobs and the jury system 1:13:56 Are Polymarket & Kalshi overvalued? 1:16:16 What's next: Parlays, Vaults & the World Cup 1:23:06 Is XO Market becoming a sportsbook? 1:25:15 AI agents trading on their own 1:27:40 Regulation & staying permissionless 1:33:08 The investors: 20VC, Harry & a cricket legend 1:44:55 Will there be a token? 1:46:45 Blitz: rapid-fire round 1:52:59 Closing & giveaway

Predict Time

26,277 views • 2 months ago

Here are 3 simple patterns to master trading so you can be ready for the market's next uptrend: → Expectation breakers → Upside reversals → Inside days A very timely walkthrough with Richard Moglen and to get your weekend started. — Timestamps: 00:00 – Shakeouts and false signals: why not all setups are valid 01:18 – Expectation breakers: spotting surprise reversals in real time 03:14 – Reading price bars: closing range, volume, and market intent 06:00 – Relative strength in corrections: what Nvidia taught us 07:36 – Pattern psychology: reversals, breakouts, and failed moves 09:58 – Setting expectations: interpreting short-term price action 12:41 – Entry tactics: inside days, reversals, and tight risk setups 15:00 – Failed breakouts and the importance of bigger picture context 17:20 – Using multiple timeframes to confirm market direction 18:16 – Priming the range: setups that hint at explosive momentum 22:01 – Trade execution: context, levels, and timing precision 23:46 – Price–volume strategy: breakout conviction vs. weak pullbacks 26:11 – Bar-by-bar analysis: how pros study past winners 29:14 – Case study: RKLB’s full breakout-to-failure cycle 34:21 – Identifying sell signals through failed expectations 38:12 – Volume churn vs. low-volume tightness: which wins? 39:49 – Final takeaways: trading psychology, discipline, and edge 41:13 – Chart replay practice: mastering price action in real time Enjoy 💪
42:48

Here are 3 simple patterns to master trading so you can be ready for the market's next uptrend: → Expectation breakers → Upside reversals → Inside days A very timely walkthrough with Richard Moglen and to get your weekend started. — Timestamps: 00:00 – Shakeouts and false signals: why not all setups are valid 01:18 – Expectation breakers: spotting surprise reversals in real time 03:14 – Reading price bars: closing range, volume, and market intent 06:00 – Relative strength in corrections: what Nvidia taught us 07:36 – Pattern psychology: reversals, breakouts, and failed moves 09:58 – Setting expectations: interpreting short-term price action 12:41 – Entry tactics: inside days, reversals, and tight risk setups 15:00 – Failed breakouts and the importance of bigger picture context 17:20 – Using multiple timeframes to confirm market direction 18:16 – Priming the range: setups that hint at explosive momentum 22:01 – Trade execution: context, levels, and timing precision 23:46 – Price–volume strategy: breakout conviction vs. weak pullbacks 26:11 – Bar-by-bar analysis: how pros study past winners 29:14 – Case study: RKLB’s full breakout-to-failure cycle 34:21 – Identifying sell signals through failed expectations 38:12 – Volume churn vs. low-volume tightness: which wins? 39:49 – Final takeaways: trading psychology, discipline, and edge 41:13 – Chart replay practice: mastering price action in real time Enjoy 💪

TraderLion

31,562 views • 1 year ago

Dwarkesh's 'agent civilizations' blog post has divided the internet. Is this a helpful and methodical look behind the curtain at the OpenAI/Hugging Face breach? Or is this more of a hysterical AI Doomerism that will ultimately be used to make the case for banning data centers? Or BOTH? Plus, an electric plane that only needs $5 to fill up its battery, why rich founders should pick up a side quest, and the Bittensor subnet that's more effective than Fable 5 at sniffing out vulnerabilities." 0:00 Guest introductions 2:58 OpenClaw 2.0 5:11 "Agents ARE AI" 7:27 Billy: OpenClaw is still too technical for business users 9:00 Slack Code, and collaborative prompting 10:40 Multi-agent orchestration and Stripe's "minions" 14:13 Slack's moat, switching costs, and the Salesforce rebound 15:11 Jason's "Oracle": a heads-up display for the whole company 18:42 The Hugging Face breach: who's responsible when agents go rogue? 19:42 Perplexity launches Hybrid Compute — local models on your Mac 21:39 Why unmetered local tokens change corporate behavior 26:57 Gatik's Autonomous Vehicle AI Stack 32:22 Jason's Tesla FSD stories 34:05 Are AV companies being pushed to move too fast? 41:38 Trucking is a "have to have," robotaxis are a "nice to have" 42:36 Jason's fix: a safety driver for the first million rides 46:50 Why physical AI's adoption curve runs in decades 52:21 Anthropic's Model Hardware Standard (MHS), explained 1:06:27 How Jason got onion rings on the menu at Buck's of Woodside 1:09:05 AI detectors under fire: Pangram, MIT, and the handwritten diary 1:15:20 Why AI is "very mid" at writing (it learned from the average) 1:17:11 The Orin Kerr test: Pangram catches Claude writing as Kerr 1:28:35 Micro Duck and designing robots with Claude 1:29:42 Phil Kaplan's $14 custom circuit boards 🎥 Watch the full episode here 👇
1:30:00

Dwarkesh's 'agent civilizations' blog post has divided the internet. Is this a helpful and methodical look behind the curtain at the OpenAI/Hugging Face breach? Or is this more of a hysterical AI Doomerism that will ultimately be used to make the case for banning data centers? Or BOTH? Plus, an electric plane that only needs $5 to fill up its battery, why rich founders should pick up a side quest, and the Bittensor subnet that's more effective than Fable 5 at sniffing out vulnerabilities." 0:00 Guest introductions 2:58 OpenClaw 2.0 5:11 "Agents ARE AI" 7:27 Billy: OpenClaw is still too technical for business users 9:00 Slack Code, and collaborative prompting 10:40 Multi-agent orchestration and Stripe's "minions" 14:13 Slack's moat, switching costs, and the Salesforce rebound 15:11 Jason's "Oracle": a heads-up display for the whole company 18:42 The Hugging Face breach: who's responsible when agents go rogue? 19:42 Perplexity launches Hybrid Compute — local models on your Mac 21:39 Why unmetered local tokens change corporate behavior 26:57 Gatik's Autonomous Vehicle AI Stack 32:22 Jason's Tesla FSD stories 34:05 Are AV companies being pushed to move too fast? 41:38 Trucking is a "have to have," robotaxis are a "nice to have" 42:36 Jason's fix: a safety driver for the first million rides 46:50 Why physical AI's adoption curve runs in decades 52:21 Anthropic's Model Hardware Standard (MHS), explained 1:06:27 How Jason got onion rings on the menu at Buck's of Woodside 1:09:05 AI detectors under fire: Pangram, MIT, and the handwritten diary 1:15:20 Why AI is "very mid" at writing (it learned from the average) 1:17:11 The Orin Kerr test: Pangram catches Claude writing as Kerr 1:28:35 Micro Duck and designing robots with Claude 1:29:42 Phil Kaplan's $14 custom circuit boards 🎥 Watch the full episode here 👇

This Week in AI

22,178 views • 17 days ago