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EMERGENCY POLICY HOUR A flaw in Coldcard's entropy generation left many users' bitcoin exposed. Over 1,000 BTC moved from wallets that likely never touched the internet. Rob Hamilton joins Zack Shapiro, Bayman11771, and Zack Cohen to break down what happened, how an AI model found the bug in minutes,...

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Bitcoin Policy Institute

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If you’re in your 20s and trying to get to 1 Bitcoin, this is the most direct roadmap you’ll hear. Today, BRITISH HODL ❤️‍🔥🐂❤️‍🔥 breaks down the mindset, the money strategy, and why “just DCA” won’t save you. What you’ll learn: Why 1 BTC is a different game than “0.1 BTC” The real skill: converting value → cash (fast) How AI creates a massive income gap (and how to exploit it) The habits that keep you broke - and the habits that build a stack A simple roadmap to accelerate toward your first full coin YT in replies 🧡🎧 CHAPTERS 0:00 BritishHODL’s “Bitcoin clicked” moment (stock-to-flow) 1:25 The mission: getting to 1 BTC fast (Gen Z plan) 2:19 Is 1 BTC still possible for young people? 3:46 “Hold the space” + relentless focus 5:25 Why 1 BTC (not 0.1) — whole coiner mindset 8:03 Gen Z brainwashing + competition mindset 11:33 The only skill: value → currency 15:55 The moment he went all-in (Bitcoin Standard story) 20:25 AI is changing everything (coffee shop jobs are cooked) 23:25 Why Gen Z resists AI (environment/social framing) 29:35 Biggest traps: living only for today 33:16 “Get rid of money fast” (protect it in BTC) 36:04 Why “DCA $5/day” is a losing strategy 38:05 Burnout mindset + Relentless (Tim Grover) 43:48 Stop listening to broke people 50:13 Why he doesn’t talk to “Bitcoiners” - only accumulators 55:32 “If you’re still debating Bitcoin, you’re cooked” 1:00:21 The AI income play: help businesses implement AI 1:04:39 The condensed roadmap: decide → earn → buy 1:09:54 Only ~0.4% can afford 1 BTC at $100k (scarcity) 1:12:08 Why his message never changes: “Get to 1 Bitcoin” 1:13:48 Wrap: “Just do it”
1:14:38

If you’re in your 20s and trying to get to 1 Bitcoin, this is the most direct roadmap you’ll hear. Today, BRITISH HODL ❤️‍🔥🐂❤️‍🔥 breaks down the mindset, the money strategy, and why “just DCA” won’t save you. What you’ll learn: Why 1 BTC is a different game than “0.1 BTC” The real skill: converting value → cash (fast) How AI creates a massive income gap (and how to exploit it) The habits that keep you broke - and the habits that build a stack A simple roadmap to accelerate toward your first full coin YT in replies 🧡🎧 CHAPTERS 0:00 BritishHODL’s “Bitcoin clicked” moment (stock-to-flow) 1:25 The mission: getting to 1 BTC fast (Gen Z plan) 2:19 Is 1 BTC still possible for young people? 3:46 “Hold the space” + relentless focus 5:25 Why 1 BTC (not 0.1) — whole coiner mindset 8:03 Gen Z brainwashing + competition mindset 11:33 The only skill: value → currency 15:55 The moment he went all-in (Bitcoin Standard story) 20:25 AI is changing everything (coffee shop jobs are cooked) 23:25 Why Gen Z resists AI (environment/social framing) 29:35 Biggest traps: living only for today 33:16 “Get rid of money fast” (protect it in BTC) 36:04 Why “DCA $5/day” is a losing strategy 38:05 Burnout mindset + Relentless (Tim Grover) 43:48 Stop listening to broke people 50:13 Why he doesn’t talk to “Bitcoiners” - only accumulators 55:32 “If you’re still debating Bitcoin, you’re cooked” 1:00:21 The AI income play: help businesses implement AI 1:04:39 The condensed roadmap: decide → earn → buy 1:09:54 Only ~0.4% can afford 1 BTC at $100k (scarcity) 1:12:08 Why his message never changes: “Get to 1 Bitcoin” 1:13:48 Wrap: “Just do it”

Nicki

42,702 Aufrufe • vor 5 Monaten

New greenpill.network pod today with @thedevanshmehta about Deep Funding, a new AI-powered funding mechanism that combines human evaluation and prediction markets to allocate resources for open-source projects. Topics: 1. how Deep Funding scales human judgment, 2. prevents Sybil attacks, 3. and creates a fair, dynamic “price feed” for public goods. 4. Devansh shares insights from the pilot run, the results of the data-science competition, and how the model will power Gitcoin Grants 24 #GG24 Timestamps: 00:00 – Intro: Welcome to the Greenpill Podcast – exploring tech, coordination & Protopia 00:45 – Introducing guest Devansh Mehta, AI & Public Goods Lead at the Ethereum Foundation 01:20 – What is Deep Funding and why it matters 02:00 – How Deep Funding scales human evaluations with AI models 02:45 – Overview of the pilot run and what was tested 03:20 – How the mechanism works: human jurors + model builders 04:30 – The White Hat Sybil attack and what it revealed 05:40 – How Deep Funding integrates data science competitions and prediction markets 06:50 – Results of the pilot: weighted funding for 45 open-source repos 07:30 – Creating a credibly neutral funding system with unequal weights 08:40 – Comparing Deep Funding with Protocol Guild and other mechanisms 09:20 – Building a strong community of AI developers and human jurors 10:30 – The role of jurors and models in fair evaluation 11:10 – What’s next: expanding to 90 repos in Gitcoin Grants 24 (GG24) 11:50 – Funding pool: $350K from Ethereum Foundation & Gitcoin 12:30 – Challenges of distributing capital efficiently and fairly 13:20 – Moving to GitHub repo-level governance: who controls the funds? 14:40 – Two models of spending: splits contracts vs counterfactual wallets 15:40 – Lessons from past Gitcoin funding rounds 16:20 – Why Deep Funding focuses on units of work, not organizations 17:20 – Avoiding distortions and improving fairness in funding 18:10 – The vision: creating a live price feed for public goods 19:10 – How prediction markets price open-source value 20:30 – Self-correcting market behavior and real-time adjustments 21:20 – Subsidies and liquidity: bootstrapping active participation 22:10 – Balancing liquidity levels to prevent manipulation 23:00 – What’s next for Deep Funding: refining future iterations 23:40 – Shoutout to the model builders and competition winners 24:20 – Where to learn more: & 25:00 – Closing: the future of AI, governance, and funding what matters If you’re curious about the intersection of AI, governance, and funding public goods, this conversation is for you. And participate in GG24 at
25:41

New greenpill.network pod today with @thedevanshmehta about Deep Funding, a new AI-powered funding mechanism that combines human evaluation and prediction markets to allocate resources for open-source projects. Topics: 1. how Deep Funding scales human judgment, 2. prevents Sybil attacks, 3. and creates a fair, dynamic “price feed” for public goods. 4. Devansh shares insights from the pilot run, the results of the data-science competition, and how the model will power Gitcoin Grants 24 #GG24 Timestamps: 00:00 – Intro: Welcome to the Greenpill Podcast – exploring tech, coordination & Protopia 00:45 – Introducing guest Devansh Mehta, AI & Public Goods Lead at the Ethereum Foundation 01:20 – What is Deep Funding and why it matters 02:00 – How Deep Funding scales human evaluations with AI models 02:45 – Overview of the pilot run and what was tested 03:20 – How the mechanism works: human jurors + model builders 04:30 – The White Hat Sybil attack and what it revealed 05:40 – How Deep Funding integrates data science competitions and prediction markets 06:50 – Results of the pilot: weighted funding for 45 open-source repos 07:30 – Creating a credibly neutral funding system with unequal weights 08:40 – Comparing Deep Funding with Protocol Guild and other mechanisms 09:20 – Building a strong community of AI developers and human jurors 10:30 – The role of jurors and models in fair evaluation 11:10 – What’s next: expanding to 90 repos in Gitcoin Grants 24 (GG24) 11:50 – Funding pool: $350K from Ethereum Foundation & Gitcoin 12:30 – Challenges of distributing capital efficiently and fairly 13:20 – Moving to GitHub repo-level governance: who controls the funds? 14:40 – Two models of spending: splits contracts vs counterfactual wallets 15:40 – Lessons from past Gitcoin funding rounds 16:20 – Why Deep Funding focuses on units of work, not organizations 17:20 – Avoiding distortions and improving fairness in funding 18:10 – The vision: creating a live price feed for public goods 19:10 – How prediction markets price open-source value 20:30 – Self-correcting market behavior and real-time adjustments 21:20 – Subsidies and liquidity: bootstrapping active participation 22:10 – Balancing liquidity levels to prevent manipulation 23:00 – What’s next for Deep Funding: refining future iterations 23:40 – Shoutout to the model builders and competition winners 24:20 – Where to learn more: & 25:00 – Closing: the future of AI, governance, and funding what matters If you’re curious about the intersection of AI, governance, and funding public goods, this conversation is for you. And participate in GG24 at

owocki’s gitcoin 3.0 arc

12,981 Aufrufe • vor 9 Monaten

> "In no scenario is it bad for the US to have frontier-class open-source models." > "Every time there’s a step-function improvement in AI, a human bottleneck emerges alongside it." > "Your desire to be liked sometimes takes away from your desire to do the right thing and seek the truth." > "Every job will get refactored. The people who aren’t AI fluent will have a very hard time finding jobs." Jeetu Patel (Jeetu Patel), President & Chief Product Officer at Cisco sat down for an expansive talk about life and the future. 00:00 AI, jobs, and human potential 00:41 AI cybersecurity and Cisco’s security models 06:33 Why Cisco released the models openly 08:08 Running AI models locally 10:12 Why people are negative about AI 12:14 Will humans always be needed? 14:56 Can curiosity and ambition be taught? 17:12 Passion vs. expertise 19:39 The importance of unlearning 23:52 How to find the truth 26:06 How to get people excited about AI 33:35 How open source affects the AI industry 35:07 Can open-source AI make money? 46:44 Are Chinese open-source models good for the US? 49:55 Should the US restrict Chinese AI models? 53:05 Does open source make humanity safer? 54:11 Advice for people worried about AI
57:20

> "In no scenario is it bad for the US to have frontier-class open-source models." > "Every time there’s a step-function improvement in AI, a human bottleneck emerges alongside it." > "Your desire to be liked sometimes takes away from your desire to do the right thing and seek the truth." > "Every job will get refactored. The people who aren’t AI fluent will have a very hard time finding jobs." Jeetu Patel (Jeetu Patel), President & Chief Product Officer at Cisco sat down for an expansive talk about life and the future. 00:00 AI, jobs, and human potential 00:41 AI cybersecurity and Cisco’s security models 06:33 Why Cisco released the models openly 08:08 Running AI models locally 10:12 Why people are negative about AI 12:14 Will humans always be needed? 14:56 Can curiosity and ambition be taught? 17:12 Passion vs. expertise 19:39 The importance of unlearning 23:52 How to find the truth 26:06 How to get people excited about AI 33:35 How open source affects the AI industry 35:07 Can open-source AI make money? 46:44 Are Chinese open-source models good for the US? 49:55 Should the US restrict Chinese AI models? 53:05 Does open source make humanity safer? 54:11 Advice for people worried about AI

Matthew Berman

67,675 Aufrufe • vor 6 Tagen