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Why funding open source is NOT philanthropy with Pavlenex | SLP734 Pavlenex, Bitcoin open source contributor, joins me to discuss why funding builders matters, how open source projects evolve, and what’s new with Stratum V2 & BTCPay Server. Timestamps: (00:00) - Intro (01:09) - Open source is not philanthropy...

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Stephan Livera

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11,641 views • 4 months ago •via X (Twitter)

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My biggest fear for AI is concentration of power. Open-source is a solution. Watch this video to understand what's going on: 0:00 Intro 0:52 NVIDIA's letter 1:36 What is open-source? 3:53 How open-source works 5:48 Kimi K3 6:38 Closed vs Open 8:39 Open-source in the U.S. 12:10 The AI stack 13:05 What if open source wins? 14:08 Jevon's Paradox 14:56 How the AI stack is affected 18:04 User experience 19:38 AI safety 30:30 China 35:50 Distillation 41:40 Banning Chinese models? 43:38 Anthropic's response

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To support the open-source AI community, CHAI is giving out unlimited number of grants ranging from $1,000 - $5,000. Submit any open-source projects (GitHub / Huggingface Repos), it does not need to be AI related! Prize determined based on impact and number of stars / downloads.
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To support the open-source AI community, CHAI is giving out unlimited number of grants ranging from $1,000 - $5,000. Submit any open-source projects (GitHub / Huggingface Repos), it does not need to be AI related! Prize determined based on impact and number of stars / downloads.

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270,415 views • 2 months ago

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119,268 views • 5 months ago

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257,182 views • 2 months ago

Michael Bolin (Michael Bolin) is the tech lead of the Codex open source repository at OpenAI and formerly a distinguished eng (E9) at Meta. I asked him for all the details on his career story and how he uses Codex for max benefit. Timestamps: 00:00:00 - Intro 00:00:56 - Chickenfoot 00:02:45 - Working at Google 00:06:34 - Overhauling Facebook's build system 00:16:36 - Rewriting Facebook's IDE 00:26:01 - Struggles after Principal Eng (E8) promo 00:28:39 - Building a virtual filesystem for Facebook 00:35:47 - Delayed Distinguished promo (E9) and learnings 00:39:56 - Joining OpenAI 00:43:05 - Research-led vs engineering-led cultures 00:44:53 - The story behind Codex 00:51:00 - How he uses Codex 00:57:00 - Why Codex's harness is open source 00:59:50 - Top technical book recommendations 01:05:02 - Why deep technical skills are still valuable (for now) 01:11:07 - How to start projects well 01:14:27 - Advice on writing better and career planning 01:17:06 - Advice for his younger self 01:19:10 - Outro He was a dream guest of mine and I'm excited to share his story with you all! Other places to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:
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Michael Bolin (Michael Bolin) is the tech lead of the Codex open source repository at OpenAI and formerly a distinguished eng (E9) at Meta. I asked him for all the details on his career story and how he uses Codex for max benefit. Timestamps: 00:00:00 - Intro 00:00:56 - Chickenfoot 00:02:45 - Working at Google 00:06:34 - Overhauling Facebook's build system 00:16:36 - Rewriting Facebook's IDE 00:26:01 - Struggles after Principal Eng (E8) promo 00:28:39 - Building a virtual filesystem for Facebook 00:35:47 - Delayed Distinguished promo (E9) and learnings 00:39:56 - Joining OpenAI 00:43:05 - Research-led vs engineering-led cultures 00:44:53 - The story behind Codex 00:51:00 - How he uses Codex 00:57:00 - Why Codex's harness is open source 00:59:50 - Top technical book recommendations 01:05:02 - Why deep technical skills are still valuable (for now) 01:11:07 - How to start projects well 01:14:27 - Advice on writing better and career planning 01:17:06 - Advice for his younger self 01:19:10 - Outro He was a dream guest of mine and I'm excited to share his story with you all! Other places to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

Ryan Peterman

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> "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
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> "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

69,339 views • 1 month ago

NEW POD vitalik.eth on the greenpill.network podcast for a year-end deep dive into public goods funding in the Ethereum ecosystem. Thx Devansh Mehta for co-hosting. We discuss how the landscape has shifted from “vibes-based” funding to verifiable, dependency-driven mechanisms, and why this is the best moment to reform PGF using new tools like programmable cryptography, AI-assisted evaluation, and deep funding models. Vitalik shares how he thinks about dependencies, credible neutrality, open-source licensing, pluralism, accountability, ethereum localism, and what builders should prioritize in the coming year. 00:00 – Welcome to the Greenpill Podcast 01:50 – Vitalik joins: why public goods funding matters 02:19 – Why PGF is essential for decentralization 04:18 – The crypto spirit: censorship resistance, institutional design & funding 06:42 – The shift from vibes-era PGF to verifiable mechanisms 08:25 – Why 2026 is the best moment to reform PGF 10:19 – Where does PGF money actually come from? 12:45 – Open-source licensing, taxes & funding dependencies 17:34 – “Fund your dependencies” as a stable mechanism 19:35 – Why general-purpose QF doesn’t work in a chaotic world 21:59 – Bottom-up vs top-down: polycentric PGF 25:29 – How to create accountability loops in public goods 27:22 – Funding open-source as an Ethereum priority 29:31 – Privacy as a public good & why it’s upstream of PGF 31:54 – What OSS developers really think about crypto 33:52 – Mixing social outreach with financial support 35:56 – What should PGF builders focus on in 2026? 38:13 – Work with new projects, not legacy ones 39:44 – Ecosystem cycles & “layers of sediment” 41:39 – Yield-based funding (Octant) & treasury strategies 43:40 – Accountability: from vibes to rigorous mechanisms 47:35 – Motivation, feedback & the psychology of public goods 50:43 – Profit sharing licenses & sustainable PGF pools 53:46 – Security, issuance & public goods 56:12 – Technology, democracy & long-term risks 58:31 – How PGF relates to DIAC (Defensive/Decentralized Acceleration) 01:00:05 – Solving the free-rider problem without coercion 01:02:12 – Mechanisms vs coercion: credible neutrality 01:04:16 – Institutions, power & capture risks 01:06:16 – Individuals vs institutions in PGF 01:08:41 – Why PGF is more error-tolerant than governance 01:11:01 – Pluralism: many funders, many mechanisms 01:13:14 – Why diversity of funders is healthy 01:15:17 – What Vitalik wants built next 01:17:12 – Ethereum localism & real-world experiments 01:19:28 – What success in PGF looks like by end of 2026 01:24:28 – Closing thoughts
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NEW POD vitalik.eth on the greenpill.network podcast for a year-end deep dive into public goods funding in the Ethereum ecosystem. Thx Devansh Mehta for co-hosting. We discuss how the landscape has shifted from “vibes-based” funding to verifiable, dependency-driven mechanisms, and why this is the best moment to reform PGF using new tools like programmable cryptography, AI-assisted evaluation, and deep funding models. Vitalik shares how he thinks about dependencies, credible neutrality, open-source licensing, pluralism, accountability, ethereum localism, and what builders should prioritize in the coming year. 00:00 – Welcome to the Greenpill Podcast 01:50 – Vitalik joins: why public goods funding matters 02:19 – Why PGF is essential for decentralization 04:18 – The crypto spirit: censorship resistance, institutional design & funding 06:42 – The shift from vibes-era PGF to verifiable mechanisms 08:25 – Why 2026 is the best moment to reform PGF 10:19 – Where does PGF money actually come from? 12:45 – Open-source licensing, taxes & funding dependencies 17:34 – “Fund your dependencies” as a stable mechanism 19:35 – Why general-purpose QF doesn’t work in a chaotic world 21:59 – Bottom-up vs top-down: polycentric PGF 25:29 – How to create accountability loops in public goods 27:22 – Funding open-source as an Ethereum priority 29:31 – Privacy as a public good & why it’s upstream of PGF 31:54 – What OSS developers really think about crypto 33:52 – Mixing social outreach with financial support 35:56 – What should PGF builders focus on in 2026? 38:13 – Work with new projects, not legacy ones 39:44 – Ecosystem cycles & “layers of sediment” 41:39 – Yield-based funding (Octant) & treasury strategies 43:40 – Accountability: from vibes to rigorous mechanisms 47:35 – Motivation, feedback & the psychology of public goods 50:43 – Profit sharing licenses & sustainable PGF pools 53:46 – Security, issuance & public goods 56:12 – Technology, democracy & long-term risks 58:31 – How PGF relates to DIAC (Defensive/Decentralized Acceleration) 01:00:05 – Solving the free-rider problem without coercion 01:02:12 – Mechanisms vs coercion: credible neutrality 01:04:16 – Institutions, power & capture risks 01:06:16 – Individuals vs institutions in PGF 01:08:41 – Why PGF is more error-tolerant than governance 01:11:01 – Pluralism: many funders, many mechanisms 01:13:14 – Why diversity of funders is healthy 01:15:17 – What Vitalik wants built next 01:17:12 – Ethereum localism & real-world experiments 01:19:28 – What success in PGF looks like by end of 2026 01:24:28 – Closing thoughts

owockai

93,860 views • 9 months ago

SPECIAL: How Erik Voorhees Built the Leading Private, Uncensored AI Venice Timestamps: 00:00 Intro & ShapeShift Origin Story 05:25 Did Crypto Play Out as Expected? 06:25 AI vs. Crypto: Are They Similar? 07:23 What Is Venice AI? 09:38 From ShapeShift to Venice 10:31 Censorship in AI & the Open Source Alternative 11:38 Hibachi, infiniFi Ads 12:00 Are AI Labs Too Censored? 13:24 Relay Ad 13:41 Geopolitics: Chinese Open Source vs. US Closed Models 14:15 SBF, the Anthropic Investment & Crypto Scammers 16:26 NearCon, Illia & the AI/Crypto Convergence
17:28

SPECIAL: How Erik Voorhees Built the Leading Private, Uncensored AI Venice Timestamps: 00:00 Intro & ShapeShift Origin Story 05:25 Did Crypto Play Out as Expected? 06:25 AI vs. Crypto: Are They Similar? 07:23 What Is Venice AI? 09:38 From ShapeShift to Venice 10:31 Censorship in AI & the Open Source Alternative 11:38 Hibachi, infiniFi Ads 12:00 Are AI Labs Too Censored? 13:24 Relay Ad 13:41 Geopolitics: Chinese Open Source vs. US Closed Models 14:15 SBF, the Anthropic Investment & Crypto Scammers 16:26 NearCon, Illia & the AI/Crypto Convergence

The Rollup

47,841 views • 6 months ago

Announcing the Open Model Series: a new series on open source AI models, with merve of Hugging Face. Hugging Face is the open model hub: it hosts model weights, datasets, evals, & demo apps, and maintains the open-source libraries (like transformers) used to run and train them. I think of it like GitHub, but for AI models. You can download open models and run them on your own machines. In this series we'll cover what open source and open weight models are, how they work, how to run them yourself, and why they're important. By the way - this video is edited entirely with Claude! I can make a tutorial on how I did it. If there's a question you want answered about open models, leave it in the comments. We will read them all. Episode 1 is out soon.
0:26

Announcing the Open Model Series: a new series on open source AI models, with merve of Hugging Face. Hugging Face is the open model hub: it hosts model weights, datasets, evals, & demo apps, and maintains the open-source libraries (like transformers) used to run and train them. I think of it like GitHub, but for AI models. You can download open models and run them on your own machines. In this series we'll cover what open source and open weight models are, how they work, how to run them yourself, and why they're important. By the way - this video is edited entirely with Claude! I can make a tutorial on how I did it. If there's a question you want answered about open models, leave it in the comments. We will read them all. Episode 1 is out soon.

Harper Carroll

30,392 views • 1 month ago

Exclusive: Meta just released Llama 3.1 405B — the first-ever open-sourced frontier AI model, beating top closed models like GPT-4o across several benchmarks. I sat down with Mark Zuckerberg, diving into why this marks a major moment in AI history. Timestamps: 00:00 Intro 00:38 Meta’s Llama 3.1 rundown 03:44 Real-world use cases for Llama 3.1 06:15 Educating developers on open-source AI tools 09:43 Societal implications of open-source AI 13:00 Balancing power and managing bad actors 14:40 Open source and global competition 16:59 Accelerating innovation and economic growth 20:04 Zuck on Apple and lessons from the past 24:22 Future of AI: Llama 3 and beyond 26:43 Prediction: Billions of personalized AI agents 31:32 Factors to changing anti-AI sentiment
35:22

Exclusive: Meta just released Llama 3.1 405B — the first-ever open-sourced frontier AI model, beating top closed models like GPT-4o across several benchmarks. I sat down with Mark Zuckerberg, diving into why this marks a major moment in AI history. Timestamps: 00:00 Intro 00:38 Meta’s Llama 3.1 rundown 03:44 Real-world use cases for Llama 3.1 06:15 Educating developers on open-source AI tools 09:43 Societal implications of open-source AI 13:00 Balancing power and managing bad actors 14:40 Open source and global competition 16:59 Accelerating innovation and economic growth 20:04 Zuck on Apple and lessons from the past 24:22 Future of AI: Llama 3 and beyond 26:43 Prediction: Billions of personalized AI agents 31:32 Factors to changing anti-AI sentiment

Rowan Cheung

2,657,507 views • 2 years ago