Podcast appearances and mentions of Jack Dorsey

Episode 562: Neal and Toby talk about the latest chapter in the US-China trade war, with China holding out on two things: rare earth minerals and Boeing deliveries. Then, Mark Zuckerberg takes the stand in the trial against the FTC where old emails are being dubbed the ‘smoking gun'. Also, LVMH loses its crown to Hermès in market cap. Plus, Twitter founder Jack Dorsey and Elon Musk agree on something: IP law should be deleted. Do they have a strong case? Finally, American Airlines offers free WI-FI, OpenAI's naming flubs, and the baseball to photographer career path. Subscribe to Morning Brew Daily for more of the news you need to start your day. Share the show with a friend, and leave us a review on your favorite podcast app. Visit https://planetoat.com/ to learn more! Listen to Morning Brew Daily Here: https://link.chtbl.com/MBD Watch Morning Brew Daily Here: https://www.youtube.com/@MorningBrewDailyShow How much progress have we made this year: https://year-progress.cnln.dev/ 00:00 - Year in Progress 03:00 - China Makes a Move vs US 07:40 - Meta vs the FTC 12:35 - LVMH Sto Drops 17:40 - IP Law Debate 21:45 - Headlines  Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's show: In this episode, Jason, Alex, and Lon dive into Blue Origin's all-female celeb spaceflight (yes, Katy Perry sang on reentry), Hugging Face's unexpected move into robotics, and Jack Dorsey's wild take that we should “delete all IP law.” Plus, they break down Figure AI's eye-popping $39B valuation, the risks of SPVs, and what founders and investors can learn from the SPAC boom. As Jason puts it: “You just have to assume an 80% failure rate.”*Timestamps:(0:00) Jason kicks off the show!(1:34) Blue Origin all-female crew launch and space tourism(7:17) Emerging technologies and tech adoption trends(10:07) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!(12:38) Hugging Face acquires Pollen Robotics; Open AI and robotics debate(19:42) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWIST(20:42) Significance of Hugging Face in generative AI; Jack Dorsey's IP law stance(25:01) U.S. high-tech job market; revisiting IP law discussions(30:03) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(31:03) IP law and American innovation(32:22) Challenges in startup exits and secondary trading platforms(37:09) Figure AI's valuation controversy(46:37) Startup insights and investing perspectives(50:39) Jeff Bezos on risk assessment(57:03) Jason's personal journey and reflections(1:02:06) Developing a samurai mindset; societal systems abstraction*Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(10:07) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!(19:42) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWIST(30:03) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twistGreat TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com*Subscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

Kinsella on Liberty Podcast: Episode 459. In response to lots of froth on Twitter related to Jack Dorsey's call to "delete all IP law," which was echoed by Elon Musk (Musk and Dorsey: “delete all IP law”) I decided to attempt to host an impromptu Twitter Spaces about this. After overcoming some technical glitches, here is the result (and thanks to @Brunopbch, @NotGovernor (Patrick Smith), and @TrueAmPatriot86 for assists). I proposed to the space: "Fielding Questions About Abolishing Intellectual Property, about IP, and About Libertarian Property Rights", and that's basically what we ended up talking about. The Twitter spaces can be viewed here; I have clipped off the first 8 minutes or so of setup talk for this podcast episode. Grok summaries and shownotes and Youtube Transcript below. https://t.co/IHeVhPhlbs I'm going to do an impromptu Twitter space in an hour (2pm CST) to field any questions about the Libertarian Case Against Intellectual Property, in view of recent Twitter debates inspired by @jack Dorsey's and @elonmusk 's anti-IP comments,… — Stephan Kinsella (@NSKinsella) April 14, 2025 https://youtu.be/01FdFoB9QHY GROK HIGH LEVEL SUMMARY: Below is a concise summary of the video "Stephan Kinsella on Intellectual Property (IP)" (https://www.youtube.com/watch?v=01FdFoB9QHY), divided into six parts, based on the provided transcript and informed by the linked post (https://c4sif.org/2025/04/musk-dorsey-delete-all-ip-law/). The video features Stephan Kinsella discussing the case for abolishing IP laws in a Twitter Spaces session. Summary in Six Parts 1. Introduction and Context (0:01–1:03) Kinsella opens the session, discussing technical setup and his recent online IP debates, sparked by figures like Elon Musk and Jack Dorsey, who advocate abolishing IP laws. 2. Addressing IP Objections (1:09–5:16) Kinsella invites questions and tackles a common concern: IP protects small creators from big corporations. He argues this is misguided, noting Musk and Dorsey's history of non-aggressive patent use (e.g., Tesla, Twitter), and challenges the assumption that creators deserve government-enforced rights. 3. Misconceptions and Debate Challenges (5:23–12:28) He debunks myths equating copying to theft or plagiarism, criticizing IP as anti-competitive. Kinsella laments Twitter's combative nature, where users avoid substantive dialogue, and shares his desire for recorded discussions to foster learning, citing past successes. 4. China and IP's Economic Impact (12:34–15:22) Responding to a question, Kinsella argues China's growth shows benefits of lax IP, as adopting Western technology isn't theft but learning. He critiques U.S. politicians for using “IP theft” to justify tariffs and impose Western IP laws globally. 5. IP vs. Property Rights and Innovation (15:48–38:02) Kinsella disputes claims that IP is a natural right, explaining ownership comes from first use or contract, not creation. Using Bitcoin as an example, he emphasizes secrecy over legal enforcement. He argues IP reduces innovation by granting monopolies, slowing progress for patent holders and competitors alike. 6. Corporate Power and IP's Decline (38:09–1:15:40) He asserts IP fuels corporate giants (e.g., pharmaceuticals, Microsoft), not small creators, inflating prices and harming consumers. Kinsella notes copyright's decline due to piracy and predicts technology (e.g., 3D printing) may render patents obsolete. He concludes that abolishing IP requires embracing uncertainty for justice, despite public fear of change. This summary condenses the video's key points into six sections, aligning with the principled and pragmatic arguments Kinsella makes, while reflecting Musk and Dorsey's anti-IP stance from the linked post. Let me know if you need further refinement! GROK DETAILED SUMMARY: Below is a summary of the video "Stephan Kinsella on Intellectual Property (IP)" (https://www.youtube.com/watch?v=01FdFoB9QHY),

Trump gives Apple a giant break with wide-ranging tariff exemptions Car safety experts at NHTSA, which regulates Tesla, axed by DOGE Jack Dorsey and Elon Musk would like to 'delete all IP law' 5 things to know about Meta's upcoming FTC trial Meta's New Tech Wants You Using Phones in Theaters Trump Orders Investigation into Former Cybersecurity Chief Beyond Showerheads: Trump's Attempts to Kill Appliance Regulations Cause Chaos Microsoft rolls out Recall AI in preview to Copilot+ PCs, after delaying the feature twice, from June 2024 and October 2024, over security and privacy concerns The Dire Wolf Isn't Back—But Here's What 'De-Extinction' Tech Can Actually Do Trump White House budget proposal eviscerates science funding at NASA Linda McMahon just handed A.1. steak sauce an unbelievable opportunity Researcher uncovers dozens of sketchy Chrome extensions with 4 million installs Vizio Shows What Happens When U.S. Fascism And TV Ensh*ttification Meet Host: Leo Laporte Guests: Sam Abuelsamid, Allyn Malventano, and Fr. Robert Ballecer, SJ Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ZipRecruiter.com/Twit threatlocker.com/twit NetSuite.com/TWIT expressvpn.com/twit bitwarden.com/twit

Host Christine Lee breaks down the latest news in the crypto industry after MANTRA's OM token crash.Investors are reeling over MANTRA's OM token crash that has erased $5 billion in market cap within hours. Plus, Jack Dorsey, Elon Musk push to "delete all IP law" and Etehreum Founder VitalikButerin calls for improving privacy. CoinDesk's Christine Lee breaks down April 14, 2025 top headlines on "CoinDesk Daily."-This episode was hosted by Christine Lee. “CoinDesk Daily” is produced by Christine Lee and edited by Victor Chen.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Trump gives Apple a giant break with wide-ranging tariff exemptions Car safety experts at NHTSA, which regulates Tesla, axed by DOGE Jack Dorsey and Elon Musk would like to 'delete all IP law' 5 things to know about Meta's upcoming FTC trial Meta's New Tech Wants You Using Phones in Theaters Trump Orders Investigation into Former Cybersecurity Chief Beyond Showerheads: Trump's Attempts to Kill Appliance Regulations Cause Chaos Microsoft rolls out Recall AI in preview to Copilot+ PCs, after delaying the feature twice, from June 2024 and October 2024, over security and privacy concerns The Dire Wolf Isn't Back—But Here's What 'De-Extinction' Tech Can Actually Do Trump White House budget proposal eviscerates science funding at NASA Linda McMahon just handed A.1. steak sauce an unbelievable opportunity Researcher uncovers dozens of sketchy Chrome extensions with 4 million installs Vizio Shows What Happens When U.S. Fascism And TV Ensh*ttification Meet Host: Leo Laporte Guests: Sam Abuelsamid, Allyn Malventano, and Fr. Robert Ballecer, SJ Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ZipRecruiter.com/Twit threatlocker.com/twit NetSuite.com/TWIT expressvpn.com/twit bitwarden.com/twit

Trump gives Apple a giant break with wide-ranging tariff exemptions Car safety experts at NHTSA, which regulates Tesla, axed by DOGE Jack Dorsey and Elon Musk would like to 'delete all IP law' 5 things to know about Meta's upcoming FTC trial Meta's New Tech Wants You Using Phones in Theaters Trump Orders Investigation into Former Cybersecurity Chief Beyond Showerheads: Trump's Attempts to Kill Appliance Regulations Cause Chaos Microsoft rolls out Recall AI in preview to Copilot+ PCs, after delaying the feature twice, from June 2024 and October 2024, over security and privacy concerns The Dire Wolf Isn't Back—But Here's What 'De-Extinction' Tech Can Actually Do Trump White House budget proposal eviscerates science funding at NASA Linda McMahon just handed A.1. steak sauce an unbelievable opportunity Researcher uncovers dozens of sketchy Chrome extensions with 4 million installs Vizio Shows What Happens When U.S. Fascism And TV Ensh*ttification Meet Host: Leo Laporte Guests: Sam Abuelsamid, Allyn Malventano, and Fr. Robert Ballecer, SJ Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ZipRecruiter.com/Twit threatlocker.com/twit NetSuite.com/TWIT expressvpn.com/twit bitwarden.com/twit

Trump gives Apple a giant break with wide-ranging tariff exemptions Car safety experts at NHTSA, which regulates Tesla, axed by DOGE Jack Dorsey and Elon Musk would like to 'delete all IP law' 5 things to know about Meta's upcoming FTC trial Meta's New Tech Wants You Using Phones in Theaters Trump Orders Investigation into Former Cybersecurity Chief Beyond Showerheads: Trump's Attempts to Kill Appliance Regulations Cause Chaos Microsoft rolls out Recall AI in preview to Copilot+ PCs, after delaying the feature twice, from June 2024 and October 2024, over security and privacy concerns The Dire Wolf Isn't Back—But Here's What 'De-Extinction' Tech Can Actually Do Trump White House budget proposal eviscerates science funding at NASA Linda McMahon just handed A.1. steak sauce an unbelievable opportunity Researcher uncovers dozens of sketchy Chrome extensions with 4 million installs Vizio Shows What Happens When U.S. Fascism And TV Ensh*ttification Meet Host: Leo Laporte Guests: Sam Abuelsamid, Allyn Malventano, and Fr. Robert Ballecer, SJ Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ZipRecruiter.com/Twit threatlocker.com/twit NetSuite.com/TWIT expressvpn.com/twit bitwarden.com/twit

Trump gives Apple a giant break with wide-ranging tariff exemptions Car safety experts at NHTSA, which regulates Tesla, axed by DOGE Jack Dorsey and Elon Musk would like to 'delete all IP law' 5 things to know about Meta's upcoming FTC trial Meta's New Tech Wants You Using Phones in Theaters Trump Orders Investigation into Former Cybersecurity Chief Beyond Showerheads: Trump's Attempts to Kill Appliance Regulations Cause Chaos Microsoft rolls out Recall AI in preview to Copilot+ PCs, after delaying the feature twice, from June 2024 and October 2024, over security and privacy concerns The Dire Wolf Isn't Back—But Here's What 'De-Extinction' Tech Can Actually Do Trump White House budget proposal eviscerates science funding at NASA Linda McMahon just handed A.1. steak sauce an unbelievable opportunity Researcher uncovers dozens of sketchy Chrome extensions with 4 million installs Vizio Shows What Happens When U.S. Fascism And TV Ensh*ttification Meet Host: Leo Laporte Guests: Sam Abuelsamid, Allyn Malventano, and Fr. Robert Ballecer, SJ Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ZipRecruiter.com/Twit threatlocker.com/twit NetSuite.com/TWIT expressvpn.com/twit bitwarden.com/twit

Two stories dominated headlines this week, and they both have to do with Trump: Hut 8 launches a new Trump-back subsidiary, American Bitcoin, and blanket tariffs are set to disrupt everything from auto sales to ASIC miner imports. You're listening to The Mining Pod. Subscribe to the newsletter, trusted by over 10,000 Bitcoiners: https://newsletter.blockspacemedia.comWant to mine Bitcoin? Check out the Blockspace Media store today!Welcome to The Mining Pod's news roundup! Colin Harper and Matt Kimmel are joined by special guest Ethan Vera, the COO of Luxor, to discuss one of the most electric weeks for bitcoin mining news this year. They break down Hut8's new Trump-affiliated subsidiary American Bitcoin, Galaxy Digital's 15-year, $4.5 billion hosting agreement with CoreWeave, and how the Trump administration's blanket tariffs are bad news for miners and could lead to a 20-30% rise in ASIC miner prices. Plus, they cover Cango's proposal to sell its auto-finance business to a Bitmain-linked entity for $352 million, and for this week's cry corner, why Jack Dorsey thinks Lightning just isn't cutting it.# Notes:- Hash price at pre-election lows of $40/PH/s/day- Hut 8'sTrump-backed American Bitcoin- Galaxy-CoreWeave deal worth $4.5B over 15 years- New tariffs that will impact miners: 36% Thailand, 32% Indonesia, 24% Malaysia-Cango proposes to sell its autofi business for $352 million- Jack Dorsey: "We can do better than Lightning"Timestamps:00:00 Start01:50 Difficulty Report04:58 Trumps enter BTC mining11:14 Galaxy CoreWeave deal16:14 Tariffs are taxes25:14 Cango Exits Auto Business30:40 Cry Corner-LN a failure?

Welcome to The Mining Pod's news roundup! Colin Harper and Matt Kimmel are joined by special guest Ethan Vera, the COO of Luxor, to discuss one of the most electric weeks for bitcoin mining news this year. They break down Hut8's new Trump-affiliated subsidiary American Bitcoin, Galaxy Digital's 15-year, $4.5 billion hosting agreement with CoreWeave, and how the Trump administration's blanket tariffs are bad news for miners and could lead to a 20-30% rise in ASIC miner prices. Plus, they cover Cango's proposal to sell its auto-finance business to a Bitmain-linked entity for $352 million, and for this week's cry corner, why Jack Dorsey thinks Lightning just isn't cutting it. # Notes: - Hash price at pre-election lows of $40/PH/s/day - Hut 8'sTrump-backed American Bitcoin - Galaxy-CoreWeave deal worth $4.5B over 15 years - New tariffs that will impact miners: 36% Thailand, 32% Indonesia, 24% Malaysia -Cango proposes to sell its autofi business for $352 million - Jack Dorsey: "We can do better than Lightning" Timestamps: 00:00 Start 01:50 Difficulty Report 04:58 Trumps enter BTC mining 11:14 Galaxy CoreWeave deal 16:14 Tariffs are taxes 25:14 Cango Exits Auto Business 30:40 Cry Corner-LN a failure?

Lets dig in on what Jack Dorsey said about Bitcoin and what makes it irrelevant.Check out the BitBox02 Hardware Wallet Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.bitbox.swiss/bitcoinmadesimple⁠⁠⁠⁠⁠ use the promo code "bitcoinmadesimple" to get 5% off standard products.BitBox wants to hear from you! Take the survey and help them learn more about what you want in a hardware wallet: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bitbox.typeform.com/to/VF1DNK4

Jack Dorsey, CEO of Block and former CEO of Twitter (Now X), has cautioned that Bitcoin may risk losing relevance if it remains solely a store of value. Speaking during an interview at Presidio Bitcoin, Dorsey emphasized the necessity for Bitcoin to evolve beyond mere “hodling” to ensure its long-term viability, highlighting the importance of enhancing Bitcoin's utility.~This episode is sponsored by Tangem~Tangem ➜ https://bit.ly/TangemPBNUse Code: "PBN" for Additional Discounts!Guest: Paul Sztorc, Founder and CEO · LayerTwo LabsLayerTwo Labs website  ➜ https://layertwolabs.com/00:00 Intro00:17 Sponsor: Tangem01:00 Jack Dorsey on Bitcoin risking irrelevancy02:40 Pauls paper05:45 How long does a Bitcoin transaction currently take?07:03 Bitcoin ETFs09:05 Payments11:20 Tokenized commodities (gold)12:42 What's holding Bitcoin back?14:41 After every BTC is mined?17:40 Nostr vs Bluesky: Can bitcoin handle social media?18:45 Outro#Bitcoin #Ethereum #Crypto~Bitcoin Innovation Dead?

BlueSky was once a research initiative within Jack Dorsey's Twitter aimed at decentralizing the architecture or the platform social media writ large. Today, BlueSky is an  independent platform with remarkable momentum. Following Elon Musk's acquisition of Twitter and subsequent policy shifts, BlueSky has experienced unprecedented growth, expanding from 3 million to 30 million users since February 2024.That “X-odus” of frustrated progressives to BlueSky has perhaps inadvertently shaped public perception of it as "Lib Twitter"—a characterization reinforced by its prominent progressive voices and more restrictive community moderation tools. However, this political framing obscures BlueSky's fundamental innovation: the AT Protocol, which reimagines social media as a decentralized ecosystem rather than a platform controlled by a master algorithm ruled by a CEO.Unlike conventional social networks, BlueSky's architectural philosophy challenges the centralized control model by introducing a "marketplace of algorithms" where users select or create their own content curation systems. Imagine a feed that skews left, one that skews right, or one that avoids politics altogether.This "algorithmic choice" approach could represent the biggest challenge yet to the centralized engagement machines that have dominated—and arguably degraded—our digital discourse. But can Bluesky outgrow its political bubbles and fulfill its techno-utopian promise? Or will it remain just another partisan bunker in our increasingly fragmented online world?Evan and Luke are joined by Jay Graber, CEO of Bluesky. 

Welcome back to Truth, Lies & Work, the award-winning podcast from the HubSpot Podcast Network, hosted by Chartered Occupational Psychologist Leanne Elliott and business owner Al Elliott. Each week we unpack workplace news, explore the psychology behind behaviour at work, and tackle your toughest workplace questions.

Greg Kidd on Fireside with a VC. Greg recently acquired VastBank | Fintech Pioneer | Early Investor: Twitter, Square, Coinbase, Solana | Ex-Ripple (#10) | Built & Scaled First Company to IPO | Co-Founder, GlobaliD | CEO, USBC | Ex Federal Reserve | Former roommate with Jack Dorsey. Greg and I get into a few topics, including all things related to the future of finance, banking, payments, USDC vs USBC, identity being added to crypto payments and transactions, open banking and fair access, democratizing money, 10,000% markups banks take on ACH and wire transfers over the Fed charges, banking without borders, who needs Visa, Mastercard, Amex, Google or Apple to take rent on payments and how to stop this, importance of securitization and tokenization of real assets, risk management in a world of crypto and digitized centralized and decentralized banking and finance.  

Business Brain episode 633 celebrates Twitter Day and discusses Blue Sky, a decentralized social network originally started as a project within Twitter by Jack Dorsey and now run by Jay Graber. The show then moves to AI topics, emphasizing that people won't be replaced by AI but by people who […] The post FridAI – GPT vs. Perplexity, Zoom AI and Bluesky – Business Brain 633 appeared first on Business Brain - The Entrepreneurs' Podcast.

Tech Shifts: Google Assistant Shutdown, Jack Dorsey's Goose, and Major Acquisitions In this episode, host Jim Love discusses major updates in the tech world, including Google's decision to shut down Google Assistant and replace it with the advanced AI assistant Gemini, which has already begun its rollout. Jack Dorsey announces Goose, an open-source AI assistant gaining popularity among developers for its coding and productivity features. Google's parent company Alphabet makes a significant move by acquiring cybersecurity firm Wiz for $32 billion to enhance cloud security. Meta's AI model Lama surpasses 1 billion downloads, signaling its growing influence in AI applications. Additionally, Chinese EV manufacturer BYD unveils a rapid charging system, potentially outpacing Tesla in charging efficiency. The episode wraps up with a note of gratitude to supporters of the Tech podcast. 00:00 Introduction and Headlines 00:27 Google Assistant's Transition to Gemini 01:38 Jack Dorsey's Open Source AI Assistant Goose 03:56 Google Acquires Cybersecurity Firm Wiz 05:01 Meta's Llama Reaches 1 Billion Downloads 06:56 BYD's Groundbreaking Charging System 08:04 Conclusion and Thank You

Want to sharpen your focus, build unbreakable discipline, and tap into peak mental performance?  In this episode, we break down how fasting rewires your brain for productivity, boosts BDNF for sharper thinking, and trains your willpower like a Navy SEAL. Hear how Jack Dorsey, Georges St-Pierre, and monks use fasting to gain an edge—and learn how you can do the same. Plus, get a simple fasting protocol to unlock mental clarity and self-control starting today!

Linktree: https://linktr.ee/AnalyticIn this segment of Notorious Mass Effect, host Analytic Dreamz dives into the high-stakes legal battle of Patel v. Dorsey. Shawn Carter, aka Jay-Z, faces a shareholder lawsuit alongside Block, Inc. co-founder Jack Dorsey. Filed on February 5, 2025, in California, the suit alleges Cash App enabled illegal activities like money laundering and terrorism financing due to board negligence. Analytic Dreamz unpacks the timeline, from federal probes to multimillion-dollar settlements, exploring how this case could impact Jay-Z's legacy and the future of payment apps.Support this podcast at — https://redcircle.com/analytic-dreamz-notorious-mass-effect/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

We are working with Amplify on the 2025 State of AI Engineering Survey to be presented at the AIE World's Fair in SF! Join the survey to shape the future of AI Eng!We first met Snipd over a year ago, and were immediately impressed by the design, but were doubtful about the behavior of snipping as the title behavior:Podcast apps are enormously sticky - Spotify spent almost $1b in podcast acquisitions and exclusive content just to get an 8% bump in market share among normies.However, after a disappointing Overcast 2.0 rewrite with no AI features in the last 3 years, I finally bit the bullet and switched to Snipd. It's 2025, your podcast app should be able to let you search transcripts of your podcasts. Snipd is the best implementation of this so far.And yet they keep shipping:What impressed us wasn't just how this tiny team of 4 was able to bootstrap a consumer AI app against massive titans and do so well; but also how seriously they think about learning through podcasts and improving retention of knowledge over time, aka “Duolingo for podcasts”. As an educational AI podcast, that's a mission we can get behind.Full Video PodFind us on YouTube! This was the first pod we've ever shot outdoors!Show Notes* How does Shazam work?* Flutter/FlutterFlow* wav2vec paper* Perplexity Online LLM* Google Search Grounding* Comparing Snipd transcription with our Bee episode* NIPS 2017 Flo Rida* Gustav Söderström - Background AudioTimestamps* [00:00:03] Takeaways from AI Engineer NYC* [00:00:17] Weather in New York.* [00:00:26] Swyx and Snipd.* [00:01:01] Kevin's AI summit experience.* [00:01:31] Zurich and AI.* [00:03:25] SigLIP authors join OpenAI.* [00:03:39] Zurich is very costly.* [00:04:06] The Snipd origin story.* [00:05:24] Introduction to machine learning.* [00:09:28] Snipd and user knowledge extraction.* [00:13:48] App's tech stack, Flutter, Python.* [00:15:11] How speakers are identified.* [00:18:29] The concept of "backgroundable" video.* [00:29:05] Voice cloning technology.* [00:31:03] Using AI agents.* [00:34:32] Snipd's future is multi-modal AI.* [00:36:37] Snipd and existing user behaviour.* [00:42:10] The app, summary, and timestamps.* [00:55:25] The future of AI and podcasting.* [1:14:55] Voice AITranscriptswyx [00:00:03]: Hey, I'm here in New York with Kevin Ben-Smith of Snipd. Welcome.Kevin [00:00:07]: Hi. Hi. Amazing to be here.swyx [00:00:09]: Yeah. This is our first ever, I think, outdoors podcast recording.Kevin [00:00:14]: It's quite a location for the first time, I have to say.swyx [00:00:18]: I was actually unsure because, you know, it's cold. It's like, I checked the temperature. It's like kind of one degree Celsius, but it's not that bad with the sun. No, it's quite nice. Yeah. Especially with our beautiful tea. With the tea. Yeah. Perfect. We're going to talk about Snips. I'm a Snips user. I'm a Snips user. I had to basically, you know, apart from Twitter, it's like the number one use app on my phone. Nice. When I wake up in the morning, I open Snips and I, you know, see what's new. And I think in terms of time spent or usage on my phone, I think it's number one or number two. Nice. Nice. So I really had to talk about it also because I think people interested in AI want to think about like, how can we, we're an AI podcast, we have to talk about the AI podcast app. But before we get there, we just finished. We just finished the AI Engineer Summit and you came for the two days. How was it?Kevin [00:01:07]: It was quite incredible. I mean, for me, the most valuable was just being in the same room with like-minded people who are building the future and who are seeing the future. You know, especially when it comes to AI agents, it's so often I have conversations with friends who are not in the AI world. And it's like so quickly it happens that you, it sounds like you're talking in science fiction. And it's just crazy talk. It was, you know, it's so refreshing to talk with so many other people who already see these things and yeah, be inspired then by them and not always feel like, like, okay, I think I'm just crazy. And like, this will never happen. It really is happening. And for me, it was very valuable. So day two, more relevant, more relevant for you than day one. Yeah. Day two. So day two was the engineering track. Yeah. That was definitely the most valuable for me. Like also as a producer. Practitioner myself, especially there were one or two talks that had to do with voice AI and AI agents with voice. Okay. So that was quite fascinating. Also spoke with the speakers afterwards. Yeah. And yeah, they were also very open and, and, you know, this, this sharing attitudes that's, I think in general, quite prevalent in the AI community. I also learned a lot, like really practical things that I can now take away with me. Yeah.swyx [00:02:25]: I mean, on my side, I, I think I watched only like half of the talks. Cause I was running around and I think people saw me like towards the end, I was kind of collapsing. I was on the floor, like, uh, towards the end because I, I needed to get, to get a rest, but yeah, I'm excited to watch the voice AI talks myself.Kevin [00:02:43]: Yeah. Yeah. Do that. And I mean, from my side, thanks a lot for organizing this conference for bringing everyone together. Do you have anything like this in Switzerland? The short answer is no. Um, I mean, I have to say the AI community in, especially Zurich, where. Yeah. Where we're, where we're based. Yeah. It is quite good. And it's growing, uh, especially driven by ETH, the, the technical university there and all of the big companies, they have AI teams there. Google, like Google has the biggest tech hub outside of the U S in Zurich. Yeah. Facebook is doing a lot in reality labs. Uh, Apple has a secret AI team, open AI and then SwapBit just announced that they're coming to Zurich. Yeah. Um, so there's a lot happening. Yeah.swyx [00:03:23]: So, yeah, uh, I think the most recent notable move, I think the entire vision team from Google. Uh, Lucas buyer, um, and, and all the other authors of Siglip left Google to join open AI, which I thought was like, it's like a big move for a whole team to move all at once at the same time. So I've been to Zurich and it just feels expensive. Like it's a great city. Yeah. It's great university, but I don't see it as like a business hub. Is it a business hub? I guess it is. Right.Kevin [00:03:51]: Like it's kind of, well, historically it's, uh, it's a finance hub, finance hub. Yeah. I mean, there are some, some large banks there, right? Especially UBS, uh, the, the largest wealth manager in the world, but it's really becoming more of a tech hub now with all of the big, uh, tech companies there.swyx [00:04:08]: I guess. Yeah. Yeah. And, but we, and research wise, it's all ETH. Yeah. There's some other things. Yeah. Yeah. Yeah.Kevin [00:04:13]: It's all driven by ETH. And then, uh, it's sister university EPFL, which is in Lausanne. Okay. Um, which they're also doing a lot, but, uh, it's, it's, it's really ETH. Uh, and otherwise, no, I mean, it's a beautiful, really beautiful city. I can recommend. To anyone. To come, uh, visit Zurich, uh, uh, let me know, happy to show you around and of course, you know, you, you have the nature so close, you have the mountains so close, you have so, so beautiful lakes. Yeah. Um, I think that's what makes it such a livable city. Yeah.swyx [00:04:42]: Um, and the cost is not, it's not cheap, but I mean, we're in New York city right now and, uh, I don't know, I paid $8 for a coffee this morning, so, uh, the coffee is cheaper in Zurich than the New York city. Okay. Okay. Let's talk about Snipt. What is Snipt and, you know, then we'll talk about your origin story, but I just, let's, let's get a crisp, what is Snipt? Yeah.Kevin [00:05:03]: I always see two definitions of Snipt, so I'll give you one really simple, straightforward one, and then a second more nuanced, um, which I think will be valuable for the rest of our conversation. So the most simple one is just to say, look, we're an AI powered podcast app. So if you listen to podcasts, we're now providing this AI enhanced experience. But if you look at the more nuanced, uh, podcast. Uh, perspective, it's actually, we, we've have a very big focus on people who like your audience who listened to podcasts to learn something new. Like your audience, you want, they want to learn about AI, what's happening, what's, what's, what's the latest research, what's going on. And we want to provide a, a spoken audio platform where you can do that most effectively. And AI is basically the way that we can achieve that. Yeah.swyx [00:05:53]: Means to an end. Yeah, exactly. When you started. Was it always meant to be AI or is it, was it more about the social sharing?Kevin [00:05:59]: So the first version that we ever released was like three and a half years ago. Okay. Yeah. So this was before ChatGPT. Before Whisper. Yeah. Before Whisper. Yeah. So I think a lot of the features that we now have in the app, they weren't really possible yet back then. But we already from the beginning, we always had the focus on knowledge. That's the reason why, you know, we in our team, why we listen to podcasts, but we did have a bit of a different approach. Like the idea in the very beginning was, so the name is Snips and you can create these, what we call Snips, which is basically a small snippet, like a clip from a, from a podcast. And we did envision sort of like a, like a social TikTok platform where some people would listen to full episodes and they would snip certain, like the best parts of it. And they would post that in a feed and other users would consume this feed of Snips. And use that as a discovery tool or just as a means to an end. And yeah, so you would have both people who create Snips and people who listen to Snips. So our big hypothesis in the beginning was, you know, it will be easy to get people to listen to these Snips, but super difficult to actually get them to create them. So we focused a lot of, a lot of our effort on making it as seamless and easy as possible to create a Snip. Yeah.swyx [00:07:17]: It's similar to TikTok. You need CapCut for there to be videos on TikTok. Exactly.Kevin [00:07:23]: And so for, for Snips, basically whenever you hear an amazing insight, a great moment, you can just triple tap your headphones. And our AI actually then saves the moment that you just listened to and summarizes it to create a note. And this is then basically a Snip. So yeah, we built, we built all of this, launched it. And what we found out was basically the exact opposite. So we saw that people use the Snips to discover podcasts, but they really, you know, they don't. You know, really love listening to long form podcasts, but they were creating Snips like crazy. And this was, this was definitely one of these aha moments when we realized like, hey, we should be really doubling down on the knowledge of learning of, yeah, helping you learn most effectively and helping you capture the knowledge that you listen to and actually do something with it. Because this is in general, you know, we, we live in this world where there's so much content and we consume and consume and consume. And it's so easy to just at the end of the podcast. You just start listening to the next podcast. And five minutes later, you've forgotten everything. 90%, 99% of what you've actually just learned. Yeah.swyx [00:08:31]: You don't know this, but, and most people don't know this, but this is my fourth podcast. My third podcast was a personal mixtape podcast where I Snipped manually sections of podcasts that I liked and added my own commentary on top of them and published them as small episodes. Nice. So those would be maybe five to 10 minute Snips. Yeah. And then I added something that I thought was a good story or like a good insight. And then I added my own commentary and published it as a separate podcast. It's cool. Is that still live? It's still live, but it's not active, but you can go back and find it. If you're, if, if you're curious enough, you'll see it. Nice. Yeah. You have to show me later. It was so manual because basically what my process would be, I hear something interesting. I note down the timestamp and I note down the URL of the podcast. I used to use Overcast. So it would just link to the Overcast page. And then. Put in my note taking app, go home. Whenever I feel like publishing, I will take one of those things and then download the MP3, clip out the MP3 and record my intro, outro and then publish it as a, as a podcast. But now Snips, I mean, I can just kind of double click or triple tap.Kevin [00:09:39]: I mean, those are very similar stories to what we hear from our users. You know, it's, it's normal that you're doing, you're doing something else while you're listening to a podcast. Yeah. A lot of our users, they're driving, they're working out, walking their dog. So in those moments when you hear something amazing, it's difficult to just write them down or, you know, you have to take out your phone. Some people take a screenshot, write down a timestamp, and then later on you have to go back and try to find it again. Of course you can't find it anymore because there's no search. There's no command F. And, um, these, these were all of the issues that, that, that we encountered also ourselves as users. And given that our background was in AI, we realized like, wait, hey, this is. This should not be the case. Like podcast apps today, they're still, they're basically repurposed music players, but we actually look at podcasts as one of the largest sources of knowledge in the world. And once you have that different angle of looking at it together with everything that AI is now enabling, you realize like, hey, this is not the way that we, that podcast apps should be. Yeah.swyx [00:10:41]: Yeah. I agree. You mentioned something that you said your background is in AI. Well, first of all, who's the team and what do you mean your background is in AI?Kevin [00:10:48]: Those are two very different things. I'm going to ask some questions. Yeah. Um, maybe starting with, with my backstory. Yeah. My backstory actually goes back, like, let's say 12 years ago or something like that. I moved to Zurich to study at ETH and actually I studied something completely different. I studied mathematics and economics basically with this specialization for quant finance. Same. Okay. Wow. All right. So yeah. And then as you know, all of these mathematical models for, um, asset pricing, derivative pricing, quantitative trading. And for me, the thing that, that fascinates me the most was the mathematical modeling behind it. Uh, mathematics, uh, statistics, but I was never really that passionate about the finance side of things.swyx [00:11:32]: Oh really? Oh, okay. Yeah. I mean, we're different there.Kevin [00:11:36]: I mean, one just, let's say symptom that I noticed now, like, like looking back during that time. Yeah. I think I never read an academic paper about the subject in my free time. And then it was towards the end of my studies. I was already working for a big bank. One of my best friends, he comes to me and says, Hey, I just took this course. You have to, you have to do this. You have to take this lecture. Okay. And I'm like, what, what, what is it about? It's called machine learning and I'm like, what, what, what kind of stupid name is that? Uh, so you sent me the slides and like over a weekend I went through all of the slides and I just, I just knew like freaking hell. Like this is it. I'm, I'm in love. Wow. Yeah. Okay. And that was then over the course of the next, I think like 12 months, I just really got into it. Started reading all about it, like reading blog posts, starting building my own models.swyx [00:12:26]: Was this course by a famous person, famous university? Was it like the Andrew Wayne Coursera thing? No.Kevin [00:12:31]: So this was a ETH course. So a professor at ETH. Did he teach in English by the way? Yeah. Okay.swyx [00:12:37]: So these slides are somewhere available. Yeah. Definitely. I mean, now they're quite outdated. Yeah. Sure. Well, I think, you know, reflecting on the finance thing for a bit. So I, I was, used to be a trader, uh, sell side and buy side. I was options trader first and then I was more like a quantitative hedge fund analyst. We never really use machine learning. It was more like a little bit of statistical modeling, but really like you, you fit, you know, your regression.Kevin [00:13:03]: No, I mean, that's, that's what it is. And, uh, or you, you solve partial differential equations and have then numerical methods to, to, to solve these. That's, that's for you. That's your degree. And that's, that's not really what you do at work. Right. Unless, well, I don't know what you do at work. In my job. No, no, we weren't solving the partial differential. Yeah.swyx [00:13:18]: You learn all this in school and then you don't use it.Kevin [00:13:20]: I mean, we, we, well, let's put it like that. Um, in some things, yeah, I mean, I did code algorithms that would do it, but it was basically like, it was the most basic algorithms and then you just like slightly improve them a little bit. Like you just tweak them here and there. Yeah. It wasn't like starting from scratch, like, Oh, here's this new partial differential equation. How do we know?swyx [00:13:43]: Yeah. Yeah. I mean, that's, that's real life, right? Most, most of it's kind of boring or you're, you're using established things because they're established because, uh, they tackle the most important topics. Um, yeah. Portfolio management was more interesting for me. Um, and, uh, we, we were sort of the first to combine like social data with, with quantitative trading. And I think, uh, I think now it's very common, but, um, yeah. Anyway, then you, you went, you went deep on machine learning and then what? You quit your job? Yeah. Yeah. Wow.Kevin [00:14:12]: I quit my job because, uh, um, I mean, I started using it at the bank as well. Like try, like, you know, I like desperately tried to find any kind of excuse to like use it here or there, but it just was clear to me, like, no, if I want to do this, um, like I just have to like make a real cut. So I quit my job and joined an early stage, uh, tech startup in Zurich where then built up the AI team over five years. Wow. Yeah. So yeah, we built various machine learning, uh, things for, for banks from like models for, for sales teams to identify which clients like which product to sell to them and with what reasons all the way to, we did a lot, a lot with bank transactions. One of the actually most fun projects for me was we had an, an NLP model that would take the booking text of a transaction, like a credit card transaction and pretty fired. Yeah. Because it had all of these, you know, like numbers in there and abbreviations and whatnot. And sometimes you look at it like, what, what is this? And it was just, you know, it would just change it to, I don't know, CVS. Yeah.swyx [00:15:15]: Yeah. But I mean, would you have hallucinations?Kevin [00:15:17]: No, no, no. The way that everything was set up, it wasn't like, it wasn't yet fully end to end generative, uh, neural network as what you would use today. Okay.swyx [00:15:30]: Awesome. And then when did you go like full time on Snips? Yeah.Kevin [00:15:33]: So basically that was, that was afterwards. I mean, how that started was the friend of mine who got me into machine learning, uh, him and I, uh, like he also got me interested into startups. He's had a big impact on my life. And the two of us were just a jam on, on like ideas for startups every now and then. And his background was also in AI data science. And we had a couple of ideas, but given that we were working full times, we were thinking about, uh, so we participated in Hack Zurich. That's, uh, Europe's biggest hackathon, um, or at least was at the time. And we said, Hey, this is just a weekend. Let's just try out an idea, like hack something together and see how it works. And the idea was that we'd be able to search through podcast episodes, like within a podcast. Yeah. So we did that. Long story short, uh, we managed to do it like to build something that we realized, Hey, this actually works. You can, you can find things again in podcasts. We had like a natural language search and we pitched it on stage. And we actually won the hackathon, which was cool. I mean, we, we also, I think we had a good, um, like a good, good pitch or a good example. So we, we used the famous Joe Rogan episode with Elon Musk where Elon Musk smokes a joint. Okay. Um, it's like a two and a half hour episode. So we were on stage and then we just searched for like smoking weed and it would find that exact moment. It will play it. And it just like, come on with Elon Musk, just like smoking. Oh, so it was video as well? No, it was actually completely based on audio. But we did have the video for the presentation. Yeah. Which had a, had of course an amazing effect. Yeah. Like this gave us a lot of activation energy, but it wasn't actually about winning the hackathon. Yeah. But the interesting thing that happened was after we pitched on stage, several of the other participants, like a lot of them came up to us and started saying like, Hey, can I use this? Like I have this issue. And like some also came up and told us about other problems that they have, like very adjacent to this with a podcast. Where's like, like this. Like, could, could I use this for that as well? And that was basically the, the moment where I realized, Hey, it's actually not just us who are having these issues with, with podcasts and getting to the, making the most out of this knowledge. Yeah. The other people. Yeah. That was now, I guess like four years ago or something like that. And then, yeah, we decided to quit our jobs and start, start this whole snip thing. Yeah. How big is the team now? We're just four people. Yeah. Just four people. Yeah. Like four. We're all technical. Yeah. Basically two on the, the backend side. So one of my co-founders is this person who got me into machine learning and startups. And we won the hackathon together. So we have two people for the backend side with the AI and all of the other backend things. And two for the front end side, building the app.swyx [00:18:18]: Which is mostly Android and iOS. Yeah.Kevin [00:18:21]: It's iOS and Android. We also have a watch app for, for Apple, but yeah, it's mostly iOS. Yeah.swyx [00:18:27]: The watch thing, it was very funny because in the, in the Latent Space discord, you know, most of us have been slowly adopting snips. You came to me like a year ago and you introduced snip to me. I was like, I don't know. I'm, you know, I'm very sticky to overcast and then slowly we switch. Why watch?Kevin [00:18:43]: So it goes back to a lot of our users, they do something else while, while listening to a podcast, right? Yeah. And one of the, us giving them the ability to then capture this knowledge, even though they're doing something else at the same time is one of the killer features. Yeah. Maybe I can actually, maybe at some point I should maybe give a bit more of an overview of what the, all of the features that we have. Sure. So this is one of the killer features and for one big use case that people use this for is for running. Yeah. So if you're a big runner, a big jogger or cycling, like really, really cycling competitively and a lot of the people, they don't want to take their phone with them when they go running. So you load everything onto the watch. So you can download episodes. I mean, if you, if you have an Apple watch that has internet access, like with a SIM card, you can also directly stream. That's also possible. Yeah. So of course it's a, it's basically very limited to just listening and snipping. And then you can see all of your snips later on your phone. Let me tell you this error I just got.swyx [00:19:47]: Error playing episode. Substack, the host of this podcast, does not allow this podcast to be played on an Apple watch. Yeah.Kevin [00:19:52]: That's a very beautiful thing. So we found out that all of the podcasts hosted on Substack, you cannot play them on an Apple watch. Why is this restriction? What? Like, don't ask me. We try to reach out to Substack. We try to reach out to some of the bigger podcasters who are hosting the podcast on Substack to also let them know. Substack doesn't seem to care. This is not specific to our app. You can also check out the Apple podcast app. Yeah. It's the same problem. It's just that we actually have identified it. And we tell the user what's going on.swyx [00:20:25]: I would say we host our podcast on Substack, but they're not very serious about their podcasting tools. I've told them before, I've been very upfront with them. So I don't feel like I'm shitting on them in any way. And it's kind of sad because otherwise it's a perfect creative platform. But the way that they treat podcasting as an afterthought, I think it's really disappointing.Kevin [00:20:45]: Maybe given that you mentioned all these features, maybe I can give a bit of a better overview of the features that we have. Let's do that. Let's do that. So I think we're mostly in our minds. Maybe for some of the listeners.swyx [00:20:55]: I mean, I'll tell you my version. Yeah. They can correct me, right? So first of all, I think the main job is for it to be a podcast listening app. It should be basically a complete superset of what you normally get on Overcast or Apple Podcasts or anything like that. You pull your show list from ListenNotes. How do you find shows? You've got to type in anything and you find them, right?Kevin [00:21:18]: Yeah. We have a search engine that is powered by ListenNotes. Yeah. But I mean, in the meantime, we have a huge database of like 99% of all podcasts out there ourselves. Yeah.swyx [00:21:27]: What I noticed, the default experience is you do not auto-download shows. And that's one very big difference for you guys versus other apps, where like, you know, if I'm subscribed to a thing, it auto-downloads and I already have the MP3 downloaded overnight. For me, I have to actively put it onto my queue, then it auto-downloads. And actually, I initially didn't like that. I think I maybe told you that I was like, oh, it's like a feature that I don't like. Like, because it means that I have to choose to listen to it in order to download and not to... It's like opt-in. There's a difference between opt-in and opt-out. So I opt-in to every episode that I listen to. And then, like, you know, you open it and depends on whether or not you have the AI stuff enabled. But the default experience is no AI stuff enabled. You can listen to it. You can see the snips, the number of snips and where people snip during the episode, which roughly correlates to interest level. And obviously, you can snip there. I think that's the default experience. I think snipping is really cool. Like, I use it to share a lot on Discord. I think we have tons and tons of just people sharing snips and stuff. Tweeting stuff is also like a nice, pleasant experience. But like the real features come when you actually turn on the AI stuff. And so the reason I got snipped, because I got fed up with Overcast not implementing any AI features at all. Instead, they spent two years rewriting their app to be a little bit faster. And I'm like, like, it's 2025. I should have a podcast that has transcripts that I can search. Very, very basic thing. Overcast will basically never have it.Kevin [00:22:49]: Yeah, I think that was a good, like, basic overview. Maybe I can add a bit to it with the AI features that we have. So one thing that we do every time a new podcast comes out, we transcribe the episode. We do speaker diarization. We identify the speaker names. Each guest, we extract a mini bio of the guest, try to find a picture of the guest online, add it. We break the podcast down into chapters, as in AI generated chapters. That one. That one's very handy. With a quick description per title and quick description per each chapter. We identify all books that get mentioned on a podcast. You can tell I don't use that one. It depends on the podcast. There are some podcasts where the guests often recommend like an amazing book. So later on, you can you can find that again.swyx [00:23:42]: So you literally search for the word book or I just read blah, blah, blah.Kevin [00:23:46]: No, I mean, it's all LLM based. Yeah. So basically, we have we have an LLM that goes through the entire transcript and identifies if a user mentions a book, then we use perplexity API together with various other LLM orchestration to go out there on the Internet, find everything that there is to know about the book, find the cover, find who or what the author is, get a quick description of it for the author. We then check on which other episodes the author appeared on.swyx [00:24:15]: Yeah, that is killer.Kevin [00:24:17]: Because that for me, if. If there's an interesting book, the first thing I do is I actually listen to a podcast episode with a with a writer because he usually gives a really great overview already on a podcast.swyx [00:24:28]: Sometimes the podcast is with the person as a guest. Sometimes his podcast is about the person without him there. Do you pick up both?Kevin [00:24:37]: So, yes, we pick up both in like our latest models. But actually what we show you in the app, the goal is to currently only show you the guest to separate that. In the future, we want to show the other things more.swyx [00:24:47]: For what it's worth, I don't mind. Yeah, I don't think like if I like if I like somebody, I'll just learn about them regardless of whether they're there or not.Kevin [00:24:55]: Yeah, I mean, yes and no. We we we have seen there are some personalities where this can break down. So, for example, the first version that we released with this feature, it picked up much more often a person, even if it was not a guest. Yeah. For example, the best examples for me is Sam Altman and Elon Musk. Like they're just mentioned on every second podcast and it has like they're not on there. And if you're interested in it, you can go to Elon Musk. And actually like learning from them. Yeah, I see. And yeah, we updated our our algorithms, improved that a lot. And now it's gotten much better to only pick it up if they're a guest. And yeah, so this this is maybe to come back to the features, two more important features like we have the ability to chat with an episode. Yes. Of course, you can do the old style of searching through a transcript with a keyword search. But I think for me, this is this is how you used to do search and extracting knowledge in the in the past. Old school. And the A.I. Web. Way is is basically an LLM. So you can ask the LLM, hey, when do they talk about topic X? If you're interested in only a certain part of the episode, you can ask them for four to give a quick overview of the episode. Key takeaways afterwards also to create a note for you. So this is really like very open, open ended. And yeah. And then finally, the snipping feature that we mentioned just to reiterate. Yeah. I mean, here the the feature is that whenever you hear an amazing idea, you can trip. It's up your headphones or click a button in the app and the A.I. summarizes the insight you just heard and saves that together with the original transcript and audio in your knowledge library. I also noticed that you you skip dynamic content. So dynamic content, we do not skip it automatically. Oh, sorry. You detect. But we detect it. Yeah. I mean, that's one of the thing that most people don't don't actually know that like the way that ads get inserted into podcasts or into most podcasts is actually that every time you listen. To a podcast, you actually get access to a different audio file and on the server, a different ad is inserted into the MP3 file automatically. Yeah. Based on IP. Exactly. And that's what that means is if we transcribe an episode and have a transcript with timestamps like words, word specific timestamps, if you suddenly get a different audio file, like the whole time says I messed up and that's like a huge issue. And for that, we actually had to build another algorithm that would dynamically on the floor. I re sync the audio that you're listening to the transcript that we have. Yeah. Which is a fascinating problem in and of itself.swyx [00:27:24]: You sync by matching up the sound waves? Or like, or do you sync by matching up words like you basically do partial transcription?Kevin [00:27:33]: We are not matching up words. It's happening on the basically a bytes level matching. Yeah. Okay.swyx [00:27:40]: It relies on this. It relies on the exact match at some point.Kevin [00:27:46]: So it's actually. We're actually not doing exact matches, but we're doing fuzzy matches to identify the moment. It's basically, we basically built Shazam for podcasts. Just as a little side project to solve this issue.swyx [00:28:02]: Actually, fun fact, apparently the Shazam algorithm is open. They published the paper, it's talked about it. I haven't really dived into the paper. I thought it was kind of interesting that basically no one else has built Shazam.Kevin [00:28:16]: Yeah, I mean, well, the one thing is the algorithm. If you now talk about Shazam, the other thing is also having the database behind it and having the user mindset that if they have this problem, they come to you, right?swyx [00:28:29]: Yeah, I'm very interested in the tech stack. There's a big data pipeline. Could you share what is the tech stack?Kevin [00:28:35]: What are the most interesting or challenging pieces of it? So the general tech stack is our entire backend is, or 90% of our backend is written in Python. Okay. Hosting everything on Google Cloud Platform. And our front end is written with, well, we're using the Flutter framework. So it's written in Dart and then compiled natively. So we have one code base that handles both Android and iOS. You think that was a good decision? It's something that a lot of people are exploring. So up until now, yes. Okay. Look, it has its pros and cons. Some of the, you know, for example, earlier, I mentioned we have a Apple Watch app. Yeah. I mean, there's no Flutter for that, right? So that you build native. And then of course you have to sort of like sync these things together. I mean, I'm not the front end engineer, so I'm not just relaying this information, but our front end engineers are very happy with it. It's enabled us to be quite fast and be on both platforms from the very beginning. And when I talk with people and they hear that we are using Flutter, usually they think like, ah, it's not performant. It's super junk, janky and everything. And then they use it. They use our app and they're always super surprised. Or if they've already used our app, I couldn't tell them. They're like, what? Yeah. Um, so there is actually a lot that you can do with it.swyx [00:29:51]: The danger, the concern, there's a few concerns, right? One, it's Google. So when were they, when are they going to abandon it? Two, you know, they're optimized for Android first. So iOS is like a second, second thought, or like you can feel that it is not a native iOS app. Uh, but you guys put a lot of care into it. And then maybe three, from my point of view, JavaScript, as a JavaScript guy, React Native was supposed to be there. And I think that it hasn't really fulfilled that dream. Um, maybe Expo is trying to do that, but, um, again, it is not, does not feel as productive as Flutter. And I've, I spent a week on Flutter and dot, and I'm an investor in Flutter flow, which is the local, uh, Flutter, Flutter startup. That's doing very, very well. I think a lot of people are still Flutter skeptics. Yeah. Wait. So are you moving away from Flutter?Kevin [00:30:41]: I don't know. We don't have plans to do that. Yeah.swyx [00:30:43]: You're just saying about that. What? Yeah. Watch out. Okay. Let's go back to the stack.Kevin [00:30:47]: You know, that was just to give you a bit of an overview. I think the more interesting things are, of course, on the AI side. So we, like, as I mentioned earlier, when we started out, it was before chat GPT for the chat GPT moment before there was the GPT 3.5 turbo, uh, API. So in the beginning, we actually were running everything ourselves, open source models, try to fine tune them. They worked. There was us, but let's, let's be honest. They weren't. What was the sort of? Before Whisper, the transcription. Yeah, we were using wave to work like, um, there was a Google one, right? No, it was a Facebook, Facebook one. That was actually one of the papers. Like when that came out for me, that was one of the reasons why I said we, we should try something to start a startup in the audio space. For me, it was a bit like before that I had been following the NLP space, uh, quite closely. And as, as I mentioned earlier, we, we did some stuff at the startup as well, that I was working up. But before, and wave to work was the first paper that I had at least seen where the whole transformer architecture moved over to audio and bit more general way of saying it is like, it was the first time that I saw the transformer architecture being applied to continuous data instead of discrete tokens. Okay. And it worked amazingly. Ah, and like the transformer architecture plus self-supervised learning, like these two things moved over. And then for me, it was like, Hey, this is now going to take off similarly. It's the text space has taken off. And with these two things in place, even if some features that we want to build are not possible yet, they will be possible in the near term, uh, with this, uh, trajectory. So that was a little side, side note. No, it's in the meantime. Yeah. We're using whisper. We're still hosting some of the models ourselves. So for example, the whole transcription speaker diarization pipeline, uh,swyx [00:32:38]: You need it to be as cheap as possible.Kevin [00:32:40]: Yeah, exactly. I mean, we're doing this at scale where we have a lot of audio.swyx [00:32:44]: We're what numbers can you disclose? Like what, what are just to give people an idea because it's a lot. So we have more than a million podcasts that we've already processed when you say a million. So processing is basically, you have some kind of list of podcasts that you will auto process and others where a paying pay member can choose to press the button and transcribe it. Right. Is that the rough idea? Yeah, exactly.Kevin [00:33:08]: Yeah. And if, when you press that button or we also transcribe it. Yeah. So first we do the, we do the transcription. We do the. The, the speaker diarization. So basically you identify speech blocks that belong to the same speaker. This is then all orchestrated within, within LLM to identify which speech speech block belongs to which speaker together with, you know, we identify, as I mentioned earlier, we identify the guest name and the bio. So all of that comes together with an LLM to actually then assign assigned speaker names to, to each block. Yeah. And then most of the rest of the, the pipeline we've now used, we've now migrated to LLM. So we use mainly open AI, Google models, so the Gemini models and the open AI models, and we use some perplexity basically for those things where we need, where we need web search. Yeah. That's something I'm still hoping, especially open AI will also provide us an API. Oh, why? Well, basically for us as a consumer, the more providers there are.swyx [00:34:07]: The more downtime.Kevin [00:34:08]: The more competition and it will lead to better, better results. And, um, lower costs over time. I don't, I don't see perplexity as expensive. If you use the web search, the price is like $5 per a thousand queries. Okay. Which is affordable. But, uh, if you compare that to just a normal LLM call, um, it's, it's, uh, much more expensive. Have you tried Exa? We've, uh, looked into it, but we haven't really tried it. Um, I mean, we, we started with perplexity and, uh, it works, it works well. And if I remember. Correctly, Exa is also a bit more expensive.swyx [00:34:45]: I don't know. I don't know. They seem to focus on the search thing as a search API, whereas perplexity, maybe more consumer-y business that is higher, higher margin. Like I'll put it like perplexity is trying to be a product, Exa is trying to be infrastructure. Yeah. So that, that'll be my distinction there. And then the other thing I will mention is Google has a search grounding feature. Yeah. Which you, which you might want. Yeah.Kevin [00:35:07]: Yeah. We've, uh, we've also tried that out. Um, not as good. So we, we didn't, we didn't go into. Too much detail in like really comparing it, like quality wise, because we actually already had the perplexity one and it, and it's, and it's working. Yeah. Um, I think also there, the price is actually higher than perplexity. Yeah. Really? Yeah.swyx [00:35:26]: Google should cut their prices.Kevin [00:35:29]: Maybe it was the same price. I don't want to say something incorrect, but it wasn't cheaper. It wasn't like compelling. And then, then there was no reason to switch. So, I mean, maybe like in general, like for us, given that we do work with a lot of content, price is actually something that we do look at. Like for us, it's not just about taking the best model for every task, but it's really getting the best, like identifying what kind of intelligence level you need and then getting the best price for that to be able to really scale this and, and provide us, um, yeah, let our users use these features with as many podcasts as possible. Yeah.swyx [00:36:03]: I wanted to double, double click on diarization. Yeah. Uh, it's something that I don't think people do very well. So you know, I'm, I'm a, I'm a B user. I don't have it right now. And, and they were supposed to speak, but they dropped out last minute. Um, but, uh, we've had them on the podcast before and it's not great yet. Do you use just PI Anode, the default stuff, or do you find any tricks for diarization?Kevin [00:36:27]: So we do use the, the open source packages, but we have tweaked it a bit here and there. For example, if you mentioned the BAI guys, I actually listened to the podcast episode was super nice. Thank you. And when you started talking about speaker diarization, and I just have to think about, uh, I don't know.Kevin [00:36:49]: Is it possible? I don't know. I don't know. F**k this. Yeah, no, I don't know.Kevin [00:36:55]: Yeah. We are the best. This is a.swyx [00:37:07]: I don't know. This is the best. I don't know. This is the best. Yeah. Yeah. Yeah. You're doing good.Kevin [00:37:12]: So, so yeah. This is great. This is good. Yeah. No, so that of course helps us. Another thing that helps us is that we know certain structural aspects of the podcast. For example, how often does someone speak? Like if someone, like let's say there's a one hour episode and someone speaks for 30 seconds, that person is most probably not the guest and not the host. It's probably some ad, like some speaker from an ad. So we have like certain of these heuristics that we can use and we leverage to improve things. And in the past, we've also changed the clustering algorithm. So basically how a lot of the speaker diarization works is you basically create an embedding for the speech that's happening. And then you try to somehow cluster these embeddings and then find out this is all one speaker. This is all another speaker. And there we've also tweaked a couple of things where we again used heuristics that we could apply from knowing how podcasts function. And that's also actually why I was feeling so much with the BAI guys, because like all of these heuristics, like for them, it's probably almost impossible to use any heuristics because it can just be any situation, anything.Kevin [00:38:34]: So that's one thing that we do. Yeah, another thing is that we actually combine it with LLM. So the transcript, LLMs and the speaker diarization, like bringing all of these together to recalibrate some of the switching points. Like when does the speaker stop? When does the next one start?swyx [00:38:51]: The LLMs can add errors as well. You know, I wouldn't feel safe using them to be so precise.Kevin [00:38:58]: I mean, at the end of the day, like also just to not give a wrong impression, like the speaker diarization is also not perfect that we're doing, right? I basically don't really notice it.swyx [00:39:08]: Like I use it for search.Kevin [00:39:09]: Yeah, it's not perfect yet, but it's gotten quite good. Like, especially if you compare, if you look at some of the, like if you take a latest episode and you compare it to an episode that came out a year ago, we've improved it quite a bit.swyx [00:39:23]: Well, it's beautifully presented. Oh, I love that I can click on the transcript and it goes to the timestamp. So simple, but you know, it should exist. Yeah, I agree. I agree. So this, I'm loading a two hour episode of Detect Me Right Home, where there's a lot of different guests calling in and you've identified the guest name. And yeah, so these are all LLM based. Yeah, it's really nice.Kevin [00:39:49]: Yeah, like the speaker names.swyx [00:39:50]: I would say that, you know, obviously I'm a power user of all these tools. You have done a better job than Descript. Okay, wow. Descript is so much funding. They had their open AI invested in them and they still suck. So I don't know, like, you know, keep going. You're doing great. Yeah, thanks. Thanks.Kevin [00:40:12]: I mean, I would, I would say that, especially for anyone listening who's interested in building a consumer app with AI, I think the, like, especially if your background is in AI and you love working with AI and doing all of that, I think the most important thing is just to keep reminding yourself of what's actually the job to be done here. Like, what does actually the consumer want? Like, for example, you now were just delighted by the ability to click on this word and it jumps there. Yeah. Like, this is not, this is not rocket science. This is, like, you don't have to be, like, I don't know, Android Kapathi to come up with that and build that, right? And I think that's, that's something that's super important to keep in mind.swyx [00:40:52]: Yeah, yeah. Amazing. I mean, there's so many features, right? It's, it's so packed. There's quotes that you pick up. There's summarization. Oh, by the way, I'm going to use this as my official feature request. I want to customize what, how it's summarized. I want to, I want to have a custom prompt. Yeah. Because your summarization is good, but, you know, I have different preferences, right? Like, you know.Kevin [00:41:14]: So one thing that you can already do today, I completely get your feature request. And I think it just.swyx [00:41:18]: I'm sure people have asked it.Kevin [00:41:19]: I mean, maybe just in general as a, as a, how I see the future, you know, like in the future, I think all, everything will be personalized. Yeah, yeah. Like, not, this is not specific to us. Yeah. And today we're still in a, in a phase where the cost of LLMs, at least if you're working with, like, such long context windows. As us, I mean, there's a lot of tokens in, if you take an entire podcast, so you still have to take that cost into consideration. So if for every single user, we regenerate it entirely, it gets expensive. But in the future, this, you know, cost will continue to go down and then it will just be personalized. So that being said, you can already today, if you go to the player screen. Okay. And open up the chat. Yeah. You can go to the, to the chat. Yes. And just ask for a summary in your style.swyx [00:42:13]: Yeah. Okay. I mean, I, I listen to consume, you know? Yeah. Yeah. I, I've never really used this feature. I don't know. I think that's, that's me being a slow adopter. No, no. I mean, that's. It has, when does the conversation start? Okay.Kevin [00:42:26]: I mean, you can just type anything. I think what you're, what you're describing, I mean, maybe that is also an interesting topic to talk about. Yes. Where, like, basically I told you, like, look, we have this chat. You can just ask for it. Yeah. And this is, this is how ChatGPT works today. But if you're building a consumer app, you have to move beyond the chat box. People do not want to always type out what they want. So your feature request was, even though theoretically it's already possible, what you are actually asking for is, hey, I just want to open up the app and it should just be there in a nicely formatted way. Beautiful way such that I can read it or consume it without any issues. Interesting. And I think that's in general where a lot of the, the. Opportunities lie currently in the market. If you want to build a consumer app, taking the capability and the intelligence, but finding out what the actual user interface is the best way how a user can engage with this intelligence in a natural way.swyx [00:43:24]: Is this something I've been thinking about as kind of like AI that's not in your face? Because right now, you know, we like to say like, oh, use Notion has Notion AI. And we have the little thing there. And there's, or like some other. Any other platform has like the sparkle magic wand emoji, like that's our AI feature. Use this. And it's like really in your face. A lot of people don't like it. You know, it should just kind of become invisible, kind of like an invisible AI.Kevin [00:43:49]: 100%. I mean, the, the way I see it as AI is, is the electricity of, of the future. And like no one, like, like we don't talk about, I don't know, this, this microphone uses electricity, this phone, you don't think about it that way. It's just in there, right? It's not an electricity enabled product. No, it's just a product. Yeah. It will be the same with AI. I mean, now. It's still a, something that you use to market your product. I mean, we do, we do the same, right? Because it's still something that people realize, ah, they're doing something new, but at some point, no, it'll just be a podcast app and it will be normal that it has all of this AI in there.swyx [00:44:24]: I noticed you do something interesting in your chat where you source the timestamps. Yeah. Is that part of this prompt? Is there a separate pipeline that adds source sources?Kevin [00:44:33]: This is, uh, actually part of the prompt. Um, so this is all prompt engine. Engineering, um, uh, you should be able to click on it. Yeah, I clicked on it. Um, this is all prompt engineering with how to provide the, the context, you know, we, because we provide all of the transcript, how to provide the context and then, yeah, I get them all to respond in a correct way with a certain format and then rendering that on the front end. This is one of the examples where I would say it's so easy to create like a quick demo of this. I mean, you can just go to chat to be deep, paste this thing in and say like, yeah, do this. Okay. Like 15 minutes and you're done. Yeah. But getting this to like then production level that it actually works 99% of the time. Okay. This is then where, where the difference lies. Yeah. So, um, for this specific feature, like we actually also have like countless regexes that they're just there to correct certain things that the LLM is doing because it doesn't always adhere to the format correctly. And then it looks super ugly on the front end. So yeah, we have certain regexes that correct that. And maybe you'd ask like, why don't you use an LLM for that? Because that's sort of the, again, the AI native way, like who uses regexes anymore. But with the chat for user experience, it's very important that you have the streaming because otherwise you need to wait so long until your message has arrived. So we're streaming live the, like, just like ChatGPT, right? You get the answer and it's streaming the text. So if you're streaming the text and something is like incorrect. It's currently not easy to just like pipe, like stream this into another stream, stream this into another stream and get the stream back, which corrects it, that would be amazing. I don't know, maybe you can answer that. Do you know of any?swyx [00:46:19]: There's no API that does this. Yeah. Like you cannot stream in. If you own the models, you can, uh, you know, whatever token sequence has, has been emitted, start loading that into the next one. If you fully own the models, uh, I don't, it's probably not worth it. That's what you do. It's better. Yeah. I think. Yeah. Most engineers who are new to AI research and benchmarking actually don't know how much regexing there is that goes on in normal benchmarks. It's just like this ugly list of like a hundred different, you know, matches for some criteria that you're looking for. No, it's very cool. I think it's, it's, it's an example of like real world engineering. Yeah. Do you have a tooling that you're proud of that you've developed for yourself?Kevin [00:47:02]: Is it just a test script or is it, you know? I think it's a bit more, I guess the term that has come up is, uh, vibe coding, uh, vibe coding, some, no, sorry, that's actually something else in this case, but, uh, no, no, yes, um, vibe evals was a term that in one of the talks actually on, on, um, I think it might've been the first, the first or the first day at the conference, someone brought that up. Yeah. Uh, because yeah, a lot of the talks were about evals, right. Which is so important. And yeah, I think for us, it's a bit more vibe. Evals, you know, that's also part of, you know, being a startup, we can take risks, like we can take the cost of maybe sometimes it failing a little bit or being a little bit off and our users know that and they appreciate that in return, like we're moving fast and iterating and building, building amazing things, but you know, a Spotify or something like that, half of our features will probably be in a six month review through legal or I don't know what, uh, before they could sell them out.swyx [00:48:04]: Let's just say Spotify is not very good at podcasting. Um, I have a documented, uh, dislike for, for their podcast features, just overall, really, really well integrated any other like sort of LLM focused engineering challenges or problems that you, that you want to highlight.Kevin [00:48:20]: I think it's not unique to us, but it goes again in the direction of handling the uncertainty of LLMs. So for example, with last year, at the end of the year, we did sort of a snipped wrapped. And one of the things we thought it would be fun to, just to do something with, uh, with an LLM and something with the snips that, that a user has. And, uh, three, let's say unique LLM features were that we assigned a personality to you based on the, the snips that, that you have. It was, I mean, it was just all, I guess, a bit of a fun, playful way. I'm going to look up mine. I forgot mine already.swyx [00:48:57]: Um, yeah, I don't know whether it's actually still in the, in the, we all took screenshots of it.Kevin [00:49:01]: Ah, we posted it in the, in the discord. And the, the second one, it was, uh, we had a learning scorecard where we identified the topics that you snipped on the most, and you got like a little score for that. And the third one was a, a quote that stood out. And the quote is actually a very good example of where we would run that for user. And most of the time it was an interesting quote, but every now and then it was like a super boring quotes that you think like, like how, like, why did you select that? Like, come on for there. The solution was actually just to say, Hey, give me five. So it extracted five quotes as a candidate, and then we piped it into a different model as a judge, LLM as a judge, and there we use a, um, a much better model because with the, the initial model, again, as, as I mentioned also earlier, we do have to look at the, like the, the costs because it's like, we have so much text that goes into it. So we, there we use a bit more cheaper model, but then the judge can be like a really good model to then just choose one out of five. This is a practical example.swyx [00:50:03]: I can't find it. Bad search in discord. Yeah. Um, so, so you do recommend having a much smarter model as a judge, uh, and that works for you. Yeah. Yeah. Interesting. I think this year I'm very interested in LM as a judge being more developed as a concept, I think for things like, you know, snips, raps, like it's, it's fine. Like, you know, it's, it's, it's, it's entertaining. There's no right answer.Kevin [00:50:29]: I mean, we also have it. Um, we also use the same concept for our books feature where we identify the, the mention. Books. Yeah. Because there it's the same thing, like 90% of the time it, it works perfectly out of the box one shot and every now and then it just, uh, starts identifying books that were not really mentioned or that are not books or made, yeah, starting to make up books. And, uh, they are basically, we have the same thing of like another LLM challenging it. Um, yeah. And actually with the speakers, we do the same now that I think about it. Yeah. Um, so I'm, I think it's a, it's a great technique. Interesting.swyx [00:51:05]: You run a lot of calls.Kevin [00:51:07]: Yeah.swyx [00:51:08]: Okay. You know, you mentioned costs. You move from self hosting a lot of models to the, to the, you know, big lab models, open AI, uh, and Google, uh, non-topic.Kevin [00:51:18]: Um, no, we love Claude. Like in my opinion, Claude is the, the best one when it comes to the way it formulates things. The personality. Yeah. The personality. Okay. I actually really love it. But yeah, the cost is. It's still high.swyx [00:51:36]: So you cannot, you tried Haiku, but you're, you're like, you have to have Sonnet.Kevin [00:51:40]: Uh, like basically we like with Haiku, we haven't experimented too much. We obviously work a lot with 3.5 Sonnet. Uh, also, you know, coding. Yeah. For coding, like in cursor, just in general, also brainstorming. We use it a lot. Um, I think it's a great brainstorm partner, but yeah, with, uh, with, with a lot of things that we've done done, we opted for different models.swyx [00:52:00]: What I'm trying to drive at is how much cheaper can you get if you go from cloud to cloud? Closed models to open models. And maybe it's like 0% cheaper, maybe it's 5% cheaper, or maybe it's like 50% cheaper. Do you have a sense?Kevin [00:52:13]: It's very difficult to, to judge that. I don't really have a sense, but I can, I can give you a couple of thoughts that have gone through our minds over the time, because obviously we do realize like, given that we, we have a couple of tasks where there are just so many tokens going in, um, at some point it will make sense to, to offload some of that. Uh, to an open source model, but going back to like, we're, we're a startup, right? Like we're not an AI lab or whatever, like for us, actually the most important thing is to iterate fast because we need to learn from our users, improve that. And yeah, just this velocity of this, these iterations. And for that, the closed models hosted by open AI, Google is, uh, and swapping, they're just unbeatable because you just, it's just an API call. Yeah. Um, so you don't need to worry about. Yeah. So much complexity behind that. So this is, I would say the biggest reason why we're not doing more in this space, but there are other thoughts, uh, also for the future. Like I see two different, like we basically have two different usage patterns of LLMs where one is this, this pre-processing of a podcast episode, like this initial processing, like the transcription, speaker diarization, chapterization. We do that once. And this, this usage pattern it's, it's quite predictable. Because we know how many podcasts get released when, um, so we can sort of have a certain capacity and we can, we, we're running that 24 seven, it's one big queue running 24 seven.swyx [00:53:44]: What's the queue job runner? Uh, is it a Django, just like the Python one?Kevin [00:53:49]: No, that, that's just our own, like our database and the backend talking to the database, picking up jobs, finding it back. I'm just curious in orchestration and queues. I mean, we, we of course have like, uh, a lot of other orchestration where we're, we're, where we use, uh, the Google pub sub, uh, thing, but okay. So we have this, this, this usage pattern of like very predictable, uh, usage, and we can max out the, the usage. And then there's this other pattern where it's, for example, the snippet where it's like a user, it's a user action that triggers an LLM call and it has to be real time. And there can be moments where it's by usage and there can be moments when there's very little usage for that. There. So that's, that's basically where these LLM API calls are just perfect because you don't need to worry about scaling this up, scaling this down, um, handling, handling these issues. Serverless versus serverful.swyx [00:54:44]: Yeah, exactly. Okay.Kevin [00:54:45]: Like I see them a bit, like I see open AI and all of these other providers, I see them a bit as the, like as the Amazon, sorry, AWS of, of AI. So it's a bit similar how like back before AWS, you would have to have your, your servers and buy new servers or get rid of servers. And then with AWS, it just became so much easier to just ramp stuff up and down. Yeah. And this is like the taking it even, even, uh, to the next level for AI. Yeah.swyx [00:55:18]: I am a big believer in this. Basically it's, you know, intelligence on demand. Yeah. We're probably not using it enough in our daily lives to do things. I should, we should be able to spin up a hundred things at once and go through things and then, you know, stop. And I feel like we're still trying to figure out how to use LLMs in our lives effectively. Yeah. Yeah.Kevin [00:55:38]: 100%. I think that goes back to the whole, like that, that's for me where the big opportunity is for, if you want to do a startup, um, it's not about, but you can let the big labs handleswyx [00:55:48]: the challenge of more intelligence, but, um, it's the... Existing intelligence. How do you integrate? How do you actually incorporate it into your life? AI engineering. Okay, cool. Cool. Cool. Cool. Um, the one, one other thing I wanted to touch on was multimodality in frontier models. Dwarcash had a interesting application of Gemini recently where he just fed raw audio in and got diarized transcription out or timestamps out. And I think that will come. So basically what we're saying here is another wave of transformers eating things because right now models are pretty much single modality things. You know, you have whisper, you have a pipeline and everything. Yeah. You can't just say, Oh, no, no, no, we only fit like the raw, the raw files. Do you think that will be realistic for you? I 100% agree. Okay.Kevin [00:56:38]: Basically everything that we talked about earlier with like the speaker diarization and heuristics and everything, I completely agree. Like in the, in the future that would just be put everything into a big multimodal LLM. Okay. And it will output, uh, everything that you want. Yeah. So I've also experimented with that. Like just... With, with Gemini 2? With Gemini 2.0 Flash. Yeah. Just for fun. Yeah. Yeah. Because the big difference right now is still like the cost difference of doing speaker diarization this way or doing transcription this way is a huge difference to the pipeline that we've built up. Huh. Okay.swyx [00:57:15]: I need to figure out what, what that cost is because in my mind 2.0 Flash is so cheap. Yeah. But maybe not cheap enough for you.Kevin [00:57:23]: Uh, no, I mean, if you compare it to, yeah, whisper and speaker diarization and especially self-hosting it and... Yeah. Yeah. Yeah.swyx [00:57:30]: Yeah.Kevin [00:57:30]: Okay. But we will get there, right? Like this is just a question of time.swyx [00:57:33]: And, um, at some point, as soon as that happens, we'll be the first ones to switch. Yeah. Awesome. Anything else that you're like sort of eyeing on the horizon as like, we are thinking about this feature, we're thinking about incorporating this new functionality of AI into our, into our app? Yeah.Kevin [00:57:50]: I mean, we, there's so many areas that we're thinking about, like our challenge is a bit more... Choosing. Yeah. Choosing. Yeah. So, I mean, I think for me, like looking into like the next couple of years, like the big areas that interest us a lot, basically four areas, like one is content. Um, right now it's, it's podcasts. I mean, you did mention, I think you mentioned like you can also upload audio books and YouTube videos. YouTube. I actually use the YouTube one a fair amount. But in the future, we, we want to also have audio books natively in the app. And, uh, we want to enable AI generated content. Like just think of, take deep research and notebook analysis. Like put these together. That should be, that should be in our app. The second area is discovery. I think in general. Yeah.swyx [00:58:38]: I noticed that you don't have, so you

Is Bluesky the Next Big Thing or Just Another Social Media Experiment?In this episode of Let's Talk Social, we're diving into Bluesky, the decentralized social media platform backed by Twitter's co-founder Jack Dorsey. Is it just a Twitter clone, or could it be a game-changer for businesses in 2025?

Matt and Nic return for another week of news and deals. In this episode:  Figure Markets announced the launch of their YLDS stablecoin, which is the first yield-bearing stablecoin to be approved by and registered with the SEC Crypto exchange Bybit was hacked on Friday for an estimated $1.48 billion worth of ETH in the largest hack in the industry's history n the past week, the SEC dropped lawsuits and investigations related to Coinbase, Robinhood, OpenSea, Uniswap, Gemini, and MetaMask Microstrategy purchased an additional 20,356 BTC last week Crypto exchange OKX pled guilty and agreed to pay $504 million in penalties for anti-money laundering law violations U.S. Treasury Secretary Scott Bessent has appointed Tyler Williams as an advisor on digital asset and blockchain policy During an interview with Bloomberg, Bank of America CEO Brian Moynihan stated that in light of the expected upcoming stablecoin legislation, he expects that Bank of America will "get into that business," and may even launch their own stablecoin Content mentioned in this episode: Jameson Lopp, Jack Dorsey is not Satoshi Nakamoto DeFi Education Fund, Examining the burdens, costs, and failures of the Bank Secrecy Act (BSA), and the potentially disastrous implications of applying the BSA to DeFi.

On this episode of Inside the Firm, the NAHB is claiming that the multifamily market will stabilize at the end of 2025, then will banning gas stations lead to affordable housing, and finally Jack Dorsey reads. Join us as we go back Inside the Firm!

Keith Coleman, the VP of product at Twitter/X, and Jay Baxter, the founding ML engineer, are the minds behind Community Notes. Here they reveal how a small, scrappy team built the most trusted crowdsourced information system on the internet—one that's changing the way we understand truth online. What you'll learn:1. How Community Notes actually works—a deep dive into the groundbreaking algorithm that rewards “bridging agreement” instead of majority rule2. The seemingly crazy yet brilliant way this idea survived multiple CEO changes—from Jack to Parag to Elon3. How this project started with a dumpster fire GIF (literally)—the untold backstory of its early launch4. The secret to running ultra-fast, high-impact product teams—no OKRs, no Jira; just one Google Doc5. What Meta's adoption of Community Notes means for the future of online (mis)information—why this open source system is becoming the industry standard—Brought to you by:• WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs• Productboard—Make products that matter• Wix Studio—The web creation platform built for agencies—Find the transcript at: https://www.lennysnewsletter.com/p/how-x-built-the-best-fact-checking-system-on-the-internet—Where to find Keith Coleman:• X: https://x.com/kcoleman• LinkedIn: https://www.linkedin.com/in/keith-coleman-19b12b46/—Where to find Jay Baxter:• X: https://x.com/_jaybaxter_• LinkedIn: https://www.linkedin.com/in/jaybaxter/• Website: http://jaybaxter.net/—In this episode, we cover:(00:00) Introduction to Community Notes(06:56) How the “bridging-based” algorithm works(13:33) The impact and scale of Community Notes(17:24) Understanding the note publishing threshold(21:32) Challenges and philosophies(26:26) The effect of notes on re-sharing content(29:41) Origin story(35:46) Embracing small teams for big impact(40:23) The thermal project approach(47:47) Algorithm development and internal competitions(50:34) An inside look at how the team operates(58:56) Working with Elon(01:05:30) Launching Birdwatch(01:10:48) The core principles behind Community Notes(01:26:15) Anonymity and pseudonymity in contributions(01:32:17) Sustaining the project through leadership changes(01:37:57) Future directions for Community Notes(01:42:12) Final thoughts and optimism for the future—Referenced:• Community Notes on X: https://x.com/CommunityNotes• Sign up to be a Community Notes contributor: https://communitynotes.x.com/guide/en/contributing/signing-up• The Making of Community Notes: https://asteriskmag.com/issues/08/the-making-of-community-notes• “Readers added a Community Note to this Tweet”: https://x.com/HelpfulNotes/status/1718103364792205704• Note-ranking algorithm: https://communitynotes.x.com/guide/en/under-the-hood/ranking-notes#matrix-factorization• Study: Community Notes on X could be key to curbing misinformation: https://giesbusiness.illinois.edu/news/2024/11/18/study--community-notes-on-x-could-be-key-to-curbing-misinformation• Study Finds X's (Formerly Twitter's) Community Notes Provide Accurate, Credible Answers to Vaccine Misinformation: https://qi.ucsd.edu/study-finds-xs-formerly-twitters-community-notes-provide-accurate-credible-answers-to-vaccine-misinformation/• Did the Roll-Out of Community Notes Reduce Engagement with Misinformation on X/Twitter?: https://dl.acm.org/doi/10.1145/3686967• Kayvon Beykpour on LinkedIn: https://www.linkedin.com/in/kayvz/• Jack Dorsey on X: https://x.com/jack• “Birdwatch gives me the creeps” tweet: https://x.com/elonmusk/status/1589454464611540992• Blake Scholl on LinkedIn: https://www.linkedin.com/in/blakescholl/• Creating Truthtelling Incentives with the Bayesian Truth Serum: https://www.eecs.harvard.edu/cs286r/courses/fall12/papers/DW08.pdf• Asana: https://asana.com/• Spaces: https://blog.x.com/en_us/topics/product/2021/spaces-is-here• Amazon MTurk: https://www.mturk.com/• Community notes on GitHub: https://github.com/twitter/communitynotes• What do I think about Community Notes?: https://vitalik.eth.limo/general/2023/08/16/communitynotes.html• X's community-led approach: tackling inaccurate and misleading information: https://blog.x.com/en_us/topics/company/2023/xs-community-led-approach-tackling-inaccurate-and-misleading-information• Linda Yaccarino on LinkedIn: https://www.linkedin.com/in/lindayaccarino/• Messi-Ronaldo rivalry: https://en.wikipedia.org/wiki/Messi%E2%80%93Ronaldo_rivalry• Supernotes paper: https://arxiv.org/pdf/2411.06116v1—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

In the first official episode of Supply Shock, Jameson Lopp joins the show to explain why Jack Dorsey is NOT Satoshi, threat vectors for Bitcoiners, and security prevention strategies to protect yourself. We also delve into attacker stories, how Jameson protects his own financial and physical security, and more. Enjoy! — Follow Jameson Lopp: https://x.com/lopp Follow Rizzo: https://x.com/pete_rizzo_ Follow Supply Shock: https://twitter.com/SupplyShockBW Follow Blockworks: https://twitter.com/Blockworks_ The Bitcoin Historian Newsletter: https://bitcoinhistorynewsletter.com/ — Join us at Digital Asset Summit 2025 March 18th - 20th. USE CODE SHOCK10 FOR 10% OFF general admission! https://blockworks.co/event/digital-asset-summit-2025-new-york — Bitcoin DeFi is here. Stake, bridge, swap and earn real yield on Core - Bitcoin's consumer chain and staking layer.  Join Ignition and get onchain: https://ignition.coredao.org/?utm_source=blockworks&utm_medium=podcast&utm_campaign=blockworks  Stake your Bitcoin with Core: https://stake.coredao.org/?utm_source=blockworks&utm_medium=podcast&utm_campaign=blockworks Ledger, the global leader in digital asset security, proudly sponsors Supply Shock. As Bitcoin adoption grows, Ledger celebrates 10 years of securing over 20% of the world's crypto. Buy a LEDGER™ device now for true self-custody and peace of mind in securing your Bitcoin. Devices are also available in Bitcoin orange. For every device ordered in BTC Orange, we'll donate $5 to brink.dev. Buy now at Ledger.com. Need liquidity without selling your Bitcoin? For 6+ years, Ledn has been the trusted choice for Bitcoin-backed lending. With transparency, security, and trust at our core, we help you access your BTC's wealth while HODLing. Discover what your Bitcoin can do at ledn.io/borrowing. — Timestamps: (00:00) Introduction (01:01) Is Jack Dorsey Satoshi Nakamoto? (05:50) Debunking the Jack-Satoshi Theory (13:04) Ads (Core, Ledger, Ledn) (14:38) Debunking the Jack-Satoshi Theory (Con't) (31:00) The Threat Vectors for Bitcoiners (31:39) Ads (Core, Ledger, Ledn) (33:44) The Threat Vectors for Bitcoiners (Con't) (37:04) Mitigating Security Risks (49:19) Rapid Fire Questions — Disclaimer: Nothing discussed on Supply Shock should be considered as investment advice. Please always do your own research & speak to a financial advisor before thinking about, thinking about putting your money into these crazy markets.

Foram dias bem agitados no X do bitdov! Taxas baixas na rede Bitcoin, Stablecoins na Lightning, etapa do ciclo de alta do BTC, sorteio de Trezor Freedom Edition, adoção em El Salvador, sobre crédito em um mundo hiperbitcoinizado, o rugpull Libra do presidente da Argentina Javier Milei, mineração solo em hotel, PlanB troca seus bitcoin soberanos por ETF por medo da autocustódia, quanto você teria se junta-se 0,50 centavos de dólar em BTC por dia durante 1 ano, atualizações de emergência de nodes Lightning, sobre o boato de Jack Dorsey ser Satoshi Nakamoto, auditoria das reservas de ouro do Forte Knox, #FreeSamourai, Bitcoin++ em Floripa acontecendo...Para agendar uma CONSULTA PRIVADA com o Dov: https://consultorio.bitcoinheiros.com/Consulta pública: https://ask.arata.se/bitdovPublicações no X que apareceram no vídeo:https://x.com/bitdov/status/1889599071263793593https://x.com/bitdov/status/1892324971529031771https://x.com/bitdov/status/1892094672622731441https://x.com/bitdov/status/1892157429397545080https://x.com/bitdov/status/1892206781549437295https://x.com/bitdov/status/1891890334868607064Extra - A inflação é cruel:https://x.com/bitdov/status/1888993357059211510Gravado no bloco 884558________________APOIE O CANALhttps://bitcoinheiros.com/apoie/⚡ln@pay.bitcoinheiros.com00:00 Introdução Toca do Bitcoin no X00:25 Situação da mempool em Fevereiro de 202506:38 Tether na lightning network utilizando taproot assets09:24 Abra canal lightning com os Bitcoinheiros10:05 Consultas com o Dov no consultorio.bitcoinheiros.com13:30 Otimismo dos Bitcoinheiros verdadeiros16:39 Se fosse fácil todo mundo seria Bitcoinheiro18:05 Concorrência desleal das moedas fiat com o Bitcoin21:35 Bitcoinheiros não tem pressa pro preço do bitcoin subir25:12 Auto custódia de bitcoin da maneira certa26:12 Sorteio de uma Trezor Safe 5 Freedom Edition29:02 Adoção do Bitcoin em El Salvador - Podcast do Lunaticoin30:20 Censura das máquinas de escrever a Turquia 33:27 Como será o crédito com o Bitcoin no futuro?34:39 Avanços tecnológicos são diluídos pela inflação36:55 Incentivos para aprendizagem de outros idiomas38:15 Vídeo Colapso do Bitcoin: Em 10 anos tudo terá acabado38:43 Malucos com shitcoinhagem 41:12 O crédito com Bitcoin 49:25 Banco central Europeu comemorando inflação51:07 Javier Milei e rug pull do token Libra59:10 Mineração de Bitcoin em um Hotel1:03:17 Socialista de Wall Street e perguntas idiotas sobre Bitcoin1:05:49 PlanB desiste de fazer auto custódia de Bitcoin e compra ETF1:18:28 Como PlanB vendeu seus bitcoins sem gerar um evento tributário?1:22:10 Quanto você teria se tivesse comprado 50 cents de bitcoin por dia em 2016?1:25:14 FTX começa pagar clientes que perderam fundos em 2022?1:26:05 Uso de IA para análise de textos1:27:20 Atualizações de segurança do node de Bitcoin1:33:19 Incentivos para postar no NOSTR e X1:35:51 Jack Dorsey é Satoshi?1:39:06 Qual a motivação da narrativa de Jack Dorsey ser Satoshi?1:43:18 Todos somos Satoshi1:45:35 Ouro de Schrodinger do Fort Knox1:53:34 Evento Bitcoin++ em Florianópolis1:53:49 FreeSamourai 1:54:26 Software livre é discurso e não transmissor de dinheiro1:55:45 CoinJoin são transações colaborativas1:56:30 Ashigaru Wallet e Servidor Dojo1:58:11 Software Open Source é imparávelISENÇÃO DE RESPONSABILIDADE:Este conteúdo foi preparado para fins meramente informativos.NÃO é uma recomendação financeira nem de investimento.As opiniões apresentadas são apenas opiniões.Faça sua própria pesquisa.Não nos responsabilizamos por qualquer decisão de investimento que você tomar ou ação que você executar inspirada em nossos vídeos.P.S. para os buscadoresSomos bitcoinheiros, não bitconheiros, nem bitconheros, bitcoinheros, biticonheiros, biticonheros ou biticoinheros.O Dov é bitcoinheiro, não bitconheiro, nem bitconhero, bitcoinhero, biticonheiro, biticonhero ou biticoinhero.É Bitcoin, não Bitcon e nem Biticoin :)

Ce jeudi 27 février, la question de savoir "qui est derrière Bictoin ?", et la mauvaise gestion de la plateforme FTX, ont été abordées par Manuel Valente, directeur scientifique chez Coinhouse, dans Tout pour investir, présenté par Lorraine Goumot, sur BFM Business. Retrouvez l'émission du lundi au vendredi et réécoutez la en podcast.

Today, we're diving into one of the biggest hacks in history – Bybit just got drained for a staggering $1.4 billion. How did it happen, and what does it mean for the industry?But let's pause on that for a second because there is fresh blood on the street after Trump Tarif war threat? Is this a short-term trend?Then – is Jack Dorsey actually Satoshi Nakamoto? The internet is spiraling down the rabbit hole, and we're unpacking the theories.And finally, stay around for some crazy Kayne news….Buckle up – it's a big episode! Let's get into it.

022525 SHORT 18 MIN Jack Dorsey Secret Inventor Of Bitcoin Not So Fast by Kate Dalley

47e6GvjL4in5Zy5vVHMb9PQtGXQAcFvWSCQn2fuwDYZoZRk3oFjefr51WBNDGG9EjF1YDavg7pwGDFSAVWC5K42CBcLLv5U OR DONATE HERE: https://www.monerotalk.live/donate LINKS: TIMESTAMPS (00:00:00) Monerotopia Introduction. (00:02:28) Monerotopia Price Report Segment w/ Bawdyanarchist. (01:06:25) Monerotopia News Segment w/ Tony. (01:11:10) Peter Schiff monero pilled? (01:16:27) Monero mentioned in a Turkish movie. (01:17:45) Monero back on CEXs? No (01:25:52) NK owns the most ETH (01:26:35) Bybit hack. (01:27:55) Apple surrenders in the UK (01:31:58) SEC withdraws its appeal over Defi (01:32:25) Quantum breakthroughs (01:34:44) Lightning network things (01:35:22) Fort Knox live (01:37:35) Jack Dorsey is Satoshi? (01:41:20) Zcash anthem (01:44:10) Monerotopia Viewers on Stage Segment. (02:33:40) Monerotopia Finalization. NEWS SEGMENT LINKS: Monero mentioned in a Turkish movie: https://x.com/undetectedtx/status/1891183354650734824?s=46&t=mVZ0A2C1bwwnAvgawJjlw Jack Dorsey is Satoshi?: https://x.com/matthewsigel/status/1891852538376487327?s=46&t=mVZ0A2C1bwwnAvgawJjlw Peter Schiff monero pilled?: https://x.com/moneromavrick/status/1891909236382118386?s=46&t=mVZ0A2C1bwwnAvgawJjlw Zcash anthem: https://x.com/allismadenew/status/1892040995505578167?s=46&t=mVZ0A2C1bwwnAvgawJjlw Lightning network things: https://x.com/cryptonator1337/status/1892139131213697448?s=46&t=mVZ0A2C1bwwnAvgawJjlw Quantum breakthroughs: https://x.com/satyanadella/status/1892242895094313420?s=46&t=mVZ0A2C1bwwnAvgawJjlw SEC withdraws its appeal over Defi: https://x.com/cointelegraph/status/1892454136567730467?s=46&t=mVZ0A2C1bwwnAvgawJjlw Apple surrenders in the UK: https://x.com/inevitablewest/status/1892959668458156298?s=46 Fort Knox live: https://x.com/elonmusk/status/1892779555548443116?s=46&t=mVZ0A2C1bwwnAvgawJjlw NK owns the most ETH: https://x.com/0xwenmoon/status/1893161253985481000?s=46&t=mVZ0A2C1bwwnAvgawJjlw Monero back on CEXs? No: https://www.reddit.com/r/Monero/s/8BZjsjrkVx SPONSORS: PRICE REPORT: https://exolix.com/ GUEST SEGMENT: https://cakewallet.com & https://monero.com NEWS SEGMENT: https://www.wizardswap.io Don't forget to SUBSCRIBE! The more subscribers, the more we can help Monero grow! XMRtopia TELEGRAM: https://t.me/monerotopia XMRtopia MATRIX: https://matrix.to/#/%23monerotopia%3Amonero.social ODYSEE: https://bit.ly/3bMaFtE WEBSITE: monerotopia.com CONTACT: monerotopia@protonmail.com MASTADON: @Monerotopia@mastodon.social MONERO.TOWN https://monero.town/u/monerotopia Get Social with us: X: https://twitter.com/monerotopia INSTAGRAM: https://www.instagram.com/monerotopia DOUGLAS: https://twitter.com/douglastuman SUNITA: https://twitter.com/sunchakr TUX: https://twitter.com/tuxpizza

There's a new theory that Twitter founder Jack Dorsey is Satoshi Nakamoto. We dive into the crazy (yes, it's truly crazy) rabbithole that is the Dorsey x Nakamoto conspiracy.You're listening to Bitcoin Season 2. Subscribe to the newsletter, trusted by over 7,000 Bitcoiners: https://newsletter.blockspacemedia.comCharlie & Colin break down the conspiracy theory that claims Jack Dorsey is Satoshi Nakamoto. You might be surprised how deep the rabbithole goes and how crazy the connections sound.Notes:• Jack Dorsey's Vietnamese restaurant• Hidden address references in old Bitcoin transactions• Are clues hidden in comic books?Check out our Bitcoin scaling conference! Visit opnext.dev to learn more.Chapters:00:00 Is Jack Dorsey Satoshi?01:14 The bizarre connections begin02:29 Jack's “Satoshi” Shirt05:02 Jack Dorsey was a Cypherpunk09:52 Clues in old vanity addresses19:07 Jack, Bitcoin, and nautical references36:54 Why Jack Dorsey isn't Satoshi-

On the SUPERWOMEN podcast, I'm sitting down with Laurie Segall, the founder of Mostly Human Media and a former senior technology correspondent and editor-at-large at CNN. Throughout her award-winning career, Laurie has investigated the dangers of technology, and has interviewed some of the most powerful figures in Silicon Valley, like Mark Zuckerberg and Jack Dorsey. Laurie had always dreamt of being a journalist and started at the bottom of the newsroom as a CNN intern. Fast-forward several years, and she was leading the organization's tech coverage at one of the most pivotal moments in modern history—the rise of social media. Her groundbreaking reporting has shed light on some of the most terrifying consequences of the digital era, including unregulated A.I. chatbots, tech addiction, revenge pornography, and more. After she spent nearly a decade at CNN, at the top of her game, she left it all behind in 2019 to start her own media company, where her work has continued her push for a safer future. She has also written a memoir, “Special Characters: My Adventures with Tech's Titans and Misfits,” an unflinching look at how she built her career alongside the tech startup nerds turned giants, who have shaped the world as we know it today.In this episode, Laurie shares her best advice for women who feel intimidated by the challenges of starting a business, the YouTube video that inspired her to quit her dream job, and how she plans to take on her latest target: MrDeepFakes.Thank you for listening! Don't forget to order my book, “Fearless: The New Rules for Unlocking Creativity, Courage, and Success.”Follow SUPERWOMEN (@rmsuperwomen) and Chelsea (@cmrh) on Instagram.Support this podcast: https://bit.ly/rmsuperwomen

Welcome to the Alfalfa Podcast

Send us a textMiguel Armaza welcomes back Jackie Reses, CEO and Co-Founder of Lead Bank, a pioneering bank reimagining modern financial infrastructure and fintech partnerships. Jackie previously held leadership roles at Square and Yahoo, and served on the board of Alibaba, working alongside visionaries like Jack Dorsey and Jack Ma.In this episode, we discuss:How Lead Bank achieved instant product-market fit before even acquiring their bank charterWhy banking regulation needs a "first principles" rethinking approach and why the CFPB may need significant reformThe evolution of AI in financial services and why regulators are becoming more open to algorithmic innovationInvaluable leadership lessons from working with Masayoshi Son, Jack Ma, and Jack Dorsey... and lots more!Want more podcast episodes? Join me and follow Fintech Leaders today on Apple, Spotify, or your favorite podcast app for weekly conversations with today's global leaders that will dominate the 21st century in fintech, business, and beyond.Do you prefer a written summary? Check out the Fintech Leaders newsletter and join ~70,000+ readers and listeners worldwide!Miguel Armaza is Co-Founder and General Partner of Gilgamesh Ventures, a seed-stage investment fund focused on fintech in the Americas. He also hosts and writes the Fintech Leaders podcast and newsletter.Miguel on LinkedIn: https://bit.ly/3nKha4ZMiguel on Twitter: https://bit.ly/2Jb5oBcFintech Leaders Newsletter: bit.ly/3jWIp

Self-Perfected Podcast #232 Algorithms, Tirades and Memetic WarfareIn this riveting episode of the Self-Perfected Podcast, we DIVE deep into the influence of algorithms on our daily lives and the potential for change. Inspired by insights from Jack Dorsey, we explore how algorithms might be controlling us more than we realize—and how we can take back control, not just of the algorithm but of our entire lives to make it best for ALL.We also tackle the recent tirades by Ye and the pervasive impact of meme warfare in shaping public opinion and social dynamics. These discussions are not just about understanding the phenomena but actively engaging in changing the system for the better.We are all in this together.In This Episode:Algorithm Control vs. Personal Agency: Analyze the current state of digital algorithms and their profound impact on our choices and lifestyles.Ye's Impact and Memetic Warfare: Dive into the controversies and the strategic use of memes as powerful tools in modern discourse.Call to Action: We are all part of this system, and together, we can initiate meaningful changes.Join us as we unpack these complex topics with critical insights and a forward-thinking approach. If you're ready to challenge the status quo and influence the algorithms that guide our lives, this episode is a must-listen.Subscribe to the Self-Perfected Podcast for more discussions on how we can transform society, one episode at a time.

Scaling an e-commerce brand isn't just about getting more sales—it's about increasing profits without driving up costs and complexity. Many brands hit a wall where growth starts feeling expensive, with ad costs rising and margins shrinking. The challenge is finding ways to optimize operations, build a loyal customer base, and create new revenue streams that don't rely solely on constant customer acquisition. The brands that break through find smarter, more sustainable ways to grow—focusing on retention, pricing strategy, and efficiency instead of just chasing more traffic. Jesse Kay is the founder and CEO of Vyber Media, a performance marketing agency that specializes in helping eight and nine-figure brands unlock scalable, high-margin digital growth. With over a decade of entrepreneurial experience, Jesse has also hosted a successful podcast where he interviewed renowned business leaders such as Jack Dorsey and Gary Vaynerchuk. Today, Jesse shares his expertise on the power of mastering the fundamentals of email, SMS, and automation in e-commerce marketing. Stay tuned! Resources Vyber Media: Next-Generation Marketing That Drives ROI Connect with Jesse Kay on LinkedIn Follow Jesse Kay on Facebook

Sleuth says new evidence links Jack Dorsey to Bitcoin like never beforeAustralian regulators blitz hits crypto exchanges, money remitters

BlueSky is ONLY popular right now because it's not X, according to Twitter/BlueSky creator Jack Dorsey. And he claims that's not sustainable long-term -- people have to WANT to be there because of what the platform offers. We talk more about BlueSky and put its user numbers in perspective. ✨ Shadowbinders Pin Set Campaign - https://www.kickstarter.com/projects/nydaria/shadowbinders-steampunk-fantasy-hard-enamel-pin-set-series-1

Host Ron Steslow welcomes Mike Brock, CEO of TBD, a subsidiary of Block Inc. (formerly Square), the financial technology firm led by Twitter founder Jack Dorsey. The Internet is dominated by massive, corporate walled gardens like Google, Facebook, and Twitter (now X), where centralized control makes their users (us!) vulnerable to censorship and manipulation. In this episode, we explore how the movement to decentralize technology empowers individuals, protects against corporate and government abuse, and addresses real problems in finance and social media. We'll also discuss how decentralized technology can enhance financial access and freedom, bypassing intermediaries and censorship, and shifting power from financial corporations to individuals. Finally, we turn to the political landscape, focusing on the Democratic party's approach to decentralized technology and early signs it may be changing. Segments to look forward to: (04:45) Mike's background  (10:50) Empowering individuals through decentralized finance and identity  (15:45) Building infrastructure for a decentralized future  (19:10) The potential of decentralized identity  (29:49) The importance of Bitcoin's decentralization  (31:31) Financial Access and Freedom  (34:27) Preserving agency  (44:44) Changing the balance of power  (50:54) The varied stance of the Democratic party Follow Ron and Mike on X (formerly Twitter): https://twitter.com/RonSteslow https://x.com/brockm Email your questions to podcast@politicology.com or leave us a voicemail at ‪(202) 455-4558‬  Learn more about your ad choices. Visit megaphone.fm/adchoices

We've curated a special 10-minute version of the podcast for those in a hurry. Here you can listen to the full episode: https://podcasts.apple.com/no/podcast/block-ceo-twitter-evolution-bitcoin-and-digital-freedom/id1614211565?i=1000691288472&l=nbIn this episode of In Good Company, Nicolai Tangen sits down with tech pioneer Jack Dorsey to explore the evolution of social media and the future of digital finance. The co-founder of Twitter (now X) and Block shares his insights into how Twitter emerged, why he believes open protocols are crucial for social media's future, and his vision for Bitcoin as the Internet's native currency. Dorsey discusses his entrepreneurial philosophy and the importance of algorithmic choice in technology. What would social media look like if Bitcoin had existed when Twitter started? Tune in for a fascinating discussion where technology, money, and personal development come together.In Good Company is hosted by Nicolai Tangen, CEO of Norges Bank Investment Management. New full episodes every Wednesday, and don't miss our Highlight episodes every Friday.The production team for this episode includes Isabelle Karlsson and PLAN-B's Niklas Figenschau Johansen, Sebastian Langvik-Hansen and Pål Huuse. Background research was conducted by Sara Arnesen.Watch the episode on YouTube: Norges Bank Investment Management - YouTubeWant to learn more about the fund? The fund | Norges Bank Investment Management (nbim.no)Follow Nicolai Tangen on LinkedIn: Nicolai Tangen | LinkedInFollow NBIM on LinkedIn: Norges Bank Investment Management: Administrator for bedriftsside | LinkedInFollow NBIM on Instagram: Explore Norges Bank Investment Management on Instagram Hosted on Acast. See acast.com/privacy for more information.

In this episode of In Good Company, Nicolai Tangen sits down with tech pioneer Jack Dorsey to explore the evolution of social media and the future of digital finance. The co-founder of Twitter (now X) and Block shares his insights into how Twitter emerged, why he believes open protocols are crucial for social media's future, and his vision for Bitcoin as the Internet's native currency. Dorsey discusses his entrepreneurial philosophy and the importance of algorithmic choice in technology. What would social media look like if Bitcoin had existed when Twitter started? Tune in for a fascinating discussion where technology, money, and personal development come together.In Good Company is hosted by Nicolai Tangen, CEO of Norges Bank Investment Management. New full episodes every Wednesday, and don't miss our Highlight episodes every Friday.The production team for this episode includes Isabelle Karlsson and PLAN-B's Niklas Figenschau Johansen, Sebastian Langvik-Hansen and Pål Huuse. Background research was conducted by Sara Arnesen.Watch the episode on YouTube: Norges Bank Investment Management - YouTubeWant to learn more about the fund? The fund | Norges Bank Investment Management (nbim.no)Follow Nicolai Tangen on LinkedIn: Nicolai Tangen | LinkedInFollow NBIM on LinkedIn: Norges Bank Investment Management: Administrator for bedriftsside | LinkedInFollow NBIM on Instagram: Explore Norges Bank Investment Management on Instagram Hosted on Acast. See acast.com/privacy for more information.

// GUEST //Nos.social: ⁠https://nos.social/⁠Website: ⁠https://evan.henshaw-plath.com/⁠X: ⁠https://x.com/rabble⁠LinkedIn: ⁠https://nz.linkedin.com/in/rabble⁠ // SPONSORS //The Farm at Okefenokee: ⁠https://okefarm.com/⁠Heart and Soil Supplements (use discount code BREEDLOVE): ⁠https://heartandsoil.co/⁠In Wolf's Clothing: ⁠https://wolfnyc.com/⁠NetSuite: ⁠https://netsuite.com/whatismoney⁠On Ramp: ⁠https://onrampbitcoin.com/?grsf=breedlove⁠Mindlab Pro: ⁠https://www.mindlabpro.com/breedlove⁠Coinbits: ⁠https://coinbits.app/breedlove⁠Emerge Dynamics: ⁠https://emergedynamics.com/breedlove⁠ // PRODUCTS I ENDORSE //Protect your mobile phone from SIM swap attacks: ⁠https://www.efani.com/breedlove⁠Noble Protein (discount code BREEDLOVE for 15% off): ⁠https://nobleorigins.com/⁠Lineage Provisions (use discount code BREEDLOVE): ⁠https://lineageprovisions.com/?ref=breedlove_22⁠Colorado Craft Beef (use discount code BREEDLOVE): ⁠https://coloradocraftbeef.com/⁠ // SUBSCRIBE TO THE CLIPS CHANNEL //⁠https://www.youtube.com/@robertbreedloveclips2996/videos⁠ // OUTLINE //0:00 - WiM Episode Trailer0:00 - WiM Episode Trailer1:06 - The Early Days of Twitter7:14 - When Will Nostr Go Mainstream?9:24 - Why Did Rabble Leave Twitter?11:51 - How has Jack Dorsey Changed Since Founding Twitter?14:19 - Elon Musk's Twitter Takeover15:46 - What Exactly Is Nostr?19:41 - How Nostr Works – A Simple Breakdown22:03 - The Farm at Okefenokee23:30 - Heart & Soil Supplements24:30 - How Nostr Fights Censorship and Preserves Free Speech31:46 - Can You Create Your Own Algorithm on Nostr?35:01 - The Overlap Between Bitcoin and Nostr36:56 - How Do We Get People to Use Decentralized Tech Like Nostr?42:13 - Helping Lightning Startups with In Wolf's Clothing43:05 - Mine Bitcoin with Blockware Solutions44:27 - The Best Apps Being Built on Nostr51:36 - The Tradeoffs of Building on Nostr55:24 - Anarchism and the Solar Punk Ethos1:04:28 - Comparing TCP/IP and Nostr – A Deeper Look1:06:59 - On-Ramp Bitcoin Custody1:08:22 - NetSuite: Business Software1:09:39 - The Power of Community in Nostr's Growth1:13:47 - The Deplatforming of Charles Coughlin1:16:22 - Freedom of Speech vs. Freedom of Reach – The Debate1:19:32 - How Will Decentralized Tech Reshape Society?1:25:08 - How Will Governments Respond to Nostr?1:30:22 - MindLab Pro Supplements1:31:33 - Buy Bitcoin with Coinbits1:33:01 - What Is nos.social?1:36:12 - What Is Cashu? The Future of E-Cash on Nostr1:39:33 - Nostr vs. Bluesky1:47:17 - The Future of Nostr and Decentralized Tech1:56:55 - Where to Find Rabble and His Work // PODCAST //Podcast Website: ⁠https://whatismoneypodcast.com/⁠Apple Podcast: ⁠https://podcasts.apple.com/us/podcast/the-what-is-money-show/id1541404400⁠Spotify: ⁠https://open.spotify.com/show/25LPvm8EewBGyfQQ1abIsE⁠RSS Feed: ⁠https://feeds.simplecast.com/MLdpYXYI⁠ // SUPPORT THIS CHANNEL //Bitcoin: 3D1gfxKZKMtfWaD1bkwiR6JsDzu6e9bZQ7Sats via Strike: ⁠https://strike.me/breedlove22⁠Dollars via Paypal: ⁠https://www.paypal.com/paypalme/RBreedlove⁠Dollars via Venmo: ⁠https://account.venmo.com/u/Robert-Breedlove-2⁠ // SOCIAL //Breedlove X: ⁠https://x.com/Breedlove22⁠WiM? X: ⁠https://x.com/WhatisMoneyShow⁠Linkedin: ⁠https://www.linkedin.com/in/breedlove22/⁠Instagram: ⁠https://www.instagram.com/breedlove_22/⁠TikTok: ⁠https://www.tiktok.com/@breedlove22⁠Substack: ⁠https://breedlove22.substack.com/⁠All My Current Work: ⁠https://linktr.ee/robertbreedlove

GMoney is joined by renowned neurosurgeon and Bitcoin maximalist Dr. Jack Kruse for an absolute fire conversation on Bitcoin, decentralized medicine, and the future of human sovereignty. The deep state is crumbling, the financial system is shifting, and Trump's Executive Order 13818 may be the key to unraveling the corrupt global money machine. But what comes next? Dr. Kruse breaks down why Bitcoin is the ultimate weapon against financial tyranny, how light, water, and magnetism are more important than food for optimizing human health, and why fixing your circadian rhythm is the first step in reclaiming your biology. Plus, the wild story of how Jack Dorsey orange-pilled him on Bitcoin, the hidden risks of modern tech and EMF radiation, and why medical decentralization is the future. This episode is a must-listen for anyone who wants to escape the matrix...both financially and physically. If you're not thinking about sovereignty, health, and Bitcoin together, you're already behind.

Who doesn't like to talk about Twitter and Tweets? Word of mouth (or tweet) is the secret sauce of its success. But has it ever been successful? And if it hasn't, how do you gauge the impact of Elon Musk's shock therapy over the past two years? Journalist Kurt Wagner joins to share his deep dive profile of the tortured history of Twitter. [Repeat from May, 2024]For more on Bubble Trouble, including transcripts of the show, visit us online at http://bubbletroublepodcast.comYou can learn more about Richard at https://www.linkedin.com/in/richard-kramer-16306b2/More on Will Page at: https://pivotaleconomics.com(Times below correspond to the episode without considering any inserted advertisements.)This episode of Bubble Trouble features a conversation with Bloomberg journalist Kurt Wagner, author of 'Battle for the Bird,' a book about Twitter's tumultuous history and evolution, particularly under Elon Musk's ownership. The hosts, independent analyst Richard Kramer and economist Will Page, delve into Twitter's origins, its struggle to monetize effectively compared to giants like Meta, and the significant influence of Jack Dorsey's leadership style on the platform's direction. They discuss the platform's missed opportunities, such as Vine and Periscope, and how it became a place where 'good ideas go to die.' The discussion also covers Musk's takeover, his attempts to transform Twitter into 'X', and the challenges of balancing free speech with the need for content moderation and advertiser appeal. Wagner shares insights on the potential future of 'X', the impact of Musk's leadership on the platform's advertising and user engagement, and the skepticism surrounding the 'everything app' concept Musk envisions.00:00 Introduction01:02 Part One01:02 Deep Dive with Kurt Wagner: The Story of Twitter02:36 The Origins and Evolution of Twitter06:20 Twitter's User Base and Business Model Explored09:10 The Challenges of Twitter's Business Model14:10 Board Dynamics and Google's Influence on Twitter18:03 Extravagant Spending and Corporate Culture at Twitter21:13 Reflections on Twitter's Stock Performance23:47 The Almost Disney-Twitter Deal: A Glimpse into Corporate Negotiations24:29 Twitter's Quest for a Savior and Its Struggle for Independence25:53 Missed Opportunities: The Story of Vine and Periscope27:27 Part Two27:27 Transition to Part Two: The Elon Musk Era at Twitter27:49 The Challenges of Rebranding Twitter to X and Musk's Controversial Leadership28:32 The Impact of Elon Musk's Actions on Twitter's Ad Revenue and Brand Safety36:52 The Struggle with Bots and Spam: Has It Gotten Worse?40:06 Free Speech Under Musk: A Double-Edged Sword44:26 The Everything App Ambition: A Skeptical View46:33 Closing Thoughts and Acknowledgements47:01 Credits Hosted on Acast. See acast.com/privacy for more information.

Boom's XB-1 jet broke the sound barrier for the first time, Jack Dorsey's Block has an AI agent too, and good luck figuring out what time it is on the new Asteroids watch. It's Wednesday, January 29th and this is Engadget News. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Jack Dorsey is founder of both Twitter, now X, and Square, now Block. We discuss his strong focus on bitcoin and nostr, lessons learned across his many years of experience, censorship on twitter, and the promise that open source freedom tech holds for humanity.We also celebrate the pardon of Ross Ulbricht after 12 years in jail for the nonviolent crime of running SIlk Road. The news broke while we were live.Jack on Nostr: https://primal.net/jackEPISODE: 150BLOCK: 880265PRICE: 939 sats per dollarsupport dispatch: https://citadeldispatch.com/donatenostr live chat: https://citadeldispatch.com/streamodell nostr account: https://primal.net/odelldispatch nostr account: https://primal.net/citadelyoutube: https://www.youtube.com/@CitadelDispatchpodcast: https://serve.podhome.fm/CitadelDispatchstream sats to the show: https://www.fountain.fm/join the chat: https://citadeldispatch.com/chatlearn more about me: https://odell.xyz(00:00:03) Ross Ulbricht - 2021 Interview - Bitcoin Miami(00:05:55) Introduction and Ross's Background(00:07:35) Conversation with Jack Dorsey Begins(00:10:14) Jack Dorsey on Bitcoin's Importance(00:15:13) Bitcoin's Challenges and Distractions(00:19:12) ETFs and Bitcoin Adoption(00:23:00) Companies Stacking Bitcoin(00:25:32) Bitcoin Usage and Adoption Challenges(00:31:09) US Financial System and Global Comparisons(00:35:57) Trump Coin and Meme Coins(00:39:02) Nostr as a Social Media Protocol(00:47:02) Nostr's Potential and Challenges(00:54:01) Nostr's Bootstrapping and Community Building(01:00:06) Algorithmic Choice and Content Discovery(01:06:13) Nostr's Role in Content and News(01:17:03) Jack Dorsey on Nostr and Bitcoin Wallets(01:34:08) Nostr vs. Traditional Social Media(01:40:24) Cashu and Open Protocols(01:51:01) Final Thoughts and Ross Ulbricht's Pardon

On this year's final episode of FYI, we will be taking the opportunity to highlight some of the best moments from throughout the year. While we are grateful for every single guest that has joined the For Your Innovation podcast, here is a compilation of some of our favorite moments.Key Points From This Episode:SoFi CEO Anthony Noto explains how he managed to diversify SoFi's product line from beyond it's start as a student loan platform, and why Anthony felt he needed to purchase the rights to a stadium to grow SoFi's business.NBA stars Andre Iguodala and Evan Turner talk about their early intellectual pursuits in financial literacy, and how they parleyed their experience as NBA athletes into the world of venture capital.OpenAI CFO, Sarah Friar, discusses the scope of the AI opportunity and how OpenAI is just getting started.Jack Dorsey explains the importance and implications of bitcoins open source nature, and how it's truly a disruptive innovation.Shopify's president, Harley Finkelstein, explains the rise of entrepreneurship globally, the critical role of AI in reducing barriers for entrepreneurs, and Shopify's vision for the future.