Podcast appearances and mentions of Jack Dorsey

In this thought-provoking Market Mondays clip, the hosts Rashad Bilal, Ian Dunlap, and Troy Millings dive into the intersection of war, technology, and market resilience. They start by breaking down the “war index” — highlighting major players like Palantir, Anderil, OpenAI, Microsoft, and Meta — and reveal how data and algorithms are the new battlegrounds alongside traditional military might. Discover why having user data on 3.4 billion people gives Meta unprecendented influence, and how information (and propaganda) shape global conflict just as much as firepower.The conversation pivots to current geopolitical flashpoints, including Yemen's bold entry into the fray, the critical importance of waterways like the Strait of Hormuz, and the complex dance between America, Israel, Iran, China, and Russia. Does long-term regime change trigger more instability? Rashad explores lessons from history, the risks of forced changes, and what global players want for Iran's future.But it's not all global tension! The clip also covers how the markets respond to conflict, why “the market is literally rigged to stay up,” and tactical investment tips on stocks like Palantir and Meta, especially as they break new all-time highs.Crypto fans, this one's for you too—debate heats up over Bitcoin, Jack Dorsey versus Michael Saylor, and the ever-polarizing XRP. Rashad opens up about his fraught relationship with the XRP crowd and pushes Ian and Troy to weigh in: will XRP ever hit $10,000, or will institutional power always win out?Plus, hear exclusive details about Invest Fest, including a raffle for an all-expenses-paid trip to Ghana and special appearances from the likes of Jack Dorsey and past panelists like Cathie Wood.

47e6GvjL4in5Zy5vVHMb9PQtGXQAcFvWSCQn2fuwDYZoZRk3oFjefr51WBNDGG9EjF1YDavg7pwGDFSAVWC5K42CBcLLv5U OR DONATE HERE: https://www.monerotalk.live/donate GUEST LINKS: https://x.com/TorEkelandPLLC https://x.com/mikehassard TIMESTAMPS (00:00:00) Doug XMR Workshop at Porcfest. (00:59:50) Monerotopia News Segment w/ Tony. (01:00:29) House in Argentina for XMR. (01:02:00) MoneroKon. (01:05:20) Doug strong like XMR. (01:06:57) Monero Community Fundraiser. (01:08:11) Coinmarketcap has been hacked. (01:08:55) A new payment channel concept for Monero. (01:09:35) Privacy, Banks and the Digital Euro Threat. (01:15:25) Saylor couldn't sleep when he found BTC. (01:17:18) Jack Dorsey explaining Bitcoin. (01:25:10) Monerotopia Guest Segment w/ Mike Hassard and Tor Ekeland. (01:45:30) Sal The Agorist. (02:04:15) Monerotopia Finalization. NEWS SEGMENT LINKS: House in Argentina for xmr: https://www.reddit.com/r/Monero/s/wSBXWZ7QPy Monerokon speeches: https://www.reddit.com/r/Monero/s/YKRL4wrmGY Saylor couldn't sleep when he found BTC: https://x.com/saylordocs/status/1936423966832234529?s=46&t=mVZ0A2C1bwwnAvgawJjlw Xmr in Australia: https://x.com/thestoiccoiner/status/1936398520648609858?s=46&t=mVZ0A2C1bwwnAvgawJjlw Doug strong like XMR: https://x.com/douglastuman/status/1935785882537410645?s=46&t=mVZ0A2C1bwwnAvgawJjlw Porcfest: https://x.com/douglastuman/status/1936249310397563070?s=46&t=mVZ0A2C1bwwnAvgawJjlw Jack Dorsey explaining BTC: https://x.com/vivek4real/status/1936418970967667143?s=46&t=mVZ0A2C1bwwnAvgawJjlw Monerokon part 1: https://x.com/exiledsurfer/status/1936364845852491896?s=46&t=mVZ0A2C1bwwnAvgawJjlw Monerokon part 2: https://x.com/cakewallet/status/1936087997536956915?s=46&t=mVZ0A2C1bwwnAvgawJjlw Monerokon part 3: https://x.com/monerokon/status/1935953875632074809?s=46&t=mVZ0A2C1_bwwnAvgawJjlw 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

One stock recently impacted by a whirlwind of volatility is Block – the fintech powerhouse behind Square, CashApp, TIDAL Music, and more. The company's COO & CFO, Amrita Ahuja, joins Rapid Response to share how her team is using new AI tools to find opportunity amid disruption, steadfast on Block's mission to move money faster and reimagine how users everywhere sell, pay and save. Ahuja also shares lessons from the video game industry, Gen Z's surprising approach to money, and what lessons she's learned under tech icon Jack Dorsey. Visit the Rapid Response website here: https://www.rapidresponseshow.com/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Secretary of Defense Pete Hegseth has announced they are getting rid of all the woke Navy ship names. Let's see what's on the list. Elon Musk has come out against Trump's Big Beautiful Bill. Chuck Schumer and Jack Dorsey agree. Wait, what?GUEST: Josh FirestineLet American Financing help you regain control of your finances. Go to https://americanfinancing.net/crowder or call 1-800-974-6500. NMLS 182334, http://nmlsconsumeraccess.org/Buy the OG Mug Club Mug on Crowder Shop now! https://crowdershop.com/products/og-mug-club-mugLink to today's sources: https://www.louderwithcrowder.com/sources-june-4-2025DOWNLOAD THE RUMBLE APP TODAY: https://rumble.com/our-appsJoin Rumble Premium to watch this show every day! http://louderwithcrowder.com/PremiumGet your favorite LWC gear: https://crowdershop.com/Bite-Sized Content: https://rumble.com/c/CrowderBitsSubscribe to my podcast: https://rss.com/podcasts/louder-with-crowder/FOLLOW ME: Website: https://louderwithcrowder.com/ Twitter: https://twitter.com/scrowder Instagram: http://www.instagram.com/louderwithcrowder Facebook: https://www.facebook.com/stevencrowderofficialMusic by @Pogo

In this episode of The Bitcoin Podcast, Walker America interviews Rockstar Dev at the Bitcoin conference in Las Vegas, discussing Bitcoin adoption, the use of Bitcoin in everyday transactions, Jack Dorsey's SQUARE enabling Bitcoin payments, the federal reserve, shitcoin scammers, and the broader implications of Bitcoin on society and the economy. FOLLOW ROCKSTAR: NOSTR: https://primal.net/rockstar X: https://x.com/r0ckstardev THE Bitcoin Podcast Partners: > GET FOLD: https://use.foldapp.com/r/WALKER > SIGN UP FOR THE FOLD BITCOIN REWARDS CREDIT CARD: https://foldapp.com/credit-card?r=UZoiP > Get the BITKIT mobile wallet: https://get.bitkit.to/walker > http://bitbox.swiss/walker -- use promo code WALKER for 5% off the Bitcoin-only Bitbox02 hardware wallet. ***** If you enjoy THE Bitcoin Podcast you can help support the show by doing the following: FOLLOW ME (Walker) on @WalkerAmerica on X | @TitcoinPodcast on X | Nostr Personal (walker) | Nostr Podcast (Titcoin) | Instagram Subscribe to THE Bitcoin Podcast (and leave a review) on Fountain | YouTube | Spotify | Rumble | EVERYWHERE ELSE

De ogen van de wereldwijde cryptosector waren vorige week even gericht op Las Vegas. Daar vond de belangrijkste Bitcoinconferentie van het jaar plaats, met een opvallende mix van bekende namen uit de industrie, internationale beleidsmakers en vertegenwoordigers van overheden. Zelfs de Amerikaanse vicepremier JD Vance nam het woord op het podium. Zijn aanwezigheid maakte veel los, zowel binnen als buiten de sector. Wetgeving en de rol van de Amerikaanse overheid waren sowieso grote thema’s in Las Vegas. Het sentiment was overwegend optimistisch, mede dankzij de aanwezigheid van meerdere regeringsvertegenwoordigers. Daarnaast presenteerde Jack Dorsey’s bedrijf Square een nieuwe stap: lightningbetalingen worden geïntegreerd in hun betaalterminals. Deze functionaliteit werd ter plekke getest en blijkt snel en praktisch te werken. Naast het podiumprogramma bracht de conferentie ook een stroom aan nieuws. Zo kondigde een afgevaardigde van de Pakistaanse regering aan dat het land een eigen Bitcoinreserve wil opbouwen, naar voorbeeld van de Verenigde Staten. Het doel is om via een strategische voorraad digitale valuta economische stabiliteit te bevorderen. Ook Trump Media, het bedrijf achter Truth Social, voegde Bitcoin toe aan de reserves. Daarmee onderstreept het opnieuw het pro-crypto-standpunt van de president. Tot slot kijken we naar de markt. De koers van Bitcoin bleef deze week opvallend vlak. Volgens portfoliomanager Tim Stolte van Amdax wijst dit op een afwachtende houding onder beleggers, mogelijk in aanloop naar grotere economische of politieke ontwikkelingen. Ook bij Ethereum is weinig beweging te zien, maar het op één na grootste cryptoproject doet het de laatste tijd wél stukken beter dan andere altcoins. En dat is dan weer positief te noemen, want verloor Ethereum ten opzichte van zijn concurrentie. Co-host is Bart Mol. Gasten Bart Mol Links Host Daniël Mol Redactie Daniël MolSee omnystudio.com/listener for privacy information.

Bitcoin is bigger now than it's ever been. But is it better?FEATURING:Thomas Hunt (https://twitter.com/MadBitcoins)THIS WEEK:  Conference Recap - the size  - the attendees and booths - VP Vance - stablecoins, regulatory support, blame previous admin - Trump Sons - we had rich banking problems and found bitcoin  1 no mention of banking the unbanked or digital currency. All digital gold now.  - Michael Saylor - AI, Bitcoin, building companies for generational wealth  - Ross Ulbricht - Freedom Decentralisation Unity - the Bitcoin movement became so powerful it freed me. Jack Dorsey confirms #Bitcoin Lightning payments will be enabled by default for all Square sellers.https://twitter.com/tftc21/status/1927743889558974781?s=46Source: Twitter/XJames Howells, still chasing his lost 8,000 $BTC in a landfill, has a new plan:Tokenize 1,675 of those coins as ordinals.https://twitter.com/tftc21/status/1927852787553161333?s=46Source: Twitter/XMichael Saylor calls onchain proof-of-reserves a ‘bad idea,' rules it out for Strategy over security concernshttps://www.theblock.co/amp/post/355811/strategy-saylor-onchain-proof-of-reserves-bad-idea-security-threats-lack-of-liabilitiesSource: The BlockJack Mallers announces Twenty One Capital will publish a Proof of Reserves.https://twitter.com/tftc21/status/1928165557548773599?s=46Source: Twitter/XBitcoin is at $110,000 and normies would rather pick free Starbucks instead.What went wrong?https://twitter.com/lynk0x/status/1926357637391622410?s=46Source: Twitter/XCharles Schwab CEO says Bitcoin and crypto buying is coming for 37 million clients.https://twitter.com/fiatarchive/status/1926759898248839369?s=46Source: Twitter/XJUST IN: Tether announces it owns over 100,000 #Bitcoin and more than 50 tons of gold.https://twitter.com/bitcoinmagazine/status/1928166935537058181?s=46Source: Twitter/X___________________________________________________________________________________________World Crypto Networkhttps://www.worldcryptonetwork.com/On This Day in World Crypto Network Historyhttps://www.worldcryptonetwork.com/onthisday/------------------------------------------------------------------------------------------------------------------------------------------------------Please Subscribe to our Youtube Channelhttps://m.youtube.com/channel/UCR9gdpWisRwnk_k23GsHf

Most of us have our smartphones on our person more or less all day, every day. Our photos, payment methods and a lot of personal data are stored on them. So we're all wary of the risk of having them stolen when out in public. But did you know there's another way someone can take control of your phone line without you even losing the device? It's called sim swapping and while it's not new, it's been on the rise in recent years. According to the FBI, Americans lost a combined $68M to sim swapping scams in 2021. One of the most high-profile examples saw Twitter founder Jack Dorsey fall prey to it in 2019. How does SIM swapping work? How can I avoid falling victim to SIM swapping? In under 3 minutes, we answer your questions! To listen to the last episodes, you can click here: ⁠What are the pros and cons of homeownership in the UK?⁠ ⁠How can I make and keep my new year's resolutions?⁠ ⁠Why does the year begin on January 1st?⁠ A podcast written and realised by Joseph Chance. First broadcast : 7/5/2023 Learn more about your ad choices. Visit megaphone.fm/adchoices

As a CFO, how should the way you navigate risk and return change from venture-backed companies to publicly-traded companies to private equity companies? To answer this question, CJ speaks with Mohit Daswani, a seasoned CFO with experience across multiple stages, including roles as CFO of Payments, Platform, and Risk at PayPal, and Head of Finance & Strategy at Square. Mohit shares the lessons learned from his time at Square, including when Jack Dorsey seeded a second billion-dollar business from within the company, and his experience at PayPal when they spun out from eBay under activist pressure. The conversation also covers the Rule of 40 in the different financial models, the dangers of using valuation as a scorecard, how founders should reset their mindset on what defines success, and the likelihood of a super app for the USA.—LINKS:Mohit Daswani on LinkedIn: https://www.linkedin.com/in/mohitdaswani1/SimplePractice: https://www.simplepractice.com/CJ on X (@cjgustafson222): https://x.com/cjgustafson222Mostly metrics: http://mostlymetrics.comRELATED EPISODES:From CF-No to CF-Go: Serial CFO Michael Bayer's Guide to Hypergrowth: Inside Grab: How a Super App Transformed Southeast Asia — with CFO Peter Oey: —Timestamps:(00:00) Preview and Intro(02:42) Sponsor – Planful | Tabs | Rippling Spend(06:36) Mohit's Office and a Tip From Churchill(09:07) Risk and Return in Different Investment Models(13:05) Financial Discipline Versus Room for Growth in Venture-Backed Companies(16:30) Sponsor – Pulley | Tropic | NetSuite(20:25) Balancing Short-Term Performance and Long-Term Bets in the PE Space(24:00) The Rule of 40 in Different Financial Models(30:19) What People Get Wrong About the Private Equity Model(34:40) The Benefits of Using Leverage(37:41) The Dangers of Using Valuation as a Scorecard(41:41) How Founders Should Reset Their Mindset on What Constitutes Success(44:00) Being at Square When Jack Dorsey Seeded a Second Billion-Dollar Business(49:43) Being at PayPal When They Spun Out From eBay(53:59) PayPal's Acquisition of Braintree(55:48) The Probability of a Super App for the USA(58:38) Learnings From Launching PayPal's Payments Dongle in Japan(1:04:12) Long-Ass Lightning Round: A Flight Mistake(1:06:20) Advice to Younger Self(1:07:31) Finance Software Stack(1:09:28) Craziest Expense Story—SPONSORS:Planful's financial planning software can transform your FP&A function. Built for speed, accuracy, and confidence, you'll be planning your way to success and have time left over to actually put it to work. Find out more at www.planful.com/metrics.Tabs is a platform that brings all of your revenue-facing data and workflows - billing, AR, payments, rev rec, and reporting - onto a single system so you can automate and be more flexible. Find out more at: tabs.inc/metrics.Rippling Spend is a spend management software that gives you complete visibility and automated policy controls across every type of spend, saving you time and money. Get a demo to see how much time your org would save at rippling.com/metrics.Pulley is the cap table management platform built for CFOs and finance leaders who need reliable, audit-ready data and intuitive workflows, without the hidden fees or unreliable support. Switch in as little as 5 days and get 25% off your first year: pulley.com/mostlymetrics.Tropic is an intelligent spend management solution that consolidates your spend data and processes into one unified offering, enabling insights and decisive action. Take control of your spend with intelligent spend management at tropicapp.io/mostlymetrics.NetSuite is an AI-powered business management suite, encompassing ERP/Financials, CRM, and ecommerce for more than 41,000 customers. If you're looking for an ERP, head to https://netsuite.com/metrics and get the CFO's Guide to AI and Machine Learning.#VentureCapital #PrivateEquity #RiskManagement #RuleOf40 #PayPal Get full access to Mostly metrics at www.mostlymetrics.com/subscribe

How can you preserve simplicity and work at a reasonable pace in an increasingly complex and rushed environment? That's the question I'm answering today. You can subscribe to this podcast on:  Podbean | Apple Podcasts | Stitcher | Spotify | TUNEIN Links: Email Me | Twitter | Facebook | Website | Linkedin The ULTIMATE PRODUCTIVITY WORKSHOP Get Your Copy Of Your Time, Your Way: Time Well Managed, Life Well Lived The Time Sector System 5th Year Anniversary The Working With… Weekly Newsletter Carl Pullein Learning Centre Carl's YouTube Channel Carl Pullein Coaching Programmes Subscribe to my Substack  The Working With… Podcast Previous episodes page Script | 370 Hello, and welcome to episode 370 of the Your Time, Your Way Podcast. A podcast to answer all your questions about productivity, time management, self-development, and goal planning. My name is Carl Pullein, and I am your host of this show. Two of the challenges we face today are the increasing complexity in our work life. Yet, that has been around forever. New technology requires us to learn new techniques for doing things and, perhaps, the biggest challenge of all is dealing with the speed at which things come at us.  Interestingly, the number of emails we get today is comparable to the number of letters people in the 1970s and 80s received. Yet the number of phone calls we get have dramatically dropped. That's largely due to the move towards instant messages—which were not around in the 70s and 80s.  The difference is the speed at which we are expected to respond. With a letter, there was some doubt about when the letter would arrive. It might arrive the next day, but there was always a chance it would take two or three days.  And when it did arrive, we had at least twenty four hours to respond. Today, there are some people who expect you to respond to an email immediately—no thought that you may be working on something else or in a meeting with an important customer.  So the question we should explore is how we can navigate the way we work today without letting people down, but at the same time work at a comfortable speed which minimises mistakes and leaves us feeling fulfilled at the end of the day.  So, with that stated, let me hand you over to the Mystery Podcast Voice for this week's question.  This week's question comes from Tom. Tom asks, Hi Carl, over the years, my productivity system has changed with technology. I began, like you, with a Franklin Planner in the 1990s, then I moved to Getting Things Done and managed everything digitally. These days, I am struggling to keep up, and it just seems so complicated. Do you have any thoughts on how to keep things simple? Hi Tom, thank you for your question.  One way to look at this is to remember that the basic principles of good time management and productivity will never change. Those principles are incorporated in COD—Collect, Organise and Do.  No matter how complicated or fast things get, we still need a way to collect stuff and trust that what we collect will be where we want it to be when we process it.  We need an organisation system that works for us. And that means, we can find what we need when we need it.  And finally, we want to be maximising the time we spend doing the work, so we avoid backlogs building.  It's within this framework we can evolve our systems.  Thirty years ago, we would have been collecting with pen and paper. Today, it's likely we will collect using our phones or computer. Thirty years ago we would have had stacks of file folders and a filing cabinet or two to store those folders. Today, those files will likely be held in the cloud—Google Drive, iCloud or OneDrive, for instance.  So while the tools have changed, the principles have not.  I'm a big rugby fan. I've been following Leeds Rhinos since my grandfather took me to my first game when I was five years old.  The teams that win the championships and cup games are the ones who get the basics right. In rugby, that is playing the majority of the game in the oppositions half. Being aggressive in defence and ensuring their players are disciplined—giving away silly penalties is one sure way to lose games.  The teams that lose are the ones who don't get these basics right. They try to be clever, get frustrated, and drop the ball (quite literally) and give away unnecessary penalties, which results in them giving away territory and playing the majority of the game in their own half.  The message is always the same. Get the basics right and the results will come.  This is the same for you, too, Tom. Get the basics right and that's following the principles of COD.  The problems will start when we begin trying to do multiple things at the same time. Multi-tasking is not a strategy. Sure there are some things you can do at the same time. Walking and thinking about solving a problem, listening to a podcast while doing the dishes or cleaning up the house.  But you are not going to be able to write a report, prepare a presentation and reply to your emails at the same time. These are very different types of work requiring different skills.  A report is well thought out words and conclusions. A presentation is a visual representation of your main points and writing emails is about communicating clearly in words. All requiring different parts of your brain.  This is why categorising the work you do works so well. With categorising, or chunking or batch processing—they all mean the same thing—you are grouping similar tasks together and doing them at the same time. For example, you can collect your actionable emails together and set aside thirty to sixty minutes each day for responding to them.  If you were consistent with that, you would always be on top of your mails and no one would be waiting much longer that 24 hours for a reply.  Similarly if you were responsible for sending out proposals to prospective customers, if you were to spend an hour or so on those each day, you would rarely have any backlogs and your proposals would be going out quickly without errors.  It's when we stop following these principles we become like the losing rugby teams. We've stopped following the game plan and become frustrated, which leads to mistakes which in turn means we lose the game.  Or in the world of work, we create backlogs, deadlines are missed and we feel horrible, stressed out and overwhelmed.  I've always found it fascinating to learn how productive people work. I saw recently an interview with Tim Cook, where he mentioned he wakes up at 4:00 am, and the first hour of his day is spent doing email.  I remember reading that Jack Dorsey, one of the founders of Twitter and the CEO of Square, who would schedule his days by category of work. Monday and Tuesdays were spend on marketing, Wednesdays were problem solving and Thursdays would be spent at Square and Fridays at Twitter.  They all have some structure to their days. Incidentally, this was the same for Winston Churchill and Charles Darwin. They both followed a strict structure to their days which ensured they spent time each day on the things that mattered.  While the way we work and the tools we use to do our work may change, the way we structure our days doesn't have to.  Twenty years ago, spending an hour on returning phone messages was the norm. Today, that same hour will likely be spent responding to Slack or Teams messages and email.  If you want to get control of your time and remain productive, it will be helpful to know what is important.  What is your core work? The work you are paid to do? What does that look like at a task level? Working in concepts doesn't work here. You need to go to the next level and determine what your work looks like at a task level.  An accountant will need to put numbers into a spreadsheet (or something similar) in order to get the information they need to be able to advise their clients. The question therefore becomes how much time do they need to do that each day to ensure they are on top of their work?  As a former Franklin Planner user, you will know the importance of daily and weekly planning. This is about knowing what is important today and this week. It's about allocating sufficient time to getting that work done and being strict about what you allow on your calendar.  Perhaps part of the problem we face today is the increasing demands on our time. It's easy to ask someone to jump on a Teams or Zoom call for “a few minutes” Ha! How often does five minutes turn into thirty minutes?  And because of the simplicity of doing these calls, we accept. Perhaps too readily.  I don't have Zoom or Teams on my phone. If I am not with my laptop, I cannot do a video call. It's a rule. And a non-negotiable one too.  Where are your rules? What will you accept and, more importantly, not accept?  One way you can manage this is to limit the number of meetings you have each day. If you spend seven hours of your eight hours of your work day in meetings, how will you find the time to do the work you are employed to do?  That isn't a task management issue. That's a time issue. It doesn't matter how many tasks you have to do today if you do not have the time protected for doing them. It's on you to protect that time and that doesn't matter where you are in the hierarchy chain.  If your boss expects you to be in seven hours of meetings each day and write reports, prepare presentations and respond to your emails and messages, that's an issue you need to take up with your boss. No tool or productivity system will sort that out for you.  Even with the help of AI, you will struggle to do your work with that kind of time conflict.  Now when it comes to managing your files and notes, I would say don't reinvent the wheel.  Several years ago, Microsoft and Apple's engineers released we were terrible at managing our documents. So, they began rolling out self contained folders for their professional tools such as Word and Keynote.  You no longer need to file these documents in folders you create. Instead you can save them and let your computer organise them for you. For example, if you use Word, all your word documents can be saved to the Word container folder in OneNote. Just like Google Docs. These are all kept together and you can then organise them in a variety of ways. You can do it alphabetically, the date the document was created or when it was last modified (great for when collaborating with other people). In iCloud and Google Drive, you can also organise by which documents are shared.  Your computer does the hard work so you don't have to. There's certainly no longer a need to create sophisticated file folder structures that take forever to keep organised. You don't have time for that. Let your computer do the work for you.  And not only have these companies made organising our work easier, they have been gradually improving search features too. Now as long as you know a date range, a keyword or a title, you'll be able to find any document in seconds.  There is no longer any need to manually organise your documents. The only responsibility you have is to ensure the names of the documents you have saved mean something to you. If you're downloading a document, make sure you rename it. There's some very strange file naming conventions out there.  And that's about it, Tom.  Stick to the basics of COD—Collect, Organise, Do. Be strict about what you allow on your calendar (even if that means you need to an uncomfortable talk with your boss) and let your computer do the hard work of filing for you.  I hope that has helped. Thank you for your question.  And thank you to you too for listening. It just remains for me now to with you all a very very productive week.   

- btcpay servers get stuck on block 896727 and need to be updated https://github.com/dgarage/NBXplorer/issues/518 and https://primal.net/e/nevent1qqs2l8hewqnz7y7jgqhe8pfzkqustl7aqftd9nwer8xxz28yalrqx0qycz0zh- bitcoin payments at bitcoin 2025 conference- Hot Style Takeover 2: https://lu.ma/gn9uoj6b- coinbase kyc leak https://www.coinbase.com/blog/protecting-our-customers-standing-up-to-extortionists- opensats 11th wave of bitcoin grants https://opensats.org/blog/elevent-wave-of-bitcoin-grants- China | Law Enforcement Freezes Bank Accounts of Independent Media Outlet Channel CHong Kong-based Channel C, an independent media outlet founded by former Apple Daily employees, reports that its bank accounts are frozen, forcing the news outlet to halt operations. Local law enforcement claim the outlet abused a COVID-era loan scheme and arrested one of its directors for alleged fraud. Still, the closure fits a well-worn pattern: using financial and legal repression to silence independent media in Hong Kong. Pro-democracy newspaper Apple Daily faced a nearly identical fate in 2021 when its assets were seized and its founder, Jimmy Lai, was imprisoned under Hong Kong's new national security law. Lai now faces up to life in prison. When access to money becomes contingent on political obedience, press freedom can't survive. FinancialFreedomReport.org- dorsey vibe codes https://nostream.pub- primal article editor launched https://primal.net/e/nevent1qqsdxku9htc2pwfdcdqw9vqt7k2ukqvr9g852y6qlsgccntw6eldwpsmmx0f8- maple ai releases ios apps https://primal.net/e/nevent1qqszxzehvlglrnlmn5xzfqdt4fyspwkvl4ud7yc6mfthquhhcthxw2g70vdkd- damus notedeck beta released for supporters https://damus.io/notedeck/install/- zap stream launches ios testflight https://testflight.apple.com/join/5Qh7mfvU0:00 - TWO guests?3:05 - BTCPayServer issue12:05 - Bitcoin Conf59:00 - Dashboard1:00:05 - Coinbase breach1:12:20 OpenSats1:19:25 - HRF Story of the Week1:28:00 - Shoutouts1:33:20 - Jack Dorsey's vibe code1:35:45 - Primal Article Editor1:42:18 - Maple AI on App Store1:51:20 - Damus Notedeck1:55:10 - ZapStream TestFlightShoutout to our sponsors:Coinkitehttps://coinkite.com/Bitkeyhttps://bitkey.world/Stakworkhttps://stakwork.ai/Follow Marty Bent:Twitterhttps://twitter.com/martybentNostrhttps://primal.net/martyNewsletterhttps://tftc.io/martys-bent/Podcasthttps://tftc.io/podcasts/Follow Odell:Nostrhttps://primal.net/odellNewsletterhttps://discreetlog.com/Podcasthttps://citadeldispatch.com/

Today we are talking with Valeska Pederson Hinz, partner at Perkins Coie, about what's happening in the world of music tech investment. Valeska has extensive experience in guiding companies and investors from Series A to IPO and has an indispensable vantage point. Our conversation includes the current state of venture capital funding, the impact of generative AI on the industry and the ongoing legal debates surrounding fair use versus licensing in AI training data. She also has practical advice for startup founders from the legal standpoint of someone who guides growth stage companies.    News Shoutouts UMG generated $3bn+ in Q1 Spotify posts record-high operating profit for Q1 Splice acquires Spitfire Audio Epidemic Sound acquires AI startup Song Sleuth  NMPA says Spotify's Q1 growth due to ‘undercutting of songwriters' via audiobook bundling Jack Dorsey's ‘Delete All IP Law' post highlights the hypocrisy of Big Tech Billionaires Hearing Things   The Music Tectonics podcast goes beneath the surface of the music industry to explore how technology is changing the way business gets done. Visit musictectonics.com to find shownotes and a transcript for this episode, and find us on LinkedIn, Twitter, and Instagram. Let us know what you think!    Get Dmitri's Rock Paper Scanner newsletter.  

Jack Dorsey. Tony Xu ,Vinod Khosla, Peter McGuinness and Jacob DeWitte and Their Obsession with ... (aspirational)

Meet Jesse Kay, the Founder and CEO of Vyber Media. His performance marketing agency focuses squarely on helping brands achieve scalable, data-driven growth that genuinely connects with the Gen Z audience. What began as a side project when Jesse was just 17 years old quickly blossomed. Recognizing the venture's potential, he made the significant decision to leave a role at Goldman Sachs and pour all his energy into building Vyber Media. Today, Vyber Media collaborates with a wide spectrum of companies, ranging from ambitious high-growth startups to established Fortune 500 giants. The agency utilizes a strategic mix of email, SMS, paid marketing, and targeted media strategies to drive high-margin revenue growth and elevate brand engagement across diverse industries. Beyond the agency world, Jesse is no stranger to the microphone. He's hosted a podcast for nearly a decade, featuring insightful interviews with high-profile guests like Jack Dorsey, Mark Cuban, Gary Vaynerchuk, Leslie Berland, and Candace Parker, delving into their journeys and expertise. Jesse's drive also extends to making a difference. During the COVID-19 pandemic, he co-founded the Makin' Lemonade Fund. This initiative successfully mobilized over 400 students, impressively raising $130,000 in only 45 days to support vital nonprofit organizations during a critical time. His work and perspectives have garnered significant attention, with features in prestigious outlets such as The Wall Street Journal, ESPN, Adobe, Fast Company, Inc., Business Insider, and an appearance on the Dr. Phil Show. Jesse's approach is partly shaped by his education at Cornell University, where he studied Persuasion and Social Influence. This academic background provides a unique lens through which he views marketing and entrepreneurship, particularly in understanding the nuances of connecting with younger generations. Vyber Media was founded to redefine performance marketing, rooted in ambition, digital understanding, and delivering impactful results. For More Info: https://www.vybermedia.com/

Show Notes: Are Google and Meta Screwed?And does it make any Sense?April 18, 2025OverviewThis week's newsletter delves into a pivotal moment for two of tech's biggest players: Meta and Google. Long dominant through strategic acquisitions and platform control, both are now under intense legal scrutiny. At the same time, a new platform shift—centered on AI—threatens to upend their business models, just as geopolitical forces reshape global markets.Listeners will gain insight into how antitrust battles, legacy acquisitions, AI innovation, and trade wars intersect to challenge the future of these giants. We'll connect disparate articles to reveal patterns that go beyond individual stories.Key TrendsKey Trend 1: Government Antitrust Pressure and Legal BattlesSignificance: After decades of unchecked growth, Meta and Google face unprecedented antitrust scrutiny. The outcomes could reset the rules for digital markets—and determine whether breakups or massive fines become the norm.Talking Point 1: Meta's High-Stakes Trial“In a just world, the FTC has no shot to win this case. The case is so nebulous and weak…”– M.G. Siegler, “The Meta Points of Meta's Trial” (https://spyglass.org/meta-trial/)• Highlights the FTC's challenge: litigating past acquisitions with vague theories of harm.Talking Point 2: Google Guilty in Ad Tech Monopoly“A judge ruled that Google holds a monopolistic position in the technology of online advertising, unfairly harming rivals and advertisers.”– David McCabe, New York Times(https://www.nytimes.com/2025/04/17/technology/google-ad-tech-antitrust-ruling.html)• Marks the second major U.S. court loss for Google in under a year, setting the stage for structural remedies.Key Trend 2: Strategic Platform Shifts and Legacy AcquisitionsSignificance: Meta's survival has hinged on buying Instagram and WhatsApp; now those very deals are under fire. The pattern echoes past shifts—desktop to mobile—and underscores how acquisitions can both secure and imperil platform relevance.Talking Point 1: The Value and Vulnerability of Instagram“Without Instagram, Meta is screwed.”– M.G. Siegler, Spyglass (https://spyglass.org/without-instagram-meta-is-screwed/)• Shows Instagram's ad revenue underpins Meta's funding for new bets (metaverse, AI).Talking Point 2: Echoes of the Mobile Battle“Facebook 2.0 will try to kill Facebook 1.0 and Google 2.0 will try to kill Google 1.0.”– Editorial, “Are Google and Meta Screwed?” (Newsletter for April 11, 2025)• Reminds us how prior platform shifts demanded reinvention—AI may require the same.Key Trend 3: AI‑Driven Disruption and the Next PlatformsSignificance: Just as mobile upended desktop, AI is redrawing the map of search, discovery, and social engagement. Meta and Google must adapt to challengers like OpenAI, Anthropic, xAI and novel features such as memory and reasoning.Talking Point 1: AI Search and Discovery Race“OpenAI, Anthropic, Perplexity, and Grok capture users for AI based search and discovery.”– Editorial, “Are Google and Meta Screwed?”• Signals user migration away from traditional search and feeds.Talking Point 2: The AI Price War and Memory Features“OpenAI slashes prices for GPT‑4.1 by up to 75%, igniting an AI price war among tech giants.”– Bryson Masse, VentureBeat (https://venturebeat.com/ai/gpt-4-1-ai-price-war-developers/)“Claude's memory feature … allows the chatbot to recall details from previous interactions.”– Michael Nuñez, VentureBeat(https://venturebeat.com/ai/claude-just-gained-superpowers-anthropics-ai-can-now-search-your-entire-google-workspace-without-you/)• Underscores how product feature arms races could outflank legacy ad models.Key Trend 4: Global Economic Realignments and Trade WarsSignificance: Tech doesn't operate in a vacuum. Tariffs and nationalism are reshaping supply chains and consumer behavior, with knock‑on effects for digital giants reliant on ad dollars and global audiences.Talking Point 1: Tariffs as a “Tectonic Plate Shift”“Trump's tariffs are part of a broader movement in the global economy which he describes as a ‘tectonic plate shift.'”– Peter R. Orszag, New York Times video (https://www.nytimes.com/video/opinion/100000010103488/trumps-tariffs-are-part-of-a-tectonic-plate-shift-in-the-global-economy.html)• Reflects how trade policy uncertainty seeps into tech investment and consumer prices.Talking Point 2: The End of Globalism vs Economic Globalization“Globalisation as we've known it for the past couple of decades has come to an end.”– Frank Furedi, Spiked (https://www.spiked-online.com/2025/04/15/the-end-of-globalism-is-nigh/)• Positions economic nationalism alongside persistent interdependence—tech firms must navigate both.Discussion QuestionsHow do the FTC's and DOJ's strategies against Meta and Google reflect a shift in government confidence and capability to regulate tech giants?Would breaking up Instagram and WhatsApp—or forcing Google to divest its ad tech—spur innovation or simply weaken platforms in an era of AI competition?In what ways has the shift from mobile to AI mirrored past platform transitions, and what lessons should Meta and Google apply as they pursue “2.0” strategies?Is the AI price war (GPT‑4.1 cuts, Claude memory, Grok features) a sustainable model for developers and businesses, or will it erode margins across the ecosystem?Do Trump's tariffs and rising economic nationalism ultimately strengthen China's tech incumbents (Huawei, Temu, Shein) more than they pressure U.S. companies? (Controversial)With visionaries like Jack Dorsey and Elon Musk calling to “delete all IP law,” how should tech firms balance creator rights against AI training needs? (Controversial) 7. How does the narrative of “the end of globalism” influence Big Tech's investment in international expansion and localized product strategies?Closing IdeasMeta and Google stand at a crossroads: legal rulings threaten their core business structures while AI challengers redefine user engagement.Their historic playbook—acquiring emerging rivals and evolving ad models—now collides with fast‑moving technology, activist regulators, and geopolitical headwinds.Final Thought: Survival for these giants will depend on agility—embracing AI as the next platform, rethinking past acquisitions, and navigating a world where borders, both digital and national, are being redrawn.Generated on 4/18/2025 with Newsletter Creator This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.thatwastheweek.com/subscribe

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NVIDIA gets caught up in the trade war, the titans of Twitter/X debate intellectual property law — and the Federal Trade Commission's antitrust case against Meta kicks off in court.We're digging into all of it on today's Tech Bytes: Week in Review. Marketplace's Meghan McCarty Carino speaks with Anita Ramaswamy, columnist at The Information, about what we learned in week one of Meta's monopoly trial.

NVIDIA gets caught up in the trade war, the titans of Twitter/X debate intellectual property law — and the Federal Trade Commission's antitrust case against Meta kicks off in court.We're digging into all of it on today's Tech Bytes: Week in Review. Marketplace's Meghan McCarty Carino speaks with Anita Ramaswamy, columnist at The Information, about what we learned in week one of Meta's monopoly trial.

Welcome back to Tank Talks! In this episode, host Matt Cohen is joined by John Ruffolo for another high-voltage rundown of the most urgent headlines at the intersection of business, politics, and innovation. As Canada stares down the barrel of a snap federal election and the U.S. economy teeters on a razor's edge, this episode is all about decoding the chaos.* Can Canada avoid a recession as political gridlock looms?* Will U.S. economic volatility derail global investment?* What happens when tech titans like Musk and Dorsey call for the end of intellectual property law?From capital gains clashes and cross-border tax traps to TikTok-fueled counterfeits and China's IP free-for-all, this conversation goes deep into the geopolitical and economic fault lines shaping our future.Election Whiplash: Personality Over Policy (00:01:00)With Canada's snap election just days away, John and Matt unpack the shift from hard policy debate to emotional brand politics. Despite mounting economic concerns like productivity slumps, unaffordable housing, and rising interest rates, voters seem more fixated on the personalities of frontrunners Mark Carney and Pierre Poilievre.John's take: We may be headed toward a minority government, but the real issue is voter apathy. If younger voters don't turn up, expect unpredictable outcomes. Meanwhile, the debates are muddying policy distinctions, making this more of a popularity contest than a strategic vote.Tax Turbulence: Capital Gains and Cross-Border Chaos (00:04:00)Capital gains are back in the spotlight on both sides of the border. In Canada, competing parties offer conflicting visions on taxation. But south of the border, new U.S. proposals could triple taxes on Canadian investors holding U.S. assets.John's take: Canada's assumption that U.S. Democrats would win and raise capital gains taxes might backfire. If Republicans take over and slash taxes instead, Canada's competitiveness could tank. The stakes? Talent flight, diminished foreign investment, and a harsh wake-up call for young Canadians evaluating life abroad.Trump, Tariffs, and the Trade War Ripple Effect (00:07:31)Trump's tariff spree continues to rattle markets. Mixed signals and shifting policies have left Canada and much of the world scrambling for economic footing.John's take: Canada has been over-indexing on Trump rather than addressing its domestic weaknesses. Blaming external forces won't fix structural problems like low productivity and weak innovation infrastructure.Recession Realities: Brace for Impact (00:11:50)With interest rates climbing and the bond market flashing red, John paints a sobering picture: a Canadian recession is not just likely, it's imminent. But not all is doom and gloom.John's take: Recessions are where great companies are made. The key is balance sheet strength and a strategy to gain market share, even at the cost of short-term profits. It's survival of the most prepared.Fear vs. Opportunity: Investing Amid Uncertainty (00:13:00)Despite market jitters, John's firm is busier than ever. He sees opportunity in volatility, just not for the faint of heart.John's take: Most people freeze in a downturn. That's a mistake. Investors and founders need to think like race car drivers, slow down strategically, but stay ready to accelerate when the track clears.The IP Debate Goes Nuclear: Musk & Dorsey Speak Out (00:17:00)In a viral exchange, Jack Dorsey and Elon Musk call for the abolishing of intellectual property laws. They argue IP stifles creativity and prioritizes lawsuits over innovation.John's take: While the system needs reform, scrapping IP entirely is extreme. Protection encourages R&D, especially for startups. The real threat? Patent trolls and uneven enforcement that favors deep-pocketed players.The Counterfeit Tsunami and China's Rule-of-Law Rebellion (00:20:50)From luxury bags to Tesla knockoffs, China's casual relationship with IP law is costing Western economies over $600 billion annually. And the stakes are rising.John's take: The U.S. once stood as a beacon for rule-based trade. Now, it's playing the same unpredictable game as China. Without global cooperation, the IP battlefield could become a free-for-all, and that's dangerous for everyone, especially startups.As elections, tariffs, and tech wars reshape the global economy, this episode is your essential guide to what's coming and how to prepare. Whether you're a founder, policymaker, or investor trying to read the tea leaves, John and Matt deliver the no-nonsense insight you won't find anywhere else.Connect with John Ruffolo on LinkedIn: https://ca.linkedin.com/in/joruffoloConnect with Matt Cohen on LinkedIn: https://ca.linkedin.com/in/matt-cohen1Visit the Ripple Ventures website: https://www.rippleventures.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tanktalks.substack.com

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

Katie Razzall talks to Katy Balls, Political Editor of the Spectator as she heads off for her new posting as Washington Editor for the Times and Sunday Times. What's it like reporting on the industrial crisis which led to the recall of parliament at the weekend? Sky's Economics Editor Ed Conway describes his difficulties gaining access to the Chinese owned British Steel factory in Scunthorpe, BBC North reporter Jo Makel has followed the story for years and former BBC political correspondent Nick Jones is a veteran of industrial reporting and author of "The Lost Tribe: Whatever Happened to Fleet Street's Industrial Correspondents?" Intellectual property law in the age of artificial intelligence under threat: At the weekend Jack Dorsey, co-founder of Twitter, posted “delete all IP law” on the social media platform, now rebranded as X. Current owner Elon Musk swiftly responded to the tweet with: “I agree." Dr Hayleigh Bosher, Reader in Intellectual Property Law at Brunel University, takes us through Dorsey's argument and what it tells us about Big Tech's changing attitude towards copyright. Amit Katwala, features editor at Wired, profiles Alexis Ohanian. The co-founder of Reddit is now a venture capitalist who has made headlines for acquiring the social media platform Digg, and joining Frank McCourt's 'People's Bid' for US TikTok. And is the UK ready for Sky's Saturday Night Live, the hit American show which will soon be on our screens ? We talk to comedian Tamar Broadbent and Caroline Frost from the Radio Times about what we can expect from the remake.Producer: Lisa Jenkinson Assistant Producer: Lucy Wai

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

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.

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.

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

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

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

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

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

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

// 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