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“Hey everybody, welcome back to When Words Fail, Music Speaks—the spot where we turn beats into‑beacons for anyone wrestling with the ups and downs of life. I'm your host, James Cox, and today we're thrilled to have a very special guest back on the show: Marq Electronica, the genre‑bending producer and vocalist who first joined us in episode 444.Since our last chat, Marq's sound has taken a wild ride. He's migrated from gritty trip‑hop and grime‑laden urban beats to a brighter, disco‑house vibe that still carries the weight of his introspective lyrics about insecurity, loss, and resilience. We'll hear him break down the story behind his new single “Be There,” a dance‑floor anthem that masks a deep craving for reassurance, and explore the darker, more personal tracks “Ether” and “Calling You,” which grapple with the loss of his father.Marq also opens up about the real‑life challenges that have shaped his journey: a fraught legal battle with his brother, a partner's serious illness, overwhelming caseloads at his day‑job, and the relentless pressure of finances. He'll reveal the turning point that finally let him laugh again—how community support, fresh gigs, and a stable job helped him step out of his shell and refocus on himself.We'll dive into his creative process, from hunting the perfect drum loop at 125 BPM to layering percussive textures that keep a track alive, and we'll hear the quirky “studio snack” confession that keeps his energy high. Plus, Mark shares what he's chasing beyond music—Tai Chi, storytelling, and a long‑overdue night of proper sleep.Stick around for his upcoming live gig in November—where he'll be spinning house tracks in the lounge of a Westlife concert arena—plus a reminder to check out his website markelectronica.com for new videos, merch, and the pre‑sale of his April 30th release.If you've ever felt stuck, unheard, or just need a rhythm to move through the dark, this episode is for you. So press play, breathe deep, and let the music do what words can't.
The Kendrick vs Drake beef has completely taken over the timeline, and hip-hop heads know that when the mic goes live, you aren't just getting the mainstream highlights—you're getting the unvarnished, barbershop-style truth. On this special sample of The Straight Dope Show (Episodes 344 and 345), hosts El Uno and TraB the Wonder, broadcasting on the Rock Da Crowd TV network, dig deep into the cultural fractures and playoff matchups currently shaking up our feeds.We start by doing a deep dive into the fallout of the Kendrick vs Drake battle, breaking down why Kendrick's "Not Like Us" served as the ultimate battle-ender. The conversation also critically analyzes Drake's historical strategy of using collaborations with artists like Rick Ross to manufacture street credibility and build cultural cachet over the years.Shifting gears to the court, we discuss how women's fashion in the WNBA is finally getting the mainstream tunnel-walk attention it deserves. Alongside the fashion talk, we reflect on the historical sexism within the sport, looking back at the absolute tragedy of original powerhouse dynasties like the Monarchs and Comets being disbanded despite their dominant championship runs.Wrapping things up with the NBA Playoffs, we praise Anthony Edwards' undeniable, infectious will to win against the defending champion Nuggets. We also break down Jalen Brunson's massive success with the Knicks, highlighting how leaving a restrictive environment in Dallas allowed him to completely take over New York.Download the Rock Da Crowd TV App to take us everywhere you go!00:01:22 - Hit-Making in Rap Beefs: Debating Kendrick and Drake's track strategies.00:13:30 - The New "Ether": Why "Not Like Us" officially ended the battle.00:20:23 - WNBA Fashion & History: Tunnel fits and disbanded legacy dynasties.00:28:29 - Playoff Mentality: Anthony Edwards' infectious will to win.00:35:49 - Brunson's Rise: Taking over New York after leaving Dallas.
Part 8 and the finale of the introductory ether series goes out with a bang. Jonathan Drake and Polymath return together to close out eight weeks of reality-dismantling physics with their most ambitious move yet: tying the whole thing together theologically. But first, eddy currents, gyroscopes that weigh less while spinning, Newton confessing gravity made no sense to him, Einstein admitting logic has nothing to do with understanding nature, and Tesla calling modern scientists sane enough to think deeply but possibly too far gone to think clearly. Then Polymath lays out the geometry of two types of antigravity craft, and Casimir Space Company gets a mention for apparently building a capacitor that recharges itself. The episode closes with Jonathan reading his original essay arguing that the ether's triadic structure, source, radiative, and ground, is the created fingerprint of the Trinity itself, and that physics done correctly leads to the same place revelation does. Eight episodes. One conclusion. Everything is theological.
How close did DeFi come to a real systemic collapse?In this episode, Camila Russo sits down with Mike Silagadze, co-founder and CEO of Ether.fi, to break down the Kelp exploit, the DeFi United rescue effort, and why Mike believes the default path could have been far worse if nobody had stepped in. He explains why the bigger lesson is not just smart contract risk, but operational security, app-layer responsibility, and the need to move past "decentralization theater."They also get into why Ether.fi wants to be "the safest place to stake," why application-layer protocols should have emergency controls, and how Ether.fi is evolving from liquid staking into a vertically integrated DeFi bank with vaults, card rails, and real-world utility.If you want to understand where DeFi security is failing, what serious builders are changing, and what the next phase of crypto products could look like, this is the episode to watch.
www.gnosticacademy.org
THE SOLO CUP has arrived. With Ripley Scott currently serving a short sentence at the KX-113 Interdimensional Detention Complex for an absolutely irresponsible amount of docking tickets, parking violations, and restricted wormhole tolls, Joeba Fett finds himself unsupervised aboard The Black Swirl. In the very first edition of The Solo Cup, Joeba digs through years of listener hails, answering Dimension Hopper questions ranging from favorite Blink songs and sci-fi movies to cryptids, conspiracies, shipboard disasters, and a few questions that probably should have remained classified. Then Joeba debuts a brand-new recurring segment:
There's a moment in midlife that many women recognize, even if they've never had the language for it.You're no longer who you used to be… but you're not fully who you're becoming either.In this episode of Message in the Middle, Marianne sits down with Dr. Sarah Andreas, artist, educator, and author of Step Into the Ether, to explore what she calls the identity gap. That in-between space where old identities begin to fall away and something new is quietly forming.Together, they unpack: What the identity gap actually feels like in real life Why reinvention is not a one-time event, but a cycle Sarah's three-phase framework: Reveal, Render, and Rise The role of creativity and art in accessing deeper self-understanding Why grief is often part of becoming someone new How to stay grounded when you're no longer who you were, but not yet who you'll be This conversation is thoughtful, honest, and deeply validating for anyone navigating change, transition, or reinvention in midlife.If you've been feeling untethered, uncertain, or quietly evolving… this episode will help you make sense of where you are and remind you that there is nothing wrong with being in the middle.Connect with Sarah: https://sarahandreas.com/https://www.soulzenstudio.com/resources Connect with Marianne:Website: Message In The Middle with MarianneMessage In the Middle Facebook Group: https://www.facebook.com/groups/422430469323847/YouTube: https://www.youtube.com/@MessageInTheMiddle/playlistsLinkedIn: https://www.linkedin.com/in/marianne-demello-smith-678b9966Email: Contact | Message In The Middle with MarianneSubscribe to Message In the Middle:Apple PodcastsSpotifyYouTubeLeave Us a Review: If you enjoyed today's episode, please leave a review and share your favorite takeaway. Your feedback helps us reach more listeners and bring you even more valuable content.Keep the conversation going - Join us for more insightful conversations in the Message in the Middle Private Facebook Community & subscribe to Message in the Middle podcas...
In this episode, host Mark Longo is joined by veteran futures broker and author Carley Garner of DeCarley Trading to break down a wild week of macro action, massive energy spikes, and some deeply unusual livestock drivers. Mark and Carley dive into the ongoing Middle East conflict's impact on energy, tracing why the crude oil rally is starting to "get old" despite the Strait of Hormuz remaining closed. They analyze the structural parallels between the current market and the 2022 price spikes, outline the best hedging strategies using micro futures and options, and explain why soybean oil is stepping up as a fascinating energy substitute. They also break down this week's top movers—including an unexpected surge in cash-settled butter—and take a look at the dark side of the tape, where crypto (Bitcoin and Ether) and grains are experiencing aggressive liquidations. Plus, Carley reveals how "screw worm" flesh-eating parasites, border closures, and a multi-year drought have fueled an historic, toppy rally in live cattle futures. In this episode, we cover: The Trading Pit: Early vs. later-stage trading strategies during geopolitical conflicts; selling expensive upside call premium in WTI and Brent. The Energy Overdrive: Why heating oil, RBOB, and soybean oil are pacing the year-to-date leaderboard. Crypto vs. Equities Divergence: Bitcoin ($BTC) and Ether ($ETH) falling out of lockstep with the tech-heavy NASDAQ. Is Bitcoin still a reliable risk barometer? Livestock & Ag Breakdown: Spotting a potential double-top in Live Cattle and how to manage downside risk using cheap options. Futures Free-for-All Q&A: Carley's take on the upcoming move to 23.5-hour equity trading and extended options hours, plus cutting through social media "hype" coins.
Gang of Four's Entertainment! is the moment post‑punk stopped being a scene and started sounding like a threat. This 1979 debut didn't just tweak punk's formula—it rewired it, turning guitars into percussion, bass into a funk‑driven anchor, and lyrics into a full‑frontal critique of capitalism, modern life, and what it even means to be “punk” in the first place.In this episode of Dig Me Out, Jason, Tim, and Chip dig into how Entertainment! won a razor‑thin community poll over The Damned, Lone Star, and Throbbing Gristle, then unpack why listeners still fight for this record decades later. They trace the band's tangled history (from Jon King and Andy Gill's art‑school origins to ever‑changing lineups), break down the album's knife‑edge guitar work and robotic‑yet‑human rhythms, and explore how songs like “Ether,” “Damaged Goods,” “At Home He's a Tourist,” and “Anthrax” smuggle political theory, biblical references, and literary nods into two‑to‑three‑minute agit‑funk blasts. Along the way, they connect the dots from late‑70s Leeds to 2000s dance‑punk, Red Hot Chili Peppers, Local H, and beyond—asking what it really means for a rock record to be influential, not just influential‑sounding.If you're into post‑punk, punk, or art‑damaged guitar music that actually swings, this one's for you. Fans of Wire, Public Image Ltd., The Clash's more experimental side, and 2000s bands like The Rapture, Bloc Party, and Franz Ferdinand will hear exactly where their favorite angular riffs and dance‑floor grooves came from.---Episode Highlights• 0:00 – Intro – How a community poll pitted Gang of Four against The Damned, Lone Star, and Throbbing Gristle, and why Entertainment! edged out the win• 5:12 – Setting the stage – Late‑70s Leeds, art school punks, and how Gang of Four stitched punk, funk, reggae, and dub into something new• 13:30 – “Ether” – Opening track breakdown: rhythmic knife‑edge guitars, politicized lyrics, and the groove that anchors the chaos• 20:45 – Rhythm as revolution – Why the band treats guitars and vocals like percussion, and how their subtractive choruses flip rock song structure on its head• 27:10 – “Natural's Not In” & “Not Great Men” – Capitalism, bodies as “good business,” biblical and literary references, and the link to Manic Street Preachers‑style lyric nerdery• 34:30 – “Damaged Goods” – The band's de facto anthem: from angular verses to that stripped‑back chorus, and how it became a template for generations of bands• 42:05 – “At Home He's a Tourist” & “5.45” – Melodica lines, TV‑age dread, and the way the record feels both 1979 and weirdly timeless• 50:20 – “Anthrax” – Dual vocals, anti‑love‑song energy, and how the band turns noise, rant, and groove into something iconic• 58:40 – Influence and aftershocks – From Flea and Red Hot Chili Peppers to The Rapture, Bloc Party, Franz Ferdinand, Local H, and Run the Jewels sampling “Ether”• 1:06:15 – Does it still work front to back? – The guys debate the 40‑minute runtime, favorite cuts, what they'd trim, and whether Entertainment! is best as full album or curated gateway• 1:13:50 – Final verdicts – Where Entertainment! lands in the Gang of Four catalog, why it's still required listening, and who this record is really for---If you love digging into the stories behind post‑punk, late‑70s rock, and the records that quietly rewrote the rulebook, hit follow and subscribe so you don't miss future episodes. Dive deeper into past shows, reviews, and polls at digmeoutpodcast.com, and if you want to help pick which albums we tackle next (and vote in the kinds of polls that put Entertainment! on the table), join the Union at dmounion.com. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.digmeoutpodcast.com/subscribe
De Ethereumgemeenschap kreeg deze week iets te verwerken. David Hoffman, een van de gezichten van de podcast Bankless en jarenlang een van de luidste pleitbezorgers van het netwerk, maakte bekend dat hij al zijn ether heeft verkocht. Zijn twijfel gaat niet over Ethereum zelf, maar over de munt. Dat verschil is belangrijk. Ethereum is het netwerk waarop applicaties, layer twee netwerken, stablecoins en getokeniseerde bezittingen draaien. Ether is het bijbehorende token. Hoffman blijft overtuigd van het netwerk, maar denkt dat de waarde daarvan vooral terechtkomt bij die applicaties en lagen eromheen, en veel minder bij de munt. De these dat ether geld zou worden is volgens hem niet mislukt, maar simpelweg uitgewerkt. Vrijwel tegelijk kwam medeoprichter Vitalik Buterin met een lange beschouwing over de koers van het project. Zijn stelling: de Ethereum Foundation moet een kleiner schip worden. Minder breedte, meer focus op de kern. Buterin wil terug naar de basiswaarden, die hij samenvat als censuurbestendigheid, openheid, privacy en veiligheid. De stichting gaat ook minder ether verkopen, en zijn eigen invloed neemt verder af, schrijft hij, wat hij naar eigen zeggen prima vindt. Dat alles speelt tegen de achtergrond van een reeks vertrekkende onderzoekers bij de stichting. We vragen ons af of beleggers in ether hier iets aan hebben, en of er überhaupt een brede consensus is over waar het heen moet. De bitcoinkoers zakte verder naar zo'n 69.000 dollar, terwijl we twee weken geleden nog op 80.000 stonden. Dat terwijl op de beurzen de grote indexen het ene na het andere record breken. Waarom volgt bitcoin die trend niet, en wat heeft de markt nodig om weer op te veren? Tot slot een blik op tokenisatie. Volgens een rapport van Citi kan de markt voor getokeniseerde beleggingen groeien van 17 miljard naar 5,5 biljoen dollar in 2030. Grote beurzen werken er volop aan. We bespreken wat getokeniseerde beleggingen precies zijn, wat het betekent voor de machtsconcentratie in de financiële wereld en hoe je er als belegger op kunt inspelen. De transitie gaat niet vanzelf: de Amerikaanse toezichthouder SEC stelde onlangs een regeling voor getokeniseerde aandelen uit nadat de beurzen in verzet kwamen. De vraag is of Europa de Amerikaanse ontwikkeling gaat volgen, en of Europese spelers dat aankunnen. Co-host is Bert Slagter. Over de podcast Cryptocurrency are here to stay. In deze wekelijkse podcast gidst Daniel Mol je door het belangrijkste cryptonieuws, langs hypes en trends, voor- en tegenstanders en winst en verlies. In het A-deel bespreken we het laatste nieuws en in het B-deel gaan we in gesprek met een gast. Van cypherpunkpioneers tot grootbanken die aan de haal gaan met stablecoins, van Bitcoin tot Ethereum tot CBDC's. Alles passeert de revue. Reageren? Stuur dan een mail naar cryptocast@bnr.nl Gasten Bert Slagter is analist bij kennisplatform Bitcoin Alpha. Links David Hoffman legt uit waarom hij al zijn ether heeft verkocht Vitalik Buterin over de toekomst en afslanking van de Ethereum Foundation The Block over de Ethereum Foundation die een kleiner schip wordt Citi voorspelt een tokenisatiemarkt van 5,5 biljoen dollar in 2030 SEC stelt regeling voor getokeniseerde aandelen uit na bezwaren van beurzen Host Daniel Mol is presentator en redacteur van de Cryptocast. Hij is sinds 2017 met Bitcoin bezig en kwam in 2021 bij het team van de Cryptocast. Redactie Daniel Mol Matthijs Damsteeg See omnystudio.com/listener for privacy information.
Welcome back to Horror Home School! Join Chris, Ash, and special guest D Note from Beyond the Ether for their review and discussion of Child's Play 2. Link tree at www.horrorhomeschool.com. Support the pod and get access to exclusive bonus content at www.patreon.com/horrorhomeschool
Fellow movie buffs Chris Holmes and Stephen Clements join for an electrifying ambulation through the gothic corridors of over 30 Frankenstein movies, past and present. Chris and Shane disagree on the merits and content of the original Frankenstein novel. Shane has thoughts on spoilers and people expecting them to apply forever. There's Iconic, and then there's iconic. What Frankenstein movie was so bad that Stephen wished his heart would have stopped while watching it, and he begs all of humanity never to watch it? For you Mage: The Ascension fans out there, Dr. Frankenstein was a Son of Ether (and so were the Ghostbusters). Do Frankenstein movies play into our fear of being eaten? Stephen manages to invoke the old military urban legend of the Ether Bunny. Chris will sit through every second of a putrid, horrible movie that he despises at least twice. Chris saw a movie in the theater using Smell-O-Vision… in 2025. Stephen has super-strong (like, super-strong) opinions about Poor Things. Did we mention that Stephen has super-strong opinions about Poor Things? Shane Plays Geek Talk Episode #290 - 5/30/2026 Like what you hear? Support Shane Plays Geek Talk on Patreon! https://www.patreon.com/shaneplays Listen to the Shane Plays Geek Talk podcast on YouTube, SoundCloud, iTunes, Google Play Music, Amazon Music, Podbean and Stitcher (and other fine, fine podcast directories). Hey, you! Yeah, you! Buy cool stuff, support Shane Plays Geek Talk with these affiliate links! Humble Bundle https://www.humblebundle.com?partner=shaneplays DriveThruRPG.com https://www.drivethrurpg.com/browse.php?affiliate_id=488512 SHOW NOTES Stephen Clements on YouTube https://www.youtube.com/@stephen.clements Frankenstein movies list we went into the podcast with: 1910 Frankenstein aka "Easy Bake Frankenstein" (according to Stephen :D ) 1931 Frankenstein 1935 Bride of Frankenstein 1939 Son of Frankenstein 1942 Ghost of Frankenstein 1944 House of Frankenstein 1957 I Was a Teenage Frankenstein 1957 The Curse of Frankenstein 1958 The Revenge of Frankenstein 1958 Frankenstein 1970 1962 The Brain That Wouldn't Die 1964 The Evil of Frankenstein 1965 Jesse James Meets Frankenstein's Daughter 1967 Frankenstein Created Woman 1968 The Astro-Zombies 1969 Frankenstein Must Be Destroyed 1969 The Horror of Frankenstein 1971 Lady Frankenstein 1972 Flesh for Frankenstein 1973 Frankenstein: The True Story 1973 Blackenstein 1974 Frankenstein and the Monster from Hell 1974 Young Frankenstein 1975 The Rocky Horror Picture Show 1981 Frankenstein Island 1984 The Bride 1985 Re-Animator 1990 Frankenstein Unbound 1990 Frankenhooker 1990 Bride of Re-Animator 1994 Mary Shelley's Frankenstein 2012 Frankenweenie 2015 Victor Frankenstein 2023 Poor Things 2025 Frankenstein 2025 Dead Lover Dungeons and Desktops: The History of Computer Role-Playing Games 2nd Edition Shane's book! Co-authored with Matt Barton of Matt Chat https://www.amazon.com/Dungeons-Desktops-History-Computer-Role-Playing/dp/1138574643/
A co-founder of OpenZeppelin said he's urging friends to exit blue chip DeFi. Isaac Patka and Mike Silagadze explain what he got right, what he got wrong, and what needs to change. ======================================================== Thank you to our sponsor! Coinbase One: Get 20% off the first year of your Coinbase One annual plan at coinbase.com/unchained. ======================================================== A co-founder of OpenZeppelin set off a firestorm on Crypto Twitter this week by declaring that he now considers all of DeFi unsafe, citing superhuman AI coding agents and the asymmetry between attackers and defenders. Isaac Patka, certifications lead at Security Alliance, and Mike Silagadze, CEO of Ether.Fi, join Laura Shin to push back on that framing — and to make the case that the real problem isn't AI finding sophisticated zero-days, it's that 90% of hacks are still embarrassing opsec failures. They cover the full threat taxonomy: opsec and parameter mistakes, contagion from bridge failures, AI-enabled social engineering, and the decentralization theater that leaves protocols unable to protect their own users. Mike makes a pointed argument for why every serious DeFi protocol needs a hard pause button and a blacklist mechanism, while Isaac explains the three-multisig architecture that should be the minimum standard. Plus, both lay out the practical question every user should ask before putting money into any protocol. Host: Laura Shin, Host / Unchained Guests: Isaac Patka (@isaacpatka) — Certifications Lead at Security Alliance & Co-founder of Shield3 Mike Silagadze (@MikeSilagadze) — CEO of Ether.Fi Learn more about your ad choices. Visit megaphone.fm/adchoices
Brief Summary:Bitcoin fell below $73,000 this morning, hitting its lowest level since April 13 as U.S.-Iran strikes rattled global markets.Brent crude jumped toward the mid-$90s, reviving inflation concerns and pressuring risk assets.Crypto liquidations totaled roughly $958.8 million over 24 hours, with longs accounting for about $897 million.Ethereum broke below $2,000 for the first time since late March, while Ether futures open interest hit a record 16.39 million ETH.BlackRock's IBIT saw $527.84 million in net outflows Wednesday, its second-largest single-day withdrawal since launch.The 11 U.S. spot Bitcoin ETFs lost a combined $733.43 million Wednesday, with more than $2 billion leaving the complex over two weeks.Samsung affiliates agreed to buy a combined 4% stake in Dunamu, operator of Upbit, for about $408 million.VanEck's tokenized Treasury fund VBILL is now live on Euler, allowing tokenized U.S. Treasuries to be used as onchain collateral.The White House is reviewing a proposed CFTC rule on prediction markets, which could shape Kalshi, Polymarket, sports, election, and event-contract markets.The CFTC and Gemini jointly asked a federal court to unwind Gemini's old $5 million settlement.Reuters reported that UniCredit warned Europe may be less able than the U.S. to contain crypto-bank shocks.A Google engineer was charged over alleged insider trading on Polymarket using confidential Google search data.U.S. Treasury operations from May 28 to June 5 could drain roughly $150 billion in liquidity, adding another macro pressure point for Bitcoin.CoinMarketCap's Altcoin Season indicator fell to 30 out of 100, showing broad altcoin weakness. Hosted on Acast. See acast.com/privacy for more information.
A co-founder of OpenZeppelin said he's urging friends to exit blue chip DeFi. Isaac Patka and Mike Silagadze explain what he got right, what he got wrong, and what needs to change. ======================================================== Thank you to our sponsor! Coinbase One: Get 20% off the first year of your Coinbase One annual plan at coinbase.com/unchained. ======================================================== A co-founder of OpenZeppelin set off a firestorm on Crypto Twitter this week by declaring that he now considers all of DeFi unsafe, citing superhuman AI coding agents and the asymmetry between attackers and defenders. Isaac Patka, certifications lead at Security Alliance, and Mike Silagadze, CEO of Ether.Fi, join Laura Shin to push back on that framing — and to make the case that the real problem isn't AI finding sophisticated zero-days, it's that 90% of hacks are still embarrassing opsec failures. They cover the full threat taxonomy: opsec and parameter mistakes, contagion from bridge failures, AI-enabled social engineering, and the decentralization theater that leaves protocols unable to protect their own users. Mike makes a pointed argument for why every serious DeFi protocol needs a hard pause button and a blacklist mechanism, while Isaac explains the three-multisig architecture that should be the minimum standard. Plus, both lay out the practical question every user should ask before putting money into any protocol. Host: Laura Shin, Host / Unchained Guests: Isaac Patka (@isaacpatka) — Certifications Lead at Security Alliance & Co-founder of Shield3 Mike Silagadze (@MikeSilagadze) — CEO of Ether.Fi Timestamps
Awaken pure awareness and stillness within you in this 12 minute guided meditation. This practice is inspired by the element of Ether and the space that is around you and within you. Yoga Nidra TT Summer Cohort is open for enrollment get all the details here and save 20% off through May 31st with code NIDRA75 Find Your Meditation Match- Take the quiz here More Mindful in Minutes Join the free 5-day Nervous system reset to overcome overwhelm Books Order Meditation For The Modern Family You Are Not Your Thoughts: An 8-Week Anxiety Guided Meditation Journal **Download 4 sample days from You Are Not Your Thoughts Here** Join MIM on Patreon here Order Meditation For The Modern Family Let's Connect Email Kelly your questions at info@yogaforyouonline.com Follow Kelly on instagram @yogaforyouonline Please rate, subscribe and review (it helps more than you know!) Learn more about your ad choices. Visit megaphone.fm/adchoices
This post contains affiliate links, which means I may earn a small commission at no extra cost to you.She wrote her debut novel at 18, self-published it, went viral on TikTok — and now she's a Simon & Schuster author with a dramatized audiobook. Lauren Roberts is living proof that passion plus scrappiness can take you very, very far.In this episode, Lauren breaks down the wild origin story behind Powerless — from pitching the idea live on TikTok to Googling her way through ISBN numbers and copyright filings. We talk about what makes the Powerless trilogy so addictive (enemies to lovers! forbidden romance! high-stakes trials!), the incredible new dramatized audiobook of Powerless, and the literary fiction authors who are quietly shaping Lauren's writing voice.Whether you're a romantasy superfan or just looking for your next unputdownable series, this one's for you.
How does a trader or investor differentiate one cryptocurrency from another? Join IBKR's Senior Market Analyst Steven Levine, along with Bitwise Asset Management's Chief Investment Officer Matt Hougan, and Head of Research Ryan Rasmussen, as they discuss a host of different crypto assets, including Bitcoin, Ether, AVAX, ADA, SOL, XRP, Bitcoin Cash, DOGE, and many others. The conversation also explores the technology behind these currencies, certain unique use cases, and an outlook on the ever-evolving digital asset industry.
Ethereum ha caído con fuerza, la narrativa parece haberse enfriado y muchos inversionistas están mirando únicamente el precio. Pero ¿y si el mercado estuviera ignorando el valor real de la red? En este episodio de La Revolución de la Riqueza, analizo Ethereum desde una perspectiva distinta: no como una simple criptomoneda especulativa, sino como una infraestructura digital que genera ingresos, flujo de caja, efectos de red y posibles oportunidades fuera del consenso. A partir del modelo publicado por VanEck, exploramos cómo se puede valuar Ethereum usando criterios similares a los de un negocio: mercado potencial, participación de mercado, take rate, flujo de caja libre, múltiplos y oferta circulante. La pregunta no es si Ethereum “va a subir”. La verdadera pregunta es: ¿qué tendría que pasar matemáticamente para que Ethereum valiera mucho más? LA INFORMACIÓN DE ESTE PODCAST NO ES UNA RECOMENDACIÓN DE INVERSIÓN Nada de lo contenido en este podcast constituye asesoría fiscal, contable, regulatoria, legal, de seguros o de inversiones, ni representa una oferta, solicitud o recomendación para comprar, vender o realizar cualquier operación con valores, esquemas de inversión colectiva, instrumentos financieros o servicios.
A new episode of The Crypto Masters Morning Brew is live. Ross breaks down the morning's biggest crypto stories in a practical brief focused on fundamentals, catalysts, and what actually matters for long-term investors. In this episode Washington targets a July 4 deadline for major crypto market-structure legislation Why the Digital Asset Market Clarity Act could become a major U.S. crypto catalyst BNY expands Bitcoin and Ether custody deeper into Abu Dhabi Ondo, JPMorgan, Mastercard, and Ripple test near-real-time tokenized Treasury redemption on XRP Ledger A $250 million social-engineering theft ring puts crypto security back in focus Bitcoin lending tries to grow up with clearer custody and more traditional credit standards The big picture: crypto's next phase may be less hype and more infrastructure — rules, custody, settlement rails, security, and institutional credit. Connect with The Crypto Masters Website: thecryptomasters.com Twitter/X: @theCryptoMS1 Newsletter: The Crypto Masters Daily Not financial advice. Always do your own research.
What if the next breakthrough in mental health didn't start in a lab — but in nature?In this episode of Research Renaissance, host Deborah Westphal speaks with Dr. Jacob Hooker, neuroscientist, entrepreneur, and CEO of Sensorium Therapeutics. Dr. Hooker shares how his journey from textile chemistry to molecular imaging led him to build a biotech company focused on nature-inspired treatments for anxiety and other neurological conditions.With nearly 20% of the U.S. population diagnosed with an anxiety disorder, the need for better treatments is urgent. Dr. Hooker explains why current psychiatric care often relies on trial-and-error prescribing — and how brain imaging, biomarkers, and computational tools may help match patients to the right treatment faster.This conversation explores the intersection of neuroscience, genetics, psychedelics, stigma, and precision medicine — and why solving even one patient's journey can create ripple effects for millions.
Where can we plainly see Faith in practice? Luke 17:5-6 -the parable of the mustard seed, 7-10- the master of the household and his slave and verses 11-19- the story of the 10 Lepers illustrate what faith is and what it isn't. Receiving, understanding, acting on personal revelation and becoming the sons and daughters of Jesus Christ is the object of our faith. Humility is the ounce of prevention from faith becoming self exalting. Obedience is the path on which the blessing of sanctification is received. As we receive a blessing from God in gratitude we glorify him. Alma 32 gives the blueprint of the experiment of faith that we may partake of the fruit of spiritual rebirth. Faith precedes the miracle (Ether 12:12). When a person walks the path of obedience hearkening to the words of Christ they undergo a transformative process even a mighty change of heart (Mosiah 5). Or in other words, the endowment of charity from God to the individual as a result of their entering into and keeping covenant with Him is manifested (Moroni 7:25-26, Mosiah 13:1-9, Mosiah 17:12-20). Phil illustrates these principles of exercising faith from the accounts of the lives of Abraham, Enoch, and Moses (Book of Jasher 9, 1 Book of Enoch 81 & 84, 2 Enoch 33:1-8, 44:1-3 and 66:1-7). "I give unto you these sayings that you may understand and know how to worship, and know what you worship"…(receiving truth and light is what changes a man or woman)..."that you may come unto the Father in my name and in due time receive of his fulness" (D&C 93:19, 27-28).Come and learn the Doctrine of Christ. TheRedemptionOfZion.org
Joshua Moss joins this episode of Stabled Up to cover how Visa is running a multi-billion dollar stablecoin settlement business, and the $6T B2B opportunity that is just opening up.Joshua leads stablecoin product strategy and go-to-market at Visa.The Rollup is where the leaders of digital assets and finance converge. Live from the financial capital of the world.Timestamps:00:00 Intro00:38 Joshua's Visa Role02:31 Visa's Tipping Point05:09 Scale: 12B Endpoints05:38 1% Goes to Payments06:29 $6T B2B Opportunity09:39 "Visa Is Cooked" Thesis10:18 Stablecoin Settlement Explained10:29 The Rain Breakdown15:47 Ether.fi Card Story20:57 Pre-Funding & Payouts24:35 Creators & Gig Workers26:52 Why Visa Dominates28:26 Agents vs. Cards30:54 Mastercard's Agent Warning32:24 Tokenization for Agents33:18 Corporate Chain Wars37:59 Brand Stablecoins Problem40:40 The Stablecoin Sandwich42:20 Reserve Management 24/744:39 Visa's Top 3Website: https://therollup.co/Spotify: https://open.spotify.com/show/1P6ZeYd...Podcast: https://therollup.co/category/podcastFollow us on X: https://www.x.com/therollupcoFollow Rob on X: https://x.com/robbieklagesFollow Andy on X: https://x.com/andyyyJoin our TG group: https://t.me/+TsM1CRpWFgk1NGZhThe Rollup Disclosures: https://goodidea.ventures
Dan Lowe is a therapist/counsellor practising in London, interested in Wilhelm Reich & all forms of psycho-physical therapy. In this episode we discuss Wilhelm Reich's book 'Ether, God and Devil'Lowe's site: https://bodyandbreathpsychotherapy.co.uk/---Become part of the Hermitix community:Hermitix Twitter - https://twitter.com/HermitixpodcastHermitix Discord - https://discord.gg/63yWMrGSupport Hermitix:Hermitix Subscription - https://hermitix.net/subscribe/ Patreon - https://www.patreon.com/hermitixDonations: - https://www.paypal.me/hermitixpodHermitix Merchandise - http://teespring.com/stores/hermitix-2Bitcoin Donation Address: 3LAGEKBXEuE2pgc4oubExGTWtrKPuXDDLKEthereum Donation Address: 0xfd2bbe86d6070004b9Cbf682aB2F25170046A996
Episode 27 told you WHY to question consensus physics. Episode 28 actually starts doing it. Jonathan Drake and Polymath, a formally trained engineer who had his physics worldview shattered on 9/11, dive into the oldest unresolved debate in science: is reality made of particles or a medium? They break down atomism versus ether theory in terms any curious person can follow, and introduce a deceptively simple test for evaluating any scientific framework: can it explain, or can it only predict? From quantum mechanics' ever-expanding cast of fictional particles to magnets doing things no particle theory can account for, to lightning, river watersheds, and Lichtenberg burns all drawing the same picture, this episode lays the actual groundwork for a series that promises to go deep. Spoiler: if your best defense of your theory is that nobody can understand it, that is not a defense.
Michael Saylor's Strategy, the world's largest public Bitcoin holder, added more Bitcoin last week as BTC traded above $77,000. Meanwhile, Bitmine added 101,901 ETH to its treasury, bringing its total digital and cash holdings to a value of $13.3 billion. Chairman Tom Lee describes Ether as a “wartime store of value” that is currently outperforming traditional stocks like the S&P 500.~This episode is sponsored by iTrust Capital~iTrustCapital | Get $100 Funding Reward + No Monthly Fees when you sign up using our custom link! ➜ https://bit.ly/iTrustPaul00:00 Intro00:10 Sponsor: iTrust Capital01:00 Super Bowl Earnings week02:30 Rate decision this week03:20 Powell Investigation over03:45 CNBC: Powell drama not over05:20 Domino #206:30 FOMC crash?07:00 Arthur Hayes: Driving BTC to $1M10:15 Nothing stops the train11:15 BTC ETF surging11:45 $MSTR moves13:15 Mike Novagratz: Retail is back14:30 ETH x $BMNR17:00 AAVE to TRON17:30 DeFi united18:00 Solana x Western Union19:15 Trump: We're leading w/crypto20:20 June#Crypto #Bitcoin #ethereum~Saylor & Tom Lee Buy More Bitcoin & ETH
In this episode of House of Learning: Understanding the Doctrine of the Temple, Meghan Farner and Cory Jensen explore the Brother of Jared as a powerful scriptural archetype for what it truly means to become a living temple of God.Drawing from the Book of Ether, this lesson reveals how the Brother of Jared's life mirrors the temple pattern of spiritual progression, covenant relationship, revelation, repentance, sacrifice, faith, and ultimately piercing the veil to encounter Jesus Christ.Viewers are invited to see scripture not merely as history, but as a living map for spiritual transformation and divine intimacy.You'll learn:✨ Why becoming the temple goes far beyond outward religious behavior ✨ How the Brother of Jared's journey mirrors the temple endowment pattern ✨ How discernment, intercession, repentance, and obedience shape spiritual maturity ✨ Why revelation requires initiative, asking, seeking, and knocking ✨ How faith grows through real spiritual wrestling and trust ✨ What it means to pierce the veil of unbelief ✨ How divine light transforms the soul from within ✨ Why Christ reveals Himself to those who pursue Him ✨ How your own life story reflects sacred spiritual archetypesThis episode also explores how the Book of Mormon functions as a temple text and why the stories preserved in scripture invite every seeker into personal encounter, transformation, and embodied discipleship. AScripturalArchetype_TheBrother…If you've ever wondered how scripture connects to your spiritual journey, what it means to become a temple, or how to experience deeper personal revelation and intimacy with Christ, this lesson offers profound insight and encouragement.
Cet épisode d'Avocats Génération Entrepreneurs a été enregistré en public, à la Maison de l'Avocat du Barreau de Paris, dans le cadre de la première Digital Week organisée par le Barreau de Paris et l'ACE.Tony Law, fondateur de la plateforme Le Juriste de Demain — dédiée à la formation des professionnels du droit sur les sujets business, technologie et soft skills — et Clarisse Berrebi, avocate fiscaliste et fondatrice des cabinets Bold et Ether, sont nos invités pour une conversation sans filtre sur un sujet qui agite toute la profession : l'impact de l'intelligence artificielle générative sur la tarification des avocats.Ce que vous entendrez dans cet épisode :Faut-il facturer moins cher parce que l'IA réduit le temps de travail ? Doit-on dire à ses clients qu'on l'utilise ? Le taux horaire peut-il encore tenir dans un modèle économique viable ?Tony Law propose une méthode concrète pour cartographier son historique tarifaire, identifier ses dossiers bien ou mal tarifés, et construire une fourchette de prix cohérente avec sa valeur réelle. Clarisse Berrebi va plus loin : elle affirme que le taux horaire était déjà condamné avant l'IA, qu'elle l'a abandonné dès 2008 — et que le vrai sujet est de comprendre ce que le client achète réellement, pas ce que l'avocat produit.La discussion aborde aussi les structures de cabinet (pyramide classique vs modèle associatif horizontal de type Square), la question de la transparence déontologique sur l'utilisation de l'IA, la convention d'honoraires comme contrat de prestation de services à construire sur mesure, et la formation des jeunes avocats dans un contexte où les tâches juniors sont progressivement absorbées par les outils génératifs.En fil rouge : comment passer d'un modèle opérationnel à un modèle stratégique — et pourquoi la valeur perçue par le client est désormais le seul critère de tarification pertinent.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.
Early bird discounts for the San Francisco World's Fair, the biggest AIE gathering of the year, end today - prices will go up by ~$500 tonight so do please lock in ASAP!From near-universal AI tool adoption inside Shopify to internal systems for ML experimentation, auto-research, customer simulation, and ultra-low-latency search, Mikhail Parakhin joins us for a deep dive into what it actually looks like when a 20-year-old, $200B software company goes all-in on AI. We cover why Shopify has become much more vocal about its internal stack, what changed after the December model-quality inflection, and why the real bottleneck in AI coding is no longer generation, but review, CI/CD, and deployment stability.We also go inside Tangle, Tangent, SimGym, which are three major AI initiatives that Shopify is doing to make experimentation reproducible, optimization automatic, customer behavior simulatable, and search and catalog intelligence faster and cheaper at scale. Along the way, Mikhail explains UCP, Liquid AI, and why token budgets are directionally right but often measured badly, why AI-written code can still increase bugs in production, what makes Shopify's customer simulation defensible, and what he learned from the Sydney era at Bing.We discuss:* Mikhail's path from running a major Microsoft business unit spanning Windows, Edge, Bing, and ads to becoming CTO of Shopify* Why Shopify is talking more publicly about AI now, and why staying at the frontier has become necessary for the company* Shopify's internal AI adoption curve, the December inflection, and why CLI-style tools are rising faster than traditional IDE-based tools* Why Jensen Huang is directionally right on token budgets, but raw token count is still the wrong way to evaluate engineering output* Why the real unlock is not more agents in parallel, but better critique loops, stronger models, and spending more on review than generation* Why AI coding can still lead to more bugs in production even if models write cleaner code on average than humans* Why Shopify built its own PR review flow, and why Mikhail thinks most off-the-shelf review tools miss the point* How PR volume, test failures, and deployment rollback are becoming the real bottlenecks in the agent era* Why Git, pull requests, and CI/CD may need a new metaphor once code is written at machine speed* What Tangle is, and how Shopify uses it to make ML and data workflows reproducible, collaborative, and production-ready from the start* Why Tangle is different from Airflow, and why content-addressed caching creates network effects across teams* What Tangent is, and how Shopify is using auto-research loops to optimize search, themes, prompt compression, storage, and more* Why Tangent is becoming a democratizing tool for PMs and domain experts, not just ML engineers* Why AutoML finally feels real in the LLM era, and where auto-research still falls short today* Why Tangle, Tangent, and SimGym become much more powerful when combined into one system* What SimGym is, why simulated customers only work if you have real historical behavior, and why Shopify's data gives it a moat* How SimGym evolved from comparing A/B variants to telling merchants what to change on a single live storefront to raise conversions* Why customer simulation is so expensive, from multimodal models to browser farms to serving and distillation costs* How Shopify models merchant and buyer trajectories, runs counterfactuals, and thinks about interventions like discounts, campaigns, and notifications* Why category-level behavior is so different across commerce, and why ideas like Chinese Restaurant Processes are showing up again in practice* Shopify's new UCP and catalog work, including runtime product search, bulk lookups, and identity linking* Why Shopify is using Liquid AI, and why Mikhail sees it as the first genuinely competitive non-transformer architecture he has used in practice* Where Liquid already works inside Shopify today, from low-latency query understanding to large-scale catalog and Sidekick Pulse workloads* Whether Liquid could become frontier-scale with enough compute, and why Shopify remains pragmatic and merit-based about model choice* Who Shopify is hiring right now across ML, data science, and distributed databases* The Sydney story at Bing, why its personality was not an accident, and what Mikhail learned from deliberately shaping AI character early onMikhail Parakhin* LinkedIn: https://www.linkedin.com/in/mikhail-parakhin/* X: https://x.com/MParakhinTimestamps00:00:00 Introduction: Mikhail Parakhin, Microsoft, and Shopify00:01:16 Why Shopify Is Talking More About AI00:02:29 Internal AI Adoption at Shopify and the December Inflection00:06:54 Token Budgets, Jensen Huang, and Why Usage Metrics Can Mislead00:10:55 Why Shopify Built Its Own AI PR Review System00:12:38 AI Coding, More Bugs, and the Real Deployment Bottleneck00:14:11 Why Git, PRs, and CI/CD May Need to Change for Agents00:18:24 Tangle: Shopify's Reproducible ML and Data Workflow Engine00:21:19 Why Tangle Is Different from Airflow00:26:14 Tangent: Auto Research for Optimization and Experimentation00:30:07 How Tangent Democratizes Experimentation Beyond ML Engineers00:33:06 The Limits of Auto Research00:36:36 Why Tangle, Tangent, and SimGym Compound Together00:37:20 SimGym: Simulating Customers with Shopify's Historical Data00:42:47 The Infra Behind SimGym00:46:00 Why SimGym Gets Better with Real Customer History00:47:30 Counterfactuals, HSTU, and Modeling Merchant Trajectories00:51:55 CRPs, Clustering, and Category-Level Customer Behavior00:53:30 UCP, Shopify Catalog, and Identity Linking00:55:07 Liquid AI: Why Shopify Uses Non-Transformer Models00:59:13 Real Shopify Use Cases for Liquid01:03:00 Can Liquid Scale into a Frontier Model?01:09:49 Hiring at Shopify: ML, Data Science, and Databases01:10:43 Sydney at Bing: Personality Shaping and AI Character01:13:32 Closing ThoughtsTranscript[00:00:00] swyx: Okay. We're here in the studio, a remote studio, with Mikhail Parakhin, CTO of Shopify. Welcome.[00:00:08] Mikhail Parakhin: Thank you. Welcome.[00:00:10] swyx: I don't even know if I should introduce you as CTO of Shopify. I feel like you have many identities. Uh, you led sort of the, the Bing ML team, I guess, uh, uh, or ads team. I, I don't know, I don't know, uh, you know, it's, uh, people va-variously refer you as like CEO or, or, uh, I don't know what that, that, that said previous role at Microsoft was.[00:00:29] Mikhail Parakhin: Uh, that was... Yeah, my previous role w- at Microsoft was the-- I actually was the CEO of one of Microsoft's business units, which included, as I, you know, as we discussed, all the things that people like to laugh about, uh, including Windows and Edge and Bing and ads and everything.[00:00:47] swyx: Yeah, yeah. What a, what a, what a wild time.You've obviously, uh, done a lot since you landed at Shopify. Uh, one of the reasons I reached out was because you started promoting more sort of internal tooling, uh, primarily Tangle, but also a lot of people have seen and adopted Tobi's QMD, uh, and obviously, I think, uh, Shopify has always been sort of leading in terms of, uh, engineering.I think more-- it's just more recent that you guys have been more vocal about your sort of AI adoption. Is that, is that true?[00:01:16] Mikhail Parakhin: Well, I think AI tools in general are fairly recent development, uh, and we've-- Shopify, you know, at this stage of its development, we're developing AI in-in-house and other, uh, building tools that use AI and, you know, interfacing with the wider AI community, uh, you know, are on the sort of the, uh, runaway trajectory.So it just did by sort of natural byproduct. We, we talk about it more also. We just, uh, just even yesterday, Andrej Karpathy was famous in tweeting about, oh, are there some, uh, ways, uh, that, that you can organize your agents to store the data and then, uh, look up the data so that you don't have to research or, or lose context every- Yestime. And a little bit tongue in cheek, I tweeted that, “Hey, we've, we've done it much earlier, and we even have different approaches, Tobi and I.” Tobi, of course, is a big fan of QMD, and I'm more of a SQL, SQLite fan. But, uh, yeah, very similar things that we've already done here. The point is, yeah, we're very dynamic, you know, explosively growing company, and we have to be at the forefront of AI adoption, obviously.[00:02:29] swyx: Yeah. Yeah. Um, you, your team kindly prepared some slides actually that we were gonna bring up on to, uh, the screen. I think I can, I can screen share, and then we can kind of go through some of the shocking stats that maybe, maybe put some numbers to what exactly is going on. So here we have, uh- An internal AI tool adoption chart.What are we looking at here? What ?[00:02:54] Mikhail Parakhin: Yeah, this is very interesting statistics. Uh, this is number of daily active workers, you know, think of, uh, DAO, basically the active users of-[00:03:05] swyx: Yeah ...[00:03:05] Mikhail Parakhin: AI tool as a percentage of all the people in the company, right? And then- Yeah ... different AI tools. And, uh, you could see two things here is that one is the green is total.Uh, green is just total. So you could see that it approaches really % by now. It's hard not to do your job now without interacting deeply, at least with one tool. You could see another interesting thing is just as many people commented in December was the phase transition when suddenly models gotten good enough that, that everything took off and started growing.Uh, it, it was many people noticed that the thing is that small improvements accumulated into this big change in Sep- December roughly timeframe.[00:03:52] swyx: Yeah.[00:03:52] Mikhail Parakhin: The other thing I would claim you could see is that, uh, CLI-based tools and tools that don't require you to look at the code becoming more popular, and you could see, yeah, various versions of, uh, Cloud Code and Codex and Pi and internal development tools taking off.Uh, exactly, yeah, uh, and blue is our River, just internal agent for coding, where tools, uh, that require IDEs such as, uh, GitHub, Copilot or Cursor, they're not exactly shrinking, but they're not growing as fast. Like, uh, red, red line is, is the IDE kind of tools. So you could see that they're, they're not experiencing as, as fast of a growth.[00:04:37] swyx: As I understand it, basically, every employee has their choice, right? Of choose whatever tool you use, and then you're just kind of doing a, a daily sur-survey or something.[00:04:47] Mikhail Parakhin: Exactly. And, uh, we- Yeah ... the, the push is to get your job done, you can use any tool, and we effectively fund unlimited tokens for everybody.Uh, we, we do, we do try to control the models that, uh, people use, but from the bottom, not from top. Like we basically say, “Hey, please don't use anything less than Opus four point six.”[00:05:09] swyx: Oh .[00:05:10] Mikhail Parakhin: Some people, some people end up using GPT five point four extra high. Some people use Opus four point six. Um, uh, you know, uh, there are some, uh, there are plus and minuses in going for full one million context window versus not.But, uh, we try to discourage people from using anything less than that.[00:05:28] swyx: Yeah, yeah. Got it, got it. Uh, I mean, uh, that's, you know... The, the next chart here, it really kind of shows the expansion and the sort of December twenty twenty-five inflection, right? That, uh, people are using a lot of tokens. I think it's also really interesting that no one was kind of abusing it in twenty twenty-five.Like it was- Had comparatively, uh, to this year, there was almost no growth. I mean, it's still like, you know, probably, probably gave fifty percent.[00:05:56] Mikhail Parakhin: Yeah. This is just a different scale. It's still exponential- Yeah, yeah ...growth at just a different- ...rate of expansion. Uh, there was inflection point, and Sean, I would claim the, the super interesting part here is that you could see that the distribution becoming more and more skewed.Yes. The top percentiles grow faster. So that means- Yeah ...the people in the top ten percentile, they, their consumption grows faster than seventy-five and so forth. So, uh, the distribution skews more and more towards the highest users, which is... I don't know what it tells me. It's like it feels not ideal, to be honest.Or maybe it's okay. We'll see.[00:06:36] swyx: Why does it feel not ideal? Is, is it because of, um, quantity over quality, or what's the concern?[00:06:42] Mikhail Parakhin: Because take it to the limit. That means, you know, if, if this rate of separation continued- Ah, yes ...a year, there will be one person consuming all the tokens. So it's just, it's kinda strange.[00:06:54] swyx: Yeah, I mean, um, uh, I, I think internal like teaching and all that, uh, will, will help sort of distribute things more widely. But in, in the early days, of course, the people who are sort of more AI-pilled will obviously find more ways to use it than the people who are less AI-pilled. Maybe let's, let's call it that.I'll just, I'll just kinda quickly, uh, pause from the, the... You know, we will go back to the rest of the slides, but I just wanna, um, review, you know, there are a lot of CTOs of, of large companies like yourself where they're all considering some kind of token budget, right? Like I think it's something, something that Jensen Huang has been talking about, where like if your 200K engineer is not using 100K of tokens every year, like they're, they're underutilizing coding agents.Of course, Jensen Huang would say that, but like it seems a very quantity over quality approach and like some, some people are basically saying like, well, is this comparable to judging engineer quality by lines of code, right? Which we also know is like kind of flawed, but better than nothing. So I, I don't know if you have like a sort of management take here on, on how to view this kind of, uh, metrics.[00:08:02] Mikhail Parakhin: Well, I mean, you're, you're baiting me. I, I like... This is my favorite topic. Uh, if you let me, I'll probably talk for two hours on just this. I have a lot of things to say. Like I do think Jensen gotten a lot of bad press saying, “Oh, of course you're, you know, this, uh, the- ...the cake seller says you don't need enough cakes.”You know? Like, of course. Uh, but, uh, I actually, uh, think that's undeserved. I think he, he's actually right. Uh, I do think- He,[00:08:33] swyx: he's directionally correct.[00:08:35] Mikhail Parakhin: Yeah. Yeah. He's directionally correct for sure. Uh-[00:08:37] swyx: Who knows what the right number is? Yeah.[00:08:39] Mikhail Parakhin: The thing that I do Uh, want to say, and this is something that we learned through trial and error and very important is like two things.One is that it's not about just consuming tokens. Uh, you can consume tokens and, and in fact, the anti-pattern is running multiple agents, too many agents in parallel that don't communicate with each other. That's almost useless, uh, compared to just fewer agents and burns tokens very efficiently. Uh, setting up the right critique loop, especially with the high quality models, where one agent does something, the other one, ideally with a different model, critiques it, uh, suggests ways to improve it, the agent redoes it with this critique and, and so it takes much longer.So people don't like it because latency goes up. You know, they, they have to wait until this debate is happening. But, uh, the quality of the code is much higher. And another thing, just since you mentioned like, look, uh, uh, yeah, the overall budget is just like, uh, lines of codes. Lines of codes are exploding for everybody right now, or partially because AI is really mover balls, but partially just because AI can write a lot more code, you know, doesn't get tired.And so you have to have to have a very strong narrow waist during PR review. Otherwise, just the number of bugs will go through the roof. It's, uh, it's this unexpected consequence of the just volume trumping everything. I would claim by now good model writes code on average with fewer bugs than, than the average human.But since they write so much more of it, like more of it will make it into production. So you have to- You still[00:10:26] swyx: have[00:10:26] Mikhail Parakhin: more bugs. Yeah. Have to have a very rigorous PR reviews, also automated of course. But, uh, yeah, that to spend a lot budget there. Like this, this for me, for me, actually, the important metric is the ratio of budget spent during code generation versus, uh, spent, uh, expensive tokens like GPT, uh, five point four Pro or, uh, uh, Deep Think from Gemini, you know, checking on PR reviews.[00:10:55] swyx: Yeah, totally. Uh, I noticed in your chart you didn't have any review tools. Do you just use like, like let's say a Claude code to review tools? Or do you have another set of review tools like the Greptiles, the Code Rabbits, uh, Devin Reviews has a review tool. I don't know if you've had those specialist review tools.[00:11:13] Mikhail Parakhin: You are a little bit jumping on my store tool right now because the graphs I was only showing public tools. Uh, uh, the-- I haven't found a good PR review tool that, that does what I think should be done. And, uh, partially my, my thinking is because it's so... It just goes against both what people feel like emotionally they prefer and, uh, some of the, uh, you know, frankly Even business models that, that the companies run.At peer review tool, uh, time, you want to run the largest models. That means, I don't know, Codex or, or, uh, Cloud Code is not gonna cut it. You need to have pro-level models if you really want to, uh, stand the tide of bots from going into production. And you need us to spend a lot of time, the models taking turns, but you don't want, like, a big swarm of, uh, of, uh, agents.So in fact, you end up in a different dual-dualistic world where you generate not that many tokens. You, in fact, generate few tokens, but it takes f-a long time because these are expensive models taking turns rather than many, many agents trying to do many things in parallel. So that's, that's why I feel like I haven't found good tools, so we are using our own for peer review for now.[00:12:33] swyx: Yeah. Yeah. I mean, uh, I think a lot of companies are building their own, uh, especially to their needs, right?[00:12:38] Mikhail Parakhin: Mm-hmm.[00:12:38] swyx: Um, I, uh, you also have a chart here going back to the slides on, uh, PR merge growth, where we're now at thirty percent, uh, month on month rather than ten percent. Uh, and also the, the estimated complexity is going up.You know, this is productivity, right? ‘Cause y- presumably there's more stuff going into the code base and more, more features getting worked on. I'm curious about the backlog, right? Like the, the, the-- I actually don't mind a pro-level model taking an hour or two hours to review my PR, because I've dealt with humans who take a week to review my PR, right?And I keep pinging them on Slack, “Hey, hey, review my PR.” So, you know, I think there's some trade-off here where, like, it still doesn't make sense.[00:13:18] Mikhail Parakhin: Exactly. That, that's exactly m-my point. Uh, that on one hand, you can tolerate longer latencies at, uh, PR. On the other hand, like right now, the real problem is not in spending time waiting for PR.It's real problem is since there's so much more code than- Yeah ... uh, probability of at least some tests failing going up, and then you, like, keep de-failing, then you have to find the offending PR, evict it, retest it without that PR, and so deployment cycle becomes much longer. Uh, so it actually, in terms of the overall time to deploy, it's total time savings if you spend more time on a longer model, like thinking for an hour, because then, then you, you don't have to spend all that time during testing and rolling, you know, rolling back the deployment.[00:14:03] swyx: Yeah, totally. That's still worth it. You know, you don't look at the individual, look at the aggregate, and look at the, the, the change in the aggregate system.[00:14:11] Mikhail Parakhin: Exactly.[00:14:11] swyx: I'm kind of curious if, like, there's this PR mentality and, like, c-- the, the, the CICD paradigm will be changed eventually. Some people are like, obviously a lot of people want new GitHub, but I even wonder if, like, Git is the problem, right?Like, is that the bottleneck? Is the concept of a PR a bottleneck? Do you guys use stack diffs? I don't know if, uh, that's a, like, a merge queue stack diff type of thing.[00:14:34] Mikhail Parakhin: We, we use, we use Stacks, we u- we use Graphite. We worked with, uh, Graphite a lot. Uh, so we use Stack, uh, PRs. I think, uh, like that's clearly the overall CICD in general, and the interaction with the code repository right now is the, clearly the sort of the, the main issue and the bottleneck for us, uh, and highest top of mind.I would say we probably need a different metaphor or different whole design of how to process it in new agentic world. I haven't seen anything dramatically better yet. I, I think everybody right now is just trying to keep their head above the water ‘cause, ‘cause there, there's so many PRs and then everybody's CICD pipelines start creaking, the, the times are increasing, the number of bugs slipping by increasing, and you have to, have to clap on down.And so we are a little bit in this situation when we need to first stabilize that story and then start thinking, hey, what, what it could be a completely different and new world, which I haven't... I know some people working on it. I haven't seen something, like anything super compelling yet, but clearly the old thing were designed for humans will need to be morphed into something new.[00:15:53] swyx: One of the thing that I, I think about is kind of like the merge conflict is basically a global mutex on the whole system, right? And in, in hu- in human organizations, we do have something like that. It's the company standup. But like, other than that, it's like it's actually fitting for us to be somewhat decentralized, somewhat plugged into one stream of information source, but somewhat lossy.Like it's okay, you know, that, that not every delivery is like atomic consistency. Like we're not dealing with a database sometimes.[00:16:27] Mikhail Parakhin: This is a very good point, uh, because since humans don't write code too fast, you know that global mutex is not too bad. Once you-[00:16:36] swyx: Yes ...[00:16:37] Mikhail Parakhin: start writing code at the speed of machine, it becomes the, you know, the bottleneck.Then what do you do? Maybe, and I can't believe I'm saying this because I, I'm long-- lifelong opponent of, uh, microservices, and I always thought that was, like, a really bad idea. And now that you're saying it, like, maybe in new guys like microservices will make a comeback, you know, because then you, you can ship things independently in tiny things and, and the managing all that complexity automatically will be much easier.I don't know. Like, we'll s-- we'll have to see.[00:17:10] swyx: Yeah. I mean, I don't know what the Microsoft or, or Shopify thing is, but I, I read this paper from Google where they have a monorepo that deploys into microservices, right? And then, uh, the other concept that I think about a lot is the Chaos Monkey concept from, from Netflix.Being able to create, like, this robust system where, um, uh, you know, you, you have the service discovery, you have the, uh, the independent, independent microservices discovery and, and, uh, you know, probably going to be a fair amount of duplication. That's how an organic system sort of scales, uh, that, that you have that...I don't know how you call it. Slack? Robustness? Depend-- uh, d-duplication. I, I, I forget the-- I, I'm-- And this-- those-- these are not exactly the terms- Hmm ... I'm looking for, but I c-can't really think of the words. Okay. I was gonna go into Tangent and Tangle. Uh, so, uh, we, we sort of discussed the overall stats that, uh, Shopify has.Uh, but, you know, I, I think some, some pretty cool stuff that you guys are working on is your ML experimentation, uh, and your, your sort of auto tr-research training pipeline. Presumably you're much closer to this one because it's, it's a sort of personal hobby of yours. How, how would you explain them in, together?I thought we have a slide that, like, uh, has the s- the system diagram.[00:18:24] Mikhail Parakhin: Yeah. Tangle first and then Tangent as a-[00:18:27] swyx: Yeah ...[00:18:28] Mikhail Parakhin: as a thing on top of Tangle. And, uh, Tangle is the third generation, I claim, of, uh, systems of, uh, running any data processing, but a bit with a skew for ML experiments, but not necessarily. Any sort of data processing tasks where you need to iterate, share, and you have scale so that you want maximum efficiency.You know how, like, normally you would work, you would-- Imagine you're a data scientist or an ML practitioner, you would get Jupiter notebooks or, or maybe you would get, uh, you know, Pyth- your Python scripts, and you would manage the data, and you produce those TSV files, and you put them in some JFS or something.Then you would notice that, oh, it has this, uh, weird missing values. You go and write another script that, uh, goes and replaces them with, uh-[00:19:20] swyx: Ah ...[00:19:21] Mikhail Parakhin: dash S. And then, then you, then you run some, some, uh, “Oh, I need to filter bots.” And so you run some light GBM model that, uh, removes the bots. And then, then you like-- And then you, you kind of like get into shape, and then you start experimenting, and you run multiple experiments, and then you're like, “Oh my God,” like, “this experiment is worse.”You undo, and you cannot get to previous result. And like, “Ah, what did I do?” Like that. Again, then, then you finally like get everything working. Then you like start throwing it over the fence to production. You, you replicate it, those things don't work, and then sometimes you like don't notice that you forgot some feature naming and the, the features don't match.But then, like imagine you, you did everything, and then six months later you're like, have to repeat it because now there's more data, or you wanted to do another pass, and you're like, “What, what did I do?” Or like, or like, “This script crashes now,” or the, “the path has changed.” And then, then you're trying to, like you spend another month just doing ar- digital archeology on your own, you know, history, right?Now multiply that by many, many teams. Now imagine you got an intern that you wanna ramp up. Now you have to show that intern, “Oh, you know, look, here's the folder, there's the scripts, you know, ask your cloud agent to do, and then, uh, to, to figure it out.” And then cloud agent does something, and then you're, “Ah, yeah, right, right, it was the wrong folder.I forgot to tell you, I actually have this other thing I forgot myself.” And, and that's, that's the, like, the daily life we all, uh, all know it, uh, if, if you're a data scientist, machine practitioner, ma- machine learning practitioner or, uh, or even like any data managing, uh, person.[00:21:00] swyx: Yeah. So I, I used to do this, uh, f- uh, on the quant finance side, uh, in, in my hedge fund.So we did this before Airflow, and then, uh, obviously Airflow came along and, uh, then more recently Dagster, uh, I would say is like, in my mind, what I would use for that shape of problem, uh, where you had to materialize assets and create a pipeline.[00:21:19] Mikhail Parakhin: And that's, that's very good segue because... So Airflow is great, but Airflow is more about you, you have something and you wanna repeatedly run it in production on schedule.It's less about you as a team developing things and being able to share, and you grabbing the standard pipeline and saying, “Hey, I wanna change this tiny little component in the huge sea of data processing, and I don't wanna-- I wanna run ten experiments on this, and I wanna do hyperparameter optimization.”All that is very hard to do with Airflow. It's very easy to do with Tango. Tango is m- more about, it's everything about group of people Running experiments, it might be agents too nowadays. Uh, running experiments cheaply, collaborating, sharing results. Uh, you don't need to understand fully. You, you grab-- you clone somebody else's experiment or somebody else's pipeline, uh, run, uh, change small piece, run it, be, like, get it to production state, and then ship in one click.So then the... You don't have to port it into any other system to, to run in production. You can just run the same experiment. It's, it's fully production ready. And, and it's, uh, it has lots of... Again, as I said, it's third generation system. The original one was, I would claim there was Ether and then, uh, at least in my career, Ether was the first, first, uh, that pioneered this type of approach.And then there was, uh, Nirvana, which, uh, uh, at Yandex, which did kind of sec-second take on this. And now this one aggregates the, the learnings from all of those and, and Airflow as well to, to get to the state where you try it, it, it feels kind of magical. Uh, ‘cause now everything is based on content, uh, hashes.So even if the version changed, but if the output didn't change, nothing is being rerun. It's very efficient. If you... Multiple people start experiment that needs the same sort of data preprocessing, it's not repeated multiple times. It's automatically done only once. If you start ten experiments that all require, you know, some, some data preparation first as the first step, and you don't have to coordinate for that.Like, you don't have to know that other people are starting it. You now, it's very easy compos-, uh, composability, any language you can u- uh, you wanna use, and it's very visual. So you can see immediately, you can edit it easily, you can assemble small things with just even mouse clicks if you want to, and, uh, share, clone.And everybody knows also it's fully kind of static in the sense that we rerun it second time, it will exactly have the same results. Like, you will never have to do digital archeology. So full versioning and everything is also there.[00:24:06] swyx: Uh, so, so people can, uh... It's open source. Go to the GitHub repo and, and, uh, check it out.Uh, and it is also a really good, uh, blog post about it. I think all these is, like, really appealing. The, the, the, the thing that I think sells me the most about it is that, um, sort of development to production transition, right? Which I think, um, a lot of people haven't really solved that, uh, strictly, right?Like, we develop really, really well in, in Python notebooks, but then, you know, that's obviously not a sort of production ready process. I think that, like, any way in which that is solved, I think is, is very appealing. Then the other thing that you mentioned, which also raised my eyebrows, was content-based caching, which you mentioned is, is, um, you know, is ve-very much, uh, um, a sort of efficiency measure about, uh, you know, just like recalculation only on, on sort of content addressing Which I think makes sense.Uh, it surprised me that the savings could be this much, but maybe I just haven't worked at your scale where there's so much duplication, uh, that people just rerun because they change a single ID upstream.[00:25:10] Mikhail Parakhin: It does, yeah. But it's not only you rerun. The, the main savings are coming from the fact that you ran it, you got your job done, and you moved on.Then- Yeah ... somebody else in some department you don't know existed runs the same task, but on a newer version.[00:25:27] swyx: Yeah.[00:25:27] Mikhail Parakhin: Like right now, you can't, in, in most of the organizations, you can't even find out about it so that you can't even measure that you're spending that time twice, right? Here- Yeah ... if everybody's on Tango, that's detected automatically and detected that the output is the same.And then for that person, all it looks like is like experiment just suddenly moved, jumped forward, right? Uh, uh- Yeah ... so that's because, because the, there's network effect of multiple people helping each other.[00:25:51] swyx: Yeah. This is one of those things where it's designed to be a platform from the beginning rather than an individual developer's tool from the beginning, right?And, and everything's gonna streams down from there. That is the sort of Tango, uh, orchestrator, and it's, it manages jobs. We've seen a few versions of this, and this is obviously, uh, uh, the sort of, uh, unique approaches that you guys have, have, uh, figured out. And then there's Tangent.[00:26:14] Mikhail Parakhin: Yeah. And Tangent is basically an automatic auto research loop that can help and kind of do your work for you.Uh- ... you know, uh, effectively, effectively, Andrej Karpathy recently popularized it with auto research. Yes. Remember he said like he was, uh, speed running this, uh... Yeah, uh, you know the story. The, here we're basically bringing the same capability into Tango so that, uh, the, uh, Tangent can analyze it. It's just an agent that can run multiple experiments, figure out what can be changed, and keep on rerunning it, keep on modifying until, uh, maximizing some goal, some loss function, whatever you need to, to achieve.And in general, I would say if you're not using auto research-like approach in whatever you do, like literally whatever you do, then you're missing out. We saw at Shopify that taking like a wildfire, anything where you can put measurements can be done dramatically better. Our-[00:27:19] swyx: Mm-hmm ...[00:27:20] Mikhail Parakhin: uh, speed of, uh, templatization HTML, uh, completely new UX tem- uh, templatization of, uh, reducing latency for liquid themes.Uh, we-- Our, uh, search, uh, recently we moved from It's hard even, uh, quote from eight hundred QPS to forty-two hundred QPS with the same quality just by pure optimizations and not a research loop that kept running and changing code in our index serve on the same number of machines, just increasing the throughput.We, we managed to improve the quality of gisting and machine learning process. Uh, you know, gisting is the prompt compression technique that[00:27:59] swyx: allows for[00:28:00] Mikhail Parakhin: lower latency and, and lower and, uh, actually higher quality slightly. So like literally whatever different walks of life, and it doesn't have to be AI related.Uh, we, we had a reduction in, uh, storage because the agents would go and find data sets that clearly are derivative, uh, and then you don't need to store things twice. You know, we, we, we found somewhat embarrassingly that it was one of the largest tables was hashing random IDs into another random ID, and we literally- Oofput only one. So it was translating, yeah, two random IDs hashed[00:28:36] swyx: into[00:28:37] Mikhail Parakhin: each. So, so[00:28:37] swyx: it has access to the code as well, so it can, it can check the, like what, what the hell is it doing?[00:28:42] Mikhail Parakhin: So there, there cou- it could be run in two levels. You, uh, you know, at the superficial level, it could just use ex-existing components and, uh, reshuffle them.Uh, you know, like you can grab- Yeah ... uh, XGBoost, and you can grab some, some Py- PyTorch module, and then can grab some, you know, grab another tools and, and combine them. At a deeper level, since Tangle is all sort of CLI based underneath you, every, every component is a wrapped really CLI, uh, call and a YAML file, it can analyze code and create new components and, and, uh, keep on iterating as well.So, so you can, you can both have quick modifications of existing t- uh, pipelines with the, with components that are already there pre-baked, or you can create new components, uh, and-[00:29:29] swyx: Yeah ...[00:29:29] Mikhail Parakhin: keep iterating on those. So auto research is, again, this is probably the, the thing I was excited the most in the last two months happening, and we see it taking like, like totally like a wildfire.Just, uh, everybody, every day, every... well, every day, every minute, I would, uh, have somebody Slack message saying, “Oh, look how much better I made it.” And, uh, it's all throughout the research.[00:29:53] swyx: Is this democratized in some way in, in the sense that like is it your ML, uh, engineers and researchers doing this, or is it your regular PMs and software engineers also have the ability to auto-- to use Tangent?[00:30:07] Mikhail Parakhin: This is an awesome question. Like, Tango in general and Tangent in particular are extremely democratizing. Like they- Yeah ... they are the main tools for- ‘Cause I don't[00:30:15] swyx: need the details.[00:30:16] Mikhail Parakhin: Yeah. Exactly. Initially used by ML and AI engineers, but then literally, as you said, PMs are like the highest user right now is one of PMs on our org, uh, Sartak and he was, he was number one by, by usage of, of this ‘cause they're just, uh, energetic and knowledgeable, and now it, it unlocks a lot of capability where you don't have to co-change code manually.[00:30:39] swyx: I mean, I mean, because it kind of cuts out the ML, ML engineer from the process because the, the, the PMs have the domain knowledge and the ability to think about, uh, from first principles about, okay, what, what results do I want? And they can-- they even have the access to the data that, that needs to go in.So it's like in some ways, like this is the magic black box that we've always wanted for, for training and, and for, uh, I guess, uh, uh, hill climbing, whatever.[00:31:04] Mikhail Parakhin: It's basically cloud code for your AI development- ... uh, situation, right? Like now, now you don't have to know exactly how algorithms work. You can just, uh, bring your domain knowledge and expertise and product knowledge and iterate within Tangent until you've gotten the results that you need.[00:31:21] swyx: In my previous roles, every time that someone has pitched AutoML, you know, I've always been like, “Uh, this is not, this is not gonna work. It's, you know, it's, it's always gonna be a flop.” Somehow it's working now. I mean, presumably the answer is now we have LLMs and it's good enough, right? It's, it's an emergent property that we can do auto research, but like, it doesn't feel that satisfying that how come we didn't do this before, right?Like we just did like parameter search and like, I don't know. That's maybe that's it.[00:31:48] Mikhail Parakhin: Yeah. Bayesian optimization and hyperparameter optimization was, was the one that, or facet of AutoML that was used very actively, which incidentally also built into, uh, Tango. But, you know, I know Patrice Simard very well, and, uh, he was such a, uh, such a proponent of AutoML, and he put, like literally spent careers trying to democratize it.Without LLMs, it just turned out to be very hard. Like it, you, you would have flexibility within certain narrow domain, but it was hard to wider scale, and now with LLMs suddenly it's like magic wand, and so suddenly everybody- ... is an AutoML expert.[00:32:28] swyx: Yeah, I, I think it's multiple things, right? Like I'm, I'm just gonna bring up the, the, the chart again, right?Like LLMs can do the monitoring very well. That is the very potentially unbounded, super unstructured. It can do the analysis very well, it can do the... Uh, and basically it is much more intelligence poured into every single step. Uh, there's maybe nothing structurally changed about AutoML, but this is just m-more intelligent and more unstructured.[00:32:53] Mikhail Parakhin: Exactly.[00:32:54] swyx: Any flaws that you've run into? Like everyone is like drinking the Kool-Aid, oh my God, time savings, uh, you know, performance improvements. Like what, what, uh, issues have you have, uh, come up?[00:33:06] Mikhail Parakhin: This is really cool. It's not a solution to all the world's problems for sure. The limitations are usually the ones I-- And this is where we get into a bit of a subjective territory.Uh, I can only share what I've, I've seen so far, and I'm sure the situation, uh, is changing, and, you know, maybe after I say it, like many people will reach out and say, “Hey, what about this?” And you don't know that, and then, then we'll be probably right. But what I've seen is auto research is very good at doing kind of obvious things that you don't have bandwidth to do or you didn't notice or maybe you're not aware of like the-- some standard practices.It is not good at doing something completely out of distribution, something that, you know, you have to think for, for multiple days, uh, and, and do something like none of this. So, so it's, uh, I, uh, set an experiment once, uh, on, on my sort of, uh, hobby thing, and I let it run for, uh, ended up, uh, several weeks run, uh, you know, it's like full production kind of scale, so it, you know, slow runs and, and it ex-- it performed in the end, uh, over four hundred experiments, and only one was successful.I'm like, “Okay, that's, that's good.” But-[00:34:18] swyx: But it saved time.[00:34:19] Mikhail Parakhin: Yeah, I saved time. Like it, it was the, that thing. Yeah, if I, if I were doing four hundred experiments myself, my betting average, as I said, would have been much higher, I'm sure. But also, first of all, it would take me like three years to do four hundred experiments.And, uh, I didn't have to do them. Like the machines were just, uh, the price of electricity did that. So, and I got one improvement, uh, that in, uh, my, my-- Honestly, when I was starting that experiment, my thinking was to go and show that, “Hey, Andre, maybe you just don't know how to optimize.” And I was super smart because in, in my pro-problem, it was optimized for many years, and it was like fully improved.Uh, and I didn't expect it, you know, auto research to find anything at all. Yet it did. So instead of making fun of Andre, I ended up, uh, a big, big supporter. Yeah, that's exactly the tweet. Yes.[00:35:10] swyx: You and Toby really, really go back and forth on-online a lot, which is really funny. Uh, think of it as, as an eval for the optimalness of the code it's running on.Uh, it's almost like it reminds me of like a Kolmogorov complexity thing, but, uh, I guess it's-- there's some optimal thing that you're trying to sort of reduce down to, I guess. Um, and so, so you, you, you know, you should congratulate yourself that you had, uh, you know, uh, ninety-nine percent, uh, optimality.[00:35:36] Mikhail Parakhin: Exactly, yeah. I think Andre really deserves a lot of credit for popularizing this approach. This is, uh, this is incredibly, I think, powerful and cool and You know, the, uh, even him, him just mentioning it led to a lot of gains in a lot of places in the industry, so we should be thankful.[00:35:56] swyx: Yeah. I think he also has a just...I don't know what it is. Like, um, you know, it, it is a simple self-contained project that people can take and apply to other things, which is, is, is one thing, but also just the name. Just like somehow no one, no one managed to call their thing auto research. It's just naming things is very important. I think that that is mostly, uh, our coverage of Tango and, and, uh, Tangents.I think obviously, you know, there's a lot of, uh, ML infra at, at Shopify that people can, uh, dive into. We're about to go into SimGym, but before I do that, any, any other sort of broader comments around this whole effort? Like where is it, where is it leading to?[00:36:36] Mikhail Parakhin: As a segue to SimGym, like all those things start composing strongly.And, uh, you could see a huge unlock when you can look at each one of the tools and, and you see, oh, they're extremely useful. Uh, Tango is useful by itself. Auto Research is useful by itself. SimGym is useful by itself. If you combine all three, you create like synergetic effect. I think that's why we wanted to even, uh, cover them today is because this is something that if you go back even, you know, five years ago, would've been unthinkable.Uh, replicating that, uh, would, would be either incredibly costly or impossible, right? With probably thousands of people are required.[00:37:20] swyx: Well, we have serverless human, uh, serverless intelligence, right? Like, uh, so yes, you do have thousands of hu-- of, of intelligences, not just, not humans. And that's, that's close enough, right?Even if they're not AGI, they're, they're close enough to do the, the task that you need them to do. And, and, you know, that's, there's plenty for, for a lot of routine work, knowledge work. Okay, let's get into SimGym. Um, this is one of those things I, I was surprised to see actually it's apparently your, uh, one of your most popular launches, and I think something that, uh, I think Sim AI, I think Yunjun Park, who did the Smallville thing, there's a very small cottage industry of people trying to do like the simulate customer thing.I think a lot of people maybe don't super trust this yet because they're like, well, obviously they would just do what you prompt them to do, right? But maybe just think, uh, tell us about the sort of inspiration or origin story.[00:38:10] Mikhail Parakhin: That's exactly actually the thing I wanted to cover, because if you don't have the historical data, all you can do is prompt a-agents in a vacuum, and they will do exactly what you prompt them to do.In fact, when I first proposed it, and this is a bit of, um, my brainchild initially, if I, I can boast, even Toby said like, “But wouldn't they, they just repeat what, what you tell them?” And, uh, but I'm like, “Yes, except Shopify has decades of history of how people made changes and what there is, uh, there, what it resulted in terms of sales.”So now what we can do is we can-- we have this... It's not, it's a noisy data. There's a small, usually websites, uh, you know, like things, things are never in isolation. It's almost never AB experiment. It's always AA experiment when there's has two meanings, but basically, you know, in different time you run two different things.But if you aggregate in general, uh, like everything together, and you apply, uh, denoising and collaborative filtering like approach, you can extract a very clear signal. And then you can optimize your agents. And that's why it took so long. It took almost a year of that optimization of just us sitting and fiddling, and, and we had this internal goals of correlation of hitting-- internal goal was to hit zero point seven correlation with, uh, add to cart events, for example.Like that, that if we run real AB test experiment, that it should, it should go and, and rep-uh, replicate, uh, same sort of success that, that humans had or lack thereof. And it, it took forever, and I don't think that's easily replicatable because, uh, like who else would have that data? You have to have this historic, you know, decades, uh, worth of data.And now, now the, like the other thing you need is in-infrastructure and the scale, right? Because, uh, w- again, what we found, uh, stat sig results, you need to run a lot of simulations, a lot of agents, and, and it's-- Those are expensive things. Like you're, you're making actions in the browser because you want a real friction.You want to, to be able to get the image like of what humans will see because you wanna, uh, detect effects like, “Hey, if I make my images larger, will I have more sales or l- uh, fewer sales?” And like usually people's intuition here, by the way, is that I increase my images, I will have more because they look nicer.You know, designers all look sparse and big images. Like usually your sales tank, right? But, but, uh, you know, from HTML, all the characters look the same only the, the size tag looks different, right? So it's very hard. So you have to take visual information, you have to run this in simulated browser environment on the big farm and, and of course, you have to have, uh, like very, very expensive model, good model with multi-model model.So all this it's-- is what's taken so long and, uh, to share my personal fail a little bit there, Sean, is like, you know, we always had this bias to-- for like large company bias. You know, we always, uh, whenever you-- we do, we're like, “Hey, we'll run an experiment,” right? We make, make a change, and we will run an experiment and then, uh, see, uh, see which one's better or like, “No, this is worse,” and most of them are worse, so you discard it and keep iterating, hill climbing.And we're like, “Oh, like smaller merchants, they cannot get stat sig results. They cannot really run experiments simply because, you know, in a week there would be not enough data for them.” So we thought from this perspective. What we didn't realize is that most people don't have A and B, they just have one thing, and they need suggestions of What A and B should be.So, uh, we first build this, hey, we run simulation on two separate teams and, and, uh, say, “Hey, which one is better?” We then morphed it into, and very recently just released it, when you have just your site, your theme, we run over it and we say, “Hey, here's what predicted values of, of, uh, uh, conversions are, and here's how we think you should modify it to increase your conversions.”And then circling back to what you started with, the proof is in the pudding. Like, if we are not correlating with reality, like, people will not be using it. And, uh, thankfully, we see literally every day more users than the previous day. So, so right now, uh, right now- It's working. Yeah. I'm-- Right now my problem is how to pay for it all because the so our major thing is how to optimize the LLMs, do distillation, how to run the headless browsers, uh, and handful browsers, uh, uh, cheaper so that we can accommodate the increase in traffic.[00:42:47] swyx: Yeah. I, I understand that you, uh, you published a lot of technical detail at GTC, so I was just gonna bring it up a little bit. I think s- was this in, in con-conjunction with some kind of GTC presentation? Or something like that, right?[00:42:59] Mikhail Parakhin: Well, we, yeah, we, we did it in several place, but yeah, we had the engineering- Yeahblog, uh, as well. Yeah.[00:43:05] swyx: Yeah. So you're running, uh, GPT OSS. Uh,[00:43:08] Mikhail Parakhin: the, this is an older version. You know, now we run multimodal model. But yeah- Yeah ... GPT OSS, we still run GPT OSS as well for[00:43:15] swyx: And then you have the VMs, and you also have browser-based. I really like this one where it you said, “It violates almost every assumption that standard LLM serving is designed for.”And then you had like, basically orders of magnitude differences between everything.[00:43:29] Mikhail Parakhin: Exactly. Which is, which, uh, which was, you know, a bit of a challenge to implement, like when, like even simple things. Uh, be- since it violates all the assumptions, for example, multi-instance GPUs, like MIGs don't work as well.But we needed, uh, to get MIG to work because, ‘cause otherwise it's way too expensive. And so we had to deal with the, yeah, with, uh, lots of infrastructure and, and, uh, work with, uh, uh, Fireworks and CentML, uh, you know, to help with optimizations and browser-based, as you mentioned. Yeah, like, takes a village.[00:44:04] swyx: Okay. So there's a lot of like, I guess, experimentation in the infrastructure so far, and you've published more or less what you have here. I guess I'm, I'm less familiar with CentML. I, I don't do, uh, that much work in this, this part of the stack. But why was it the sort of preferred instance platform?[00:44:22] Mikhail Parakhin: There are really three probably top companies. There used to be, uh, uh- Three top companies, uh, at least I was aware of that did, uh, LM optimization. You know, together Fireworks and Santa ML, not necessarily in that order. Santa ML recently got acquired by NVIDIA. Uh, what they did is if you have a model and you want to optimize it to a specific prof-- uh, profile of usage, uh, they would go and do it.And, uh, we work with, with those companies, uh, this was work particularly in with Santa ML and NVIDIA to get them the best possible results out of it. And, and sometimes you, you have to retune depending on, like sometimes you want the maximum throughput, sometimes you want minimal latency, sometimes you want like the cheapest, right?And, yeah, or some combination. And so yeah, these are people who would come and help you.[00:45:14] swyx: I see. I see. Yeah, yeah. I'm familiar with these people for the LLM, you know, autoregressive stack. But the other interesting category of these optimizers is also the diffusion people, whereas like Fel and, you know, uh, Pruna recently has come up a lot as well, which I think is like really underappreciated, uh, at least by myself, because I, I thought, oh, all the workload would be LLMs, but actually there's a lot of diffusion as well.[00:45:38] Mikhail Parakhin: Exactly.[00:45:38] swyx: There's a lot here, so I, I, I... it's, it's, uh, it's, it's, it's hard to cover. But I, I do think like people underappreciate the importance of customer simulation, basically. I think this is something that I'm candidly still getting to terms with. Uh, you know, uh, you also-- your team also like prepared this, like, really nice diagram.Uh, I, I assume this is AI generated.[00:46:00] Mikhail Parakhin: Yeah, it looks-[00:46:01] swyx: Maybe it's not.[00:46:01] Mikhail Parakhin: Yeah, it looks, uh, Gemini-ish. Yeah, but, uh, uh, honestly, I, I don't know where, where the hell they generated. It looks, look, uh, looks like it's, uh, Google. But the interesting part, John, that, that, uh, we haven't covered, but I, I wanted to mention is if your store had previous customers, rather than it's a new store, you're like new merchant just launching things, it helps tremendously in just correlation and forecast.Yeah, we take your previous, uh, customer's behavior, and we create agents that replicate those specific distribution of, of customers that you get, and then we a- we apply those to your changes, and then that, that raised raw, you know, the re-- uh, just correlation with the add to cart events or to-- with conversion or whatever it, it, it may be, uh, quite dramatically.So, uh, replicating humans in general seems like an interesting, cool challenge.[00:46:58] swyx: As a shareholder, I think this is the-- like if people are Shopify shareholders, they should really deeply understand this because this is basically the moat. The, the more you use Shopify, the more it will just automatically improve, right?Like you're, you're doing the job for them.[00:47:13] Mikhail Parakhin: Yeah, that's what we started with. Like, uh- ... uh, otherwise, if you're just a startup, I wouldn't do it if, uh, you know, if it was my startup because Without the data, it, yeah, as, as you said, it's, it's exactly the case that, uh, whatever you say in prompt, that's, that's what the agents will be doing.[00:47:30] swyx: The statistician in me wants to like really satisfy the sort of, um, statistical intuition, I guess. Um, to me it's kind of, uh, the, the word that comes to mind is, um, ergodicity. Uh, so let's say a, a customer takes this path, customer takes this path, customer takes this path, right? Um, the... In my mind, the way I explain it is like, okay, here, here's the ninety-five percentile, here's the five percentile, and here's the median, right?Um, but to me, what SimGym is potentially doing is that it can, uh, modify... It can sort of model the sort of in-between sort of journeys as well, that, that maybe are dependent on the previous states. This may be like a very RL-type conclusion where like basically the summary statistics, if you only did naive AB testing, you only have the, the statistics at, at, at a certain point, and you only judge based on the sort of overall summary statistics.But here you can actually model trajectories. Does that make sense? Or-[00:48:31] Mikhail Parakhin: That makes total sense because like, well, that, that makes even more sense that maybe even you realize bec- because-[00:48:38] swyx: Okay. Please,[00:48:38] Mikhail Parakhin: please. Yes ... we do-- Yeah. The, so internally, uh, we have this system, we talked about it briefly once at NeurIPS.We have a huge HSTU-based system that models the whole companies, uh, and their possible paths. And like- Yeah ... what you are, what you are showing, like actually at any point of time, you can either model the user's behavior or you mo- can also think about, uh, the whole merchant as a company, as the entity that acts in the world.You can model that as well. And then you can do, can do counterfactuals. In your graph, like in your blue graph, uh, if you're... Imagine in the center there, uh, somewhere in the middle, you would have an intervention. I give that person a coupon, or I don't know, I send a personal thank you card, or give a discount in some- somewhere.And then you can, uh, then you can do forward rollouts from that counterfactual. So what would have happened with that intervention or without the intervention? And you can even ch- change where that intervention, uh, in time can happen, right? Like some- where, where in this journey. So we, we do this at the Shopify scale for our merchants, and then if we notice that something that they can be fixing, like there's a strong counterfactual, like we have Shopify policy, they basically get a notification like, “Hey, we think your...something is wrong with your-” I don't know, Canadian sales. Like, uh, it looks like it's misconfigured. Here's what you need to do. Or do you think like, uh, you have to set up this campaign with these parameters? And we do that at the buyer level to literally offer discounts or cashback or, or things to buyers.So this is-- I'm getting very excited. Like this is my sort of area of, uh, interest, I guess, and, and hobby. But being able to m-model something complex as human beings or companies and model counterfactuals on it, where you can have interventions in the future and optimize when to make intervention, what kind inter-- uh, what kind of intervention to make.It's such an unlock that previously was completely impossible. Like the-- it was, it was always dreamed of, but never... Like how would you even simulate it without LLMs or HTUs? I think very, very exciting times.[00:50:59] swyx: I just wanted to, uh, to maybe illustrate this. I, I'm not the best illustrator, but I, I am a conceptual statistics guy.And y-you know, you cannot just do this. Like this is a dimensionality AB test doesn't do, right? Like, uh, because it doesn't have the, the, the change over time, uh, stochastic nature, uh, and it doesn't have the sort of contextual like... Here's all the context to this point. Um, okay, cool. Um, that's SimGym.You're, you're gonna burn a lot of tokens on this thing. But you're, you're one of the, the only scale platforms in the world that can, uh, that can do this across a huge variety of workloads, right? I'm even curious on a sort of human, uh, research level of like, well, do, does retail behave d-differently from like clothing sales?D-does that behave differently from electronic sales? I, I don't know. I don't know what else you guys... The Kardashian shoppers, do they differ from like people who buy, uh, I don't know, cars and, uh, whatever.[00:51:55] Mikhail Parakhin: Well, very different, and different sensitivities and different modes of, uh, shopping and, and different levels of what's important.Now, to-totally, you can do aggregations at, uh, at a store level. You can do aggregations at a different, uh, category level. I don't know if, uh, you know, for our statisticians among us, I couldn't believe, but we-- recently we're looking at it, and we had to bring back, uh, CRPs, you know, Chinese restaurant process.It's a, like, way of aggregating and, like, naturally grow clustering. So across... Specifically to answer questions that, uh, like you were just posing on how, how if, if buyers behave different categories. And I'm like, “I haven't seen CRP since two thousand and one.” It's[00:52:37] swyx: so What? It's so- What is... No, I haven't, I haven't seen this.No. This is not in my training. Uh,[00:52:44] Mikhail Parakhin: but, but yeah, it, uh, uh, it actually, like the, the-- there was a very popular kind of theory, popular neurips HTML circles in early two thousands, uh, kind of nice. And now, now it has practical applications, uh- Yeah ... that we were resurrecting.[00:53:03] swyx: Yeah, amazing. Uh, I, I can see, I can see how this is like a, uh, a fun job for you where you get to apply all these things.Um, yeah, yeah, so super cool. Super cool. So, okay, so, so anyone who, who knows what CRPs are and has always wanted to use them at work, uh, they should, they should definitely join Shopify. Okay, so w-we have a lot and but I, I'm, I'm being mindful of the time. I, I do wanted to, to sort of cover some other things.Um, I-I'll give you a choice, UCP or Liquid?[00:53:30] Mikhail Parakhin: Liquid. I think, I think on UCP, you know, like UCP is very important for us and, and it just we are-- UCP, we have a structured, uh, discussions, and you can read about them, and we have, uh, blog posts, and we have a big release this week, in fact, like with our catalog.Oh,[00:53:46] swyx: okay.[00:53:46] Mikhail Parakhin: Uh, yeah,[00:53:46] swyx: but- Le-I mean, we, we can, we can discuss the, the, the release briefly because we'll release this after the-- after it's already announced so whatever. There's a catalog that you guys are doing?[00:53:55] Mikhail Parakhin: Yeah. So we are, we are- Okay ... we are bringing in capabilities of a whole, uh, Shopify catalog.Basically, you now you can search for products, you can do lookups by specific ID, you can do bulk lookups when you need to bring m-multiple products. You don't need to know in ad-in advance what you're trying to show or to sell or check out. Like, you can now, you can now have this decided at, at runtime, and this big area for investment for us for both non-personalized and personalized searches, trying to provide basically a win-window into whole universe of products that are being sold everywhere in the world.And Shopify is really not exactly, but almost like a super set of any-anything being sold. Now we are bringing it into UCP and, uh, and, uh, identity linking is another big thing for us, uh, so that you, you can use, uh, like Google or whatever, whatever identity you have, uh, they're minimizing friction.[00:54:56] swyx: Yeah. So[00:54:57] Mikhail Parakhin: yeah, big release for us.But Liquid AI of course we never talk about, and the problem might be more, more aligned with what we d-discussed previously on this chat.[00:55:07] swyx: Sure. The main thing that everyone understands about Liquid is that it is inspired by Worm, and I still don't know why. I'm curious on your explanation. I think you, you, uh, you can make things very approachable.And also I think like what is the potential of like the, the level of efficiency that you get out of Liquid?[00:55:23] Mikhail Parakhin: You- we all familiar with transformer architectures. And, uh, for the longest time, there was a competing architecture, it's called the state space models. So, so Sams, uh, you know, Chris, Chris Reyes, one of the pioneers and, and lots of startups, uh, trying to make those realities.They have, uh, significant benefits being main being, uh, being much faster and, uh, lower footprint and not quadratic in length, you know, sort of, uh, linear in, in, uh, in your context length. But with state space models- They never quite made it. Like they're used-- They have, uh, certain niches when they thrive, their hybrid architectures are useful, but they never quite made it.And liquid neural networks are, you can think of them as a next step, like, uh, sort of, uh, state-space model square. It's non-transformer architecture that's more complicated than sta-state space and really difficult to code if you-- if I'm being honest. But it's, um, very efficient. It's, uh, subline-- sub, uh, quadratic in, in length of your context.Uh, it's very compact way to represent things, and that's a liquid AI company. They... Their goal is to productize it, and very often you have this need, uh, when you need to have long context and small model, and you want to have low latency. Like in general, it's basically on par with transformers, and if you do hybrids with transformers, it's, it's even better.That's why we at Shopify, when we tried multiple and we constantly try multiple models, multiple companies, we found that for small, particularly with low latency applications, when you have low latency and/or if you need longer context lengths, liquid was the best. And so we still use the whole zoo and always like obviously test and use everything, uh, every open source model and, you know, it feels l
This is where we come together in search of ideas that will one day change the world. Theorists, pulled from a hat, get sixty seconds to present their potentially revolutionary idea about pretty much anything. If it doesn't yet make sense, they go back to the kitchen. Assisted by guest scientist, Michael Hughes. Nastia conducts. Shilo jams. Live audience chats. Taped 3.13.26. Next one will be in June. Read more, watch, or sign up here: https://demystifysci.com/paradigm-drift-showBy the way, we had to edit out the last theorist from this episode. Airing the theory here is arguably a felony. We're sorry about this but do try not to break the law if you wanna end up published. Such is our moment. PATREON https://www.patreon.com/c/demystifysciPARADOX LOST PRE-SALE: https://buy.stripe.com/7sY7sKdoN5d29eUdYddEs0bHOMEBREW MUSIC - Check out our new album!Hard Copies (Vinyl): FREE SHIPPING https://demystifysci-shop.fourthwall.com/products/vinyl-lp-secretary-of-nature-everything-is-so-good-hereStreaming:https://secretaryofnature.bandcamp.com/album/everything-is-so-good-herePARADIGM DRIFThttps://demystifysci.com/paradigm-drift-show00:00 Go! 00:03:21 How Paradigm Drift Works00:08:06 Ciliate Genetic Mapping00:09:30 Deep Dive: Epigenetics, Retrotransposons & Evolution00:20:09 Integrated Reality Theory00:25:23 The Eight Foundational Properties of Reality00:33:44 Alternative Magnetic Field Theory00:37:16 Ether, Vacuum & the Invisible Medium Debate00:43:43 Particle Cohesion & the Nature of Space00:51:22 Gradient-Based Theory of Gravity00:54:12 Walter Russell, Motion & Spiritual Physics01:06:38 Edge Theory & Topological Modeling01:11:01 The Topological Score: Energy as Music01:13:06 Resonance, Emotion & the Science-Art Connection01:19:50 Vibration, Axioms & Dark Energy01:25:30 Numerology, Water & the Fine-Structure Constant01:31:27 Water's Anomalous Properties & Information Role01:36:23 Water, Earth Measurements & the Metric System01:43:47 Unified Field Dynamics: A New Theory01:47:06 Community Critique & the Push for Material Definitions02:01:16 Reflections on Paradigm Drift & the Future of Natural Philosophy#paradigm, #paradigmshift, #openmic #ParadigmDrift, #physicspodcast, #openmic #philosophypodcast MERCH: Rock some DemystifySci gear : https://demystifysci-shop.fourthwall.com/AMAZON: Do your shopping through this link: https://amzn.to/3YyoT98DONATE: https://bit.ly/3wkPqaDSUBSTACK: https://substack.com/@UCqV4_7i9h1_V7hY48eZZSLw@demystifysci RSS: https://anchor.fm/s/2be66934/podcast/rssMAILING LIST: https://bit.ly/3v3kz2S SOCIAL: - Discord: https://discord.gg/MJzKT8CQub- Facebook: https://www.facebook.com/groups/DemystifySci- Instagram: https://www.instagram.com/DemystifySci/- Twitter: https://twitter.com/DemystifySciMUSIC: -Shilo Delay: https://g.co/kgs/oty671
What happens when you question not just the government, not just the media, but the very atoms they told you everything is made of? Jonathan Drake, Chris Paul, and Polymath kick off a brand new series on ether physics by doing what any good troublemaker does: refusing to start the conversation in the middle. This inaugural episode lays the philosophical and theological groundwork for why the ether is treasonous territory. They dig into collective belief induction, the punishment-reward structure of mainstream consensus, and why scientific materialism may be building its entire castle on sand. Spoiler: if you preclude God before you even start asking questions, don't be shocked when your answers are all wrong. A primer for those ready to peel back the layers of reality, one uncomfortable question at a time.
Can a private company be trusted to decide which 40 firms get access to the world's most dangerous AI model? And separately — is the SEC's new Reg Crypto finally the framework the industry has been waiting for since 2020? Thanks to our sponsors! * As Bitcoin's application layer, Citrea gives you access to the first trust-minimized BTC on a fully programmable platform and a native stablecoin for Bitcoin, ctUSD. You can now participate in Bitcoin capital markets with lending, privacy, payments, Bitcoin yield, trading and predictions. You get expanded Bitcoin utility without sacrificing its security. Citrea mainnet is live. Put your BTC to work at citrea.xyz/unchained. * Ether.fi is giving Unchained listeners 15% cashback on food and ride apps — and that's on top of the 3% you get on everything else. Your bank is charging you to use your own money. Laura switched and loves her card! Go to ether.fi/unchained to claim your offer. The week StarkWare's chief product officer published a paper proposing a quantum-resistant mechanism for Bitcoin that doesn't require changing Bitcoin's code. The crew discuss the the threat quantum computers pose to bitcoin, which raises philosophical questions about what it means to “own” bitcoin. “Not your keys, not your coins” has long been the catchphrase — so what happens if a quantum computer wrests your keys away fro you? Plus they discuss the fact that Anthropic decided not to release its most powerful model to the public at the same time its technology is being removed from the government. What does it mean when a private company has greater capability than the U.S. government? Also, the SEC's Division of Trading and Markets quietly released major guidance clarifying when DeFi front ends need to register as broker-dealers — and Chair Atkins announced what could become the first actual crypto rulemaking in the agency's history. Katherine, Jessi, and TuongVy work through what each of these developments means for builders, lawyers, and founders navigating crypto right now — and why the question of who gets to make these calls is the same whether you're talking about AI or regulation. Hosts: Katherine Kirkpatrick Bos, General Counsel at StarkWare. Previously held senior legal roles across DeFi and centralized exchanges. Jessi Brooks, General Counsel at Ribbit Capital TuongVy Le, General Counsel at Veda Learn more about your ad choices. Visit megaphone.fm/adchoices
Sarah Elkhaldy of The Alchemist explores how plasma consciousness and ether may influence timeline shifts and humanity's evolving understanding of reality in episode 241 of the Far Out with Faust podcast.Sarah Elkhaldy is a consciousness researcher and spiritual educator best known for examining the hidden mechanics of reality through topics like simulation theory, telepathy, and the Universal Matrix. She is the host of Gaia's Mystery Teachings with Sarah Elkhaldy, where she explores the intersection of consciousness, spiritual sovereignty, and human evolution, and has built a large following through her ability to translate complex metaphysical ideas into accessible frameworks for personal and collective transformation.In this conversation, Faust and Sarah explore how the Mandela Effect, shifting timelines, and Revelation of the Method may point to deeper patterns shaping reality itself. The discussion moves through questions of free will, collective consciousness, and hidden systems of control, while also examining whether humanity is moving toward a more psychic, telepathic future — or toward another great reset.In this episode: • Mandela Effect & Timeline Shifts: What if those “false memories” aren't mistakes at all, but evidence that reality itself is changing beneath our feet? • Revelation of the Method: Why power structures may be required to show their hand in advance, and how recognizing the pattern changes the game. • Plasma Consciousness: The hidden force Sarah says underlies matter itself, and why it could redefine how we understand existence. • Ether & the Fifth Element: The missing element ancient traditions understood, and how it may connect human consciousness to the fabric of reality. • Reptilian Energies: Sarah unpacks how reptilian influence is understood in esoteric frameworks, and whether these forces operate through consciousness rather than physical form. • Free Will vs. Determinism: Are we making real choices, or navigating a reality shaped by forces we rarely perceive? • Organic vs. Synthetic Resets: From lost civilizations to modern collapse narratives, what kind of reset may already be unfolding now? • Psychic Evolution: Why Sarah believes humanity is becoming a more telepathic, homoluminous species — and how that shift could transform consciousness itself.If reality is far more fluid than we've been taught, what happens when humanity begins to consciously reshape the timelines ahead?00:00:00 – Introducing Sarah Elkhaldy00:02:00 – Scientists disappearing and hidden breakthroughs00:02:36 – Plasma: the most misunderstood force in the universe00:03:44 – “Time is an illusion” — science catching up00:04:04 – Plasma as the spiritual substrate of matter00:05:00 – Alchemy explained: layers of materialization00:06:13 – Plasma as higher-order “water” in alchemical systems00:09:28 – Plasma as the fabric of reality and density00:10:44 – Reptilian phenomena: literal vs energetic00:12:03 – Ritual abuse, energy embodiment, and influence00:13:04 – Reptilian energies vs human psychology00:14:00 – Auras, perception, and energetic fields00:17:00 – Free will vs control systems00:17:58 – Timeline shifts and Mandela Effect00:18:42 – What timeline splitting actually means00:20:20 – How to recognize timeline shifts00:21:01 – CERN, portals, and energetic markers00:24:00 – Consciousness and decision-based timelines00:28:34 – AI as a timeline-shifting force00:30:00 – Programming reality through awareness00:32:04 – Free will vs predeterminism balance00:40:00 – Energetic alignment and reality creation00:45:00 – Collective consciousness shifts00:50:00 – Objective vs subjective reality layers00:55:00 – Heaven/hellwe'd love to hear from you
The rapid evolution of the crypto landscape is reshaping how investors approach diversification, risk and opportunity. As digital assets like Bitcoin and Ether move from the fringes to the mainstream, their unique characteristics—decentralization, scarcity and volatility—are prompting new conversations about portfolio construction. Regulatory milestones, such as the Genius Act, are bringing greater legitimacy and structure to the market, while innovations like stablecoins are unlocking new possibilities for seamless, secure transactions. In this episode, join the Market Insights team's Jack Manley, Global Market Strategist, and Brandon Hall, Research Analyst, as they share expert perspectives on navigating the complexities and opportunities of the modern crypto market Watch the video version on YouTube. Subscribe to the Notes on the Week Ahead podcast for more insights from Dr. David Kelly: Apple Podcasts | Spotify
Why ETH outperformed Bitcoin this past week, what's really behind the prediction market activity during the Iran situation, and what comes next for institutional crypto adoption. --- Thank you to our sponsors! Ether.fi — 15% cash back on food and rideshare apps, 3% on everything else, borrow at 4% or less Citrea — Trust minimized BTC, native stablecoin CT-USD, Bitcoin capital markets --- A tenuous Iran ceasefire sent oil prices tumbling this past week, and crypto responded before any other asset class. Bitcoin climbed to around $72K, Ethereum outperformed with 6.7 to 7% gains in 48 hours, and billions poured back into ETFs after months of withdrawals. But amid the rally, uncomfortable questions are surfacing: who profited from suspicious prediction market bets placed just before the ceasefire announcement? Are Middle Eastern governments and corporations now using Bitcoin as actual settlement infrastructure? And if the Clarity Act passes without allowing yield-bearing stablecoins, has the banking lobby won? Kavita Gupta, founder and general partner at Delta Blockchain Fund, sits down with Steven Ehrlich to work through a week of whipsawing markets, fragile geopolitics, and structural shifts that could define where crypto goes from here. Host: Steven Ehrlich, Head of Research, SharpLink Guest: Kavita Gupta, Founder & General Partner at Delta Blockchain Fund Links: Ceasefire, Markets & Institutional Flows: Crypto Markets Rebound After Iran-Israel Ceasefire Deal (Unchained) Bitcoin ETFs Record $5 Billion in Daily Volume as Inflows Top $870 Million (Unchained) Crypto Adoption in MENA 2025: Crisis, Adaptation, and Growth (Chainalysis) Prediction Markets & Insider Trading: DEX in the City: Why Prediction Market 'Insider Trading' Isn't Illegal — Yet (Unchained) DEX in the City: How Prediction Markets Pose a National Security Risk (Unchained) Trading Volumes on Prediction Markets Will Drop After the November Election. Will New Market Entrants Still Attract Users? (Unchained) DOJ and CFTC Drop Investigations Into Polymarket: Report (Unchained) Clarity Act & Stablecoin Regulation: Bessent Presses Senate on Clarity Act, Labels Resistant Crypto Leaders 'Nihilists' (Unchained) Circle Stock Plunges 20% as Clarity Act Draft Threatens Stablecoin Yield (Unchained) Treasury Secretary Bessent Presses Congress to Pass CLARITY Act (The Hill) Bessent Ramps Up Pressure on Congress to Pass CLARITY Act (CoinTelegraph) Learn more about your ad choices. Visit megaphone.fm/adchoices
The basis trade paid 15–30% near risk-free for years. Options couldn't compete. Then 10/10 happened. ======================================================== As Bitcoin's application layer, Citrea gives you access to the first trust-minimized BTC on a fully programmable platform and a native stablecoin for Bitcoin, ctUSD. You can now participate in Bitcoin capital markets with lending, privacy, payments, Bitcoin yield, trading and predictions. You get expanded Bitcoin utility without sacrificing its security. Citrea mainnet is live. Put your BTC to work at citrea.xyz/unchained. Ether.fi is giving Unchained listeners 15% cashback on food and ride apps — and that's on top of the 3% you get on everything else. Your bank is charging you to use your own money. Laura switched and loves her card! Go to ether.fi/unchained to claim your offer. ======================================================== For years, the basis trade and token-launch points farming crowded out options as a yield tool in crypto — not because options were inferior, but because the alternatives were simply too easy and too lucrative. That changed on 10/10. With the basis trade effectively dead and altcoin valuations cratered, a window has opened for onchain options to compete for capital in a way they never could before. Nick Forster, CEO of Derive (formerly Lyra), has been building toward this moment for five years. He joins LTR, venture investor at Cosmos, who has tracked the full graveyard of failed options DEXes — Opyn, HEGIC, Ribbon, Dopex, Strike — and still believes this time is different. The question isn't whether crypto options will scale. It's whether the infrastructure is finally ready. Host: Laura Shin, Host / Unchained Guests: Nick Forster, CEO and Founder, Derive LTR, Venture Investor, Kosmos Learn more about your ad choices. Visit megaphone.fm/adchoices
Anthropic's new model is too dangerous to release publicly. It's already found 20 zero-days. Kain, Taylor, and Austin want to know when it finds the first one in a smart contract. Thank you to our sponsors! MultiChain Advisors is an emerging technology growth firm that has helped create over $50 billion in enterprise value for more than 80 clients, like Pyth, Moonpay Commerce, and Wormhole. They're the partner you want when you're navigating markets and trying to break out from the noise. They help navigate TGEs, go‑to‑market, BD and partnerships, capital markets advisory, PR, media placements, KOL activations and more, driving execution from launch to scale. Visit multichainadv.com. Bitcoin's application layer, Citrea, launched its mainnet, expanding Bitcoin's utility to privacy, lending, BTC yields, and more. Citrea enables: cBTC: The first trust-minimized Bitcoin on a fully programmable platform. ctUSD: A native stablecoin for Bitcoin, allowing for unified liquidity. Bitcoin Capital Markets bringing demand, and utility to the Bitcoin Network. Explore the Citrea Ecosystem. Ether.fi is giving Unchained listeners 15% cashback on food and ride apps — and that's on top of the 3% you get on everything else. Your bank is charging you to use your own money. Laura switched and loves her card! Go to ether.fi/unchained to claim your offer. Anthropic's Mythos model is so capable that the company restricted access to 12 partners and a $100 million compute budget rather than releasing it publicly. It has already identified 20 zero-day vulnerabilities in decades-old software. Now the question over DeFi: if Mythos turns its attention to smart contracts, what survives? The Balancer V2 hack rattled assumptions about immutability as a security guarantee. Kain Warwick, Taylor Monahan, and Austin Griffith of the Ethereum Foundation work through what autonomous AI hacking means for protocols built to be unhackable, why skill files are the sleeper development in the agent stack, how a degen farming bot locked funds in an Aerodrome gauge through a single wrong NFT transfer, and what Anthropic's 89% uptime tells you about the infrastructure running the most powerful AI on earth. Hosts: Kain Warwick, Founder of Infinex and Synthetix Taylor Monahan, Security Expert Guest: Austin Griffith, Ethereum Foundation Learn more about your ad choices. Visit megaphone.fm/adchoices
Join us for a deep dive into cutting-edge topics ranging from quantum sensing and secret technologies to geopolitical strategies and UFO phenomena. Discover the latest theories, scientific explanations, and behind-the-scenes insights that challenge conventional narratives. In this episode: Exploration of ghost murmurs and their potential ties to quantum physics and ether theories The use of quantum magnetometry to track human heartbeat signatures over long distances The covert application of nanotech and regenerative graphene suits in military precision tools Discussions on synthetic telepathy, mind downloading, and neural interface experiments Analysis of global geopolitical tensions, energy control, and military strategies involving the Strait of Hormuz Debunking moon landings and analyzing anomalies in space agency footage Uncovering secret treaties, black ops, and the truth behind ET interactions with foundational government agencies Timestamps: (00:02) - Welcome and show update on schedule changes (00:28) - Challenges in internet connectivity from Easter Island (01:15) - Possibility of renting programmable satellites that follow individuals (02:02) - Concept of nuclear-powered, autonomous drones following and tracking humans (02:35) - Introduction to the week's main themes: Ghost Murmur & Synthetic Telepathy (03:03) - Links between heartbeat signatures and protective cryptographic measures (03:32) - Overview of quantum sensing tech involving Josephson junctions and ether physics (07:26) - Military nanotech, super soldiers, and regenerative graphene suits (07:57) - Real-time biomarker monitoring and AI integration in military operations (09:16) - Quantum magnetometry and its limits over long distances (10:38) - The eerie parallels between 90s UFO narratives and current secret tech (14:13) - Classified projects that listen to chest pulses for surveillance (16:15) - Synthetic telepathy: mind-to-mind communication through neural interfaces (18:01) - Whistleblower insights on internal monologue signals and EMF projects (20:47) - Psyops, downloads, and alleged alien communication deceptions (24:08) - Voice replication and AI-generated audio for covert operations (27:57) - Disclosures of secret treaties, Nazi alliances, and secret ET agreements (33:43) - Government revelations about crackdowns on UFO disclosures and secret agendas (37:04) - The role of ether physics in modern physics and secret classified research (44:08) - Hidden surrender treaties and the control of extraterrestrial interactions (69:32) - Strategic energy and military maneuvers in global geopolitics (75:52) - The build-up and suppression of truth about space missions and moon landings (83:18) - The call for independent action against global elite control (87:00) - Evidence of water contamination in fuel supplies and covert economic sabotage (89:28) - The impact of propaganda, social engineering, and influence from mainstream narratives (91:05) - The awakening of political awareness through media figures (102:20) - The German political stance against migration and neocolonial agendas (103:53) - The deliberate flooding of Europe with migrants to influence political outcomes (106:46) - Evidence of covert medical interventions and government cover-ups (108:38) - Final thoughts on disinformation, government neglect, and the ongoing fight for truth To gain access to the second half of show and our Plus feed for audio and podcast please clink the link http://www.grimericaoutlawed.ca/support. For second half of video (when applicable and audio) go to our Substack and Subscribe. https://grimericaoutlawed.substack.com/ or to our Locals https://grimericaoutlawed.locals.com/ or Rokfin www.Rokfin.com/Grimerica Patreon https://www.patreon.com/grimericaoutlawed Support the show directly: https://open.spotify.com/show/2punSyd9Cw76ZtvHxMKenI?si=ImKxfMHgQZ-oshl499O4dQ&nd=1&dlsi=4c25fa9c78674de3 Watch or Listen on Spotify https://grimericacbd.com/ CBD / THC Tinctures and Gummies https://grimerica.ca/support-2/ Our Adultbrain Audiobook Podcast and Website: www.adultbrain.ca Our Audiobook Youtube Channel: https://www.youtube.com/@adultbrainaudiobookpublishing/videos Check out our next trip/conference/meetup - Contact at the Cabin www.contactatthecabin.com Other affiliated shows: www.grimerica.ca The OG Grimerica Show Join the chat / hangout with a bunch of fellow Grimericans Https://t.me.grimerica grimerica.ca/chats Discord Chats Darren's book www.acanadianshame.ca Eh-List Podcast and site: https://eh-list.ca/ Eh-List YouTube: https://www.youtube.com/@TheEh-List www.Rokfin.com/Grimerica Our channel on free speech Rokfin Leave a review on iTunes and/or Stitcher: https://itunes.apple.com/ca/podcast/grimerica-outlawed http://www.stitcher.com/podcast/grimerica-outlawed Sign up for our newsletter http://www.grimerica.ca/news SPAM Graham = and send him your synchronicities, feedback, strange experiences and psychedelic trip reports!! graham@grimerica.com InstaGRAM https://www.instagram.com/the_grimerica_show_podcast/ Purchase swag, with partial proceeds donated to the show www.grimerica.ca/swag Send us a postcard or letter http://www.grimerica.ca/contact/ ART - Napolean Duheme's site http://www.lostbreadcomic.com/ MUSIC Tru Northperception, Felix's Site sirfelix.bandcamp.com Resources & Links: Quantum sensing with Josephson junctions Ether physics and vacuum waves Nanotech and regenerative graphene suits Synthetic telepathy research Strait of Hormuz geopolitical analysis Moon landing anomaly evidence Secret treaties & ET agreements Disaster map with new features Grok AI image generator UK and Canadian political developments UFO whistleblower testimonies
The Drift hack wasn't a one-off exploit. It was a patient operation spanning months, with nation-state actors working the conference circuit. Then Circle let the hackers take the money. Bitcoin's application layer, Citrea, launched its mainnet, expanding Bitcoin's utility to privacy, lending, BTC yields, and more. Citrea enables: cBTC: The first trust-minimized Bitcoin on a fully programmable platform. ctUSD: A native stablecoin for Bitcoin, allowing for unified liquidity. Bitcoin Capital Markets bringing demand, and utility to the Bitcoin Network. Explore the Citrea Ecosystem. http://citrea.xyz/unchained =============================================================================== Ether.fi is giving Unchained listeners 15% cashback on food and ride apps — and that's on top of the 3% you get on everything else. Your bank is charging you to use your own money. Laura switched and loves her card! Go to http://ether.fi/unchained to claim your offer. =============================================================================== The Drift hack looked like a typical smart contract exploit until the postmortem revealed something far more elaborate: a six-month DPRK intelligence operation involving in-person social engineering at crypto conferences, fully constructed professional identities, and a $1 million deposit to build trust. Then, after $232 million in USDC was stolen, Circle declined to freeze the funds while attackers bridged them across chains for six hours during business hours. Michael Lewellen from Turnkey and Amanda Wick from VerifyVASP tackle what the Drift compromise teaches about operational security in crypto, why Circle's decision raises hard questions about stablecoin issuer responsibility, and whether the legal framework is forcing companies to choose between compliance and doing what's right. Host: Laura Shin, Host / Unchained Guests: Amanda Wick, Head of Americas at VerifyVASP Michael Lewellen, Head of Solutions Engineering at Turnkey Learn more about your ad choices. Visit megaphone.fm/adchoices
Will SEC guidance stick around if the administration changes? Commissioner Peirce and Sumeera Younis of the Crypto Task Force answer. Thanks to our sponsors! * Citrea — Bitcoin changed how money works. Citrea changes how Bitcoin scales. Trust-minimized BTC on a fully programmable platform with native stablecoin CTUSD. Get started at citrea.xyz/unchained * Ether.fi — 15% cash back on groceries, restaurants, and rideshares. 3% on everything else. Borrow against holdings at 4% or less. Earn up to 8% APY. Go to ether.fi/unchained. * Multichain Advisors — Emerging technology growth firm with $50B+ in enterprise value created for 80+ clients. TGEs, go-to-market, BD, capital markets advisory, and more. Visit multichainadv.com. The SEC's Crypto Task Force has spent over a year rebuilding a relationship the industry feared was broken for good. Commissioner Hester Peirce and task force Chief of Operations Sumeera Younis explain how the SEC prioritizes crypto policy questions, why tokenization leads the agenda, and what happens to this guidance when the administration changes. They tackle the gap between large players shaping policy and small builders who want clear instructions, reveal how the SEC and CFTC coordinate to prevent jurisdictional conflicts, and argue that smart contracts and AI could reinvent securities disclosure. Hosts: Katherine Kirkpatrick Bos, General Counsel at StarkWare. Previously held senior legal roles across DeFi and centralized exchanges. Jessi Brooks, General Counsel at Ribbit Capital TuongVy Le, General Counsel at Veda Guests: Commissioner Hester Peirce, U.S. Securities and Exchange Commission Sumeera Younis, Chief of Operations, SEC Crypto Task Force Learn more about your ad choices. Visit megaphone.fm/adchoices
Raised in Chicago: Alice Bradley on Family, Work, Tradition, and the Kind of Love That Shows Up | Conversations with a Chiropractor Episode Description In this episode of Conversations with a Chiropractor, Dr. Stephanie Wautier sits down with her mother-in-law, Alice Bradley, for a conversation that feels like stepping into an older version of America through somebody who actually lived it. Alice was born in Chicago in 1942, and what unfolds here is not just a life story, but a chain of memories about family closeness, responsibility, work, food, resilience, and the strange way ordinary details become priceless later. Alice talks about growing up on the north side of Chicago in a multigenerational household, being the oldest of three, and carrying responsibility early. She remembers streetcars, ether anesthesia, walking her younger sister home for lunch from school, and a childhood where her mother always worked and family members lived together because that's just what families did. From there, the episode opens into a wider story. Alice reflects on her early working years in downtown Chicago, her time in modeling and promotional work, and the surreal contrast between a glamorous paycheck and the rough streets she had to walk through to get there. She also talks about food and heritage in a way that says more than a family tree ever could, from learning Italian cooking through family connections to remembering homemade ravioli drying all over the house at Christmas. What really gives this episode its backbone, though, is Alice's worldview. Near the end, she distills a lifetime into a few plainspoken truths: work hard for what matters, keep setting goals, look for the good in people first, and if you love someone, tell them, then back it up with action. In This Episode, Discover What it was like growing up on the north side of Chicago in the 1940s and 1950s Alice's memories of streetcars, old-school hospital care, and early city life How being the oldest child shaped her sense of responsibility from a very young age The multigenerational family structure she grew up in, and what that meant day to day Her parents' work lives, including her mother's long years working outside the home Alice's early jobs in downtown Chicago, including beauty work and modeling The danger, glamour, and strange normalcy of commuting into the city for high-paying gigs How Italian cooking became part of her family life even without Italian ancestry Holiday traditions that defined her childhood, from lamb cakes to homemade ravioli The traditions she carried into her own home and passed down to her children Her reflections on work ethic, character, love, and saying what you mean Stay Connected & Explore Connect with Conversations with a Chiropractor: Follow Us on YouTube: http://www.youtube.com/@ConversationswithaChiro Follow Dr. Stephanie on Facebook: https://www.facebook.com/wautierwellness Email for show-related inquiries and sponsorships: drstephaniewautier@yahoo.com Credits Podcast production by Brand|Sound. Start your podcast journey by emailing brandsoundpodcasts@gmail.com. Chapters 00:00 Introduction to Conversations with a Chiropractor 00:40 Meet Alice Bradley 01:00 Streetcars, tonsils, and childhood memories in Chicago 02:10 Ether anesthesia and her father's Army service 03:15 Being the oldest of three in a working family 04:00 A multigenerational home and early family responsibility 05:25 Walking her sister home from school and caregiving as a child 06:35 Her parents' jobs, Baxter, and her father's work history 08:10 Losing her father young and looking back on family life 09:05 Leaving school, going to work, and heading downtown 10:00 Modeling, beauty work, and Chicago convention life 11:00 Dangerous commutes and the contrast of city glamour 12:20 What the money was like, and why the job mattered 14:00 Learning Italian cooking through family ties 15:25 German roots, home cooking, and what stayed with her 16:00 Easter baskets, lamb cakes, and holiday traditions 17:00 Missing her mother, but understanding why she worked 18:10 First nylon stockings and Christmas in the city 19:00 Homemade ravioli, sauce, and the family Christmas table 21:00 Marriage, children, and bringing traditions into a new home 22:00 Christmas Eve pajamas and blending city and farm family life 24:00 The birthday surprise that became a new sibling 25:20 Advice for grandkids, listeners, and the next generation 26:00 Work hard, keep going, and set the next goal 27:00 Look for the good in people 27:40 If you love someone, say it, then prove it
A nation state hacked a startup and won. The hosts debate who's liable, what's fixable, and what isn't. --- Thank you to our sponsors: Bitcoin's application layer, Citrea, launched its mainnet, expanding Bitcoin's utility to privacy, lending, BTC yields, and more. Citrea enables: cBTC: The first trust-minimized Bitcoin on a fully programmable platform. ctUSD: A native stablecoin for Bitcoin, allowing for unified liquidity. Bitcoin Capital Markets bringing demand, and utility to the Bitcoin Network. Explore the Citrea Ecosystem. Ether.fi is giving Unchained listeners 15% cashback on food and ride apps — and that's on top of the 3% you get on everything else. Your bank is charging you to use your own money. Laura switched and loves her card!Go to ether.fi/unchained to claim your offer. ---- North Korea just pulled off the largest DeFi hack of 2026, draining $285 million from Drift protocol in 12 minutes through a six-month social engineering campaign that included face-to-face meetings at industry conferences. Circle had a six-hour window to freeze $232 million in USDC moving through its own bridge and didn't act. Meanwhile, Iran's IRGC is reportedly collecting crypto tolls at the Strait of Hormuz in USDT via Tron, and the token market is cracking under the weight of 750,000 issuances since 2020 with the median token down 80% from peak. Ram, Austin, and Chris confront the liability question for stablecoin issuers, whether DeFi's security model can survive nation-state attackers, why Chris is calling for licensed "neoprivateers" to recover stolen funds, and what Franklin Templeton's acquisition of 250 Digital signals about where institutional capital is headed. Hosts: Austin Campbell, Host of Bits + Bips, Zero Knowledge Consulting Ram Ahluwalia, Co-Host, CEO of Lumida Chris Perkins, Co-Host, President of CoinFund Learn more about your ad choices. Visit megaphone.fm/adchoices
A full house of Badlands hosts dives into a wide ranging and unpredictable conversation that blends humor, skepticism, and deep questioning of mainstream narratives. From debates about nutrition and whether vitamins are actually helpful, to exploring unconventional ideas about how the human body really works, the crew leans into first principles thinking and challenges long held scientific assumptions. The discussion takes a fascinating turn into alternative theories like ether physics and the idea that the heart may function more as a regulator than a pump. Along the way, the hosts reflect on how accepted “truths” are formed, and what happens when you go back and actually examine the original research behind them. Equal parts entertaining and thought provoking, this episode captures the spirit of curiosity and controlled chaos that defines OnlyLands.
Originally Aired April 2, 2026: Not afraid to eff ugly. Catching up on sleep while working. Everything you wanna know about getting a GWI. Listen & subscribe to the show on Apple Podcasts, Spotify or Amazon Music. For more, visit https://www.93x.com/half-assed-morning-show/Follow the Half-Assed Morning Show:Twitter/X: @93XHAMSFacebook: @93XHAMSInstagram: @93XHAMSEmail the show: HAMS93X@gmail.com See omnystudio.com/listener for privacy information.
This week Jeremy welcomes Jeff Smith of Jerome's Dream. On this episode, Jeremy and Jeff talk FM Radio, Nine Inch Nails, 120 Minutes on MTV, Green Day basslines, stage technical difficulties, Baby Gopal, Jamey Jasta, being outcasts in a local scene, sharing vans, the worst tour routing of all time, and so much more!!! SUBSCRIBE TO THE PATREON for a bonus episode where Jeff answered questions by subscribers! FOLLOW THE SHOW ON INSTAGRAM / X
Bitcoin traded at $67,950 on Tuesday, up 0.2% over 24 hours, as a wave of optimism over a potential end to the Iran conflict lifted risk assets across the board. Ether rose 1.6% to $2,100, its strongest daily move in weeks.~This episode is sponsored by Tangem~Tangem ➜ https://bit.ly/TangemPBNUse Code: "PBN" for Additional Discounts!00:00 Intro00:10 Sponsor: Tangem00:45 Tom Lee: 90-95% done02:00 Cramer: 3 ways this ends03:40 Tom Lee: Fire, ready, aim phase04:40 Tonight05:30 Iran denies ceasefire06:15 Can't leave without opening the Strait of hormuz07:45 Self inflicted Wounds08:30 Gold doesn't believe Trump09:50 Yuan toll booth10:15 Andrei Jikh: Why gold rally not done12:45 Warren Buffet: Waiting on larger move down#Crypto #bitcoin #Ethereum~Sell Off Over Soon?
Bitcoin dropped under $69K even as the SEC and CFTC create more clarity for crypto, and agentic commerce looks like it will reshape the sector. --- Thank you to our sponsor, MultiChain Advisors --- Bitcoin dropped under $69K after the Fed, ECB, and Bank of England all held rates steady this week, while Australia hiked. Kaiko's Laurens Fraussen joins to explain what's actually happening beneath the surface, from collapsing liquidity to a quiet geographic shift in who's buying. He also makes the case that agentic commerce could reshape how crypto payments work entirely and we break down why the market mostly shrugged at the latest crypto guidance from the SEC and CFTC. Host: Steven Ehrlich, Host of Bits + Bips: The Interview Guest: Laurens Fraussen, Research Analyst at Kaiko Links: Bitcoin, Markets, and the Iran Conflict Bitcoin Holding at $70,000 as Iran War Stokes Inflation Concerns — Bloomberg These 3 Charts Show Bitcoin's War-Linked Selloff Keeps Shrinking as Iran Conflict Worsens — CoinDesk What Bitcoin's Falling Hash Rate Might Mean for Prices — CoinDesk What's Next for Bitcoin Price Amid Iran War and Oil Prices Surge — DL News Central bank rate decisions Fed Interest Rate Decision March 2026: Holds Rates Steady — CNBC Fed Meeting Recap: Powell Says Inflation Isn't Coming Down as Much as ‘Hoped' — CNBC Bank Rate Maintained at 3.75%, March 2026 — Bank of England ECB, BOE, Swiss National Bank, Riksbank Interest Rate Decisions — CNBC ECB Holds Rates, Predicts 2.6% Inflation for 2026 — Central Banking SEC/CFTC Interpretive Guidance SEC Clarifies the Application of Federal Securities Laws to Crypto Assets — SEC.gov Joint Interpretation From the SEC and CFTC on Certain Types of Crypto Assets — Free Writings & Perspectives SEC Names Bitcoin, Ether, Solana and 13 More Crypto Assets Digital Commodities — FinTech Weekly Agentic Commerce and Payments Stripe-Led Payments Blockchain Tempo Goes Live With AI Agent Protocol — CoinDesk Stripe and Paradigm's Tempo Mainnet Goes Live for Machine Payments — Crypto.news Coinbase-Backed AI Payments Protocol Wants to Fix Micropayments but Demand Is Just Not There Yet — CoinDesk Google Agentic Payments Protocol + x402: Agents Can Now Actually Pay Each Other — Coinbase Google Debuts ‘Universal' Protocol for Agentic Commerce — PYMNTS Coinbase and Cloudflare Will Launch the x402 Foundation — Coinbase World Launches AgentKit With Coinbase-Backed x402 to Verify Human Identity Behind AI Agents — CoinDesk Learn more about your ad choices. Visit megaphone.fm/adchoices
Ripple brings Coinbase Futures to platform. Ripple is expanding its institutional reach, adding the full range of crypto futures listed on Coinbase Derivatives to its Ripple Prime platform. After clearing $3 trillion in volume last year, the move allows clients to trade regulated futures for Bitcoin, Ether, and XRP. CoinDesk's Jennifer Sanasie hosts "CoinDesk Daily." - Nexo is the premier digital wealth platform. Receive interest on your crypto, borrow against it without selling, and trade a range of assets. Now available in the U.S with 30 days of exclusive privileges. Get started at nexo.com/coindesk. - This episode was hosted by Jennifer Sanasie. “CoinDesk Daily” is produced by Jennifer Sanasie and edited by Victor Chen.
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