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  • Vanguard

    18 MAY

    1

    Vanguard

    Vanguard is the most effective vehicle ever created for participating in the fruits of American capitalism. Today it’s the single largest equity owner of the majority of corporations in the S&P 500, on behalf of 50 million clients (including, likely, many of you). And yet Vanguard itself is essentially a communist organization — it has no shareholders, makes no profits, and operates more like REI than Fidelity. If you own a Vanguard fund, you own a piece of the firm itself. Any excess margin instead gets returned to clients in the form of lower fees, which since 1975 have added up to roughly five hundred billion dollars transferred out of Wall Street managers’ pockets and into retail investors’ savings accounts. And oh yeah, it all started as a cockamamie revenge plot by a guy who’d just been fired by his partners. Today we tell the story of communist capitalism at its finest — Vanguard. Sponsors: Many thanks to our fantastic Spring '26 Season partners: J.P. MorganWeAreDevelopers eventServiceNowVercelStatsigLinks: Sign up for email updates, get our takeaways and research photos from each episode, and vote on future topics!Our Vanguard "episode preview" in WSJStay the Course: The Story of Vanguard and the Index Revolution by John C. BogleThe Bogle Effect by Eric BalchunasWorldly Partners' Multi-Decade Vanguard StudyWorldly Partners' Article Generational Investing: The Discipline Behind 100+x OutcomesAll episode sourcesCarve Outs: Our WSJ pieces on Ferrari and VanguardMacBook Pro M5 MaxMichael MacKelvie on YouTubeThe Super Mario Galaxy MovieBrooks Vanguard sneakersMore Acquired: Get email updates and vote on future episodes!Join the SlackCheck out the latest swag in the ACQ Merch Store!00:00:00 Start00:00:41 Intro00:05:30 Jack Bogle's Early Life & Family Ruin (1929)00:12:34 Princeton Thesis & Mutual Funds Emerge (1949-1951)00:27:20 Joining Wellington Management (1951)00:30:38 The Go-Go Years & Fidelity's Ascent (1958-1965)00:40:36 Jack Takes the Reins & The Ivest Merger (1965)00:46:04 The Go-Go Bust & Jack's Crisis of Conscience (1970-1973)00:53:28 Jack is Fired: The Genesis of Vanguard (1974)01:13:03 The Journal Article That Inspired It All (1974-1976)01:35:02 Building the Fund & Early Struggles (1976-1981)01:44:32 The Rise of Indexing & Vanguard's Growth (1988-1992)01:49:06 Jack's Health & The CEO Transition (1995-1996)02:00:06 The ETF Debate & Jack's Second Firing (1999)02:24:18 The 2008 Financial Crisis: Vanguard's Moment02:30:46 The Warren Buffett Bet (2008-2019)02:41:28 Fidelity & BlackRock's Resurgence (Post-2008)02:52:04 Salim Ramji: Vanguard's First Outside CEO03:04:43 Wellington's Comeback & Mutual Ownership03:08:23 Analysis03:30:58 Quintessence03:39:35 Carve-Outs + Outro ‍Note: Acquired hosts and guests may hold assets discussed in this episode. This podcast is not investment advice, and is intended for informational and entertainment purposes only. You should do your own research and make your own independent decisions when considering any financial transactions.

    18 May

    •
    3h 48m
  • Eric Jang – Building AlphaGo from scratch

    15 MAY

    2

    Eric Jang – Building AlphaGo from scratch

    Eric Jang walks through how to build AlphaGo from scratch, but with modern AI tools. Sometimes you understand the future better by stepping backward. AlphaGo is still the cleanest worked example of the primitives of intelligence: search, learning from experience, and self-play. You have to go back to 2017 to get insight into how the more general AIs of the future might learn. Once he explained how AlphaGo works, it gave us the context to have a discussion about how RL works in LLMs and how it could work better – naive policy gradient RL has to figure out which of the 100k+ tokens in your trajectory actually got you the right answer, while AlphaGo’s MCTS suggests a strictly better action every single move, giving you a training target that sidesteps the credit assignment problem. The way humans learn is surely closer to the second. Eric also kickstarted an Autoresearch loop on his project. And it was very interesting to discuss which parts of AI research LLMs can already automate pretty well (implementing and running experiments, optimizing hyperparameters) and which they still struggle with (choosing the right question to investigate next, escaping research dead ends). Informative to all the recent discussion about when we should expect an intelligence explosion, and what it would look like from the inside. Watch on YouTube. Read the transcript. And check out the flashcards I wrote to retain the insights. Sponsors * Cursor‘s agent SDK let me build a pipeline to generate flashcards for this episode. For each card, I had an agent read the transcript, ingest blackboard screenshots, generate an SVG visual, and run everything through a critic. A durable agent is much better at this kind of work than a chain of LLM calls, and Cursor’s SDK made it easy. Check out the cards at flashcards.dwarkesh.com and get started with the SDK at cursor.com/dwarkesh * Jane Street gave me a real deep-dive tour of one of their datacenters. I got to ask a bunch of questions to Ron Minsky, who co-leads Jane Street’s tech group, and Dan Pontecorvo, who runs Jane Street’s physical engineering team. They were willing to literally pull up the floorboards and take out racks to explain how everything works. Check out the full tour at janestreet.com/dwarkesh Timestamps (00:00:00) – Basics of Go (00:08:17) – Monte Carlo Tree Search (00:32:04) – What the neural network does (01:00:33) – Self-play (01:25:38) – Alternative RL approaches (01:45:47) – Why doesn't MCTS work for LLMs (02:01:09) – Off-policy training (02:12:02) – RL is even more information inefficient than you thought (02:22:16) – Automated AI researchers Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    15 May

    •
    2h 37m
  • Google Part III: The AI Company

    06/10/2025

    3

    Google Part III: The AI Company

    Google faces the greatest innovator's dilemma in history. They invented the Transformer — the breakthrough technology powering every modern AI system from ChatGPT to Claude (and, of course, Gemini). They employed nearly all the top AI talent: Ilya Sutskever, Geoff Hinton, Demis Hassabis, Dario Amodei — more or less everyone who leads modern AI worked at Google circa 2014. They built the best dedicated AI infrastructure (TPUs!) and deployed AI at massive scale years before anyone else. And yet... the launch of ChatGPT in November 2022 caught them completely flat-footed. How on earth did the greatest business in history wind up playing catch-up to a nonprofit-turned-startup? Today we tell the complete story of Google's 20+ year AI journey: from their first tiny language model in 2001 through the creation Google Brain, the birth of the transformer, the talent exodus to OpenAI (sparked by Elon Musk's fury over Google’s DeepMind acquisition), and their current all-hands-on-deck response with Gemini. And oh yeah — a little business called Waymo that went from crazy moonshot idea to doing more rides than Lyft in San Francisco, potentially building another Google-sized business within Google. This is the story of how the world's greatest business faces its greatest test: can they disrupt themselves without losing their $140B annual profit-generating machine in Search? Sponsors: Sentry: https://bit.ly/acquiredsentryWorkOS: https://bit.ly/workos25Anthropic: https://bit.ly/acquiredclaude25Statsig: https://bit.ly/acquiredstatsig26Links: Sign up for email updates and vote on future episodes!Geoff Hinton’s 2007 Tech Talk at GoogleOur recent ACQ2 episode with Tobi LutkeWorldly Partners’ Multi-Decade Alphabet StudyIn the PlexSupremecyGenius MakersAll episode sourcesCarve Outs: We’re hosting the Super Bowl Innovation Summit!F1: The MovieTravelpro suitcasesGlue Guys PodcastSea of StarsStepchange Podcast More Acquired! Get email updates with hints on next episode and follow-ups from recent episodesJoin the SlackSubscribe to ACQ2Merch Store!© Copyright 2015-2026 ACQ, LLC ‍Note: Acquired hosts and guests may hold assets discussed in this episode. This podcast is not investment advice, and is intended for informational and entertainment purposes only. You should do your own research and make your own independent decisions when considering any financial transactions.

    06/10/2025

    •
    4h 4m
  • The AI Sec-Pocalypse Is Actually Nigh?

    11 MAY

    4

    The AI Sec-Pocalypse Is Actually Nigh?

    Google reported the first known case of hackers using AI to discover and weaponize a zero-day vulnerability. OpenAI launched a $4B+ deployment company and acquired Tomoro. Apple plans Liquid Glass refinements for macOS 27, TikTok rolls out an ad-free tier in the UK, and Ben Thompson argues agentic inference will reshape compute. Google's TIG reports the first known example of hackers using AI to discover and weaponize a zero-day; TIG's chief analyst says "this is the tip of the iceberg" (NYT) The 90-day vulnerability disclosure policy is dead, as LLMs compress bug finding and exploit development time, and critical issues must be patched immediately (Himanshu Anand) OpenAI launches the OpenAI Deployment Company with a $4B+ investment to help organizations build and deploy AI systems, and acquires AI consulting firm Tomoro (Reuters) Sources: Apple is working on a "slight redesign" for macOS 27 to address Liquid Glass issues and plans a feature to automatically group Safari tabs in "27" OSes (Bloomberg) TikTok is rolling out TikTok Ad-Free, a £3.99-per-month subscription for UK accounts aged 18 or older "over the coming months", after testing the option in 2023 (TechCrunch) Agentic inference is set to be different than today's inference, and will change compute infrastructure because speed won't matter when humans aren't involved (Stratechery) Learn more about your ad choices. Visit megaphone.fm/adchoices

    11 May

    •
    21 min
  • Chickens, Roosting

    8 MAY

    5

    Chickens, Roosting

    Nintendo raised the Switch 2 price to $500 amid a global memory shortage. ShinyHunters forced Canvas offline during finals season. Researchers found 5,000+ insecure vibe-coded apps, Mozilla credits Mythos for 423 Firefox bug fixes in April, and France escalates its Musk probe. Nintendo says it will increase the price of the Switch 2 globally on September 1, from $450 to $500 in the US, and the price of the original Switch in Japan (Bloomberg) Instructure disables its Canvas edtech platform, used by thousands of schools, universities, and companies, amid a data extortion attack claimed by ShinyHunters (Krebs on Security) Researchers: 5,000+ web apps built using AI coding tools like Lovable, Base44, and Replit have little to no authentication, and ~40% exposed sensitive data (Wired) Mozilla says Anthropic's Mythos Preview and other AI models helped it identify and ship 423 Firefox security bug fixes in April, compared to 31 a year earlier (TechCrunch) French prosecutors escalate an investigation into Elon Musk and X, focused on alleged algorithmic manipulation and sexual deepfakes, to a criminal probe (CNBC) Longreads Anthropic co-founder Jack Clark explains why there's a 60%+ chance of AI systems autonomously building their successors by 2029 and the consequences of automated AI R&D (Import AI) How Delta SkyMiles and airline loyalty programs turned carriers into fintech companies with wings, and why most airlines couldn't survive without them (NY Mag) Learn more about your ad choices. Visit megaphone.fm/adchoices

    8 May

    •
    22 min
  • TikTok

    08/04/2021

    6

    TikTok

    Tiktok: qué es y nuestra opinión

    08/04/2021

    •
    9 min
  • SuperBox

    7 APR

    7

    SuperBox

    What if there was a device which gave you endless movies and TV shows without ads? Ok great sign me up! In this episode we interview “D3ada55”, who found such a device, but as she gazed into it, she discovered it gazing back at her. SponsorsSupport for this show comes from ThreatLocker®. ThreatLocker® is a Zero Trust Endpoint Protection Platform that strengthens your infrastructure from the ground up. With ThreatLocker® Allowlisting and Ringfencing™, you gain a more secure approach to blocking exploits of known and unknown vulnerabilities. ThreatLocker® provides Zero Trust control at the kernel level that enables you to allow everything you need and block everything else, including ransomware! Learn more at www.threatlocker.com. This episode is sponsored by Meter, the company building networks from the ground up. Meter delivers a complete networking stack - wired, wireless, and cellular - in one solution that’s built for performance and scale. Alongside their partners, Meter designs the hardware, writes the firmware, builds the software, manages deployments, and runs support. Learn more at meter.com. This episode is sponsored by Exaforce. Exaforce was created to handle the complete security operations workflow - detect, triage, investigate, respond. Exabots autonomously manage every stage, eliminating gaps between alert and action that slow down traditional security operations. And how it works is simple too: the exabots ingest all security data and then semantically connects it to understand the full context of security events and how they relate to each other. Learn more at exaforce.com/darknet-diaries.

    7 Apr

    •
    1hr 28min
  • Will AI Models Have To Be Reviews By The Government?

    5 MAY

    8

    Will AI Models Have To Be Reviews By The Government?

    The Trump administration discussed an EO to form an AI oversight working group, a stark reversal from its hands-off approach. Apple explored using Intel and Samsung to make chips in the US, Coinbase cut 14% of its workforce, and OpenAI fast-tracks an AI phone for 2027. Sources: the Trump administration is discussing an EO to form an AI working group that would examine AI oversight procedures, like vetting models before release (NYT) Sources: Apple held exploratory talks with Intel and Apple executives visited a Samsung plant in Texas to explore producing core chips for its devices in the US (Bloomberg) Coinbase CEO Brian Armstrong announces the company is cutting ~700 jobs, or ~14% of its global workforce, to reduce costs, saying "AI is changing how we work" (Reuters) Meta is using AI on Facebook and Instagram to detect under-13 users by analyzing bone structure, height, and visual cues, but says it's "not facial recognition" (The Verge) Kuo: OpenAI appears to be fast-tracking its AI agent phone with two NPUs and a custom MediaTek Dimensity 9600 SoC, targeting mass production as early as H1 2027 (Ming-Chi Kuo) ElevenLabs raised $550M+ in its Series D, up from a previously announced $500M, adding BlackRock, Nvidia, and others as investors; its ARR passed $500M in Q1 (Tech.eu) Source: YC owns ~0.6% of OpenAI, which was seeded by a YC offshoot called YC Research in 2016; at OpenAI's current $852B valuation, the stake is worth $5B+ (Daring Fireball) Learn more about your ad choices. Visit megaphone.fm/adchoices

    5 May

    •
    21 min
  • Codex as a Productivity Super App

    4 MAY

    9

    Codex as a Productivity Super App

    Maybe There's Something to the Super App Idea

    4 May

    •
    45 min
  • My LLM Cutoff Is 1930

    1 MAY

    10

    My LLM Cutoff Is 1930

    Apple beat Q2 estimates and forecast strong Q3 growth as the MacBook Neo and Mac Mini sell out. The Senate unanimously banned prediction market trading for senators, Intel closed its best month ever at +114%, and Musk admitted xAI "partly" distilled OpenAI models. Apple forecasts Q3 revenue above estimates, with sales expected to rise between 14% and 17%, and says memory expenses will climb "significantly higher" in Q3 (Bloomberg) Amazon debuts "Join the chat", an AI-powered feature that lets users ask questions about products and get conversational audio responses generated in real time (TechCrunch) The US Senate unanimously passed a rule barring senators from trading on prediction markets like Kalshi and Polymarket, amid rising concern over insider trading (CNBC) Musk v. Altman: when asked whether xAI has distilled OpenAI models, Elon Musk says the claim is "partly" true (Wired) Intel's stock jumped 114% in April, hitting a record on April 24 and lifting its market cap past $470B, closing out the chipmaker's best month on record (CNBC) Longreads Talkie-LM: what happens when you train a language model exclusively on text from before 1930? Can it predict the future or independently rediscover General Relativity? (Talkie-LM) Learn more about your ad choices. Visit megaphone.fm/adchoices

    1 May

    •
    21 min

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