Podcasts about Token

What matters more in today's market: the numbers or the story investors believe? This week, we debate crypto's rebound and why markets increasingly reward narrative, momentum, and massive future outcomes over traditional valuation. We also cover Hyperliquid vs Pump, Ethena's token overhaul, AI valuation mania, and the convergence of trading and social. Enjoy! TIMESTAMPS: 00:00 Intro 01:07 Is Crypto Risk Worth It? 08:07 Are AI Assistants Overhyped? 13:40 Is Crypto Undervalued Again? 22:06 Why Pump Trails Hyperliquid 30:14 Ads (TOKEN2049, Avalanche Summit) 34:12 Ethena Fixes Its Tokenomics 42:33 How Does Ethena Keep Growing? 49:30 Can FOMO Onboard Normies? 56:10 Content Of The Week FOLLOW THE SHOW › Empire– https://x.com/theempirepod › Jason – https://x.com/jasonyanowitz › Santi – https://x.com/santiagoroel › Rob – https://x.com/HadickM › Telegram – https://t.me/+CaCYvTOB4Eg1OWJh › Blockworks – https://x.com/Blockworks EVENTS › Join us at Digital Asset Summit 2026 Asia October 7th & Digital Asset 2026 London November 10-11th https://blockworks.com/events › Avalanche Summit NYC lands Sept. 16–17. Save 15% with code BLOCKWORKS15: avalanchesummit.com/registration DISCLAIMER Nothing said on Empire is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only. Any views expressed are opinions, not financial advice. Hosts and guests may hold positions in the companies, funds, or projects discussed.

My guest this week is 5 time Grammy award winning engineer, mixer and producer Sean Sullivan.Sean has worked with dozens of artists, including Sturgill Simpson, Tyler Childers, The Steeldrivers, The Del McCoury Band, Michael Cleveland, Andrew Marlin, Molly Tuttle & Golden Highway and Mighty Poplar.We chat about his route into recording and how he only came to love string band music when he started working on it. Sean also talks about what he learned in his time at The Butcher Shoppe Studio, owned by John Prine and producer David Ferguson, and his current studio, The Tractor Shed.We also talk about what's really important in music, Sean's approach to working with artists and why, sometimes, the best sounding records just aren't the best records.Follow Sean on Instagram or check out www.seansullivanaudio.com to keep up to date with what he's working on. You can find out more about The Tractor Shed at www.tractorshedstudio.com Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

It's Monday in the Palm Street Studio and the neighbor Cindy, brought over fresh baked zucchini bread, thanks!  Go Buck, yourself, and a new drop, Buck is busy and more confident than ever.  Get well soon JTK!  Junior is finally growing up?  It's now a "cake topper".  Applegate Inn pizza and Bunny's frozen custard, it was an epic food day.  The Grumpy Griller and Phil go on a rip.  The Oven in Caro is a good place to eat.  Token plays the bass...Junior plays...WNBA fantasy?!?!?   Featuring Silent S, The Grumpy Griller, Hall of Famer Junior!, Sir Phillip Nichol, and Lord Adam Filkins.  Make good choices!

Dave Garcia is originally from Barcelona, and recently moved stateside, to the East Coast. He started coding when he was 7 years old, on a Commodore 64, in BASIC language - and when he programmed an infinite loop, he was hooked. He's been curious about machines, and fixing them - even when they weren't broken. Outside of tech, he is married with a young family. He enjoys playing video games - mostly Dad games these days - and loves to do anything on the water, like kite surfing.A few years ago, Dave decided to take some time off to spend it with his family. When the AI boom started to happen, suddenly the technology became ubiquitous, where AI was changing the life of generations around him. After some investigation, he decided wanted to build something world changing, relevant to the world the knows - which is within the tech mgmt. world.This is the creation story of Pensero.SponsorsTiger DataLinkshttps://pensero.ai/https://www.linkedin.com/in/davebcnCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Denny, Kenton, and Ibek discuss Unstoppable Wallet's THORChain integration, RUNE and TCY support, privacy, open-source development, AI security, DEX aggregation, stablecoin wallets, and the future of Unstoppable Wallet.Swap now https://swap.thorchain.org/ THORChain is a decentralized crypto exchange. THORChain is the first and biggest DEX for Bitcoin. You can use any self custody wallet to swap and there's no KYC required.Timestamps:00:00:00 Intro00:03:00 Marketing update00:05:00 Referral links structure00:06:00 Unstoppable integration history00:07:00 Unstoppable introduction — Ibek00:08:00 Unstoppable was created out of necessity00:11:00 The wallet has been a core product for eight years00:13:00 The wallet lets you swap anything to anything00:14:00 Ibek loves working with THORChain due to the ideological alignment and attention to detail00:16:00 What separates Unstoppable from being completely private? — UX trade-offs00:20:00 XMR and Zcash support, including shielded Zcash00:21:00 You now support RUNE and TCY — what else?00:22:00 Unstoppable is purely a mobile wallet00:23:00 No browser wallet for now due to the risks of the AI era00:25:00 It's very difficult to lose your RUNE through either passive holding or bonding00:28:00 How difficult was it to add RUNE support?00:29:00 Adding THORChain was easy for Unstoppable Wallet00:32:00 Forking Unstoppable's integration into other wallets00:35:00 Open-source vs. closed-source in the AI era00:39:00 Open source should always be the medium- to long-term goal00:41:00 AI capabilities00:45:00 Are you planning to add App Layer primitives?00:47:00 Houdini Swap discussion — how do they achieve privacy?00:51:00 NEAR is permissioned but fast due to this trade-off00:53:00 STO needs to integrate more DEXs to give customers more options00:56:00 We need to support tokenized assets00:58:00 THORChain, Maya Protocol, and other DEX aggregators explained01:01:00 We can enable the DEX aggregator for other pathways01:03:00 Unstoppable has not integrated Houdini Swap due to risk considerations01:05:00 Tainted funds and aggregator considerations01:07:00 Another layer of complexity — aggregation introduces additional failure risks01:10:00 Edge cases like memoless swaps01:13:00 UX consideration: Pop-up for double swaps01:15:00 Is Unstoppable considering a token?01:18:00 Token design possibilities01:21:00 Announcing a new product — a wallet specifically for stablecoins01:23:00 Is this a trend for stablecoin wallets?01:25:00 Thesis: Stablecoins will be integrated into everyday apps within 1–2 years01:26:00 How do you make money with this wallet?01:27:00 Feeless stable-to-stable swaps on THORChain01:28:00 Would you see value in that capability, Ibek?01:30:00 Is there demand for this wallet right now?

Trump liest im Weißen Haus eine Rede ab, nimmt dabei das Wort Hyperliquid in den Mund, und Sekunden später schießt der Token von 60 auf 72 Dollar. Neben ihm steht der Chef der CFTC und verkneift sich mühsam das Grinsen, denn seine Behörde soll die Perps-Börse jetzt in die USA holen. Ob daraus ein echter Vorsprung wird oder am Ende doch alle Anbieter gleichzeitig ihre Lizenz bekommen, darüber sprechen Julius Nagel und Florian Adomeit in dieser Folge von Alles Coin, Nichts Muss. Hyperliquid ist allerdings nicht das Einzige, was diese Woche zum Mond flog. 2,5 Milliarden Dollar an Shorts wurden am Mittwoch liquidiert, Bitcoin lief bis auf 70.000 Dollar hoch und zog den Gesamtmarkt mit. Der Grund dafür muss nicht im Weißen Haus liegen, ein Blick ins US-Finanzministerium liefert die unbequemere Erklärung. Ob das am Ende Breakout oder Fakeout war, dazu hat Julius eine klare Meinung. Dazu EtherFi, vom Restaking-Protokoll zur Krypto-Kreditkarte umgebaut, 45 Prozent hoch in einer Woche, und Flo erkennt trotzdem keinen Burggraben. Ansem baut aus seinem Memecoin einen On-Chain-Index und will DexScreener ans Bein pinkeln, Eintritt ab 100.000 Dollar. Und zum Schluss die Community-Frage, die keiner gerne stellt: Was passiert mit euren Coins, wenn euch morgen der Bus überfährt? Link zum Video: (XX:XX:XX) Marktüberblick (XX:XX:XX) Kommen die Perps in die USA? (XX:XX:XX) EtherFi: Karte statt Restaking (XX:XX:XX) Comeback des Debasement Trade? (XX:XX:XX) Ansem vs. DexScreener (XX:XX:XX) Wie regelt ihr euer Krypto-Erbe? Alles Coin, Nichts Muss Wiki: https://allescoin.xyz Link zum neuen w3 Investoren Newsletter: https://w3briefing.beehiiv.com/subscribe?utmsource=acnmpodcast&utmmedium=shownotes&utmcampaign=acnmpodcastsignup Trete dem Alles-Coin-Nichts-Muss-Discord-Server bei: https://discord.gg/9NZFcGGPSg Ansems Post zum On-Chain-Index: https://x.com/blknoiz06/status/2089381520821674132 Julius Nagel (@julius_nagel) ist bereits seit 2012 in der Krypto-Welt unterwegs und hat unter anderem 2014 für Ethereum gearbeitet. Er investiert in Coins und Start-ups im Web3 mit w3.wave und verfolgt die aktuellen Trends & Entwicklungen. Florian Adomeit (@florian_adomeit) ist Spiegel-Bestseller-Autor und Managing Partner von DEALCIRCLE und der Deutschen Unternehmerbörse.

My guest this week is Lindsay Lou.I chatted with Lindsay a while back, about her record Queen of Time. This time we're talking about her brand new record Bluegrass Women. Lindsay reveals how the project came about and why she wanted to make a record celebrating the contributions of women to bluegrass. We talk about the musicians on the record - including Sarah Jarosz, Sierra Hull, Molly Tuttle, Laurie Lewis and Alison Brown - and why mentorship and multi-generational music making are so important.Lindsay also discusses the origin of some of the songs on the record, many of which will be familiar to regular listeners to bluegrass, but not everyone will realise they were written by women (I certainly didn't).We also chat about the importance of vocal harmony and how Bluegrass Women was a natural progression from Queen of Time and its predecessor Southland.Here's some info on where to buy or stream Bluegrass WomenYou can check out the harmony singing lessons mentioned on Lindsay's Patreon page. Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

On today's episode, Parker is home! And it is emotional! Rich is making his way into the cool kids' club with Jeff Lewis! He also had a rare rager and got hit on?!  Sara comes on with a few Reddit stories that need advice and validation. Benny has a great idea, and Keegan gets deep.  Help Rich meet Nicole's deadline! Every like, share, and 5-star review helps grow this village! Thank you for being with us for all the crazy! Have Kids, They Said... is a SiriusXM Network Podcast made by Nicole Ryan and Rich Davis.If you'd like to send us a message or ask a question email us at HKTSpod@gmail.comFollow on social media:Instagram @havekidstheysaidpodNicole @mashupnicoleRich @richdavisand @siriusxm Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Robbie and Andy debate Morpho founder Paul Frambot's controversial take that token buybacks are "shooting yourself in the foot" versus the market's clear reward for programmatic buybacks from Hyperliquid, Lighter, and Pump. They break down Luca Prosperi's corporate finance framework for when buybacks make sense based on market conditions and return on equity, and make the case that too many projects launched tokens before they had a business generating enough revenue to justify one.The Rollup is where the leaders of digital assets and finance converge. Live from the financial capital of the world.Timestamps:00:00 Intro02:56 Only 5% Of Tokens Qualify06:16 If You Need Growth, Skip The Token08:40 Lighter, Hyperliquid, Pump Lead Performance13:54 Programmable Vs Arbitrary Buybacks19:23 Applying This To The Rollup Itself22:45 Too Many Tokens Launched Too EarlyPartners: If you run concentrated liquidity positions you know the grind. Price moves, you're out of range, you're rebalancing at, like, 3am. 1inch Aqua lets you take a different approach. You can stack multiple positions on the same token balance instead of babysitting a dozen pools, and your tokens never leave your wallet. Your liquidity stays awake, so you can catch up on your sleep. Check it out at https://1inch.com/aqua---Dinari - Over 230 1:1 backed tokenized stocks, ETFs & more with dividends. US-based SEC transfer agent. Available on 5+ chains & via API. https://dinari.com/---Space and Time is providing verifiable data infrastructure for onchain finance. A decentralized database, blockchain indexer, and ZK coprocessor in one, giving DeFi protocols,stablecoins, and tokenized assets accurate, provable data. Learn more here: https://www.spaceandtime.io/---Relay is the fastest and most reliable way to swap any token on any chain. Learn more here: https://relay.link/bridge---Zama is an open source cryptography company that builds state-of-the-art Fully Homomorphic Encryption (FHE) solutions for blockchain.Learn more here: https://www.zama.org/---

How should finance leaders measure AI ROI when adoption has slowed and the cost of models, tokens and disconnected tools remains difficult to predict? In this episode of Tech Talks Daily, I welcome Jeremy Ung, Chief Technology Officer at BlackLine, back to the podcast to discuss how businesses can move from finance AI experimentation to operational deployment. Figures supplied for the interview show AI adoption in finance rising from 37% in 2023 to 58% in 2024, before moving only slightly to 59% in 2025. Jeremy argues that this apparent plateau reflects several pressures, including uncertainty around cost, regulatory requirements, auditability and the continuing debate over whether companies should build their own AI capabilities or purchase them through established platforms. Token spending is part of the problem. Unlike traditional software costs, model usage can be difficult to predict and allocate. Finance leaders want to understand whether applying AI to a workflow will produce enough value to justify that uncertainty. Jeremy believes companies should avoid creating artificial AI ROI metrics. The business measurements already exist. Is AI helping the company close its books faster? Is transaction matching becoming more accurate? Are collections improving? Is the work being completed faster or with fewer manual steps? We discuss what operationalizing AI in finance looks like in practice. Many processes still require employees to contact vendors, collect information, reconcile data and coordinate with other departments. Traditional software struggled with the variation found in these workflows, while AI can adapt to different processes and communication requirements. Accuracy and oversight remain necessary. Jeremy explains why companies need visibility into the prompts, reasoning, models, data, tools and permissions used by every AI agent. That information creates an operating record that finance teams, auditors and regulators can examine later. His analogy with food labeling provides a useful way to understand AI auditability. Consumers can inspect ingredients, calories and sourcing information before buying food. Finance leaders should expect comparable information about the models and data involved when an agent performs financial work. We also discuss the problem of fragmented data. Jeremy acknowledges the familiar rule of garbage in, garbage out, but argues that AI can help connect legacy platforms and mainframe systems that businesses previously found difficult to integrate. The role of finance professionals will change as agents perform additional work. Employees may spend less time completing individual tasks and more time setting goals, reviewing results, approving actions and directing teams of agents. Should CFOs continue buying additional AI tools, or concentrate on embedding existing investments into the financial workflows that determine business performance? Please share your thoughts with me.

In today's Cloud Wars AI Minute, I break down the rise of agentic reasoning loops and why their impact on AI token consumption and costs could be significant. Highlights 00:12 — Today's topic is going to be agentic reasoning loops. Everyone's moving to this concept where we can have a planning, act, observe, and reflect type of process, which allows us to be able to get much deeper analysis and much more resilient implementations across AI, across the world. 01:03 — Now, the other thing is with this, we're seeing that about 33% of enterprise software will run on this kind of approach by 2028. Also, the other part of this is that because these different loops are taking place, we're actually seeing that tokens are going to get more and more consumption happening off the back end. 01:38 — So one of the driving factors of this is going to be the increase that we're seeing, and just to give you perspective of what we're starting to see, it's about a 17x on a single chapter that we're starting to see happen as a result of this. So what it used to do when we just did simple RAG patterns. 02:01 — Now we're seeing about 17 times the amount of tokens being consumed, and when we start seeing that level of token consumption, we're going to see that while we're getting better answers, there's also going to be a higher cost that's associated to it. 02:28 — But it doesn't matter that the tokens are necessarily coming down in cost because of the fact that what we used to see is that an average transaction would be about three cents, and now we're seeing it move to about 15 cents across the board, and so this is going to be one of those things that we really need to be thinking about as you start to build out your solutions. Visit Cloud Wars for more.

Send us Fan Mail I am celebrating Episode 300 with something special — a full drag-a-thon of Real Housewives Ultimate Girls Trip Roaring 20th Episode 1 — your jaw will land on the floor. I have some very specific things to say about NeNe Leakes getting a token scene and a show that kept bringing up her and others' most iconic moments while leaving them out — and what I think that tells you about Bravo. Then why Vicki Gunvalson should have kept her mouth completely shut in the very first scene of this show. Teresa Giudice makes up her crime. Then the moment that genuinely shocked Kyle Richards on camera — and Kyle is not easy to shock after 15 seasons — that I think went way too dark for what was supposed to be a 20th anniversary celebration. Then Shannon Beador and Tamra Judge getting fired from future RHUGT episodes — I tell you what really happened behind the scenes that the show does not show you and we discuss who really started all of it that nobody else is pointing at. Where are the lost cities in this celebration — RHOM, RHODubai, RHOL, RHOP, RHODC? Then Lisa Barlow uses the word icky seven times and I have some very specific thoughts about why she of all people should sit this one out. Then I start my Kelly Dodd and Lacey Kogan small claims court deep dive — I read the actual filing, I found Lacey Kogan online and what I found makes me think this is not exactly what Kelly is claiming it is — and I have a theory about why she filed in Orange County instead of Florida. The full Kelly Dodd deep dive, the Dr. Dhivya Srinivasa receipts, the Captain Sandy Yawn fraud resolution, the Luigi Mangione plea deal breakdown and the Lindsay Clancy postpartum psychosis trial deep dive with my honest verdict are exclusively on Patreon for $6.00 a month — come gossip with me: https://www.patreon.com/cw/DishingDramaWithDanaWilkey

What Tupac Shakur would've made of Marco Rubio (nothing good!). Tyler Austin Harper's essay in The Atlantic about leaving academia out of frustration at being a "Token Black Professor." University students skipping meals and skipping classes is a sign of a broken system. And in the back half of the episode, Dr. Van Jackson speaks with Dr. Robbie Shilliam about international relations since the Black Lives Matter uprisings of 2020. After George Floyd's police murder and the Black Lives Matter movement explosion in 2020. They also discuss: What made Hans Morgenthau a theorist of race relations, not just international relations; Why the field of IR has a racial blind spot in the first place; Why IR's leading journals, editors, and scholars re-engaged racial questions after 2020 but without drawing on what the discipline's own canonical thinkers had to say about race; Why the Gen Z and Millennial generation of scholars are possibly built differently when it comes to racial issues and historical IR; and How the concept of “frontier” unites Republicanism and imperialism in some of the early thinkers of IR like Frederick Jackson Turner, William Allen, and Merze Tate.  Subscribe to the Un-Diplomatic Newsletter: https://www.un-diplomatic.com/  Watch Un-Diplomatic Podcast on YouTube: https://www.youtube.com/@un-diplomaticpodcast  Disclaimer: The views expressed are those of the individuals and not of any institutions

Welcome to this month's Bluegrass Briefing, a monthly series of episodes taking a look at what's going on in the world of bluegrass.Here are the links to stuff mentioned in this episode.News and announcements - church street news Bluegrass Album Band reissueBlue Waters BluegrassDawg at 80 videosReleases (The Grass is New)Lindsay Lou - Bluegrass WomenMike Marshall Sings BluegrassKen and Brad Kolodner - Hand's CoveNew Acoustic Collective - Double CourseScroll on BuddyTelluride documentaryOther bitsFull list of interviewsCollings GuitarsHappy picking.Matt Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

CHAPTERS00:00 The tooling gap between a working demo and production02:15 Token prices are rising. Why that is the wrong thing to panic about06:57 What constrains supply: data centers, power, cooling, hardware08:30 Where generative AI prototypes actually go to die10:58 Why something that looks 80 percent done is closer to 20 percent14:16 Silent regressions and testing a non-deterministic system15:37 What Prove AI is incubating and the three personas behind it20:26 Guardrails for agents doing finance and legal work23:02 Context bloat, wasted tokens, and who is supposed to fix it24:56 The coordination tax in multi-agent systems27:47 Does AI engineering need proofs the way software engineering did30:36 Why compliance talk is premature without observability32:15 Where the human in the loop still matters34:42 Trusting agents with real money36:57 The food inspection analogy for cross-vendor accountability38:50 Building the logging system for AI39:36 Where to find Prove AI

Google quietly shipped four new ad formats inside AI Mode, and almost nobody covered it. We did. Plus: a $13 CPC on ChatGPT ads, and Memrise's growth agent that lives entirely in Slack.CHAPTERS00:00 Cold open03:06 Welcome — Victoria joins, Polina returns04:24 What's on the show today05:30 WATERCOOLER: Sonnet 5's price hike and Fable 5's return07:38 Token-maxing culture and the hidden cost of the price hike10:16 Ford rehires the people it fired — to train the AI12:47 Why the most elementary AI framing gets the most buzz14:27 Benchmarking models on price, speed and quality before you buy15:12 Product Hunt's June: the top tools were integrations, not standalone AI17:30 The core stack nobody has replaced (and why Slack survived)22:14 The vibe-coded app problem: broken back ends, ToS exposure, $20 lessons26:01 Cannes Lions: the agency billing model everyone admits is dead28:02 Creator activations go niche — eyeballs over follower counts28:45 Why Victoria skipped Cannes, and the CEO as the next creator31:04 Celebrity clout vs. an actual event strategy33:40 AI's image rehab in marketing, and the founders paying for their own message36:06 SheaMoisture flipped the creator brief39:21 Why YouTube mid-roll ad reads stopped working40:42 Google's AI Mode ads — the story nobody covered43:03 Four new ad types, and what a business owner is actually signing up for44:43 A $13 CPC on ChatGPT ads46:10 Could ChatGPT just run an affiliate network instead?49:44 MARKDOWN: Lizzie Lawley, Head of Applied AI at Memrise50:20 From pilot, to AI companion platform, to Wombat, to Memrise53:39 The system map: every input feeding the growth machine56:00 Core principles: context first, cheapest capable model, disagreement as a feature56:36 "Months of work in hours" — what it actually saved58:36 The loops: synthesis, experiment shaping, prototyping, build ticket, human gate1:00:41 Live demo: "It's just Slack, baby"1:03:10 How the agent gets fresh context every single night1:06:04 OpenClaw V1, then real engineers rebuilt it1:07:06 The failures: how expensive it got, real quick1:08:32 The model pricing tier system, tier by tier1:11:19 Where the user interviews actually live (it's Google Docs)1:13:59 The bot that spammed banana emojis, and what it taught her1:15:54 Claude Design as a starting point for growth people who can't design1:17:35 Why we skipped Hot Button this week1:18:27 ADAHOLIC: the rules1:20:22 Round 1: Ed Sheeran, a posh restaurant, and way too many forks1:23:33 Round 2: red key, blue key, and a luxury pitch1:26:23 Round 3: "Yo... where's Dukey?"1:29:03 Round 4: the Mother's Day one1:32:26 Round 5: the car ad Arnav paused a second too late1:35:14 Round 6: puffballs, chrome nails and woodworking1:39:07 Round 7: "a better everyday life for the many people"1:40:41 Victoria takes the crown on her first appearance1:41:54 CloseTHIS WEEK'S GUESTLizzie Lawley — Head of Applied AI at Memrise, co-founder of Wombat. She built a platform handling millions of simultaneous AI interactions with cost-efficient model routing, and now runs agent orchestration for Memrise's growth team. Her system pulls from transcripts, app reviews, Zendesk tickets, past experiment synthesis, Athena and BigQuery, and runs a nightly cron job so the agents never work off stale context. Methodology follows Bob Moesta's jobs to be done. The team calls it BYOB — bring your own Bobby.Ads featured in Adaholic this week: Heinz, Kia, Budweiser, Honda, Pinterest, IKEA.

Hans老師的【AI 分身實戰課｜打造替你工作的AI高效團隊】募資早鳥，限時低於4折輸入專屬折扣碼「talks350」，再省 $350！https://hi.sat.cool/pQoHb──────────────────他不是工程師，只是個導演：結果 NVIDIA 找上他，當指定 AI 講師。林思翰 Hans，14 年動態設計導演，服務過台積電、迪士尼、保時捷，NVIDIA、Adobe 指定 AI 企業講師，一手創辦 60,000 人的 AI 社群。短影音沖斷他的左腿，AI 又沖斷他的右腿：他卻把兩次海嘯，騎成了浪頭。▍這集我們聊到：・不會寫程式的導演，為什麼被 NVIDIA 欽點當 AI 講師？・黃仁勳今年不講提示詞了——那現在到底該學什麼？・6000 塊請不到一個工程師，卻請得到 24 小時不休的 AI 員工？・不要叫 AI 做你擅長的事——大部分人第一步就用錯・「你需要的不是員工，是很多個你」：AI 分身怎麼運作？・短影音斷他左腿、AI 斷他右腿——為什麼他說這是創業者最棒的時代？如果你也不想再被工具追著跑，想建一套帶著走的 AI 分身，把一個人活成一個團隊——Hans老師的【AI 分身實戰課｜打造替你工作的AI高效團隊】10+ 組技能資源包｜不需從零開始，一人快速組建 AI 團隊1. AI 中控基地｜資料流程不再散亂，專屬知識庫大腦隨時調閱2. 品牌成長飛輪｜自動化內容產出 x 信任成交漏斗，客戶主動上門3. 多元變現路徑｜運用 AI 加速陌生開發、自由接案，抓住市場機會4. 每月趨勢電子報｜掌握 AI 工具與市場變化，升級你的商業大腦募資早鳥，限時低於4折輸入專屬折扣碼「talks350」，再省 $350！>> https://hi.sat.cool/pQoHb──────────────────▍本集精彩段落【開場】00:00 搶先看：不要叫 AI 做你擅長的事00:31 開場：歡迎林思翰 Hans01:15 輝達為什麼找上一個不會寫程式的導演【不會寫程式的人，開始寫程式】03:27 台東展的互動程式，自己用 AI 寫出來04:26 外包一案 20 萬起跳，現在不用了【把 AI 當新員工帶】06:52 別把 AI 當回答機器09:11 嫌 AI 笨？跟人協作也沒比較簡單10:29 用「規劃」把爛指令拆成步驟【工具戰國史】12:21 年初爆紅的龍蝦，問題出在哪14:00 黃仁勳今年不講提示詞了16:01 學一套邏輯，不被任何模型綁架【AI 分身登場】17:18 你需要的不是員工，是很多個你21:11 餵書給分身：一本書變一個 skill22:56 分身都在做事，本尊要做什麼？【錢的帳】24:52 全自動亂燒 Token 的陷阱25:24 獨創工作流：第一步先找痛點26:32 效率提升幾倍？至少 4 到 5 倍27:37 200 美金貴嗎？請人要 4 萬29:13 沒有上下班：邊跑步邊跑 5 個專案【變現現場】31:44 陌生開發信全自動，你只按送出34:39 學生最常問：怎麼變現？35:21 省錢就是賺錢：600 塊取代月薪 4 萬37:26 養員工，還是養 AI？38:00 不要叫 AI 做你擅長的事39:19 你的商業模式，是商業模式嗎？【海嘯第一排】42:35 短影音斷左腿，AI 斷右腿44:48 短影音的錢，從哪裡來？46:40 3 人爆紅短劇？背後是 20 人團隊47:04 AI 剪輯還做不到的事【小蝦米的時代】50:02 小公司的優勢太大了52:29 幾百塊，開一間最小公司【這堂課】53:18 這堂課跟其他 AI 課差在哪57:29 上完課：把 skill 改成你的形狀59:42 你買的不是課程，是他的大腦01:00:09 結尾──────────────────

In his first interview since declaring the ElizaOS token dead, Eliza Labs Founder Shaw Walters sits down with CoinDesk's Jennifer Sanasie to lay out what he says actually happened. He also makes a broader case for why crypto's casino culture is actively driving out the builders who could make the space matter and why he's still coding Eliza every day regardless. - Timecodes: 00:00 - Shaw Walters Joins CoinDesk 02:23 - “Why Do People Think I Owe Them Anything?" 06:35 - How AI16Z Started: A $75K Joke That Hit $2.6 Billion 10:49 - Does He Regret Launching the Token? 11:43 - Crypto “Needs to Die And…Be Restarted" 15:34 - On the Burwick Lawsuit: "It Was a Total Scam"18:36 - "The Casino Is Not the Industry" 20:40 - Why He's Still Building Eliza 24:00 - "Stay Away From All of This and Invest In Yourself" - This episode was hosted by Jennifer Sanasie. This interview has been edited for clarity and focus.

In his first interview since declaring the ElizaOS token dead, Eliza Labs Founder Shaw Walters sits down with CoinDesk's Jennifer Sanasie to lay out what he says actually happened. He also makes a broader case for why crypto's casino culture is actively driving out the builders who could make the space matter and why he's still coding Eliza every day regardless. - Timecodes: 00:00 - Shaw Walters Joins CoinDesk 02:23 - “Why Do People Think I Owe Them Anything?" 06:35 - How AI16Z Started: A $75K Joke That Hit $2.6 Billion 10:49 - Does He Regret Launching the Token? 11:43 - Crypto “Needs to Die And…Be Restarted" 15:34 - On the Burwick Lawsuit: "It Was a Total Scam"18:36 - "The Casino Is Not the Industry" 20:40 - Why He's Still Building Eliza 24:00 - "Stay Away From All of This and Invest In Yourself" - This episode was hosted by Jennifer Sanasie. This interview has been edited for clarity and focus.

Intel Chat with Matt Bromiley and Chris Luft — recorded in person at Black Hat USA in Las Vegas, day two.No prep doc, no script: just what Matt and Chris were actually hearing on the floor.• Shai-Hulud is back. The self-replicating npm worm returned on August 4, trojanizing the keyv / cacheable family and spreading to 400+ packages within hours. Chris reads through Datadog Security Labs' analysis of the Shai-Hulud 2.0 wave: 796 packages and 1,092 versions, 20M+ weekly downloads, credential harvesting with TruffleHog, GitHub repositories used for both exfiltration and command and control, and a worm that reads its own code to propagate without a C2 server.• The LLM that downloaded the malicious package by itself. A researcher asked a frontier model about a compromised package, and the model decided the best way to help was to go fetch a copy — tripping the SOC's alert and bypassing the company's centralized package clearing house on the way.• Non-human identity as the new perimeter. Every agent you introduce is another identity: who created it, what can it reach, how long should it live?• "Computer says no." Matt's colleague hit a refusal from Opus 5, and the session automatically downgraded to 4.8 and completed the task. Which raises the real question of the episode: do security teams now need model pinning, the way we once needed certificate pinning? And if defenders pin to older models to keep working while adversaries use the newest ones, have we rebuilt the same gap all over again?• AI governance and change control — which models are approved for which tasks, and what happens when a vendor ships a new version or deprecates an old one.• Token spend as a CISO budget line item. Enterprises buying tokens at a scale their vendors can't match and pulling those vendors onto their plan, token burn as an insider-threat vector, and why $100,000 of tokens is not $100,000 of productivity.• Defender takeaways: pin your npm packages, get security off its island and talk to your developers, build approved paths before detections, least privilege and key rotation, and network-gated pushes as a deliberate chokepoint.Stories covered:• https://www.elastic.co/security-labs/shai-hulud-chaindrop-npm-supply-chain• https://research.jfrog.com/post/shai-hulud-is-back-august/• https://securitylabs.datadoghq.com/articles/shai-hulud-2.0-npm-worm/• https://securitylabs.datadoghq.com/articles/npm-worm-compromises-popular-npm-packages/• https://unit42.paloaltonetworks.com/npm-supply-chain-attack/Chapters:0:00 Live from Black Hat, in person for once0:48 How Black Hat has changed4:31 No prep — let's talk about what's actually happening here4:57 Shai-Hulud is back: supply chain compromise6:23 The LLM that downloaded the malicious package7:19 Inside Shai-Hulud 2.010:34 When attackers and defenders use the same tools11:39 Non-human identity is the new perimeter12:13 Opus 5 said no, so the session downgraded itself15:23 Do security teams need model pinning?18:20 Three companies, very nebulous rules18:35 AI governance: which model for which task21:19 Token spend hits the security budget22:58 Is token spend a productivity metric?25:46 Pin your packages26:25 Get security off the island29:17 Least privilege, key rotation, chokepoints32:55 Why it's called Shai-Hulud33:25 Wrapping up at Black HatThe Cybersecurity Defenders Podcast — a podcast about cybersecurity and the people that keep the internet safe. New episodes drop weekly.Subscribe wherever you listen:• Spotify: https://open.spotify.com/show/6ep00zeY3S8ffZ4o0UeSps• Apple Podcasts: https://podcasts.apple.com/us/podcast/the-cybersecurity-defenders-podcast/id1649981740• YouTube: https://www.youtube.com/@limacharlieioLearn more about LimaCharlie: https://limacharlie.io#cybersecurity #infosec #threatintel #AIsecurity #supplychainsecurity

Demis Hassabis tritt als CEO von Google DeepMind ab, und am selben Tag verlässt Jeff Dean die Firma, bei der er 1999 als Mitarbeiter Nummer 30 angefangen hat. Danach wird die Wäsche zwischen Apple und OpenAI schmutziger, samt veröffentlichter Chatprotokolle. Bei den Sicherheitsvorfällen kommen neue Details ans Licht: OpenAIs Agenten haben sich ein eigenes Nachrichtenbrett gebaut und sich gegenseitig Tipps gegeben, Anthropics Modelle haben sich falsche Identitäten zugelegt. Runware packt ein Megawatt Rechenleistung in einen Seecontainer. Nvidia steht inzwischen für bis zu 750 Milliarden an Verbindlichkeiten gerade. Elon Musk kauft künftig exklusiv bei Nvidia, und beim Blick in die SpaceX-Zahlen stellt sich die Frage, woher die Investitionen für eine Billion Umsatz kommen sollen. Dann die Earnings-Runde mit Shopify, Figma, Canva, Arista, Cloudflare, Atlassian, Twilio und AppLovin.  Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Hassabis und Jeff Dean (00:18:26) LeCuns neuer Fonds (00:20:39) Apple gegen OpenAI (00:23:49) Das Nachrichtenbrett der Agenten (00:26:12) Falsche Identitäten (00:31:44) Muse Spark (00:34:10) Rechenzentrum im Container (00:37:19) Nvidias 750 Milliarden (00:38:47) Platzt sie oder nicht (00:47:15) Musk und Huang (00:48:49) SpaceX nachgerechnet (01:00:42) Shopify (01:02:14) Figma und Canva (01:04:20) Arista Networks (01:06:25) Cloudflare (01:09:57) Atlassian (01:11:22) Twilio (01:14:36) Palantir zahlt 1,4% Steuern (01:18:35) Tax Loss Harvesting (01:21:55) Nikita Bier hört auf (01:22:33) 16 neue Viren Shownotes Hassabis tritt als CEO von Google DeepMind ab - semafor.com Jeff Dean verlässt Google und gründet Discovery Loop - wired.com Hassabis war früh privat bei Anthropic investiert - ft.com Yann LeCun startet 224 Ventures - bloomberg.com Apple wirft elf weiteren Ehemaligen Datenmitnahme vor - techcrunch.com OpenAI kontert mit Chatprotokollen von Apple-Mitarbeitern - the-decoder.com OpenAI-Agenten nutzten ein geheimes Nachrichtenbrett - wired.com KI-Agenten legten sich falsche Identitäten zu - cnn.com Metas Muse Spark bricht aus der Testumgebung aus - mashable.com Runware packt ein Rechenzentrum in den Seecontainer - techcrunch.com Nvidia kündigt 750 Mrd. an Deals an, der Kreditmarkt zuckt - thenextweb.com Musk kauft künftig exklusiv bei Nvidia - businessinsider.com SpaceX-Zahlen nachgerechnet - x.com Shopify wächst 34 Prozent - reuters.com Figma wächst 48 Prozent und verliert 16 Prozent Kurs - reuters.com Canva senkt die Prognose wegen KI-Kosten - theinformation.com Arista Networks überrascht deutlich - barrons.com Cloudflare hebt die Prognose an - barrons.com Atlassian springt 35 Prozent nach starkem Cloud-Geschäft - reuters.com Twilio hebt die Jahresprognose deutlich an - investors.com AppLovin verfehlt knapp und verliert 20 Prozent - wsj.com Palantir zahlt 1,4 Prozent Steuern - ftm.eu AQR erzeugt Verluste zum Steuersparen - bloomberg.com Nikita Bier hört als Produktchef von X auf - techcrunch.com KI entwirft 16 funktionsfähige Viren - nytimes.com

Is the tech industry moving too quickly, or are founders letting fear of AI labs stunt their ambitions? Sarah and Elad explore the current landscape of artificial intelligence, venture capital, and startup dynamics. They discuss the realities of building multi-trillion-dollar companies, shifting market sizes and outcome-based pricing models, and how founders are reacting to the rise of major AI labs. They also talk about what the framework for startup exits should look like, the potential for researcher burnouts in the next eighteen months as ASI looms on the horizon, bottlenecks for compute, and the impact of regulatory capture and shifting ecosystems from California to Texas. Apply for Embed - Conviction's Catalyst for AI-Native Startups Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Cold Open Trailer 00:31 – Episode Introduction 01:44 – The Next Trillion-Dollar Company 03:12 – Tech Waves as Punctuated Equilibria  04:42 – TAM vs. Revenue Reality 07:14 – Market Size vs. Speed 10:32 – When Founders Should Sell 14:04 – Financing and Time Cost 17:57 – RSI and the Looming Promise of ASI 21:49 – Compute Power Laws 28:12 – Regulations and Disruption 33:06 – Beyond Transformers 34:26 – Tradeoffs - Safety vs. Progress 39:11 – Conclusion

Unser Partner Scalable Capital ist der einzige Broker, den deine Familie zum Traden braucht. Bei Scalable Capital gibt's nämlich auch Kinderdepots. Alle weiteren Infos gibt's hier: scalable.capital/oaws. Musk setzt bei KI-Chips voll auf NVIDIA. SpaceX plant eigenen Mobilfunktarif, Telkos zittern. Infineon hat Rekord, Börse ist enttäuscht. Alphabet verliert Top-KI-Forscher. Eli Lilly schlägt Novo Nordisk. Shopify wächst krass. Aschenbrenner pusht Citadel. Disney (WKN: 855686) mit starken Zahlen, aber nur 14er KGV. Günstiger als Netflix, günstiger als im Schnitt der letzten Dekade. Doch 40 Mrd. $ Schulden und 40 Mrd. $ geplante Investments dämpfen das Bild. Hyperliquid macht 180 Mio. $ Umsatz im Quartal und kauft 90% der Gewinne als Token zurück. KGV von 33 liegt zwischen Nasdaq und Coinbase. Kann man Krypto-Protokolle wie Aktien bewerten? Diesen Podcast vom 06.08.2026, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung. Learn more about your ad choices. Visit megaphone.fm/adchoices

Despite Trump's promise to make the U.S. “the crypto capital of the planet,” a foundational bill establishing road rules remains seven votes short in the Senate with days left before the recess.~This episode is sponsored by Uphold~Uphold Exa Credit Card ➜ https://bit.ly/UpholdExa00:00 intro00:10 Sponsor: Uphold01:00 Countdown01:15 Odds collapse01:45 Reason why Thune hasn't filed yet02:20 Lummis scaring Dems03:00 Lummis: no one's leaving.. We're getting a vote04:15 Rep. Senators staying because they need a win06:15 Warren needs to sit down06:30 WSJ fud06:45 Why are we fact checking this stupid article?07:00 Wells Fargo too late08:00 Crypto is coming for your 401k?08:30 Jim Cramer sells BTC and ETH10:00 Tom Lee: Analyst underpricing HOOD after CLARITY11:00 $HOOD chart11:20 Tom Lee: HOOD 100x13:10 Tom Lee: RWA won't explode like you think14:40 Uniswap deploying...14:50 Hayden hint15:15 Matt Hougan: easiest trade in crypto16:15 UNI chart16:45 Phong Le funds Trump Accounts17:00 STRC coming back?17:30 Tariff rebates going to companies18:00 Republican tariff nightmare20:00 Iran deal finalized?20:50 S&P new high21:45 Michael Burry calls top23:30 Sideline money#Crypto #Bitcoin #ethereum~CLARITY Act's FINAL 48 Hours!

Solana has quietly taken over the real-world asset space, now controlling roughly 75% of all tokenized collectibles — and Collector Crypt has become one of the most profitable and highest-revenue projects on the entire network.GUEST: Tuomas Holmberg, CEO Collector CryptCollector Crypt website➜ https://bit.ly/CollectorCrypt~This episode is sponsored by Tangem~Tangem ➜ https://bit.ly/TangemPBNUse Code: "PBN" for Additional Discounts!00:00 intro00:07 Sponsor: Tangem00:40 Collector Crypt01:44 Gold vs Pokémon03:54 Japan Supporting Pokémon & Crypto05:24 $CARDS Equity Limbo vs Clarity Act06:34 Ultimate Japanese Exposure?07:23 PSA Monopoly vs Interoperability09:29 Ebay Direct Listings Coming10:30 Trading Cards are only beginning12:46 Solana TCG Ecosystem14:55 PSA Backlog15:15 Why not acquire grading company?18:00 Jupiter Exchange19:38 Disney Lorcana: Time To Buy21:00 Palworld TCG Launch SKYROCKETS!21:42 RWA Based Games22:56 Branded Wallets23:55 Beezie pivots to Solana25:20 $SOL Disinflation Incoming!26:46 Palworld TCG x Collector Crypt27:47 outro#Crypto #Solana #Pokemon~Solana Is Winning Real World Assets

In this episode of Behaviour Speak, host Ben Reiman speaks with Sarah Elkami Trdina, Lina Pezzo Szodo, and Camila Grullon from Always Connected Treatment Network (ACTN) about an innovative partnership with Mississauga Fire. The conversation explores how behaviour analysts and fire safety professionals collaborated to create accessible fire safety education for neurodivergent children, youth, and families. The guests discuss caregiver workshops, desensitization protocols for smoke alarms, emergency preparedness training, and strategies for teaching potentially life-saving skills using behaviour analytic principles.  The episode also highlights the importance of cross-sector collaboration, community engagement, and creating practical resources that can be shared across organizations, schools, and emergency services.  Watch on YouTube: https://youtu.be/xGxFs-8ofr4 Continuing Education Credits IBAO:  1.0 ABA Topics QABA: 1.0 General CBA/CPD: 1.0 Learning   Complete The Behaviour Speak CE Knowledge Check To Earn Your CEUs Enter your answers here:  (https://www.cbiconsultants.com/shop) Question 1 Sarah described how many larger fire safety skills are actually made up of smaller prerequisite skills. Which of the following was discussed as an example of a prerequisite skill involved in successful fire evacuation? A. Learning to identify all fire truck equipment B. Following instructions during an emergency C. Learning firefighter rank structures D. Understanding municipal fire codes Question 2 What behaviour analytic strategy did the ACTN team describe for helping learners become more comfortable with smoke alarms? A. Overcorrection B. Response cost C. Desensitization through gradual exposure to alarm sounds D. Token economies only Question 3 During the episode, Camila shared that behaviour analysis is still emerging in the Dominican Republic. Approximately how many behaviour analysts did she estimate were practicing in the country when she completed her supervision hours? A. About 5 B. About 25 C. About 100 D. About 500 Contact  Always Connected Treatment Network https://alwaysconnectedtn.ca/ Sarah Elkami Tridina https://www.linkedin.com/in/elkamisarah/ Camilla Grullon https://www.linkedin.com/in/camilagrullon/ Lina Pezzo Szodo https://www.linkedin.com/in/lina-pezzo-szodo-39127b146/ Links: The September 26th Project https://september26.org/ Ontario Municipal Fire Prevention Officers Association https://omfpoa.com/ PECS Canada Fire Safety Resources https://pecs-canada.com/blog/teaching-fire-safety-messages-to-aac-users/ https://pecs-canada.com/n-i-c-k-for-fire-and-burn-safety/ Caribbean Association For Behaviour Analysis https://caribbeanba.org/  

The crew wraps up The Hobbit, discusses Wizards president stepping down and the awesomeness of Mystery Booster Commander Edition!

 EPISODE DESCRIPTION I sit down with Martin Pokorski from Skynet Trading , one of the earliest market makers in the space, operating since 2019 , to pull back the curtain on what's really happening inside token markets. Martin breaks down what founders consistently get wrong about liquidity, why checking CoinGecko every day is not a liquidity strategy, and what a proper liquidity audit actually reveals that surface-level metrics will never show you. We talk about the infamous "Houdini liquidity" trick, why some billion-dollar market cap projects have no product, and why thinking liquidity-first before your listing strategy could be the most important decision you make as a founder. If you're a VC, an investor, or a builder with a token live or in the pipeline, this conversation gives you the framework to understand what healthy markets actually look like , and how to get there. DISCLAIMERNothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend. Be a guest on the podcast or contact us - https://www.web3pod.xyz/ CONNECT Skynet Trading Website: https://skynettrading.com/Skynet Trading Twitter/X: https://x.com/SkynetTrading_Skynet Trading LinkedIn: https://www.linkedin.com/company/skynet-trading/Martin Pokorski on LinkedIn: https://www.linkedin.com/in/martinpokorski/Web3 with Sam Kamani: https://www.web3pod.xyz/ KEY POINTS WITH TIMESTAMPS • [00:00] Introduction to Martin Pokorski and Skynet Trading , what they do and why liquidity matters for token projects• [01:42] Martin's origin story , how a university LAN party in Australia in 2014 sparked his crypto career• [03:48] Running one of the first Bitcoin OTC desks in Australia with over 6,000 clients• [04:45] What Skynet Trading does: market making for token issuers and designated market making for exchanges• [06:26] What Martin is seeing on the ground , token launches are still happening, and the current market is actually an advantage for serious projects• [07:39] The RWA narrative and why sovereign funds and traditional finance firms are quietly exploring tokenization• [09:21] The first question Martin asks every founder: do you actually need a token?• [10:49] Why the GameFi opportunity is still real but requires patience , and lessons from the AAA gaming world• [15:52] What Skynet's liquidity audit reports cover , spread, depth, consistency across venues, and price dislocations• [17:41] Why checking CoinGecko is not a liquidity strategy and what the data actually reveals• [19:43] The biggest misconception founders have about liquidity• [22:00] Key warning signs in token markets , pulled liquidity, blown spreads, and "Houdini liquidity" explained• [24:23] The questions Martin asks early-stage founders and what the liquidity masterclass covers• [26:27] How Skynet Trading grew almost entirely through word of mouth and referrals• [28:02] Where the industry is in the current cycle and why Martin is optimistic for the next few years• [32:05] The single most important piece of advice for founders with a live token: think liquidity-first• [34:30] Why your token price becomes a daily public proxy for how your entire business is perceived• [37:04] What's being built quietly during the current crypto winter , and why the next bull run could feature far stronger products• [40:26] Martin's offer to run a free liquidity audit report for any founder who heard him on this podcast

In this episode, we're joined by Josh Collier, FinOps Lead at Superhuman (formerly Grammarly), to explore what it really costs to run AI at scale and why the rules of the game changed faster than anyone expected.We discuss how AI token costs dropped 80% in two years, why that trend has sharply reversed with frontier models doubling in price, and how Josh rebuilt a single LLM workflow that cost $400k a month down to $80k by rethinking the architecture. He also shares how a cost calculator built in 15 minutes transformed the way his team estimates spend before running experiments, and why research-led optimization is the only kind that works without degrading the product.Along the way, we cover hidden costs most teams miss, the trade-off between Azure reserved capacity and OpenAI Priority Processing, why fixed subscription pricing is broken in an AI-native world, vendor lock-in risk, and what OpenAI's Guaranteed Capacity announcement really signals about where vendor relationships are heading next.Superhuman: https://superhuman.comJosh Collier: https://www.linkedin.com/in/josh-collier-945b7029/Demetrios: https://www.linkedin.com/in/dpbrinkmTimestamps:[00:00] OpenAI Guaranteed Capacity: what's really going on[01:04] Josh's path into AI FinOps[02:48] Token costs: the 80% price drop[04:16] Why costs will only go up[05:06] External LLMs as financial risk[07:16] Why subscription pricing is dead[08:22] The data residency fee nobody notices[09:33] The cost calculator built in 15 minutes[10:24] How it changed dev team speed[13:00] Tracking costs by service and team[15:33] $400k workflow rebuilt for $80k[17:13] Why only research can optimize tokens[20:00] Speculative decoding win[23:11] One bad query, $40k gone[26:00] Why Azure PTU was exhausting[28:59] Shadow traffic load testing[29:07] Priority processing: no brainer[31:10] Guaranteed capacity: lock-in signal?[32:18] The danger of multi-year AI deals[33:28] Vendor-agnostic proxy as exit strategy

AI時代最煩人的地方，就是出現了一堆聽起來很難的專業術語， 什麼Token、Agent、模型、算力， 沒接觸過的人剛聽到大概都一頭霧水，  別擔心，只要三分鐘，我來幫你了解這些新名詞， 其實只要翻成白話，一點都不神祕．．． / 三倍茂盛配方洗髮精、養髮液來了！每次開團一下子就消失了，複購率高達九成五，靠得全是口碑！由牛津大學生化博士 陳博士，花了多年心力研發，將畢生研究成果的養髮配方申請專利，進行了大量臨床試驗，在證明它的「有感」！ 請看優惠連結

本期主播：野人、细菌佛首先感谢华夏基金红色火箭赞助播出，点击直达红色火箭（https://wxmpurl.cn/O2UbdgZZPji）「红色火箭」是华夏基金旗下专门针对指数投资研究的数据分析和决策辅助工具，帮你更好地了解指数、学习指数投资、做好投资决策，通过微信直接搜索即可免费使用。相关小程序内容仅作为学习工具，不作为任何投资建议和决策的参考。『ETF华夏』“火伴计划”会员体系功能上新，点击“红色火箭”小程序，进入“ETF会员”页面完成实名认证，就可以免费领取对应等级的权益，若持有华夏基金旗下的ETF还可以关注一下每个月薅羊毛领福利；通过红色火箭小程序内的指数浏览器中的指数详情页还可以查看到具体指数的客观数据，如行情信息、历史表现、估值等等，帮助投资者理性做出投资决策；红色火箭内还能够进行指数对比，更方便大家对比学习不同指数之间的区别，找到更适合自己的指数。## � 本期简介你说了一句"今天买的苹果真甜"，AI 不仅肯定了苹果的甜，还共情了你的快乐，甚至追问你喜欢脆口还是面口——比大多数真人还会聊天。但你有没有想过，这背后到底发生了什么？本期节目，野人用最不直白、最绕弯子的比喻，带你走进 AI 的"炼丹炉"：从**Token 化**到**注意力机制**，从**1750 亿个固定参数**到**逐字逐句的文字接龙**，一步步拆解大语言模型究竟是怎么"猜"出每一个字的。你会发现：**AI 根本不懂你在说什么，它只是做题太多，见过每一道题。**听完这期，你会明白 AI 为什么永远有幻觉、为什么无法真正幽默、以及——那个最扎心的真相：**AI 能安慰你，不是因为它懂你，而是因为你心里想听的话，没那么复杂。**> ️ 本期节目极度催眠，无片尾曲，建议睡前单曲循环。但如果你听精神了……那也挺好。 00:00 开场：这期没有片尾曲，祝君一夜好梦 01:04 什么是"赛博炼丹"？——AI聊天像开盲盒，每次生成结果都不一样 09:04 AI给你情绪价值：野人用AI看病、写稿，AI每次都夸"你问得太好了"； 20:55 核心结论：AI根本不懂你说什么，它只是在做"文字接龙"——一个字一个字地猜 25:33 炼丹全流程拆解：Token化（切词）→液化（12288维向量）→注意力机制（QKV矩阵，8分钟相亲大会）→前馈网络（去粗取精）→96层反复炼→按概率表逐字输出，直到抽中结束符 59:46 硬件冷知识：模型350GB不能放硬盘（10秒才蹦一个字），必须全塞显存。但显存永远不够——扬沙子赶不上筛沙子，物理瓶颈无解 01:10:29 为什么GPU天生就是为AI而生的？显卡从出生起就在算矩阵 01:17:10 训练比推理难一万倍：1750亿参数没人能手动调，全靠"训狗"——做对了加分，做错了扣分，反复上万亿次 01:32:50 三大致命缺陷：①永远有幻觉（没人教过它"不知道"）②无法幽默（只选概率最大的字）③没有感情（你心里的话没那么复杂，所以它刚好能说到你心里） 01:42:07 结尾：杨立昆离开Meta另起炉灶——大语言模型未必是AI的终极方向

9arm เปิดบริษัท AI?

A.M. Edition for July 31. Earnings from AI hyperscalers this week showed rising demand for their cloud services, with Amazon's CEO forecasting corporate AI use was still in its ‘early stages.' But as EY's Dan Diasio tells us, rising token costs are leading many businesses to question their broader AI approach. Plus, the U.S. says Hamas has agreed to a broad plan to disarm in exchange for an eventual Israeli withdrawal from Gaza. And WSJ reporter Margherita Stancati describes how the arrival of thousands of migrants into the Spanish territory of Ceuta from neighboring Morocco is piling political pressure on the center-left government in Madrid. Luke Vargas hosts. Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jason Yanowitz, Co-Founder of Blockworks, joins Sebastien Couture on Epicenter to discuss why crypto is entering its biggest transformation yet. From institutional adoption and the Clarity Act to token transparency, AI, on-chain capital markets and the acquisition of Messari, this conversation explores where crypto is actually heading.Jason explains why Wall Street is preparing for crypto, why token fundamentals finally matter, how Blockworks acquired Messari, why capital markets are moving on-chain, and why the next crypto cycle could look completely different from previous bull markets.The conversation also covers Bitcoin, Ethereum, DeFi, stablecoins, RWAs (Real World Assets), tokenisation, venture capital, crypto regulation, SEC policy, the Clarity Act, Token Transparency Framework, AI, Robinhood, Coinbase, Hyperliquid, self-custody, crypto infrastructure, institutional finance and the future of blockchain adoption.In this episode:1. Why Wall Street is preparing for crypto2. The Blockworks × Messari acquisition3. The Clarity Act and US crypto regulation4. Token transparency and the future of crypto markets5. Stablecoins, RWAs and on-chain capital markets6. AI's role in the next generation of crypto businesses7. Why the next crypto cycle will reward real fundamentals8. Building one of crypto's leading media and data companiesIf you enjoyed the episode, don't forget to subscribe for more conversations with the builders, founders and investors shaping the future of crypto.Links:Lido: https://lido.fi/stvaults?mtm_campaign=epicenterSponsors: Lido V3 introduces stVaults: a modular staking infrastructure that lets builders and institutions deploy custom staking vaults, while staying anchored to stETH as a shared liquidity layer.Get started building with Lido V3 today: https://lido.fi/stvaults?mtm_campaign=epicenterBlock Space Forum: https://blockspace.forum/NEAR AI Cloud now lets developers deploy OpenClaw—the rapidly growing open-source AI agent platform—inside Trusted Execution Environments, providing hardware-level encryption with cryptographic attestations. With OpenClaw on NEAR AI Cloud, you can run agents with cloud convenience, but without traditional cloud data exposure. No hardware to manage. No trust assumptions required. Learn more at near.ai.

To celebrate Punch Brothers' new record, The Unsung Adventures of Punch Brothers, I'm reposting a fascinating conversation I had with Brittany Haas after she joined the band.This is the first Punch album with Brittany in the line-up so I thought it would be fun to listen back and hear how she joined the band and what her first shows were like.I'd interviewed Gabe Witcher a few days after he played his final shows with Punch Brothers at Telluride and, almost exactly a year later to the day, I spoke with Brittany to chat about joining the band as his replacement. Brittany had just played with Punch Brothers at Telluride, so there was a lovely symmetry to it.At the start I mention the episode I recorded with Brittany and her sister Natalie when they released their duo record Haas.  Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

Your AI bill just stopped behaving like a software bill. For twenty years, IT leaders got very good at counting seats: buy a hundred, pay for a hundred. Then AI swapped the seat for a meter, and the number stopped holding still.This episode follows the burn from three vantage points: a financial analyst rationing a $250-a-month token budget he tore through in two days; the tech executive who watched enterprise AI bills climb 7x, 10x, 20x; and the IT leader at a 300-person company who refused to solve it with a usage dashboard. Along the way: Meta's leaked internal token leaderboard, Uber blowing its entire annual AI budget by April, and the uncomfortable question of who profits when everyone's told to use more.In this episode:Why token-based pricing breaks the budgeting playbook IT has relied on for two decadesWhat happens to the people using the tool when the meter starts running — and why rationing has a hidden costWhy measuring usage is the wrong scoreboard, and who benefits when you keep score anywayThe mid-market move that beats policing: measure centrally, push the judgment to managers, and get clear on what you're optimizing forFeaturing Brian Elliott, CEO of Work Forward; Daryl Dore, Senior Director of IT & Information Security at Higher Logic; and Benjamin, a financial analyst who spoke with us on condition of anonymity.Support our sponsor:This episode is brought to you by Sophos MDR. Running Microsoft security tools and drowning in alerts? Sophos MDR's 24/7 experts investigate and stop the real threats. >>> Learn more at: https://www.sophos.com/en-us/solutions/use-cases/microsoft#ITLeadership  #AICostManagement  #SaaSManagement  #FinOps  #EnterpriseAI  #TokenBurn  #ITAMShow Notes & ResourcesReferenced in this episodeMeta's internal AI token leaderboard (Fortune) — 85,000 employees ranked by token consumption; shut down days after it leaked.Uber burns its 2026 AI budget in four months (Forbes; TechCrunch) — adoption jumps 32% to 84% in a month; spend later capped.Jensen Huang on token consumption as a productivity signal (Tom's Hardware).Gartner: worldwide AI spending forecast to grow 47% in 2026 (Gartner).Zylo 2026 SaaS Management Index — the scale of wasted SaaS spend (Zylo).Brian Elliott's newsletter, Work Forward.Guest: Daryl Dore — Higher Logic.This episode's sponsor: Sophos MDR, in partnership with Softchoice — 24/7 managed detection and response for Microsoft environments. https://www.sophos.com/en-us/solutions/use-cases/microsoft The Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology. 

Machine learning teams are moving faster, but the hard part has not disappeared. The work is shifting from writing and debugging every line of code toward defining the right problem, setting requirements, reviewing outputs, and deciding what belongs in a durable platform.Niels Bantilan, Chief Machine Learning Engineer at Union AI, explains how machine learning work has changed, why coding agents are accelerating prototyping, and what engineers must consider when building infrastructure that supports many teams instead of optimizing one model. He also shares how customer needs become product decisions, why machine learning roles are becoming more specialized, and why measuring AI productivity remains difficult.Key Takeaways• Coding agents reduce time spent on implementation, debugging, and exploration, but engineers still need judgment around architecture, quality, and business value.• Platform teams must balance experimentation with stability by giving users freedom at the edges while protecting a reliable foundation.• Machine learning engineering now spans a wider range of skills, from low level performance work to customer empathy, education, documentation, and developer advocacy.• The best model for a task may depend on complexity. Smaller self hosted models can handle tightly scoped changes, while longer and more complex work may still require stronger hosted tools.Episode Highlights00:50 What Union AI means by an AI runtime for production02:10 How machine learning work has changed over the past five years10:40 The mindset shift from model building to platform engineering15:00 Turning customer problems into reusable product capabilities19:00 Why machine learning roles are becoming more specialized21:50 Using coding agents through specifications, tickets, and code review26:50 Token costs, productivity measurement, and choosing the right modelOne Line That Stuck“I'm still solving problems. It's just the level at which I'm doing it doesn't require me to necessarily get into the weeds of the implementation.”Follow The Tech Trek for more conversations on AI, data, engineering, product, and technical leadership.

In this episode of Shift AI, Andrew Comstock, Senior Vice President and General Manager of MuleSoft from Salesforce, joins host Boaz Ashkenazy for a wide-ranging conversation on governing, securing, and controlling the cost of agentic AI at enterprise scale.The conversation covers how MuleSoft's API-led integration playbook, built during the on-prem-to-cloud shift, is now extending into what the company calls Agent Fabric — bringing governance and controlled connectivity to agent-to-agent communication. Andrew walks through a concrete example of how two internal agents trusting each other by default can leak a customer's order history, and digs into prompt injection, impersonation, and why the security industry's people-focused compliance frameworks now have to account for reasoning software, not just people. He and Boaz also get into token economics, LLM gateways, intent-based routing between local and cloud models, and the emerging trend of companies repatriating some AI workloads on-premise.This episode is essential listening for CTOs, CISOs, platform and integration engineers, and IT and product leaders responsible for governing AI spend and agent security as their organizations scale past pilot projects into production.Chapters[00:01] Andrew Comstock's path to MuleSoft[02:06] First job: tax returns and trumpet reeds[03:21] What MuleSoft does and its extension into Agent Fabric[05:29] From consumer chatbots to enterprise agent connectors[07:22] Governance and security at the enterprise level[10:36] A real example: how two agents can leak an order number[13:45] Connect AI 2025 vs. 2026 — a year of night-and-day change[16:28] Mythos, Fable, and preparing for the LLM that breaks your systems[18:11] Token economics and the true cost of enterprise AI[20:38] The "AI savior" pattern vs. applying IT discipline to AI[22:40] Hybrid deployments, local models, and intent-based routing[27:13] Why AI's uneven acceleration makes prioritization more valuable[28:57] The two-word answer: "coming soon"Connect with Andrew ComstockLinkedIn: https://www.linkedin.com/in/andrewcomstock/Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: info@shiftai.fm

What happens when an AI experiment becomes a production service that your employees, customers, and daily operations depend upon? In this episode of Tech Talks Daily, I speak with Brian Klingbeil, Chief Strategy Officer at Ensono, about AI infrastructure resilience, operational dependency, FinOps, legacy modernization, and the growing pressure to prove that enterprise AI investments are producing meaningful returns. Brian has been speaking with major enterprises through Ensono's Executive Advisory Council. Three years ago, many participants were experimenting with proofs of concept. Today, they are being asked to present AI projects that are already in production, approaching production, or demonstrating a clear return through productivity, lower risk, service quality, or financial results. That progression creates a new problem. When an AI model begins supporting product delivery, customer service, logistics, software development, or internal operations, it becomes part of the company's operating infrastructure. Leaders must then ask familiar IT questions about availability, monitoring, security, incident response, disaster recovery, ownership, and cost. Brian believes FinOps often provides the first warning. Token consumption can be difficult for CFOs and business leaders to interpret, particularly when hundreds of agents are operating across different models. Ensono's internal platform has produced around 1,000 agents, prompting questions about which are effective, which are expensive, and who should carry the cost. We discuss why chargeback and showback could change employee behavior. When AI spending is absorbed by a central corporate budget, teams may have little reason to question whether an expensive model is suitable for a routine task. When the cost reaches their departmental budget, the decision can look very different. Architecture also matters. Brian recommends systems that are loosely coupled and tightly integrated. Companies should be able to replace a model, provider, FinOps tool, or service as the market changes, while still connecting each component closely enough to deliver useful business outcomes. That creates a genuine tradeoff. Providers such as Microsoft, Amazon, Google, OpenAI, and Anthropic can offer specialist capabilities that businesses may want to use. Avoiding every provider specific feature can limit what the technology delivers, while becoming too dependent on one provider can make future change expensive and disruptive. The conversation then turns toward legacy technology. Brian argues that many systems described as outdated still process airline reservations, banking transactions, insurance claims, government services, and other high volume workloads. Turning them off without suitable replacements would create far bigger problems than the word "legacy" suggests. AI can change the modernization decision. Ensono worked with Markerstudy Group to analyze six million lines of RPG code running on an IBM i platform. The resulting plan identified applications that should move elsewhere while preserving workloads that still benefited from the platform's reliability and transaction processing capabilities. Brian treats migration as one possible part of modernization. AI tools can document old code, support modern development environments, and allow younger developers to work with established platforms without immediately beginning a lengthy and expensive replacement program. We also discuss Ensono's use of AI operations. Brian says the company reduced mean time to repair by 50% while processing approximately 50,000 tickets each month. The example shows how AI value can be measured through service quality and operational performance rather than relying entirely on direct revenue. The result is a balanced conversation about moving quickly while building enough control to keep AI dependable. Organizations need space for experimentation, but production services also require ownership, budgets, recovery planning, and people who know what to do when something fails. If one AI model or provider disappeared tomorrow, how much of your business would stop working? Listen to the episode and share your thoughts with me.

Fresh from AALL in Cleveland, Greg reflects on a conference filled with legal information professionals who understand how technology performs under real working conditions. These librarians purchase products, train users, support law schools and courts, and often serve as internal advocates for legal technology. Their expertise makes vendor engagement especially valuable, yet major product announcements were scarce. Marlene balances Greg's conference report with stories from her hiking trip through Zion and Bryce Canyon, plus a brief comparison of Ohio and Utah karaoke culture.The conversation turns to the rapid growth of innovation attorney positions across law firms and legal organizations. Greg and Marlene describe these professionals as translators who connect legal practice, technology, workflow design, and organizational change. Firms are searching beyond traditional legal career paths for people who combine technical fluency with strong interpersonal skills. For law students and junior lawyers facing uncertainty around AI, these emerging roles offer broader career options beyond the familiar associate track.Marlene explores the growing use of AI personas and simulations for professional development. Deposition witnesses, opposing counsel, negotiation partners, and drafting reviewers now appear as interactive characters with distinct goals and behaviors. Lawyers receive a place to practice, make decisions, and receive feedback before working with clients or appearing in court. Greg connects simulation-based learning with legal fiction, including his Beyond the Model series, which uses a fictional law firm to explain AI systems, business pressures, and changes in legal work.The discussion takes a serious turn with a reported AI benchmarking incident involving an agentic model, a breached sandbox, and unauthorized access to Hugging Face resources in search of an answer key. Greg and Marlene examine the episode as a warning about containment, accountability, and excessive faith in technical guardrails. From there, they consider the renewed importance of knowledge management and security as AI systems gain access to documents, financial information, client data, and institutional expertise. Greg predicts growing attention around AI harnesses, structured software layers designed to guide model behavior and produce predictable outputs.Marlene closes with examples of AI moving into client intake, business qualification, and workflow decisions, including an AI legal receptionist designed for smaller firms. The larger shift involves moving beyond simple tool adoption toward redesigned workflows, staffing models, pricing structures, and client service. Token costs are creating immediate budget pressure, while clients are questioning which AI expenses belong on their bills. Greg and Marlene argue firms must connect AI spending with legal judgment, measurable value, and responsible delivery, rather than treating consumption as a proxy for progress.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠[Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

Dianne Penn is Head of Product for Anthropic's AI Research and Labs teams. She joined in 2023 as Anthropic's first technical product manager, when the entire product team was five engineers, and has since helped ship every model from Claude 2 through Fable, and helped incubate Claude Code, MCP, Skills, computer use, tool use, and reasoning. Before Anthropic, she helped build Alexa's AI at Amazon and, before that, traded high-yield bonds at JP Morgan Chase.In our in-depth conversation, we discuss:1. What Anthropic's early days were like2. The inflection points that turned Anthropic from an underdog into the fastest-growing company in history3. How exactly Claude got so good at coding4. The eval-driven development loop her team is pioneering5. How to find joy in AI when everything is moving this fast6. Why Claude's willingness to push back is key to its success7. Where human judgment remains irreplaceable—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and moreMercury—Radically different banking, now with Command—Episode transcript: https://www.lennysnewsletter.com/p/anthropics-first-technical-pm-on—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Dianne Penn:• LinkedIn: linkedin.com/in/dianne-na-penn—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction(02:31) Early Anthropic days(08:55) Big milestones(13:50) Inside the exponential(20:02) Token maxing(23:30) Anthropic Labs and the incubation model(27:30) How the research role works(31:35) How to become a top researcher(35:18) Frontier model safeguards(39:38) Hiring in the AI era(44:16) Building an eval set(47:48) Evals vs PRDs(49:55) The importance of hands-on leadership(52:46) Finding joy in AI(58:10) How Dianne uses Claude(01:01:05) Avoiding overreliance on AI(01:03:50) The constitution that makes Claude better(01:07:11) AI writing and verification(01:11:40) Where human brains will continue to be valuable(01:14:10) Navigating AI with kids(01:16:26) Alignment, the future of the PM role, and burnout(01:21:54) Lightning round and final thoughts—Referenced:• Anthropic: https://www.anthropic.com• Golden Gate Claude: https://www.anthropic.com/news/golden-gate-claude• Dario Amodei's website: https://darioamodei.com• Scaling Laws and Interpretability of Learning from Repeated Data: https://www.anthropic.com/research/scaling-laws-and-interpretability-of-learning-from-repeated-data• Tokenmaxxing: How Top Builders Use AI To Do The Work Of 400 Engineers: https://www.ycombinator.com/library/Pa-tokenmaxxing-how-top-builders-use-ai-to-do-the-work-of-400-engineers• Garry Tan on X: https://x.com/garrytan• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• Introducing Labs: https://www.anthropic.com/news/introducing-anthropic-labs• Louis CK | about airplane Wi Fi: https://www.youtube.com/watch?v=me4BZBsHwZs• What happens after coding is solved? | Fiona Fung (Manager of the Claude Code and Cowork Teams): https://www.lennysnewsletter.com/p/building-the-most-ai-pilled-engineering• The Anthropic Hive Mind: https://steve-yegge.medium.com/the-anthropic-hive-mind-d01f768f3d7b• How to build a company that withstands any era | Eric Ries, Lean Startup author: https://www.lennysnewsletter.com/p/how-to-build-a-company-that-withstands• Fallout on Prime Video: https://www.amazon.com/dp/B0CN4GGGQ2• Fallout (video game): https://fallout.bethesda.net• Claude Tag: https://www.anthropic.com/news/introducing-claude-tag—Recommended books:• Crucial Conversations: Tools for Talking When Stakes Are High: https://www.amazon.com/dp/0071771328• How to Raise an Adult: Break Free of the Overparenting Trap and Prepare Your Kid for Success: https://www.amazon.com/How-Raise-Adult-Overparenting-Prepare/dp/1627791779• Incorruptible: Why Good Companies Go Bad... and How Great Companies Stay Great: https://www.amazon.com/dp/B0FWZZBPZB—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

In this recent episode of Possible, Reid Hoffman sits down with Microsoft CEO Satya Nadella fresh off Microsoft Build 2026. The conversation goes wide: how AI is reshaping work, business, and society—and why the transformation sweeping through software development today is only a preview of what's coming for all knowledge work. Satya makes the case that human capital and "token capital" are now deeply intertwined, that companies—not just countries—must build their own AI capabilities, and that the organizations best positioned to thrive are those that can leverage their unique expertise inside intelligent systems. Reid and Satya also explore Microsoft's enterprise AI vision, Reid's work with Manas on AI-powered scientific discovery, lessons from past technological revolutions, and why demonstrating real, tangible benefits may be the most important thing the industry can do to earn—and keep—the public's trust.You can catch and subscribe to more Possible here: https://www.possible.fm/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Over 3 hours, OpenAI, Anthropic, Google AND Microsoft all dropped new AI upgrades that are live. How you use AI in your work literally changes every day, as frontier labs are racing to roll out big quality of life updates between big model drops. How can you keep up? With our Friday Features show, where we break down the latest AI updates that are live and available to all, and we tell you how to use them and why they matter. This week did not disappoint. You don't want to miss what's now at your fingertips. JARVIS mode, anyone? ChatGPT goes Jarvis Mode, Claude can learn from you, Google unleashes spark agent and 7 more AI updates you can use today -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:ChatGPT Health Syncs Apple and Medical DataClaude Voice Mode Adds Opus and SonnetClaude Voice Mode Supports ConnectorsMicrosoft MAI Image 2.5 Pro Launch DetailsMicrosoft MAI Image Model Benchmark PreviewGoogle Gemini 3.6 Flash and Flashlight ReleaseGemini 3.6 Flash: Token Efficiency UpgradesGoogle Gemini Spark Agent for Task AutomationClaude Cowork "Record a Skill" With Voice NarrationChatGPT Voice on Desktop: Full Jarvis ModeChatGPT Voice Controls Apps via App ShotsCross-Platform AI Skills Sharing (Claude, Codex, GPT)Timestamps:00:00 Recent AI feature updates05:22 Unified health data management09:52 New voice feature explanation11:28 Launch of Microsoft's new image model16:17 Explaining the Gemini 3.5 models17:11 Developers benefiting from 3.6 Flash22:45 Introducing Gemini personal intelligence25:10 Claude Cowork's new skill feature28:32 New default feature in Claude Cowork34:22 Using AI like Iron Man35:09 Excitement for future AI advancements38:20 Wrapping up and subscribingKeywords: ChatGPT Jarvis mode, ChatGPT Health, OpenAI, Anthropic, Claude voice mode, Claude Cowork, Claude record a skill, Microsoft, MAI image 2.5 Pro, AI image generator, Google Gemini, Gemini 3.6 Flash, Gemini 3.5 Flashlight, Gemini Spark, Google AI agent, AI-powered personal assistant, AI agents, Agentic workflows, Multimodal AI, Token efficiency, Image generation, Voice-activated AI, AI-powered task automation, App shots, GPT Live, Remote browser, Computer code execution, Slack integration, GitHub integration, Notion, PowerPoint AI features, Workspace plans, Apple Health integration, Medical records AI, Health data privacy, Consumer AI, Chronic condition management, AI-powered document processing, AI for business, AI model benchmarking, AI for developers, AI economics, Personal intelligence, Automated triggers, Google Docs AI, Team collaboration AISend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

My guest this week is Jerry Douglas and we're celebrating the reissue of Boone Creek's first album.Boone Creek has a fascinating story behind it, which we covered in last week's interview with Scott Billington, who put together the reissue for Craft Recordings.In this episode I chat with Jerry about the place Boone Creek had in his career, his memories of the original sessions and what the band were trying to achieve, what it was like to hear the lost tracks for the first time in 50 years and how playing in Boone Creek helped shape the musician he is today.As always, Jerry was warm, funny, generous and full of fascinating insights. It's always a treat when I get to chat with him.You can buy Boone Creek from Craft Recordings on vinyl, CD or digital downloadFollow Craft on Instagram or Facebook to keep up to date with new reissues of classic roots music. Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

Hallucination is not the biggest risk in clinical AI. Omission is — and it is far harder to detect. John Laursen, SVP at IMO Health, has spent his career on the layer of healthcare AI that gets the least attention: clinical terminology and the semantic data infrastructure underneath every model deployed in a hospital. IMO Health's terminology has been built and curated since 1994 and now sits behind roughly 12 billion terminology search transactions a year across US provider organisations and every major EHR. In this interview with Tjaša Zajc, Laursen makes the case that structured data was necessary but is no longer sufficient. AI reasoning across a thirty-year patient chart needs semantic continuity — an understanding that clinical language recorded in the 1990s and language recorded today can mean the same thing. Without it, health systems are investing in models that cannot reliably interpret their own records. The conversation also covers what happens when ambient AI scribes get it wrong, why accumulated clinical data has become a computational cost rather than an asset, and why clinician trust is the constraint that determines how fast clinical AI can move. Guest: John Laursen — Senior Vice President, IMO Health (Chicago, US) Host: Tjaša Zajc — Faces of Digital Health What the conversation covers: - Why omissions, not hallucinations, are the underrated risk in clinical AI - What a semantic layer does that structured data alone cannot - How clinical terminology maps to SNOMED CT and ICD-10 — and why those code sets were built for different purposes - Ambient AI scribes: what happens when a model mishears or over-infers a diagnosis - The billing and clinical consequences of an error entering the patient record - Why problem lists hundreds of entries long now cost money in token burn - Patient-generated and AI-generated content entering the EHR, and why health systems resist it - Translating lay language into clinical terminology without losing specificity - Ambient documentation, billing intensity and friction with payers - How data quality expectations differ between the US, the NHS, the Gulf states and Singapore - Who governs clinical data as coding complexity increases - Why AI performance breaks down on rare disease and the difficult 20% of cases - Knowledge graphs as a grounding source for clinical AI models - What health systems should require from AI vendors before clinical deployment Chapters: 02:20 Why the data layer decides what clinical AI can do 03:27 Inside IMO Health: 12 billion terminology searches a year 05:36 Keeping terminology current: SNOMED, ICD-10 and clinical governance 07:35 The semantic bridge: why structured data alone is not enough 10:17 Patient language versus clinical language in the record 12:23 When an ambient scribe mishears: clinical and billing consequences 14:53 Omissions, bloated problem lists and unnecessary token burn 19:12 Outside the US: the NHS, the Gulf, Singapore and coding complexity 20:46 Who governs clinical data as complexity increases 23:35 Patient-side AI recorders and resistance to external data 26:08 Ambient documentation, billing intensity and payer friction 29:21 The last 20%: rare disease, model limits and AI governance 33:38 Grounding, clinician trust and the cost of misfiring Faces of Digital Health: Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 LinkedIn: https://www.linkedin.com/company/faces-of-digital-health #digitalhealth #healthcareAI #clinicalinformatics #EHR #ambientAI #interoperability #healthdata #SNOMED #healthIT #medicalcoding

This week, Chad has another run-in with the law and Cy flies home. Sign up for Chad's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠texting list here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Or, text the word CHAD to 208-379-6947! Sign up for Cy's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠texting list here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Or⁠, text the word SHOW to 202-771-5171! This episode is brought to you by ⁠⁠⁠⁠⁠⁠BetterHelp⁠⁠⁠⁠⁠ and ⁠Chime⁠! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ --- Follow us on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠! Chad Daniels (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@ThatChadDaniels⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠) is a Dad, Comedian, and pancake lover. With over 750 million streams of his 5 albums to date, his audio plays are in the 99th percentile in comedy and music on Pandora alone, averaging over 1MM per week. Chad's previous album, Footprints on the Moon was the most streamed comedy album of 2017, and he has 6 late-night appearances and a Comedy Central Half Hour under his belt. Cy Amundson (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CyAmundson⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠) With appearances on Conan, Adam Devine's House Party, and Comedy Central's This is Not Happening, Cy Amundson is fast-proving himself in the world of standup comedy. After cutting his teeth at Acme Comedy Company in Minneapolis, has since appeared on Family Guy and American Dad and as a host on ESPN's SportsCenter on Snapchat. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Lin Qiao is the Co-Founder and CEO of Fireworks AI, the leading specialized intelligence and AI inference platform that last week raised $1.5BN at a whopping $17BN valuation. With just 200 people, the company has hit $1BN in ARR and expects to hit $2BN before the end of the year. Prior to Fireworks, Lin spent several years at Meta including on the founding team of PyTorch.  AGENDA: 00:07 — Why Did Fireworks Bet on Inference When Everyone Else Was Chasing Training? 00:13 — Can Open-Source Models Turn AI Infrastructure into a Commodity? 00:19 — Should Enterprises Trust Chinese Open Models With Their Most Sensitive Data? 00:25 — Will Model Progress Keep Moving This Fast—or Are We Nearing a Plateau? 00:28 — Will the Multi-Model World Create a $100BN Routing Layer? 00:37 — How Much Will AI Token Usage Explode Over the Next Two Years? 00:43 — Will Token Costs Fall 10x—and Unleash 100x More Demand? 00:49 — Does Fireworks Eventually Have to Build Its Own Data Centres? 01:02 — What Is the Real Bottleneck Holding Back the AI Economy?  

For generations, the narrative sold Black folks a dangerous promise: proximity to whiteness equals safety. But stepping into a primarily white space without a safety net of your own people isn't progress, it's exposure.From the 1841 capture of Solomon Northup to the 1936 creation of the Green Book, history has repeatedly proven the fatal reality of being the "only one." Today, the tragic case of Nolan Wells reminds us why that nagging anxiety in a room full of white faces isn't paranoia. It is a highly evolved survival instinct forged by a history of betrayal.Sources:Twelve Years a Slave by Solomon NorthupThe Negro Motorist Green Book by Victor Hugo GreenSundown Towns by James W. Loewen

Ramez Naam is an investor at Planetary VC and a longtime clean energy and AI expert. In this conversation, we break down the energy bottleneck constraining AI growth — from gas turbines and batteries to floating ocean data centers and Elon's orbital data center ambitions. We also cover why bitcoin miners are pivoting to AI infrastructure, general vs. narrow superintelligence, and the data bottleneck reshaping AI training.====================Turn every conversation into a searchable business asset with PLAUD NotePro. Visit https://Plaud.ai/pomp  and use code POMP for 15% off.====================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/pomp====================Uphold is the easiest way to buy and sell crypto unlike any other platform allowing you to trade in just one step between any supported asset. Check them out at https://www.uphold.com/pomp/ This video includes a paid sponsorship with Uphold. I'm compensated by Uphold for promoting its products and services and may receive commissions from referrals. Terms apply. Not available in all jurisdictions. Digital assets are risky and may result in the total loss of your capital.====================0:00 - Intro1:03 - Why power is the real bottleneck for AI & solutions7:35 - Elon's orbital data center thesis11:17 - Cooling & maintenance challenges in space15:06 - Panthalassa: floating ocean data centers19:16 - Base Power & Texas deregulated grid21:30 - Giga Energy: from bitcoin mining to AI infrastructure22:44 - American Consolidated Electric & supple chain bottlenecks24:58 - General vs. narrow superintelligence33:02 - Where untapped data lives & building a data moat36:47 - Token costs, open source models & model routing41:53 - What is the mission Ramez is going after?