POPULARITY
Categories
313 episodes with Dram
44 episodes with Dram
54 episodes with Dram
25 episodes with Dram
20 episodes with Dram
33 episodes with Dram
30 episodes with Dram
17 episodes with Dram
32 episodes with Dram
8 episodes with Dram
11 episodes with Dram
16 episodes with Dram
20 episodes with Dram
29 episodes with Dram
13 episodes with Dram
27 episodes with Dram
14 episodes with Dram
18 episodes with Dram
12 episodes with Dram
33 episodes with Dram
16 episodes with Dram
9 episodes with Dram
9 episodes with Dram
14 episodes with Dram
8 episodes with Dram
8 episodes with Dram
5 episodes with Dram
9 episodes with Dram
6 episodes with Dram
10 episodes with Dram
6 episodes with Dram
12 episodes with Dram
20 episodes with Dram
10 episodes with Dram
4 episodes with Dram
3 episodes with Dram
14 episodes with Dram
3 episodes with Dram
3 episodes with Dram
5 episodes with Dram
4 episodes with Dram
4 episodes with Dram
4 episodes with Dram
10 episodes with Dram
4 episodes with Dram
12 episodes with Dram
5 episodes with Dram
6 episodes with Dram
4 episodes with Dram
7 episodes with Dram
4 episodes with Dram
3 episodes with Dram
4 episodes with Dram
13 episodes with Dram
Meer weten over de mogelijkheden bij Saxo Bank? Klik dan op deze link: https://refer.saxo/DeAandeelHouderMeer info over de mogelijkheden bij Kraken? Ga naar:https://www.kraken.com/nl-nl/ Boek Buffett & Co bestellen? https://www.borgerhoff-lamberigts.be/shop/boeken/buffett-coKortingscode: AANDEELHOUDERLid worden van de aandeelhouder? Ga naar: https://www.deaandeelhouder.nl/premium/ Nu lid worden van DeAandeelhouder Pro? Ga naar:https://www.deaandeelhouder.nl/login/?redirect_to=https://www.deaandeelhouder.nl/mijn-account/pro/Lid worden van ProBeleggen? Ga naar: https://www.probeleggen.nl/aanmelden/registreren/ In de wekelijkse podcast van DeAandeelhouder ontvangt Nico Inberg diverse experts uit de financiële wereld om te praten over de beurs, beleggen en aandelen. Deze week verwelkomen wij Marc Langeveld van Antaurus Capital Management. Onderwerpen die aan bod komen zijn SpaceX, ASML, Besi, Oracle, Kinepolis, Adyen & nog veel meer!Volg DeAandeelhouder op andere kanalen:Website: https://www.deaandeelhouder.nl/ Twitter (X): https://twitter.com/deaandeelhouderTikTok: https://www.tiktok.com/@deaandeelhouderInstagram: https://www.instagram.com/deaandeelhouder/Facebook: https://www.facebook.com/DeAandeelHouder/LinkedIn: https://www.linkedin.com/company/de-aandeelhouder-nl/Tijdslijn:00:00 - 06:05 Opening06:05 - 12:30 Verbazing van de week12:30 - 14:03 Olieprijs + Trump14:03 - 22:48 Hyperscalers22:48 - 26:30 Software 26:30 - 31:40 Dram & geheugenchips31:40 - 34:30 Kinepolis34:30 - 41:43 Adyen41:43 - 49:25 SpaceX49:25 - 56:35 ASML56:35 - 58:42 Aalberts58:42 - 1:01:30 Basic-Fit1:01:30 BesiOntvang al onze exclusieve analyses, video's en beurscontent:https://www.deaandeelhouder.nl/premium/Bekijk het software rapport:https://www.deaandeelhouder.nl/columns/welke-software-aandelen-verdienen-de-koersdaling-en-welke-niet/Met een premium abonnement krijgt u wekelijks exclusieve video's en uitleg over potentieel koopwaardige aandelen, regelmatig artikelen met tips om op een verstandige manier met uw geld om te gaan, verder krijgt u tweewekelijks toegang tot de chatsessie met Nico Inberg en als klap op de vuurpijl krijgt u iedere zaterdag ons online magazine. Een kleine investering, voor een veel mooier rendement.
The desk at RBC Capital Markets that sits behind 90% of Canada's ETF market has a view of where flows are really going — and it's not what most advisors expect.Pierre Daillie sits down with Valerie Grimba, Head of Global ETF Strategy at RBC Capital Markets, for a wide-ranging conversation about the forces quietly reshaping how Canadian advisors build portfolios. Valerie's team serves as designated broker to roughly 300 ETF mandates and acts as authorized participant across the majority of the Canadian ETF market — giving her a real-time, flow-level view of investor behaviour that almost nobody else has. From the structural fracture that 2022 opened in the 60/40 model, to the liquidity misconceptions her desk corrects every single day, to the explosive rise of asset allocation ETFs, covered call strategies, AAA CLOs, and precision thematic plays, this conversation covers the full terrain of where the ETF market stands today — and where it is heading.CHAPTERS00:00 — Introduction: The 60/40 failure and Canada's ETF rebuild 02:11 — Valerie's career arc: Bear Stearns, New York, New Zealand, RBC 04:21 — How the RBC ETF market making desk actually works 05:36 — What a designated broker does — and why it matters 08:18 — Flash crashes, Liberation Day, and ETFs as a release valve 10:08 — The RBC market view: yellow flags, narrow breadth, and a 12–18 month outlook 13:29 — How ETF flows changed: from net outflows in risk-off to rotation 14:05 — Gold: zero correlation, the incongruent timing, and the 2026 outlook 15:40 — Higher for longer: what advisors are missing about the rate environment 17:46 — How 2022 changed advisor behaviour and launched a new ETF ecosystem 21:49 — Covered call ETFs: what advisors are still getting wrong 24:19 — Retail vs. institutional: why retail has been outperforming 25:20 — Private assets in an ETF wrapper: the square peg, round hole problem 31:11 — What RBC looks for before taking on a designated broker mandate 32:28 — The Pac-Man of Canadian ETF flows: asset allocation ETFs 36:29 — CAGE, XEQT, FBAL: who is actually buying all-in-one ETFs 38:58 — TLT as widowmaker and the search for yield without duration risk 40:36 — AAA CLOs, active fixed income, and aggregate bond ETFs 43:07 — CTAs, trend following, and the rise of alternatives in Canada 44:30 — Why GIC sectors are becoming antiquated — and what's replacing them 45:48 — DRAM, memory chips, and the new thematic precision playbook 47:11 — Single stock ETFs: access, covered call overlays, and trade-offs 49:07 — The #1 ETF liquidity misconception — and the three layers advisors need to know 53:28 — Best execution practices: limit orders, timing, and when to call the desk #ETF #CanadianETF #ETFInvesting #PortfolioConstruction #CoveredCallETF #AssetAllocation #XEQT #FixedIncome #AlternativeInvestments #WealthManagement #FinancialAdvisor #InvestmentStrategy #ETFLiquidity #RBCCapitalMarkets #MarketOutlook #ThematicETF #PassiveInvesting #ETFTrading #InsightIsCapital #AdvisorAnalyst
The Head of our Europe and Asia Technology Team, Shawn Kim, explains how AI's appetite for memory chips is boosting the cost of everything from data centers to smartphones, with consequences that may reach far beyond the tech industry.Read more insights from Morgan Stanley.----- Transcript -----Shawn Kim: Welcome to Thoughts on the Market. I'm Shawn Kim, Head of Morgan Stanley's Europe and Asia Technology Team. Today, we're talking about chipflation – when memory chips stop getting cheaper over time, and become more expensive and even harder to find. It's Monday, June 8th, at 3pm in London.Memory chips are easy to ignore, until your laptop slows down, your phone costs more, or your cloud bill jumps. Memory is the computer's workspace. It holds whatever the machine needs at that moment, whether that is a web search, a video, a spreadsheet, or an AI model answering a question. DRAM is the fast memory inside servers, PCs and phones. NAND is what stores files in solid-state drives. And HBM, or high bandwidth memory, is the high-performance version sitting right next to the AI chip, helping them move huge amounts of data quickly. That last one – HBM – is key because AI has become intensely memory hungry. Memory prices have risen more than six-fold over the last year, a sharp break from decades when the cost of DRAM generally kept falling. The pressure is coming from AI infrastructure buildouts. We see servers accounting for 59 percent of DRAM demand by 2028, up from 37 percent in 2023. We also see enterprise solid-state drives reaching 65 percent of NAND demand, up from 18 percent. And simply put, data centers are taking a much bigger share of the memory pie. AI memory use is climbing fast, and at every scale. A newer AI chip uses 7.2 times more HBM than earlier generations. A full system uses about 65 times more. Across an entire AI data center buildout, the jump gets even bigger. HBM has gone from roughly 10 terabytes in 2020 to about 18 petabytes in 2026, orders of magnitude more. This demand is running into a supply chain that cannot respond quickly. New memory capacity takes years to build, qualify and ramp up. Supply relief is a process, not a switch. And that creates a two-tier market. Large AI and cloud buyers can sign long-term agreements, prepay and secure priority access. Traditional buyers, including PC makers, smartphone makers and industrial hardware companies, must compete for what remains. This impacts everyday products. In 2027, we see PC memory demand potentially facing a 15 percent shortfall, equivalent to about 58 million PCs. Smartphones could face a 12 percent shortfall, equivalent to about 134 million units. Companies may have to raise prices, cut specifications, delay launches, and accept lower profits. The dollar numbers are striking. We see the memory market growing from about $220 USD billion in 2025 to about $890 billion in 2026. Expectations for 2026 memory revenue rose 71 percent in just three months. That implies roughly $600 USD billion of incremental memory revenue in 2026, more than the annual market for smartphones, PCs, or servers, each taken on its own. The broader economy may not see a significant direct inflation shock. We estimate the direct impact on headline CPI at about 0.1 percent in 2026. But pressure is showing up in producer prices, in corporate margins, cloud costs, capital spending plans and delayed technology upgrades. AI has turned memory from the cheapest part of the digital economy into one of its most contested resources. These tiny chips most people never think of may now decide what gets built or delayed, and how much we all end up paying. Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.
Frederico Francisco desvaloriza o susto com a fuga de ar na Estação Espacial. O engenheiro aeroespacial explica que, numa estrutura complexa, as fugas são quase inevitáveis.See omnystudio.com/listener for privacy information.
เกาหลีใต้ “กำลังรวยเร็วสุด” ในประวัติศาสตร์ประเทศในปีนี้ | ลงทุนแมนจะเล่าให้ฟัง เกาหลีใต้ “กำลังรวยเร็วสุด” ในประวัติศาสตร์ประเทศในปีนี้ และสิ่งที่สำคัญที่สุดของเกาหลีตอนนี้ ไม่ใช่ซีรีส์ แต่คือ “DRAM” ที่มีเพียงแค่ 2 บริษัท ที่ลากประเทศ นี่คือสิ่งที่คุณควรรู้.. ลองนึกภาพตลาดหุ้นทั้งประเทศ ที่ขึ้นเป็น “เท่าตัว” ภายในเวลาไม่ถึงครึ่งปี นี่ไม่ใช่เรื่องสมมติ แต่คือสิ่งที่กำลังเกิดขึ้นจริง ๆ ที่ประเทศเกาหลีใต้ ในปี 2026 ต้นปี ดัชนี KOSPI อยู่ที่ราว 4,300 จุด วันที่ 1 มิถุนายน 2026 ดัชนีทะลุ 8,700 จุด ทำจุดสูงสุดเป็นประวัติศาสตร์ เท่ากับว่าตลาดหุ้นเกาหลี บวกไปกว่า 100% ตั้งแต่ต้นปี คำถามคือ อะไรทำให้ตลาดหุ้นของทั้งประเทศ ร้อนแรงขนาดนี้ ? คำตอบสั้น ๆ คือ ชิปความจำที่เรียกว่า “DRAM” แล้วเหตุการณ์นี้เกิดขึ้นได้อย่างไร… ลงทุนแมนจะเล่าให้ฟัง
Kevin Mack, the new president of Via Licensing Alliance, joins Eli for the Clause 8 season finale.Kevin talks about Via's plans to build its next patent pools around "de facto" standards — technology the market adopted on its own, with no standards body behind it — which would push collaborative licensing into territory it has never touched. Mack also takes a hard look at the royalty-free models spreading through tech and AI, from AV1 to the new Shared AI License Foundation (SAIL), argues that "free" rarely stays free, and explains why he's optimistic about where the patent system is heading.Kevin and Eli also discuss:*Via's model and the "tipping point" that turns a pool from a few licensors into thousands of licensees*"De facto" standards: pooling patents for technology no standards body ever blessed*Leadership turnover at Via, the HEVC pool's move to Access Advance, and a new strategy-and-growth group*The push into semiconductors, including a new DRAM memory program*AV1, SAIL, and why Mack thinks royalty-free rarely stays free*Whether AI patents are as "foundational" as advertised — and why "AI is not new"*Efficient infringement, patents as property rights, and why companies ultimately take a license*The mood out of Via's Rome summit and a US patent system tilting back toward ownersNotable names, companies & standardsPeople: Kevin Mack (president, Via Licensing Alliance); Heath Hoglund (former Via president); John Amster (Jamster Capital; RPX co-founder)Organizations: Via Licensing Alliance (Via LA), MPEG LA, Dolby, Access Advance, Alliance for Open Media, Shared AI License Foundation (SAIL), WIPO (PatentScope), DOJ, USPTOSAIL founders / board (public): Anthropic, Genentech, IBM, Meta, Microsoft; board observers eBay and TD Bank Group; members include Block and FigmaStandards & technologies: AAC, AVC (H.264), HEVC (H.265), AV1, MPEG-2, Qi wireless charging, DRAM memory, SEP / FRANDDisclaimer This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.voiceofip.com
Patrick Moorhead and Daniel Newman cover Daniel's acquisition of Enterprise Technology Research, IBM's historic $15 billion single-day commitment spanning quantum and open-source security, Anthropic's Claude Opus 4.8, and the heaviest single earnings night of the season featuring Dell, Marvell, Salesforce, Synopsys, Snowflake, HP, and Micron crossing $1 trillion in market cap. The handpicked topics for this week are: Anthropic Releases Claude Opus 4.8: Six Weeks After 4.7 Anthropic dropped Opus 4.8 just six weeks after 4.7, claiming it surpasses GPT-5.5 and Gemini 3.1 Pro on agentic coding, knowledge work, and computer use. Benchmark improvements across the board: agentic coding up from 64.3% to 69.2%, knowledge work from 1753 to 1890, agentic computer use from 82.8% to 83.4%. Three new features ship alongside it: Dynamic Workflows for multi-subagent orchestration inside Claude Code, Effort Control for managing token spend, and mid-task system messages via the API. Fast mode is now 2.5x faster and 3x cheaper. Pat's honest take: what it says on paper is good, particularly on tool triggering and citation precision, but he has lost significant trust in the company and is watching closely. (The Decode) IBM Commits $10 Billion to Quantum: The Largest Single Quantum Bet in History IBM announced a $10 billion commitment over five years targeting a large-scale fault-tolerant quantum computer by 2029, landing the same day as the $5 billion Project Lightwell announcement for a single-day IBM strategic commitment of $15 billion. Pat has been calling 2029 to 2031 as the realistic commercial quantum window and calls this the strongest single corporate financial signal yet that the timeline is real. Daniel's framing: IBM wants to be the NVIDIA of quantum, and with a $10 billion commitment, it's sending a flare to the entire industry that pure-play quantum companies cannot compete at this balance sheet level. (The Decode) IBM and Red Hat Launch Project Lightwell: $5B to Secure Open-Source Software IBM and Red Hat committed $5 billion and a global force of 20,000 engineers to secure open-source software for enterprises through frontier agentic AI, anchored by 11 of the largest US and Canadian banks including Bank of America, Goldman Sachs, JPMorgan Chase, Mastercard, and Visa. Pat's read: this is the productization answer to Anthropic Mythos. Mythos found the vulnerabilities. Lightwell is the industrial-scale patching and validation layer enterprises can actually buy on a subscription. Daniel adds that IBM is flexing its engineering talent base as a premium strategic asset, a direct counter to the narrative that AI replaces engineers. (The Decode) Anthropic Project Glasswing: 23,000 Vulnerabilities Found Across 1,000 OSS Projects Anthropic's Claude Mythos scanned more than 1,000 widely deployed open-source projects and surfaced approximately 23,000 candidate vulnerabilities, with 1,094 confirmed as critical severity. The Cyber Verification Program now gates the strongest cyber-capable Claude variant behind vetted defenders only. While the tool creates real value, the surface of attack will likely grow as fast as any tool built to defend it. (The Decode) Anthropic in Talks to Run Claude on Microsoft Maia 200 CNBC and The Information reported Microsoft is in active negotiations to supply Anthropic with its custom Maia 200 inference chip, which would make Anthropic the only frontier lab simultaneously running production workloads on four distinct silicon stacks: NVIDIA, AWS Trainium, Google TPU, and Microsoft Maia. Pat's context: Maia 200 delivers 30% better tokens per dollar than the latest Azure fleet per Satya Nadella, and this deal would be Maia's first major external deployment. Daniel's read: what can be built will be sold right now, and Anthropic chasing every available compute source is simply the structural reality of growing at 80x when you planned for 10x. (The Decode) The Flip: Is AI CapEx Too Expensive to Earn Its Return? Pat takes the affirmative. With $725 billion in hyperscaler CapEx tracking for 2026, likely $1 trillion next year, memory has become the choke point making it even more expensive, and open-source models have closed enough of the quality gap for most enterprise tasks that the premium of frontier APIs is increasingly hard to justify. A recent Signal65 white paper shows on-prem payback at 18 months. Daniel's counter: Dell just booked $24 billion in AI orders in a single quarter. Agentforce crossed $1 billion ARR at 169% growth. NVIDIA guided to $91 billion. Only 20% of enterprises are using AI and only 2% of consumers. Both hosts admitted off the flip their notes looked nearly identical. (The Flip) Micron Crosses $1 Trillion Market Cap Micron became the 12th US company ever to cross $1 trillion in market cap, surging 19% on May 26th as UBS raised its price target to $1,625, implying a $1.8 trillion market cap. Samsung's Q1 memory ASP jumped 146% year over year. DRAM spot prices spiked 55 to 60% quarter over quarter. Daniel has been pounding this call since sub-$100 and calls it a cycle elongated beyond anything seen in the 27 prior memory cycles, driven by HBM capacity reallocation away from consumer DRAM creating structural shortage. (Bulls and Bears) Dell Technologies Q1 FY27: The Biggest Enterprise AI Infrastructure Print of 2026 Record $43.8 billion revenue, up 88% year over year, crushing the $35.7 billion consensus by $8 billion. AI-optimized servers at $16.1 billion, up 757% year over year. $24.4 billion in AI orders booked in a single quarter. FY27 AI server revenue guide raised from $50 billion to $60 billion. Non-GAAP EPS of $4.86 beat the $2.96 consensus by 64%. Stock up 18% after hours. Pat's framing: Dell was very clear about what they were going to do. Rack engineering, sales, and service. The basics. And they executed the basics at an extraordinary level while building a special relationship with NVIDIA who views Dell as a market maker for both enterprise and NeoCloud. Daniel's add: play nice and win. Michael Dell navigated the political landscape brilliantly and pulled the entire Dell brand along with him. (Bulls and Bears) Marvell Technology Q1 FY27: Record Revenue, Data Center at 76% of Mix Record $2.418 billion revenue, up 28% year over year. Data center at $1.833 billion, up 27% year over year, now 76% of total revenue. Q2 guide of $2.7 billion at midpoint accelerates growth to 35% year over year. Operating cash flow a record $638.8 million. Daniel went on TV and said it's "written in the stars," arguing the market had misunderstood this one for too long by conflating its custom AI ASIC story with the full breadth of its connectivity and networking portfolio. Pat's closing: the shorts are eating it now and the custom AI ASIC versus merchant GPU debate is finally settling into the right answer, which is both in lockstep. (Bulls and Bears) Salesforce Q1 FY27: Agentforce Crosses $1 Billion ARR Revenue $11.13 billion, up 13% year over year. Non-GAAP EPS of $3.88 crushed the $3.12 consensus by 24%. Agentforce ARR crossed $1 billion, up 169% year over year, with 28.6 trillion tokens processed, up 152% quarter over quarter. 50% of Agentforce bookings came from existing customers expanding. Daniel flagged the $25 billion accelerated buyback funded by new debt as an interesting signal worth watching. Pat's bottom line: it's not perfect, but certainly no "SaaSpocalypse" in those numbers. (Bulls and Bears) Synopsys Q2 FY26: First Full Quarter With Ansys Integrated Revenue $2.276 billion, up 42% year over year, beating consensus. Non-GAAP EPS of $3.35 beat $3.15. FY26 guide raised to $9.665 billion midpoint. Daniel's framing: every chip runs through Synopsys tools, and the Ansys addition makes it the full-stack co-design platform Jensen Huang keeps talking about. Synopsys is not just the pick and shovel of current AI silicon. It is the pick and shovel of quantum, robotics, and space as well. (Bulls and Bears) Snowflake Q1 FY27: Strongest Sequential Dollar Growth in Company History Product revenue $1.33 billion, up 34% year over year, the strongest sequential dollar growth in Snowflake history. Net revenue retention 126%. FY27 product revenue guide raised to $5.84 billion. Natoma acquisition announced for secure agentic enterprise connectivity. New $6 billion multi-year AWS commitment. Daniel's closing: proprietary unique data is the real moat of the agentic era, and that data has to live somewhere. It is going to go to platforms like Snowflake. (Bulls and Bears) HP Inc. Q2 FY26: Eight Straight Quarters of Growth With AI PCs at 44% of Shipments Revenue $14.4 billion, up 9% year over year, the company marks its eighth consecutive quarter of top-line growth. Non-GAAP EPS of $0.86 beat the prior guide. Personal Systems at $10.2 billion, up 13%, with 30% operating profit growth. AI PCs jumped from 35% to 44% of shipments quarter over quarter, with HP guiding to 60 to 70% next fiscal year. FY26 EPS guide raised. Pat's note: they still need a permanent CEO, which would help investors sleep better at night. Daniel's add: the real explosive moment for device companies comes when AI moves to the edge and enterprises shift from expensive frontier model consumption to on-device inference. (Bulls and Bears) Everpure Q1 FY27: Record Revenue, Rebrand Complete Record revenue of $1.1 billion, up 35% year over year. Product revenue $577 million, up 55%. Subscription ARR at $2 billion. FY27 guide raised to $4.41 to $4.51 billion. Pure Storage officially completed its rebrand to Everpure. Daniel's emerging thesis: the agentic era has focused enormous attention on memory and compute, but after the inference runs, the data has to sit somewhere. Storage has not seen its full inflection yet and Everpure is well positioned when that wave arrives. (Bulls and Bears) The Decode Anthropic Releases Claude Opus 4.8 May 28 https://techcrunch.com/2026/05/28/anthropic-releases-opus-4-8-with-new-dynamic-workflow-tool/ IBM Commits $10B Over Five Years to Quantum Computing the Same Day as $5B Project Lightwell, Bringing IBM's One-Day AI https://www.barrons.com/articles/ibm-stock-quantum-computing-aafbb1eb IBM + Red Hat Announce Project Lightwell https://newsroom.ibm.com/2026-05-28-ibm-and-red-hat-commit-5-billion-to-redefine-the-future-of-open-source-in-the-ai-era Anthropic Project Glasswing / Claude Mythos Finds 23,000 Potential Vulnerabilities Across 1,000+ Open-Source Projects https://www.securityweek.com/anthropic-mythos-detected-23000-potential-vulnerabilities-across-1000-oss-projects/ Anthropic Negotiating to Run Claude on Microsoft's Maia 200 AI Chips https://www.cnbc.com/2026/05/21/anthropic-microsoft-maia-200-ai-chip.html OpenAI + Anthropic Walk Back the AI Jobs Apocalypse Ahead of IPOs https://finance.yahoo.com/sectors/technology/articles/ai-chiefs-walk-back-job-193605798.html https://x.com/RiskCentre/status/2059397756016611668 The Flip Is AI Capex Becoming Too Expensive to Earn Its Return — and Will the Result Be a Forced Shift to Open-Source and Smaller Use-Case-Specific Models, or a Continued $725B+ Hyperscaler Buildout That Vindicates the Capex on Productivity Gains? FOR: The shift is to open-source + smaller use-case-specific models with better token economics, not away from AI https://x.com/danielnewmanUV/status/2059822712122400975 DeepSeek 75% permanent price cut + Anthropic Claude Code restriction reversal https://www.buildfastwithai.com/blogs/ai-news-today-may-26-2026 $190B Microsoft capex + $725B+ aggregate hyperscaler capex with no analog ROI yet https://www.buildfastwithai.com/blogs/ai-news-today-may-26-2026 AGAINST: Salesforce Agentforce ARR crossed $1B this quarter on 28.6T tokens processed https://www.stocktitan.net/sec-filings/CRM/8-k-salesforce-inc-reports-material-event-3b8ead2852bb.html Lenovo +105% AI revenue, +84% Q4; Dell $43B AI backlog: the AI infrastructure flywheel is converting capex to revenue today https://investor.marvell.com/news-events/press-releases/detail/1023/marvell-technology-inc-reports-first-quarter-of-fiscal-year-2027-financial-results NVIDIA $91B Q2 guide + $1T Blackwell+Vera Rubin CY25-CY27 reaffirmed https://www.cnbc.com/2026/05/20/were-raising-our-price-target-on-nvidia-after-another-knockout-quarter-and-guide-.html DeepSeek + Chinese price war is a Chinese export-controls story, not a US economic ceiling story https://www.cnbc.com/2026/05/21/anthropic-microsoft-maia-200-ai-chip.html Bulls & Bears Micron (NASDAQ: MU) Crosses $1 TRILLION Market Cap for the First Time https://www.cnbc.com/2026/05/26/micron-stock-trillion-market-cap.html Dell Technologies Q1 FY27 ACTUALS https://www.cnbc.com/2026/05/28/dell-q1-earnings-report-2027.html Marvell Technology Q1 FY27 ACTUALS https://investor.marvell.com/news-events/press-releases/detail/1023/marvell-technology-inc-reports-first-quarter-of-fiscal-year-2027-financial-results Salesforce CRM Q1 FY27 ACTUALS https://investor.salesforce.com/financials/quarterly-results/ Synopsys SNPS Q2 FY26 ACTUALS https://investor.synopsys.com/events-and-presentations/events/event-details/2026/Q2-Fiscal-Year-2026-Earnings/default.aspx Snowflake SNOW Q1 FY27 ACTUALS https://www.businesswire.com/news/home/20260527027931/en/Snowflake-Reports-Financial-Results-for-the-First-Quarter-of-Fiscal-2027 HP Inc. HPQ Q2 FY26 ACTUALS https://finance.yahoo.com/markets/stocks/articles/hp-q2-earnings-call-highlights-230459161.html Everpure (NYSE: P, formerly Pure Storage) Q1 FY27 ACTUALS https://investor.salesforce.com/financials/quarterly-results/ Synopsys SNPS Q2 FY26 ACTUALS https://investor.synopsys.com/events-and-presentations/events/event-details/2026/Q2-Fiscal-Year-2026-Earnings/default.aspx Snowflake SNOW Q1 FY27 ACTUALS https://www.businesswire.com/news/home/20260527027931/en/Snowflake-Reports-Financial-Results-for-the-First-Quarter-of-Fiscal-2027 HP Inc. HPQ Q2 FY26 ACTUALS https://finance.yahoo.com/markets/stocks/articles/hp-q2-earnings-call-highlights-230459161.html Everpure (NYSE: P, formerly Pure Storage) Q1 FY27 ACTUALS https://www.prnewswire.com/news-releases/everpure-announces-first-quarter-fiscal-2027-financial-results-302783502.html
We often associate Taiwan with chips. Taiwanese chips. It's their thing right? But Taiwan's strength is actually only in logic chips. In the industry's other big sector, memory and DRAM memory in particular, Taiwan is second-tier. Hardly a player. It's not that the Taiwanese haven't tried to break into DRAM before. In fact, they spent billions trying for two decades. They just keep losing at it over and over again. In this video, we look at Vanguard, TI-Acer, Taiwan Memory Corporation and Taiwan's DRAM failure.
We often associate Taiwan with chips. Taiwanese chips. It's their thing right? But Taiwan's strength is actually only in logic chips. In the industry's other big sector, memory and DRAM memory in particular, Taiwan is second-tier. Hardly a player. It's not that the Taiwanese haven't tried to break into DRAM before. In fact, they spent billions trying for two decades. They just keep losing at it over and over again. In this video, we look at Vanguard, TI-Acer, Taiwan Memory Corporation and Taiwan's DRAM failure.
Cette semaine : 007: First Light, Marathon - Nightfall (Saison 2), The Witcher 3 - Songs of the Past, Call of Duty: Modern Warfare 4, Destiny 2 en mode maintenance, MindFocuser, Obsidian + Notebook Navigator + Ulysses + Scrivener, Taphouse, Captain's Deck, Rooster, Boards of Canada - Inferno, Nvidia et le gaming PC, et Corsair se met à la DDR5 chinoise. Lisez plutôt Torréfaction #373 : Marathon S2, 007: First Light, CoD: Modern Warfare 4, DLC pour The Witcher 3, plein d'apps pour écrire, et le DRAM de la RAM avec sa vraie mise en page sur Geekzone. Pensez à vos rétines.
Il fermo nazionale dell autotrasporto previsto dal 25 al 29 maggio è stato sospeso dopo l'incontro di venerdi 22 Maggio a Palazzo Chigi fra Governo e associazioni di categoria. La protesta era nata per l'aumento dei costi del carburante, con il gasolio passato in meno di due mesi da 1,70 a oltre 2,10 euro al litro, e per gli effetti considerati insufficienti del taglio generalizzato delle accise. Dal confronto con l'esecutivo è arrivato un pacchetto da circa 300 milioni di euro sotto forma di credito d imposta per compensare parte dei rincari sostenuti dalle imprese nei mesi di marzo, aprile e maggio rispetto ai prezzi medi di febbraio: non uno sconto diretto alla pompa, ma un ristoro fiscale per alleggerire l impatto del caro diesel sui bilanci delle aziende. Ne abbiamo parlato con Claudio Donati, segretario generale di Assotir. Semiconduttori: da inizio anno rally del 72%. Ma BOFA dice non è BollaLa domanda esplosa dei data center e degli hyperscaler globali ha fatto impennare i prezzi delle DRAM e consolidato il potere contrattuale dei produttori, oggi sostenuti da accordi pluriennali con i grandi operatori tecnologici. E se la domanda cresce, l'offerta si adegua. Nel suo ultimo State of Union sull'industria dei semiconduttori, Bank of America ha rivisto al rialzo in modo significativo le proprie previsioni relative alle dimensioni del mercato globale dei semiconduttori. La banca prevede che il mercato potenziale complessivo dei semiconduttori raggiungerà circa mille e trecento miliardi di dollari entro il 2026 (rispetto alla precedente previsione di mille miliardi di dollari), per arrivare a circa 2mila miliardi di dollari entro il 2030. Il rapporto sottolinea che l'intelligenza artificiale (IA) e i data center (compresi i sistemi di elaborazione, le reti e lo storage) saranno i principali motori di crescita, mentre il settore industriale (rifornimento delle scorte e robotica) fungerà da motore secondario. E a proposito del rischio "bolla" nel suo report BOFA scrive: "L'intelligenza artificiale ha ancora forza strutturale. Il peso dei semiconduttori negli indici di borsa è di circa il 18% nell S&P500 ed è vero che aumenta la sensibilità macroeconomica del mercato. Ma il movimento è guidato dagli utili, il rapporto prezzo/utili da qui ai prossimi 12mesi è di 1:25, sostanzialmente inalterato da inizio anno ed è ancora sotto i precedenti picchi. Ci sono poche evidenze di un'inflazione speculativa dei multipli, elemento che supporta la secolarità del really nel contesto della crescita strutturale A.I."Il commento di Filippo Diodovich Senior analyst di IG Sanchez a Roma. Italia e Spagna a confronto: a cosa si deve il miracolo di MadridLe tensioni geopolitiche in corso, dalla guerra in Ucraina ai dazi imposti dagli Stati Uniti e ora lo shock energetico determinato dall attacco israelo-americano all Iran, stanno avendo come del resto in tutti i paesi europei conseguenze pesanti sull economia italiana. Lo attestano le stime della Commissione europea che collocano la crescita per l Italia allo 0,5% quest anno e allo 0,6% il prossimo, con rischi evidenti di ulteriori revisioni al ribasso. Ma se si scorrono dati e tabelle del Rapporto annuale dell Istat, se ne trae la conclusione che il problema della bassa crescita nel nostro Paese è di lunga durata, come emerge dal confronto con le principali economie europee, e soprattutto con quella spagnola. Da tempo si parla di miracolo spagnolo per le indubbie performance messe a segno da Madrid. È effettivamente tale? L Istat rileva in particolare che tra il 2022 e il 2025 la crescita del Pil ha raggiunto il 9% in Spagna, a fronte del 2,3% in Italia. Un risultato che riflette «una maggiore capacità dell economia spagnola di generare una crescita più sostenuta della domanda interna e dell attività produttiva, anche attraverso incrementi della produttività e un maggiore orientamento verso settori a tecnologia più avanzata, specialmente nei servizi». Vi è senza dubbio dietro queste cifre l effetto della regolarizzazione degli immigrati irregolari. Del resto la principale fonte di immigrati in Spagna è l America latina, dove si parla lo spagnolo. Poi si registra il traino dei servizi e del Pnrr. Nel periodo 2022-2025 in Spagna si è registrata una crescita da consumi ed esportazioni pari rispettivamente a 6,8 e 3,6 punti percentuali, rispetto al 2,2 e 0,2% messo a segno in Italia nello stesso periodo. In sostanza in Spagna si evidenzia un maggiore dinamismo dei consumi delle famiglie che secondo l Istat è riconducibile sia a fattori demografici sia a una crescita sostenuta dei redditi reali. Ma ancora una volta su questa fondamentale componente demografica un effetto predominante lo si deve all aumento della popolazione spagnola tra i 15 e i 64 anni (+4,6% tra il 2022 e il 2025), superiore a quello italiano (+1,6%, grazie alla forte espansione della componente degli stranieri regolari (+22,3% contro il +4,6% in Italia). Chiediamo chiarimenti al collega Dino Pesole che ne ha scritto nei giorni scorsi.E' stato ospite a Focus Economia Dino Pesole, editorialista del Sole 24 Ore Ey-Oxford Economics, in Italia Pil a +0,4% nel 2026, pesano shock energeticiLa guerra in Medio Oriente e i conseguenti shock energetici hanno innescato un forte rallentamento della crescita a livello globale, pur senza configurare al momento una recessione mondiale. È quanto emerge dal rapporto presentato durante l'evento 'Scenari macroeconomici e intelligenza artificiale: implicazioni, sfide e opportunità', organizzato da Oxford Economics in collaborazione con Ey, in cui viene stimata una crescita del Pil italiano dello 0,4% nel 2026 (UN O,1% IN MENO RISPETTO ALLA STIMA DELL'FMI DI OGGI), "in un contesto - si legge in una nota - di elevata incertezza e domanda interna poco dinamica". Secondo l'analisi, nel 2027 si osserverà una lieve accelerazione della crescita del Pil (+0,6%), riconducibile a un andamento dei consumi privati e della domanda estera positivi, a fronte di una leggera contrazione degli investimenti, quest'ultima dovuta alla fine di importanti incentivi fiscali, all'esaurimento del Pnrr e a un contesto di maggiore incertezza. Per l'Eurozona, il rapporto stima una crescita dello 0,7% nel 2026, con un'inflazione media intorno al 3%, quasi il doppio rispetto alle previsioni precedenti, con un picco intorno al 3,5% nel secondo e terzo trimestre.L'analisi di Ey e Oxford Economics si è concentrata su quattro settori produttivi rilevanti per l'economia italiana, ovvero alimentare, tessile, automotive e il comparto dei macchinari, stimando una crescita moderata della produzione tra il 2025 e il 2027. Il settore alimentare dovrebbe registrare una crescita stabile e moderata nel medio periodo (+1,8% nel 2026 e nel 2027), sostenuta prevalentemente dall'export, a fronte di consumi interni deboli e dei rischi legati all'aumento dei costi per l'agricoltura. Il settore del tessile e dell'abbigliamento crescerà in misura contenuta nel biennio 2026- 2027 (rispettivamente +1,2% e +1,3%), trainato quasi esclusivamente dall'export, mentre la domanda interna sarà stagnante e peseranno le pressioni dei competitor internazionali, in particolare asiatici. Per quanto riguarda il comparto dei macchinari, l'analisi sostiene che attraverserà una fase di normalizzazione dopo il ciclo espansivo legato agli incentivi, tornando a una crescita stabile (+1,7% nel 2026 e +1,8% nel 2027), sostenuta dall'export e da una graduale ripresa della domanda interna. Il settore crescerà debolmente (+0,9% nel 2026 e +0,5% nel 2027), con export di segno positivo ma investimenti in contrazione. La transizione verso l'elettrico resta un elemento critico, con il rischio di ridimensionare la produzione domestica. Il settore automotive crescerà debolmente (+0,9% nel 2026 e +0,5% nel 2027), con export di segno positivo ma investimenti in contrazione; la transizione verso l elettrico resta un elemento critico, con il rischio di ridimensionare la produzione domestica.Mario Rocco, Valuation, Modelling and Economics Leader di EY in Italia, ai microfoni di Vincenzo Miglietta.
En el Radar Empresarial de hoy ponemos la atención en SK Hynix, que, igual que Micron, ha logrado entrar en el grupo de compañías valoradas en más de un billón de dólares. La empresa surcoreana se ha beneficiado del impulso de la inteligencia artificial y de las mejores previsiones de firmas financieras. Ese contexto explica el avance en el Kospi, donde protagonizó una de las subidas de 2026. Este año, sus acciones acumulan un crecimiento cercano al 250% aproximadamente. La compañía se ha convertido en una pieza esencial dentro del sector de memorias, considerado de los próximos meses. Una de las razones principales es su estrecha relación con Nvidia, ya que es único proveedor de memorias HBM para la tecnológica estadounidense. Estos componentes permiten gestionar volúmenes de datos con velocidad, algo imprescindible para los desarrollos vinculados a la inteligencia artificial. Con ese liderazgo, SK Hynix controla el 57% del mercado de HBM y el 32% del segmento DRAM. El aumento de la demanda de semiconductores y la escasez de suministros han elevado la importancia estratégica de fabricantes como SK Hynix En apenas dieciséis meses, la empresa pasó de 100.000 millones de dólares a superar el billón de capitalización Sin embargo, la compañía reconoce los riesgos en la industria Su presidente, Chey Tae-won, advirtió hace meses que la falta de obleas de silicio podría provocar un desequilibrio hasta 2030 y generar una diferencia entre oferta y demanda 20%. Las advertencias de SK Hynix coinciden con las de otros directivos del sector tecnológico Michael Dell aseguró que la demanda de memoria inteligencia artificial podría multiplicarse por 625 durante años el director ejecutivo de Micron, Sanjay Mehrotra, explicó en CNBC que la memoria se ha convertido en un recurso imprescindible Según el ejecutivo, los sistemas de inteligencia artificial necesitan más capacidad y un rendimiento superior para desarrollar todo su potencial y sostener el crecimiento esperado del sector tecnológico
"Choosing to be loved, choosing to make that commitment, is not a career-limiting decision." — Dana Perino FOX News Correspondent Nate Foy joins for a "rom-com-dram" conversation on Dana's new novel, Purple State. Dana and Nate dive into the wild New York City dating scene, chasing big dreams, and discussing why keeping a creative outlet alive is a total game-changer. Nate also explains the parts of Dana's book that hit closest to home and the unexpected life lessons he walked away with after turning the final page. Learn more about your ad choices. Visit podcastchoices.com/adchoices
Ander Iturralde da la bienvenida a Rafa Pastrana y José Pérez para analizar todo lo ocurrido en el fin de semana final, la jornada 38, de la Premier League 2025-2026... Comenzando por el definitorio triunfo del Tottenham sobre el Everton para lograr su agónica salvación; a costa de un West Ham que ganó con rotundidad al Leeds pero fue demasiado poco, demasiado tarde en una temporada que ha supuesto su primer descenso en 15 años; mientras que veintidos han sido los años desde el último título de liga del Arsenal y tras ganar al Crystal Palace pudieron llevar a cabo la ceremonia del levantamiento del trofeo; al Manchester City, por su parte, le vimos perder contra el Aston Villa en una tarde de despedir a leyendas del club como jugadores y también su entrenador; algo que también hizo el Liverpool (de momento no del entrenador) en su empate final con el Brentford; algo por lo que tuvo que pasar el Bournemouth, empatar, contra el Nottingham Forest para no darse así ninguno de los tres resultados que necesitaba el equipo de Andoni Iraola para clasificar a la Champions; algo que debió saber casi igual de dulce, clasificarse para la Europa League, para el Sunderland tras una épica victoria final sobre el Chelsea; así como el Brighton cayó ante el Manchester United (de un Bruno Fernandes de récord) y a la Conference League; algo que ni siquieran podían alcanzar ni Fulham ni Newcastle pero fue el equipo de Marco Silva quien ganó; cosa que ni Burnley ni Wolverhampton pudieron hacer en su batalla por no terminar último de la Premier League; competición a la que asciende el Hull City tras ganar al Middlesbrough en la final del play-off y el Bolton, en la división, al Stockport; y mucho más.Apoya que Alineación Indebida pueda prosperar, accede a todo nuestro contenido premium y a nuestro server de Discord suscribiéndote por tan sólo 1.00$/1.00€ en: https://www.patreon.com/posts/159149217Además... Ahora, al suscribirte en nuestra página de Patreon, puedes escuchar todo nuestro contenido de Alineación Indebida Premium a través del siguiente link de Spotify. Sólo tienes que vincular la cuenta que abras en Patreon y, a partir de ahí, tendrás desbloqueado todo el contenido premium que producimos: https://open.spotify.com/show/6WeulpfbWFjVtLlpovTmPv¡Volvemos el Jueves!Sigue a Ander: https://x.com/andershoffmanSigue a Rafa: https://x.com/RafaPastrana7Sigue a José: https://x.com/jcperez_Sigue al programa en Twitter: https://twitter.com/PodcastIndebidoSigue al programa en Instagram: instagram.com/podcastindebidoContacto: anderpodcast@gmail.com // alineacionindebidapodcast@gmail.com Hosted on Acast. See acast.com/privacy for more information.
Welcome to the Tech Latest podcast. Every Tuesday, our tech experts Katey Creel and Shotaro Tani deliver the hottest trends and news from the sector.In this episode, Katey speaks with Taipei tech correspondent Annie Cheng Ting-Fang about about China's top memory chipmaker CXMT, its surprise profit surge ahead of a planned IPO and how the AI boom is accelerating Beijing's push for semiconductor self-sufficiency. == == == == == == == ==Check out this episode's featured story below: China chipmaker CXMT logs 1,688% profit surge amid global memory crunch== == == == == == == ==And register for our weekly #techAsia newsletter here.Find more of our tech coverage here.And for the Asian business, politics, economy and tech stories others miss, please subscribe to Nikkei Asia here.Thanks for listening!
Micron President and CEO Sanjay Mehrotra discusses the company's significant expansion of DRAM manufacturing in the US. Speaking with Bloomberg's Tyler Kendall, Mehrotra highlights the importance of this advanced memory technology for critical sectors such as automotive, aerospace, defense, industrial and networking.See omnystudio.com/listener for privacy information.
Send us Fan MailFeaturing Pam, Cassidy and FionaThis Episode is sponsored by Sherbrooke Liquor, one of the World's Best Top Bottle Shops.Support the showThank you for listening and remember to drink respectfully!We want to hear from you! Send us an email at dramfineyeg@gmail.com
When it comes to heavy asset, low obsolescence stocks, Dave Mazza of Roundhill Investments talks about how his firm's HALO ETF (LOHA) capitalizes on the trend. As for the memory trade, he talks about Roundhill's Memory ETF (DRAM) and the surge it has seen since inception earlier this year. When it comes to heavy asset, low obsolescence stocks, Dave Mazza of Roundhill Investments talks about how his firm's HALO ETF (LOHA) capitalizes on the trend. As for the memory trade, he talks about Roundhill's Memory ETF (DRAM) and the surge it has seen since inception earlier this year.
Aktuální dění očima Jana Krause každé ráno 5:00 – 9:00 vždy po zprávách v celou a v půl exkluzivně na Frekvenci 1. Vtipně, originálně a s nadhledem, tak to umí jenom Jan Kraus. Blondýna Miluška Bittnerová se ptá na vše, o čem se mluví, a Jan Kraus jí to vysvětlíSee omnystudio.com/listener for privacy information.
A jovem fadista Teresinha Landeiro é a convidada desta semana do Posto Emissor. Com o quarto álbum a chegar na próxima semana, a inspiração do novo disco, que passou pela obra do pintor Alfredo Luz, o começo da carreira, aos 12 anos, com as ‘madrinhas’ Ana Moura e Raquel Tavares, o curso de Gestão e as lições de Celeste Rodrigues foram temas de conversa. Falámos ainda do Festival da Eurovisão e da estreia na música da atriz Helena Caldeira.See omnystudio.com/listener for privacy information.
Risks are rising in this market, but earnings are still solid. There are things to watch and buying the dip is still a real possibility. Here's how to create a watch list from ETF's. FORMULA - Alpha Picks + Seeking Alpha Premium + Trendspider and Sidekick - PERFECT TOGETHER! THESE SALES END SOON: TRENDSPIDER - get my 4 hour algorithm on any annual plan.Seeking Alpha's Tool kit (throw this in for the complete package)*BEST DEAL - SEEKING ALPHA BUNDLE - Save over $150 and get Premium and Alpha Picks together ALPHA PICKS - Want to Beat the S&P? Save $50 Seeking Alpha Premium - FREE 7 DAY TRIAL SEEKING ALPHA PRO - TRY IT FOR A MONTH FOR ONLY $89 EPISODE SUMMARY
News and Updates: AI Compute Tax Debate: Economists and policymakers are debating taxing AI processing power to offset job displacement and fund social services, though critics argue it's too blunt a tool. AI Dividend Proposal: NY congressional candidate Alex Bores unveiled an "AI Dividend" plan funding direct payments to Americans through a token tax on AI consumption and equity stakes in frontier AI firms. Screenless Fitness Trackers Surge: Screenless wearables like Oura Ring and Whoop are booming, with U.S. fitness tracker purchases up 88% and smart ring sales up 195% between 2024 and 2025. Canvas Hacker Payout: Instructure, maker of the Canvas education platform, reached an undisclosed "agreement" with the ShinyHunters hacking gang after a breach exposed data from 275 million users across 9,000 institutions. FCC Router Ban vs. Supply Chain: AT&T warned the FCC that a global DRAM and NAND flash shortage, driven by AI deployments, is complicating compliance with its ban on foreign-made Wi-Fi routers. Google Unveils Googlebook: Google announced a new laptop line called Googlebooks running a fused Android/ChromeOS platform, featuring Gemini AI integration and a "Magic Pointer," with hardware partners including Acer, Dell, HP, and Lenovo.
Hoy hablamos del acelerón de China en memoria DRAM con CXMT, de GovWell y su apuesta por meter IA en la burocracia municipal, del truco de Apple para convertir chips imperfectos en negocio con el MacBook Neo, del chantaje a Grafana tras un acceso no autorizado a GitHub, y del James Webb enseñando una estructura rarísima en el corazón de Messier 77.Puedes seguirnos en YouTube en https://youtube.com/olivernabani y puedes unirte al Discord Mashain en https://olivernabani.com/discord
VettaFi's Head of Research Todd Rosenbluth discussed the Roundhill Memory ETF (DRAM) on this week's “ETF of the Week” podcast with Chuck Jaffe of “Money Life.”
Micron's stock and Roundhill's DRAM ETF have become the poster-children for the AI memory rally. But here's what could be the next “phase” of the AI buildout. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Eric Diton says chips remain king in the current market environment. However, he notes an inflation concern in the memory space as DRAM prices show no signs of decreasing. "I would not be diving in here," says Eric, expecting profit-taking to hit stocks that skyrocketed in recent weeks. He urges investors to find "unloved" names in the stock market. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about
Hello & Welcome to the Podcast!In today's episode, I'm joined by Orla O'Doherty @thecliniccoach for a chat about using coaching skills for behaviour change, especially around physical activity in postpartum womenOrla shared her journey, including insights from her masters training in behaviour change and health coaching, explaining key frameworks such as COM-B (Capability, Opportunity, Motivation, Behaviour) and emphasising the importance of helping the people we work with identify their own goals, rather than prescriptively telling them what to do.We discussed practical strategies including goal setting, habit formation, motivation maintenance and the challenge of implementing these in clinical practice.We highlight how coaching skills can liberate the clinician's role from being a fixer to supporting the person's self-efficacy, noting that this approach not only helps the people we are working with, but also reduces frustration for healthcare providers, while making clinical work more effective and sustainable.Some of the topics we covered:Behaviour change in health coachingHealth coaching on Postpartum careEffective goal setting discussionsBehavioural goals in patient careMotivation vs WillpowerPatient resistance in physio strategies Trust, compassion and how to deal with challengesand much more!Orla is doing great work on changing how we can help move from the old model of healthcare professionals acting as mechanics to fix people, but rather empowering them with self efficacy toolboxes - she offers coursework on all of this so make sure you're following her on instagramWant to learn more about a bio psychosocial approach to Perinatal Pelvic Rehab? I designed my new online course to cover all of this and more, from preconception ,through pregnancy and into postpartum and beyond. Full of up to date evidence and 'how to' strategies, from PGP to DRAM and R2R!all of the info on this and all of my other online courses can be found at CelebrateMuliebrity.comUntil next time, Onwards & Upwards, Mx#celebratemuliebrity
On this week's episode of The MacRumors Show, we talk through how the global memory shortage is forcing Apple's hand across multiple key products, killing configurations, delaying launches, and prompting spec decisions that would have seemed unlikely a year ago.The pressure originates outside Apple's control. JPMorgan analysis cited by the Financial Timesfound that memory could account for as much as 45% of an iPhone's component costs by 2027, up from around 10% today. Companies like Nvidia are reportedly outbidding consumer electronics makers for limited DRAM supply from Samsung, SK Hynix, and Micron, while cloud firms are locking in capacity with multi-billion-dollar upfront commitments. Apple, which buys memory for roughly 250 million iPhones per year, has shifted from a position where it could dictate terms to one where it must compete for supply, and component prices are being driven up as a result.The consequences are already visible in the Mac lineup. Apple last week removed the Mac mini's 256GB storage option, pushing its starting price from $599 to $799. Days later, it eliminated Mac mini models with 32GB and 64GB of RAMand stripped the M3 Ultra Mac Studio to a single 96GB configuration, with delivery estimates for remaining Studio models at 9 to 10 weeks. The Mac Studio had already lost its 512GB memory option in March, and multiple configurations became entirely unavailable in April. On Apple's April 30 earnings call, CEO Tim Cook acknowledged that both machines would be "hard to get for months to come" and said Apple expects "significantly higher memory costs" in the current quarter. The MacBook Neo was sold out through April and Cook described demand on the earnings call as “off the charts." The MacBook Neo uses binned A18 Pro chips, adopting manufacturing rejects from the iPhone 16 lineup with one GPU core disabled, repurposed rather than discarded to keep costs low enough to hit the $599 price point.Apple's initial production target is believed to be about five to six million units, but demand has since pushed the company to instruct suppliers to prepare for at least 10 million. TSMC's N3E production lines, where the A18 Pro was made, are now running at maximum capacity, with AI-related orders consuming much of the available output. A fresh manufacturing run for the A18 Pro would yield fully functional chips rather than defective ones, raising the per-unit cost before any expedited manufacturing premium is applied.Apple is now said to be weighing up its options for the MacBook Neo. The company is purportedly considering cutting the 256GB entry-level model, which would push the effective starting price up by $100 without changing any existing configuration's price, the same mechanism used with the Mac mini. Separately, Apple may be considering new color options to soften any price increase.Upcoming products are apparently being reshaped too. Weibo leaker "Fixed Focus Digital" has claimed in a series of posts that the standard iPhone 18 is being downgraded as a cost-cutting measure, with both display and chip specifications affected. Most recently, the leaker said certain parts are interchangeable between the iPhone 18 and the lower-cost iPhone 18e. For context, iPhone 17 and iPhone 17e differ meaningfully: the standard model has a larger ProMotion display, Dynamic Island, Ultra Wide camera, five-core GPU, and significantly better battery life, but it looks like there could be fewer differences with the next generation.A follow-up post framed the new split launch strategy, under which the iPhone 18 ships in spring 2027 rather than alongside the Pro models in the fall, as a deliberate commercial mechanism to smooth out demand. By extending the iPhone 17's flagship run, Apple is also said to be creating conditions under which a lower-specced successor will be more palatable. The split launch itself has been widely reported since last year, with Ming-Chi Kuo and Nikkei among those to have corroborated it.The launch of the rumored all-new high-end MacBook Pro or "MacBook Ultra" with an OLED display and touchscreen has also apparently slipped. Bloomberg's Mark Gurman has said early 2027 is now looking more likely than late 2026 due to Apple's constrained memory supply cited as a factor.
Our Head of Europe and Asia Technology Research Shawn Kim discusses AI's move from passive chatbots to active agents—and how this influences tech supply chains.Read more insights from Morgan Stanley.----- Transcript -----Welcome to Thoughts on the Market. I'm Shawn Kim, Head of Morgan Stanley's Europe and Asia Technology Team. Today: A foundational shift in the development of AI and its broad market implications. It's Tuesday, May 5th, at 3pm in London. Think about the last time you asked a chatbot to write a summary or a draft. Or maybe answer a query. It was probably useful. But you were also still driving the interaction: asking, refining, copying, checking, and moving the work forward. Now imagine a system that does not just respond, but acts. It remembers what you asked last week, understands your preferences, works across digital tools, plans a workflow, and adapts as circumstances change. That is the shift from GenAI to agentic AI: from AI that helps with thinking to AI that helps with doing. GenAI is mostly passive. It takes a prompt and produces an answer. Agentic AI is active – less a copilot for one task but an autopilot for multi-step workflows. The distinction is key because computing requirements are changing. In GenAI, large language models and GPUs handle much of the thinking. GPUs, or graphics processing units, process many calculations in parallel, making them central to modern AI models. In agentic AI, CPU becomes more important. CPUs, or central processing units, coordinate tasks and connect systems to the broader digital infrastructure. Agentic AI also depends on three stacks: the brain, or the large language model; orchestration, where the CPU manages the doing; and knowledge, which is memory.Memory may be the most important layer. An agent that knows your preferences, documents, tone, and task history becomes more useful over time. That creates a context flywheel. The more context it collects, the more personalized it becomes, and the harder it is to leave. Typically, in computing, we think of memory as storage, mainly. We need to rethink this. Memory is also continuity. When an AI system can use past experiences, memory becomes a long-term state, shared knowledge, and behavioral grounding. And that matters because LLMs have fixed context windows. Once a conversation exceeds that window, older content falls off. For simple questions, that may be fine. But for a coding agent working across a large codebase over days or weeks, it is a major limitation. Serious work requires persistent memory, short-term orientation, and active retrieval – remembering prior decisions, understanding changed files, and finding relevant codes without the user pointing to every dependency. For investors, the implication is clear – agentic AI changes the bottlenecks. We see CPUs as the new bottleneck, with memory seeing the highest content increase. We estimate as much as 60 percent, or $60 billion of incremental CPU total addressable market by 2030, within a total CPU market of more than $100 billion. We also estimate up to 70 percent of incremental DRAM bit shipment tied to this theme. That makes us more positive on supply chains including memory, foundry, substrates, CPU and memory interface, and capacitors and CPU sockets. These areas benefit from content growth, pricing power, and capacity constraints into 2027. As AI moves from answering questions to taking actions, investors should watch the infrastructure behind the shift. Because in the agentic era, the next big AI leap may be less about the prompt, but more about the processor. Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.
This week on The Whiskey Trip, Big Chief rides into Houston, Texas to link up with the crew from The Noble Dram—a show that's built its reputation on exploring whiskey from around the world and delivering tasting notes that help you decide what's worth the chase. Aaron and Gavin bring that global perspective, and this episode turns into a true collaboration—stories, insight, and pours that stretch from Georgia to Texas and beyond. On the first half, Big Chief pours something special—Effie Jewel from Doc Brown Farm & Distillers. This limited run, four-year-old Georgia bourbon is crafted with heirloom Jimmy Red corn, then sent to the Texas Coast where six months of humidity and salt air shape it into a bold, one-of-a-kind pour. Then on the second half, he shifts gears and opens up an 8-year-old cask strength Jimmy's from Kiepersol Distillery—and this one flat out delivers. It's loaded with a stunning rye spice that hits with authority, layered with that unmistakable horehound candy note that lingers and pulls you right back in for another sip. But this ride isn't just about what's in the glass. The conversation drifts into hometown sports—loyalty, pride, and the teams that raised us—and rolls right into BBQ philosophy, where opinions run strong and tradition matters just as much as technique. This episode is about more than whiskey—it's about culture, community, and the stories that come with every pour. Take the Ride with Big Chief. Cheers.
Drew has been a friend for half a decade, and as well as being a lauded bar owner, we created Moonbird Gin (double gold at the San Francisco World Spirits Awards) and GOATz Spiced Rum together - and he's a hilarious, fascinating guy. Drew on IG: https://www.instagram.com/drewbarman/ (Get in touch with Duff!Podcast business enquiries: consulting@liquidsolutions.org (PR friends: we're only interested in having your client on if they can talk for a couple of hours about OTHER things besides their prepared speaking points or their new thing, whatever that is. They need to be able to hang. Oh, plus we don't edit, we won't supply prepared or sample questions, nor listener or “reach” stats, either, and no, you can't sit in on the interview (or lurk on the Zoom.) And our AI automatically deletes pitch emails that are clearly written using AI. Retain Philip's consulting firm, Liquid Solutions, specialised in on-trade engagement & education, liquor brand creation and repositioning: philip@liquidsolutions.orgPhilip on Instagram: https://www.instagram.com/philipsduff/ Philip on Facebook: Philip Duff Philip on X/Twitter: Philip Duff (@philipduff) / Twitter Philip on LinkedIn: linkedin.com Old Duff Genever on Instagram: Old Duff Genever (@oldduffgenever) • Instagram photos and videos Old Duff Genever on Faceboo...
Brought to you by TogetherLetters & Edgewise!In this episode: AI FrontierAnthropic's New Mythos A.I. Model Sets Off Global AlarmsMozilla Used Anthropic's Mythos to Find and Fix 271 Bugs in FirefoxSam Altman compares Mythos to dropping a bomb while selling a $100B bomb shelterAnthropic could raise a new $50B round at a valuation of $900BOpenAI releases GPT-5.57-0 wipeout: ChatGPT-5.5 vs Claude 4.7 in 7 impossible testsChina orders Meta to unwind $2B Manus acquisitionHe Built a $1.8 Billion Company Alone with AITech Layoffs & Big MovesJohn Ternus named Apple CEO to replace Tim CookNearly 40,000 tech jobs lost in April 202620,000 job cuts at Meta, Microsoft raise AI labor crisis concernNetflix plans vertical video feed and AI recommendationsPrivacy, Security & Age ChecksUS Bill Mandates On-Device Age VerificationBrussels age-checking app hacked in 2 minutes$5 Bluetooth tracker in a postcard exposes Dutch warshipHardware, Science & EngineeringNIST creates 'any wavelength' lasers in tiny circuitsNASA shuts off instrument on Voyager 1Anker made its own AI chip (Thus)YouTuber builds working DRAM in backyardLinux begins dropping Intel 486 supportPancreatic cancer mRNA vaccine shows lasting resultsBMW one step closer to a color-changing carAlberta startup sells "no-tech" tractors for half priceRobots Take the FieldChinese android beats human half-marathon recordJapan Airlines pilots humanoid robots at HanedaTable tennis robot defeats top human playersWeird & WackyChinese carmaker patents voice-controlled in-vehicle toiletAir New Zealand adds economy bunk beds (with rules)Hairdryer allegedly used to trick weather sensor for $34K Polymarket betDOJ arrests soldier who made $400K betting on Maduro's removalI bought Friendster for $30K — here's what I'm doing with itNZ DOC: remote tech begins a "new era" for conservationTech Rec:Sanjay - Citymapper Adam - Claude DesignFind us here:sanjayparekh.com & adamjwalker.comTech Talk Y'all is a proud production of Edgewise.Media.
Join The Full Nerd gang as they talk about the latest PC building news. In this episode the gang covers PCWorld's review of the Ryzen 9 9950X3D2, Mike's investigation into flash storage pricing, what we think of the recent DRAM stock/pricing trends, and much more. And of course we answer questions live! Join the PC related discussions and ask us questions on Discord: https://discord.gg/UWhjwg778a Follow the crew on X and Bluesky: @AdamPMurray @BradChacos @MorphingBall @WillSmith ============= Read PCWorld! Website: http://www.pcworld.com Newsletter: http://www.pcworld.com/newsletters/signup ============= Learn more about your ad choices. Visit megaphone.fm/adchoices
In this lively episode of the Rolex Whiskey Passion Project, host Gavin Linde and guest Matt Lurin dive deep into the evolving landscape of the spirits industry.They explore the rising popularity of independent bottling and the "out of control" trend of high-ABV cask strength whiskies, contrasting modern preferences with the classic, lower-proof vintages of the past.They also take a candid look at shifting cultural norms—from the "shame" of being a lone cigar smoker at a family pool party to the challenge of engaging a younger, more distracted generation with traditional liquor culture.They also highlight the upcoming Water of Life NYC charity event in June, featuring a unique "whiskey speed dating" format where every pour supports a good cause.
Dave Mazza with Roundhill Investments calls memory the "true bottleneck" of AI. As demand outpaces supply, he explains how previous "boom and bust" cycles in tech differ from the rally stocks like Micron (MU), SanDisk (SNDK), and Western Digital (WDC) are experiencing. Dave sees "incredible" revenue growth backing these earnings throughout the coming weeks. He then talks about how his firm offers exposure to these companies and others through the Roundhill Memory ETF (DRAM). ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about
Tightening budget constraints and rising data trust requirements are increasing operational pressure on managed service providers by shifting risk and accountability downward through the service chain. Developments in both the European and US markets, together with supply chain volatility and heightened scrutiny of where and how data is handled, are forcing MSPs to redefine both service delivery and governance models. According to Speaker A, MSPs focusing on auditability, clear data residency, and sovereignty will remain viable, while those relying on traditional narratives or ambiguous transformation pitches risk being sidelined. The episode points to evidence from several reports: Politico notes that 8 out of 10 Europeans do not trust US or Chinese firms with their data, highlighting explicit concerns over data location and custodianship. Concurrently, the U.S. Chamber of Commerce Small Business Index, cited by Axios, shows declining confidence among American small businesses, with only 37% expecting new investments and 53% listing inflation as their top challenge. Further, Channel Insider flags “memflation,” with DRAM and NAND prices expected to rise 125% and 243% respectively by 2026, intensifying margin pressure and pricing risk for operators. Additional risk drivers come from both operational and technical layers. Speaker A references the Blackpoint Cyber 2026 threat report, which attributes most breaches to the abuse of trusted credentials and tools—such as RMM solutions and SSL VPNs—rather than new vulnerabilities. Governance gaps are also worsened by declining white-collar hiring, as cited by Gallup and Axios, reducing internal capacity for vendor reviews, incident follow-up, and process controls. Increased automation and outsourcing in response to these gaps tend to create more dependency chains and larger blast radii, making explicit governance even more important. For MSPs, these findings point to operational needs that go beyond technical capability. Contract terms must address volatile input costs directly, with shorter quote validity and explicit repricing clauses. Governance processes should include audit-ready data maps, clear documentation of subprocessors, and proactive credential management. Without these measures, MSPs risk being treated as interchangeable commodities and exposed to margin compression and heightened liability from external compliance and trust requirements. 00:00 SMB Caution 03:48 Coordination Crunch 06:24 RMM Exposed 09:36 Why Do We Care? Supported by: Zero Networks HaloPSA
We review top Data Center Memory-Chip Stocks, their amazing YTD performance, and a brand-new Exchange Traded Fund (ETF) in that space, DRAM. We also introduce you to Optoelectronics and some top investment picks there from Barron's Magazine. We finish up with up-and-coming Nextgen Dividend Aristocrat Plays for Investment Income.
This show has been flagged as Clean by the host. In this show, Marc Abel presents an introduction to Dauug|18, an 18-bit controller developed by The Dauug House. About the size of a postcard, Dauug|18 avoids the use of complex VLSI such as microprocessors, FPGAs, PLDs, ASICs, and DRAM. Instead, the architecture is built from trivial glue logic and synchronous static RAM, using components that can be hand-soldered and verified for connectivity after assembly. The motivation for Dauug|18 is to provide refuge in situations where transparency, auditability, and supply chain integrity are priorities. Rather than relying on high-integration silicon, Dauug|18 is auditable at the logic-gate level, allowing owners to verify the integrity of their hardware. This show covers key architectural details, the decision to use SRAM for both memory and logic, and system constraints that stem from Dauug|18's brutal simplicity, limited component selection, and succinctness. The practical effect of these constraints on programming Dauug|18 is also discussed in detail. Anticipated uses for Dauug|18 include privacy assertion, critical infrastructure, and curricula for fields relating to computer engineering. Files supplied with this show include a short PDF of Dauug|18 architectural details, as well as word-accurate, spell-checked subtitles and their matching transcript. More information, technical documentation, and updates on related projects like Dauug|36 can be found at https://dauug.org. Provide feedback on this episode.
This is a recap of the top 10 posts on Hacker News on April 01, 2026. This podcast was generated by wondercraft.ai (00:30): Claude Code Unpacked : A visual guideOriginal post: https://news.ycombinator.com/item?id=47597085&utm_source=wondercraft_ai(01:56): Live: Artemis II Launch Day UpdatesOriginal post: https://news.ycombinator.com/item?id=47603657&utm_source=wondercraft_ai(03:23): EmDash – A spiritual successor to WordPress that solves plugin securityOriginal post: https://news.ycombinator.com/item?id=47602832&utm_source=wondercraft_ai(04:50): DRAM pricing is killing the hobbyist SBC marketOriginal post: https://news.ycombinator.com/item?id=47606840&utm_source=wondercraft_ai(06:17): I quit. The clankers wonOriginal post: https://news.ycombinator.com/item?id=47598511&utm_source=wondercraft_ai(07:43): CERN levels up with new superconducting kartsOriginal post: https://news.ycombinator.com/item?id=47597935&utm_source=wondercraft_ai(09:10): SpaceX files to go publicOriginal post: https://news.ycombinator.com/item?id=47604155&utm_source=wondercraft_ai(10:37): Claude wrote a full FreeBSD remote kernel RCE with root shellOriginal post: https://news.ycombinator.com/item?id=47597119&utm_source=wondercraft_ai(12:04): U.S. exempts oil industry from protecting Gulf animals, for 'national security'Original post: https://news.ycombinator.com/item?id=47595620&utm_source=wondercraft_ai(13:31): Is BGP safe yet?Original post: https://news.ycombinator.com/item?id=47600382&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai
I'm quitting the podcast and closing on my mansion after my lambo got delivered yesterday thanks to sports betting and zero DTE options. But seriously - KNOW WHAT TYPE OF INVESTOR YOU ARE! That's the message after yesterdays historic market move. Get my FREE newsletter or sign up for the paid version with benefits like the Office Hours and tracking the portfolios in Savvy Trader https://dailystockpick.substack.com/THESE SALES END SOON: TRENDSPIDER - get any annual plan and I'll send you my 4 hour algorithm plus SIDEKICK - the AI that gives me help in understanding my choices Seeking Alpha's Tool kit *BEST DEAL - SEEKING ALPHA BUNDLE - Save over $150 and get Premium and Alpha Picks together ALPHA PICKS - Want to Beat the S&P? Save $50 Seeking Alpha Premium - FREE 7 DAY TRIAL SEEKING ALPHA PRO - TRY IT FOR A MONTH FOR ONLY $89 EPISODE SUMMARY
A Midwinter Night's Dram is a whiskey that has been historically sought after. Once a combination of well aged rye from from Barton and MGP, this whiskey is now a combination of High West's own distillate and MGP. How does it taste? You'll have to listen to find out. In this episode, we wax poetically about MWND in the past and we have high hopes for the future. During the tasting, we got a bit sidetracked by the return of our co-host Steven and by large shipping lables. After all is said and done, we give you our honest and candid assessment of this bottle from last year.--------------------------SocialsIG: https://www.instagram.com/themashupkyFB: https://www.facebook.com/themashupkyYouTube: https://www.youtube.com/@themashupkyJoin our community on Patreon: https://www.patreon.com/TheMashUpBourbonPodcastPartnership(s)Visit Bourbonoutfitter.com and enter code THEMASHUP for a special discount or visit bourbonoutfitter.com/THEMASHUPMusic: All the Fixings by Zachariah HickmanThank you so much for listening!
Rosana Laviada analiza con Maite Rico, Luis Herrero y Quirós el caso de la joven a la que han dado el visto bueno a la eutanasia.
Rosana Laviada analiza con Maite Rico, Luis Herrero y Quirós el caso de la joven a la que han dado el visto bueno a la eutanasia.
Micron CEO Sanjay Mehrotra predicts Level 4 autonomous vehicles and next-gen robots will require more than 300 GB of DRAM, a major leap from the current 16 GB in today’s cars, signaling a boom in automotive memory demand that could strain chip supply. A California jury awarded Donna Motsinger $19.25 million after finding Bill Cosby liable for drugging and sexually assaulting her in a 1972 incident in Northern California. The verdict included $17.5 million in past damages and $1.75 million for future harm, with the option for additional punitive damages still to be determined. Please Like, Comment and Follow 'Philip Teresi on KMJ' on all platforms: --- Philip Teresi on KMJ is available on the KMJNOW app, Apple Podcasts, Spotify, YouTube or wherever else you listen to podcasts. -- Philip Teresi on KMJ Weekdays 2-6 PM Pacific on News/Talk 580 AM & 105.9 FM KMJ | Website | Facebook | Instagram | X | Podcast | Amazon | - Everything KMJ KMJNOW App | Podcasts | Facebook | X | Instagram See omnystudio.com/listener for privacy information.
1. TRS sigue marcando el terreno sobre la vista de mañana. Gobernadora confirma Domenech comparecerá y lanza ataque a TRS.2. TRS les abre fuego a las agencias anticorrupción y apunta la mira en la Oficina de Ética o 1er post 3. Nueva crisis del gobierno de Jenniffer González: alegaciones de hostigamiento laborar y sexual contra el secretario de Corrección 4. Dramático el estancamiento de la estadidad en Washington y la inacción del gobierno del PNP 5. En riesgo de que el aumento en la luz para los próximos 3 meses sea más del 4% que solicitó LUMA 6. Caos en los aeropuertos. Llegan los agentes de ICE 7. Trump se echa para atrás y dice NO atacará instalaciones energéticas de Irán. Alega negociaciones que Irán niega 8. Deportes con José Aníbal HerreroSee omnystudio.com/listener for privacy information.
It is Single Malt History's 100th episode! To celebrate, I'm taking a look back at its most downloaded episode and its (shaky!) first. There are clips from West End actors, stars of the silver screen, the first historian to stop by for a chat, and the two episodes that are still brought up to me the most often by listeners.
Joel Harrison, a veteran whiskey writer, joined the "Rolex Whiskey Passion Project" to discuss the dramatic changes in the whiskey industry over his nearly 20-year career. They centered on the evolution of whiskey pricing, with Harrison and host Gavin Linde recalling a time two decades ago when quality, mature whiskies, including rare bottles from now-closed distilleries like Port Ellen, were abundant and significantly cheaper. Harrison shares his "aha" moment with Balvenie Doublewood and his eventual transition from the music industry to full-time whiskey writing, highlighting the global, passionate nature of the whiskey community.
Turbopuffer came out of a reading app.In 2022, Simon was helping his friends at Readwise scale their infra for a highly requested feature: article recommendations and semantic search. Readwise was paying ~$5k/month for their relational database and vector search would cost ~$20k/month making the feature too expensive to ship. In 2023 after mulling over the problem from Readwise, Simon decided he wanted to “build a search engine” which became Turbopuffer.We discuss:• Simon's path: Denmark → Shopify infra for nearly a decade → “angel engineering” across startups like Readwise, Replicate, and Causal → turbopuffer almost accidentally becoming a company • The Readwise origin story: building an early recommendation engine right after the ChatGPT moment, seeing it work, then realizing it would cost ~$30k/month for a company spending ~$5k/month total on infra and getting obsessed with fixing that cost structure • Why turbopuffer is “a search engine for unstructured data”: Simon's belief that models can learn to reason, but can't compress the world's knowledge into a few terabytes of weights, so they need to connect to systems that hold truth in full fidelity • The three ingredients for building a great database company: a new workload, a new storage architecture, and the ability to eventually support every query plan customers will want on their data • The architecture bet behind turbopuffer: going all in on object storage and NVMe, avoiding a traditional consensus layer, and building around the cloud primitives that only became possible in the last few years • Why Simon hated operating Elasticsearch at Shopify: years of painful on-call experience shaped his obsession with simplicity, performance, and eliminating state spread across multiple systems • The Cursor story: launching turbopuffer as a scrappy side project, getting an email from Cursor the next day, flying out after a 4am call, and helping cut Cursor's costs by 95% while fixing their per-user economics • The Notion story: buying dark fiber, tuning TCP windows, and eating cross-cloud costs because Simon refused to compromise on architecture just to close a deal faster • Why AI changes the build-vs-buy equation: it's less about whether a company can build search infra internally, and more about whether they have time especially if an external team can feel like an extension of their own • Why RAG isn't dead: coding companies still rely heavily on search, and Simon sees hybrid retrieval semantic, text, regex, SQL-style patterns becoming more important, not less • How agentic workloads are changing search: the old pattern was one retrieval call up front; the new pattern is one agent firing many parallel queries at once, turning search into a highly concurrent tool call • Why turbopuffer is reducing query pricing: agentic systems are dramatically increasing query volume, and Simon expects retrieval infra to adapt to huge bursts of concurrent search rather than a small number of carefully chosen calls • The philosophy of “playing with open cards”: Simon's habit of being radically honest with investors, including telling Lachy Groom he'd return the money if turbopuffer didn't hit PMF by year-end • The “P99 engineer”: Simon's framework for building a talent-dense company, rejecting by default unless someone on the team feels strongly enough to fight for the candidate —Simon Hørup Eskildsen• LinkedIn: https://www.linkedin.com/in/sirupsen• X: https://x.com/Sirupsen• https://sirupsen.com/aboutturbopuffer• https://turbopuffer.com/Full Video PodTimestamps00:00:00 The PMF promise to Lachy Groom00:00:25 Intro and Simon's background00:02:19 What turbopuffer actually is00:06:26 Shopify, Elasticsearch, and the pain behind the company00:10:07 The Readwise experiment that sparked turbopuffer00:12:00 The insight Simon couldn't stop thinking about00:17:00 S3 consistency, NVMe, and the architecture bet00:20:12 The Notion story: latency, dark fiber, and conviction00:25:03 Build vs. buy in the age of AI00:26:00 The Cursor story: early launch to breakout customer00:29:00 Why code search still matters00:32:00 Search in the age of agents00:34:22 Pricing turbopuffer in the AI era00:38:17 Why Simon chose Lachy Groom00:41:28 Becoming a founder on purpose00:44:00 The “P99 engineer” philosophy00:49:30 Bending software to your will00:51:13 The future of turbopuffer00:57:05 Simon's tea obsession00:59:03 Tea kits, X Live, and P99 LiveTranscriptSimon Hørup Eskildsen: I don't think I've said this publicly before, but I just called Lockey and was like, local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you. But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working.So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people. We're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards. Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before.Alessio: Hey everyone, welcome to the Leading Space podcast. This is Celesio Pando, Colonel Laz, and I'm joined by Swix, editor of Leading Space.swyx: Hello. Hello, uh, we're still, uh, recording in the Ker studio for the first time. Very excited. And today we are joined by Simon Eski. Of Turbo Farer welcome.Simon Hørup Eskildsen: Thank you so much for having me.swyx: Turbo Farer has like really gone on a huge tear, and I, I do have to mention that like you're one of, you're not my newest member of the Danish AHU Mafia, where like there's a lot of legendary programmers that have come out of it, like, uh, beyond Trotro, Rasmus, lado Berg and the V eight team and, and Google Maps team.Uh, you're mostly a Canadian now, but isn't that interesting? There's so many, so much like strong Danish presence.Simon Hørup Eskildsen: Yeah, I was writing a post, um, not that long ago about sort of the influences. So I grew up in Denmark, right? I left, I left when, when I was 18 to go to Canada to, to work at Shopify. Um, and so I, like, I've, I would still say that I feel more Danish than, than Canadian.This is also the weird accent. I can't say th because it, this is like, I don't, you know, my wife is also Canadian, um, and I think. I think like one of the things in, in Denmark is just like, there's just such a ruthless pragmatism and there's also a big focus on just aesthetics. Like, they're like very, people really care about like where, what things look like.Um, and like Canada has a lot of attributes, US has, has a lot of attributes, but I think there's been lots of the great things to carry. I don't know what's in the water in Ahu though. Um, and I don't know that I could be considered part of the Mafi mafia quite yet, uh, compared to the phenomenal individuals we just mentioned.Barra OV is also, uh, Danish Canadian. Okay. Yeah. I don't know where he lives now, but, and he's the PHP.swyx: Yeah. And obviously Toby German, but moved to Canada as well. Yes. Like this is like import that, uh, that, that is an interesting, um, talent move.Alessio: I think. I would love to get from you. Definition of Turbo puffer, because I think you could be a Vector db, which is maybe a bad word now in some circles, you could be a search engine.It's like, let, let's just start there and then we'll maybe run through the history of how you got to this point.Simon Hørup Eskildsen: For sure. Yeah. So Turbo Puffer is at this point in time, a search engine, right? We do full text search and we do vector search, and that's really what we're specialized in. If you're trying to do much more than that, like then this might not be the right place yet, but Turbo Buffer is all about search.The other way that I think about it is that we can take all of the world's knowledge, all of the exabytes and exabytes of data that there is, and we can use those tokens to train a model, but we can't compress all of that into a few terabytes of weights, right? Compress into a few terabytes of weights, how to reason with the world, how to make sense of the knowledge.But we have to somehow connect it to something externally that actually holds that like in full fidelity and truth. Um, and that's the thing that we intend to become. Right? That's like a very holier than now kind of phrasing, right? But being the search engine for unstructured, unstructured data is the focus of turbo puffer at this point in time.Alessio: And let's break down. So people might say, well, didn't Elasticsearch already do this? And then some other people might say, is this search on my data, is this like closer to rag than to like a xr, like a public search thing? Like how, how do you segment like the different types of search?Simon Hørup Eskildsen: The way that I generally think about this is like, there's a lot of database companies and I think if you wanna build a really big database company, sort of, you need a couple of ingredients to be in the air.We don't, which only happens roughly every 15 years. You need a new workload. You basically need the ambition that every single company on earth is gonna have data in your database. Multiple times you look at a company like Oracle, right? You will, like, I don't think you can find a company on earth with a digital presence that it not, doesn't somehow have some data in an Oracle database.Right? And I think at this point, that's also true for Snowflake and Databricks, right? 15 years later it's, or even more than that, there's not a company on earth that doesn't, in. Or directly is consuming Snowflake or, or Databricks or any of the big analytics databases. Um, and I think we're in that kind of moment now, right?I don't think you're gonna find a company over the next few years that doesn't directly or indirectly, um, have all their data available for, for search and connect it to ai. So you need that new workload, like you need something to be happening where there's a new workload that causes that to happen, and that new workload is connecting very large amounts of data to ai.The second thing you need. The second condition to build a big database company is that you need some new underlying change in the storage architecture that is not possible from the databases that have come before you. If you look at Snowflake and Databricks, right, commoditized, like massive fleet of HDDs, like that was not possible in it.It just wasn't in the air in the nineties, right? So you just didn't, we just didn't build these systems. S3 and and and so on was not around. And I think the architecture that is now possible that wasn't possible 15 years ago is to go all in on NVME SSDs. It requires a particular type of architecture for the database that.It's difficult to retrofit onto the databases that are already there, including the ones you just mentioned. The second thing is to go all in on OIC storage, more so than we could have done 15 years ago. Like we don't have a consensus layer, we don't really have anything. In fact, you could turn off all the servers that Turbo Buffer has, and we would not lose any data because we have all completely all in on OIC storage.And this means that our architecture is just so simple. So that's the second condition, right? First being a new workload. That means that every company on earth, either indirectly or directly, is using your database. Second being, there's some new storage architecture. That means that the, the companies that have come before you can do what you're doing.I think the third thing you need to do to build a big database company is that over time you have to implement more or less every Cory plan on the data. What that means is that you. You can't just get stuck in, like, this is the one thing that a database does. It has to be ever evolving because when someone has data in the database, they over time expect to be able to ask it more or less every question.So you have to do that to get the storage architecture to the limit of what, what it's capable of. Those are the three conditions.swyx: I just wanted to get a little bit of like the motivation, right? Like, so you left Shopify, you're like principal, engineer, infra guy. Um, you also head of kernel labs, uh, inside of Shopify, right?And then you consulted for read wise and that it kind of gave you that, that idea. I just wanted you to tell that story. Um, maybe I, you've told it before, but, uh, just introduce the, the. People to like the, the new workload, the sort of aha moment for turbo PufferSimon Hørup Eskildsen: For sure. So yeah, I spent almost a decade at Shopify.I was on the infrastructure team, um, from the fairly, fairly early days around 2013. Um, at the time it felt like it was growing so quickly and everything, all the metrics were, you know, doubling year on year compared to the, what companies are contending with today. It's very cute in growth. I feel like lot some companies are seeing that month over month.Um, of course. Shopify compound has been compounding for a very long time now, but I spent a decade doing that and the majority of that was just make sure the site is up today and make sure it's up a year from now. And a lot of that was really just the, um, you know, uh, the Kardashians would drive very, very large amounts of, of data to, to uh, to Shopify as they were rotating through all the merch and building out their businesses.And we just needed to make sure we could handle that. Right. And sometimes these were events, a million requests per second. And so, you know, we, we had our own data centers back in the day and we were moving to the cloud and there was so much sharding work and all of that that we were doing. So I spent a decade just scaling databases ‘cause that's fundamentally what's the most difficult thing to scale about these sites.The database that was the most difficult for me to scale during that time, and that was the most aggravating to be on call for, was elastic search. It was very, very difficult to deal with. And I saw a lot of projects that were just being held back in their ambition by using it.swyx: And I mean, self-hosted.Self-hosted. ‘causeSimon Hørup Eskildsen: it's, yeah, and it commercial, this is like 2015, right? So it's like a very particular vintage. Right. It's probably better at a lot of these things now. Um, it was difficult to contend with and I'm just like, I just think about it. It's an inverted index. It should be good at these kinds of queries and do all of this.And it was, we, we often couldn't get it to do exactly what we needed to do or basically get lucine to do, like expose lucine raw to, to, to what we needed to do. Um, so that was like. Just something that we did on the side and just panic scaled when we needed to, but not a particular focus of mine. So I left, and when I left, I, um, wasn't sure exactly what I wanted to do.I mean, it spent like a decade inside of the same company. I'd like grown up there. I started working there when I was 18.swyx: You only do Rails?Simon Hørup Eskildsen: Yeah. I mean, yeah. Rails. And he's a Rails guy. Uh, love Rails. So good. Um,Alessio: we all wish we could still work in Rails.swyx: I know know. I know, but some, I tried learning Ruby.It's just too much, like too many options to do the same thing. It's, that's my, I I know there's a, there's a way to do it.Simon Hørup Eskildsen: I love it. I don't know that I would use it now, like given cloud code and, and, and cursor and everything, but, um, um, but still it, like if I'm just sitting down and writing a teal code, that's how I think.But anyway, I left and I wasn't, I talked to a couple companies and I was like, I don't. I need to see a little bit more of the world here to know what I'm gonna like focus on next. Um, and so what I decided is like I was gonna, I called it like angel engineering, where I just hopped around in my friend's companies in three months increments and just helped them out with something.Right. And, and just vested a bit of equity and solved some interesting infrastructure problem. So I worked with a bunch of companies at the time, um, read Wise was one of them. Replicate was one of them. Um, causal, I dunno if you've tried this, it's like a, it's a spreadsheet engine Yeah. Where you can do distribution.They sold recently. Yeah. Um, we've been, we used that in fp and a at, um, at Turbo Puffer. Um, so a bunch of companies like this and it was super fun. And so we're the Chachi bt moment happened, I was with. With read Wise for a stint, we were preparing for the reader launch, right? Which is where you, you cue articles and read them later.And I was just getting their Postgres up to snuff, like, which basically boils down to tuning, auto vacuum. So I was doing that and then this happened and we were like, oh, maybe we should build a little recommendation engine and some features to try to hook in the lms. They were not that good yet, but it was clear there was something there.And so I built a small recommendation engine just, okay, let's take the articles that you've recently read, right? Like embed all the articles and then do recommendations. It was good enough that when I ran it on one of the co-founders of Rey's, like I found out that I got articles about, about having a child.I'm like, oh my God, I didn't, I, I didn't know that, that they were having a child. I wasn't sure what to do with that information, but the recommendation engine was good enough that it was suggesting articles, um, about that. And so there was, there was recommendations and uh, it actually worked really well.But this was a company that was spending maybe five grand a month in total on all their infrastructure and. When I did the napkin math on running the embeddings of all the articles, putting them into a vector index, putting it in prod, it's gonna be like 30 grand a month. That just wasn't tenable. Right?Like Read Wise is a proudly bootstrapped company and it's paying 30 grand for infrastructure for one feature versus five. It just wasn't tenable. So sort of in the bucket of this is useful, it's pretty good, but let us, let's return to it when the costs come down.swyx: Did you say it grows by feature? So for five to 30 is by the number of, like, what's the, what's the Scaling factor scale?It scales by the number of articles that you embed.Simon Hørup Eskildsen: It does, but what I meant by that is like five grand for like all of the other, like the Heroku, dinos, Postgres, like all the other, and this then storage is 30. Yeah. And then like 30 grand for one feature. Right. Which is like, what other articles are related to this one.Um, so it was just too much right to, to power everything. Their budget would've been maybe a few thousand dollars, which still would've been a lot. And so we put it in a bucket of, okay, we're gonna do that later. We'll wait, we will wait for the cost to come down. And that haunted me. I couldn't stop thinking about it.I was like, okay, there's clearly some latent demand here. If the cost had been a 10th, we would've shipped it and. This was really the only data point that I had. Right. I didn't, I, I didn't, I didn't go out and talk to anyone else. It was just so I started reading Right. I couldn't, I couldn't help myself.Like I didn't know what like a vector index is. I, I generally barely do about how to generate the vectors. There was a lot of hype about, this is a early 2023. There was a lot of hype about vector databases. There were raising a lot of money and it's like, I really didn't know anything about it. It's like, you know, trying these little models, fine tuning them.Like I was just trying to get sort of a lay of the land. So I just sat down. I have this. A GitHub repository called Napkin Math. And on napkin math, there's just, um, rows of like, oh, this is how much bandwidth. Like this is how many, you know, you can do 25 gigabytes per second on average to dram. You can do, you know, five gigabytes per second of rights to an SSD, blah blah.All of these numbers, right? And S3, how many you could do per, how much bandwidth can you drive per connection? I was just sitting down, I was like, why hasn't anyone build a database where you just put everything on O storage and then you puff it into NVME when you use the data and you puff it into dram if you're, if you're querying it alive, it's just like, this seems fairly obvious and you, the only real downside to that is that if you go all in on o storage, every right will take a couple hundred milliseconds of latency, but from there it's really all upside, right?You do the first go, it takes half a second. And it sort of occurred to me as like, well. The architecture is really good for that. It's really good for AB storage, it's really good for nvm ESSD. It's, well, you just couldn't have done that 10 years ago. Back to what we were talking about before. You really have to build a database where you have as few round trips as possible, right?This is how CPUs work today. It's how NVM E SSDs work. It's how as, um, as three works that you want to have a very large amount of outstanding requests, right? Like basically go to S3, do like that thousand requests to ask for data in one round trip. Wait for that. Get that, like, make a new decision. Do it again, and try to do that maybe a maximum of three times.But no databases were designed that way within NVME as is ds. You can drive like within, you know, within a very low multiple of DRAM bandwidth if you use it that way. And same with S3, right? You can fully max out the network card, which generally is not maxed out. You get very, like, very, very good bandwidth.And, but no one had built a database like that. So I was like, okay, well can't you just, you know, take all the vectors right? And plot them in the proverbial coordinate system. Get the clusters, put a file on S3 called clusters, do json, and then put another file for every cluster, you know, cluster one, do js O cluster two, do js ON you know that like it's two round trips, right?So you get the clusters, you find the closest clusters, and then you download the cluster files like the, the closest end. And you could do this in two round trips.swyx: You were nearest neighbors locally.Simon Hørup Eskildsen: Yes. Yes. And then, and you would build this, this file, right? It's just like ultra simplistic, but it's not a far shot from what the first version of Turbo Buffer was.Why hasn't anyone done thatAlessio: in that moment? From a workload perspective, you're thinking this is gonna be like a read heavy thing because they're doing recommend. Like is the fact that like writes are so expensive now? Oh, with ai you're actually not writing that much.Simon Hørup Eskildsen: At that point I hadn't really thought too much about, well no actually it was always clear to me that there was gonna be a lot of rights because at Shopify, the search clusters were doing, you know, I don't know, tens or hundreds of crew QPS, right?‘cause you just have to have a human sit and type in. But we did, you know, I don't know how many updates there were per second. I'm sure it was in the millions, right into the cluster. So I always knew there was like a 10 to 100 ratio on the read write. In the read wise use case. It's, um, even, even in the read wise use case, there'd probably be a lot fewer reads than writes, right?There's just a lot of churn on the amount of stuff that was going through versus the amount of queries. Um, I wasn't thinking too much about that. I was mostly just thinking about what's the fundamentally cheapest way to build a database in the cloud today using the primitives that you have available.And this is it, right? You just, now you have one machine and you know, let's say you have a terabyte of data in S3, you paid the $200 a month for that, and then maybe five to 10% of that data and needs to be an NV ME SSDs and less than that in dram. Well. You're paying very, very little to inflate the data.swyx: By the way, when you say no one else has done that, uh, would you consider Neon, uh, to be on a similar path in terms of being sort of S3 first and, uh, separating the compute and storage?Simon Hørup Eskildsen: Yeah, I think what I meant with that is, uh, just build a completely new database. I don't know if we were the first, like it was very much, it was, I mean, I, I hadn't, I just looked at the napkin math and was like, this seems really obvious.So I'm sure like a hundred people came up with it at the same time. Like the light bulb and every invention ever. Right. It was just in the air. I think Neon Neon was, was first to it. And they're trying, they're retrofitted onto Postgres, right? And then they built this whole architecture where you have, you have it in memory and then you sort of.You know, m map back to S3. And I think that was very novel at the time to do it for, for all LTP, but I hadn't seen a database that was truly all in, right. Not retrofitting it. The database felt built purely for this no consensus layer. Even using compare and swap on optic storage to do consensus. I hadn't seen anyone go that all in.And I, I mean, there, there, I'm sure there was someone that did that before us. I don't know. I was just looking at the napkin mathswyx: and, and when you say consensus layer, uh, are you strongly relying on S3 Strong consistency? You are. Okay.SoSimon Hørup Eskildsen: that is your consensus layer. It, it is the consistency layer. And I think also, like, this is something that most people don't realize, but S3 only became consistent in December of 2020.swyx: I remember this coming out during COVID and like people were like, oh, like, it was like, uh, it was just like a free upgrade.Simon Hørup Eskildsen: Yeah.swyx: They were just, they just announced it. We saw consistency guys and like, okay, cool.Simon Hørup Eskildsen: And I'm sure that they just, they probably had it in prod for a while and they're just like, it's done right.And people were like, okay, cool. But. That's a big moment, right? Like nv, ME SSDs, were also not in the cloud until around 2017, right? So you just sort of had like 2017 nv, ME SSDs, and people were like, okay, cool. There's like one skew that does this, whatever, right? Takes a few years. And then the second thing is like S3 becomes consistent in 2020.So now it means you don't have to have this like big foundation DB or like zookeeper or whatever sitting there contending with the keys, which is how. You know, that's what Snowflake and others have do so muchswyx: for goneSimon Hørup Eskildsen: Exactly. Just gone. Right? And so just push to the, you know, whatever, how many hundreds of people they have working on S3 solved and then compare and swap was not in S3 at this point in time,swyx: by the way.Uh, I don't know what that is, so maybe you wanna explain. Yes. Yeah.Simon Hørup Eskildsen: Yes. So, um, what Compare and swap is, is basically, you can imagine that if you have a database, it might be really nice to have a file called metadata json. And metadata JSON could say things like, Hey, these keys are here and this file means that, and there's lots of metadata that you have to operate in the database, right?But that's the simplest way to do it. So now you have might, you might have a lot of servers that wanna change the metadata. They might have written a file and want the metadata to contain that file. But you have a hundred nodes that are trying to contend with this metadata that JSON well, what compare and Swap allows you to do is basically just you download the file, you make the modifications, and then you write it only if it hasn't changed.While you did the modification and if not you retry. Right? Should just have this retry loops. Now you can imagine if you have a hundred nodes doing that, it's gonna be really slow, but it will converge over time. That primitive was not available in S3. It wasn't available in S3 until late 2024, but it was available in GCP.The real story of this is certainly not that I sat down and like bake brained it. I was like, okay, we're gonna start on GCS S3 is gonna get it later. Like it was really not that we started, we got really lucky, like we started on GCP and we started on GCP because tur um, Shopify ran on GCP. And so that was the platform I was most available with.Right. Um, and I knew the Canadian team there ‘cause I'd worked with them at Shopify and so it was natural for us to start there. And so when we started building the database, we're like, oh yeah, we have to build a, we really thought we had to build a consensus layer, like have a zookeeper or something to do this.But then we discovered the compare and swap. It's like, oh, we can kick the can. Like we'll just do metadata r json and just, it's fine. It's probably fine. Um, and we just kept kicking the can until we had very, very strong conviction in the idea. Um, and then we kind of just hinged the company on the fact that S3 probably was gonna get this, it started getting really painful in like mid 2024.‘cause we were closing deals with, um, um, notion actually that was running in AWS and we're like, trust us. You, you really want us to run this in GCP? And they're like, no, I don't know about that. Like, we're running everything in AWS and the latency across the cloud were so big and we had so much conviction that we bought like, you know, dark fiber between the AWS regions in, in Oregon, like in the InterExchange and GCP is like, we've never seen a startup like do like, what's going on here?And we're just like, no, we don't wanna do this. We were tuning like TCP windows, like everything to get the latency down ‘cause we had so high conviction in not doing like a, a metadata layer on S3. So those were the three conditions, right? Compare and swap. To do metadata, which wasn't in S3 until late 2024 S3 being consistent, which didn't happen until December, 2020.Uh, 2020. And then NVMe ssd, which didn't end in the cloud until 2017.swyx: I mean, in some ways, like a very big like cloud success story that like you were able to like, uh, put this all together, but also doing things like doing, uh, bind our favor. That that actually is something I've never heard.Simon Hørup Eskildsen: I mean, it's very common when you're a big company, right?You're like connecting your own like data center or whatever. But it's like, it was uniquely just a pain with notion because the, um, the org, like most of the, like if you're buying in Ashburn, Virginia, right? Like US East, the Google, like the GCP and, and AWS data centers are like within a millisecond on, on each other, on the public exchanges.But in Oregon uniquely, the GCP data center sits like a couple hundred kilometers, like east of Portland and the AWS region sits in Portland, but the network exchange they go through is through Seattle. So it's like a full, like 14 milliseconds or something like that. And so anyway, yeah. It's, it's, so we were like, okay, we can't, we have to go through an exchange in Portland.Yeah. Andswyx: you'd rather do this than like run your zookeeper and likeSimon Hørup Eskildsen: Yes. Way rather. It doesn't have state, I don't want state and two systems. Um, and I think all that is just informed by Justine, my co-founder and I had just been on call for so long. And the worst outages are the ones where you have state in multiple places that's not syncing up.So it really came from, from a a, like just a, a very pure source of pain, of just imagining what we would be Okay. Being woken up at 3:00 AM about and having something in zookeeper was not one of them.swyx: You, you're talking to like a notion or something. Do they care or do they just, theySimon Hørup Eskildsen: just, they care about latency.swyx: They latency cost. That's it.Simon Hørup Eskildsen: They just cared about latency. Right. And we just absorbed the cost. We're just like, we have high conviction in this. At some point we can move them to AWS. Right. And so we just, we, we'll buy the fiber, it doesn't matter. Right. Um, and it's like $5,000. Usually when you buy fiber, you buy like multiple lines.And we're like, we can only afford one, but we will just test it that when it goes over the public internet, it's like super smooth. And so we did a lot of, anyway, it's, yeah, it was, that's cool.Alessio: You can imagine talking to the GCP rep and it's like, no, we're gonna buy, because we know we're gonna turn, we're gonna turn from you guys and go to AWS in like six months.But in the meantime we'll do this. It'sSimon Hørup Eskildsen: a, I mean, like they, you know, this workload still runs on GCP for what it's worth. Right? ‘cause it's so, it was just, it was so reliable. So it was never about moving off GCP, it was just about honesty. It was just about giving notion the latency that they deserved.Right. Um, and we didn't want ‘em to have to care about any of this. We also, they were like, oh, egress is gonna be bad. It was like, okay, screw it. Like we're just gonna like vvc, VPC peer with you and AWS we'll eat the cost. Yeah. Whatever needs to be done.Alessio: And what were the actual workloads? Because I think when you think about ai, it's like 14 milliseconds.It's like really doesn't really matter in the scheme of like a model generation.Simon Hørup Eskildsen: Yeah. We were told the latency, right. That we had to beat. Oh, right. So, so we're just looking at the traces. Right. And then sort of like hand draw, like, you know, kind of like looking at the trace and then thinking what are the other extensions of the trace?Right. And there's a lot more to it because it's also when you have, if you have 14 versus seven milliseconds, right. You can fit in another round trip. So we had to tune TCP to try to send as much data in every round trip, prewarm all the connections. And there was, there's a lot of things that compound from having these kinds of round trips, but in the grand scheme it was just like, well, we have to beat the latency of whatever we're up against.swyx: Which is like they, I mean, notion is a database company. They could have done this themselves. They, they do lots of database engineering themselves. How do you even get in the door? Like Yeah, just like talk through that kind of.Simon Hørup Eskildsen: Last time I was in San Francisco, I was talking to one of the engineers actually, who, who was one of our champions, um, at, AT Notion.And they were, they were just trying to make sure that the, you know, per user cost matched the economics that they needed. You know, Uhhuh like, it's like the way I think about, it's like I have to earn a return on whatever the clouds charge me and then my customers have to earn a return on that. And it's like very simple, right?And so there has to be gross margin all the way up and that's how you build the product. And so then our customers have to make the right set of trade off the turbo Puffer makes, and if they're happy with that, that's great.swyx: Do you feel like you're competing with build internally versus buy or buy versus buy?Simon Hørup Eskildsen: Yeah, so, sorry, this was all to build up to your question. So one of the notion engineers told me that they'd sat and probably on a napkin, like drawn out like, why hasn't anyone built this? And then they saw terrible. It was like, well, it literally that. So, and I think AI has also changed the buy versus build equation in terms of, it's not really about can we build it, it's about do we have time to build it?I think they like, I think they felt like, okay, if this is a team that can do that and they, they feel enough like an extension of our team, well then we can go a lot faster, which would be very, very good for them. And I mean, they put us through the, through the test, right? Like we had some very, very long nights to to, to do that POC.And they were really our biggest, our second big customer off the cursor, which also was a lot of late nights. Right.swyx: Yeah. That, I mean, should we go into that story? The, the, the sort of Chris's story, like a lot, um, they credit you a lot for. Working very closely with them. So I just wanna hear, I've heard this, uh, story from Sole's point of view, but like, I'm curious what, what it looks like from your side.Simon Hørup Eskildsen: I actually haven't heard it from Sole's point of view, so maybe you can now cross reference it. The way that I remember it was that, um, the day after we launched, which was just, you know, I'd worked the whole summer on, on the first version. Justine wasn't part of it yet. ‘cause I just, I didn't tell anyone that summer that I was working on this.I was just locked in on building it because it's very easy otherwise to confuse talking about something to actually doing it. And so I was just like, I'm not gonna do that. I'm just gonna do the thing. I launched it and at this point turbo puffer is like a rust binary running on a single eight core machine in a T Marks instance.And me deploying it was like looking at the request log and then like command seeing it or like control seeing it to just like, okay, there's no request. Let's upgrade the binary. Like it was like literally the, the, the, the scrappiest thing. You could imagine it was on purpose because just like at Shopify, we did that all the time.Like, we like move, like we ran things in tux all the time to begin with. Before something had like, at least the inkling of PMF, it was like, okay, is anyone gonna hear about this? Um, and one of the cursor co-founders Arvid reached out and he just, you know, the, the cursor team are like all I-O-I-I-M-O like, um, contenders, right?So they just speak in bullet points and, and facts. It was like this amazing email exchange just of, this is how many QPS we have, this is what we're paying, this is where we're going, blah, blah, blah. And so we're just conversing in bullet points. And I tried to get a call with them a few times, but they were, so, they were like really writing the PMF bowl here, just like late 2023.And one time Swally emails me at like five. What was it like 4:00 AM Pacific time saying like, Hey, are you open for a call now? And I'm on the East coast and I, it was like 7:00 AM I was like, yeah, great, sure, whatever. Um, and we just started talking and something. Then I didn't know anything about sales.It was something that just comp compelled me. I have to go see this team. Like, there's something here. So I, I went to San Francisco and I went to their office and the way that I remember it is that Postgres was down when I showed up at the office. Did SW tell you this? No. Okay. So Postgres was down and so it's like they were distracting with that.And I was trying my best to see if I could, if I could help in any way. Like I knew a little bit about databases back to tuning, auto vacuum. It was like, I think you have to tune out a vacuum. Um, and so we, we talked about that and then, um, that evening just talked about like what would it look like, what would it look like to work with us?And I just said. Look like we're all in, like we will just do what we'll do whatever, whatever you tell us, right? They migrated everything over the next like week or two, and we reduced their cost by 95%, which I think like kind of fixed their per user economics. Um, and it solved a lot of other things. And we were just, Justine, this is also when I asked Justine to come on as my co-founder, she was the best engineer, um, that I ever worked with at Shopify.She lived two blocks away and we were just, okay, we're just gonna get this done. Um, and we did, and so we helped them migrate and we just worked like hell over the next like month or two to make sure that we were never an issue. And that was, that was the cursor story. Yeah.swyx: And, and is code a different workload than normal text?I, I don't know. Is is it just text? Is it the same thing?Simon Hørup Eskildsen: Yeah, so cursor's workload is basically, they, um, they will embed the entire code base, right? So they, they will like chunk it up in whatever they would, they do. They have their own embedding model, um, which they've been public about. Um, and they find that on, on, on their evals.It. There's one of their evals where it's like a 25% improvement on a very particular workload. They have a bunch of blog posts about it. Um, I think it works best on larger code basis, but they've trained their own embedding model to do this. Um, and so you'll see it if you use the cursor agent, it will do searches.And they've also been public around, um, how they've, I think they post trained their model to be very good at semantic search as well. Um, and that's, that's how they use it. And so it's very good at, like, can you find me on the code that's similar to this, or code that does this? And just in, in this queries, they also use GR to supplement it.swyx: Yeah.Simon Hørup Eskildsen: Um, of courseswyx: it's been a big topic of discussion like, is rag dead because gr you know,Simon Hørup Eskildsen: and I mean like, I just, we, we see lots of demand from the coding company to ethicsswyx: search in every part. Yes.Simon Hørup Eskildsen: Uh, we, we, we see demand. And so, I mean, I'm. I like case studies. I don't like, like just doing like thought pieces on this is where it's going.And like trying to be all macroeconomic about ai, that's has turned out to be a giant waste of time because no one can really predict any of this. So I just collect case studies and I mean, cursor has done a great job talking about what they're doing and I hope some of the other coding labs that use Turbo Puffer will do the same.Um, but it does seem to make a difference for particular queries. Um, I mean we can also do text, we can also do RegX, but I should also say that cursors like security posture into Tur Puffer is exceptional, right? They have their own embedding model, which makes it very difficult to reverse engineer. They obfuscate the file paths.They like you. It's very difficult to learn anything about a code base by looking at it. And the other thing they do too is that for their customers, they encrypt it with their encryption keys in turbo puffer's bucket. Um, so it's, it's, it's really, really well designed.swyx: And so this is like extra stuff they did to work with you because you are not part of Cursor.Exactly like, and this is just best practice when working in any database, not just you guys. Okay. Yeah, that makes sense. Yeah. I think for me, like the, the, the learning is kind of like you, like all workloads are hybrid. Like, you know, uh, like you, you want the semantic, you want the text, you want the RegX, you want sql.I dunno. Um, but like, it's silly to like be all in on like one particularly query pattern.Simon Hørup Eskildsen: I think, like I really like the way that, um, um, that swally at cursor talks about it, which is, um, I'm gonna butcher it here. Um, and you know, I'm a, I'm a database scalability person. I'm not a, I, I dunno anything about training models other than, um, what the internet tells me and what.The way he describes is that this is just like cash compute, right? It's like you have a point in time where you're looking at some particular context and focused on some chunk and you say, this is the layer of the neural net at this point in time. That seems fundamentally really useful to do cash compute like that.And, um, how the value of that will change over time. I'm, I'm not sure, but there seems to be a lot of value in that.Alessio: Maybe talk a bit about the evolution of the workload, because even like search, like maybe two years ago it was like one search at the start of like an LLM query to build the context. Now you have a gentech search, however you wanna call it, where like the model is both writing and changing the code and it's searching it again later.Yeah. What are maybe some of the new types of workloads or like changes you've had to make to your architecture for it?Simon Hørup Eskildsen: I think you're right. When I think of rag, I think of, Hey, there's an 8,000 token, uh, context window and you better make it count. Um, and search was a way to do that now. Everything is moving towards the, just let the agent do its thing.Right? And so back to the thing before, right? The LLM is very good at reasoning with the data, and so we're just the tool call, right? And that's increasingly what we see our customers doing. Um, what we're seeing more demand from, from our customers now is to do a lot of concurrency, right? Like Notion does a ridiculous amount of queries in every round trip just because they can't.And I'm also now, when I use the cursor agent, I also see them doing more concurrency than I've ever seen before. So a bit similar to how we designed a database to drive as much concurrency in every round trip as possible. That's also what the agents are doing. So that's new. It means just an enormous amount of queries all at once to the dataset while it's warm in as few turns as possible.swyx: Can I clarify one thing on that?Simon Hørup Eskildsen: Yes.swyx: Is it, are they batching multiple users or one user is driving multiple,Simon Hørup Eskildsen: one user driving multiple, one agent driving.swyx: It's parallel searching a bunch of things.Simon Hørup Eskildsen: Exactly.swyx: Yeah. Yeah, exactly. So yeah, the clinician also did, did this for the fast context thing, like eight parallel at once.Simon Hørup Eskildsen: Yes.swyx: And, and like an interesting problem is, well, how do you make sure you have enough diversity so you're not making the the same request eight times?Simon Hørup Eskildsen: And I think like that's probably also where the hybrid comes in, where. That's another way to diversify. It's a completely different way to, to do the search.That's a big change, right? So before it was really just like one call and then, you know, the LLM took however many seconds to return, but now we just see an enormous amount of queries. So the, um, we just see more queries. So we've like tried to reduce query, we've reduced query pricing. Um, this is probably the first time actually I'm saying that, but the query pricing is being reduced, like five x.Um, and we'll probably try to reduce it even more to accommodate some of these workloads of just doing very large amounts of queries. Um, that's one thing that's changed. I think the right, the right ratio is still very high, right? Like there's still a, an enormous amount of rights per read, but we're starting probably to see that change if people really lean into this pattern.Alessio: Can we talk a little bit about the pricing? I'm curious, uh, because traditionally a database would charge on storage, but now you have the token generation that is so expensive, where like the actual. Value of like a good search query is like much higher because they're like saving inference time down the line.How do you structure that as like, what are people receptive to on the other side too?Simon Hørup Eskildsen: Yeah. I, the, the turbo puffer pricing in the beginning was just very simple. The pricing on these on for search engines before Turbo Puffer was very server full, right? It was like, here's the vm, here's the per hour cost, right?Great. And I just sat down with like a piece of paper and said like, if Turbo Puffer was like really good, this is probably what it would cost with a little bit of margin. And that was the first pricing of Turbo Puffer. And I just like sat down and I was like, okay, like this is like probably the storage amp, but whenever on a piece of paper I, it was vibe pricing.It was very vibe price, and I got it wrong. Oh. Um, well I didn't get it wrong, but like Turbo Puffer wasn't at the first principle pricing, right? So when Cursor came on Turbo Puffer, it was like. Like, I didn't know any VCs. I didn't know, like I was just like, I don't know, I didn't know anything about raising money or anything like that.I just saw that my GCP bill was, was high, was a lot higher than the cursor bill. So Justine and I was just like, well, we have to optimize it. Um, and I mean, to the chagrin now of, of it, of, of the VCs, it now means that we're profitable because we've had so much pricing pressure in the beginning. Because it was running on my credit card and Justine and I had spent like, like tens of thousands of dollars on like compute bills and like spinning off the company and like very like, like bad Canadian lawyers and like things like to like get all of this done because we just like, we didn't know.Right. If you're like steeped in San Francisco, you're just like, you just know. Okay. Like you go out, raise a pre-seed round. I, I never heard a word pre-seed at this point in time.swyx: When you had Cursor, you had Notion you, you had no funding.Simon Hørup Eskildsen: Um, with Cursor we had no funding. Yeah. Um, by the time we had Notion Locke was, Locke was here.Yeah. So it was really just, we vibe priced it 100% from first Principles, but it wasn't, it, it was not performing at first principles, so we just did everything we could to optimize it in the beginning for that, so that at least we could have like a 5% margin or something. So I wasn't freaking out because Cursor's bill was also going like this as they were growing.And so my liability and my credit limit was like actively like calling my bank. It was like, I need a bigger credit. Like it was, yeah. Anyway, that was the beginning. Yeah. But the pricing was, yeah, like storage rights and query. Right. And the, the pricing we have today is basically just that pricing with duct tape and spit to try to approach like, you know, like a, as a margin on the physical underlying hardware.And we're doing this year, you're gonna see more and more pricing changes from us. Yeah.swyx: And like is how much does stuff like VVC peering matter because you're working in AWS land where egress is charged and all that, you know.Simon Hørup Eskildsen: We probably don't like, we have like an enterprise plan that just has like a base fee because we haven't had time to figure out SKU pricing for all of this.Um, but I mean, yeah, you can run turbo puffer either in SaaS, right? That's what Cursor does. You can run it in a single tenant cluster. So it's just you. That's what Notion does. And then you can run it in, in, in BYOC where everything is inside the customer's VPC, that's what an for example, philanthropic does.swyx: What I'm hearing is that this is probably the best CRO job for somebody who can come in and,Simon Hørup Eskildsen: I mean,swyx: help you with this.Simon Hørup Eskildsen: Um, like Turbo Puffer hired, like, I don't know what, what number this was, but we had a full-time CFO as like the 12th hire or something at Turbo Puffer, um, I think I hear are a lot of comp.I don't know how they do it. Like they have a hundred employees and not a CFO. It's like having a CFO is like a runningswyx: business man. Like, you know,Simon Hørup Eskildsen: it's so good. Yeah, like money Mike, like he just, you know, just handles the money and a lot of the business stuff and so he came in and just hopped with a lot of the operational side of the business.So like C-O-O-C-F-O, like somewhere in between.swyx: Just as quick mention of Lucky, just ‘cause I'm curious, I've met Lock and like, he's obviously a very good investor and now on physical intelligence, um, I call it generalist super angel, right? He invests in everything. Um, and I always wonder like, you know, is there something appealing about focusing on developer tooling, focusing on databases, going like, I've invested for 10 years in databases versus being like a lock where he can maybe like connect you to all the customers that you need.Simon Hørup Eskildsen: This is an excellent question. No, no one's asked me this. Um, why lockey? Because. There was a couple of people that we were talking to at the time and when we were raising, we were almost a little, we were like a bit distressed because one of our, one of our peers had just launched something that was very similar to Turbo Puffer.And someone just gave me the advice at the time of just choose the person where you just feel like you can just pick up the phone and not prepare anything. And just be completely honest, and I don't think I've said this publicly before, but I just called Lockey and was like local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you.But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working. So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people and we're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards and.Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before. As I said, I didn't even know what a seed or pre-seed round was like before, probably even at this time. So I was just like very honest with him. And I asked him like, Lockie, have you ever have, have you ever invested in database company?He was just like, no. And at the time I was like, am I dumb? Like, but I think there was something that just like really drew me to Lockie. He is so authentic, so honest, like, and there was something just like, I just felt like I could just play like, just say everything openly. And that was, that was, I think that that was like a perfect match at the time, and, and, and honestly still is.He was just like, okay, that's great. This is like the most honest, ridiculous thing I've ever heard anyone say to me. But like that, like that, whyswyx: is this ridiculous? Say competitor launch, this may not work out. It wasSimon Hørup Eskildsen: more just like. If this doesn't work out, I'm gonna close up shop by the end of the mo the year, right?Like it was, I don't know, maybe it's common. I, I don't know. He told me it was uncommon. I don't know. Um, that's why we chose him and he'd been phenomenal. The other people were talking at the, at the time were database experts. Like they, you know, knew a lot about databases and Locke didn't, this turned out to be a phenomenal asset.Right. I like Justine and I know a lot about databases. The people that we hire know a lot about databases. What we needed was just someone who didn't know a lot about databases, didn't pretend to know a lot about databases, and just wanted to help us with candidates and customers. And he did. Yeah. And I have a list, right, of the investors that I have a relationship with, and Lockey has just performed excellent in the number of sub bullets of what we can attribute back to him.Just absolutely incredible. And when people talk about like no ego and just the best thing for the founder, I like, I don't think that anyone, like even my lawyer is like, yeah, Lockey is like the most friendly person you will find.swyx: Okay. This is my most glow recommendation I've ever heard.Alessio: He deserves it.He's very special.swyx: Yeah. Yeah. Yeah. Okay. Amazing.Alessio: Since you mentioned candidates, maybe we can talk about team building, you know, like, especially in sf, it feels like it's just easier to start a company than to join a company. Uh, I'm curious your experience, especially not being n SF full-time and doing something that is maybe, you know, a very low level of detail and technical detail.Simon Hørup Eskildsen: Yeah. So joining versus starting, I never thought that I would be a founder. I would start with it, like Turbo Puffer started as a blog post, and then it became a project and then sort of almost accidentally became a company. And now it feels like it's, it's like becoming a bigger company. That was never the intention.The intentions were very pure. It's just like, why hasn't anyone done this? And it's like, I wanna be the, like, I wanna be the first person to do it. I think some founders have this, like, I could never work for anyone else. I, I really don't feel that way. Like, it's just like, I wanna see this happen. And I wanna see it happen with some people that I really enjoy working with and I wanna have fun doing it and this, this, this has all felt very natural on that, on that sense.So it was never a like join versus versus versus found. It was just dis found me at the right moment.Alessio: Well I think there's an argument for, you should have joined Cursor, right? So I'm curious like how you evaluate it. Okay, I should actually go raise money and make this a company versus like, this is like a company that is like growing like crazy.It's like an interesting technical problem. I should just build it within Cursor and then they don't have to encrypt all this stuff. They don't have to obfuscate things. Like was that on your mind at all orSimon Hørup Eskildsen: before taking the, the small check from Lockie, I did have like a hard like look at myself in the mirror of like, okay, do I really want to do this?And because if I take the money, I really have to do it right. And so the way I almost think about it's like you kind of need to ha like you kind of need to be like fucked up enough to want to go all the way. And that was the conversation where I was like, okay, this is gonna be part of my life's journey to build this company and do it in the best way that I possibly can't.Because if I ask people to join me, ask people to get on the cap table, then I have an ultimate responsibility to give it everything. And I don't, I think some people, it doesn't occur to me that everyone takes it that seriously. And maybe I take it too seriously, I don't know. But that was like a very intentional moment.And so then it was very clear like, okay, I'm gonna do this and I'm gonna give it everything.Alessio: A lot of people don't take it this seriously. But,swyx: uh, let's talk about, you have this concept of the P 99 engineer. Uh, people are 10 x saying, everyone's saying, you know, uh, maybe engineers are out of a job. I don't know.But you definitely see a P 99 engineer, and I just want you to talk about it.Simon Hørup Eskildsen: Yeah, so the P 99 engineer was just a term that we started using internally to talk about candidates and talk about how we wanted to build the company. And you know, like everyone else is, like we want a talent dense company.And I think that's almost become trite at this point. What I credit the cursor founders a lot with is that they just arrived there from first principles of like, we just need a talent dense, um, talent dense team. And I think I've seen some teams that weren't talent dense and like seemed a counterfactual run, which if you've run in been in a large company, you will just see that like it's just logically will happen at a large company.Um, and so that was super important to me and Justine and it's very difficult to maintain. And so we just needed, we needed wording for it. And so I have a document called Traits of the P 99 Engineer, and it's a bullet point list. And I look at that list after every single interview that I do, and in every single recap that we do and every recap we end with.End with, um, some version of I'm gonna reject this candidate completely regardless of what the discourse was, because I wanna see people fight for this person because the default should not be, we're gonna hire this person. The default should be, we're definitely not hiring this person. And you know, if everyone was like, ah, maybe throw a punch, then this is not the right.swyx: Do, do you operate, like if there's one cha there must have at least one champion who's like, yes, I will put my career on, on, on the line for this. You know,Simon Hørup Eskildsen: I think career on the line,swyx: maybe a chair, butSimon Hørup Eskildsen: yeah. You know, like, um, I would say so someone needs to like, have both fists up and be like, I'd fight.Right? Yeah. Yeah. And if one person said, then, okay, let's do it. Right?swyx: Yeah.Simon Hørup Eskildsen: Um. It doesn't have to be absolutely everyone. Right? And like the interviews are always the sign that you're checking for different attributes. And if someone is like knocking it outta the park in every single attribute, that's, that's fairly rare.Um, but that's really important. And so the traits of the P 99 engineer, there's lots of them. There's also the traits of the p like triple nine engineer and the quadruple nine engineer. This is like, it's a long list.swyx: Okay.Simon Hørup Eskildsen: Um, I'll give you some samples, right. Of what we, what we look for. I think that the P 99 engineer has some history of having bent, like their trajectory or something to their will.Right? Some moment where it was just, they just, you know, made the computer do what it needed to do. There's something like that, and it will, it will occur to have them at some point in their career. And, uh. Hopefully multiple times. Right.swyx: Gimme an example of one of your engineers that like,Simon Hørup Eskildsen: I'll give an eng.Uh, so we, we, we launched this thing called A and NV three. Um, we could, we're also, we're working on V four and V five right now, but a and NV three can search a hundred billion vectors with a P 50 of around 40 milliseconds and a p 99 of 200 milliseconds. Um, maybe other people have done this, I'm sure Google and others have done this, but, uh, we haven't seen anyone, um, at least not in like a public consumable SaaS that can do this.And that was an engineer, the chief architect of Turbo Puffer, Nathan, um, who more or less just bent this, the software was not capable of this and he just made it capable for a very particular workload in like a, you know, six to eight week period with the help of a lot of the team. Right. It's been, been, there's numerous of examples of that, like at, at turbo puff, but that's like really bending the software and X 86 to your will.It was incredible to watch. Um. You wanna see some moments like that?swyx: Isn't that triple nine?Simon Hørup Eskildsen: Um, I think Nathan, what's calledAlessio: group nine, that was only nine. I feel like this is too high forSimon Hørup Eskildsen: Nathan. Nathan is, uh, Nathan is like, yeah, there's a lot of nines. Okay. After that p So I think that's one trait. I think another trait is that, uh, the P 99 spends a lot of time looking at maps.Generally it's their preferred ux. They just love looking at maps. You ever seen someone who just like, sits on their phone and just like, scrolls around on a map? Or did you not look at maps A lot? You guys don't look atswyx: maps? I guess I'm not feeling there. I don't know, butSimon Hørup Eskildsen: you just dis What about trains?Do you like trains?swyx: Uh, I mean they, not enough. Okay. This is just like weapon nice. Autism is what I call it. Like, like,Simon Hørup Eskildsen: um, I love looking at maps, like, it's like my preferred UX and just like I, you know, I likeswyx: lotsAlessio: of, of like random places, soswyx: like,youswyx: know.Alessio: Yes. Okay. There you go. So instead of like random places, like how do you explore the maps?Simon Hørup Eskildsen: No, it's, it's just a joke.swyx: It's autism laugh. It's like you are just obsessed by something and you like studying a thing.Simon Hørup Eskildsen: The origin of this was that at some point I read an interview with some IOI gold medalistswyx: Uhhuh,Simon Hørup Eskildsen: and it's like, what do you do in your spare time? I was just like, I like looking at maps.I was like, I feel so seen. Like, I just like love, like swirling out. I was like, oh, Canada is so big. Where's Baffin Island? I don't know. I love it. Yeah. Um, anyway, so the traits of P 99, P 99 is obsessive, right? Like, there's just like, you'll, you'll find traits of that we do an interview at, at, at, at turbo puffer or like multiple interviews that just try to screen for some of these things.Um, so. There's lots of others, but these are the kinds of traits that we look for.swyx: I'll tell you, uh, some people listen for like some of my dere stuff. Uh, I do think about derel as maps. Um, you draw a map for people, uh, maps show you the, uh, what is commonly agreed to be the geographical features of what a boundary is.And it shows also shows you what is not doing. And I, I think a lot of like developer tools, companies try to tell you they can do everything, but like, let's, let's be real. Like you, your, your three landmarks are here, everyone comes here, then here, then here, and you draw a map and, and then you draw a journey through the map.And like that. To me, that's what developer relations looks like. So I do think about things that way.Simon Hørup Eskildsen: I think the P 99 thinks in offs, right? The P 99 is very clear about, you know, hey, turbo puffer, you can't run a high transaction workload on turbo puffer, right? It's like the right latency is a hundred milliseconds.That's a clear trade off. I think the P 99 is very good at articulating the trade offs in every decision. Um. Which is exactly what the map is in your case, right?swyx: Uh, yeah, yeah. My, my, my world. My world.Alessio: How, how do you reconcile some of these things when you're saying you bend the will the computer versus like the trade
PODCAST LAS NOTICIAS CON CALLE DE 10 DE MARZO DE 2026 - Trump y Putin hablaron y llegan a acuerdo para liberar petróleo ruso - Reuters Petróleo bajó de precio a 87 el barril - CNBCLe dan asilo a mujeres iraníes que no quisieron cantar el himno de Irán en protesta - One Sports Representante busca que informante que investigó a Ciary vaya a vista en Legislatura - Notidel Plantean traer cohetes a Roosevelt Roads - El Nuevo DíaInvestigación contra Ciary seguirá por tres meses más, Rivera Schatz pide revisión - El Nuevo Día Plantean medida para impedir a gobierno federal a detener aguantar los fondos federales - El Nuevo DíaJuicio contra Anthonieska comienza el 6 de abril - El Nuevo Día¿Deben hablar inglés los meseros? - El Nuevo Día Dramática baja del precio del combustible luego de subida, pero el litro de gasolina ronda por el peso - El Vocero Expropiaciones forzosas tras el estado activarse - El Vocero Hay momentos en los que no necesitas solo respuestas sino tranquilidad y apoyo. En Universal Group combinamos tecnología avanzada con el Toque Humano que te da calma y te responde al instante. Universal: Auspiciador oficial del equipo de Puerto Rico en el World Baseball Classic.Incluye auspicio
© 2020-2026 Ivy Podcast Discovery LLC
