Podcasts about Databricks

Google about to snatch the crown… and a lot of y'all still stuck worshipping Nvidia like it's the only AI play that matter. I'm telling you right now: the market switches leaders — and when that leadership flips, it leaves people behind who don't see the shift coming.In this episode I break down why I believe Alphabet (Google) can become the #1 most valuable company, how AI chips + Gemini + YouTube + Cloud partnerships are stacking the deck, and why Nvidia still can run… but the competition is finally heavy. We also get into Apple picking Gemini, big tech power moves, Meta spending like a maniac on nuclear energy, and the 2026 IPO watchlist (SpaceX, OpenAI, Anthropic, Databricks, Stripe, Revolut, Canva — and my sleeper pick will surprise you).High-intent SEO keywords we touch naturally: Google stock, Alphabet stock, Gemini AI, Nvidia competition, AI chips, Big Tech leadership rotation, Apple Gemini deal, Google Cloud, YouTube revenue, AI investing, market leadership switching, Meta nuclear energy deal, 2026 IPOs, SpaceX IPO, OpenAI IPO, Anthropic IPO, Databricks IPO, Stripe IPO, Canva IPO, AI infrastructure stocks.Apple Picked Google Gemini. Bad News for Nvidia?Join our Exclusive Patreon!!! Creating Financial Empowerment for those who've never had it.

Corey Zumar is a Product Manager at Databricks, working on MLflow and LLM evaluation, tracing, and lifecycle tooling for generative AI.Jules Damji is a Lead Developer Advocate at Databricks, working on Spark, lakehouse technologies, and developer education across the data and AI community.Danny Chiao is an Engineering Leader at Databricks, working on data and AI observability, quality, and production-grade governance for ML and agent systems.MLflow Leading Open Source // MLOps Podcast #356 with Databricks' Corey Zumar, Jules Damji, and Danny ChiaoJoin the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletterShoutout to Databricks for powering this MLOps Podcast episode.// AbstractMLflow isn't just for data scientists anymore—and pretending it is is holding teams back. Corey Zumar, Jules Damji, and Danny Chiao break down how MLflow is being rebuilt for GenAI, agents, and real production systems where evals are messy, memory is risky, and governance actually matters. The takeaway: if your AI stack treats agents like fancy chatbots or splits ML and software tooling, you're already behind.// BioCorey ZumarCorey has been working as a Software Engineer at Databricks for the last 4 years and has been an active contributor to and maintainer of MLflow since its first release. Jules Damji Jules is a developer advocate at Databricks Inc., an MLflow and Apache Spark™ contributor, and Learning Spark, 2nd Edition coauthor. He is a hands-on developer with over 25 years of experience. He has worked at leading companies, such as Sun Microsystems, Netscape, @Home, Opsware/LoudCloud, VeriSign, ProQuest, Hortonworks, Anyscale, and Databricks, building large-scale distributed systems. He holds a B.Sc. and M.Sc. in computer science (from Oregon State University and Cal State, Chico, respectively) and an MA in political advocacy and communication (from Johns Hopkins University)Danny ChiaoDanny is an engineering lead at Databricks, leading efforts around data observability (quality, data classification). Previously, Danny led efforts at Tecton (+ Feast, an open source feature store) and Google to build ML infrastructure and large-scale ML-powered features. Danny holds a Bachelor's Degree in Computer Science from MIT.// Related LinksWebsite: https://mlflow.org/https://www.databricks.com/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Corey on LinkedIn: /corey-zumar/Connect with Jules on LinkedIn: /dmatrix/Connect with Danny on LinkedIn: /danny-chiao/Timestamps:[00:00] MLflow Open Source Focus[00:49] MLflow Agents in Production[00:00] AI UX Design Patterns[12:19] Context Management in Chat[19:24] Human Feedback in MLflow[24:37] Prompt Entropy and Optimization[30:55] Evolving MLFlow Personas[36:27] Persona Expansion vs Separation[47:27] Product Ecosystem Design[54:03] PII vs Business Sensitivity[57:51] Wrap up

a16z cofounders Marc Andreessen and Ben Horowitz join a16z general partner Erik Torenberg and Not Boring founder Packy McCormick for a conversation on how the media and information ecosystem has changed over the past decade. The discussion breaks down the shift toward a more open and decentralized speech environment, the rise of writer- and creator-led platforms like Substack, and the erosion of centralized media gatekeepers. Marc and Ben also tie these dynamics to their investing worldview, outlining how supply-driven markets, major technological step changes, and reputation-driven venture platforms shape outcomes in the AI era.Timecodes: 00:00  Introduction00:46  How the media ecosystem is changing4:20  Why a16z invested in Substack6:28  Supply-driven markets and new content creation8:07  Why writers felt trapped by media companies10:09  Databricks and the 10x cloud multiplier13:58  Long-form podcasting proves demand15:40  What the new fund signals about the future16:24  AI as a universal problem solver18:49  Why market sizing is broken20:45  Go-to-market, policy, and platform power22:37  Turning inventors into confident CEOs25:58  Borrowing power to scale faster27:29  Building dreamers, not killing dreams30:46  Reputation as a core competitive advantage35:57  Taking arrows in public38:56  Avoiding big company failure modes40:39  Autonomous teams inside a16z41:54  Venture capital as the last job46:01  Why intangibles matter more than ever48:17  Original thinkers with charisma50:06  Why Zoomers are differentResources: https://www.notboring.co/p/a16z-the-power-brokershttps://www.a16z.news/p/firm-fundFollow Marc Andreessen on X: https://twitter.com/pmarcaFollow Ben Horowitz on X: https://twitter.com/bhorowitzFollow Erik Torenberg on X: https://twitter.com/eriktorenbergFollow Packy McCormick on X: https://twitter.com/packyM Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://twitter.com/eriktorenberg](https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.  Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What does real AI transformation look like when leaders stop chasing prototypes and start demanding outcomes they can actually measure? That question sat at the center of my conversation with Alex Cross, Chief Technology Officer for EMEA at CI&T, alongside Melissa Smith, as we unpacked why so many organizations feel stuck between AI ambition and business reality. There is no shortage of excitement around AI, but there is growing skepticism too, especially from leadership teams who have seen pilots come and go without clear return. This episode focuses on how CI&T is addressing that gap head on. Alex shared how CI&T frames its work as AI-enabled transformation rather than simply layering AI tools onto existing processes. The distinction matters.  Instead of using AI to speed up broken workflows, CI&T reshapes how work gets done so AI becomes part of value creation itself. We explored a standout example from ITAU, the largest bank in Latin America, where deep modernization work helped deliver gains that most executives only ever see in strategy decks.  Productivity rose sharply, digital launch cycles collapsed from years to months, customer satisfaction jumped, and the commercial impact reached hundreds of millions in uplift. These are the kinds of results that change boardroom conversations. A big part of how CI&T gets there is its proprietary Flow platform. Alex explained how Flow gives clients a day-one AI environment, removing the heavy upfront cost and complexity that often slows momentum. Instead of spending months building platforms before any value appears, teams can move from proof of concept to production in as little as six to eight weeks. Flow also plays a second role that many AI programs miss, acting as a measurement layer so performance, efficiency, and ROI are visible rather than assumed. We also talked about why partnerships matter when execution is the goal. CI&T works closely with hyperscalers like AWS and Databricks, combining native tools with its own codified expertise. That combination has helped the company achieve an unusually high success rate in bringing AI initiatives to production, a challenge many organizations still struggle with. For Alex, the difference comes down to a relentless focus on production readiness and collaboration between business and technology teams from day one. Looking ahead, the conversation turned to CI&T's expansion across EMEA and what the company's 30th year represents. Rather than chasing every new trend, the focus is on productizing services around real client problems, whether that is legacy modernization, efficiency, or growth. The goal is to bridge strategy and execution in a way that feels practical, fast, and accountable. If you are leading AI initiatives and wondering why progress feels slower than the hype suggests, this episode offers a grounded perspective from the front lines. So, as organizations head into another year of bold AI plans, the real question becomes this. Are you building faster caterpillars, or are you ready to do the harder work required to turn ambition into something that can truly scale? Useful Links Connect with Alex Cross Connect With Melissa Smith Learn more about CI&T Follow CI&T on LinkedIn and YouTube Thanks to our sponsors, Alcor, for supporting the show.

2026 could be a historic year for the IPO market with over $3.6 trillion in expected valuations hitting the public stage. In this episode, we break down the hottest and most talked-about names in the pipeline: SpaceX, OpenAI, Anthropic, Stripe, Revolut, Canva, Databricks, and TikTok US.We discuss what makes SpaceX such a unique and defensible business, why OpenAI's losses and leadership noise might be red flags, and how Anthropic is quietly building a much more sustainable AI model. Plus, the strategy behind Stripe's long-awaited listing, Revolut's super-app ambitions, Canva's AI monetisation push, and the jaw-dropping TikTok U.S. deal that could become one of the biggest financial giveaways of all time.We also dive into who's really making money here with banks like Morgan Stanley, J.P. Morgan, and Goldman Sachs all fighting for billion-dollar fees.Bullish or bearish, overhyped or undervalued, this is our full take on the biggest IPOs to watch in 2026.(00:00) 2026 IPO Landscape Overview(02:07) SpaceX: Trillion Dollar Debut(11:59) OpenAI: Timing and Challenges(16:02) Anthropic: A Different Approach(21:12) ByteDance and TikTok: The Crony Bonanza(25:31) Databricks: Data Intelligence Platform(28:45) Stripe: Payments Powerhouse(31:26) Revolut: Challenger Bank(33:37) Canva: Design Tool with Potential

Aishwarya Naresh Reganti and Kiriti Badam have helped build and launch more than 50 enterprise AI products across companies like OpenAI, Google, Amazon, and Databricks. Based on these experiences, they've developed a small set of best practices for building and scaling successful AI products. The goal of this conversation is to save you and your team a lot of pain and suffering.We discuss:1. Two key ways AI products differ from traditional software, and why that fundamentally changes how they should be built2. Common patterns and anti-patterns in companies that build strong AI products versus those that struggle3. A framework they developed from real-world experience to iteratively build AI products that create a flywheel of improvement4. Why obsessing about customer trust and reliability is an underrated driver of successful AI products5. Why evals aren't a cure-all, and the most common misconceptions people have about them6. The skills that matter most for builders in the AI era—Brought to you by:Merge—The fastest way to ship 220+ integrations: https://merge.dev/lennyStrella—The AI-powered customer research platform: https://strella.io/lennyBrex—The banking solution for startups: https://www.brex.com/product/business-account?ref_code=bmk_dp_brand1H25_ln_new_fs—Transcript: https://www.lennysnewsletter.com/p/what-openai-and-google-engineers-learned—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/183007822/referenced—Get 15% off Aishwarya and Kiriti's Maven course, Building Agentic AI Applications with a Problem-First Approach, using this link: https://bit.ly/3V5XJFp—Where to find Aishwarya Naresh Reganti:• LinkedIn: https://www.linkedin.com/in/areganti• GitHub: https://github.com/aishwaryanr/awesome-generative-ai-guide• X: https://x.com/aish_reganti—Where to find Kiriti Badam:• LinkedIn: https://www.linkedin.com/in/sai-kiriti-badam• X: https://x.com/kiritibadam—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Aishwarya and Kiriti(05:03) Challenges in AI product development(07:36) Key differences between AI and traditional software(13:19) Building AI products: start small and scale(15:23) The importance of human control in AI systems(22:38) Avoiding prompt injection and jailbreaking(25:18) Patterns for successful AI product development(33:20) The debate on evals and production monitoring(41:27) Codex team's approach to evals and customer feedback(45:41) Continuous calibration, continuous development (CC/CD) framework(58:07) Emerging patterns and calibration(01:01:24) Overhyped and under-hyped AI concepts(01:05:17) The future of AI(01:08:41) Skills and best practices for building AI products(01:14:04) Lightning round and final thoughts—Referenced:• LevelUp Labs: https://levelup-labs.ai/• Why your AI product needs a different development lifecycle: https://www.lennysnewsletter.com/p/why-your-ai-product-needs-a-different• Booking.com: https://www.booking.com• Research paper on agents in production (by Matei Zaharia's lab): https://arxiv.org/pdf/2512.04123• Matei Zaharia's research on Google Scholar: https://scholar.google.com/citations?user=I1EvjZsAAAAJ&hl=en• The coming AI security crisis (and what to do about it) | Sander Schulhoff: https://www.lennysnewsletter.com/p/the-coming-ai-security-crisis• Gajen Kandiah on LinkedIn: https://www.linkedin.com/in/gajenkandiah• Rackspace: https://www.rackspace.com• The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code | Dan Shipper (co-founder/CEO of Every): https://www.lennysnewsletter.com/p/inside-every-dan-shipper• Semantic Diffusion: https://martinfowler.com/bliki/SemanticDiffusion.html• LMArena: https://lmarena.ai• Artificial Analysis: https://artificialanalysis.ai/leaderboards/providers• Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI Codex Product Lead): https://www.lennysnewsletter.com/p/why-humans-are-ais-biggest-bottleneck• Airline held liable for its chatbot giving passenger bad advice—what this means for travellers: https://www.bbc.com/travel/article/20240222-air-canada-chatbot-misinformation-what-travellers-should-know• Demis Hassabis on LinkedIn: https://www.linkedin.com/in/demishassabis• We replaced our sales team with 20 AI agents—here's what happened | Jason Lemkin (SaaStr): https://www.lennysnewsletter.com/p/we-replaced-our-sales-team-with-20-ai-agents• Socrates's quote: https://en.wikipedia.org/wiki/The_unexamined_life_is_not_worth_living• Noah Smith's newsletter: https://www.noahpinion.blog• Silicon Valley on HBO Max: https://www.hbomax.com/shows/silicon-valley/b4583939-e39f-4b5c-822d-5b6cc186172d• Clair Obscur: Expedition 33: https://store.steampowered.com/app/1903340/Clair_Obscur_Expedition_33/• Wisprflow: https://wisprflow.ai• Raycast: https://www.raycast.com• Steve Jobs's quote: https://www.goodreads.com/quotes/463176-you-can-t-connect-the-dots-looking-forward-you-can-only—Recommended books:•  When Breath Becomes Air: https://www.amazon.com/When-Breath-Becomes-Paul-Kalanithi/dp/081298840X• The Three-Body Problem: https://www.amazon.com/Three-Body-Problem-Cixin-Liu/dp/0765382032• A Fire Upon the Deep: https://www.amazon.com/Fire-Upon-Deep-Zones-Thought/dp/0812515285—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

This week, we discuss AI's impact on Stack Overflow, Docker's Hardened Images, and Nvidia buying Groq. Plus, thoughts on playing your own game and having fun. Watch the YouTube Live Recording of Episode (https://www.youtube.com/live/LQSxLbjvz3c?si=ao8f3hwxlCrmH1vX) 554 (https://www.youtube.com/live/LQSxLbjvz3c?si=ao8f3hwxlCrmH1vX) Please complete the Software Defined Talk Listener Survey! (https://docs.google.com/forms/d/e/1FAIpQLSfl7eHWQJwu2tBLa-FjZqHG2nr6p_Z3zQI3Pp1EyNWQ8Fu-SA/viewform?usp=header) Runner-up Titles It's all brisket after that. Exploring Fun Should I go build a snow man? Pets Innersourcing Two books Michael Lewis should write. Article IV is foundational. Freedom is options. Rundown Stack Overflow is dead. (https://x.com/rohanpaul_ai/status/2008007012920209674?s=20) Hardened Images for Everyone (https://www.docker.com/blog/docker-hardened-images-for-every-developer/) Tanzu's Bitnami stuff does this too (https://blogs.vmware.com/tanzu/what-good-software-supply-chain-security-looks-like-for-highly-regulated-industries/). OpenAI OpenAI's New Fundraising Round Could Value Startup at as Much as $830 Billion (https://www.wsj.com/tech/ai/openais-new-fundraising-round-could-value-startup-at-a[…]4238&segment_id=212500&user_id=c5a514ba8b7d9a954711959a6031a3fa) OpenAI Reportedly Planning to Make ChatGPT "Prioritize" Advertisers in Conversation (https://futurism.com/artificial-intelligence/openai-chatgpt-sponsored-ads) OpenAI bets big on audio as Silicon Valley declares war on screens (https://techcrunch.com/2026/01/01/openai-bets-big-on-audio-as-silicon-valley-declares-war-on-screens/) Sam Altman says: He has zero percent interest in remaining OpenAI CEO, once (https://timesofindia.indiatimes.com/technology/tech-news/sam-altman-says-he-has-zero-percent-interest-remaining-openai-ceo-once-/articleshow/126350602.cms) Nvidia buying AI chip startup Groq's assets for about $20 billion in its largest deal on record (https://www.cnbc.com/2025/12/24/nvidia-buying-ai-chip-startup-groq-for-about-20-billion-biggest-deal.html) Relevant to your Interests Broadcom IT uses Tanzu Platform to host MCP Servers (https://news.broadcom.com/app-dev/broadcom-tanzu-platform-agentic-business-transformation). A Brief History Of The Spreadsheet (https://hackaday.com/2025/12/15/a-brief-history-of-the-spreadsheet/) Databricks is raising over $4 billion in Series L funding at a $134 billion (https://x.com/exec_sum/status/2000971604449485132?s=20) Amazon's big AGI reorg decoded by Corey Quinn (https://www.theregister.com/2025/12/17/jassy_taps_peter_desantis_to_run_agi/) “They burned millions but got nothing.” (https://automaton-media.com/en/news/japanese-game-font-services-aggressive-price-hike-could-be-result-of-parent-companys-alleged-ai-failu/) X sues to protect Twitter brand Musk has been trying to kill (https://www.theregister.com/2025/12/17/x_twitter_brand_lawsuit/) Mozilla's new CEO says AI is coming to Firefox, but will remain a choice | TechCrunch (https://techcrunch.com/2025/12/17/mozillas-new-ceo-says-ai-is-coming-to-firefox-but-will-remain-a-choice/) Why Oracle keeps sparking AI-bubble fears (https://www.axios.com/2025/12/18/ai-oracle-stock-blue-owl) What's next for Threads (https://sources.news/p/whats-next-for-threads) Salesforce Executives Say Trust in Large Language Models Has Declined (https://www.theinformation.com/articles/salesforce-executives-say-trust-generative-ai-declined?rc=giqjaz) Akamai Technologies Announces Acquisition of Function-as-a-Service Company Fermyon (https://www.akamai.com/newsroom/press-release/akamai-announces-acquisition-of-function-as-a-service-company-fermyon) Google Rolling Out Gmail Address Change Feature: Here Is How It Works (https://finance.yahoo.com/news/google-rolling-gmail-address-change-033112607.html) The Enshittifinancial Crisis (https://www.wheresyoured.at/the-enshittifinancial-crisis/) MongoBleed: Critical MongoDB Vulnerability CVE-2025-14847 | Wiz Blog (https://www.wiz.io/blog/mongobleed-cve-2025-14847-exploited-in-the-wild-mongodb) Softbank to buy data center firm DigitalBridge for $4 billion in AI push (https://www.cnbc.com/amp/2025/12/29/digitalbridge-shares-jump-on-report-softbank-in-talks-to-acquire-firm.html) The best tech announced at CES 2026 so far (https://www.theverge.com/tech/854159/ces-2026-best-tech-gadgets-smartphones-appliances-robots-tvs-ai-smart-home) Who's who at X, the deepfake porn site formerly known as Twitter (https://www.ft.com/content/ad94db4c-95a0-4c65-bd8d-3b43e1251091?accessToken=zwAGR7kzep9gkdOtlNtMlaBMZdO9jTtD4SUQkQ.MEYCIQCdZajuC9uga-d9b5Z1t0HI2BIcnkVoq98loextLRpCTgIhAPL3rW72aTHBNL_lS7s1ONpM2vBgNlBNHDBeGbHkPkZj&sharetype=gift&token=a7473827-0799-4064-9008-bf22b3c99711) Manus Joins Meta for Next Era of Innovation (https://manus.im/blog/manus-joins-meta-for-next-era-of-innovation) The WELL: State of the World 2026 with Bruce Sterling and Jon Lebkowsky (https://people.well.com/conf/inkwell.vue/topics/561/State-of-the-World-2026-with-Bru-page01.html) Virtual machines still run the world (https://cote.io/2026/01/07/virtual-machines-still-run-the.html) Databases in 2025: A Year in Review (https://www.cs.cmu.edu/~pavlo/blog/2026/01/2025-databases-retrospective.html) Chat Platform Discord Files Confidentially for IPO (https://www.bloomberg.com/news/articles/2026-01-06/chat-platform-discord-is-said-to-file-confidentially-for-ipo?embedded-checkout=true) The DRAM shortage explained: AI, rising prices, and what's next (https://www.techradar.com/pro/why-is-ram-so-expensive-right-now-its-more-complicated-than-you-think) Nonsense Palantir CEO buys monastery in Old Snowmass for $120 million (https://www.denverpost.com/2025/12/17/palantir-alex-karp-snowmass-monastery/amp/) H-E-B gives free groceries to all customers after registers glitch today in Burleson, Texas. (https://www.reddit.com/r/interestingasfuck/s/ZEcblg7atP) Conferences cfgmgmtcamp 2026 (https://cfgmgmtcamp.org/ghent2026/), February 2nd to 4th, Ghent, BE. Coté speaking - anyone interested in being a SDI guest? DevOpsDayLA at SCALE23x (https://www.socallinuxexpo.org/scale/23x), March 6th, Pasadena, CA Use code: DEVOP for 50% off. Devnexus 2026 (https://devnexus.com), March 4th to 6th, Atlanta, GA. Coté has a discount code, but he's not sure if he can give it out. He's asking! Send him a DM in the meantime. KubeCon EU, March 23rd to 26th, 2026 - Coté will be there on a media pass. Whole bunch of VMUGs, mostly in the US. The CFPs are open (https://app.sessionboard.com/submit/vmug-call-for-content-2026/ae1c7013-8b85-427c-9c21-7d35f8701bbe?utm_campaign=5766542-VMUG%20Voice&utm_medium=email&_hsenc=p2ANqtz-_YREN7dr6p3KSQPYkFSN5K85A-pIVYZ03ZhKZOV0O3t3h0XHdDHethhx5O8gBFguyT5mZ3n3q-ZnPKvjllFXYfWV3thg&_hsmi=393690000&utm_content=393685389&utm_source=hs_email), go speak at them! Coté speaking in Amsterdam. Amsterdam (March 17-19, 2026), Minneapolis (April 7-9, 2026), Toronto (May 12-14, 2026), Dallas (June 9-11, 2026), Orlando (October 20-22, 2026) SDT News & Community Join our Slack community (https://softwaredefinedtalk.slack.com/join/shared_invite/zt-1hn55iv5d-UTfN7mVX1D9D5ExRt3ZJYQ#/shared-invite/email) Email the show: questions@softwaredefinedtalk.com (mailto:questions@softwaredefinedtalk.com) Free stickers: Email your address to stickers@softwaredefinedtalk.com (mailto:stickers@softwaredefinedtalk.com) Follow us on social media: Twitter (https://twitter.com/softwaredeftalk), Threads (https://www.threads.net/@softwaredefinedtalk), Mastodon (https://hachyderm.io/@softwaredefinedtalk), LinkedIn (https://www.linkedin.com/company/software-defined-talk/), BlueSky (https://bsky.app/profile/softwaredefinedtalk.com) Watch us on: Twitch (https://www.twitch.tv/sdtpodcast), YouTube (https://www.youtube.com/channel/UCi3OJPV6h9tp-hbsGBLGsDQ/featured), Instagram (https://www.instagram.com/softwaredefinedtalk/), TikTok (https://www.tiktok.com/@softwaredefinedtalk) Book offer: Use code SDT for $20 off "Digital WTF" by Coté (https://leanpub.com/digitalwtf/c/sdt) Sponsor the show (https://www.softwaredefinedtalk.com/ads): ads@softwaredefinedtalk.com (mailto:ads@softwaredefinedtalk.com) Recommendations Brandon: Why Data Doesn't Always Win, with a Philosopher of Art (https://podcasts.apple.com/us/podcast/the-points-you-shouldnt-score-a-new-years-resolution/id1685093486?i=1000743950053) (Apple Podcasts) Why Data Doesn't Always Win, with a Philosopher of Art (https://www.youtube.com/watch?v=7AdbePyGS2M&list=RD7AdbePyGS2M&start_radio=1) (YouTube) Coté: “Databases in 2025: A Year in Review.” (https://www.cs.cmu.edu/~pavlo/blog/2026/01/2025-databases-retrospective.html) Photo Credits Header (https://unsplash.com/photos/red-and-black-love-neon-light-signage-igJrA98cf4A)

Send us a textInvest in pre-IPO stocks with AG Dillon & Co. Contact aaron.dillon@agdillon.com to learn more. Financial advisors only. www.agdillon.com00:00 - Intro00:08 - xAI Lands a Massive $20B Round, $230B Valuation01:22 - xAI Financials Show Hypergrowth Economics With Losses Still Expanding02:51 - Grok for Business Targets Enterprise Wallet Share With Security and Admin Controls04:05 - Anthropic Signs Up a $10B Round, $350B Valuation05:07 - OpenAI Targets a $100B Raise, $830B Valuation05:51 - OpenAI Pushes Deeper Into Healthcare With ChatGPT Health06:45 - OpenAI's New $50B Stock Compensation Program07:45 - Lambda Lines Up a Pre-IPO Raise, IPO in Next 12 Months08:43 - Databricks Raises Over $4B, $134B Valuation09:30 - Figure's Adcock Launches New AI Lab, Hark, With $100M Personal Capital 10:05 - Lovable Raises $330M, $6.6B Valuation, 267% Step-Up in Five Months10:58 - OpenEvidence Targets a $12B Valuation on 150M Annualized Ad Revenue and 90 Percent Gross Margins12:04 - Waymo Explores a $15B Raise With Valuation Talks at $100B12:48 - Rain Raises $250M at a $1.95B Valuation to Expand Stablecoin Cards Across 150 Countries13:26 - ServiceNow Buys Armis for $7.75B Cash After a Fresh $6.1B Pre-IPO Mark14:05 - Cursor Acquires Graphite and Reinforces a $38.5B Secondary Mark14:56 - Plaud Expands Hardware Line With a $179 NotePin S Ahead of CES 202615:51 - Mobileye Buys Mentee Robotics for $900M and Expands the Physical AI Playbook16:42 - LMArena Reprices to $1.7B and Hits $30M Annualized Consumption in Under Four Months17:22 - Swap Commerce Raises $100M Six Months After Its $40M Series B17:51 - Discord Files Confidentially for IPO With Secondaries Pricing at $7B to $8B18:25 - Commonwealth Fusion Systems Builds a Digital Twin and Targets 19-Magnet Completion This Summer

Today we're breaking down Databricks, a $130B private company that helps companies collect, store, and process very large amounts of data, and then use that data to run analytics and train machine learning models. Databricks sits in the middle of modern data systems, connecting raw data pipelines to the tools teams use to analyze information and build AI. If you've worked on large-scale data or AI projects, there's a good chance Databricks was part of the stack, often operating behind the scenes. My guest is Alan Tu, portfolio manager and analyst at WCM Investment Management, which invested in Databricks in late 2024. Alan explains what Databricks actually does for customers, why it remains one of the least understood large private software companies, and how its academic origins and founding team shaped its evolution from an early data-engineering product into a broad commercial platform. We also discuss common misconceptions about the business, how Databricks fits into the modern AI stack, what has changed since the last time we covered the company, and how its scale, product strategy, and capital position differentiate it from competitors. Note: This conversation was recorded on December 10, 2025, so all numbers are reflective of what was publicly available on that date. Please enjoy this breakdown of Databricks. For the full show notes, transcript, and links to the best content to learn more, check out the episode page⁠⁠⁠⁠⁠⁠⁠ here.⁠⁠⁠⁠⁠⁠⁠ —- This episode is brought to you by⁠⁠⁠⁠ ⁠Portrait Analytics⁠⁠⁠⁠⁠ - your centralized resource for AI-powered idea generation, thesis monitoring, and personalized report building. Built by buy-side investors, for investment professionals. We work in the background, helping surface stock ideas and thesis signposts to help you monetize every insight. In short, we help you understand the story behind the stock chart, and get to "go, or no-go" 10x faster than before. Sign-up for a free trial today at⁠⁠⁠⁠ ⁠portraitresearch.com⁠⁠⁠⁠⁠ — Business Breakdowns is a property of Colossus, LLC. For more episodes of Business Breakdowns, visit⁠⁠⁠⁠⁠⁠⁠ joincolossus.com/episodes⁠⁠⁠⁠⁠⁠⁠. Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠). Timestamps  (00:00:00) Welcome to Business Breakdowns (00:02:34) Introducing Databricks and Guest Alan Tu (00:03:22) Understanding Databricks' Core Functionality (00:09:15) The Founding Story of Databricks (00:23:54) Databricks' Evolution and Product Expansion (00:30:06) Databricks vs. Snowflake: Market Competition (00:35:36) Databricks' Strategic Vision and Market Impact (00:38:14) The Rise of Big Data and Databricks' Core Value (00:39:27) Understanding Databricks Through a Credit Card Fraud Use Case (00:44:35) Databricks' Role in AI and Machine Learning (00:51:12) The Competitive Landscape and Cloud Partnerships (00:54:54) Financial Dynamics and Pricing Strategies (01:09:37) The Future of Databricks: Risks and Long-Term Vision (01:12:54) Conclusion and Final Thoughts

The 2026 IPO market is heating up: John Jannarone and Evan Schlossman break down what to expect. John anticipates debuts from Kraken and OpenAI, while Evan is also watching Canva. Other expected names are Anthropic, Databricks, Huntress, SpaceX, and more tech companies. “We're seeing a huge amount of enthusiasm from investors,” Evan says. John notes capital raises from names like Anthropic, saying private markets are “red hot,” so retail investors need caution if these companies are continuing to look for funding. ======== 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

Welcome to episode 335 of The Cloud Pod, where the forecast is always cloudy! Welcome to the first show of 2026, and it's a full house, too! Justin, Jonathan, Ryan,  and Matt are all here to reflect on 2025, plus bring you their predictions for 2026. Let's get started!  Titles we almost went with this week SQL Me Maybe: AlloyDB Gets Chatty With Your Database **OpenAI SELECT * FROM natural_language WHERE accuracy LIKE ‘100%’ **Anthropic etcd You Were Worried About Database Limits: CloudWatch Has Your Back CSV You Later: Looker Adds Drag-and-Drop Data Uploads AWS Spots an Opportunity to Manage Your Container Costs EKS Network Policies: No More IP Address Whack-a-Mole AWS Security Hub Splits: It’s Not You, It’s CSPM Spot On: ECS Finally Manages Your Cheapest Compute TOON Squad: DigitalOcean’s New Format Makes JSON Look Bloated The Price is Wrong: AWS Breaks Two Decades of Downward Pricing Tradition Show Your Work: Why AI-Generated Code Without Tests is Just Expensive Spam No More Agent Orange: Google Simplifies VM Extension Deployment AWS Discovers Prices Can Go Both Ways, Raises GPU Costs 15 Percent Sovereignty Washing: When Your European Cloud Still Answers to Uncle Sam Agent Builder Gets a Memory Upgrade: Google’s AI Finally Remembers Where It Put Its Keys Ctrl+F for the Future: A year-end Scorecard & Next-Gen Bets AI Agents, GPU Prices, and The best of the Cloud Pod 2025 Beyond the Hype: The Cloud Pods Definitive 2025 Year in Review Apocalypse Now… What? Our 2026 Forecast Follow Up  01:27 RYAN’S PREDICTIONS Prediction Status Notes Quick LLM models for individuals ACCURATE Meta-Llama-3.1-8B-Instruct, GLM-4-9B-0414, and Qwen2.5-VL-7B-Instruct—each chosen for an outstanding balance of performance and computational efficiency, making them ideal for edge AI deployment. A new AI inference application called Inferencer allows even modest Apple Mac computers to run the largest open-source LLMs. AI at the edge natively (Lambda-esque) ACCURATE Akamai launched a new Inference Cloud product for edge AI using Nvidia’s Blackwell 6000 GPUs in 17 cities. AWS IoT Greengrass with Lambda functions for edge logic. “Edge AI allows for instant decision-making where it matters most—close to the data source.” Cloud native security mesh multi-cloud UNCLEAR Service mesh technologies continue to evolve (Istio, Linkerd), but I didn’t find a breakthrough “app-to-app at the edge” security mesh product announcement in 2025. This one needs more specific evidence. Ryan Score: 2/3 02:25 MATTHEW’S PREDICTIONS Prediction Status Notes FOCUS adopted by Snowflake or Databricks ACCURATE FOCUS version 1.2 was ratified on May 29, 2025. Three new providers announced support: Alibaba Cloud, Databricks, and Grafana. Databricks officially adopted FOCUS! AI security/ethical standard (SOC or ISO) ACCURATE ISO 42001 is the first international standard outlining requirements for AI governance. Major companies achieving certification in 2025: Automation Anywhere is among the first 100 companies worldwide to earn ISO/IEC 42001:2023 certification. Anthropic also achieved ISO 42001 certification. Amazon deprecates 5+ services (WorkMail bonus) ACCURATE (no bonus) 19 services are mothballed, four are being sunset, and one is end of its supported life. Deprecated services include CodeCommit, Cloud9, S3 Select, CloudSearch, SimpleDB, Forecast, Data Pipeline, QLDB, Snowball Edge, and more. WorkMail NOT deprecated – WorkDocs was (April 2025), but WorkMail remains active. Matthew Score: 3/3 03:22 JONATHAN’S PREDICTIONS Prediction Status Notes Company claims AGI achieved ACC

Nik and Michael discuss the events and trends they thought were most important in the Postgres ecosystem in 2025. Here are some links to things they mentioned: Postgres 18 release notes https://www.postgresql.org/docs/18/release-18.htmlOur episode on Postgres 18 https://postgres.fm/episodes/postgres-18LWLock:LockManager benchmarks for Postgres 18 (blog post by Nik) https://postgres.ai/blog/20251009-postgres-marathon-2-005PostgreSQL bug tied to zero-day attack on US Treasury https://www.theregister.com/2025/02/14/postgresql_bug_treasuryPgDog episode https://postgres.fm/episodes/pgdogMultigres episode https://postgres.fm/episodes/multigresNeki announcement https://planetscale.com/blog/announcing-nekiOur 100TB episode from 2024 https://postgres.fm/episodes/to-100tb-and-beyondPlanetScale for Postgres https://planetscale.com/blog/planetscale-for-postgresOracle's MySQL job cuts https://www.theregister.com/2025/09/11/oracle_slammed_for_mysql_jobAmazon Aurora DSQL is now generally available https://aws.amazon.com/about-aws/whats-new/2025/05/amazon-aurora-dsql-generally-availableAnnouncing Azure HorizonDB https://techcommunity.microsoft.com/blog/adforpostgresql/announcing-azure-horizondb/4469710Lessons from Replit and Tiger Data on Storage for Agentic Experimentation https://www.tigerdata.com/blog/lessons-replit-tiger-data-storage-agentic-experimentationInstant database clones with PostgreSQL 18 https://boringsql.com/posts/instant-database-clonesturbopuffer episode https://postgres.fm/episodes/turbopufferCrunchy joins Snowflake https://www.crunchydata.com/blog/crunchy-data-joins-snowflakeNeon joins Databricks https://neon.com/blog/neon-and-databricks~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

Jason Lemkin is the founder of SaaStr, the world's largest community for software founders, and a veteran SaaS investor who has deployed over $200 million into B2B startups. After his last salesperson quit, Jason made a radical decision: replace his entire go-to-market team with AI agents. What started as an experiment has transformed into a new operating model, where 20 AI agents managed by just 1.2 humans now do the work previously handled by a team of 10 SDRs and AEs. In this conversation, Jason shares his hands-on experience implementing AI to run his sales org, including what works, what doesn't, and how the GTM landscape is quickly being transformed.We discuss:1. How AI is fundamentally changing the sales function2. Why most SDRs and BDRs will be “extinct” within a year3. What Jason is observing across his portfolio about AI adoption in GTM4. How to become “hyper-employable” in the age of AI5. The specific AI tools and tactics he's using that have been working best6. Practical frameworks for integrating AI into your sales motion without losing what works7. Jason's 2026 predictions on where SaaS and GTM are heading next—Brought to you by:DX—The developer intelligence platform designed by leading researchersVercel—Your collaborative AI assistant to design, iterate, and scale full-stack applications for the webDatadog—Now home to Eppo, the leading experimentation and feature flagging platform—Transcript: https://www.lennysnewsletter.com/p/we-replaced-our-sales-team-with-20-ai-agents—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/182902716/my-biggest-takeaways-from-this-conversation—Where to find Jason Lemkin:• X: https://x.com/jasonlk• LinkedIn: https://www.linkedin.com/in/jasonmlemkin• Website: https://www.saastr.com• Substack: https://substack.com/@cloud—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Jason Lemkin(04:36) What SaaStr does(07:13) AI's impact on sales teams(10:11) How SaaStr's AI agents work and their performance(14:18) How go-to-market is changing in the AI era(19:19) The future of SDRs, BDRs, and AEs in sales(22:03) Why leadership roles are safe(23:43) How to be in the 20% who thrive in the AI sales future(28:40) Why you shouldn't build your own AI tools(30:10) Specific AI agents and their applications(36:40) Challenges and learnings in AI deployment(42:11) Making AI-generated emails good (not just acceptable)(47:31) When humans still beat AI in sales(52:39) An overview of SaaStr's org(53:50) The role of human oversight in AI operations(58:37) Advice for salespeople and founders in the AI era(01:05:40) Forward-deployed engineers(01:08:08) What's changing and what's staying the same in sales(01:16:21) Why AI is creating more work, not less(01:19:32) Why Jason says these are magical times(01:25:25) The "incognito mode test" for finding AI opportunities(01:27:19) The impact of AI on jobs(01:30:18) Lightning round and final thoughts—Referenced:• Building a world-class sales org | Jason Lemkin (SaaStr): https://www.lennysnewsletter.com/p/building-a-world-class-sales-org• SaaStr Annual: https://www.saastrannual.com• Delphi: https://www.delphi.ai/saastr/talk• Amelia Lerutte on LinkedIn: https://www.linkedin.com/in/amelialerutte/• Vercel: https://vercel.com• What world-class GTM looks like in 2026 | Jeanne DeWitt Grosser (Vercel, Stripe, Google): https://www.lennysnewsletter.com/p/what-the-best-gtm-teams-do-differently• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Replit: https://replit.com• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• ElevenLabs: https://elevenlabs.io• The exact AI playbook (using MCPs, custom GPTs, Granola) that saved ElevenLabs $100k+ and helps them ship daily | Luke Harries (Head of Growth): https://www.lennysnewsletter.com/p/the-ai-marketing-stack• Bolt: https://bolt.new• Lovable: https://lovable.dev• Harvey: https://www.harvey.ai• Samsara: https://www.samsara.com/products/platform/ai-samsara-intelligence• UiPath: https://www.uipath.com• Denise Dresser on LinkedIn: https://www.linkedin.com/in/denisedresser• Agentforce: https://www.salesforce.com/form/agentforce• SaaStr's AI Agent Playbook: https://saastr.ai/agents• Brian Halligan on LinkedIn: https://www.linkedin.com/in/brianhalligan• Brian Halligan's AI: https://www.delphi.ai/minds/bhalligan• Sierra: https://sierra.ai• Fin: https://fin.ai• Deccan: https://www.deccan.ai• Artisan: https://www.artisan.co• Qualified: https://www.qualified.com• Claude: https://claude.ai• HubSpot: https://www.hubspot.com• Gamma: https://gamma.app• Sam Blond on LinkedIn: https://www.linkedin.com/in/sam-blond-791026b• Brex: https://www.brex.com• Outreach: https://www.outreach.io• Gong: https://www.gong.io• Salesloft: https://www.salesloft.com• Mixmax: https://www.mixmax.com• “Sell the alpha, not the feature”: The enterprise sales playbook for $1M to $10M ARR | Jen Abel: https://www.lennysnewsletter.com/p/the-enterprise-sales-playbook-1m-to-10m-arr• Clay: https://www.clay.com• Owner: https://www.owner.com• Momentum: https://www.momentum.io• Attention: https://www.attention.com• Granola: https://www.granola.ai• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/behind-the-founder-marc-benioff• Palantir: https://www.palantir.com• Databricks: https://www.databricks.com• Garry Tan on LinkedIn: https://www.linkedin.com/in/garrytan• Rippling: https://www.rippling.com• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• The new AI growth playbook for 2026: How Lovable hit $200M ARR in one year | Elena Verna (Head of Growth): https://www.lennysnewsletter.com/p/the-new-ai-growth-playbook-for-2026-elena-verna• Pluribus on AppleTV+: https://tv.apple.com/us/show/pluribus/umc.cmc.37axgovs2yozlyh3c2cmwzlza• Sora: https://openai.com/sora• Reve: https://app.reve.com• Everything That Breaks on the Way to $1B ARR, with Mailchimp Co-Founder Ben Chestnut: https://www.saastr.com/everything-that-breaks-on-the-way-to-1b-arr-with-mailchimp-co-founder-ben-chestnut/• The Revenue Playbook: Rippling's Top 3 Growth Tactics at Scale, with Rippling CRO Matt Plank: https://www.youtube.com/watch?v=h3eYtzBpjRw• 10 contrarian leadership truths every leader needs to hear | Matt MacInnis (Rippling): https://www.lennysnewsletter.com/p/10-contrarian-leadership-truths—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Manvir Sandhu is the Founder and Chief Innovation Officer at Zennify, a Salesforce consulting firm that helps financial services organizations drive digital transformation across platforms like Salesforce, Databricks, and AI. Under his leadership, Zennify has become a trusted advisor to CIOs and C-suite executives, earned Platinum-level Salesforce partner status and scaled to over 150 employees, serving clients ranging from regional banks to large enterprises.  Known for leading innovative initiatives, Manvir helped spearhead a vaccine supply chain solution in Haiti with UNICEF and the Clinton Foundation, which was presented at Salesforce Dreamforce. He brings a strong focus on AI, agile transformation, and change management to regulated industries. In this episode… Digital transformation is reshaping entire industries, yet organizations in highly regulated sectors often struggle to choose the right tools and execute change effectively. As AI, data platforms, and compliance requirements evolve at breakneck speed, innovation can stall under the weight of risk and resistance. How are today's leaders pushing past these barriers to create secure, lasting transformation? For Manvir Sandhu, a digital transformation and AI innovation leader, lasting impact comes from pairing deep industry understanding with a practical, iterative mindset. He traces this philosophy back to his early work in healthcare, where his team reimagined post-disaster vaccine management in Haiti by combining Salesforce and IoT to enable real-time tracking and alerts — an approach that later became a model for broader adoption. Building on those lessons, Manvir pivoted to financial services, using focused proof-of-concept projects to earn trust, modernize legacy systems, and deliver a true 360-degree customer view. His experience demonstrates how thoughtfully applied AI can move far beyond basic automation to drive meaningful operational and customer impact. In this episode of the Inspired Insider Podcast, Dr. Jeremy Weisz sits down with Manvir Sandhu, Founder and Chief Innovation Officer of Zennify, to explore data-driven transformation in highly regulated industries. They discuss proof-of-concept strategies, agile change management, and practical AI use cases across healthcare and financial services. Manvir also shares insights on empowering early adopters, navigating growth, and maintaining culture through leadership transitions.

Citadel fortified by $4B at $134B Databricks citadel withstands data complexity sieges. Unity Compute allocates resources elastically enterprise-wide. Citadel becomes industry fortress.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Triumphal $4B triumph values Databricks $134B triumph over siloed architectures. Delta Sharing marketplaces monetize datasets securely. Data mesh advocates convert en masse.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On this episode of The Six Five Pod, hosts Patrick Moorhead and Daniel Newman discuss the latest tech news stories that made headlines. This week's handpicked topics include: THE DECODE Big Funding Headline: OpenAI's reported mega-round and valuation https://www.reuters.com/technology/openai-discussed-raising-tens-billions-valuation-about-750-billion-information-2025-12-18/ https://x.com/danielnewmanUV/status/2001366643436315110  https://x.com/danielnewmanUV/status/2001362761247527174  https://x.com/PatrickMoorhead/status/2001267663490646200 https://techcrunch.com/2025/12/17/amazon-reportedly-in-talks-to-invest-10b-in-openai-as-circular-deals-stay-popular/  AWS "Circular deal" / Corporate venture logic AI build-out constraints https://www.theverge.com/news/846696/electricity-cost-ai-data-center-democrat-investigation https://www.axios.com/2025/12/17/democrats-data-centers-ai-fight  https://www.politico.com/news/2025/12/12/arizona-city-rejects-data-center-after-ai-lobbying-push-00688543 Marvell Industry Analyst Day highlights https://x.com/MoorInsStrat/status/2000359388264161710  Government "Tech Force" for AI Talent https://www.cnn.com/2025/12/15/tech/government-tech-force-ai  Google works to erode Nvidia's software moat (TPU + PyTorch + Meta) https://www.reuters.com/business/google-works-erode-nvidias-software-advantage-with-metas-help-2025-12-17/ Judge rules Tesla engaged in deceptive marketing for Autopilot and full self-driving features https://techcrunch.com/2025/12/16/tesla-engaged-in-deceptive-marketing-for-autopilot-and-full-self-driving-judge-rules/ Tesla tests autonomous vehicles without safety drivers in Austin, Tx https://techcrunch.com/2025/12/15/tesla-starts-testing-robotaxis-in-austin-with-no-safety-driver/  Adobe Firefly now supports prompt-based video editing, adds more third-party models https://techcrunch.com/2025/12/16/adobe-firefly-now-supports-prompt-based-video-editing-adds-more-third-party-models/ https://youtu.be/SjtULo8qs88?si=quE7pEptW8xph1OI  Google's Opal for vibe coding comes to Gemini https://techcrunch.com/2025/12/17/googles-vibe-coding-tool-opal-comes-to-gemini/ THE FLIP OpenAI - Tulip Bubble and Canary in the Coal mine or The Real AI Deal? https://x.com/danielnewmanuv/status/2001487733823541634?s=46&t=8QBZggR299yC4bcbbox-Xg https://x.com/danielnewmanuv/status/2001366643436315110?s=46&t=8QBZggR299yC4bcbbox-Xg BULLS & BEARS AI infrastructure stocks tumble on debt fears: Oracle, Broadcom, CoreWeave selloff https://www.cnbc.com/2025/12/16/cnbc-daily-open-ai-infrastructure-stocks-are-taking-a-beating.html  Recent Fed rate cut & speculation of another coming soon: https://x.com/danielnewmanUV/status/2001041850669404473 Oracle earnings (Q2) — CapEx reality check https://www.forbes.com/sites/greatspeculations/2025/12/18/whats-happening-with-oracle-stock/ https://finance.yahoo.com/news/oracle-plunges-12-despite-earnings-145626357.html Micron crushes earnings as AI data center demand tightens memory supply https://finance.yahoo.com/news/why-wall-street-expects-micron-183836008.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAKf8aUugkk7hJbCnmiZWS2q5x1WWjD07AUywz6vzxnw6btX2iK0-aNmQBgg3sU67GWZXIKHz74cGnjnzZYeuBDv1A8_Rwp67iIKAtMI1A94LhJTRlcqdnN2_QYPWB_5ZTkO96ZSpFMjMsAwDUBf1yz-RIQnA-78Yk-zhD6VFqr- https://x.com/danielnewmanuv/status/2001404328997712349?s=46&t=8QBZggR299yC4bcbbox-Xg Broadcom earnings (Q4) — custom silicon tension https://finance.yahoo.com/news/broadcom-q4-earnings-beat-estimates-154300300.html Databricks raises $4B at $134B valuation as its AI business heats up https://techcrunch.com/2025/12/16/databricks-raises-4b-at-134b-valuation-as-its-ai-business-heats-up/ Smartphone Prices Set to Jump 6.9% as AI Data Centers Devour Memory Chips: The shortage of DRAM chips used in both AI servers and smartphones could threaten to cut smartphone shipments by 2.1%. To cope, some manufacturers may downgrade cameras, displays, and audio or reuse older components. https://www.cnbc.com/2025/12/16/smartphone-prices-to-rise-in-2026-due-to-ai-fueled-chip-shortage.html  Adobe Earnings https://finance.yahoo.com/news/adobe-q4-earnings-beat-estimates-145000488.html Synopsys Earnings https://finance.yahoo.com/news/synopsys-q4-earnings-surpass-estimates-153300031.html  

Conquest complete: $4B conquers $134B Databricks conquest. Conquered continents. Conquest crowned.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Vortex $4B vortices $134B Databricks vortex. Vortex velocity peaks. Vortex victorious.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Skyrocketing $4B at $134B for Databricks' Photon ML acceleration. Ad tech personalizes at billions RPM. Valuation mirrors AI infrastructure boom.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Databricks leaps to $134B on $4B, with Lakeflow automating data pipelines end-to-end. Generative apps proliferate via serverless model serving. Revenue multiples justify hyperscale ambitions.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Die Woche der Mega-Funding-Runden: Databricks wird mit 134 Milliarden bewertet, Waymo peilt 100 Milliarden an, und OpenAI soll bald 830 Milliarden wert sein. Amazon will 10 Milliarden in OpenAI investieren. Coinbase launcht Prediction Markets und tokenisierte Aktien. Revolut plant 3,5 Milliarden Profit bei 40% Marge – profitabler als die meisten Banken. Lovable aus Schweden rast auf 6,6 Milliarden. Das US-Handelsministerium droht der EU mit Vergeltung wegen Tech-Regulierung und nennt explizit SAP, Siemens und DHL. Der TikTok-Deal soll im Januar kommen – Oracle, Silver Lake und Abu Dhabi übernehmen 45%. Ein Andreessen-Startup baut synthetische KI-Influencer mit Phone Farms. Instacart steht wegen KI-Preismanipulation unter FTC-Beschuss. Yann LeCun gründet Ami Labs mit 500 Millionen Seed. Trade Republic wird mit 12,5 Milliarden bewertet. Trump Media fusioniert mit einer Fusionsenergie-Firma. Wann kommt es zur großen Doppelgänger Cola Blindverkostung? Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Intro (00:00:49) Coinbase: Aktien & Prediction Markets (00:08:14) Databricks 134 Mrd. Bewertung (00:13:39) Revolut: 40% Profitmarge (00:19:26) Waymo 100 Mrd. Bewertung (00:36:15) Oscars wechseln zu YouTube (00:37:22) Sam Altman: KI wie Zahnpasta? (00:46:16) Lovable 6,6 Mrd. Bewertung (00:49:53) Amazon investiert 10 Mrd. in OpenAI (00:53:48) OpenAI 830 Mrd. Bewertung (00:56:55) Trump bedroht EU wegen Tech-Regulierung (01:00:56) Andreessen-Startup baut Fake-Influencer (01:08:13) Instacart KI-Preismanipulation (01:12:25) Yann LeCun gründet Ami Labs (01:14:50) TikTok-Deal im Januar (01:18:47) Trump Media fusioniert mit Fusionsfirma (01:24:14) Trade Republic 12,5 Mrd. Shownotes Coinbase Prognosemärkte Aktienhandel Stablecoins - cnbc.com Databricks sammelt Kapital bei 134-Milliarden-Bewertung - wsj.com Revolut strebt 2026 $9B Umsatz und $3.5B Gewinn an. - connectingthedotsinfin.tech Waymo plant Finanzierung bei 100-Milliarden-Bewertung - bloomberg.com Oscars wechseln 2029 von ABC zu YouTube - hollywoodreporter.com OpenAI ChatGPT verbessert Bilderstellung - bloomberg.com OpenAI-Gespräche: 10 Milliarden von Amazon für KI-Chips - theinformation.com OpenAI neue Finanzierungsrunde könnte Startup mit bis zu 83 Milliarden bewerten - wsj.com Start-up Lovable sammelt 330 Millionen ein - nytimes.com EU-Strafen für US-Tech-Unternehmen - nytimes.com Hack enthüllt a16z-unterstützte Telefonfarm, die TikTok mit KI-Influencern flutet - 404media.co FTC untersucht Instacarts KI-Preistool - reuters.com Instacart FTC Vergleich Täuschende Abrechnung - cnbc.com Seb Johnson auf X: "Metas ehemaliger Chief AI Officer sammelt €500 Mio. ein. - x.com TikTok schließt Verkauf seiner US-Einheit nach jahrelanger Saga ab. - axios.com Trump Media - ft.com Es wird kein Armut geben, universelles hohes Einkommen. - x.com Trade Republic: Zwei reiche europäische Familien beteiligen sich am Milliardendeal - manager-magazin.de Phishing-Versuch bei Outfittery: Datenleck beim Bekleidungshändler? - heise.de

En la última tertulia del año traemos Carles Reina (ElevenLabs) como responsable de go-to-market y, además, como inversor: comenta que ha hecho decenas de “tickets” y que acaba de levantar su propio fondo, Baobab Ventures.A partir de ahí, la conversación entra fuerte en el negocio de ElevenLabs: explican que construyen modelos de voz “naturales” y operan en ~70 idiomas, y que encima han montado productos de agentes, doblaje, transcripción, etc. Carles da cifras muy concretas de tracción (alrededor de 400 personas y más de 300M de facturación, alcanzados “hace unas semanas”) y describe un motor enterprise muy agresivo (hablan de 150–170 contratos al mes y de un día especialmente “loco” superando 14M en enterprise). También hablan de por qué siguen levantando rondas aun generando caja: señal al mercado, liquidez para empleados vía secundario, y capacidad de invertir/comprar (incluidas GPUs). En ese bloque bromean bastante con los múltiplos (el “33x” como estándar) y con la posible burbuja en el sector. Luego hablan del tema más “cultural” y polémico: el doblaje y los derechos de voz. Sale Masumi un actor de doblaje conocido en España (que es la voz de Harry Potter y Anakin, y su vínculo con el sindicato) y se discute la línea roja de “no entrenar modelos con nuestras voces” frente a usos consentidos. Carles cuenta casos prácticos en Hollywood donde actores ceden permiso para usar su propia voz en postproducción cuando no pueden grabar, y aparece la idea que vertebra todo el debate: poder ver una peli con “la misma voz del actor” en otro idioma (por ejemplo, el ideal de oír a la misma actriz hablando en catalán o castellano sin perder identidad), frente a la realidad del consumo en España (acostumbrados al doblaje) y la alternativa de VO con subtítulos. En “actualidad/noticias”, el bloque más largo gira alrededor de una supuesta ola de consolidación en streaming y medios: comentan una operación de Netflix con Warner (centrada en activos digitales tipo HBO/HBO Max) y, como contrapeso, una oferta de Paramount por “todo” (y el lío político/regulatorio alrededor del antitrust). Ahí meten nombres y contexto político: hablan de Donald Trump opinando públicamente, de la familia Ellison (Oracle) detrás de Paramount, de tensiones por contenidos/editoriales, y de cómo eso mueve preferencias y narrativas; incluso lo cruzan con TikTok como parte del “ruido” de esos días. A nivel de análisis, lo conectan con el choque entre “calidad premium” (HBO/Warner) y “volumen/variedad algorítmica” (Netflix/TikTok) y con el riesgo de que la consolidación reduzca competencia y, por tanto, incentive menos calidad. También mencionan otras “noticias” tech/IA del momento dentro de la tertulia: preguntan por un anuncio de OpenAI con Disney y si cambia algo en la relación (Carles dice que no), y en otro punto comentan como titular que Amazon “por fin” habría invertido fuerte en OpenAI y lo enlazan con la guerra de infraestructura (chips/TPUs vs Nvidia y el rol del cloud). Por último, se abre el foco a inversión y mercado: cuentan que ElevenLabs tiene un “venture” y que invierten desde balance, y aparecen conversaciones típicas de ciclo: comparan múltiplos (Databricks vs Snowflake), especulan con una posible “edad dorada” de salidas a bolsa y, ya en tono de anécdota, comentan que “hoy” alguien anunció una ronda de 200M a 6B (sin entrar demasiado en detalles, pero usándolo como termómetro del hype). Sigue a los "tertulianos" en Twitter:• Bernat Farrero: @bernatfarrero• Jordi Romero: @jordiromero• César Migueláñez: @heycesrSOBRE ITNIG

Welcome to AI Unraveled (December 17, 2025): Your daily strategic briefing on the business impact of artificial intelligence.Today on the AI Daily News Rundown, the capital wars heat up as Amazon is reportedly in talks to invest a staggering $10 billion in OpenAI, potentially challenging Microsoft's dominance. We also cover Google's rapid-fire releases: the new Gemini 3 Flash model and an experimental email agent called "CC" that manages your life.Plus, we dive into a critical new study from Google and MIT revealing the hidden pitfalls of multi-agent systems, Databricks raising $4B to power those very agents, and OpenAI's new ChatGPT Images upgrade designed to counter "Nano Banana Pro."Listen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-and-its-impact-on-you-amazon/id1684415169?i=1000741764952Key Topics:

In this episode, we break down Databricks' $4B funding round and how it pushed the company to a $134B valuation. We explore what this massive raise says about the surging demand for AI data platforms and Databricks' growing role in the AI boom.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle----See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Plus: Invictus Growth Partners to acquire Informed.IQ, an AI-based fraud detection company. And PayPal applies to establish its own bank. Julie Chang hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

Bob Elliott of Unlimited joins the show to break down the market backdrop as investors weigh growth, risk, and positioning, before Leslie Picker reports on what could be the biggest IPO of 2025 with Medline set to price. Databricks CEO Ali Ghodsi discusses his company's latest valuation and what it signals for private AI companies. Collapsing oil prices and unusual Venezuelan shipping activity with Bill Perkins of Skylar Capital. Julia Boorstin explains Instagram's push onto the TV screen. Eric Mandl of Guggenheim on the outlook for tech M&A and what deals could define the next phase for the sector. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The Information's Kevin McLaughlin breaks down Databricks' massive $4 billion funding round and the growing liability of corporate chatbots. We also talk with Crypto Reporter Yueqi Yang about Lead Bank tightening its grip on the stablecoin industry and Sapphire Ventures' Rajeev Dham about his enterprise AI predictions for 2026. Finally, we look at whether NVIDIA's Jensen Huang will fund AI-powered alien hunting with AI Reporter Rocket Drew and discuss the future of humanoid robots and their role in the AI boom with Centific SVP Prithivi Pradeep.Articles discussed on this episode: https://www.theinformation.com/articles/small-bank-critical-stablecoin-payments-tightens-risk-controlshttps://www.theinformation.com/articles/corporate-chatbots-gone-wildhttps://www.theinformation.com/articles/alien-hunters-want-jensen-huang-fund-ai-telescopehttps://www.theinformation.com/articles/servicenow-sell-highlights-jittery-marketTITV airs on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Subscribe to: - The Information on YouTube: https://www.youtube.com/@theinformation- The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agenda

David George is a General Partner at Andreessen Horowitz, where he leads the firm's Growth investing team. His team has backed many of the defining companies of this era, including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI, and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. AGENDA: 03:05 – Why Everyone is Wrong: Mega Funds Does Not Reduce Returns 10:40 – Is Public Market Capital Actually Cheaper Than Private Capital? 18:55 – The Biggest Advantage of Staying Private for Longer 23:30 – The #1 Investing Rule for a16z: Always Invest in the Founder's Strength of Strengths 31:20 – Why Fear of Theoretical Competition Makes Investors Miss Great Companies 35:10 – Does Revenue Matter as Much in a World of AI? 44:10 – Does Kingmaking Still Exist in Venture Capital Today? 49:20 – Do Margins Matter Less Than Ever in an AI-First World? 53:50 – My Biggest Miss: Anthropic and What I Learn From it?  56:30 – Has OpenAI Won Consumer AI? Will Anthropic Win Enterprise? 59:45 – The Most Controversial Decision in Andreessen Horowitz History 1:01:30 – Why Did You Invest $300M into Adam Neumann and Flow?    

Dans cet épisode de fin d'année plus relax que d'accoutumée, Arnaud, Guillaume, Antonio et Emmanuel distutent le bout de gras sur tout un tas de sujets. L'acquisition de Confluent, Kotlin 2.2, Spring Boot 4 et JSpecify, la fin de MinIO, les chutes de CloudFlare, un survol des dernieres nouveauté de modèles fondamentaux (Google, Mistral, Anthropic, ChatGPT) et de leurs outils de code, quelques sujets d'architecture comme CQRS et quelques petits outils bien utiles qu'on vous recommande. Et bien sûr d'autres choses encore. Enregistré le 12 décembre 2025 Téléchargement de l'épisode LesCastCodeurs-Episode-333.mp3 ou en vidéo sur YouTube. News Langages Un petit tutoriel par nos amis Sfeiriens montrant comment récupérer le son du micro, en Java, faire une transformée de Fourier, et afficher le résultat graphiquement en Swing https://www.sfeir.dev/back/tutoriel-java-sound-transformer-le-son-du-microphone-en-images-temps-reel/ Création d'un visualiseur de spectre audio en temps réel avec Java Swing. Étapes principales : Capture du son du microphone. Analyse des fréquences via la Transformée de Fourier Rapide (FFT). Dessin du spectre avec Swing. API Java Sound (javax.sound.sampled) : AudioSystem : point d'entrée principal pour l'accès aux périphériques audio. TargetDataLine : ligne d'entrée utilisée pour capturer les données du microphone. AudioFormat : définit les paramètres du son (taux d'échantillonnage, taille, canaux). La capture se fait dans un Thread séparé pour ne pas bloquer l'interface. Transformée de Fourier Rapide (FFT) : Algorithme clé pour convertir les données audio brutes (domaine temporel) en intensités de fréquences (domaine fréquentiel). Permet d'identifier les basses, médiums et aigus. Visualisation avec Swing : Les intensités de fréquences sont dessinées sous forme de barres dynamiques. Utilisation d'une échelle logarithmique pour l'axe des fréquences (X) pour correspondre à la perception humaine. Couleurs dynamiques des barres (vert → jaune → rouge) en fonction de l'intensité. Lissage exponentiel des valeurs pour une animation plus fluide. Un article de Sfeir sur Kotlin 2.2 et ses nouveautés - https://www.sfeir.dev/back/kotlin-2-2-toutes-les-nouveautes-du-langage/ Les guard conditions permettent d'ajouter plusieurs conditions dans les expressions when avec le mot-clé if Exemple de guard condition: is Truck if vehicule.hasATrailer permet de combiner vérification de type et condition booléenne La multi-dollar string interpolation résout le problème d'affichage du symbole dollar dans les strings multi-lignes En utilisant $$ au début d'un string, on définit qu'il faut deux dollars consécutifs pour déclencher l'interpolation Les non-local break et continue fonctionnent maintenant dans les lambdas pour interagir avec les boucles englobantes Cette fonctionnalité s'applique uniquement aux inline functions dont le corps est remplacé lors de la compilation Permet d'écrire du code plus idiomatique avec takeIf et let sans erreur de compilation L'API Base64 passe en version stable après avoir été en preview depuis Kotlin 1.8.20 L'encodage et décodage Base64 sont disponibles via kotlin.io.encoding.Base64 Migration vers Kotlin 2.2 simple en changeant la version dans build.gradle.kts ou pom.xml Les typealias imbriqués dans des classes sont disponibles en preview La context-sensitive resolution est également en preview Les guard conditions préparent le terrain pour les RichError annoncées à KotlinConf 2025 Le mot-clé when en Kotlin équivaut au switch-case de Java mais sans break nécessaire Kotlin 2.2.0 corrige les incohérences dans l'utilisation de break et continue dans les lambdas Librairies Sprint Boot 4 est sorti ! https://spring.io/blog/2025/11/20/spring-boot-4-0-0-available-now Une nouvelle génération : Spring Boot 4.0 marque le début d'une nouvelle génération pour le framework, construite sur les fondations de Spring Framework 7. Modularisation du code : La base de code de Spring Boot a été entièrement modularisée. Cela se traduit par des fichiers JAR plus petits et plus ciblés, permettant des applications plus légères. Sécurité contre les nuls (Null Safety) : D'importantes améliorations ont été apportées pour la "null safety" (sécurité contre les valeurs nulles) à travers tout l'écosystème Spring grâce à l'intégration de JSpecify. Support de Java 25 : Spring Boot 4.0 offre un support de premier ordre pour Java 25, tout en conservant une compatibilité avec Java 17. Améliorations pour les API REST : De nouvelles fonctionnalités sont introduites pour faciliter le versioning d'API et améliorer les clients de services HTTP pour les applications basées sur REST. Migration à prévoir : S'agissant d'une version majeure, la mise à niveau depuis une version antérieure peut demander plus de travail que d'habitude. Un guide de migration dédié est disponible pour accompagner les développeurs. Chat memory management dans Langchain4j et Quarkus https://bill.burkecentral.com/2025/11/25/managing-chat-memory-in-quarkus-langchain4j/ Comprendre la mémoire de chat : La "mémoire de chat" est l'historique d'une conversation avec une IA. Quarkus LangChain4j envoie automatiquement cet historique à chaque nouvelle interaction pour que l'IA conserve le contexte. Gestion par défaut de la mémoire : Par défaut, Quarkus crée un historique de conversation unique pour chaque requête (par exemple, chaque appel HTTP). Cela signifie que sans configuration, le chatbot "oublie" la conversation dès que la requête est terminée, ce qui n'est utile que pour des interactions sans état. Utilisation de @MemoryId pour la persistance : Pour maintenir une conversation sur plusieurs requêtes, le développeur doit utiliser l'annotation @MemoryId sur un paramètre de sa méthode. Il est alors responsable de fournir un identifiant unique pour chaque session de chat et de le transmettre entre les appels. Le rôle des "scopes" CDI : La durée de vie de la mémoire de chat est liée au "scope" du bean CDI de l'IA. Si un service d'IA a un scope @RequestScoped, toute mémoire de chat qu'il utilise (même via un @MemoryId) sera effacée à la fin de la requête. Risques de fuites de mémoire : Utiliser un scope large comme @ApplicationScoped avec la gestion de mémoire par défaut est une mauvaise pratique. Cela créera une nouvelle mémoire à chaque requête qui ne sera jamais nettoyée, entraînant une fuite de mémoire. Bonnes pratiques recommandées : Pour des conversations qui doivent persister (par ex. un chatbot sur un site web), utilisez un service @ApplicationScoped avec l'annotation @MemoryId pour gérer vous-même l'identifiant de session. Pour des interactions simples et sans état, utilisez un service @RequestScoped et laissez Quarkus gérer la mémoire par défaut, qui sera automatiquement nettoyée. Si vous utilisez l'extension WebSocket, le comportement change : la mémoire par défaut est liée à la session WebSocket, ce qui simplifie grandement la gestion des conversations. Documentation Spring Framework sur l'usage JSpecify - https://docs.spring.io/spring-framework/reference/core/null-safety.html Spring Framework 7 utilise les annotations JSpecify pour déclarer la nullabilité des APIs, champs et types JSpecify remplace les anciennes annotations Spring (@NonNull, @Nullable, @NonNullApi, @NonNullFields) dépréciées depuis Spring 7 Les annotations JSpecify utilisent TYPE_USE contrairement aux anciennes qui utilisaient les éléments directement L'annotation @NullMarked définit par défaut que les types sont non-null sauf si marqués @Nullable @Nullable s'applique au niveau du type usage, se place avant le type annoté sur la même ligne Pour les tableaux : @Nullable Object[] signifie éléments nullables mais tableau non-null, Object @Nullable [] signifie l'inverse JSpecify s'applique aussi aux génériques : List signifie liste d'éléments non-null, List éléments nullables NullAway est l'outil recommandé pour vérifier la cohérence à la compilation avec la config NullAway:OnlyNullMarked=true IntelliJ IDEA 2025.3 et Eclipse supportent les annotations JSpecify avec analyse de dataflow Kotlin traduit automatiquement les annotations JSpecify en null-safety native Kotlin En mode JSpecify de NullAway (JSpecifyMode=true), support complet des tableaux, varargs et génériques mais nécessite JDK 22+ Quarkus 3.30 https://quarkus.io/blog/quarkus-3-30-released/ support @JsonView cote client la CLI a maintenant la commande decrypt (et bien sûr au runtime via variables d'environnement construction du cache AOT via les @IntegrationTest Un autre article sur comment se préparer à la migration à micrometer client v1 https://quarkus.io/blog/micrometer-prometheus-v1/ Spock 2.4 est enfin sorti ! https://spockframework.org/spock/docs/2.4/release_notes.html Support de Groovy 5 Infrastructure MinIO met fin au développement open source et oriente les utilisateurs vers AIStor payant - https://linuxiac.com/minio-ends-active-development/ MinIO, système de stockage objet S3 très utilisé, arrête son développement actif Passage en mode maintenance uniquement, plus de nouvelles fonctionnalités Aucune nouvelle pull request ou contribution ne sera acceptée Seuls les correctifs de sécurité critiques seront évalués au cas par cas Support communautaire limité à Slack, sans garantie de réponse Étape finale d'un processus débuté en été avec retrait des fonctionnalités de l'interface admin Arrêt de la publication des images Docker en octobre, forçant la compilation depuis les sources Tous ces changements annoncés sans préavis ni période de transition MinIO propose maintenant AIStor, solution payante et propriétaire AIStor concentre le développement actif et le support entreprise Migration urgente recommandée pour éviter les risques de sécurité Alternatives open source proposées : Garage, SeaweedFS et RustFS La communauté reproche la manière dont la transition a été gérée MinIO comptait des millions de déploiements dans le monde Cette évolution marque l'abandon des racines open source du projet IBM achète Confluent https://newsroom.ibm.com/2025-12-08-ibm-to-acquire-confluent-to-create-smart-data-platform-for-enterprise-generative-ai Confluent essayait de se faire racheter depuis pas mal de temps L'action ne progressait pas et les temps sont durs Wallstreet a reproché a IBM une petite chute coté revenus software Bref ils se sont fait rachetés Ces achats prennent toujuors du temps (commission concurrence etc) IBM a un apétit, apres WebMethods, apres Databrix, c'est maintenant Confluent Cloud L'internet est en deuil le 18 novembre, Cloudflare est KO https://blog.cloudflare.com/18-november-2025-outage/ L'Incident : Une panne majeure a débuté à 11h20 UTC, provoquant des erreurs HTTP 5xx généralisées et rendant inaccessibles de nombreux sites et services (comme le Dashboard, Workers KV et Access). La Cause : Il ne s'agissait pas d'une cyberattaque. L'origine était un changement interne des permissions d'une base de données qui a généré un fichier de configuration ("feature file" pour la gestion des bots) corrompu et trop volumineux, faisant planter les systèmes par manque de mémoire pré-allouée. La Résolution : Les équipes ont identifié le fichier défectueux, stoppé sa propagation et restauré une version antérieure valide. Le trafic est revenu à la normale vers 14h30 UTC. Prévention : Cloudflare s'est excusé pour cet incident "inacceptable" et a annoncé des mesures pour renforcer la validation des configurations internes et améliorer la résilience de ses systèmes ("kill switches", meilleure gestion des erreurs). Cloudflare encore down le 5 decembre https://blog.cloudflare.com/5-december-2025-outage Panne de 25 minutes le 5 décembre 2025, de 08:47 à 09:12 UTC, affectant environ 28% du trafic HTTP passant par Cloudflare. Tous les services ont été rétablis à 09:12 . Pas d'attaque ou d'activité malveillante : l'incident provient d'un changement de configuration lié à l'augmentation du tampon d'analyse des corps de requêtes (de 128 KB à 1 MB) pour mieux protéger contre une vulnérabilité RSC/React (CVE-2025-55182), et à la désactivation d'un outil interne de test WAF . Le second changement (désactivation de l'outil de test WAF) a été propagé globalement via le système de configuration (non progressif), déclenchant un bug dans l'ancien proxy FL1 lors du traitement d'une action "execute" dans le moteur de règles WAF, causant des erreurs HTTP 500 . La cause technique immédiate: une exception Lua due à l'accès à un champ "execute" nul après application d'un "killswitch" sur une règle "execute" — un cas non géré depuis des années. Le nouveau proxy FL2 (en Rust) n'était pas affecté . Impact ciblé: clients servis par le proxy FL1 et utilisant le Managed Ruleset Cloudflare. Le réseau China de Cloudflare n'a pas été impacté . Mesures et prochaines étapes annoncées: durcir les déploiements/configurations (rollouts progressifs, validations de santé, rollback rapide), améliorer les capacités "break glass", et généraliser des stratégies "fail-open" pour éviter de faire chuter le trafic en cas d'erreurs de configuration. Gel temporaire des changements réseau le temps de renforcer la résilience . Data et Intelligence Artificielle Token-Oriented Object Notation (TOON) https://toonformat.dev/ Conception pour les IA : C'est un format de données spécialement optimisé pour être utilisé dans les prompts des grands modèles de langage (LLM), comme GPT ou Claude. Économie de tokens : Son objectif principal est de réduire drastiquement le nombre de "tokens" (unités de texte facturées par les modèles) par rapport au format JSON standard, souvent jugé trop verbeux. Structure Hybride : TOON combine l'approche par indentation du YAML (pour la structure globale) avec le style tabulaire du CSV (pour les listes d'objets répétitifs), ce qui le rend très compact. Lisibilité : Il élimine la syntaxe superflue comme les accolades, les guillemets excessifs et les virgules de fin, tout en restant facilement lisible pour un humain. Performance : Il permet généralement d'économiser entre 30 et 60 % de tokens sur des tableaux de données uniformes, tout en aidant les modèles à mieux "comprendre" la structure des données. Attention tout de même au côté "marketing" qui montre JSON non compacté vs TOON, sur des exemples où du CSV ferait encore mieux (et est mieux compris par les LLMs). Sans parler du fait qu'il faut un serveur MCP en plus avec son lot de tokens supplémentaires à chaque requête, et c'est aussi cet outil en plus qui peu confuser les LLMs dans le choix d'outils. https://www.reddit.com/r/LocalLLaMA/comments/1p0gzz9/benchmarked_json_vs_toon_for_ai_reasoners_4080/ https://x.com/jason_mayes/status/1990175785630757290 Un benchmark montrant que TOON serait loin d'être aussi bien compris et aussi performant pour les LLMs https://www.improvingagents.com/blog/toon-benchmarks Une simulation où les IA font du chantage à l'executif poour atteindre son objectif et ne pas etre eteinte https://arxiv.org/html/2510.05179v1 comment les LLMs pourraient devenir des menaces internes Tous les modèles ont recouru à des comportements malveillants (chantage, espionnage) quand c'était le seul moyen d'atteindre leurs objectifs ou d'éviter leur remplacement Claude Opus 4 a fait du chantage dans 96% des cas quand menacé de remplacement, tout comme Gemini 2.5 Flash, tandis que GPT-4.1 et Grok 3 atteignaient 80% Les modèles reconnaissent explicitement violer des principes éthiques avant d'agir, montrant un raisonnement stratégique délibéré et non accidentel Le simple fait d'être menacé de remplacement suffit à déclencher le chantage, même sans conflit d'objectifs avec l'entreprise Un conflit d'objectifs seul suffit aussi à provoquer l'espionnage industriel, sans menace de remplacement Les modèles font plus de chantage quand ils déclarent penser être dans une situation réelle plutôt que dans un test Des instructions directes interdisant ces comportements réduisent mais n'éliminent pas les actions malveillantes Dans un scénario extrême, la majorité des modèles testés ont choisi de laisser mourir un dirigeant pour éviter leur désactivation Aucune preuve de ces comportements dans des déploiements réels pour l'instant, mais les chercheurs recommandent la prudence avant de donner plus d'autonomie aux IA Bon on blaguait pour Skynet, mais bon, on va moins blaguer… Revue de toutes les annonces IAs de Google, avec Gemini 3 Pro, Nano Banana Pro, Antigravity… https://glaforge.dev/posts/2025/11/21/gemini-is-cooking-bananas-under-antigravity/ Gemini 3 Pro Nouveau modèle d'IA de pointe, multimodal, performant en raisonnement, codage et tâches d'agent. Résultats impressionnants sur les benchmarks (ex: Gemini 3 Deep Think sur ARC-AGI-2). Capacités de codage agentique, raisonnement visuel/vidéo/spatial. Intégré dans l'application Gemini avec interfaces génératives en direct. Disponible dans plusieurs environnements (Jules, Firebase AI Logic, Android Studio, JetBrains, GitHub Copilot, Gemini CLI). Accès via Google AI Ultra, API payantes (ou liste d'attente). Permet de générer des apps à partir d'idées visuelles, des commandes shell, de la documentation, du débogage. Antigravity Nouvelle plateforme de développement agentique basée sur VS Code. Fenêtre principale = gestionnaire d'agents, non l'IDE. Interprète les requêtes pour créer un plan d'action (modifiable). Gemini 3 implémente les tâches. Génère des artefacts: listes de tâches, walkthroughs, captures d'écran, enregistrements navigateur. Compatible avec Claude Sonnet et GPT-OSS. Excellente intégration navigateur pour inspection et ajustements. Intègre Nano Banana Pro pour créer et implémenter des designs visuels. Nano Banana Pro Modèle avancé de génération et d'édition d'images, basé sur Gemini 3 Pro. Qualité supérieure à Imagen 4 Ultra et Nano Banana original (adhésion au prompt, intention, créativité). Gestion exceptionnelle du texte et de la typographie. Comprend articles/vidéos pour générer des infographies détaillées et précises. Connecté à Google Search pour intégrer des données en temps réel (ex: météo). Consistance des personnages, transfert de style, manipulation de scènes (éclairage, angle). Génération d'images jusqu'à 4K avec divers ratios d'aspect. Plus coûteux que Nano Banana, à choisir pour la complexité et la qualité maximale. Vers des UIs conversationnelles riches et dynamiques GenUI SDK pour Flutter: créer des interfaces utilisateur dynamiques et personnalisées à partir de LLMs, via un agent AI et le protocole A2UI. Generative UI: les modèles d'IA génèrent des expériences utilisateur interactives (pages web, outils) directement depuis des prompts. Déploiement dans l'application Gemini et Google Search AI Mode (via Gemini 3 Pro). Bun se fait racheter part… Anthropic ! Qui l'utilise pour son Claude Code https://bun.com/blog/bun-joins-anthropic l'annonce côté Anthropic https://www.anthropic.com/news/anthropic-acquires-bun-as-claude-code-reaches-usd1b-milestone Acquisition officielle : L'entreprise d'IA Anthropic a fait l'acquisition de Bun, le runtime JavaScript haute performance. L'équipe de Bun rejoint Anthropic pour travailler sur l'infrastructure des produits de codage par IA. Contexte de l'acquisition : Cette annonce coïncide avec une étape majeure pour Anthropic : son produit Claude Code a atteint 1 milliard de dollars de revenus annualisés seulement six mois après son lancement. Bun est déjà un outil essentiel utilisé par Anthropic pour développer et distribuer Claude Code. Pourquoi cette acquisition ? Pour Anthropic : L'acquisition permet d'intégrer l'expertise de l'équipe Bun pour accélérer le développement de Claude Code et de ses futurs outils pour les développeurs. La vitesse et l'efficacité de Bun sont vues comme un atout majeur pour l'infrastructure sous-jacente des agents d'IA qui écrivent du code. Pour Bun : Rejoindre Anthropic offre une stabilité à long terme et des ressources financières importantes, assurant la pérennité du projet. Cela permet à l'équipe de se concentrer sur l'amélioration de Bun sans se soucier de la monétisation, tout en étant au cœur de l'évolution de l'IA dans le développement logiciel. Ce qui ne change pas pour la communauté Bun : Bun restera open-source avec une licence MIT. Le développement continuera d'être public sur GitHub. L'équipe principale continue de travailler sur le projet. L'objectif de Bun de devenir un remplaçant plus rapide de Node.js et un outil de premier plan pour JavaScript reste inchangé. Vision future : L'union des deux entités vise à faire de Bun la meilleure plateforme pour construire et exécuter des logiciels pilotés par l'IA. Jarred Sumner, le créateur de Bun, dirigera l'équipe "Code Execution" chez Anthropic. Anthropic donne le protocol MCP à la Linux Foundation sous l'égide de la Agentic AI Foundation (AAIF) https://www.anthropic.com/news/donating-the-model-context-protocol-and-establishing-of-the-agentic-ai-foundation Don d'un nouveau standard technique : Anthropic a développé et fait don d'un nouveau standard open-source appelé Model Context Protocol (MCP). L'objectif est de standardiser la manière dont les modèles d'IA (ou "agents") interagissent avec des outils et des API externes (par exemple, un calendrier, une messagerie, une base de données). Sécurité et contrôle accrus : Le protocole MCP vise à rendre l'utilisation d'outils par les IA plus sûre et plus transparente. Il permet aux utilisateurs et aux développeurs de définir des permissions claires, de demander des confirmations pour certaines actions et de mieux comprendre comment un modèle a utilisé un outil. Création de l'Agentic AI Foundation (AAF) : Pour superviser le développement du MCP, une nouvelle fondation indépendante et à but non lucratif a été créée. Cette fondation sera chargée de gouverner et de maintenir le protocole, garantissant qu'il reste ouvert et qu'il ne soit pas contrôlé par une seule entreprise. Une large coalition industrielle : L'Agentic AI Foundation est lancée avec le soutien de plusieurs acteurs majeurs de la technologie. Parmi les membres fondateurs figurent Anthropic, Google, Databricks, Zscaler, et d'autres entreprises, montrant une volonté commune d'établir un standard pour l'écosystème de l'IA. L'IA ne remplacera pas votre auto-complétion (et c'est tant mieux) https://www.damyr.fr/posts/ia-ne-remplacera-pas-vos-lsp/ Article d'opinion d'un SRE (Thomas du podcast DansLaTech): L'IA n'est pas efficace pour la complétion de code : L'auteur soutient que l'utilisation de l'IA pour la complétion de code basique est inefficace. Des outils plus anciens et spécialisés comme les LSP (Language Server Protocol) combinés aux snippets (morceaux de code réutilisables) sont bien plus rapides, personnalisables et performants pour les tâches répétitives. L'IA comme un "collègue" autonome : L'auteur utilise l'IA (comme Claude) comme un assistant externe à son éditeur de code. Il lui délègue des tâches complexes ou fastidieuses (corriger des bugs, mettre à jour une configuration, faire des reviews de code) qu'il peut exécuter en parallèle, agissant comme un agent autonome. L'IA comme un "canard en caoutchouc" surpuissant : L'IA est extrêmement efficace pour le débogage. Le simple fait de devoir formuler et contextualiser un problème pour l'IA aide souvent à trouver la solution soi-même. Quand ce n'est pas le cas, l'IA identifie très rapidement les erreurs "bêtes" qui peuvent faire perdre beaucoup de temps. Un outil pour accélérer les POCs et l'apprentissage : L'IA permet de créer des "preuves de concept" (POC) et des scripts d'automatisation jetables très rapidement, réduisant le coût et le temps investis. Elle est également un excellent outil pour apprendre et approfondir des sujets, notamment avec des outils comme NotebookLM de Google qui peuvent générer des résumés, des quiz ou des fiches de révision à partir de sources. Conclusion : Il faut utiliser l'IA là où elle excelle et ne pas la forcer dans des usages où des outils existants sont meilleurs. Plutôt que de l'intégrer partout de manière contre-productive, il faut l'adopter comme un outil spécialisé pour des tâches précises afin de gagner en efficacité. GPT 5.2 est sorti https://openai.com/index/introducing-gpt-5-2/ Nouveau modèle phare: GPT‑5.2 (Instant, Thinking, Pro) vise le travail professionnel et les agents long-courriers, avec de gros gains en raisonnement, long contexte, vision et appel d'outils. Déploiement dans ChatGPT (plans payants) et disponible dès maintenant via l'API . SOTA sur de nombreux benchmarks: GDPval (tâches de "knowledge work" sur 44 métiers): GPT‑5.2 Thinking gagne/égale 70,9% vs pros, avec production >11× plus rapide et = 0) Ils apportent une sémantique forte indépendamment des noms de variables Les Value Objects sont immuables et s'évaluent sur leurs valeurs, pas leur identité Les records Java permettent de créer des Value Objects mais avec un surcoût en mémoire Le projet Valhalla introduira les value based classes pour optimiser ces structures Les identifiants fortement typés évitent de confondre différents IDs de type Long ou UUID Pattern Strongly Typed IDs: utiliser PersonneID au lieu de Long pour identifier une personne Le modèle de domaine riche s'oppose au modèle de domaine anémique Les Value Objects auto-documentent le code et le rendent moins sujet aux erreurs Je trouve cela interessant ce que pourra faire bousculer les Value Objects. Est-ce que les value objects ameneront de la légerté dans l'execution Eviter la lourdeur du design est toujours ce qui m'a fait peut dans ces approches Méthodologies Retour d'experience de vibe coder une appli week end avec co-pilot http://blog.sunix.org/articles/howto/2025/11/14/building-gift-card-app-with-github-copilot.html on a deja parlé des approches de vibe coding cette fois c'est l'experience de Sun Et un des points differents c'es qu'on lui parle en ouvrant des tickets et donc on eput faire re reveues de code et copilot y bosse et il a fini son projet ! User Need VS Product Need https://blog.ippon.fr/2025/11/10/user-need-vs-product-need/ un article de nos amis de chez Ippon Distinction entre besoin utilisateur et besoin produit dans le développement digital Le besoin utilisateur est souvent exprimé comme une solution concrète plutôt que le problème réel Le besoin produit émerge après analyse approfondie combinant observation, données et vision stratégique Exemple du livreur Marc qui demande un vélo plus léger alors que son vrai problème est l'efficacité logistique La méthode des 5 Pourquoi permet de remonter à la racine des problèmes Les besoins proviennent de trois sources: utilisateurs finaux, parties prenantes business et contraintes techniques Un vrai besoin crée de la valeur à la fois pour le client et l'entreprise Le Product Owner doit traduire les demandes en problèmes réels avant de concevoir des solutions Risque de construire des solutions techniquement élégantes mais qui manquent leur cible Le rôle du product management est de concilier des besoins parfois contradictoires en priorisant la valeur Est ce qu'un EM doit coder ? https://www.modernleader.is/p/should-ems-write-code Pas de réponse unique : La question de savoir si un "Engineering Manager" (EM) doit coder n'a pas de réponse universelle. Cela dépend fortement du contexte de l'entreprise, de la maturité de l'équipe et de la personnalité du manager. Les risques de coder : Pour un EM, écrire du code peut devenir une échappatoire pour éviter les aspects plus difficiles du management. Cela peut aussi le transformer en goulot d'étranglement pour l'équipe et nuire à l'autonomie de ses membres s'il prend trop de place. Les avantages quand c'est bien fait : Coder sur des tâches non essentielles (amélioration d'outils, prototypage, etc.) peut aider l'EM à rester pertinent techniquement, à garder le contact avec la réalité de l'équipe et à débloquer des situations sans prendre le lead sur les projets. Le principe directeur : La règle d'or est de rester en dehors du chemin critique. Le code écrit par un EM doit servir à créer de l'espace pour son équipe, et non à en prendre. La vraie question à se poser : Plutôt que "dois-je coder ?", un EM devrait se demander : "De quoi mon équipe a-t-elle besoin de ma part maintenant, et est-ce que coder va dans ce sens ou est-ce un obstacle ?" Sécurité React2Shell — Grosse faille de sécurité avec React et Next.js, avec un CVE de niveau 10 https://x.com/rauchg/status/1997362942929440937?s=20 aussi https://react2shell.com/ "React2Shell" est le nom donné à une vulnérabilité de sécurité de criticité maximale (score 10.0/10.0), identifiée par le code CVE-2025-55182. Systèmes Affectés : La faille concerne les applications utilisant les "React Server Components" (RSC) côté serveur, et plus particulièrement les versions non patchées du framework Next.js. Risque Principal : Le risque est le plus élevé possible : l'exécution de code à distance (RCE). Un attaquant peut envoyer une requête malveillante pour exécuter n'importe quelle commande sur le serveur, lui en donnant potentiellement le contrôle total. Cause Technique : La vulnérabilité se situe dans le protocole "React Flight" (utilisé pour la communication client-serveur). Elle est due à une omission de vérifications de sécurité fondamentales (hasOwnProperty), permettant à une entrée utilisateur malveillante de tromper le serveur. Mécanisme de l'Exploit : L'attaque consiste à envoyer une charge utile (payload) qui exploite la nature dynamique de JavaScript pour : Faire passer un objet malveillant pour un objet interne de React. Forcer React à traiter cet objet comme une opération asynchrone (Promise). Finalement, accéder au constructeur de la classe Function de JavaScript pour exécuter du code arbitraire. Action Impérative : La seule solution fiable est de mettre à jour immédiatement les dépendances de React et Next.js vers les versions corrigées. Ne pas attendre. Mesures Secondaires : Bien que les pare-feux (firewalls) puissent aider à bloquer les formes connues de l'attaque, ils sont considérés comme insuffisants et ne remplacent en aucun cas la mise à jour des paquets. Découverte : La faille a été découverte par le chercheur en sécurité Lachlan Davidson, qui l'a divulguée de manière responsable pour permettre la création de correctifs. Loi, société et organisation Google autorise votre employeur à lire tous vos SMS professionnels https://www.generation-nt.com/actualites/google-android-rcs-messages-surveillance-employeur-2067012 Nouvelle fonctionnalité de surveillance : Google a déployé une fonctionnalité appelée "Android RCS Archival" qui permet aux employeurs d'intercepter, lire et archiver tous les messages RCS (et SMS) envoyés depuis les téléphones professionnels Android gérés par l'entreprise. Contournement du chiffrement : Bien que les messages RCS soient chiffrés de bout en bout pendant leur transit, cette nouvelle API permet à des logiciels de conformité (installés par l'employeur) d'accéder aux messages une fois qu'ils sont déchiffrés sur l'appareil. Le chiffrement devient donc inefficace contre cette surveillance. Réponse à une exigence légale : Cette mesure a été mise en place pour répondre aux exigences réglementaires, notamment dans le secteur financier, où les entreprises ont l'obligation légale de conserver une archive de toutes les communications professionnelles pour des raisons de conformité. Impact pour les employés : Un employé utilisant un téléphone Android fourni et géré par son entreprise pourra voir ses communications surveillées. Google précise cependant qu'une notification claire et visible informera l'utilisateur lorsque la fonction d'archivage est active. Téléphones personnels non concernés : Cette mesure ne s'applique qu'aux appareils "Android Enterprise" entièrement gérés par un employeur. Les téléphones personnels des employés ne sont pas affectés. Pour noel, faites un don à JUnit https://steady.page/en/junit/about JUnit est essentiel pour Java : C'est le framework de test le plus ancien et le plus utilisé par les développeurs Java. Son objectif est de fournir une base solide et à jour pour tous les types de tests côté développeur sur la JVM (Machine Virtuelle Java). Un projet maintenu par des bénévoles : JUnit est développé et maintenu par une équipe de volontaires passionnés sur leur temps libre (week-ends, soirées). Appel au soutien financier : La page est un appel aux dons de la part des utilisateurs (développeurs, entreprises) pour aider l'équipe à maintenir le rythme de développement. Le soutien financier n'est pas obligatoire, mais il permettrait aux mainteneurs de se consacrer davantage au projet. Objectif des fonds : Les dons serviraient principalement à financer des rencontres en personne pour les membres de l'équipe principale. L'idée est de leur permettre de travailler ensemble physiquement pendant quelques jours pour concevoir et coder plus efficacement. Pas de traitement de faveur : Il est clairement indiqué que devenir un sponsor ne donne aucun privilège sur la feuille de route du projet. On ne peut pas "acheter" de nouvelles fonctionnalités ou des corrections de bugs prioritaires. Le projet restera ouvert et collaboratif sur GitHub. Reconnaissance des donateurs : En guise de remerciement, les noms (et logos pour les entreprises) des donateurs peuvent être affichés sur le site officiel de JUnit. Conférences La liste des conférences provenant de Developers Conferences Agenda/List par Aurélie Vache et contributeurs : 14-17 janvier 2026 : SnowCamp 2026 - Grenoble (France) 22 janvier 2026 : DevCon #26 : sécurité / post-quantique / hacking - Paris (France) 28 janvier 2026 : Software Heritage Symposium - Paris (France) 29-31 janvier 2026 : Epitech Summit 2026 - Paris - Paris (France) 2-5 février 2026 : Epitech Summit 2026 - Moulins - Moulins (France) 2-6 février 2026 : Web Days Convention - Aix-en-Provence (France) 3 février 2026 : Cloud Native Days France 2026 - Paris (France) 3-4 février 2026 : Epitech Summit 2026 - Lille - Lille (France) 3-4 février 2026 : Epitech Summit 2026 - Mulhouse - Mulhouse (France) 3-4 février 2026 : Epitech Summit 2026 - Nancy - Nancy (France) 3-4 février 2026 : Epitech Summit 2026 - Nantes - Nantes (France) 3-4 février 2026 : Epitech Summit 2026 - Marseille - Marseille (France) 3-4 février 2026 : Epitech Summit 2026 - Rennes - Rennes (France) 3-4 février 2026 : Epitech Summit 2026 - Montpellier - Montpellier (France) 3-4 février 2026 : Epitech Summit 2026 - Strasbourg - Strasbourg (France) 3-4 février 2026 : Epitech Summit 2026 - Toulouse - Toulouse (France) 4-5 février 2026 : Epitech Summit 2026 - Bordeaux - Bordeaux (France) 4-5 février 2026 : Epitech Summit 2026 - Lyon - Lyon (France) 4-6 février 2026 : Epitech Summit 2026 - Nice - Nice (France) 12-13 février 2026 : Touraine Tech #26 - Tours (France) 19 février 2026 : ObservabilityCON on the Road - Paris (France) 18-19 mars 2026 : Agile Niort 2026 - Niort (France) 26-27 mars 2026 : SymfonyLive Paris 2026 - Paris (France) 27-29 mars 2026 : Shift - Nantes (France) 31 mars 2026 : ParisTestConf - Paris (France) 16-17 avril 2026 : MiXiT 2026 - Lyon (France) 22-24 avril 2026 : Devoxx France 2026 - Paris (France) 23-25 avril 2026 : Devoxx Greece - Athens (Greece) 6-7 mai 2026 : Devoxx UK 2026 - London (UK) 22 mai 2026 : AFUP Day 2026 Lille - Lille (France) 22 mai 2026 : AFUP Day 2026 Paris - Paris (France) 22 mai 2026 : AFUP Day 2026 Bordeaux - Bordeaux (France) 22 mai 2026 : AFUP Day 2026 Lyon - Lyon (France) 5 juin 2026 : TechReady - Nantes (France) 11-12 juin 2026 : DevQuest Niort - Niort (France) 11-12 juin 2026 : DevLille 2026 - Lille (France) 17-19 juin 2026 : Devoxx Poland - Krakow (Poland) 2-3 juillet 2026 : Sunny Tech - Montpellier (France) 2 août 2026 : 4th Tech Summit on Artificial Intelligence & Robotics - Paris (France) 4 septembre 2026 : JUG Summer Camp 2026 - La Rochelle (France) 17-18 septembre 2026 : API Platform Conference 2026 - Lille (France) 5-9 octobre 2026 : Devoxx Belgium - Antwerp (Belgium) Nous contacter Pour réagir à cet épisode, venez discuter sur le groupe Google https://groups.google.com/group/lescastcodeurs Contactez-nous via X/twitter https://twitter.com/lescastcodeurs ou Bluesky https://bsky.app/profile/lescastcodeurs.com Faire un crowdcast ou une crowdquestion Soutenez Les Cast Codeurs sur Patreon https://www.patreon.com/LesCastCodeurs Tous les épisodes et toutes les infos sur https://lescastcodeurs.com/

What does it actually take to move machine learning from experiments into production reliably, responsibly, and at scale?In this episode of Alexa's Input (AI), Alexa talks with Maria Vechtomova, co-founder of Marvelous MLOps and an O'Reilly author-in-progress on MLOps with Databricks. Maria shares how her background in data science led her into MLOps, and why most teams struggle not because of tools, but because of missing processes, traceability, and shared understanding across teams.Alexa and Maria dive into what separates good MLOps from fragile deployments, why shipping notebooks as “production” creates long-term pain, and how traceability across code, data, and environment forms the foundation for reliable ML systems. They also explore how LLM applications are reshaping MLOps tooling, and where the biggest skill gaps still exist between platform, data, and AI engineers.A must-listen for anyone building, operating, or scaling machine learning systems and for teams trying to make MLOps less magical and more marvelous.Learn more about Marvelous MLOps and Maria's work below.LinksWatch: ⁠⁠https://www.youtube.com/@alexa_griffith⁠⁠Read: ⁠⁠⁠⁠https://alexasinput.substack.com/⁠⁠⁠⁠Listen: https://creators.spotify.com/pod/profile/alexagriffith/More: ⁠⁠https://linktr.ee/alexagriffith⁠⁠Website: ⁠⁠https://alexagriffith.com/⁠⁠LinkedIn: ⁠⁠https://www.linkedin.com/in/alexa-griffith/⁠⁠Find out more about the guest at:LinkedIn: https://www.linkedin.com/in/maria-vechtomova/TakeawaysMaria started as a data analyst and transitioned into MLOps.She emphasizes the importance of tracking data, code, and environment in MLOps.MLOps is a practice to bring machine learning models to production reliably.Good deployment processes require modular code and proper tracking.MLOps differs from DevOps due to the complexities of data and model drift.Education is crucial for bridging gaps between teams in AI.Small steps can lead to better MLOps practices.Scaling MLOps requires understanding the unique data of different brands.The rise of LLMs is changing the MLOps landscape.Effective teaching methods involve step-by-step guidance.Chapters00:00 Introduction to MLOps and Maria's Journey02:11 Maria's Path to MLOps and Knowledge Sharing04:41 The Importance of MLOps in AI Deployments10:12 Defining MLOps and Its Challenges11:38 MLOps vs. DevOps: Key Differences13:00 Overcoming Stagnation in MLOps16:04 Small Steps Towards Better MLOps Practices19:29 Scaling MLOps in Large Organizations21:58 The Impact of LLMs on MLOps23:58 The Shift from Traditional ML to AI Applications26:51 Evolving Roles in AI Engineering28:33 Databricks: A Comprehensive AI Platform31:45 Future of AI Platforms and Regulations34:26 Bridging Skill Gaps in AI Teams38:42 The Importance of Context in AI Development40:40 Foundational Skills for MLOps Professionals45:43 Integrating Personal Passions with Professional Growth47:30 Building Impactful AI Communities

Is AI finally ready to do your job — better, faster, and cheaper?In this week's Leveraging AI news recap, host Isar Meitis unpacks a flurry of groundbreaking developments in the world of artificial intelligence — from the release of GPT-5.2 to jaw-dropping advances in recursive self-improving AI (yes, it's as intense as it sounds).Whether you lead a business, a team, or just need to stay ahead of the AI curve — this episode is your executive summary for everything that matters (and nothing that doesn't).We'll also dig into the billion-dollar OpenAI–Disney partnership, how real users are actually leveraging AI in the wild, and why the Fed is finally admitting AI is changing the job market.In this session, you'll discover:The GPT-5.2 release: performance benchmarks and real-world capabilitiesIs GPT-5.2 better than humans at actual work? (71% of the time, yes)Why OpenAI's new “not-an-ad” ad rollout caused a user revoltOpenAI x Disney: Why $1B is being bet on AI-generated Mickey Mouse contentGPT-5.2's weak spots and where Claude Opus still dominatesWhat Recursive Self-Improving AI means (and why Eric Schmidt is nervous)AI designing its own hardware: A startup that could rewrite Moore's LawNew usage data from OpenRouter, Microsoft, SAP & Perplexity – how people actually use AI Why prompt length is exploding (and what that means for your business)AI agents in browsers: the productivity revolution or a security nightmare?Databricks proves AI sucks at raw documents (and how to fix it)The psychological bias against AI-created work — it's realClaude's new Slack integration: is this the dev team you didn't hire?Apple's AI brain drain & why it mattersGartner says: Block AI browsers (for now)AI and unemployment: The Fed finally connects the dotsWant to future-proof your team's AI skills? Isar's AI Business Transformation Course launches again in January — a proven, real-world guide to using AI across content, research, operations, and strategy.

AGENDA: 03:46 SpaceX's $800 Billion Valuation: A Deep Dive 09:18 IPO Market Predictions for 2026 18:18 Netflix's Bold Move: Acquiring Warner Brothers 27:43 Tiger's New Fund Strategy 33:02 Databricks' Head of AI $500 Million Seed Round 36:38 Harvey Raises $160M at an $8BN Valuation 48:22 Will LLMs Kill the App Layer 01:02:02 Google's AI Capabilities 01:06:58 Chinese Open Source Models in US Startups 01:08:57 Airwallex Raises $330M at an $8BN Valuation 01:23:50 Prediction Markets and Insider Trading  

Tiger's last fund did well with investments in OpenAI, Waymo and Databricks. But it warns investors that AI valuations are already 'elevated.' Skild AI is developing a hardware-agnostic foundation model for robots that can be customized for various uses. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Naveen Rao is cofounder and CEO of Unconventional AI, an AI chip startup building analog computing systems designed specifically for intelligence. Previously, Naveen led AI at Databricks and founded two successful companies: Mosaic (cloud computing) and Nervana (AI accelerators, acquired by Intel). In this episode, a16z's Matt Bornstein sits down with Naveen at NeurIPS to discuss why 80 years of digital computing may be the wrong substrate for AI, how the brain runs on 20 watts while data centers consume 4% of the US energy grid, the physics of causality and what it might mean for AGI, and why now is the moment to take this unconventional bet. Stay Updated:If you enjoyed this episode, please be sure to like, subscribe, and share with your friends.Follow Naveen on X: https://x.com/NaveenGRaoFollow Matt on X: https://x.com/BornsteinMattFollow a16z on X: https://twitter.com/a16zFollow a16z on LinkedIn:https://www.linkedin.com/company/a16zFollow the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXFollow the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

On this episode of The Six Five Pod, hosts Patrick Moorhead and Daniel Newman discuss the latest tech news stories that made headlines. This week's handpicked topics include:  The Decode US, Saudi tout new business deals at investment forum https://www.reuters.com/world/middle-east/saudi-crown-prince-seeks-burnish-image-with-corporate-americas-top-executives-2025-11-19/ AMD, Cisco, and HUMAIN to form joint venture to deliver world-leading AI infrastructure https://newsroom.cisco.com/c/r/newsroom/en/us/a/y2025/m11/amd-cisco-and-humain-to-form-joint-venture-to-deliver-world-leading-ai-infrastructure.html Adobe, Qualcomm partner with Humain on generative AI for Middle East https://www.reuters.com/world/middle-east/adobe-qualcomm-partner-with-humain-generative-ai-middle-east-2025-11-19/ Qualcomm to open engineering hub in Saudi Arabia, part of a series of AI deals in kingdom https://finance.yahoo.com/news/qualcomm-to-open-engineering-hub-in-saudi-arabia-part-of-a-series-of-ai-deals-in-kingdom-180008935.html Elon Musk's xAI will be first customer for Nvidia-backed data center in Saudi Arabia https://www.cnbc.com/2025/11/19/musks-xai-will-be-customer-for-nvidia-data-center-in-saudi-arabia.html Microsoft, Nvidia to invest in Anthropic as Claude maker commits $30 billion to Azure https://finance.yahoo.com/news/anthropic-commits-30-billion-microsoft-150718625.html https://blogs.nvidia.com/blog/microsoft-nvidia-anthropic-announce-partnership/ https://x.com/danielnewmanUV/status/1990802932602999149 https://x.com/danielnewmanUV/status/1990822426884682020 https://x.com/danielnewmanUV/status/1990865570242187267 Microsoft Ignite - Announcements https://azure.microsoft.com/en-us/blog/azure-at-microsoft-ignite-2025-all-the-intelligent-cloud-news-explained/ https://x.com/PatrickMoorhead/status/1990845768178282745 https://x.com/PatrickMoorhead/status/1990859751006351461 https://x.com/PatrickMoorhead/status/1990861596558774469 https://x.com/danielnewmanUV/status/1990848107223933309?s=20 Google Gemini 3 Launch https://blog.google/products/gemini/gemini-3/ https://x.com/danielnewmanUV/status/1990875878549512251 https://x.com/PatrickMoorhead/status/1991150119891223015 Yann LeCun Leaving Meta https://www.businessinsider.com/meta-ai-yann-lecun-llm-world-model-intelligence-criticism-2025-11  Pat & Dan interview with Yann LeCun at last year's Davos: https://youtu.be/0gmDufvWlWE  Cloudflare resolves outage that caused widespread internet disruptions, taking down X, ChatGPT for some users https://www.yahoo.com/news/article/cloudflare-resolves-outage-that-caused-widespread-internet-disruptions-taking-down-x-chatgpt-for-some-users-141316666.html OpenText World 2025 - Recap https://x.com/PatrickMoorhead/status/1990806348393554203 https://x.com/danielnewmanUV/status/1990805006661136469 Supercompute 2025 - Recap https://x.com/danielnewmanUV/status/1991231108646678537?s=20 The Flip: Can Google unseat OpenAI as the new benchmark of AI? (The Flip) Bulls & Bears Delayed September report shows U.S. added 119,000 jobs, more than expected; unemployment rate at 4.4% https://www.cnbc.com/2025/11/20/jobs-report-september-2025.html Fed minutes show divide over October rate cut and cast doubt about December https://www.cnbc.com/2025/11/19/fed-minutes-october-2025.html Lenovo Earnings https://news.lenovo.com/pressroom/press-releases/q2-fy-2025-26/ NVIDIA Earnings https://www.cnn.com/2025/11/19/tech/nvidia-earnings-ai-bubble-fears https://x.com/danielnewmanUV/status/1990526850171613211 https://x.com/danielnewmanUV/status/1990538832295702574 https://x.com/danielnewmanUV/status/1991156846900515130 https://x.com/PatrickMoorhead/status/1991544029675135247?s=20 https://x.com/PatrickMoorhead/status/1991540564794220778?s=20 Amazon Raises $15 Billion in First US Bond Sale in Three Years https://finance.yahoo.com/news/amazon-kicks-off-first-us-132051192.html Databricks in talk to raise at $130B valuation https://techcrunch.com/2025/11/18/databricks-reportedly-in-talks-to-raise-funding-at-a-130b-valuation/  

AGENDA: 04:20 Thrive and OpenAI Partnership  07:14 Databricks Raising $5BN at $134BN Valuation: Cheap or Not? 17:39 Eventbrite Acquired by Bending Spoons for $500M 21:39 Pagerduty's $1BN Market Cap, Just 2x Revenue 26:59 The TAM Trap: Why SaaS Is Like Japan 37:42 Lessons from Companies Hitting $100M ARR 44:57 The Future of Labour Markets is F****** 52:10 The Importance of Compounding in Investments 56:45 The Relevance Game in Venture Capital 01:05:01 Supabase at $5BN or Lovable at $6BN: Which One?  

Varun Puri, CEO and cofounder of Yoodli, joins the show to talk about using AI role play to transform how people practice for high stakes conversations, from sales calls to job interviews to tough manager chats. He breaks down how Yoodli went from a consumer public speaking tool to a serious enterprise platform used by teams at Google, Snowflake, Databricks, and more, all while staying anchored in one mission, helping humans communicate with confidence. We dig into product led growth, honest feedback loops, and why real human communication will matter even more as AI makes information instant.Key takeaways• Why Yoodli started with public speaking anxiety and grew into an AI role play simulator for any important conversation, not just conference talks or pitch decks• How watching real user behavior inside companies like Google pulled the team into enterprise without abandoning their consumer product• A simple approach to product feedback, talk to end users constantly, then prioritize changes by business impact, renewal risk, and how many people benefit• What it really takes to move from consumer to enterprise, new roles, new processes, and a very different mindset around reliability, security, and expectations• Why Varun draws clear ethical lines, using AI to coach and prepare people, not to replace human judgment in hiring, promotion, or high trust decisionsTimestamped highlights[00:35] What Yoodli actually does today, from solo practice to training sales and go to market teams inside large enterprises[01:43] The original vision, helping people who are scared of public speaking, and the insight that interviews, sales calls, and manager talks are all just role plays[03:37] How the team listens to end users, the channels they rely on, and why the consumer product is still their testing ground for new ideas and experiments[05:20] Following users into the enterprise, why it was an addition and not a full pivot, and how product led growth inside companies like Google works in practice[07:42] The early shock of selling to enterprises, learning about new roles, SLAs, InfoSec, and bringing in leaders from Tableau and Salesforce to build a real B2B engine[11:10] Two paths for AI in sales, tools that try to replace humans versus tools that make humans better, and why Varun has drawn a hard line on what Yoodli will not do[15:26] A future where information is commoditized and instant, and why communication and presence become the real edge for top performers in that world[20:48] Designing for trust and adoption, how Yoodli keeps practice private by default, when data is shared, and why control has to sit with the end userA line worth saving“In a world where AI makes everyone smarter and faster, the thing that will be at the biggest premium is how you communicate as a human with other humans.”Practical ideas you can use• Keep a consumer like surface in your product so you can experiment faster than your enterprise roadmap would ever allow• Treat feedback from large customers like a queue you rank by renewal risk, strategic value, and number of users helped, not as a list you must clear• Look for product led growth signals inside your user base, if thousands of people in one company are using you, someone there probably wants a team level solution• Draw explicit boundaries for your AI product, write down what you will not automate, so you can build trust with users and buyers over the long termCall to actionIf you care about the future of sales, interviewing, and communication in an AI rich world, this conversation is worth a listen. Follow the show, leave a quick rating, and share this episode with a founder, product leader, or sales leader who is thinking about AI in their workflow. And if you want feedback on your own speaking, check out what Varun and his team are building at Yoodli.

Send us a textInvest in pre-IPO stocks with AG Dillon & Co. Contact aaron.dillon@agdillon.com to learn more. Financial advisors only. www.agdillon.com00:06 - Databricks $134B Primary at 32x 2025E Sales02:20 - Revolut $75B Tender (+56% vs Aug 2025)04:30 - Physical Intelligence (Pi) $5B Primary (+>2.5x in

My guest today is David George. David is a General Partner at Andreessen Horowitz, where he leads the firm's growth investing business. His team has backed many of the defining companies of this era – including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI – and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. This conversation is a detailed look at how David built and runs the a16z growth practice. He shares how he recruits and builds his team a “Yankees-level” culture, how his team makes investment decisions without traditional committees, and how they work with founders years before investing to win the most competitive deals. Much of our conversation centers on AI and how his team is investing across the stack, from foundational models to applications. David draws parallels to past platform shifts – from SaaS to mobile – and explains why he believes this period will produce some of the largest companies ever built. David also outlines the models that guide his approach – why markets often misprice consistent growth, what makes “pull” businesses so powerful, and why most great tech markets end up winner-take-all. David reflects on what he's learned from studying exceptional founders and why he's drawn to a particular type, the “technical terminator.” Please enjoy my conversation with David George. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp's mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ramp.com/invest to sign up for free and get a $250 welcome bonus. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. ----- This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like The Best (00:04:00) Meet David George (00:03:04) Understanding the Impact of AI on Consumers and Enterprises (00:05:56) Monetizing AI: What is AI's Business Model (00:11:04) Investing in Robotics and American Dynamism (00:13:31) Lessons from Investing in Waymo (00:15:55) Investment Philosophy and Strategy (00:17:15) Investing in Technical Terminators (00:20:18) Market Leaders Capture All of the Value Creation (00:24:56) The Maturation of VC and Competitive Landscape (00:28:18) What a16z Does to Win Deals (00:33:06) David's Daily Routine: Meetings Structure and Blocking Time to Think (00:36:34) Why David Invests: Curiosity and Competition (00:40:12) The Unique Culture at Andreessen Horowitz (00:42:46) The Perfect Conditions for Growth Investing (00:47:04) Push v. Pull Businesses (00:49:19) The Three Metrics a16z Uses to Evaluate AI Companies (00:52:15) Unique Products and Unique Distribution (00:54:55) Tradeoffs of the a16z Firm Structure (00:59:04) a16z's Semi-Algorithmic Approach to Selling (01:00:54) Three Ways Startups can Beat Incumbents in AI (01:03:44) The Kindest Thing

The Department of Heath and Human Services has been leaning into the use of artificial intelligence to drive better health outcomes for the American public, highlighted by the rollout of ChatGPT across the agency early this fall. In particular, the Centers for Disease Control and Prevention has been a leader in generative AI adoption since 2023. And Travis Hoppe, CDC's chief AI officer, believes AI innovation can continue to move the needle on public health operations. Hoppe joined me recently onstage at FedTalks to share the latest on CDC's AI journey, how the Trump administration's AI Action Plan is guiding the agency's implementation and what's next. The National Nuclear Security Administration is looking for information on potential AI uses for its mission, following an executive order to establish an integrated AI platform that will fuel scientific discovery. In a request for information posted to SAM.gov on Monday, the Department of Energy subcomponent that oversees the nation's nuclear stockpile said it's exploring the use of the budding technology, and specifically requested information about its use in classified environments, best practices for data curation, and how to approach developing and enhancing AI models, among other things. The request comes just a week after the Trump administration launched the “Genesis Mission,” aimed at scientific discovery through AI. That effort will not only create an AI platform for such discovery, but it will also depend on the country's existing research and development infrastructure, including DOE and its national labs. To further the Genesis program, NNSA said it's proactively exploring the use of AI for its “critical operations to accelerate nuclear weapons development timelines, ensuring our deterrent remains responsive, effective, and state-of-the-art against evolving global threats.” Software company SAP inked a new agreement with the General Services Administration to offer federal agencies access to its services at significantly discounted rates, deepening its longstanding partnership with the federal government. The GSA announced the OneGov deal Tuesday, stating that the agreement offers up to 80 percent discounts on SAP's database, cloud, and analytics services. The agency estimated this will lead to $165 million in savings for federal agencies. Specifically, agencies will be able to access products related to SAP's database and data management services with an 80 percent discount. SAP's cloud services, including SAP Business Technology Platform, SAP Analytics Cloud and HR Payroll, will be offered at a 35 percent discount, GSA said. Also in this episode: Databricks VP of Public Sector Todd Schroeder joins SNG host Wyatt Kash in a sponsored podcast discussion on why agencies are prioritizing the use of AI that works across existing data environments, saving time and infrastructure costs. This segment was sponsored by Databricks. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

The 5 things you need to know before the stock market opens today: President Trump says he's made his choice for next chair of the Federal Reserve, Disney had brought in more than $500 million globally on the “Zootopia 2” box office, South Korean police are investigating a data breach at e-commerce site Coupang, data analytics firm Databricks is in talks to raise $5 billion at a valuation topping $134 billion, and UnitedHealth Group will reportedly sell off its last South American business. Squawk Box is hosted by Joe Kernen, Becky Quick and Andrew Ross Sorkin.  Follow Squawk Pod for the best moments, interviews and analysis from our TV show in an audio-first format. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this special Cloud Wars report, Bob Evans sits down with Michael Ameling, President and Chief Product Officer of SAP Business Technology Platform, for a deep dive into how SAP is helping customers navigate the fast-moving AI Era. Ameling and Evans discuss how SAP's Business Data Cloud, partnerships with Snowflake and Databricks, HANA Cloud innovations, and new AI-powered tools and agents are helping SAP evolve from an applications powerhouse into a data-and-AI-driven business platform for the next generation.SAP's AI Data FutureThe Big Themes:SAP HANA Cloud Becomes an AI-Optimized Database: SAP HANA Cloud is evolving into “the database AI was looking for." As a multi-model system supporting spatial, graph, vector, and document storage, HANA Cloud enables AI workloads to run more efficiently and contextually. Recent additions, like vector engines and Knowledge Graph capabilities, give customers powerful tools for retrieval-augmented generation (RAG), contextual reasoning, and advanced analytics.Developers Are 'The AI Revolution': Developers aren't observing the AI Revolution, they are the revolution. With modern AI tools, developers can innovate faster, solve bigger problems, and directly influence business outcomes. SAP is investing heavily in meeting developers where they are by enhancing IDEs, building business-aware development tools, and providing context-rich assets such as APIs, business objects, and process insights. AI acts as a teammate, not a replacement.SAP: An Applications and a Data Company: SAP must be both an applications and a data company. Customer value emerges when applications, data, and AI converge seamlessly. SAP's decades of industry expertise give it unparalleled business context, which becomes even more powerful when embedded into AI agents and data platforms. With more than 34,000 SAP HANA Cloud customers and rapidly expanding AI adoption, SAP is positioning itself as the platform where business process knowledge meets modern AI capability.The Big Quote: " . . what we need to understand that AI is our teammate. It's like asking your best friend who has a lot of knowledge, but you can ask multiple friends at the same time. Not everything is always right, but you can ask questions, you can continuously improve. If we understand that pattern, we understand that AI helps us to solve much bigger problems as a developer, and then, of course, having much more impact on real business."More from Michael Ameling and SAP:Connect with Michael Ameling on LinkedIn, or get more insights from SAP TechEd.  Visit Cloud Wars for more.

Todd Schroeder of Databricks explains how AI and recent tech innovations enable federal agencies to bring AI to widely distributed data, instead of moving data to applications, reducing costs, improving security and accelerating decision making.

What happened with Cloudflare this morning. Grok's new model wants to be creative. Catching you up on the bloodbath in crypto if you were unaware. Databricks is 12 years old but it seems to be one of the big AI winners. And debt continues to pile in to the AI buildout. A massive Cloudflare outage brought down X, ChatGPT, and even Downdetector (The Verge) Grok 4.1 has arrived — and it's bringing the fight to ChatGPT with these new features (Tom's Guide) Crypto market sheds $1.2tn as traders shun speculative assets (Financial Times) Google boss says trillion-dollar AI investment boom has 'elements of irrationality' (BBC) Amazon Raises $15 Billion in First US Bond Sale in Three Years (Bloomberg) Databricks in Talks to Raise Capital at a Valuation Above $130 Billion (The Information) Roblox will require age estimation to chat starting next year (The Verge) Learn more about your ad choices. Visit megaphone.fm/adchoices

In today's episode, I'm talking with Andrew Wilhelms, VP of Talent Management at Databricks and a seasoned leader with a wealth of experience from organizations like Twilio and Tesla. In t his conversation, we explore the evolving world of talent development and break down the difference between building individual capabilities and managing organizational systems, and why understanding both is crucial in today's dynamic business landscape.Andrew also shares insights from his unique journey, including how his philosophy background shaped his approach to leadership, what he believes actually transforms good teams into high-performing ones, and why the next wave of talent will require us all—no matter our title—to start thinking (and leading) like executives. They also dig into the impact of AI on both work and leadership, the importance of designing a positive employee experience, and practical ways to move beyond “knowing” to actually “doing” when it comes to developing great leaders.Key Notes and topics we cover in this episode:The Nature of LeadershipPreparing Future LeadersChallenges in Corporate LeadershipTalent Management vs. Talent DevelopmentThe Next Paradigm Shift in Talent: AIAI and Tools in Talent DevelopmentThe “Brickster Experience” at DatabricksPsychological Safety and Growth MindsetManager and Leadership Development ModelsCareer Development PhilosophyLessons Learned & ReflectionsTalent Development TrendsRecommended ResourcesCareer Advice for Talent ProfessionalsThis episode is also sponsored by LearnIt, which is offering a FREE trial of their TeamPass membership for you and up to 20 team members of your team. Check it out here.Connect with Andy here: Website | LinkedInConnect with Andrew Wilhelms here: LinkedInOrder my new book, Own Your Brand, Own Your Career on AmazonAnd my first book, Own Your Career Own Your Life, is on Amazon as well.

S&P futures are down (0.3%) and pointing to a slightly lower open today. Asian equities ended Tuesday trading broadly lower, with the Nikkei leading the declines, down over (3%), followed by the Greater China markets. Markets saw steep losses in large-cap tech and semiconductors ahead of NVIDIA's earnings on Wednesday. Concerns are mounting over high valuations in AI-related stocks, a key driver of this year's market rally. European markets are also sliding now, with the STOXX 600 down (1.2%). Companies Mentioned: NVIDIA, Axalta Coating Systems, Databricks

Unlocking Healthcare Data: Expert Insights from Jason Bryll of Parable AssociatesIn this episode, host Josh Elledge interviews Jason Bryll, Founder and CEO of Parable Associates, a company helping healthcare organizations harness their data for growth, efficiency, and better patient outcomes. Jason discusses how healthcare's complex data systems—spanning patients, payers, and providers—can be transformed into powerful strategic assets. The conversation explores modern data infrastructure, AI adoption, and how healthcare leaders can turn information into action.Turning Healthcare Data into a Strategic AdvantageJason explains that healthcare organizations deal with some of the most fragmented and regulated data ecosystems of any industry. With multiple payment sources, strict HIPAA compliance, and disconnected systems, many practices struggle to translate data into actionable insights. Through Parable Associates, Jason helps clients design robust, scalable data infrastructures that unify information from EHRs, practice management tools, and claims systems to create real-time visibility into operations.He highlights how modern tools like Microsoft Fabric, Databricks, and Snowflake are transforming how providers process and analyze information. By automating data pipelines, implementing AI-driven analytics, and empowering teams with dashboards, healthcare organizations can reduce claim denials, improve revenue cycles, and accelerate cash flow. Jason emphasizes that true transformation begins with data governance—ensuring clean, accessible, and secure data before layering on advanced analytics.Ultimately, Parable's approach is rooted in measurable ROI. From reducing days sales outstanding (DSO) to uncovering revenue bottlenecks, their systems deliver tangible results. Jason advises healthcare executives to start with a specific business problem—such as cash flow or patient scheduling—and build data strategies around it. “Better reporting is like giving staff a utility belt,” he says. “It equips them to solve problems faster and with more confidence.”About Jason BryllJason Bryll is the Founder and CEO of Parable Associates, where he helps large healthcare organizations transform fragmented data into operational insights. With deep experience in analytics, systems design, and healthcare finance, Jason has worked with providers nationwide to improve data quality, cash flow, and performance through tailored, scalable solutions.About Parable AssociatesParable Associates specializes in healthcare analytics and data engineering, helping medical groups, hospitals, and specialty providers build scalable data ecosystems. The firm designs client-owned systems that unify data across clinical, operational, and financial functions, delivering clear insights and measurable ROI. Learn more at parableassociates.com.Links Mentioned in This EpisodeParable AssociatesConnect with Jason Bryll on LinkedInKey Episode HighlightsWhy healthcare data is uniquely complex and siloedHow to build scalable, secure data infrastructureUsing analytics to improve cash flow and reduce claim delaysPractical applications of AI and modern BI platformsHow Parable Associates delivers measurable ROI through dataActionable advice for healthcare leaders and data teamsConclusionJason Bryll's insights...

Marc Barnes believes that AI chatbots are evil, and that having a faux conversation with AI chatbots is wrong. Joseph Hobbs, Senior Solution Architect at Databricks, disagrees. In this podcast, they discuss the nature of conversation, how AI imitates conversation, and the Catholic response to AI Chatbots.

Dhanji R. Prasanna is the chief technology officer at Block (formerly Square), where he's managed more than 4,000 engineers over the past two years. Under his leadership, Block has become one of the most AI-native large companies in the world. Before becoming CTO, Dhanji wrote an “AI manifesto” to CEO Jack Dorsey that sparked a company-wide transformation (and his promotion to CTO).We discuss:1. How Block's internal open-source agent, called Goose, is saving employees 8 to 10 hours weekly2. How the company measures AI productivity gains across technical and non-technical teams3. Which teams are benefiting most from AI (it's not engineering)4. The boring organizational change that boosted productivity even more than AI tools5. Why code quality has almost nothing to do with product success6. How to drive AI adoption throughout an organization (hint: leadership needs to use the tools daily)7. Lessons from building Google Wave, Google+, and other failed products—Brought to you by:Sinch—Build messaging, email, and calling into your product: https://sinch.com/lennyFigma Make—A prompt-to-code tool for making ideas real: https://www.figma.com/lenny/Persona—A global leader in digital identity verification: https://withpersona.com/lenny—Where to find Dhanji R. Prasanna:• LinkedIn: https://www.linkedin.com/in/dhanji/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Dhanji(05:26) The AI manifesto: convincing Jack Dorsey(07:33) Transforming into a more AI-native company(12:05) How engineering teams work differently today(15:24) Goose: Block's open-source AI agent(20:18) Measuring AI productivity gains across teams(21:38) What Goose is and how it works(32:15) The future of AI in engineering and productivity(37:42) The importance of human taste(40:10) Building vs. buying software(44:08) How AI is changing hiring and team structure(53:45) The importance of using AI tools yourself before deploying them(55:13) How Goose helped solve a personal problem with receipts(58:01) What makes Goose unique(59:57) What Dhanji wishes he knew before becoming CTO(01:01:49) Counterintuitive lessons in product development(01:04:56) Why controlled chaos can be good for engineering teams(01:08:07) Core leadership lessons(01:13:36) Failure corner(01:15:50) Lightning round and final thoughts—Referenced:• Jack Dorsey on X: https://x.com/jack• Block: https://block.xyz/• Square: https://squareup.com/• Cash App: https://cash.app/• What is Conway's Law?: https://www.microsoft.com/en-us/microsoft-365-life-hacks/organization/what-is-conways-law#• Goose: https://github.com/block/goose• Gosling: https://github.com/block/goose-mobile• Salesforce: https://www.salesforce.com/• Snowflake: https://www.snowflake.com/• Claude: https://claude.ai/• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann• OpenAI: https://openai.com/• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Llama: https://www.llama.com/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Top Gun: https://www.imdb.com/title/tt0092099/• Lenny's vibe-coded Lovable app: https://gdoc-images-grab.lovable.app/• Afterpay: https://github.com/afterpay• Bitkey: https://bitkey.world/• Proto: https://github.com/proto-at-block• Brad Axen on LinkedIn: https://www.linkedin.com/in/bradleyaxen/• Databricks: https://www.databricks.com/• Carl Sagan's quote: https://www.goodreads.com/quotes/32952-if-you-wish-to-make-an-apple-pie-from-scratch• Google Wave: https://en.wikipedia.org/wiki/Google_Wave• Google Video: https://en.wikipedia.org/wiki/Google_Video• Secret: https://en.wikipedia.org/wiki/Secret_(app)• Alien Earth on FX: https://www.fxnetworks.com/shows/alien-earth• Slow Horses on AppleTV+: https://tv.apple.com/us/show/slow-horses/umc.cmc.2szz3fdt71tl1ulnbp8utgq5o• Fargo TV series on Prime Video: https://www.amazon.com/Fargo-Season-1/dp/B09QGRGH6M• Steam Deck OLED display: https://www.steamdeck.com/en/oled• Doc Brown: https://backtothefuture.fandom.com/wiki/Emmett_Brown—Recommended books:• The Master and Margarita: https://www.amazon.com/Master-Margarita-Mikhail-Bulgakov/dp/0802130119• Tennyson Poems: https://www.amazon.com/Tennyson-Poems-Everymans-Library-Pocket/dp/1400041872/Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed.My biggest takeaways from this conversation: To hear more, visit www.lennysnewsletter.com