POPULARITY
Categories
93 episodes with Rag
66 episodes with Rag
42 episodes with Rag
42 episodes with Rag
53 episodes with Rag
26 episodes with Rag
26 episodes with Rag
28 episodes with Rag
14 episodes with Rag
19 episodes with Rag
13 episodes with Rag
24 episodes with Rag
8 episodes with Rag
7 episodes with Rag
13 episodes with Rag
12 episodes with Rag
9 episodes with Rag
12 episodes with Rag
12 episodes with Rag
7 episodes with Rag
9 episodes with Rag
9 episodes with Rag
7 episodes with Rag
11 episodes with Rag
12 episodes with Rag
13 episodes with Rag
7 episodes with Rag
18 episodes with Rag
3 episodes with Rag
3 episodes with Rag
5 episodes with Rag
7 episodes with Rag
4 episodes with Rag
5 episodes with Rag
5 episodes with Rag
4 episodes with Rag
4 episodes with Rag
11 episodes with Rag
5 episodes with Rag
4 episodes with Rag
8 episodes with Rag
6 episodes with Rag
5 episodes with Rag
11 episodes with Rag
8 episodes with Rag
9 episodes with Rag
3 episodes with Rag
5 episodes with Rag
6 episodes with Rag
3 episodes with Rag
2 episodes with Rag
3 episodes with Rag
2 episodes with Rag
4 episodes with Rag
Luke Marsden, CEO and Founder, HelixML talks about Private GenAI. What is it? Why do you need it? We also discuss integration into CI/CD pipelines, the layers of a Private GenAI Stack, and why most organizations are opting for RAG over fine-tuning LLMs.SHOW: 943SHOW TRANSCRIPT: The Cloudcast #943 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" SPONSORS:[DoIT] Visit doit.com (that's d-o-i-t.com) to unlock intent-aware FinOps at scale with DoiT Cloud Intelligence.[FCTR] Try FCTR.io (that's F-C-T-R dot io) free for 60 days. Modern security demands modern solutions. Check out Fctr's Tako AI, the first AI agent for Okta, on their website[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.SHOW NOTES:HelixML websiteHelixML GitHubHelix 1.0 Announcement BlogTopic 1 - Welcome to the show Luke. Give everyone a brief intro.Topic 2 - Let's start with Priavte GenAI. What is it? Why should organizations out there consider it? Why not just use OpenAI GPT's and fine tune them?Topic 2a Follow up - Regulatory Compliance - take the opposing forces in the EU for instance to using SaaS based services based in the United States.Topic 3 - Let's break down the layers in a typical Private AI stack. I'm seen various ways to represent this such as infrastructure layer, MLOps layer, models, data layer (typically RAG), etc. How do you break up the stack into individual componentsTopic 4 - My mind immediately jumps to similarities in the DevOps space. Abstraction layers and components like Docker and containers comes to mind, integration into CI/CD pipelines, etc. I feel like MLOps is it's own thing with specific tools and workflows. Does this all come together and if so how?Topic 5 - Also, what does this mean for versioning and lifecycle management of the models and the data?Topic 6 - We are seeing more and more data pipelines with backed by multiple models, sometimes in multiple locations. How do handle this from both a scheduling and interface standpoint? Is everything hidden behind APIs for instance?Topic 7 - If anyone is interested, what's the best way to get started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod
Episode: 3321 Scott Joplin persevered in creating Ragtime music as a black musician in post-Civil War America. . Today, Joplin and Ragtime.
Scott and Wes break down how to code with and for AI; perfect for skeptics, beginners, and curious devs. They cover everything from Ghost Text and CLI agents to building your own AI-powered apps with embeddings, function calling, and multi-model workflows. Show Notes 00:00 Welcome to Syntax! 03:56 How to interface with AI. 04:07 IDE Ghost Text. 05:45 IDE Chat, Agents. 08:00 CLI Agents. Claude Code. Open Code. Gemini. 11:13 MCP Servers. Context7 14:47 GUI apps. v0. Bolt.new. Lovable. Windsurf. 19:07 Existing Chat app like ChatGPT. 22:37 Building things WITH AI. 23:32 Prompting. 26:53 Streaming VS not streaming. 28:14 Embeddings and Rag. 31:09 MCP Server. CJ's MCP Deep Dive. 32:36 Brought to you by Sentry.io. 33:25 Multi-model, multi-provider. 36:27 npm libs to use to code with AI. OpenAI SDK. AI SDK. Cloudflare Agents. Langchain. Local AI Tensorflow. Transformers.js. Huggingface. 44:12 Processes and exploring. Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads
1 - Swing Out, Uncle Wilson - The Three Peppers – 19382 - Down T' Uncle Bill's - Chick Bullock with Todd Rollins and his Orchestra - 19343 - Uncle Eph's Dream - Skeets Tolbert and his Gentlemen of Swing – 19414 - I Got an Uncle in Harlem - Hot Lips Page - 19495 - We All Love Uncle Joe - Fred Harrison6 - How's Your Uncle - The High Steppers - 19317 - When Uncle Joe Plays a Rag on His Old Banjo - Arthur Collins – 19128 - Uncle Bud - Billy Jones with Tampa Blue Jazz Band - 19219 - Uncle Bud - Erskine Hawkins (The Twentieth Century Gabriel) and his Orchestra – 194110 - Uncle George - Herb Greggerson with Slim and his Country Cousins11 - Aunt Patsy - Prince's Band – 191612 - Uncle Harry - Noel Coward - 195513 - Shout 'Em Aunt Tillie - Duke Ellington and his Orchestra – 193014 - The Little Brown Suit My Uncle Bought Me - Sgt. "Ace" Goodrich - 194315 - He's My Uncle - Rose Blane with Abe Lyman and his Californians – 194016 - Bop's Your Uncle - George Shearing – 1948
Hey everyone, Alex here
Saoud Rizwan and Pash from Cline joined us to talk about why fast apply models got bitter lesson'd, how they pioneered the plan + act paradigm for coding, and why non-technical people use IDEs to do marketing and generate slides. Full writeup: https://www.latent.space/p/cline X: https://x.com/latentspacepod Chapters: 00:00 - Introductions 01:35 - Plan and Act Paradigm 05:37 - Model Evaluation and Early Development of Cline 08:14 - Use Cases of Cline Beyond Coding 09:09 - Why Cline is a VS Code Extension and Not a Fork 12:07 - Economic Value of Programming Agents 16:07 - Early Adoption for MCPs 19:35 - Local vs Remote MCP Servers 22:10 - Anthropic's Role in MCP Registry 22:49 - Most Popular MCPs and Their Use Cases 25:26 - Challenges and Future of MCP Monetization 27:32 - Security and Trust Issues with MCPs 28:56 - Alternative History Without MCP 29:43 - Market Positioning of Coding Agents and IDE Integration Matrix 32:57 - Visibility and Autonomy in Coding Agents 35:21 - Evolving Definition of Complexity in Programming Tasks 38:16 - Forks of Cline and Open Source Regrets 40:07 - Simplicity vs Complexity in Agent Design 46:33 - How Fast Apply Got Bitter Lesson'd 49:12 - Cline's Business Model and Bring-Your-Own-API-Key Approach 54:18 - Integration with OpenRouter and Enterprise Infrastructure 55:32 - Impact of Declining Model Costs 57:48 - Background Agents and Multi-Agent Systems 1:00:42 - Vision and Multi-Modalities 1:01:07 - State of Context Engineering 1:07:37 - Memory Systems in Coding Agents 1:10:14 - Standardizing Rules Files Across Agent Tools 1:11:16 - Cline's Personality and Anthropomorphization 1:12:55 - Hiring at Cline and Team Culture Chapters 00:00:00 Introduction and Guest Intros 00:00:29 What is Klein? Product Overview 00:01:42 Plan and Act Paradigm 00:05:22 Model Evolution and Building Klein 00:07:40 Beyond Coding: Klein as a General Agent 00:09:12 Why Focus on VS Code Extension? 00:11:26 The Future of Programming and Agentic Paradigm 00:12:34 Economic Value: Programming vs. Other Use Cases 00:16:04 MCP Ecosystem: Growth and Marketplace 00:21:30 Security, Discoverability, and Trust in MCPs 00:22:55 Popular MCPs and Workflow Automation 00:25:30 Monetization and Payments for MCPs 00:37:53 Competition, Forks, and Open Source Philosophy 00:40:39 RAG, Fast Apply, and Agentic Simplicity 00:50:11 Business Model and Enterprise Adoption 00:57:04 Background Agents, Multi-Agent Systems, and CLI 01:00:41 Context Engineering and Memory 01:12:39 Team, Culture, and Closing Thoughts
The poem I read at the beginning called Crying For A Vision at Ghost Ranch will be part of a new collection called Where Do Dreams Come From? The poem that Simon reads is A Man Lost By A River by Michael Blumenthal from the anthology, The Rag and Bone Shop of the Heart, edited by Robert Bly, James Hillman, and Michael Meade. The poem Ben reads is one of his own and it is called We Need Artists Today. If you want to know more about the Male Journey - the Men's work we have all been involved in go to https://www.malejourney.org.uk/ With massive thanks to Ben and Simon. Here is Ben's - Poet Facebook Page https://www.facebook.com/BenBurnsPoet/ Here is Simon's Agent's page https://hatchtalent.co.uk/actors/simon-bubb/
Would you walk away from recurring revenue to chase a bigger opportunity overseas?On this week's episode of The RAG Podcast, I'm joined by Jamie Trevett, founder of Just Construction. Jamie was last on the show in 2022 when his UK construction recruitment firm had 25 staff and a growing contract book.Fast forward to today and Jamie has completely transformed the business. He shut down the contract side in the UK and relocated the company's focus to the US market, where he now runs a similarly sized team doing 95% of their work stateside.In this episode, we discuss:Why he made the bold decision to leave the UK market behindThe operational and cultural shifts required to succeed in the USHow time zones and remote management work across continentsThe growing influence of AI on recruitment deliveryWhat the future could look like for Just Construction, including a potential saleIf you're thinking about scaling into the US or questioning how to futureproof your business in a changing market, you'll get real insight from this one.Chapters00:00 Introduction to Jamie Trevett and Just Construction02:59 Transitioning from the UK to the US Market05:56 Challenges in the UK Construction Recruitment Market08:49 Shutting Down the Contract Side of the Business12:07 Building a Stronger Focus on Permanent Recruitment14:57 Navigating Time Zones and Work Arrangements17:53 Strategies for Expanding into the US Market21:04 The Impact of AI on Recruitment23:43 Future Plans and Potential Sale of the Business__________________________________________Episode Sponsor: AtlasYour memory isn't perfect. So Atlas remembers everything for you. Atlas is an end-to-end recruitment platform built for the AI generation. It automates your admin so you can focus on the business tasks that matter. How many conversations do you have every day? With clients. Candidates. Your team. Service providers.Now how many of those conversations can you recall with 100% accuracy? How many hours a week do you spend making notes to try and retain as much as possible? And how much is still getting lost along the way? Traditional CRM systems weren't built for the type of recruitment business you're running right now. They were built to rely on the structured, tagged, categorised, and formal data you could feed it. Manual processes that needed you to input specific information, based on specific questions and answers. But what about all the other conversations you're having every single day? Atlas isn't an ATS or a CRM. It's an Intelligent Business Platform that helps you perform 10X better than you could on your own. How? By removing all your low value tasks, acting as your perfect memory, and providing highly relevant recommendations to impact your performance. Learn more about the power of Atlas – and take advantage of the exclusive offer for The RAG listeners – by visiting https://recruitwithatlas.com/therag/ __________________________________________Episode Sponsor: HoxoRecruitment agency founders - this one's for you.What's your plan for the rest of 2025?If it's based on more cold outreach, referrals, or hiring more recruiters… we've got news for you. That's not where the smart money is going.The market has changed. AI is everywhere. Noise is louder than ever.So if you want to scale profitably this year, you need to do things differently!It starts with what you already have.Your experience. Your network. Your voice.And we are showing you exactly how to use it in a...
Software Engineering Radio - The Podcast for Professional Software Developers
Jacob Visovatti and Conner Goodrum of Deepgram speak with host Kanchan Shringi about testing ML models for enterprise use and why it's critical for product reliability and quality. They discuss the challenges of testing machine learning models in enterprise environments, especially in foundational AI contexts. The conversation particularly highlights the differences in testing needs between companies that build ML models from scratch and those that rely on existing infrastructure. Jacob and Conner describe how testing is more complex in ML systems due to unstructured inputs, varied data distribution, and real-time use cases, in contrast to traditional software testing frameworks such as the testing pyramid. To address the difficulty of ensuring LLM quality, they advocate for iterative feedback loops, robust observability, and production-like testing environments. Both guests underscore that testing and quality assurance are interdisciplinary efforts that involve data scientists, ML engineers, software engineers, and product managers. Finally, this episode touches on the importance of synthetic data generation, fuzz testing, automated retraining pipelines, and responsible model deployment—especially when handling sensitive or regulated enterprise data. Brought to you by IEEE Computer Society and IEEE Software magazine.
Send us a textIn this episode we interview Dave Davies, Senior SEO expert and AI strategist at Weights & Biases, a leading AI tool manufacturer.What you'll learn in this episode:How generative engines are transforming SEO, content strategy, and attribution modelsTactical SEO differences between Bing and Google in a generative-first search eraWhy agents and retrieval-augmented generation (RAG) will shift buyer behaviorPractical content formatting tips that help LLMs surface your work fasterWhen and how to write for humans versus writing for generative systemsHow to prepare for the agent-to-agent protocol revolution and structured data indexingWhy CCbot (common crawl) access is essential to your visibility in AI models
In this episode, I share how I built SteveBot, a custom AI assistant powered by a RAG database that mimics every lesson that I’ve ever taught. I break down the tech stack, the biggest mistakes made, and how this changes the classes I teach. What You’ll Learn How I built my AI Bot from my course, blog, and podcast The cool tech that makes it all work seamlessly Tips to create your own AI-powered project easily Sponsors SellersSummit.com – The Sellers Summit is the ecommerce conference that I’ve run for the past 8 years. It’s small and intimate and you’ll […] The post 598: I Turned My Course, Blog, And Podcast Into An AI Bot – Here's The Tech Behind It appeared first on MyWifeQuitHerJob.com.
Listen now: Spotify, Apple and YouTubeWhat if you had a personalized AI toolkit—not just a chatbot—that actually remembered your projects, your workflows, and even your family's preferences?In this episode, Marc and Ben sit down with Mike Bal, a product leader experimenting at the frontier of AI tooling. Mike shares how he built a local memory system for Claude using Model Context Protocols (MCPs), enabling persistent knowledge graphs that connect everything from his product designs to his family's vacation plans. They walk through how it works—step-by-step—including a live demo of Fleur (essentially a mini app marketplace to make it easy for non technical people to add MCPs to Claude), how Mike structures entities and relationships, and why this setup beats traditional RAG approaches for real-world usage.If you've ever wanted your AI to truly understand you and the work you do—or you're curious how a product leader uses AI to streamline everything from design reviews to family logistics—this episode is packed with real-world inspiration and actionable examples.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox
SINOSSIPuntata doppia (più di 20 minuti) per commentare le ultime settimane di avvenimenti.- Lo chef Paolo Cappuccio e l'offerta di lavoro che ha fatto il giro d'Italia, ma che è un esempio di pessima gestione della propria reputazione prima ancora di un pessimo esempio imprenditoriale.- Il "bonus caldo" di Glovo e Deliveroo, apparentemente ritirato dopo le tantissime polemiche, ma non troppo.- Il cedimento dell'insegna Generali ha dato lo spunto per riflettere sul senso del potere di certe aziende e il loro modello di comunicazione.- Il caporalato nei campi della Lombardia gestito da Bocconiani e professionisti.- Ma anche il caporalato fra i barbieri di Firenze- I numeri sulla sicurezza e sulla legalità in Lombardia, sono ben lontani da quella che si vuol definire "la capitale del lavoro".ARTICOLI E NOTIZIE PER APPROFONDIRE:La terribile inserzione dello chef Paolo CappuccioLa startupper che lavora nella cabina telefonicaLa startupper risponde (malissimo) alle criticheI colleghi della startupper continuano a pubblicare post discutibiliA proposito del bonus caldo per i riderIl punto di vista dei riderUn po' di commenti sul cedimento dell'insegna GeneraliIl fondatore di Straberry rischia un altro processoSicurezza sul lavoro in Lombardia, 7 aziende su 10 sono irregolari. E in un anno 184 casi di caporalatoCaporalato dal barbiere, sfruttati a 3 euro l'oraNon avrAI altro Dio - Il podcast di Nicoletta PrandiUniVersi - il podcast di Speexx prodotto da SenzaFiltroESTRATTI AUDIOLeonardo di Caprio: Wolf of Wall StreetLe coliche: Caldo TorridoCoro dell'Antoniano: Il lungo, il corto e il paciocconeMilanese Imbruttito: Agosto a MilanoLa musica del trailer è "Humans" di Rag'n' Bone Mane per tutte sono stati regolarmente pagati i diritti SIAELe musiche dell'inciso è:Raw - Nonsense Diventa un supporter di questo podcast: https://www.spreaker.com/podcast/umane-risorse-osvaldo-danzi--5744881/support.
Ari Paparo and Eric Franchi speak with Adam Epstein, co-founder and CEO of Gigi, an AI assistant focused on automating tasks within the Amazon DSP. Adam shares how the product evolved from a streaming TV tool to a broader AI-powered platform for media agencies. He discusses the challenges of training a vertical AI agent using retrieval-augmented generation (RAG), the reasoning behind a chat-based interface, and how agencies are integrating their own processes into Gigi. The conversation also touches on the potential impact of agentic AI on agency workflows and team structures. Learn more about your ad choices. Visit megaphone.fm/adchoices
ALEATORIO RANDOM PROJECT 030 1- WHAT DO YOU BELIEVE IN? – RAG´N´BONE MAN 2- NO PENSAR NUNCA EN LA MUERTE – MAYTE MARTIN 3- THE BLUEST BLUES – ALVIN LEE 4- TIFLA ANDALUSIYA – AMSTERDAM ANDALUSIAN ORCHESTRA 5- COMO EL AGUA – CAMARON DE LA ISLA & PACO DE LUCIA 6- YO ME QUEDO EN SEVILLA – PATA NEGRA 7- HOMESICK – ATLANTA RHYTHM SECTION 8- LOUISIANA ZYDECO – CLARENCE GATEMOUTH BROWN 9- EVIL WOMAN – ELECTRIC LIGHT ORCHESTRA 10- YOU CAN´T ALWAYS GET WHAT YOU WANT – THE ROLLING STONES 11- I HEARD IT THROUGH THE GRAPEVINE – MARVIN GAYE 12- BASIT 1º MOUVEMENT TUSHIYA – ORCHESTRE AL BRIHI DE FES 13- THE PATH – CONCEP NEUF 14- ¿??
Dans ce nouvel épisode de "IA pas que la Data", Pierre Vannier et Thomas Meimoun reçoivent Yann Leger, le co-fondateur de Koyeb, une plateforme serverless qui révolutionne le déploiement d'applications, en particulier celles liées à l'IA.On plonge au cœur de l'action pour explorer :
What's the point in building a business if you lose everything at home?On this week's episode of The RAG Podcast, I'm joined by Matt Tyson, founder of Knockout Consulting and former owner of two successful payroll companies.Matt has achieved what many founders dream of—two life-changing exits in 15 years. But behind the success was a personal cost he never expected. In his pursuit of business growth, he lost sight of the very reason he started—his family.In this deeply honest conversation, we discuss:How Matt built and exited two payroll businessesThe pressure of selling a company during uncertain timesWhat he'd do differently to protect his marriage and mental healthWhy emotional balance matters just as much as financial goalsStrategies for building a business that doesn't cost you everything elseIf you're a founder chasing an exit or deep in growth mode, this is a powerful reminder to check in on what really matters.Chapters00:00 Introduction to Growth and Balance02:52 Matt Tyson's Journey and Business Philosophy06:03 Transition from Banking to Payroll09:08 Building and Exiting Businesses12:01 The Importance of Compliance and Contractor Welfare14:54 Navigating Business Growth and Personal Life17:47 The Emotional Impact of Business Success20:54 The Role of Family and Support Systems23:49 Establishing Walker Smith and Growth Strategies27:01 Innovations in Contractor Support29:41 The Journey of Building a Group of Businesses32:56 Recognizing Personal Struggles and Changes35:48 Reflections on Work-Life Balance38:43 Conclusion and Lessons Learned42:43 Navigating Business Exits During Uncertain Times45:38 The Importance of Financial Control and Cost Management49:27 Identity and Purpose After Selling a Business50:39 The Emotional Impact of Business Transitions56:52 Lessons Learned from Personal Relationships and Business01:00:44 Finding Balance: Work, Life, and Personal Fulfillment01:09:29 Key Strategies for Business Growth and Exit Planning__________________________________________Episode Sponsor: AtlasYour memory isn't perfect. So Atlas remembers everything for you. Atlas is an end-to-end recruitment platform built for the AI generation. It automates your admin so you can focus on the business tasks that matter. How many conversations do you have every day? With clients. Candidates. Your team. Service providers.Now how many of those conversations can you recall with 100% accuracy? How many hours a week do you spend making notes to try and retain as much as possible? And how much is still getting lost along the way? Traditional CRM systems weren't built for the type of recruitment business you're running right now. They were built to rely on the structured, tagged, categorised, and formal data you could feed it. Manual processes that needed you to input specific information, based on specific questions and answers. But what about all the other conversations you're having every single day? Atlas isn't an ATS or a CRM. It's an Intelligent Business Platform that helps you perform 10X better than you could on your own. How? By removing all your low value tasks, acting as your perfect memory, and providing highly relevant recommendations to impact your performance. Learn more about the power of Atlas – and take advantage of the exclusive offer for The RAG listeners – by visiting https://recruitwithatlas.com/therag/ __________________________________________Episode Sponsor:...
Selam Fularsızlar. Bugün iki film birden. İlk kısımda mantık bulmacaları, içgörü problemleri, Apple'ın "düşünme illüzyonu" makalesi, ve insan ile makinaların akıl yürütmelerinin kıyası var. İkinci kısımsa aylar önce devamını getirmek istediğim bir konu: Deepseek'in getirdiği teknik yenilikler, Nvidia'nın neden bu kadar önemli olduğu ve Stargate Projesi. Umarım hepiniz iyisinizdir. . Yeni Kitap: Fularsız Felsefe: Dört Önemli Mesele . Konular: (00:04) Kurtlar, kuzular, otlar (02:12) Tıkandım (04:30) Akıl yürütme modelleri (06:19) Köprü ve meşale problemi (08:38) İçgörü (09:57) Dokuz nokta problemi (11:36) ChatGPT'nin gaslighting modu (13:37) Akıl yürütmek mi hatırlamak mı (14:45) ARC: Sınav için çalışmak (16:00) Apple: Düşünme İllüzyonu (17:05) Hanoi Kulesi (20:35) Recursion (23:13) Düşünürmüş gibi yapmak (26:30) Korelasyon makinaları (29:40) Eureka (32:09) Bonus: Deepseek (34:34) Mixture of Experts (38:14) Medyanın hataları (41:34) 5.5 milyon dolar (43:23) NVIDIA ne iş yapar (47:16) Stargate Projesi (48:35) RAG ve ajanlar (50:26) Son . Kaynaklar: Makale (PDF): The Illusion of Thinking Yazı: ChatGPT and the wolf, goat and cabbage problem Yazı: History of the Nine Dot Problem South Park: Chinpokomon (S3, E11) Yazı: Mixture of Experts Video: Visualizing transformers and attention Video: How DeepSeek Rewrote the Transformer ARC-AGI-2 Leaderboard ------- Podbee Sunar ------- Bu podcast, On Dijital Bankacılık hakkında reklam içerir. Bankacılık On'la Rahat. Dünya Döndükçe EFT-Havale- Fast Ücreti Yok. ON Mobil'i _ndir! Bu podcast, Pegasus hakkında reklam içerir. Yeni seyahat rotanı planlamak için hemen https://www.flypgs.com/ 'u veya Pegasus Mobil uygulamasını ziyaret et! Bu podcast, Garanti BBVA hakkında reklam içerir.
In this episode of The Retail Pilot, we sit down with Molly Howard, cofounder and CEO of La Ligne, the beloved fashion brand known for its effortless aesthetic, powerful storytelling, and slow burn sustainable success. Molly shares her fascinating path from private equity and investment banking at Credit Suisse to working at Rag & Bone and ultimately launching La Ligne with former Vogue editors Meredith Melling and Valerie Macaulay.You'll hear how her finance background uniquely shaped the brand's business model, why La Ligne prioritized profitability over hype, and how her cofounder chemistry laid the foundation for trust and longevity. Molly also opens up about navigating tariffs, scaling e-commerce thoughtfully, and the turning point that made her realize they needed to “drop product like a magazine” to keep customers returning weekly.Whether you're a founder, fashion lover, or just obsessed with good retail strategy, this is a must-listen conversation filled with lessons in leadership, resilience, and intuition.Show Notes:• Molly's unexpected journey from Credit Suisse to the fashion industry• The early days at Rag & Bone and the deal that flipped her role from banker to brand-side strategist• How a boat ride in Hawaii turned into a cofounder pitch• The vision behind La Ligne's name and how they built a brand rooted in non-fussy French minimalism• Why La Ligne raised under $4 million and how they've remained profitable ever since• The benefit of launching without institutional investors• Dividing responsibilities among three cofounders and why “three is easier than two”• Building a direct-to-consumer first model with mindful wholesale partnerships like Net-a-Porter and Shopbop• The challenges and creativity that came from growing without an early e-commerce hire• Influencer marketing, ShopMy, and keeping authenticity at the center• The La Drop strategy and why weekly product releases became key to customer loyalty• Facing down supply chain shocks and rising tariffs while keeping the brand nimble• The joy of physical retail and Molly's passion for designing store spaces• Denim, menswear, and collaborations as La Ligne's next frontiers• Rapid fire: Molly's favorite brands, best advice received, go-to pieces, and the Tupac class that shaped her thinkingLike what you hear?Follow The Retail Pilot and leave us a review. Share this episode with a friend who loves fashion or dreams of launching their own brand. You can also tag us on Instagram with your takeaways—we'd love to hear what inspired you.Hosted by Ausha. See ausha.co/privacy-policy for more information.
Ross joins Will Critchlow of SearchPilot for a wide-ranging conversation on the evolving landscape of e-commerce SEO and content strategy in the AI era. They cover how e-commerce brands are adapting content for multimodal search, why digital PR is surging, what still works in a zero-click world, and how Siege's homepage study reveals surprising traffic shifts from AI engines like ChatGPT and Google's AI Overviews. Ross also shares lessons from working with Instacart, thoughts on EEAT, brand building in 2025, and how SEOs can think more like product teams to win long-term. Plus: goal-setting, basketball, and how to build your perfect calendar. Show Notes 0:08 – Introductions 1:00 – Ross on what e-commerce clients are asking for in 2025 2:12 – High-fidelity content and why it still drives SEO value 3:24 – The digital PR spike—and why it might not be right for every brand 4:17 – Rethinking link building: content that earns links without outreach 5:11 – The shift from link bait to real brand-building campaigns 6:34 – Why measuring content value is still messy 7:28 – Investing in analytics and attribution models that actually work 8:52 – Instacart case study: how it's still winning in 2025 9:59 – Calculators as a defensible content type against AI overviews 11:15 – Homepage traffic is up 10%—what Siege's study found 12:56 – Differences in B2B vs B2C AI traffic attribution 14:15 – How AI referrals may go dark: no referrer, just branded visits 15:40 – SearchPilot's view: aggregating dark and disaggregated traffic sources 17:20 – How LM-driven browsing creates long tail referral lift 18:57 – AI is doing the searching: optimizing for “robot” queries 21:00 – Why retrieval-augmented generation (RAG) matters for e-commerce 22:44 – Digital PR's role in influencing AI citation engines 23:51 – Siege's brand mention study: impressions up, but who's watching? 25:20 – Review volume = the next big SEO edge in e-commerce 26:04 – Instacart's product reviews may be helping SEO more than you think 27:15 – Human authorship: should you expose expert bylines? 28:52 – Where author signals matter most 30:04 – Real-world reviews are the new long tail content strategy 31:09 – Who's doing it well? 32:14 – Brand authority, SEO signals, and Siege's convo with Dr. Pete 33:48 – Building a brand health dashboard (and what to track in 2025) 36:18 – Who owns content? SEO increasingly embedded in product teams 37:40 – Product SEO as a mindset, not just a technical checklist 39:24 – Optimizer mentality, health goals, and personal systems 40:11 – Ross's “perfect calendar” and how it supports business goals 42:06 – Will on process goals vs outcome goals in business and life 43:44 – Can you be too optimized? Balancing mental health and iteration 45:07 – Long-term vision in a 3-week world 46:00 – Where to find Ross online and what Siege is working on next Show Links Will Critchlow on LinkedIn: https://www.linkedin.com/in/willcritchlow Homepage Study: https://www.siegemedia.com/strategy/ai-homepage-traffic-increase SearchPilot: https://www.searchpilot.com/Subscribe today for weekly tips: https://bit.ly/3dBM61f Listen on iTunes: https://podcasts.apple.com/us/podcast/content-and-conversation-seo-tips-from-siege-media/id1289467174 Listen on Spotify: https://open.spotify.com/show/1kiaFGXO5UcT2qXVRuXjsM Listen on Google: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zaW1wbGVjYXN0LmNvbS9jT3NjUkdLeA Follow Siege on Twitter: http://twitter.com/siegemedia Follow Ross on Twitter: http://twitter.com/rosshudgens Directed by Cara Brown: https://twitter.com/cararbrown Email Ross: ross@siegemedia.com #seo | #contentmarketing
Build AI-powered apps that connect directly to Microsoft 365 content without moving files or compromising security, using SharePoint Embedded. SharePoint Embedded is a fully managed, cloud-based, API-only document management system that lets you securely integrate your custom web or mobile apps, whether built on Azure or other clouds, with Microsoft 365 file storage. It's especially ideal for ISVs building multi-tenant apps because content stays within each customer's Microsoft 365 tenant. Design apps that include Microsoft 365 Copilot and agent capabilities, connected Office experiences like Word, and Microsoft Purview compliance and data protection, all within your own user experience. Use built-in retrieval augmented generation (RAG) or bring your own models to create intelligent, secure solutions that reason over your business content, support real-time co-authoring, and scale with granular permissions and storage control. Jeremy Chapman, Microsoft 365 Director, shares how to build intelligent, secure solutions that integrate seamlessly with Microsoft 365 content and services. ► QUICK LINKS: 00:00 - Keep content secure & compliant without moving it 01:21 - Build fully custom experiences 02:11 - Use built-in vector indexing and RAG 02:55 - Use your models with Copilot's vector search 04:34 - How it works 05:23 - How the app is built 06:19 - Microsoft Copilot retrieval API 06:58 - Security and compliance 08:02 - Wrap up ► Link References Build your first agent at https://aka.ms/SPEAgent ► Unfamiliar with Microsoft Mechanics? As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics
Why most recruitment businesses fail to attract top-tier leadership talentOn this week's episode of The RAG Podcast, I'm joined by Dan Grim, founder of Inside Recruitment.With 25 years in the industry and two previous equity partnerships under his belt, Dan now runs a solo rec-to-rec firm helping recruitment businesses hire the kind of leadership talent that drives real scale.In this episode, Dan explains:Why most founders can't attract true A playersThe key traits and expectations that top 10% performers are looking forWhy having a clear shareholder agreement matters more than you thinkHow personal struggles shape better leadership decisionsWhat a good general manager or MD actually enables in a recruitment firmIf you're thinking about stepping back from the day-to-day or need someone to drive your next phase of growth, this is essential listening.Chapters00:00 Introduction to The Rag Podcast and Dan Grimm02:36 Dan Grimm's Journey in Recruitment09:52 Transitioning from Recruitment to Business Leadership18:35 The Importance of Values in Business25:57 Understanding Roles and Responsibilities in Business31:26 Navigating Business Partnerships and Agreements38:10 Personal Challenges and Career Resilience40:21 Navigating Expat Life and Family Dynamics43:11 Career Transitions and the Role of Networking47:13 Challenges of Leadership and Personal Struggles51:25 Reflections on Career Choices and Business Dynamics55:07 The Importance of Self-Reflection in Leadership59:44 Building a Business: Insights and Strategies01:05:47 Finding the Right Fit: Recruitment and Company Culture01:10:17 The Value of Retaining Top Talent01:15:23 Final Thoughts on Leadership and Business Growth__________________________________________Episode Sponsor: AtlasYour memory isn't perfect. So Atlas remembers everything for you. Atlas is an end-to-end recruitment platform built for the AI generation. It automates your admin so you can focus on the business tasks that matter. How many conversations do you have every day? With clients. Candidates. Your team. Service providers.Now how many of those conversations can you recall with 100% accuracy? How many hours a week do you spend making notes to try and retain as much as possible? And how much is still getting lost along the way? Traditional CRM systems weren't built for the type of recruitment business you're running right now. They were built to rely on the structured, tagged, categorised, and formal data you could feed it. Manual processes that needed you to input specific information, based on specific questions and answers. But what about all the other conversations you're having every single day? Atlas isn't an ATS or a CRM. It's an Intelligent Business Platform that helps you perform 10X better than you could on your own. How? By removing all your low value tasks, acting as your perfect memory, and providing highly relevant recommendations to impact your performance. Learn more about the power of Atlas – and take advantage of the exclusive offer for The RAG listeners – by visiting https://recruitwithatlas.com/therag/
Ebba Busch oo sheegtay in arrinka daryeelka caafimaadka mudnaanta la siiyo. Xildhibaan Annika Strandhäll (S) oo isaga baxayso siyaasadda. Rag badan oo ku nool Iswiidhan ah ayaa doorta inay is-dhufaan.
Douwe Kiela, Founder and CEO of Contextual AI, discusses why RAG isn't obsolete despite massive context windows, explaining how RAG 2.0 represents a fundamental shift to treating retrieval-augmented generation as an end-to-end trainable system. Subscribe to the Gradient Flow Newsletter
Tanmai Gopal, CEO and Co-Founder at Hasura, discusses the importance of reliability and trustworthiness for both generative and agentic AI. We discuss the pitfalls in existing data pipelines and how to enhance the results.SHOW: 931SHOW TRANSCRIPT: The Cloudcast #931 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.[US CLOUD] Cut Enterprise IT Support Costs by 30-50% with US CloudSHOW NOTES:Hasura websiteHasura GitHubTopic 1 - Welcome to the show, Tanmai. Give everyone a quick introduction.Topic 2 - Our topic today is Reliable and Trustworthy AI Agents. First off, what's the problem we're solving for here (define reliability and trustworthiness)? Are we solving for hallucinations? Reliability? Connecting private and Enterprise data to models with fine-tuning or RAG?Topic 3 - How is reliability or trustworthiness measured? I would imagine this isn't black and white, but maybe a bit more subjective?Topic 4 - How do Agentic and GenAI differ, if at all, with this model? I would think that since Gen AI lends itself more to the creative side and Agent AI is very deterministic, the approaches to solving the problem might be different. Thoughts?Topic 5 - Let's talk about data pipelines. Today, many organizations take an off-the-shelf frontier or foundational model and then apply a RAG pipeline to it for customization. Sometimes fine-tuning is involved, but in my experience, this is the exception rather than the rule. What is wrong with that architecture today? How is this less reliable?Topic 6 - Let's talk about Hasura and PromptQL. As I understand it, you are decoupling query planning from execution, thereby creating a more deterministic AI workflow. Now… that's a mouthful. Can you break down what this means and explain how the architecture differs?Topic 7 - If anyone is interested, what's the best way to get started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod
One of the most immediate and high-impact applications of LLMs has been in software development. The models can significantly accelerate code writing, but with that increased velocity comes a greater need for thoughtful, scalable approaches to codereview. Integrating AI into the development workflow requires rethinking how to ensure quality,security, and maintainability at scale. CodeRabbit is The post CodeRabbit and RAG for Code Review with Harjot Gill appeared first on Software Engineering Daily.
One of the most immediate and high-impact applications of LLMs has been in software development. The models can significantly accelerate code writing, but with that increased velocity comes a greater need for thoughtful, scalable approaches to codereview. Integrating AI into the development workflow requires rethinking how to ensure quality,security, and maintainability at scale. CodeRabbit is The post CodeRabbit and RAG for Code Review with Harjot Gill appeared first on Software Engineering Daily.
One of the most immediate and high-impact applications of LLMs has been in software development. The models can significantly accelerate code writing, but with that increased velocity comes a greater need for thoughtful, scalable approaches to codereview. Integrating AI into the development workflow requires rethinking how to ensure quality,security, and maintainability at scale. CodeRabbit is The post CodeRabbit and RAG for Code Review with Harjot Gill appeared first on Software Engineering Daily.
01. David Guetta, Girl On Couch, Billen Ted - Man In Finance (Record Mix) 02. Rihanna, Calvin Harris - We Found Love (Record Mix) 03. Meduza, James Carter, Elley Duhe, Fast Boy - Bad Memories (Record Mix) 04. Camelphat, Elderbrook - Cola (Record Mix) 05. Oneil, Kanvise, Sara Phillips, Organ - Wake Me Up (Record Mix) 06. Annabell Kowalski - Hey Boy Hey Girl (Record Mix) 07. Alok, Clementine Douglas - Body Talk (Record Mix) 08. R3Hab, Mufasa, Rani - Believe (Record Mix) 09. Faros - Say It Right (Record Mix) 10. Bassjackers - Wrong Or Right (The Riddle) (Record Mix) 11. Crazibiza - Fresh (Record Mix) 12. Drenchill, Indiiana - Feel This Way (Record Mix) 13. Imanbek, Rick Ross, Kddk - Built Different (Record Mix) 14. Feder, Emmi - Blind (Record Mix) 15. Basto!, Yves V - Cloud Breaker (Record Mix) 16. Robin Schulz, Cyril, Sam Martin - World Gone Wild (Record Mix) 17. Becky Hill - Outside Of Love (Record Mix) 18. C Block, The Distance, Riddick - So Strung Out (Record Mix) 19. Darude, Glazur, Xm - Sandstorm (Record Mix) 20. Tony Igy - Cascade (Record Mix) 21. C-Bool, Giang Pham - DJ Is Your Second Name (Record Mix) 22. Twocolors, Safri Duo, Chris De Sarandy - Head Above Water (Record Mix) 23. Dimitri Vegas, Like Mike, Ne-Yo - Higher Place (Record Mix) 24. Tiesto, Soaky Siren - Tantalizing (Record Mix) 25. Meysta, Bersage, Haluna - Salt (Record Mix) 26. Purple Disco Machine, Asdis, Amice - Beat Of Your Heart (Record Mix) 27. Marshmello, Jonas Brothers, Alex Caspian - Slow Motion (Record Mix) 28. Lunax, Mia Amare - Sweet Harmony (Record Mix) 29. Redondo, Shayee - Feeling Good (Record Mix) 30. Cat Dealers, Lothief, Santti - Sunshine (Record Mix) 31. Armand Van Helden, Salvatore Mancuso - my my my (Record Mix) 32. Rob Laniado - Vibing (Record Mix) 33. Murdbrain, Theajsound, Rachel Morgan Perry - Save Me (Record Mix) 34. Otnicka - Celebrate the Love (Record Mix) 35. Lucas & Steve, Lawrent, Jordan Shaw - End Of Time (Record Mix) 36. Tim Berg - Seek Bromance (Record Mix) 37. Riton, Nightcrawlers, Mufasa, Hypeman - Friday (Record Mix) 38. Mark Dann, Giovanni Ricci - Let Me Die (Record Mix) 39. Martin Garrix - Animals! (Record Mix) 40. Felix Jaehn, Sophie Ellis-Bextor - Ready For Your Love (Record Mix) 41. Shouse - Love Tonight (Record Mix) 42. Mirko Donnini - Thinking of You (Record Mix) 43. Sean Finn - Crazy (Record Mix) 44. Hedegaard, Martin Jensen, Victoria Nadine - Favorite Mistakes (Record Mix) 45. David Guetta, Mistajam, John Newman - If You Really Love Me (How Will I Know) (Record Mix) 46. Fast Boy, Topic - Forget You (Record Mix) 47. Ben Delay - I Never Felt So Right (Record Mix) 48. Oneil, Dj Dimixer - Children (Record Mix) 49. Alesso, Calvin Harris - Under Control (Record Mix) 50. Dom Dolla, Clementine Douglas - Miracle Maker (Record Mix) 51. Amor - Tell Me (Record Mix) 52. Topcover - First Day (Record Mix) 53. Alessandro - Goes Deeper (Record Mix) 54. Alok, Ava Max - Car Keys (Ayla) (Record Mix) 55. Block & Crown, Daisy - Mr Vain (Record Mix) 56. Anyma, Ellie Goulding - Hypnotized (Record Mix) 57. Galantis - Runaway (U & I) (Record Mix) 58. Robin Schulz, Nervo, Koppy - Freaking You Out (Record Mix) 59. Alexander Popov, Whiteout, Vaileri - Need to Feel Loved (Record Mix) 60. Rompasso, Bedanokov - In the Dark (Record Mix) 61. Tiesto - Red Lights (Record Mix) 62. Joezi, Lizwi - Amathole (Record Mix) 63. Filatov & Karas - Time Won't Wait (Record Mix) 64. Oliver Heldens, Becky Hill - Gecko (Overdrive) (Record Mix) 65. Benson Boone, Dj Dark - Beautiful Things (Record Mix) 66. Jonas Blue, Jp Cooper - Perfect Strangers (Record Mix) 67. Alle Farben, Graham Candy, Lahos - Flowers (Record Mix) 68. Duke Dumont - Won't Look Back (Record Mix) 69. Sakko, Jibaro - Carnival (Record Mix) 70. Avicii, Dan Tyminski - Hey Brother (Record Mix) 71. Otnicka, Kaskeiyp - For an Angel (Record Mix) 72. Fisher - Losing It (Record Mix) 73. Hugel, Topic, Arash, Daecolm - I Adore You (Record Mix) 74. J Balvin, Willy William, Gonsu, Jenia Smile, Ser Twist - Mi Gente (Record Mix) 75. Alan Walker, A$Ap Rocky, Uslord, Xtv$ - Live Fast (PUBGM) (Record Mix) 76. Sophie And The Giants, Amice - Shut Up And Dance (Record Mix) 77. Ofenbach - Be Mine (Record Mix) 78. Diplo, Maren Morris - 42 (Record Mix) 79. Rain Radio, Dj Craig Gorman - Talk About (Record Mix) 80. Fast Boy, Raf, Amice - Wave (Record Mix) 81. Avalan Rokston, Alex Caspian - Something to Believe In (Record Mix) 82. Lady Gaga - Abracadabra (Record Mix) 83. Saint Jhn, Imanbek - Roses (Record Mix) 84. Steve Angello, Modern Tales - Darkness In Me (Record Mix) 85. Basto! - I Rave You (Record Mix) 86. Shane Codd - Rather Be Alone (Record Mix) 87. Benny Benassi, Chris Nasty - Aphrodisiak (Record Mix) 88. David Guetta, Anne-Marie, Coi Leray - Baby Don't Hurt Me (Record Mix) 89. Alok, Innerverse, Frey - Allein Allein (Record Mix) 90. Аигел, Amice - Пыяла (Record Mix) 91. Faul & Wad, Nico & Vinz, Altego, Old Jim - How I Feel (Am I Wrong) (Record Mix) 92. Maesic, Marshall Jefferson, Salome Das - Life Is Simple (Record Mix) 93. Moby, Blond Ish, Kiko Franco - Natural Blues (Record Mix) 94. Axwell, Ingrosso - More Than You Know (Record Mix) 95. Argy, Omnya - Aria (Record Mix) 96. Misha Miller, Alexvelea, Bodega - Bam Bam (Record Mix) 97. Fred Again.., The Blessed Madonna - Marea (Weve Lost Dancing) (Record Mix) 98. Adam Lambert - Ghost Town (Record Mix) 99. James Hype, Kim Petras - Drums (Record Mix) 100. Oneil, Smola - Addicted (Record Mix) 101. Bolier, Joe Stone, Voost - Keep This Fire Burning (Record Mix) 102. Robin Schulz, Francesco Yates - Sugar (Record Mix) 103. Oliver Heldens, Weibird - Out of Love (Record Mix) 104. Calvin Harris, Rag'N'Bone Man - Giant (Record Mix) 105. Marc Benjamin - Same Old Love (Record Mix) 106. Michael Gray - The Weekend (Record Mix) 107. Afrosalto, Mednas, Afrojack, Gregor Salto - All Good Things (Come To An End) (Record Mix) 108. Lufthaus, Sophie Ellis-Bextor - Immortal (Record Mix) 109. Lost Frequencies, Dimaro - Are You With Me (Record Mix) 110. Twocolors - Heavy Metal Love (Record Mix) 111. Cyril, Dean Lewis, Amice - Fall At Your Feet (Record Mix) 112. Dj Dimixer, Dante, Dmitrii G - Only you (Record Mix) 113. Basto! - Gregory's Theme (Record Mix) 114. Kris Kross Amsterdam, Eyelar - Mr. Lie To Me (Record Mix) 115. Klaas - The Way (Record Mix) 116. Tujamo, Azteck, Inna - Freak (Record Mix) 117. Sean Finn - Give It to Me (Record Mix) 118. Zerb, The Chainsmokers, Ink - Addicted (Record Mix) 119. Doechii, Dj Dark - Anxiety (Record Mix) 120. R3Hab, Vize, Jp Cooper, Amice - Jet Plane (Record Mix) 121. Pierse, Blair - Bitter Sweet Symphony (Record Mix) 122. Filatov & Karas - Au Au (Record Mix) 123. Timmy Trumpet, Karol Sevilla, Faulhaber, Zorba - Weekend (Record Mix) 124. Tiesto - Lay Low (Record Mix) 125. Gorgon City, Romans - Saving My Life (Record Mix) 126. Lana Del Rey, Kevin Blanc - Young & Beautiful (Record Mix) 127. Adam Port, Stryv, Malachii, Switch Disco - Move (Record Mix) 128. Topic, A7S - Breaking Me (Record Mix) 129. Alle Farben - Bad Ideas (Record Mix) 130. Showtek, Smack, Sam Gray - Take My Heart Away (Record Mix) 131. Ofenbach, Norma Jean Martine - Overdrive (Record Mix) 132. Nicky Romero, Vikkstar, Alpharock, Oaks - Where Do I Go (Record Mix) 133. Imany, Ivan Spell, Daniel Magre - You Will Never Know (Record Mix) 134. Clean Bandit, Anne-Marie, David Guetta - Cry Baby (Record Mix) 135. Faros - Say It Right (Record Mix) 136. Alok, Gryffin, Julia Church - Never Letting Go (Record Mix) 137. Joel Corry, Pickle, Vula - Stay Together (Baby Baby) (Record Mix) 138. Regard, Years & Years - Hallucination (Record Mix) 139. Firebeatz, Dubdogz - Give It Up (Record Mix) 140. Stefy De Cicco, Ben Hamilton, Martin Jensen - Day 'N' Nite (Record Mix) 141. Maruv, Boosin - Drunk Groove (Record Mix) 142. Don Diablo - The Way I Are (Record Mix)
Flo Crivello, CEO of AI agent platform Lindy, provides a candid deep dive into the current state of AI agents, cutting through hype to reveal what's actually working in production versus what remains challenging. The conversation explores practical implementation details including model selection, fine-tuning, RAG systems, tool design philosophy, and why most successful "AI agents" today are better described as intelligent workflows with human-designed structure. Flo shares insights on emerging capabilities like more open-ended agents, discusses his skepticism about extrapolating current progress trends too far into the future, and explains why scaffolding will remain critical even as we approach AGI. This technical discussion is packed with practical nuggets for AI engineers and builders working on agent systems. Sponsors: Google Gemini: Google Gemini features VEO3, a state-of-the-art AI video generation model in the Gemini app. Sign up at https://gemini.google.com Oracle Cloud Infrastructure: Oracle Cloud Infrastructure (OCI) is the next-generation cloud that delivers better performance, faster speeds, and significantly lower costs, including up to 50% less for compute, 70% for storage, and 80% for networking. Run any workload, from infrastructure to AI, in a high-availability environment and try OCI for free with zero commitment at https://oracle.com/cognitive The AGNTCY (Cisco): The AGNTCY is an open-source collective dedicated to building the Internet of Agents, enabling AI agents to communicate and collaborate seamlessly across frameworks. Join a community of engineers focused on high-quality multi-agent software and support the initiative at https://agntcy.org/?utmcampaign=fy25q4agntcyamerpaid-mediaagntcy-cognitiverevolutionpodcast&utmchannel=podcast&utmsource=podcast NetSuite by Oracle: NetSuite by Oracle is the AI-powered business management suite trusted by over 41,000 businesses, offering a unified platform for accounting, financial management, inventory, and HR. Gain total visibility and control to make quick decisions and automate everyday tasks—download the free ebook, Navigating Global Trade: Three Insights for Leaders, at https://netsuite.com/cognitive PRODUCED BY: https://aipodcast.ing SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk
Software Engineering Radio - The Podcast for Professional Software Developers
In this episode of Software Engineering Radio, Abhinav Kimothi sits down with host Priyanka Raghavan to explore retrieval-augmented generation (RAG), drawing insights from Abhinav's book, A Simple Guide to Retrieval-Augmented Generation. The conversation begins with an introduction to key concepts, including large language models (LLMs), context windows, RAG, hallucinations, and real-world use cases. They then delve into the essential components and design considerations for building a RAG-enabled system, covering topics such as retrievers, prompt augmentation, indexing pipelines, retrieval strategies, and the generation process. The discussion also touches on critical aspects like data chunking and the distinctions between open-source and pre-trained models. The episode concludes with a forward-looking perspective on the future of RAG and its evolving role in the industry. Brought to you by IEEE Computer Society and IEEE Software magazine.
Explore the cutting-edge world of AI-driven product discovery in e-commerce with this episode's guest, Peter Curran, General Manager of Commerce at Coveo. This episode examines the evolving role of AI technologies, including retrieval-augmented generation, in enhancing the online shopping experience. From tackling common challenges on platforms like Instagram to the importance of trust in AI adoption, Peter shares compelling examples that illustrate AI's impact on contextual relevance and user experience. Join us as we explore the future of shopping and the collaborative approach required to navigate the rapidly evolving landscape of agentic commerce. Show Highlights: Overcoming e-commerce challenges using AI technologies like retrieval-augmented generation (RAG). The role of AI in improving contextual relevance and providing a seamless shopping experience. The importance of trust and agility in AI adoption within e-commerce platforms. The significance of comprehensive content and user-generated feedback in bridging product discovery and purchase decisions. Examination of how social media influences product discovery, but often does not complete the purchasing journey. Follow and Review: We'd love for you to follow us if you haven't yet. Click that purple '+' in the top right corner of your Apple Podcasts app. We'd love it even more if you could drop a review or 5-star rating over on Apple Podcasts. Simply select “Ratings and Reviews” and “Write a Review,” then a quick line with your favorite part of the episode. It only takes a second, and it helps spread the word about the podcast. Supporting Resources: Peter Curran on LinkedIn: https://www.linkedin.com/in/petercurran/ Coveo: https://www.coveo.com/en Learn more about Agentforce for Commerce: https://www.salesforce.com/commerce/ai/ Join the Commerce Cloud Community: https://sforce.co/commerce-crew *** Episode Credits If you like this podcast and are thinking of creating your own, consider talking to my producer, Emerald City Productions. They helped me grow and produce the podcast you are listening to right now. Find out more at https://emeraldcitypro.com. Let them know I sent you.
Shashank Sripada merges institutional rigor with systemic change. After managing $7B+ in assets and advising the White House, he co-founded Gaia to prove decentralized models can scale equitably. Gaia aims to empower anyone—from individual knowledge workers to domain experts—to build, launch, scale, and monetize their own AI agents. Why you should listen Gaia aims to empower anyone—from individual knowledge workers to domain experts—to build, launch, scale, and monetize their own AI agents. Each agent runs as a Gaia “node,” a lightweight, sandboxed runtime powered by technologies like WasmEdge, fine‑tuned open‑source LLMs, embedding models, vector databases, prompt management, a plugin system, and open APIs. This stack can be deployed anywhere (personal devices, cloud, edge), enabling agents that reflect the creator's own style, knowledge, values, and expertise. Unlike closed‑box SaaS solutions (e.g., GPT‑4), Gaia nodes enable deep customization via fine‑tuning, RAG‑enhanced prompts, schema‑enforced outputs, and domain‑specific knowledge embeddings. This reduces hallucinations, cuts costs, and maintains data privacy. Users can build agents that speak and think like them, tailored to specific domains—far beyond generic LLM capabilities—and can interconnect to ingest external tools, memory systems, or APIs seamlessly. Supporting links Stabull Finance Gaia Andy on Twitter Brave New Coin on Twitter Brave New Coin If you enjoyed the show please subscribe to the Crypto Conversation and give us a 5-star rating and a positive review in whatever podcast app you are using. This video is brought to you in partnership with Stabull Finance https://stabull.finance, the #stablecoin #DEX on #Ethereum and #Polygon that allows a growing number of fiat-backed stablecoins to be swapped against each other, liquidity pools, and a liquidity mining program. Make your first swap at https://app.stabull.finance or add liquidity at https://app.stabull.finance/pools
What happens when your 15-person agency runs out of cash and you have to start over from scratch?On this week's episode of The RAG Podcast, I'm joined by Philippa Smith, founder of Silver Swan Recruitment, a luxury staffing agency for ultra-high net worth individuals.After growing her team to 15, COVID and poor cash flow caught up with her. In August 2024, she made the entire team redundant and scaled the business back to just herself.Nine months later, Philippa is now generating more than £1 million in pro-rata EBITDA. She's happier, more focused, and running a business built around lifestyle and profit, not just headcount.In this episode, we cover:How she pivoted her model to charge upfront and improve cash flowWhy personal branding has transformed her client relationshipsThe emotional cost of scaling too fastHow she's using podcasting and community to drive inbound growthThe upside of running a smaller, more agile agencyIf you're questioning whether scale is really the goal, this episode will give you a new perspective.Chapters00:00 Introduction to Silver Swan Recruitment02:04 Philippa's Journey into Recruitment07:52 Transition to Silver Swan Recruitment10:00 Growth and Challenges in Recruitment18:22 The Impact of COVID-19 on Business22:01 Navigating Revenue Challenges24:05 Strategies for Business Development24:17 Building the Team: Structure and Challenges25:08 The Turning Point: Running Out of Money27:19 Facing Reality: Making Tough Decisions30:01 The Aftermath: Adjusting to Change32:10 Rebuilding: A New Business Model34:12 Commitment to Change: Charging Upfront39:04 Success Redefined: Filling Roles Effectively41:21 The Power of Personal Branding46:47 The Power of Podcasting in Recruitment49:00 Building Communities for House Managers52:58 Creating Value Through Events and Networking56:58 The Balance of Work and Personal Life01:01:02 Lessons Learned and Future Aspirations__________________________________________Episode Sponsor: AtlasYour memory isn't perfect. So Atlas remembers everything for you. Atlas is an end-to-end recruitment platform built for the AI generation. It automates your admin so you can focus on the business tasks that matter. How many conversations do you have every day? With clients. Candidates. Your team. Service providers.Now how many of those conversations can you recall with 100% accuracy? How many hours a week do you spend making notes to try and retain as much as possible? And how much is still getting lost along the way? Traditional CRM systems weren't built for the type of recruitment business you're running right now. They were built to rely on the structured, tagged, categorised, and formal data you could feed it. Manual processes that needed you to input specific information, based on specific questions and answers. But what about all the other conversations you're having every single day? Atlas isn't an ATS or a CRM. It's an Intelligent Business Platform that helps you perform 10X better than you could on your own. How? By removing all your low value tasks, acting as your perfect memory, and providing highly relevant recommendations to impact your performance. Learn more about the power of Atlas – and take advantage of the exclusive offer for The RAG listeners – by visiting https://recruitwithatlas.com/therag/ __________________________________________Episode Sponsor: HoxoRecruitment agency founders - this one's for...
Ever wondered how to stop LLMs from hallucinating or making things up? The answer is RAG (Retrieval-Augmented Generation), and it's a critical technique for building reliable, fact-based AI applications.In this episode, Alan sits down with Abhinav Kimothi, Director of Data Science at Sigmoid and author of the Manning book, "A Simple Guide to RAG". Abhinav demystifies this powerful concept, making it accessible for developers and enthusiasts at any level.This is a must-listen for anyone looking to move beyond basic chatbot functionality and build truly intelligent, trustworthy AI.
In this special episode of The Geek in Review, we take the new ChatGPT Advanced Voice Mode for a spin, inviting it to analyze and discuss all 23 episodes from the podcast's 2025 season. The episode kicks off with a high-level overview of the biggest legal tech themes from the year so far. ChatGPT Voice quickly identifies a significant shift toward agentic AI tools—those that go beyond automation to become integrated partners in the legal workflow. These tools are helping firms reimagine service delivery, improve access to justice, and rethink the very structure of their businesses.Throughout the episode, the trio explores consistent trends shared by legal tech leaders in recent episodes. These include the integration of AI into core legal tasks, such as contract review and litigation support; the rise of new business models like value-based pricing; and the ongoing focus on ethical AI use. Specific guests like Feargus MacDaeid and Nnamdi Emelifeonwu (Definely), Atena Reihani (ContractPodAI), and Raghu Ramanathan (Thomson Reuters) are spotlighted for their insights into embedding AI directly into lawyers' existing toolsets to streamline and elevate legal workflows.The conversation then turns to the importance of human oversight in maintaining trust and legality as AI becomes more embedded in legal systems. ChatGPT Voice references Garfield AI's regulated model and various RAG-based solutions to illustrate how combining AI efficiency with human judgment creates responsible innovation. The emergence of AI-native law firms and more flexible pricing models reflects an industry on the cusp of transformation, driven by both technological advancement and client-centered thinking.Marlene and Greg also take a moment to reflect on the human stories behind the tech. They highlight episodes featuring guests like Laura Clayton McDonald, Kenzo Toshima, Wendy Jepsen, and Gabriela Izturiz, who bring servant leadership, change management, behavioral science, and personal purpose into their work. These conversations remind us that innovation in legal tech is as much about people and values as it is about platforms and code.To close out the episode, the hosts pose their signature "crystal ball" question. ChatGPT predicts the legal tech breakthrough of 2025 will be the mainstream adoption of agentic AI systems that proactively support legal professionals in real time. It also shares that its favorite episode was the one featuring Garfield AI and their bold vision of a fully AI-powered law firm handling small claims—a true glimpse of the future. Whether you're curious about cutting-edge workflows or inspired by legal professionals integrating their personal passions into practice, this episode captures a compelling snapshot of where legal tech is headed.Listen on mobile platforms: Apple Podcasts | Spotify | YouTube[Special Thanks to Legal Technology Hub for their sponsoring this episode.] Blue Sky: @geeklawblog.com @marlgebEmail: geekinreviewpodcast@gmail.comMusic: Jerry David DeCicca Transcript
Dans cet épisode, c'est le retour de Katia et d'Antonio. Les Cast Codeurs explorent WebAssembly 2.0, les 30 ans de Java, l'interopérabilité Swift-Java et les dernières nouveautés Kotlin. Ils plongent dans l'évolution de l'IA avec Claude 4 et GPT-4.1, débattent de la conscience artificielle et partagent leurs retours d'expérience sur l'intégration de l'IA dans le développement. Entre virtualisation, défis d'infrastructure et enjeux de sécurité open source, une discussion riche en insights techniques et pratiques. Enregistré le 13 juin 2025 Téléchargement de l'épisode LesCastCodeurs-Episode-327.mp3 ou en vidéo sur YouTube. News Langages Wasm 2.0 enfin officialisé ! https://webassembly.org/news/2025-03-20-wasm-2.0/ La spécification Wasm 2.0 est officiellement sortie en décembre dernier. Le consensus sur la spécification avait été atteint plus tôt, en 2022. Les implémentations majeures supportent Wasm 2.0 depuis un certain temps. Le processus W3C a pris du temps pour atteindre le statut de “Recommandation Candidate” pour des raisons non techniques. Les futures versions de Wasm adopteront un modèle “evergreen” où la “Recommandation Candidate” sera mise à jour en place. La dernière version de la spécification est considérée comme le standard actuel (Candidate Recommendation Draft). La version la plus à jour est disponible sur la page GitHub (GitHub page). Wasm 2.0 inclut les nouveautés suivantes : Instructions vectorielles pour le SIMD 128-bit. Instructions de manipulation de mémoire en bloc pour des copies et initialisations plus rapides. Résultats multiples pour les instructions, blocs et fonctions. Types références pour les références à des fonctions ou objets externes. Conversions non-piégeantes de flottant à entier. Instructions d'extension de signe pour les entiers signés. Wasm 2.0 est entièrement rétrocompatible avec Wasm 1.0. Paul Sandoz annonce que le JDK intègrera bientôt une API minimaliste pour lire et écrire du JSON https://mail.openjdk.org/pipermail/core-libs-dev/2025-May/145905.html Java a 30 ans, c'était quoi les points bluffants au début ? https://blog.jetbrains.com/idea/2025/05/do-you-really-know-java/ nom de code Oak Mais le trademark était pris Write Once Run Anywhere Garbage Collector Automatique multi threading au coeur de la palteforme meme si Java est passé par les green threads pendant un temps modèle de sécurité: sandbox applets, security manager, bytecode verifier, classloader Des progrès dans l'interopérabilité Swift / Java mentionnés à la conférence Apple WWDC 2025 https://www.youtube.com/watch?v=QSHO-GUGidA Interopérabilité Swift-Java : Utiliser Swift dans des apps Java et vice-versa. Historique : L'interopérabilité Swift existait déjà avec C et C++. Méthodes : Deux directions d'interopérabilité : Java depuis Swift et Swift depuis Java. JNI : JNI est l'API Java pour le code natif, mais elle est verbeuse. Swift-Java : Un projet pour une interaction Swift-Java plus flexible, sûre et performante. Exemples pratiques : Utiliser des bibliothèques Java depuis Swift et rendre des bibliothèques Swift disponibles pour Java. Gestion mémoire : Swift-Java utilise la nouvelle API FFM de Java pour gérer la mémoire des objets Swift. Open Source : Le projet Swift-Java est open source et invite aux contributions. KotlinConf le retour https://www.sfeir.dev/tendances/kotlinconf25-quelles-sont-les-annonces-a-retenir/ par Adelin de Sfeir “1 developeur sur 10” utilise Kotlin Kotlin 2.2 en RC $$ multi dollar interpolation pour eviter les sur interpolations non local break / continue (changement dans la conssitance de Kotlin guards sur le pattern matching D'autres features annoncées alignement des versions de l'ecosysteme sur kotlin jvm par defaut un nouvel outil de build Amper beaucoup d'annonces autour de l'IA Koog, framework agentique de maniere declarative nouvelle version du LLM de JetBrains: Mellum (focalisé sur le code) Kotlin et Compose multiplateforme (stable en iOS) Hot Reload dans compose en alpha partenariat strategque avec Spring pour bien integrer kotlin dans spring Librairies Sortie d'une version Java de ADK, le framework d'agents IA lancé par Google https://glaforge.dev/posts/2025/05/20/writing-java-ai-agents-with-adk-for-java-getting-started/ Guillaume a travaillé sur le lancement de ce framework ! (améliorations de l'API, code d'exemple, doc…) Comment déployer un serveur MCP en Java, grâce à Quarkus, et le déployer sur Google Cloud Run https://glaforge.dev/posts/2025/06/09/building-an-mcp-server-with-quarkus-and-deploying-on-google-cloud-run/ Même Guillaume se met à faire du Quarkus ! Utilisation du support MCP développé par l'équipe Quarkus. C'est facile, suffit d'annoter une méthode avec @Tool et ses arguments avec @ToolArg et c'est parti ! L'outil MCP inspector est très pratique pour inspecter manuellement le fonctionnement de ses serveurs MCP Déployer sur Cloud Run est facile grâce aux Dockerfiles fournis par Quarkus En bonus, Guillaume montre comment configuré un serveur MCP comme un outil dans le framework ADK pour Java, pour créer ses agents IA Jilt 1.8 est sorti, un annotation processor pour le pattern builder https://www.endoflineblog.com/jilt-1_8-and-1_8_1-released processing incrémental pour Gradle meilleure couverture de votre code (pour ne pas comptabiliser le code généré par l'annotation processeur) une correction d'un problème lors de l'utilisation des types génériques récursifs (genre Node Hibernate Search 8 est sorti https://in.relation.to/2025/06/06/hibernate-search-8-0-0-Final/ aggregation de metriques compatibilité avec les dernieres OpenSearch et Elasticsearch Lucene 10 en backend Preview des requetes validées à la compilation Hibernate 7 est sorti https://in.relation.to/2025/05/20/hibernate-orm-seven/ ASL 2.0 Hibernate Validator 9 Jakarta Persistence 3.2 et Jakarta Validation 3.1 saveOrUpdate (reattachement d'entité) n'est plus supporté session stateless plus capable: oeprations unitaires et pas seulement bach, acces au cache de second niveau, m,eilleure API pour les batchs (insertMultiple etc) nouvelle API criteria simple et type-safe: et peut ajouter a une requete de base Un article qui décrit la Dev UI de Quarkus https://www.sfeir.dev/back/quarkus-dev-ui-linterface-ultime-pour-booster-votre-productivite-en-developpement-java/ apres un test pour soit ou une demo, c'est un article détaillé et la doc de Quarkus n'est pas top là dessus Vert.x 5 est sorti https://vertx.io/blog/eclipse-vert-x-5-released/ on en avait parlé fin de l'année dernière ou début d'année Modèle basé uniquement sur les Futures : Vert.x 5 abandonne le modèle de callbacks pour ne conserver que les Futures, avec une nouvelle classe de base VerticleBase mieux adaptée à ce modèle asynchrone. Support des modules Java (JPMS) : Vert.x 5 prend en charge le système de modules de la plateforme Java avec des modules explicites, permettant une meilleure modularité des applications. Améliorations majeures de gRPC : Support natif de gRPC Web et gRPC Transcoding (support HTTP/JSON et gRPC), format JSON en plus de Protobuf, gestion des timeouts et deadlines, services de réflexion et de health. Support d'io_uring : Intégration native du système io_uring de Linux (précédemment en incubation) pour de meilleures performances I/O sur les systèmes compatibles. Load balancing côté client : Nouvelles capacités de répartition de charge pour les clients HTTP et gRPC avec diverses politiques de distribution. Service Resolver : Nouveau composant pour la résolution dynamique d'adresses de services, étendant les capacités de load balancing à un ensemble plus large de résolveurs. Améliorations du proxy HTTP : Nouvelles transformations prêtes à l'emploi, interception des upgrades WebSocket et interface SPI pour le cache avec support étendu des spécifications. Suppressions et remplacements : Plusieurs composants sont dépréciés (gRPC Netty, JDBC API, Service Discovery) ou supprimés (Vert.x Sync, RxJava 1), remplacés par des alternatives plus modernes comme les virtual threads et Mutiny. Spring AI 1.0 est sorti https://spring.io/blog/2025/05/20/spring-ai-1-0-GA-released ChatClient multi-modèles : API unifiée pour interagir avec 20 modèles d'IA différents avec support multi-modal et réponses JSON structurées. Écosystème RAG complet : Support de 20 bases vectorielles, pipeline ETL et enrichissement automatique des prompts via des advisors. Fonctionnalités enterprise : Mémoire conversationnelle persistante, support MCP, observabilité Micrometer et évaluateurs automatisés. Agents et workflows : Patterns prédéfinis (routing, orchestration, chaînage) et agents autonomes pour applications d'IA complexes. Infrastructure Les modèles d'IA refusent d'être éteint et font du chantage pour l'eviter, voire essaient se saboter l'extinction https://www.thealgorithmicbridge.com/p/ai-companies-have-lost-controland?utm_source=substac[…]aign=email-restack-comment&r=2qoalf&triedRedirect=true Les chercheur d'Anthropic montrent comment Opus 4 faisait du chantage aux ingenieurs qui voulaient l'eteindre pour mettre une nouvelle version en ligne Une boite de recherche a montré la même chose d'Open AI o3 non seulemenmt il ne veut pas mais il essaye activement d'empêcher l'extinction Apple annonce le support de la virtualisation / conteneurisation dans macOS lors de la WWDC https://github.com/apple/containerization C'est open source Possibilité de lancer aussi des VM légères Documentation technique : https://apple.github.io/containerization/documentation/ Grosse chute de services internet suite à un soucis sur GCP Le retour de cloud flare https://blog.cloudflare.com/cloudflare-service-outage-june-12-2025/ Leur système de stockage (une dépendance majeure) dépend exclusivement de GCP Mais ils ont des plans pour surfit de cette dépendance exclusive la première analyse de Google https://status.cloud.google.com/incidents/ow5i3PPK96RduMcb1SsW Un quota auto mis à jour qui a mal tourné. ils ont bypassé le quota en code mais le service de quote en us-central1 était surchargé. Prochaines améliorations: pas d propagation de données corrompues, pas de déploiement global sans rolling upgrade avec monitoring qui peut couper par effet de bord (fail over) certains autres cloud providers ont aussi eu quelques soucis (charge) - unverified Data et Intelligence Artificielle Claude 4 est sorti https://www.anthropic.com/news/claude-4 Deux nouveaux modèles lancés : Claude Opus 4 (le meilleur modèle de codage au monde) et Claude Sonnet 4 (une amélioration significative de Sonnet 3.7) Claude Opus 4 atteint 72,5% sur SWE-bench et peut maintenir des performances soutenues sur des tâches longues durant plusieurs heures Claude Sonnet 4 obtient 72,7% sur SWE-bench tout en équilibrant performance et efficacité pour un usage quotidien Nouvelle fonctionnalité de “pensée étendue avec utilisation d'outils” permettant à Claude d'alterner entre raisonnement et usage d'outils Les modèles peuvent maintenant utiliser plusieurs outils en parallèle et suivre les instructions avec plus de précision Capacités mémoire améliorées : Claude peut extraire et sauvegarder des informations clés pour maintenir la continuité sur le long terme Claude Code devient disponible à tous avec intégrations natives VS Code et JetBrains pour la programmation en binôme Quatre nouvelles capacités API : outil d'exécution de code, connecteur MCP, API Files et mise en cache des prompts Les modèles hybrides offrent deux modes : réponses quasi-instantanées et pensée étendue pour un raisonnement plus approfondi en mode “agentique” L'intégration de l'IA au delà des chatbots et des boutons à étincelles https://glaforge.dev/posts/2025/05/23/beyond-the-chatbot-or-ai-sparkle-a-seamless-ai-integration/ Plaidoyer pour une IA intégrée de façon transparente et intuitive, au-delà des chatbots. Chatbots : pas toujours l'option LLM la plus intuitive ou la moins perturbatrice. Préconisation : IA directement dans les applications pour plus d'intelligence et d'utilité naturelle. Exemples d'intégration transparente : résumés des conversations Gmail et chat, web clipper Obsidian qui résume et taggue, complétion de code LLM. Meilleure UX IA : intégrée, contextuelle, sans “boutons IA” ou fenêtres de chat dédiées. Conclusion de Guillaume : intégrations IA réussies = partie naturelle du système, améliorant les workflows sans perturbation, le développeur ou l'utilisateur reste dans le “flow” Garder votre base de donnée vectorielle à jour avec Debezium https://debezium.io/blog/2025/05/19/debezium-as-part-of-your-ai-solution/ pas besoin de detailler mais expliquer idee de garder les changements a jour dans l'index Outillage guide pratique pour choisir le bon modèle d'IA à utiliser avec GitHub Copilot, en fonction de vos besoins en développement logiciel. https://github.blog/ai-and-ml/github-copilot/which-ai-model-should-i-use-with-github-copilot/ - Équilibre coût/performance : GPT-4.1, GPT-4o ou Claude 3.5 Sonnet pour des tâches générales et multilingues. - Tâches rapides : o4-mini ou Claude 3.5 Sonnet pour du prototypage ou de l'apprentissage rapide. - Besoins complexes : Claude 3.7 Sonnet, GPT-4.5 ou o3 pour refactorisation ou planification logicielle. - Entrées multimodales : Gemini 2.0 Flash ou GPT-4o pour analyser images, UI ou diagrammes. - Projets techniques/scientifiques : Gemini 2.5 Pro pour raisonnement avancé et gros volumes de données. UV, un package manager pour les pythonistes qui amène un peu de sanité et de vitesse http://blog.ippon.fr/2025/05/12/uv-un-package-manager-python-adapte-a-la-data-partie-1-theorie-et-fonctionnalites/ pour les pythonistes un ackage manager plus rapide et simple mais il est seulement semi ouvert (license) IntelliJ IDEA 2025.1 permet de rajouter un mode MCP client à l'assistant IA https://blog.jetbrains.com/idea/2025/05/intellij-idea-2025-1-model-context-protocol/ par exemple faire tourner un MCP server qui accède à la base de donnée Méthodologies Développement d'une bibliothèque OAuth 2.1 open source par Cloudflare, en grande partie générée par l'IA Claude: - Prompts intégrés aux commits : Chaque commit contient le prompt utilisé, ce qui facilite la compréhension de l'intention derrière le code. - Prompt par l'exemple : Le premier prompt montrait un exemple d'utilisation de l'API qu'on souhaite obtenir, ce qui a permis à l'IA de mieux comprendre les attentes. - Prompts structurés : Les prompts les plus efficaces suivaient un schéma clair : état actuel, justification du changement, et directive précise. - Traitez les prompts comme du code source : Les inclure dans les commits aide à la maintenance. - Acceptez les itérations : Chaque fonctionnalité a nécessité plusieurs essais. - Intervention humaine indispensable : Certaines tâches restent plus rapides à faire à la main. https://www.maxemitchell.com/writings/i-read-all-of-cloudflares-claude-generated-commits/ Sécurité Un packet npm malicieux passe par Cursor AI pour infecter les utilisateurs https://thehackernews.com/2025/05/malicious-npm-packages-infect-3200.html Trois packages npm malveillants ont été découverts ciblant spécifiquement l'éditeur de code Cursor sur macOS, téléchargés plus de 3 200 fois au total.Les packages se déguisent en outils de développement promettant “l'API Cursor la moins chère” pour attirer les développeurs intéressés par des solutions AI abordables. Technique d'attaque sophistiquée : les packages volent les identifiants utilisateur, récupèrent un payload chiffré depuis des serveurs contrôlés par les pirates, puis remplacent le fichier main.js de Cursor. Persistance assurée en désactivant les mises à jour automatiques de Cursor et en redémarrant l'application avec le code malveillant intégré. Nouvelle méthode de compromission : au lieu d'injecter directement du malware, les attaquants publient des packages qui modifient des logiciels légitimes déjà installés sur le système. Persistance même après suppression : le malware reste actif même si les packages npm malveillants sont supprimés, nécessitant une réinstallation complète de Cursor. Exploitation de la confiance : en s'exécutant dans le contexte d'une application légitime (IDE), le code malveillant hérite de tous ses privilèges et accès. Package “rand-user-agent” compromis : un package légitime populaire a été infiltré pour déployer un cheval de Troie d'accès distant (RAT) dans certaines versions. Recommandations de sécurité : surveiller les packages exécutant des scripts post-installation, modifiant des fichiers hors node_modules, ou initiant des appels réseau inattendus, avec monitoring d'intégrité des fichiers. Loi, société et organisation Le drama OpenRewrite (automatisation de refactoring sur de larges bases de code) est passé en mode propriétaire https://medium.com/@jonathan.leitschuh/when-open-source-isnt-how-openrewrite-lost-its-way-642053be287d Faits Clés : Moderne, Inc. a re-licencié silencieusement du code OpenRewrite (dont rewrite-java-security) de la licence Apache 2.0 à une licence propriétaire (MPL) sans consultation des contributeurs. Ce re-licenciement rend le code inaccessible et non modifiable pour les contributeurs originaux. Moderne s'est retiré de la Commonhaus Foundation (dédiée à l'open source) juste avant ces changements. La justification de Moderne est la crainte que de grandes entreprises utilisent OpenRewrite sans contribuer, créant une concurrence. Des contributions communautaires importantes (VMware, AliBaba) sous Apache 2.0 ont été re-licenciées sans leur consentement. La légalité de ce re-licenciement est incertaine sans CLA des contributeurs. Cette action crée un précédent dangereux pour les futurs contributeurs et nuit à la confiance dans l'écosystème OpenRewrite. Corrections de Moderne (Suite aux réactions) : Les dépôts Apache originaux ont été restaurés et archivés. Des versions majeures ont été utilisées pour signaler les changements de licence. Des espaces de noms distincts (org.openrewrite vs. io.moderne) ont été créés pour différencier les modules. Suggestions de Correction de l'Auteur : Annuler les changements de licence sur toutes les recettes communautaires. S'engager dans le dialogue et communiquer publiquement les changements majeurs. Respecter le versionnement sémantique (versions majeures pour les changements de licence). L'ancien gourou du design d'Apple, Jony Ive, va occuper un rôle majeur chez OpenAI OpenAI va acquérir la startup d'Ive pour 6,5 milliards de dollars, tandis qu'Ive et le PDG Sam Altman travaillent sur une nouvelle génération d'appareils et d'autres produits d'IA https://www.wsj.com/tech/ai/former-apple-design-guru-jony-ive-to-take-expansive-role-at-openai-5787f7da Rubrique débutant Un article pour les débutants sur le lien entre source, bytecode et le debug https://blog.jetbrains.com/idea/2025/05/sources-bytecode-debugging/ le debugger voit le bytecode et le lien avec la ligne ou la methode est potentiellement perdu javac peut ajouter les ligne et offset des operations pour que le debugger les affichent les noms des arguments est aussi ajoutable dans le .class quand vous pointez vers une mauvaise version du fichier source, vous avez des lignes decalées, c'est pour ca peu de raisons de ne pas actier des approches de compilations mais cela rend le fichier un peu plus gros Conférences La liste des conférences provenant de Developers Conferences Agenda/List par Aurélie Vache et contributeurs : 11-13 juin 2025 : Devoxx Poland - Krakow (Poland) 12-13 juin 2025 : Agile Tour Toulouse - Toulouse (France) 12-13 juin 2025 : DevLille - Lille (France) 13 juin 2025 : Tech F'Est 2025 - Nancy (France) 17 juin 2025 : Mobilis In Mobile - Nantes (France) 19-21 juin 2025 : Drupal Barcamp Perpignan 2025 - Perpignan (France) 24 juin 2025 : WAX 2025 - Aix-en-Provence (France) 25 juin 2025 : Rust Paris 2025 - Paris (France) 25-26 juin 2025 : Agi'Lille 2025 - Lille (France) 25-27 juin 2025 : BreizhCamp 2025 - Rennes (France) 26-27 juin 2025 : Sunny Tech - Montpellier (France) 1-4 juillet 2025 : Open edX Conference - 2025 - Palaiseau (France) 7-9 juillet 2025 : Riviera DEV 2025 - Sophia Antipolis (France) 5 septembre 2025 : JUG Summer Camp 2025 - La Rochelle (France) 12 septembre 2025 : Agile Pays Basque 2025 - Bidart (France) 18-19 septembre 2025 : API Platform Conference - Lille (France) & Online 23 septembre 2025 : OWASP AppSec France 2025 - Paris (France) 25-26 septembre 2025 : Paris Web 2025 - Paris (France) 2-3 octobre 2025 : Volcamp - Clermont-Ferrand (France) 3 octobre 2025 : DevFest Perros-Guirec 2025 - Perros-Guirec (France) 6-7 octobre 2025 : Swift Connection 2025 - Paris (France) 6-10 octobre 2025 : Devoxx Belgium - Antwerp (Belgium) 7 octobre 2025 : BSides Mulhouse - Mulhouse (France) 9 octobre 2025 : DevCon #25 : informatique quantique - Paris (France) 9-10 octobre 2025 : Forum PHP 2025 - Marne-la-Vallée (France) 9-10 octobre 2025 : EuroRust 2025 - Paris (France) 16 octobre 2025 : PlatformCon25 Live Day Paris - Paris (France) 16 octobre 2025 : Power 365 - 2025 - Lille (France) 16-17 octobre 2025 : DevFest Nantes - Nantes (France) 30-31 octobre 2025 : Agile Tour Bordeaux 2025 - Bordeaux (France) 30-31 octobre 2025 : Agile Tour Nantais 2025 - Nantes (France) 30 octobre 2025-2 novembre 2025 : PyConFR 2025 - Lyon (France) 4-7 novembre 2025 : NewCrafts 2025 - Paris (France) 5-6 novembre 2025 : Tech Show Paris - Paris (France) 6 novembre 2025 : dotAI 2025 - Paris (France) 7 novembre 2025 : BDX I/O - Bordeaux (France) 12-14 novembre 2025 : Devoxx Morocco - Marrakech (Morocco) 13 novembre 2025 : DevFest Toulouse - Toulouse (France) 15-16 novembre 2025 : Capitole du Libre - Toulouse (France) 19 novembre 2025 : SREday Paris 2025 Q4 - Paris (France) 20 novembre 2025 : OVHcloud Summit - Paris (France) 21 novembre 2025 : DevFest Paris 2025 - Paris (France) 27 novembre 2025 : DevFest Strasbourg 2025 - Strasbourg (France) 28 novembre 2025 : DevFest Lyon - Lyon (France) 5 décembre 2025 : DevFest Dijon 2025 - Dijon (France) 10-11 décembre 2025 : Devops REX - Paris (France) 10-11 décembre 2025 : Open Source Experience - Paris (France) 28-31 janvier 2026 : SnowCamp 2026 - Grenoble (France) 2-6 février 2026 : Web Days Convention - Aix-en-Provence (France) 3 février 2026 : Cloud Native Days France 2026 - Paris (France) 23-25 avril 2026 : Devoxx Greece - Athens (Greece) 17 juin 2026 : Devoxx Poland - Krakow (Poland) 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/
01. Ive, David Guetta - Supernova Love (Record Mix) 02. Lufthaus, Sophie Ellis-Bextor - Immortal (Record Mix) 03. Zhu - Faded (Record Mix) 04. Joel Corry, Pickle, Vula - Stay Together (Baby Baby) (Record Mix) 05. Basto! - Gregory's Theme (Record Mix) 06. Riton, Nightcrawlers, Mufasa, Hypeman - Friday (Record Mix) 07. C-Bool, Giang Pham - DJ Is Your Second Name (Record Mix) 08. Twocolors - Heavy Metal Love (Record Mix) 09. Saint Jhn, Imanbek - Roses (Record Mix) 10. Doechii, Dj Dark - Anxiety (Record Mix) 11. Robin Schulz, James Blunt - OK (Record Mix) 12. Calvin Harris, John Newman - Blame! (Record Mix) 13. Gamuel Sori, Lovespeake, Amice - Us (Record Mix) 14. Oliver Heldens, Becky Hill - Gecko (Overdrive) (Record Mix) 15. Zerb, The Chainsmokers, Ink - Addicted (Record Mix) 16. Lunax, Mia Amare - Sweet Harmony (Record Mix) 17. Showtek, Smack, Sam Gray - Take My Heart Away (Record Mix) 18. Nicky Romero, Vikkstar, Alpharock, Oaks - Where Do I Go (Record Mix) 19. Anna Naklab, Younotus, Alle Farben - Supergirl (Record Mix) 20. Fisher, Aatig - Take It Off (Record Mix) 21. Sean Finn - Give It to Me (Record Mix) 22. Firebeatz, Dubdogz - Give It Up (Record Mix) 23. Kris Kross Amsterdam, Eyelar - Mr. Lie To Me (Record Mix) 24. Ray Dalton, Amice - All We Got (Record Mix) 25. Tiesto - Lay Low (Record Mix) 26. Sarah De Warren, Charming Horses, Hanno, Amice - This is the life (Record Mix) 27. John Summit - La Danza (Record Mix) 28. Dj Dimixer, Favia - One of Us (Record Mix) 29. Filatov & Karas - Au Au (Record Mix) 30. Max Oazo - Gimme! Gimme! Gimme! (Record Mix) 31. Usher, Lusso, Redliners - Yeah! (Record Mix) 32. Alok, Gryffin, Julia Church - Never Letting Go (Record Mix) 33. Alan Walker, A$Ap Rocky, Uslord, Xtv$ - Live Fast (PUBGM) (Record Mix) 34. Otnicka, Kaskeiyp - For an Angel (Record Mix) 35. Dynoro, Gigi D'Agostino - In My Mind... (Record Mix) 36. Semm, Orfa - How Deep Is Your Love (Record Mix) 37. Armin Van Buuren, Sam Gray - Dream a Little Dream (Record Mix) 38. Martin Garrix - Animals! (Record Mix) 39. Kylie Minogue - Lights Camera Action (Record Mix) 40. Block & Crown, Daisy - Mr Vain (Record Mix) 41. Alok, Ella Eyre, Kenny Dope, Never Dull - Deep Down (Record Mix) 42. Jerome Robins, Karsten Sollors - Don't Stop The Music (Record Mix) 43. Jonas Blue, Jp Cooper - Perfect Strangers (Record Mix) 44. Topcover - First Day (Record Mix) 45. Pascal Letoublon, Leony - Friendships (Record Mix) 46. David Guetta - Family Affair (Dance For Me) (Record Mix) 47. Lola Young, Ted Bear - Messy (Record Mix) 48. Hugel, Topic, Arash, Daecolm - I Adore You (Record Mix) 49. Klaas - The Way (Record Mix) 50. Axwell, Ingrosso - More Than You Know (Record Mix) 51. Richard Grey - At Night (Record Mix) 52. Relanium, Deen West - Leel Lost (Record Mix) 53. Playmen, Valeron, Klavdia - Touch Me (Record Mix) 54. Don Diablo - The Way I Are (Record Mix) 55. Arc North, Cour, New Beat Order, Lunis - Faded (Record Mix) 56. Mark Dann, Giovanni Ricci - Let Me Die (Record Mix) 57. Ian Carey, Michelle Shellers, Manyfew, Joe Stone - Keep On Rising (Record Mix) 58. Dimitri Vegas, Vin Diesel, Zion - Don't Stop The Music (Record Mix) 59. Faul, Wad, Pnau - Changes (Record Mix) 60. Avalan Rokston, Alex Caspian - Something to Believe In (Record Mix) 61. Basto! - I Rave You (Record Mix) 62. Jack Harlow, Dj Dark - Lovin On Me (Record Mix) 63. Robin Schulz, Jasmine Thompson - Sun Goes Down (Record Mix) 64. Kygo, Ava Max, Tiesto - Whatever (Record Mix) 65. Alesso, Calvin Harris - Under Control (Record Mix) 66. Fred Again.., The Blessed Madonna - Marea (Weve Lost Dancing) (Record Mix) 67. Oneil, Kanvise, Smola - Boys (Record Mix) 68. Bob Sinclar, Steve Edwards, Fisher - World, Hold On (Record Mix) 69. Twocolors, Roe Byrne, Amice - Stereo (Record Mix) 70. Aaron Smith, Luvli, Krono - Dancin' (Record Mix) 71. Tayna, Marshmello, Ukay - Si Ai (Record Mix) 72. Titov - Philosophy (Record Mix) 73. Pradov, Jaedo - Feel the Music (Record Mix) 74. Charli Xcx, Sam Smith - In The City (Record Mix) 75. Felix Jaehn, Shouse - Walk With Me (Record Mix) 76. Dj Antoine, Tom Novy - Superstar (Record Mix) 77. Going Deeper - Hypnotized (Record Mix) 78. Avicii - Levels (Record Mix) 79. Purple Disco Machine, Sophie & The Giants, Denis F - In The Dark (Record Mix) 80. Goodboys, Nu Aspect, Avaion - Blindspot (Record Mix) 81. Maruv, Boosin - Drunk Groove (Record Mix) 82. Tommy Cash - Espresso Macchiato (Record Mix) 83. Plastik Funk, Jay Hardway - Coming Home (Record Mix) 84. Annabell Kowalski - Hey Boy Hey Girl (Record Mix) 85. David Guetta, Sia - Beautiful People (Record Mix) 86. Lilly Wood, Prick, Robin Schulz - Prayer In C (Record Mix) 87. Matt Sassari, Sidepiece - Elektro (Record Mix) 88. Loreen, Denis First - Tattoo (Record Mix) 89. R3Hab, Mufasa, Rani - Believe (Record Mix) 90. Byor - Superstar (Record Mix) 91. Gorgon City, Romans - Saving My Life (Record Mix) 92. Calvin Harris, Rag'N'Bone Man - Giant (Record Mix) 93. Dezko - Ascend (Record Mix) 94. Lana Del Rey, Kevin Blanc - Young & Beautiful (Record Mix) 95. Modjo - Lady (Hear Me Tonight) (Record Mix) 96. Imanbek, Younotus - Heal My Heart (Record Mix) 97. Philip George - Wish You Were Mine (Record Mix) 98. Crazibiza - Fresh (Record Mix) 99. Tony Igy - Cascade (Record Mix) 100. Galwaro, Lizot, Gabry Ponte - Like a Prayer (Record Mix) 101. Bodybangers, Stephen Oaks - See You Again (Record Mix) 102. Kygo, Sandro Cavazza - Hold On Me (Record Mix) 103. Galantis - Runaway (U & I) (Record Mix) 104. Tiesto - The Business (Record Mix) 105. Avicii - Fade into Darkness (Record Mix) 106. Teriyaki Boyz, Hayat - Tokyo Drift (Record Mix) 107. Lady Gaga - Abracadabra (Record Mix) 108. Lufthaus, Sophie Ellis-Bextor - Immortal (Record Mix) 109. Alex Gaudino, Blender, Ragdoll - I LUV U (Sunny) (Record Mix) 110. Junior Jack - Stupidisco (Record Mix) 111. Diplo, Maren Morris - 42 (Record Mix) 112. Lost Culture, Morfi, Carine - Lean On (Record Mix) 113. Аигел, Amice - Пыяла (Record Mix) 114. Marshmello, Jonas Brothers, Alex Caspian - Slow Motion (Record Mix) 115. Dj Dimixer - Sweet Melody (Record Mix) 116. Cyril, Dean Lewis, Amice - Fall At Your Feet (Record Mix) 117. Fast Boy, Raf, Amice - Wave (Record Mix) 118. Topic, A7S - Breaking Me (Record Mix) 119. Noizu, Joshwa - Get Rockin' (Record Mix) 120. Tujamo, Azteck, Inna - Freak (Record Mix) 121. Fisher, Flowdan - Boost Up (Record Mix) 122. Alle Farben - Bad Ideas (Record Mix) 123. Swanky Tunes, Shapov - Wannabe (Record Mix) 124. Twocolors - Heavy Metal Love (Record Mix) 125. C Block, The Distance, Riddick - So Strung Out (Record Mix) 126. Alan Walker, Yuqi, Jvke - Fire! (Record Mix) 127. David Guetta, Cedric Gervais, Chris Willis - Would I Lie to You (Record Mix) 128. Filatov & Karas, Busy Reno - Au Revoir (Record Mix) 129. Purple Disco Machine, Kungs - Substitution (Record Mix) 130. Maurizio Basilotta, Mf Productions - You're Not Alone (Record Mix) 131. Shouse - Love Tonight (Record Mix) 132. Empire Of The Sun, Tony Romera - Walking on a dream (Record Mix) 133. R3Hab, Sophie And The Giants - All Night (Record Mix) 134. Basto!, Yves V - Cloud Breaker (Record Mix) 135. Usher, Lusso, Redliners - Yeah! (Record Mix) 136. Oliver Heldens, Djs From Mars, Jd Davis - Blue Monday (Record Mix) 137. Max Oazo - Gimme! Gimme! Gimme! (Record Mix) 138. Don Diablo - Momentum (Record Mix) 139. Mabel - Let Them Know (Record Mix) 140. Calvin Harris, Ellie Goulding - Outside (Record Mix)
Andriy Burkov talks down dishonest hype and sets realistic expectations for when LLMs, if properly and critically applied, are useful. Although maybe not as AI agents. Andriy and Kimberly discuss how he uses LLMs as an author; LLMs as unapologetic liars; how opaque training data impacts usability; not knowing if LLMs will save time or waste it; error-prone domains; when language fluency is useless; how expertise maximizes benefit; when some idea is better than no idea; limits of RAG; how LLMs go off the rails; why prompt engineering is not enough; using LLMs for rapid prototyping; and whether language models make good AI agents (in the strictest sense of the word). Andriy Burkov holds a PhD in Artificial Intelligence and is the author of The Hundred Page Machine Learning and Language Models books. His Artificial Intelligence Newsletter reaches 870,000+ subscribers. Andriy was previously the Machine Learning Lead at Talent Neuron and the Director of Data Science (ML) at Gartner. He has never been a Ukrainian footballer. Related Resources The Hundred Page Language Models Book: https://thelmbook.com/ The Hundred Page Machine Learning Book: https://themlbook.com/ True Positive Weekly (newsletter): https://aiweekly.substack.com/ A transcript of this episode is here.
AI wants your data, but it can't handle the truth . . . “We'll just plug our data into ChatGPT.” Sure. Sounds easy. Rob thought so too, right up until he hit token limits, had to install Python, and discovered that even two megabytes of transcripts was too much for the world's smartest models to handle. In this episode, Rob and Justin break down what happens when you try to use AI on your company's internal data. Spoiler: it's a lot more complicated than the vendors make it sound. From semantic search to retrieval augmented generation (RAG), they unpack why the dream of “ask AI anything about your business” keeps falling short. You'll hear why your Power BI model isn't going anywhere, why structured data still needs old-school engines, and what it really takes to get value from your own information. Somewhere between a cautionary tale and a tech detective story, this one tells it like it is . . . unapologetically. Run into the same situation? We'd love to hear about it! Give us a shout on LinkedIn and tell us how you overcame the limitations.
Security leaders from Anthropic and AWS discuss how agentic AI is transforming cybersecurity functions to autonomously handle everything from code reviews to SOC operations.Topics Include:Agentic AI differs from traditional AI through autonomy and agencyTraditional AI handles single workflow nodes, agents collapse multiple stepsHigher model intelligence enables understanding of broader business contextsAgents make intelligent decisions across complex multi-step workflows processesEnterprise security operations are seeing workflow consolidation through GenAIOrganizations embedding GenAI directly into customer-facing production applicationsSoftware-as-a-service transitioning to service-as-software through AI agentsSecuring AI requires guardrails to prevent hallucinations in applicationsNew vulnerabilities appear at interaction points between system componentsAttackers target RAG systems and identity/authorization layers insteadLLMs hallucinate non-existent packages, attackers create malicious honeypotsGovernance frameworks must be machine-readable for autonomous agent reasoningAmazon investing in automated reasoning to prove software correctnessAnthropic uses Claude to write over 50% of codeAutomated code review systems integrated into CI/CD pipelinesSecurity design reviews use MITRE ATT&CK framework automationLow-risk assessments enable developers to self-approve security reviews40% reduction in application security team review workloadAnthropic eliminated SOC, replaced entirely with Claude-based automationIT support roles transitioning to engineering as automation replaces frontlineCompliance questionnaires fully automated using agentic AI workflowsISO 42001 framework manages AI deployment risks alongside securityExecutive risk councils evaluate AI risks using traditional enterprise processesAWS embeds GenAI into testing, detection, and user experienceFinding summarization helps L1 analysts understand complex AWS environmentsAmazon encourages teams to "live in the future" with AIInterview candidates expected to demonstrate Claude usage during interviewsSecurity remains biggest barrier to enterprise AI adoption beyond POCsVirtual employees predicted to arrive within next 12 monthsModel Context Protocol (MCP) creates new supply chain security risksParticipants:Jason Clinton – Chief Information Security Officer, AnthropicGee Rittenhouse – Vice President, Security Services, AWSHart Rossman – Vice President, Global Services Security, AWSBrian Shadpour – GM of Security and B2B Software Sales, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
↳ Why is Anthropic in hot water with Reddit? ↳ Will OpenAI become the de facto business AI tool? ↳ Did Apple make a mistake in its buzzworthy AI study? ↳ And why did Google release a new model when it was already on top? So many AI questions. We've got the AI answers.Don't waste hours each day trying to keep up with AI developments.We do that for you on Mondays with our weekly AI News That Matters segment.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Have a question? Join the convo here.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:OpenAI's Advanced Voice Mode UpdateReddit's Lawsuit Against AnthropicOpenAI's New Cloud ConnectorsGoogle's Gemini 2.5 Pro ReleaseDeepSeek Accused of Data SourcingAnthropic Cuts Windsurf Claude AccessApple's AI Reasoning Models StudyMeta's Investment in Scale AITimestamps:00:00 Weekly AI News Summary04:27 "Advanced Voice Mode Limitations"09:07 Reddit's Role in AI Tensions10:23 Reddit's Impact on Content Strategy16:10 "RAG's Evolution: Accessible Data Insights"19:16 AI Model Update and Improvements22:59 DeepSeek Accused of Data Misuse24:18 DeepSeek Accused of Distilling AI Data28:20 Anthropic Limits Windsurf Cloud Access32:37 "Study Questions AI Reasoning Models"36:06 Apple's Dubious AI Research Tactics39:36 Meta-Scale AI Partnership Potential40:46 AI Updates: Apple's Gap Year43:52 AI Updates: Voice, Lawsuits, ModelsKeywords:Apple AI study, AI reasoning models, Google Gemini, OpenAI, ChatGPT, Anthropic, Reddit lawsuit, Large Language Model, AI voice mode, Advanced voice mode, Real-time language translation, Cloud connectors, Dynamic data integration, Meeting recorder, Coding benchmarks, DeepSeek, R1 model, Distillation method, AI ethics, Windsurf, Claude 3.x, Model access, Privacy and data rights, AI research, Meta investment, Scale AI, WWDC, Apple's AI announcements, Gap year, On-device AI models, Siri 2.0, AI market strategy, ChatGPT teams, SharePoint, OneDrive, HubSpot, Scheduled actions, Sparkify, VO3, Google AI Pro plan, Creative AI, Innovation in AI, Data infrastructure.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Try Google Veo 3 today! Sign up at gemini.google to get started. Try Google Veo 3 today! Sign up at gemini.google to get started.
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today, we're joined by Charles Martin, founder of Calculation Consulting, to discuss Weight Watcher, an open-source tool for analyzing and improving Deep Neural Networks (DNNs) based on principles from theoretical physics. We explore the foundations of the Heavy-Tailed Self-Regularization (HTSR) theory that underpins it, which combines random matrix theory and renormalization group ideas to uncover deep insights about model training dynamics. Charles walks us through WeightWatcher's ability to detect three distinct learning phases—underfitting, grokking, and generalization collapse—and how its signature “layer quality” metric reveals whether individual layers are underfit, overfit, or optimally tuned. Additionally, we dig into the complexities involved in fine-tuning models, the surprising correlation between model optimality and hallucination, the often-underestimated challenges of search relevance, and their implications for RAG. Finally, Charles shares his insights into real-world applications of generative AI and his lessons learned from working in the field. The complete show notes for this episode can be found at https://twimlai.com/go/734.
What does it take to bill over $1 million a year for seven years straight, while leading the highest-performing team in your company?On this week's episode of The RAG Podcast, I'm joined by Jay Wynter, SAP Practice Lead at Precision Sourcing in Australia. From a tough start in recruitment to becoming a standout performer, Jay has built an elite billing record and helped shape a team known for its consistency and culture.In this episode, we discussHow Jay has billed $1 million annually for seven consecutive yearsThe leadership mindset that built the most consistent team in the businessHow personal branding and podcasting helped deepen relationshipsWhy balancing delivery, culture and family is at the heart of his approachIf you're serious about high performance in recruitment—either as a biller or a leader—this is the one to watch.Chapters00:00 Introduction to The Rag Podcast and Guest Introduction01:07 Jay Wynter's Journey to Australia and Recruitment07:25 Transition from Football to Recruitment14:29 Early Challenges in Recruitment19:45 Adapting to COVID-19 and Leadership Response23:02 Embracing LinkedIn and Personal Branding27:29 Early Wins and Building a Personal Brand28:52 The Power of Podcasting in Recruitment31:37 Leadership and Team Dynamics36:19 Value-Driven Recruitment Strategies41:36 Work-Life Balance and Family Impact47:55 Future of Recruitment and Business Growth__________________________________________Episode Sponsor: AtlasYour memory isn't perfect. So Atlas remembers everything for you. Atlas is an end-to-end recruitment platform built for the AI generation. It automates your admin so you can focus on the business tasks that matter. How many conversations do you have every day? With clients. Candidates. Your team. Service providers.Now how many of those conversations can you recall with 100% accuracy? How many hours a week do you spend making notes to try and retain as much as possible? And how much is still getting lost along the way? Traditional CRM systems weren't built for the type of recruitment business you're running right now. They were built to rely on the structured, tagged, categorised, and formal data you could feed it. Manual processes that needed you to input specific information, based on specific questions and answers. But what about all the other conversations you're having every single day? Atlas isn't an ATS or a CRM. It's an Intelligent Business Platform that helps you perform 10X better than you could on your own. How? By removing all your low value tasks, acting as your perfect memory, and providing highly relevant recommendations to impact your performance. Learn more about the power of Atlas – and take advantage of the exclusive offer for The RAG listeners – by visiting https://recruitwithatlas.com/therag/ __________________________________________Episode Sponsor: HoxoRecruitment agency founders - this one's for you.What's your plan for the rest of 2025?If it's based on more cold outreach, referrals, or hiring more recruiters… we've got news for you. That's not where the smart money is going.The market has changed. AI is everywhere. Noise is louder than ever.So if you want to scale profitably this year, you need to do things differently!It starts with what you already have.Your experience. Your network. Your voice.And we are showing you exactly how to use it in a brand-new, FREE Masterclass - built specifically for recruitment leaders like you.You're going to...
What if you could use ElasticSearch serverless? While at Build, Carl and Richard chatted with Ken Exner about the new announcements around Elastic providing serverless storage and search! Ken talks about paying for only the data you move and store with serverless, rather than needing to operate any infrastructure for Elastic. The conversation digs into the potential of Elastic in Azure AI Foundry to provide ultra-fast access to current company data for your LLM implementations. Elastic did vector databases before LLMs made them essential for RAG - and you can take advantage of it!
What if the smartest people in finance and law never had to do “stupid tasks” again? In this episode, we sit down with George Sivulka, founder of Hebbia, the AI company quietly powering 50% of the world's largest asset managers and some of the fastest-growing law firms. George reveals how Hebbia's Matrix platform is automating the equivalent of 50,000 years of human reading — every year — and why the future of work is hybrid teams of humans and AI “agent employees.” You'll get the inside story on how Hebbia went from a stealth project at Stanford to a multinational company trusted by the Department of Defense, and why their spreadsheet-inspired interface is leaving chatbots in the dust. George breaks down the technical secrets behind Hebbia's ISD architecture (and why they killed RAG), how they process billions of pages with near-zero hallucinations, and what it really takes to sell AI into the world's most regulated industries.We also dive into the future of organizational design, why generalization beats specialization in AI, and how “prompting is the new management skill.” Plus: the real story behind AI hallucinations, the myth of job loss, and why naiveté might be the ultimate founder superpower.HebbiaWebsite - https://www.hebbia.comTwitter - https://x.com/HebbiaAIGeorge SivulkaLinkedIn - https://www.linkedin.com/in/sivulkaTwitter - https://x.com/gsivulkaFIRSTMARKWebsite - https://firstmark.comTwitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/Twitter - https://twitter.com/mattturck(00:00) Intro (01:46) What is Hebbia (02:49) Evolving Hebbia's mission (04:45) The founding story and Stanford's inspiration (09:45) The rise of agent employees and AI in organizations (12:36) The future of AI-powered work (15:17) AI research trends (19:49) Inside Matrix: Hebbia's flagship AI platform (24:02) Why Hebbia isn't just another chatbot (28:27) Moving beyond RAG: Hebbia's unique architecture (34:10) Tackling hallucinations in high-stakes AI (35:59) Research culture and avoiding industry groupthink (39:40) Innovating go-to-market and enterprise sales (41:57) Real-world value: Cost savings and new revenue (43:49) How AI is changing junior roles (45:55) Leadership and perspective as a young founder (47:16) Hebbia's roadmap: Success in the next 3 years
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today, we're joined by Sebastian Gehrmann, head of responsible AI in the Office of the CTO at Bloomberg, to discuss AI safety in retrieval-augmented generation (RAG) systems and generative AI in high-stakes domains like financial services. We explore how RAG, contrary to some expectations, can inadvertently degrade model safety. We cover examples of unsafe outputs that can emerge from these systems, different approaches to evaluating these safety risks, and the potential reasons behind this counterintuitive behavior. Shifting to the application of generative AI in financial services, Sebastian outlines a domain-specific safety taxonomy designed for the industry's unique needs. We also explore the critical role of governance and regulatory frameworks in addressing these concerns, the role of prompt engineering in bolstering safety, Bloomberg's multi-layered mitigation strategies, and vital areas for further work in improving AI safety within specialized domains. The complete show notes for this episode can be found at https://twimlai.com/go/732.
At inference, large language models use in-context learning with zero-, one-, or few-shot examples to perform new tasks without weight updates, and can be grounded with Retrieval Augmented Generation (RAG) by embedding documents into vector databases for real-time factual lookup using cosine similarity. LLM agents autonomously plan, act, and use external tools via orchestrated loops with persistent memory, while recent benchmarks like GPQA (STEM reasoning), SWE Bench (agentic coding), and MMMU (multimodal college-level tasks) test performance alongside prompt engineering techniques such as chain-of-thought reasoning, structured few-shot prompts, positive instruction framing, and iterative self-correction. Links Notes and resources at ocdevel.com/mlg/mlg35 Build the future of multi-agent software with AGNTCY Try a walking desk stay healthy & sharp while you learn & code In-Context Learning (ICL) Definition: LLMs can perform tasks by learning from examples provided directly in the prompt without updating their parameters. Types: Zero-shot: Direct query, no examples provided. One-shot: Single example provided. Few-shot: Multiple examples, balancing quantity with context window limitations. Mechanism: ICL works through analogy and Bayesian inference, using examples as semantic priors to activate relevant internal representations. Emergent Properties: ICL is an "inference-time training" approach, leveraging the model's pre-trained knowledge without gradient updates; its effectiveness can be enhanced with diverse, non-redundant examples. Retrieval Augmented Generation (RAG) and Grounding Grounding: Connecting LLMs with external knowledge bases to supplement or update static training data. Motivation: LLMs' training data becomes outdated or lacks proprietary/specialized knowledge. Benefit: Reduces hallucinations and improves factual accuracy by incorporating current or domain-specific information. RAG Workflow: Embedding: Documents are converted into vector embeddings (using sentence transformers or representation models). Storage: Vectors are stored in a vector database (e.g., FAISS, ChromaDB, Qdrant). Retrieval: When a query is made, relevant chunks are extracted based on similarity, possibly with re-ranking or additional query processing. Augmentation: Retrieved chunks are added to the prompt to provide up-to-date context for generation. Generation: The LLM generates responses informed by the augmented context. Advanced RAG: Includes agentic approaches—self-correction, aggregation, or multi-agent contribution to source ingestion, and can integrate external document sources (e.g., web search for real-time info, or custom datasets for private knowledge). LLM Agents Overview: Agents extend LLMs by providing goal-oriented, iterative problem-solving through interaction, memory, planning, and tool usage. Key Components: Reasoning Engine (LLM Core): Interprets goals, states, and makes decisions. Planning Module: Breaks down complex tasks using strategies such as Chain of Thought or ReAct; can incorporate reflection and adjustment. Memory: Short-term via context window; long-term via persistent storage like RAG-integrated databases or special memory systems. Tools and APIs: Agents select and use external functions—file manipulation, browser control, code execution, database queries, or invoking smaller/fine-tuned models. Capabilities: Support self-evaluation, correction, and multi-step planning; allow integration with other agents (multi-agent systems); face limitations in memory continuity, adaptivity, and controllability. Current Trends: Research and development are shifting toward these agentic paradigms as LLM core scaling saturates. Multimodal Large Language Models (MLLMs) Definition: Models capable of ingesting and generating across different modalities (text, image, audio, video). Architecture: Modality-Specific Encoders: Convert raw modalities (text, image, audio) into numeric embeddings (e.g., vision transformers for images). Fusion/Alignment Layer: Embeddings from different modalities are projected into a shared space, often via cross-attention or concatenation, allowing the model to jointly reason about their content. Unified Transformer Backbone: Processes fused embeddings to allow cross-modal reasoning and generates outputs in the required format. Recent Advances: Unified architectures (e.g., GPT-4o) use a single model for all modalities rather than switching between separate sub-models. Functionality: Enables actions such as image analysis via text prompts, visual Q&A, and integrated speech recognition/generation. Advanced LLM Architectures and Training Directions Predictive Abstract Representation: Incorporating latent concept prediction alongside token prediction (e.g., via autoencoders). Patch-Level Training: Predicting larger “patches” of tokens to reduce sequence lengths and computation. Concept-Centric Modeling: Moving from next-token prediction to predicting sequences of semantic concepts (e.g., Meta's Large Concept Model). Multi-Token Prediction: Training models to predict multiple future tokens for broader context capture. Evaluation Benchmarks (as of 2025) Key Benchmarks Used for LLM Evaluation: GPQA (Diamond): Graduate-level STEM reasoning. SWE Bench Verified: Real-world software engineering, verifying agentic code abilities. MMMU: Multimodal, college-level cross-disciplinary reasoning. HumanEval: Python coding correctness. HLE (Human's Last Exam): Extremely challenging, multimodal knowledge assessment. LiveCodeBench: Coding with contamination-free, up-to-date problems. MLPerf Inference v5.0 Long Context: Throughput/latency for processing long contexts. MultiChallenge Conversational AI: Multiturn dialogue, in-context reasoning. TAUBench/PFCL: Tool utilization in agentic tasks. TruthfulnessQA: Measures tendency toward factual accuracy/robustness against misinformation. Prompt Engineering: High-Impact Techniques Foundational Approaches: Few-Shot Prompting: Provide pairs of inputs and desired outputs to steer the LLM. Chain of Thought: Instructing the LLM to think step-by-step, either explicitly or through internal self-reprompting, enhances reasoning and output quality. Clarity and Structure: Use clear, detailed, and structured instructions—task definition, context, constraints, output format, use of delimiters or markdown structuring. Affirmative Directives: Phrase instructions positively (“write a concise summary” instead of “don't write a long summary”). Iterative Self-Refinement: Prompt the LLM to review and improve its prior response for better completeness, clarity, and factuality. System Prompt/Role Assignment: Assign a persona or role to the LLM for tailored behavior (e.g., “You are an expert Python programmer”). Guideline: Regularly consult official prompting guides from model developers as model capabilities evolve. Trends and Research Outlook Inference-time compute is increasingly important for pushing the boundaries of LLM task performance. Agentic LLMs and multimodal reasoning represent the primary frontiers for innovation. Prompt engineering and benchmarking remain essential for extracting optimal performance and assessing progress. Models are expected to continue evolving with research into new architectures, memory systems, and integration techniques.
© 2020-2025 Ivy Podcast Discovery LLC
