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SUMMARY: Brandon speaks with Rich Ziade, co-founder and CEO of Aboard, about why enterprise AI projects fail without real discovery, why "agents" have been oversold as a headcount play, and why organizational urgency, not new tooling, is what actually makes digital transformation succeed.SHOW: 1057SHOW TRANSCRIPT: The Enterprise AI Show #1057 TranscriptSHOW VIDEO: https://youtu.be/RMgycbmuXGsSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoSHOW LINKS:https://www.aboard.com/https://aboard.com/podcast/Topic 1 - From lawyer to digital transformation CEO: Rich's path through Postlight (with co-founder Paul Ford), the sale in 2021, and how Aboard was already incubating inside Postlight Labs before AI "landed like a spaceship."Topic 1a - The six months after ChatGPT arrived: why Aboard resisted rushing a prompt-based fix into messy, political, human organizations, and why "vibe coding" convinced them to hang back rather than parachute AI into a company.Topic 2 - The doctor/patient analogy: executives walk in asking for a specific AI "medicine" instead of describing the underlying pain, and why real engagements start with tests and diagnosis, not the prescription the client thinks they want.Topic 2a - Why discovery hasn't fundamentally changed in the AI era — still in-person interviews and observation, with AI mainly useful for note-taking and summarizing documentation, not for skipping the hard thinking.Topic 3 - The agent hype cycle: why Rich thinks the "millions of agents" narrative (including Anthropic's Boris Cherny running swarms of planning/implementation agents) reflects an engineering-execution worldview rather than a product or organizational one — and why he sees the agent narrative cooling off.Topic 3a - The "spreadsheet problem" vs. targeted AI: most of Aboard's actual delivery work (90%+) isn't agents — it's modernizing spreadsheet-run processes and building narrow RAG/vector tools so people can query their own data in plain English.Topic 4 - "Forward deployed" as the new name for an old idea — going on-site, listening, and understanding a client's world before proposing a solution.Topic 5 - Why no successful digital transformation starts without a real, externally imposed deadline or crisis — and why "innovation labs" without urgency rarely ship anything.Topic 6 - Lightning round: Is AI a bubble? Should GPUs be securitized assets? Three things to do in NYC in one day.FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow
As the 2026-27 athletics calendar begins, Ben Weiner Director of Athletics David Harris sits down with Corey for a wide-ranging, extensive conversation on the Wave. A new era begins for Tulane football under Will Hall, with the Wave garnering major attention for the City Edition Mardi Gras uniforms and the return of The Battle for the Rag in 2030. As college athletics changes rapidly, David addresses Tulane's approach to new eligibility rules, increasing scholarship numbers and more. Plus, his goals for the 2026-27 season.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Software Engineering Radio - The Podcast for Professional Software Developers
Sathiesh Veera, a GenAI Solutions Architect at At&T, speaks with host Brijesh Ammanath about the data-protection guardrails required when using LLMs. The core issue is that LLMs sit outside the cloud tenant in most enterprise AI deployments, which means that data leaves the company's perimeter with every prompt, RAG retrieval, and tool call. Contractual agreements can restrict the data that LLM vendors are allowed to use for training and audits, but they don't stop prompt injection or unintended exposure as company data is often shared to LLMs via natural language queries, APIs, tool and function calls, and MCPs. Sathiesh discusses ways to employ security measures and data filtering at each layer to conform to data security policies and protect the data.
Stewart Alsop sits down with Juan Verhook, founder of Tender Market, for a second conversation that ranges from the mechanics of European public tenders to the future of how we organize digital information. They cover how Tender Market helps smaller companies work around barriers like SOC 2 and ISO certification requirements, the surprising scale of public procurement (roughly 20% of GDP), and how AI and machine learning are reshaping the bidding process. From there the conversation opens up into bigger territory: the changing tolerance for being wrong in an AI-saturated information landscape, how language and culture shape perception, the reverse Turing test and the challenge of verifying human versus AI identity online, and Juan's daily workflow running eight or nine MCP servers through Claude Code. They close out talking about whether the folder and file system will survive the shift to AI-native interfaces, tying back to Stewart's own Stewart Squared episodes on the history of the PC. You can visit Tender Market at tendermarket.eu.Timestamps05:00 — Tender Market's origin story and how they help smaller companies work around SOC 2 and ISO certificate barriers.10:00 — Public procurement and its scale, roughly 20% of GDP, plus a look at public-private partnerships.15:00 — Local LLMs on a plane with no Wi-Fi, and comparing local model performance to frontier models.20:00 — Supply versus demand in AI infrastructure and whether hyperscaler token efficiency is quietly improving.25:00 — Whether AI will replace knowledge work tasks, and the shifting reality of what lawyers and other professionals actually do.30:00 — Reverse Turing test, digital identity verification, and the idea of a "pre-AI internet."35:00 — Model poisoning, RLHF, and the difference between pretraining and post-training.40:00 — Interleaved tool calling and how Tender Market ties pricing to task deliverables instead of billable hours.45:00 — RAG versus fine-tuning, prompt engineering, and when context windows actually matter.50:00 — Deterministic programming versus probabilistic agents, and when to build custom tools versus buy existing ones.55:00 — Juan's daily MCP stack (Supabase, GitHub, Calendly, CRM), and whether the folder-and-file system will survive the shift to AI-native interfaces.Key InsightsCertification requirements aren't dead ends—they're routing problems. When smaller companies got rejected from tenders for lacking SOC 2 or ISO certificates, Juan didn't turn them away. He found that EU procurement rules allow bidding as a consortium or subcontracting to a certified partner, turning a disqualifier into a workaround that builds trust with clients.Public procurement is a massive, underexamined market. Roughly 20% of GDP flows through public purchasing of private-sector goods and services, yet most people have no visibility into how tenders work or how governments post and award these contracts.Being wrong has become more socially acceptable. Juan traced this shift to the falling cost of information: in the Stack Overflow era, giving a wrong answer was costly, but now that answers are instant and abundant, both mistakes and corrections happen faster, changing how people learn and communicate.Task-based pricing beats hourly billing for AI-era services. Rather than charging per hour, Tender Market prices around the deliverable, winning a tender, which avoids the perverse incentive of hourly billing to be inefficient and instead rewards actually solving the client's problem.RAG and fine-tuning solve different problems. RAG helps a model reference large documents without hitting context limits, while fine-tuning changes a model's internal weights so it learns new behavior or style. Juan noted that true RAG use cases needing thousands of pages of context are rarer than the hype suggests.Deterministic code should replace repeated LLM calls once a pattern is found. Stewart described his own workflow: solve a task with an LLM a handful of times, then convert the repeated pattern into deterministic software so tokens are no longer spent on it, freeing the model for genuinely new problems.AI agents are never truly autonomous. Both hosts agreed that no matter how many steps an agent chains together, a human operator always initiates the first prompt, meaning accountability and intent trace back to a person even in multi-agent systems.
In today's Cloud Wars AI Minute, I break down the rise of agentic reasoning loops and why their impact on AI token consumption and costs could be significant. Highlights 00:12 — Today's topic is going to be agentic reasoning loops. Everyone's moving to this concept where we can have a planning, act, observe, and reflect type of process, which allows us to be able to get much deeper analysis and much more resilient implementations across AI, across the world. 01:03 — Now, the other thing is with this, we're seeing that about 33% of enterprise software will run on this kind of approach by 2028. Also, the other part of this is that because these different loops are taking place, we're actually seeing that tokens are going to get more and more consumption happening off the back end. 01:38 — So one of the driving factors of this is going to be the increase that we're seeing, and just to give you perspective of what we're starting to see, it's about a 17x on a single chapter that we're starting to see happen as a result of this. So what it used to do when we just did simple RAG patterns. 02:01 — Now we're seeing about 17 times the amount of tokens being consumed, and when we start seeing that level of token consumption, we're going to see that while we're getting better answers, there's also going to be a higher cost that's associated to it. 02:28 — But it doesn't matter that the tokens are necessarily coming down in cost because of the fact that what we used to see is that an average transaction would be about three cents, and now we're seeing it move to about 15 cents across the board, and so this is going to be one of those things that we really need to be thinking about as you start to build out your solutions. Visit Cloud Wars for more.
Send us Fan MailWhat if AI could tap into live operational data — without ETL or RAG? In this episode, Deepti Srivastava, founder of Snow Leopard, reveals how her company is transforming enterprise data access with intelligent data retrieval, semantic intelligence, and a governance-first approach. Tune in for a fresh perspective on the future of AI and the startup journey behind it.We explore how companies are revolutionizing their data access and AI strategies. Deepti Srivastava, founder of Snow Leopard, shares her insights on bridging the gap between live operational data and generative AI — and how it's changing the game for enterprises worldwide.We dive into Snow Leopard's innovative approach to data retrieval, semantic intelligence, and governance-first architecture.04:54 Meeting Deepti Srivastava 14:06 AI with No ETL, no RAG 17:11 Snow Leopard's Intelligent Data Fetching 19:00 Live Query Challenges 21:01 Snow Leopard's Secret Sauce 22:14 Latency 23:48 Schema Changes 25:02 Use Cases 26:06 Snow Leopard's Roadmap 29:16 Getting Started 33:30 The Startup Journey 34:12 A Woman in Technology 36:03 The Contrarian View
Send us Fan MailWhat if AI could tap into live operational data — without ETL or RAG? In this episode, Deepti Srivastava, founder of Snow Leopard, reveals how her company is transforming enterprise data access with intelligent data retrieval, semantic intelligence, and a governance-first approach. Tune in for a fresh perspective on the future of AI and the startup journey behind it.We explore how companies are revolutionizing their data access and AI strategies. Deepti Srivastava, founder of Snow Leopard, shares her insights on bridging the gap between live operational data and generative AI — and how it's changing the game for enterprises worldwide.We dive into Snow Leopard's innovative approach to data retrieval, semantic intelligence, and governance-first architecture.04:54 Meeting Deepti Srivastava 14:06 AI with No ETL, no RAG 17:11 Snow Leopard's Intelligent Data Fetching 19:00 Live Query Challenges 21:01 Snow Leopard's Secret Sauce 22:14 Latency 23:48 Schema Changes 25:02 Use Cases 26:06 Snow Leopard's Roadmap 29:16 Getting Started 33:30 The Startup Journey 34:12 A Woman in Technology 36:03 The Contrarian View
A great copy isn't just a “nice to have” anymore, it's the difference between traffic that prints money and traffic that quietly bleeds your ad budget dry. In a world where attention is short, feeds are noisy, and AI-generated fluff is everywhere, only truly persuasive words cut through and convert. Today's guest, Jon Benson of BNSN.AI, is the copywriter credited with inventing the Video Sales Letter (VSL), a format that has generated billions of dollars in digital sales and reshaped online direct response marketing.In this episode of Marketer of the Day, Jon breaks down the evolution of the “ugly” VSL, from plain text on a black screen with voiceover, to hypnotic slide patterns, NLP command phrases, and innovations like magic buy buttons, no-pause video players, and timed call-to-action reveals. He explains why words on the screen plus spoken words outperform talking-head videos, how dual modalities (reading + listening) supercharge retention, and why removing distractions can multiply conversions even in today's muted, mobile-first world. Jon then pulls back the curtain on Benson (BNSN.AI), his AI-driven copy platform built specifically for high-converting VSLs and funnels. Instead of generic prompts and AI “stink,” Benson uses promptless AI, pre-prompting, frameworks, and RAG to train multiple LLMs on proven copy patterns. You'll hear how his system breaks a VSL into specialized sections, uses different models for different copy tasks, and rewrites behind the scenes so what you see sounds like a top-tier human copywriter, not a template-spitting chatbot. A big theme of this conversation is mindset: you are not your avatar. Jon explains why writing “how you talk” usually kills conversions, why your copy shouldn't sound exactly like you, and how to instead sound like the best version of you that your market will respond to. He shares lessons from decades as a hired gun copywriter and ghostwriter, the importance of writing for cold traffic, and why the words are still 80% of the funnel, even if you use ClickFunnels, GoHighLevel, or any other page builder. https://youtu.be/deBPX78TpHQ?si=wuWrOAUu9AaXn9b- If you've ever been frustrated by weak AI copy, low-converting VSLs, or the feeling that your offer “should” be selling better than it is, this episode will recalibrate how you think about persuasion, funnels, and AI-powered copywriting. You'll walk away with a deeper understanding of what truly moves cold prospects to buy, and how tools like BNSN.AI can help you scale high-quality copy across your entire funnel without sacrificing human-level persuasion. Quotes: “It's not enough to just give AI a good VSL and say ‘you figure it out.' You have to break it into components and get very specific.” “What people call ‘AI stink' is really just AI pulling from the wrong training. If you don't feed it the right patterns, you'll never get what you're wanting.” “The words are the most important things that you have to sell anything… if you get the words that sell, you are 80% there.” Contact Details: Turn AI Into Your Best Copywriter: Start with BNSN Today Master the Words That Sell: Learn from Jon Benson Connect with Jon Benson on LinkedIn and Master Copy That Sells Subscribe to Jon Benson's YouTube Channel for Sales Copy Secrets Follow Jon Benson on Instagram for Daily Copywriting Tips Follow Jon Benson for AI & Copywriting Strategies Master Copywriting: Follow Jon Benson on Facebook
Government software development pipelines are increasingly integrating AI coding assistants, but Air Force Sustainment Center Software Directorate CTO Kurt Jarvis said success depends on improving how developers use existing code, not just generating new code faster. Speaking with GovCIO Media & Research at the Carahsoft DevSecOps Conference, Jarvis outlined an engineer-first approach that uses retrieval-augmented generation (RAG), vector databases and established DevSecOps pipelines to safely accelerate software development. Jarvis said one of the biggest opportunities for AI is helping developers discover and reuse decades of trusted software already maintained by the Air Force. The goal, he said, is to make AI a code‑reuse engine, not a code‑generation machine. He also emphasized that AI has not changed the Air Force's software engineering standards. Existing CI/CD pipelines are still the foundation for evaluating AI-generated code. AI can accelerate development, Jarvis said, but engineering discipline and human oversight remain essential to producing mission-ready software.
AI isn't just transforming the way we work, but also the way we write the software that people use for work. In this episode, we talk to two engineering productivity leads at Dropbox: Uma Namasivayam, senior director of software engineering productivity, and Anuradha Agarwal, director of software engineering. Whether it's writing tests, fixing bugs, tackling tech debt, or accelerating migrations, they explain how Dropbox engineers are using agentic AI—including in-house tools like Nova—to build the future of Dropbox, and create more space to do impactful work. ~ ~ ~ Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!
Join Andreas Walbrodt, CEO and Co-Founder of enclaive, for an essential exploration of cybersecurity, data sovereignty, and business confidentiality in an increasingly cloud-reliant world. While enterprises have spent decades securing data at rest (in storage) and in transit (over networks), sensitive workloads remain completely unencrypted the moment they are processed in memory. As organizations rush to adopt public cloud platforms, scale Industry 4.0 smart manufacturing, and deploy proprietary AI models, this "in-use" vulnerability creates catastrophic exposure to cloud operator access, third-party subpoenas, and cyber threats. Drawing on over 30 years of enterprise IT leadership at IBM and TÜV Rheinland, Andreas explains how confidential computing closes this gap—allowing businesses to leverage hyper-scale cloud power without sacrificing sovereignty, compliance, or core intellectual property.
On the Rag, episode 104: Us Weekly- August 7, 2006 | Tori and Candy Spelling are BEEFING The Sherman Sisters
Plenty of AI assistants can answer the question in front of them. Fewer can work out what someone is actually trying to do and help them do it.In this episode, we're joined by Pete Kowalczyk, AI Conversation Designer at the Government Digital Service (GDS), to talk about designing AI experiences across the vast and complex landscape of UK government services.Pete explains how GDS is exploring knowledge graphs, persistent state and goal detection to move beyond basic RAG systems. The aim is to connect information with action and guide people through non-linear journeys, such as moving house or registering a birth. One of the key goals is to reduce the burden created by fragmented processes and legacy systems.We discuss why conversational systems need to track user goals, how small interaction loops can be built into rich experiences over time and why transitions between stages of a conversation carry so much weight for trust and usability.We also get into progressive disclosure, deciding when an AI should stay concise and when it should offer more, and how to judge whether a link belongs in a response at all. Pete points to a bank surfacing patterns in someone's spending as an example of how organisations can build proactive features from data they already hold, rather than only responding when asked.Pete shares how the designer role is evolving. Designers now need sufficient technical understanding to prototype and work directly with LLMs through practices like vibe coding, while maintaining the creative ability to understand experiences beyond incremental chatbot improvements. He closes with a warning against the industry's current resolution rut, where success gets defined too narrowly as fast ticket resolution rather than genuinely useful, proactive AI.Show notes Follow Pete on LinkedIn:https://www.linkedin.com/in/petekowalczykVideo of Pete's talk at the Conversational AI Meetup in London: https://youtu.be/001PeZv3N0kLead with Tempo 2026: https://www.leadwithtempo.com/2026scheduleLondon Design Festival: https://londondesignfestival.comFollow Kane on LinkedIn:https://www.linkedin.com/in/kanesimmsFind out more about VUX:https://vux.aiSubscribe to VUX World: https://vuxworld.typeform.com/to/Qlo5aaeW?utm_source=podcast&utm_medium=audioSubscribe to The AI Ultimatum Substack: https://open.substack.com/pub/kanesimms
Public Domain AI Flipping: Build & Monetize Custom GPTs With 19th‑Century Books (Before the Window Closes) Make money online by flipping public domain AI content—the overlooked side hustle for busy parents. Learn how to find, repurpose, and sell digital products without creating anything from scratch. This contrarian strategy saves time, cuts through the noise of traditional side gigs, and generates income faster than you think. Perfect for the AI entrepreneur who wants results without the grind. https://DarkHorseEntrepreneur.com The episode explains a “public domain AI flipping” strategy: training custom GPTs on 19th-century public domain books (including Project Gutenberg and the Internet Archive) to create niche, highly specific tools that can be monetized quickly via subscriptions or products. It argues most custom GPT monetization fails due to content creation costs or licensing, but public domain works published on or before 1930 can be used and monetized without copyright barriers, with the public domain expanding yearly. The script outlines a four-step process: pick a narrow vertical with an unmet need, curate matching public domain texts, build a custom GPT using prompts and retrieval-augmented generation (RAG), then monetize via recurring revenue using platforms like GPT Plus, Gumroad, or API interfaces. It recommends verticals such as historical accuracy consulting, academic supplementation, content engines for podcasters, and archival tools, while warning about uncertain platform rules, limited precedent, and the need for distribution over technical execution. 00:00 Intro to public domain AI flipping 01:05 Why Most Custom GPT Monetization Fails 02:10 Clarify U.S. Public-Domain Cutoff 03:40 4-step Mechanism 06:20 RAG & Tightly Sourced Corpus > GPT 08:05 Monetization Options 09:40 Necessary Callouts 11:10 4 Promising Verticals 14:30 Real Trap Warning 17:10 Whiskered Wisdom Custom GPT monetization, Public domain,AI, Project Gutenberg, training data, AI side hustle 2026, ChatGPT, passive income, Public domain, Train GPT on books, RAG, custom chatbot,AI entrepreneur, niche GPT, recurring revenue, how to make money with chatgpt, ChatGPT, GPT-4o, OpenAI, Custom GPT, GPT Store, how to make money online, make money online, ai side gig, digital products for beginners, side hustles, income growth hacks https://DarkHorseEntrepreneur.com Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
In this episode, we reflect on the most impactful themes from season eleven of the HR Data Labs Podcast, emphasizing the transformative role of artificial intelligence (AI) in the world of work. Host David Turetsky discusses how AI has become a central focus across industries, influencing regulation, data governance, organizational change, and HR practices. Tune in for a comprehensive summary of trends, predictions, and key conversations that are shaping HR's future. Key Topics Covered: The dominance of artificial intelligence in season eleven and its influence on HR. The importance of data governance for AI integration, highlighted by insights from Talenode. Practical applications of AI, including the use of large language models and local AI hosting solutions. Discussions with industry experts on AI ethics, security, talent acquisition, and leadership. Predictions and insights about AI's role and regulation in HR over the next six months and beyond. Notable interviews with HR thought leaders discussing organizational change, burnout, women in leadership, and HR technology innovation. Future episodes focusing on pay equity, county-level HR issues, and machine learning use cases. Timestamps: 00:00 - Welcome and season eleven wrap-up overview 00:33 - Changes in HR over the past years and current transformations 01:31 - Introduction of chickens and personal updates 02:29 - Recap of season eleven and its focus on artificial intelligence 03:12 - AI's influence on organizational change, trust, and data governance 03:57 - The importance of data foundations for AI initiatives 04:27 - The increasing integration of AI into daily work and business practices 04:56 - The evolution from early computer use to AI today 05:54 - The proliferation of AI tools in corporate technology stacks 06:24 - Environmental and infrastructure challenges of AI data centers 07:10 - Advances in small form factor AI hardware and local hosting options 08:07 - Real-world AI applications at the desk and secure data practices 09:34 - Building AI models with retrieval-augmented generation (RAG) techniques 10:03 - Resources available at hrdatalabs.ai and hrdatalabs.com 11:02 - Notable interviews, including legal, security, talent acquisition, and leadership insights 12:29 - Reflection on season eleven, personal connections, and upcoming season twelve topics 13:00 - Highlights from upcoming episodes, including county HR challenges and practical AI applications 14:26 - Reviewing past predictions and setting new forecasts for the next six months 15:25 - Using AI to evaluate predictions and industry trends 16:17 - The shift from AI experimentation to measurable ROI in HR 17:44 - Current state of HR AI use cases, human-in-the-loop importance, and regulatory outlook 19:11 - Predicted regulation developments at the state and federal levels 20:44 - Host's forecast: increased progress in AI adoption and ROI validation in HR 22:36 - The impact of AI-related layoffs, rehiring, and reputational considerations 25:02 - Exciting plans for future episodes, conferences, and continued industry insights 26:26 - Appreciation for listeners and partners, and encouragement to follow the show This episode offers a deep dive into the evolving landscape of HR technology, emphasizing AI's transformative potential and ongoing challenges. Whether you're an HR professional, a business leader, or an enthusiast of HR innovation, these insights provide vital context for navigating the future of work.
Eric Chou welcomes Juulia Santala, a Solutions Engineer at Cisco, to discuss her transition from traditional network programmability to cutting-edge AI research. They explore how she moved beyond simple RAG to make AI truly agentic, while solving some hallucination problems in production configurations. They also cover the number one skill network engineers need by 2027,... Read more »
Eric Chou welcomes Juulia Santala, a Solutions Engineer at Cisco, to discuss her transition from traditional network programmability to cutting-edge AI research. They explore how she moved beyond simple RAG to make AI truly agentic, while solving some hallucination problems in production configurations. They also cover the number one skill network engineers need by 2027,... Read more »
Max Learmonth was a professional rugby player who fell into recruitment by accident. He answered one trainee ad at Robert Half, started two weeks later, and never looked back.He climbed fast. £180,000 in his first year, £300,000 in his second, then off the tools rebuilding offices for a global giant. But somewhere in the grind, he lost himself. 'I'd become an arsehole,' he says. 'A typical Wolf of Wall Street recruitment dickhead. All I cared about was what my P&L looked like.'In May 2023, with a young daughter at home, he finally made the move and started again from his kitchen table. He turned down over £500,000 of investment to keep it 100% his. The plan was narrow on purpose: finance and accounting recruitment in the North West, and nothing else.Three years on, Forge Talent is a team of 16 that did £2.4 million in net fee income last year, entirely bootstrapped, built on a single stubborn belief: relationships, not transactions.On this episode of The RAG Podcast, Max breaks down exactly how he did it, the one KPI his whole business runs on each week, and why he thinks the average recruiter is finished while the specialist is only getting started.Max is not building the biggest recruitment business in the country. He is building the most dominant finance and accounting firm the North West has ever seen, and he already has a date on the exit.The difference is that he is doing it in the open, on his own terms, with a team of 16 who all know exactly what the 10-year goal is.If you have ever wondered whether going smaller and more specific is actually the smartest way to grow in the age of AI, this episode is evidence of that idea working right now.The Season 9 finale with Max Learmonth of Forge Talent is available now.----------------------------------------------Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, a CRM that actually understands context.Atlas captures everything you say, hear, read and write. Every interview, every client call, every LinkedIn message, email and WhatsApp, automatically. Not because you typed it up, but because Atlas was listening. Then it goes one step further and tells you the next action to take.So when you need to fill a role, People Search ranks your best candidates and tells you why, no digging required. That same memory turns your BD into a shortlist of exactly who to chase and why, so you win more clients. And when you want to see your pipeline, you just speak to your dashboards and Atlas builds the view for you in real time, tracking only what you care about.Whether you place permanent or contract, Atlas covers both. Its Contract Suite means you never chase a timesheet again, with live margin visibility across every placement. And with its new MCP and API, Atlas plugs straight into your LLMs and the rest of your stack, so the low-value admin that keeps you from billing gets done for you.This is not theory. Atlas customers are seeing 50% higher candidate response rates, a 35% increase in new clients won, 15+ hours saved every week, and monthly billings jumping by 85%. Some agencies are hitting 130% of their annual revenue target after building their business around Atlas.So if you're thinking you need to bolt AI onto your CRM, don't bother. Take a look at Atlas instead.Head to https://recruitwithatlas.com/therag/ to find out more.----------------------------------------------Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn, but AI has turned templated posts and outreach into a commodity. When everyone sounds the same, the market stops listening. The recruiters winning now are the ones the market trusts.At Hoxo we help recruitment founders become the most influential name in their niche, using AI to multiply output while trust stays the product. Our clients turn their existing networks into £100K to £300K in new billings within months. Watch the free RAG listener training to see how: https://hubs.ly/Q03lBpYC0
מה קורה כשאתם שולטים טוב בLLM, אבל רוצים לעלות לשלב הבא וללמוד איך להטמיע במודל את כל הידע, ה־Best Practices וההקשר שלכם, בלי להסביר את עצמכם מחדש בכל שיחה?אירחתי היום את דנה ממן, מייסדת Salted Mind, לשיחה על Second Brain, LLM Wiki ואיך הופכים את מודלי השפה למערכת הפעלה אישית ועסקית.איך פורמטים כמו OKF של גוגל שומרים על סדר ואחידות? איך מונעים ממידע להירקב, מוודאים שהמודל מתבסס על עובדות ולא על ניחושים, ומתי מגיע הרגע שבו חייבים לעבור ל־RAG? בפרק נגענו בכל אלה, וגם באיך רותמים את המערכת לרפלקציה עצמית ולזיהוי פערים בלמידה בזמן אמת.
On the Rag, episode 103: Us Weekly- July 31, 2006 | Pam's Surprise Wedding! The Sherman Sisters Download
Llevo 15 años escribiendo notas, artículos y tutoriales. El resultado: unos 5000 archivos markdown repartidos por mi disco duro. Y, como te puedes imaginar, encontrar algo ahí dentro es como buscar una aguja en un pajar. Por eso en este episodio me he puesto manos a la obra para montar un sistema RAG (Retrieval-Augmented Generation) 100% local, sin depender de APIs externas, sin enviar tus datos a la nube, y con herramientas que ya conoces: SQLite, Ollama y Python.Este es el primero de dos episodios sobre RAG. Aquí nos centramos en construir la base de conocimiento: un pipeline que escanea tus documentos, los trocea en fragmentos manejables, extrae los metadatos del frontmatter YAML, genera embeddings con el modelo bge-m3 de Ollama, y lo guarda todo en una base de datos SQLite con búsqueda FTS5. Todo esto, además, con detección incremental de cambios: la primera ejecución tarda lo que tenga que tardar, pero las siguientes son cuestión de segundos porque solo reprocesa lo que ha cambiado.El stack es sencillo pero potente. SQLite con FTS5 para búsqueda textual, Ollama con bge-m3 para los embeddings, y seis scripts Python que suman unas 1300 líneas. Nada de LangChain, nada de frameworks pesados. Código limpio, comentado y que entiendes de un vistazo. El chunking respeta las cabeceras markdown, usa tiktoken para contar tokens con precisión, y los embeddings se almacenan como BLOBs en la propia SQLite. En el próximo episodio (el 821) usaremos esta base de conocimiento para hacer búsqueda semántica con similitud de coseno, búsqueda híbrida combinando FTS5 con embeddings, y hasta un plugin para Neovim.Puntos clave del episodio:- El problema: 15 años de notas, 5000 archivos, cero capacidad de búsqueda- La solución: RAG local con SQLite + FTS5 + Ollama, todo en tu máquina- Chunking híbrido que respeta cabeceras markdown y usa tiktoken- Pipeline incremental con detección de cambios mediante MD5- Embeddings con bge-m3 (568M parámetros, 1024 dimensiones)- Búsqueda FTS5 con snippet(), colores ANSI y sintaxis avanzada- Errores comunes y cómo solucionarlosSi te gusta el contenido, ya sabes: dale a seguir, compártelo con quien creas que le puede interesar, y déjame un comentario si tienes dudas o sugerencias. La semana que viene, en el episodio 821, montamos la búsqueda semántica y el plugin para Neovim. No te lo pierdas.Capítulos del episodio:0:00 - Introducción: RAG y base de conocimiento local2:12 - El problema: 15 años de notas sin buscar4:58 - La solución: SQLite + FTS5 + Ollama, 100% local7:00 - Escaneo de archivos y extracción de front matter10:20 - Preparación del entorno: Ollama, uv y dependencias12:00 - Chunking: cómo trocear los documentos15:45 - Estructura de la base de datos SQLite17:46 - Pipeline incremental con detección de cambios19:22 - Demo en vivo: consultas y resultados22:44 - Errores comunes y cómo solucionarlos24:10 - Resumen y adelanto del episodio 82125:15 - Despedida y cierreMás información y enlaces en las notas del episodio
What parts of yourself have you learned to hide in order to be taken seriously? My guest on this episode is Mark Heywood, a friend of the show, returning guest and someone I've collaborated with on a number of projects. Episode Summary & Guest ProfileMark has spent more than twenty years working in crisis management and operational resilience, while simultaneously building a successful career as a bestselling novelist, screenwriter and, more recently, stand-up comedian.On the morning we recorded this conversation, Mark published an article marking his fifty-first birthday. In it, he reflected on the pressure many of us feel to present only one version of ourselves professionally, arguing that his creative and corporate lives were never really separate. As he puts it, they were 'not two jobs, but one obsession wearing two different lanyards.' That simple idea becomes the starting point for a much wider discussion about the stories we tell ourselves, and the stories organisations tell themselves.Along the way we explore:Why "stay in your lane" may say more about other people's expectations than your own potential.Why organisations often encourage people to bring their whole selves to work, while rewarding conformity.What interviews, dress codes and organisational culture reveal about human behaviour.Why stories often influence behaviour more effectively than rules, policies and frameworks.What films can teach us about operational resilience, cybersecurity and crisis management.Why the Titanic remains one of the most powerful lessons in organisational failure.How imagination is a strategic capability rather than a soft skill.Why thinking through "severe but plausible" scenarios requires organisations to become better storytellers.LinksMark's birthday article: "A Birthday Declaration from Someone Who Spent Over Twenty Years Pretending to Be Half of Himself" (LinkedIn)Mark's Behind The Spine podcastThe Writing SalonBehind The Spine podcastMark on LinkedInMark's previous appearances on the show talking about The Creative Industries under COVID, and Human Risk in the Creative IndustriesFilms, Stories & People MentionedDie Hard Apollo 13 The Martian The Odyssey (Christopher Nolan)Don't Look UpSnakes on a Plane Sharknado Noah's Ark RMS TitanicRachel Heyhoe Flint Jeremy King AI-Generated Timestamped Summary00:00 – Why do we hide parts of ourselves to be taken seriously?03:40 – Mark explains why he stopped separating his creative and corporate identities.08:00 – Which hobbies and outside interests are considered professionally acceptable—and why?10:30 – Job interviews, authenticity and bringing your whole self to work.16:00 – Jeremy King on why behaviour matters more than dress codes.19:00 – Rachel Heyhoe Flint, the MCC and what institutional rules reveal about culture.23:00 – Why stories influence behaviour more effectively than rules.24:00 – The Trojan Horse and using films to teach cybersecurity and resilience.29:00 – The Titanic as a lesson in organisational resilience rather than maritime history.32:00 – Conduct versus outcomes: why testing matters more than compliance.36:00 – Using stories and popular culture to make risk real.38:00 – Noah's Ark, history and the enduring power of storytelling.40:30 – CrowdStrike, PPE and why organisations keep repeating the same mistakes.46:00 – Stories aren't predictions—they're a way of exploring possibility.49:00 – A ransomware exercise and the danger of relying on fixed policies.52:00 – Returning to the Titanic: preparing for the inquiry before the crisis.55:00 – Thinking like an attacker and challenging assumptions about cyber risk.58:00 – Taylor Swift, insurance and why seemingly ordinary data can become highly sensitive.1:02:00 – The idea of "risk inflation" and why yesterday's rules aren't enough.1:10:00 – Why memorable stories change behaviour more effectively than realistic scenarios.1:15:00 – Reverse stress testing and imagining what could really break an organisation.1:20:00 – RAG ratings, reporting and the danger of looking resilient instead of being resilient.1:23:00 – Final reflections on creativity, identity and why being more than one thing is a strength.
01. David Guetta, Sia, Morten - Titanium (Record Mix) 02. Bob Sinclar, Kiesza - I Can't Wait (Record Mix) 03. Calvin Harris, Ellie Goulding - I Need Your Love (Record Mix) 04. Alok, Gryffin, Julia Church - Never Letting Go (Record Mix) 05. Ofenbach, Norma Jean Martine - Overdrive (Record Mix) 06. Kddk, Alex Alta - 1&2 (Record Mix) 07. Diplo, Maren Morris - 42 (Record Mix) 08. Don Diablo, R3hab, Neeka - Disco Marathon 09. Oneil, Kanvise, Ercodes - Smalltown Boy (Record Mix) 10. Anyma, Joji - Beautiful (Record Mix) 11. Zhu - In the Morning! (Record Mix) 12. Argy, Omnya - Aria (Record Mix) 13. Dr Kucho!, Gregor Salto, Oliver Heldens - Can't Stop Playing (Record Mix) 14. DJ Louis - Let Me Blow Ya Mind 15. Avicii - Levels (Record Mix) 16. ONE-T, Ywy, Nika - The Way To Love (Record Mix) 17. Robin Schulz, Ilsey - Headlights (Record Mix) 18. Zerb, Ty Dolla $ign, Wiz Khalifa - Location (Record Mix) 19. Sebastian Ingrosso, Tommy Trash, John Martin - Reload (Record Mix) 20. Pupa Nas T, James Hype, Denise Belfon - Work (Record Mix) 21. Tujamo, Azteck, Inna - Freak (Record Mix) 22. Sean Paul, Odd Mob - Get Busy 23. Fisher - Losing It (Record Mix) 24. Topcover - First Day (Record Mix) 25. Ben Delay - I Never Felt So Right (Record Mix) 26. Kygo, Ava Max, Tiesto - Whatever (Record Mix) 27. DJ Snake, Bipolar Sunshine - Paradise (Record Mix) 28. Junior Jack - Stupidisco (Record Mix) 29. Mind Electric - Things You Say (Record Mix) 30. Klaas - The Way (Record Mix) 31. Disclosure - She's Gone, Dance On 32. Jonas Blue, Jp Cooper - Perfect Strangers (Record Mix) 33. Fedde Le Grand - Got Your Money (Record Mix) 34. Swedish House Mafia, Pharell - One (Your Name) (Record Mix) 35. Hugel, Topic, Arash, Daecolm - I Adore You (Record Mix) 36. Maruv, Boosin - Drunk Groove (Record Mix) 37. Garas, Eugenio Fico - Perfect 38. Shane Codd - Get Out My Head (Record Mix) 39. Oceana, Bodybangers - Endless Summer (Record Mix) 40. The Chemical Brothers, De Soffer - Go (Record Mix) 41. Adam Lambert - Ghost Town (Record Mix) 42. Rue Jay - I Want Your Love 43. Lunax, Mia Amare - Sweet Harmony (Record Mix) 44. Bebe Rexha, David Guetta - Sad Girls (Record Mix) 45. Bausa - Magnetic (Record Mix) 46. Tony Igy, Vicetone - Astronomia (Record Mix) 47. Alle Farben, Rene Miller - Body Talk (Record Mix) 48. Avalan Rokston, Alex Caspian - Something to Believe In (Record Mix) 49. Dynoro, Gigi D'agostino - In My Mind... (Record Mix) 50. Lola Young, Ted Bear - Messy (Record Mix) 51. Faul, Wad, Pnau - Changes (Record Mix) 52. Bob Sinclar, Steve Edwards, Fisher - World, Hold On (Record Mix) 53. Shouse, Vintage Culture - take me (to the sunrise) (Record Mix) 54. Alok, Jess Glynne - Summer's Back (Record Mix) 55. Block & Crown, Daisy - Mr Vain (Record Mix) 56. Global Deejays, Jenia Smile, Ser Twister - The Sound Of San Francisco (Record Mix) 57. Calvin Harris, Benny Blanco - I Found You (Record Mix) 58. Don Diablo - The Way I Are (Record Mix) 59. Armin Van Buuren - Es Vedra (Record Mix) 60. Alesso, Sacha - Destiny (Record Mix) 61. Philip George - Wish You Were Mine (Record Mix) 62. Vize - Wait (Alibi Blue) (Record Mix) 63. Lady Gaga, DJ Dark - The Dead Dance (Record Mix) 64. Killteq, D.hash, Vallhee - I Like It (Record Mix) 65. Afrojack, Aloe Blacc - In My World 66. Avicii - Fade into Darkness (Record Mix) 67. Anyma, Ejae - Out Of My Body (Record Mix) 68. Oliver Heldens, Riton, Vula - Turn Me On (Record Mix) 69. Ava Max - Don't Click Play (Record Mix) 70. Imany, Ivan Spell, Daniel Magre - You Will Never Know (Record Mix) 71. Daft Punk - Around The World (Record Mix) 72. Meduza, Henry Camamile - Don't Wanna Go Home (Record Mix) 73. Zerb, The Chainsmokers, Ink - Addicted (Record Mix) 74. Duke Dumont - Won't Look Back (Record Mix) 75. Richard Grey, Kamafro - No Scrubs (Record Mix) 76. Lost Frequencies, Janieck Devy - Reality (Record Mix) 77. Kygo, Max Mcnown - Take Me Back (Record Mix) 78. James Hype, Kim Petras - Drums (Record Mix) 79. Baauer - Calling Out For U (Record Mix) 80. Faul & Wad, Nico & Vinz, Altego, Old Jim - How I Feel (Am I Wrong) (Record Mix) 81. Amor - Tell Me (Record Mix) 82. Leony, Calum Scott - Stay (Record Mix) 83. Hypaton, David Guetta, La Bouche - Be My Lover (Record Mix) 84. Bassjackers, KSHMR, Sirah - Memories (Record Mix) 85. Don Diablo - Momentum (Record Mix) 86. Shouse, Cub Sport - Only You (Record Mix) 87. Bebe Rexha, Faithless - New Religion (Record Mix) 88. Basto!, Yves V - Cloud Breaker (Record Mix) 89. Hugel, Alleh, Yorghaki - una noche con hugel (Record Mix) 90. Showtek, Smack, Sam Gray - Take My Heart Away (Record Mix) 91. Otnicka - Celebrate the Love (Record Mix) 92. Imanbek, Sofia Reyes, Luisa Sonza - NOT U (Record Mix) 93. Hurts, Purple Disco Machine - Wonderful Life '25 (Record Mix) 94. Lost Culture, Morfi, Carine - Lean On (Record Mix) 95. Doechii, DJ Dark - Anxiety (Record Mix) 96. Joezi, Lizwi - Amathole (Record Mix) 97. Argy, Omiki - WIND (Record Mix) 98. Relanium, Deen West - Leel Lost (Record Mix) 99. Adam Port, Stryv, Malachii, Switch Disco - Move (Record Mix) 100. Diplo, Miguel - Don't Forget My Love (Record Mix) 101. Aaron Smith, Luvli, Krono - Dancin' (Record Mix) 102. Goodboys, Nu Aspect, Avaion - Blindspot (Record Mix) 103. Gorgon City, Mk - There for You (Record Mix) 104. DJ Louis, Sweetpower - Billie Jean (Record Mix) 105. Calvin Harris, Rag'n'bone Man - Giant (Record Mix) 106. Sonny Fodera, D.O.D, Poppy Baskcomb - Think About Us (Record Mix) 107. Rain Radio, DJ Craig Gorman - Talk About (Record Mix)
These days, AI is everywhere, and it's increasingly hard to separate the gains from the slop. With that in mind, we're re-releasing my conversation with Stanford Law professor Daniel Ho on the future of AI and the law. When we look for applications where AI can deliver measurable benefit, the legal profession stands out, both for its potential gains in efficiency and equity, and for how much is at stake if we get it wrong. Dan's research — from using AI to identify racist property covenants buried in county deed records, to mapping obsolete regulations that waste thousands of hours of government time — shows what's possible when the technology is applied with rigor and purpose. If you're curious about how AI can serve both justice and good governance, this one is well worth another listen. Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu. Episode Reference Links: Stanford Profile: Dan Ho Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / Facebook Chapters: (00:00:00) Introduction Russ Altman introduces guest Dan Ho, a professor of law, political science, and computer science at Stanford University. (00:02:19) Path into Legal AI How Ho's background shaped his interest in law, and technology. (00:03:35) What Lawyers Do What makes law a complex domain for AI. (00:05:28) Legal Hallucinations When AI performs well and when it fails. (00:07:52) Searching Legal Records in California How AI can help identify outdated, harmful, or legally important material. (00:10:28) Scaling Redaction How a model accelerated a process that overwhelmed county recorder offices. (00:13:04) Legal Reform at Scale How AI has supported legal reform by scanning massive bodies of law. (00:15:02) STARA & The City of San Francisco How AI was used to go through San Francisco's code and clean up reporting. (00:20:53) Outdated Obligations How “regulatory sludge” takes the time & resources of the public service (00:25:02) Open vs. Closed AI The differences and associated risks of the different AI systems. (00:30:58) Legal Chatbots Why legal chatbots are promising but risky. (00:33:42) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
AI makes it easier than ever to find and act on information—especially now that teams can connect to and search across all the apps they use for work. So how do you ensure that only the right people and the right tools can access your team's most sensitive content? In this episode, we talk with Jess Jimenez, the head of security at Dropbox, about what security looks like in the age of AI at Dropbox-scale—from building AI products securely to building trust with the people who use them. Jess talks about the importance of access control lists, defending against the latest AI threats, and how Dropbox Protect helps teams securely share content with both humans and AI so they can collaborate more safely. ~ ~ ~ Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!
Scott Lechley started Lechley Associates with £10,000, a new baby at home, and six months of recruitment experience. Twenty four years later he is still the only person in the business, and he is on track for the best year he has ever had.Lechley Associates places the people who run the UK's biggest construction and infrastructure programmes. Framework directors, board level hires, the leaders behind HS2 scale rail and new hospital builds. Clients like Laing O'Rourke, Balfour Beatty and Hochtief. One retained search at a time.Six months into this year Scott had already cleared £300,000, with another £150,000 confirmed. He did it by doing something most recruiters never attempt: going fully retained, staying completely solo, and building an AI stack that means he now wakes up to a BD intelligence report, an automated outreach system, and a dashboard of ranked opportunities before most people have made their first coffee.He also did something almost no recruiter would admit to. This year he deliberately lost £40,000 in fees by talking a client out of a hire he did not believe in, and it does not cost him a minute of sleep.On this episode of The RAG Podcast, Scott breaks down exactly how the stack works, why 24 years of saying no to the wrong things is the real engine behind the numbers, and what a solo business actually makes possible when you stop trying to grow headcount.Scott is 54, having the best year of his career, and building a community for the next generation of construction professionals on the side. He is not slowing down.If you have ever wondered whether the pressure to build a team, hire more people and grow headcount is actually the only way, this episode is your answer.-------------------------------------------------------------------Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, a CRM that actually understands context.Atlas captures everything you say, hear, read and write. Every interview, every client call, every LinkedIn message, email and WhatsApp, automatically. Not because you typed it up, but because Atlas was listening. Then it goes one step further and tells you the next action to take.So when you need to fill a role, People Search ranks your best candidates and tells you why, no digging required. That same memory turns your BD into a shortlist of exactly who to chase and why, so you win more clients. And when you want to see your pipeline, you just speak to your dashboards and Atlas builds the view for you in real time, tracking only what you care about.Whether you place permanent or contract, Atlas covers both. Its Contract Suite means you never chase a timesheet again, with live margin visibility across every placement. And with its new MCP and API, Atlas plugs straight into your LLMs and the rest of your stack, so the low-value admin that keeps you from billing gets done for you.This is not theory. Atlas customers are seeing 50% higher candidate response rates, a 35% increase in new clients won, 15+ hours saved every week, and monthly billings jumping by 85%. Some agencies are hitting 130% of their annual revenue target after building their business around Atlas.So if you're thinking you need to bolt AI onto your CRM, don't bother. Take a look at Atlas instead.Head to https://recruitwithatlas.com/therag/ to find out more.-------------------------------------------------------------------Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn, but AI has turned templated posts and outreach into a commodity. When everyone sounds the same, the market stops listening. The recruiters winning now are the ones the market trusts.At Hoxo we help recruitment founders become the most influential name in their niche, using AI to multiply output while trust stays the product. Our clients turn their existing networks into £100K to £300K in new billings within months. Watch the free RAG listener training to see how: https://hubs.ly/Q03lBpYC0
In this episode of UC Today, host Kristian McCann is joined by Devashri Datta, a Senior Security Architect at NVIDIA, but appearing in a personal capacity as a researcher, to explore why organizations need to rethink how they govern AI-powered tools. Devashri explains why Software Bills of Materials (SBOMs) must evolve to account for AI models, training data, agent behavior, and new attack methods such as prompt injection and data poisoning. From Microsoft Copilot and Slack integrations to autonomous AI agents capable of accessing sensitive business systems, this conversation explores the hidden risks enterprises face as AI adoption accelerates. Watch to understand why AI governance needs to move at machine speed and why treating AI like “just another tool” could leave organizations exposed. Key topics discussed include:
In this talk, Paul Iusztin, Creator of Decoding AI and author of the LLM Engineer's Handbook, shares his deep expertise in personal automation from managing a digital life with lightweight data pipelines to architecting autonomous agents for deep research. We explore the mechanics of building personal AI assistants and the critical role of using a "second brain" as a context layer over heavy, over-engineered RAG infrastructure.You'll learn about:- Organizing your digital life using the PARA method and lightweight data pipelines.- Capturing and retrieving resources effortlessly with Obsidian, Readwise, and custom deep research algorithms.- Leveraging your "second brain" setup as the ultimate context layer for personal AI assistants.- Generating ad-hoc wikis from markdown brain dumps to streamline content creation and research.- Optimizing AI-generated content by deliberately lowering LLM reasoning capabilities for better styling.- Adapting multi-agent workflows and personal wikis to accelerate software engineering and coding tasks.TIMECODES:00:00 Digital life organization using the PARA method and lightweight data pipelines05:21 Seamless resource capture with Obsidian and Readwise09:26 Resource retrieval optimization using a deep research algorithm12:44 High-quality internet curation versus heavy RAG pipelines16:31 Second brain setup as a context layer for personal AI assistants21:40 AI workflow simplification with Anthropic APIs and CLI tools25:26 Ad-hoc wiki generation from markdown brain dumps for content creation29:18 Codebase ingestion and web scraping proxy tool workarounds34:43 Resource reranking and context window management for large texts39:06 Content styling optimization by lowering LLM reasoning capabilities46:18 Multi-agent workflows and personal wikis for software engineering tasks52:32 Personal wiki scaling for enterprise knowledge bases and book writingThis talk is perfect for individual developers, AI engineers, and knowledge workers looking to escape "PoC purgatory" and build practical, low-maintenance personal AI assistants. It offers highly actionable insights for anyone wanting to integrate agentic workflows into their daily productivity systems without over-engineering their tech stack.Connect with Paul- Linkedin - https://www.linkedin.com/in/pauliusztin/- Website - https://www.pauliusztin.ai/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/
Join us as Faye Ellis breaks down what responsible AI actually looks like in practice on Amazon Bedrock - live demos included, straight from her prep for the AWS Generative AI Developer Professional certification. Faye walks through the NIST AI risk framework's core characteristics of trustworthy systems, then demos two hands-on builds: a RAG pipeline using S3 Vectors as a low-cost knowledge base, and Bedrock Guardrails blocking financial advice, prompt injection attacks, and sensitive information in real time. You'll learn the difference between prompt engineering and guardrails, how contextual grounding checks catch hallucinations before they reach a user, why data cleaning and deduplication matter as much for cost and sustainability as for bias, and what Faye wishes she'd known going into one of AWS's hardest professional-level exams. Timestamps 0:00 Welcome & Introduction 9:28 What Makes an AI System Trustworthy - The NIST Framework 15:19 Famous AI Failures - From ChatGPT Code Leaks to Biased Systems 22:56 Building RAG with Bedrock Knowledge Bases and S3 Vectors 26:29 Live Demo - Setting Up RAG with S3 Vectors 31:19 Prompt Engineering and Bedrock Prompt Management 34:46 What Are Bedrock Guardrails and How They Work 41:22 Live Demo - Blocking Financial Advice, Jailbreaks, and PII 53:00 Preparing for the AWS Generative AI Developer Professional Exam 59:04 Resources and Wrapping Up How to find Faye: https://www.linkedin.com/in/fayeellis/ https://app.pluralsight.com/profile/author/faye-ellis Links from the show: https://aws.amazon.com/bedrock/ https://skillbuilder.aws/ https://aws.amazon.com/certification/
Louise Archer spent more than twenty years as a contingent recruiter. She believed retained was probably smoke and mirrors, something dressed up to justify a bigger fee, and definitely not a pool she was ever going to swim in.Then her employer handed her a project called Most Money Soonest, with a brief to make the permanent division's revenue predictable enough to survive a major acquisition. She and one colleague started visiting clients, asking better questions, and converting them to retained one conversation at a time.The division went from five million pounds in annual revenue to twelve million, all of it retained, from a standing start of zero retained revenue. Then Louise walked away and set out to teach the rest of the industry how to do the same.Since founding Retrained Search in 2018, she has trained more than fifteen hundred recruiters across thirty-one countries. In December 2024 she completed a management buyout with her three directors, and the target now is three point four million pounds in revenue by the close of 2027.On this episode of The RAG Podcast, Louise breaks down how the retained conversation actually works, why exclusivity is the worst model of all, and why the industry is now splitting in two.Louise Archer did not just theorise about retained search. She built the proof of concept inside someone else's business, walked away, and has spent the last eight years showing thousands of recruiters around the world how to do the same.The numbers do not lie. The contingent model is under pressure, the industry is splitting into trusted advisors and commodity suppliers, and the window to move is still open.If you have ever looked at your fill rate and thought something feels wrong, this episode has the blueprint.-----------------------------------------------------------Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, a CRM that actually understands context.Atlas captures everything you say, hear, read and write. Every interview, every client call, every LinkedIn message, email and WhatsApp, automatically. Not because you typed it up, but because Atlas was listening. Then it goes one step further and tells you the next action to take.So when you need to fill a role, People Search ranks your best candidates and tells you why, no digging required. That same memory turns your BD into a shortlist of exactly who to chase and why, so you win more clients. And when you want to see your pipeline, you just speak to your dashboards and Atlas builds the view for you in real time, tracking only what you care about.Whether you place permanent or contract, Atlas covers both. Its Contract Suite means you never chase a timesheet again, with live margin visibility across every placement. And with its new MCP and API, Atlas plugs straight into your LLMs and the rest of your stack, so the low-value admin that keeps you from billing gets done for you.This is not theory. Atlas customers are seeing 50% higher candidate response rates, a 35% increase in new clients won, 15+ hours saved every week, and monthly billings jumping by 85%. Some agencies are hitting 130% of their annual revenue target after building their business around Atlas.So if you're thinking you need to bolt AI onto your CRM, don't bother. Take a look at Atlas instead.Head to https://recruitwithatlas.com/therag/ to find out more.-----------------------------------------------------------Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn, but AI has turned templated posts and outreach into a commodity. When everyone sounds the same, the market stops listening. The recruiters winning now are the ones the market trusts.At Hoxo we help recruitment founders become the most influential name in their niche, using AI to multiply output while trust stays the product. Our clients turn their existing networks into £100K to £300K in new billings within months. Watch the free RAG listener training to see how: https://hubs.ly/Q03lBpYC0
In this episode, hosts Candace Gillhoolley and Frank La Vigne are joined by Neil Katz, Chief Product Officer at Valantor AI—a four-time Emmy winner whose unconventional journey spans from technology startups to award-winning journalism, and now to the forefront of enterprise AI innovation.Neil shares his unique perspective on the evolution of AI, from the early days of digital design and machine learning, to building large-scale AI and document intelligence platforms for major organizations. The conversation explores the critical challenges of knowledge extraction, document comprehension, and securing sensitive data in today's era of sovereign AI. Together, they uncover the hidden complexities behind Retrieval-Augmented Generation (RAG), discuss the importance of hybrid search strategies, and reflect on where the field is heading as enterprise needs push the boundaries of what AI can do.Whether you're a data professional, an AI enthusiast, or just curious about how language models are transforming how we understand information, you won't want to miss this candid and thought-provoking deep dive into the future of AI and data integrity.LinksNeil on LinkedIn -https://www.linkedin.com/in/neilkatz/Watch on YouTube -https://www.youtube.com/watch?v=qf8qifz_RL8Time Stamps00:00 Early career in tech and journalism04:01 Early consumer AI experiences06:49 Early AI and machine learning developments11:43 Anthropic's new findings on AI models16:15 Data sovereignty in AI systems19:27 Implementing open source AI models22:49 Breaking down documents for models25:45 Understanding the RAG system process28:47 Challenges in AI data processing31:22 Challenges in RAG with Insurance Data36:35 Understanding and managing data security39:35 Early days with OpenAI GPT40:48 Explaining vector and similarity search46:57 The evolution of computing models47:29 Computing evolution to cloud and edge
Want to actually build agents and RAG systems like the ones I mention in this episode? That's exactly what we do inside Parsity's AI engineering program: https://parsity.io/ai-devI've been coding for nearly 12 years, I own and operate a coding bootcamp, and I've done over 1,000 free phone calls with people trying to break into tech. So this is the harsh advice I'd give you if you were my own kid. The stuff I can't really say on LinkedIn without getting flamed by people who've never worked a day in tech.The market for juniors is rough right now. That part is true. But most people trying to break in are doing the exact same thing as everyone else: building the same to-do app, obsessing over green dots on their GitHub, slapping "passionate junior developer" on their resume, and smashing LinkedIn easy-apply 1,000 times. That's your competition. And it's beatable.In this episode:Why "look junior, act passionate, wait for someone to take a chance on you" is a losing strategyHow to build real, verifiable experience when you have none (start an LLC, get actual users, stop building toy apps)The one skill that actually matters now, and why "I use Claude" is table stakes, not a differentiatorWhy agents and RAG are still wide open. Even senior and staff engineers mostly aren't doing this yetWhere the jobs actually are (small businesses and startups are hiring, big tech is slashing) and how to find them off LinkedInThe LinkedIn search-ranking trick most people ignoreWhy your timeline might take 2, 3, even 4 years, and why the ROI math still makes it worth itStop outsourcing your brain to ChatGPT before you've even built the skillTake it all with a grain of salt. It's one opinion. But I'll never tell you to do something I haven't done myself or seen work firsthand.Free resources I mention:Parsity AI Engineering Program: https://parsity.io/ai-devFree 5-Day AI Advisory Board course (build agents + RAG hands-on): https://www.parsity.io/5-day-ai-advisory-boardFree RAG project (better than most paid ones): https://www.parsity.io/ai-with-ragThe agent project I mention: https://www.parsity.io/ai-agentGusto Small Business Jobs Report (hundreds of thousands of net new small-business jobs this year): https://gusto.com/resources/gusto-insights/smb-jobs-report-june-2026My video on the entry-level hiring collapse, "Entry-level jobs didn't disappear. They moved. Got a question or something you want me to cover? Drop it in the comments. I get tons on YouTube but almost none on Spotify, and this is where the hardcore Develop Yourself crew lives. Comment away, it genuinely helps the show get found.
Flight Instructor Suicide: A flight instructor jumps from a plane to leave his student to fend for herself. Could this be the greatest teacher we've ever seen?AI Robot Fails: As they keep trying to get us to work with robots, one of our favorite things is robot fails. Speaking of robot fails, here are a couple of new robot butlers on the horizon.Diarrhea Epidemic: Cyclosporiasis is spreading the country meaning that it's a diarrhea summer.FUCK YOU WATCH THIS!, THE BEAR!, TIP YOUR BARTENDER!, GLASSJAW!, DARYL!, NEW SPECIAL!, SHELL TV!, QR CODE!, SUPERTIPS!, PLATITUDES!, ZEN FELDMAN!, BOOPAC!, TIM TAMS!, FLIGHT INSTRUCTOR!, SUICIDE!, STUDENT PILOT!, NEWS!, MISHAP!, JUMPS FROM PLANE!, TALLER!, BIG!, YOU KNOW WHAT TO DO!, LET'S ROLL!, SIMPSONS!, GAG!, SUICIDE HERO!, KRISPY KREME!, PUT IT IN DRIVE!, BOYZ N DA HOOD!, RICKY!, PHONE THAT TELLS THE FUTURE!, DRIVE!, OLD LADY NEWS!, DISGUISE!, FREAK OUT!, GEEKING!, FALL!, KUNG FU!, DANCING!, BALLET!, GET UP!, GRABBED!, BRUCE LEE!, ROBOT FIGHTS!, AMERICA'S FUNNIEST HOME VIDEOS!, BABIES PUKING!, WALKING THROUGH GLASS!, WEAVE!, SEGWAY!, ISAAC!, STARTUP!, NORI!, REMOTE TASK ROBOTS!, MOP!, RAG!, ROBOT CAMERA!, SKATEBOARDING!, KICKSTARTER!, HORROR UNLEASHED!, DIARRHEA!, INFECTION!, PARASITE!, VEGETABLES!, IMMIGRANTS SHITTING ON LETTUCE!, ICE!, AUSTRALIAN!, GOLDEN CORRAL!, FOREIGNERS!, WORLD CUP!, TOURISTS!, CUT DICK OFF!, SET FIRE!, MUTILATING!, BOOKIE!, PEDEN!, LOAN SHARK!You can find the videos from this episode at our Discord RIGHT HERE!
Michael interviews new exhibitor Dr. Jeffrey M. Kelly, a full-time biblical counselor and former church planter, and David Driskill, a veteran software developer and Care Assist Pro's CTO, about their platform (careassist-pro.com). They explain that Care Assist Pro was built to address the shortage of soul care in local churches by reducing counseling roadblocks and increasing counselor confidence through secure, HIPAA-compliant tools such as note organization, encrypted communication, built-in video conferencing with transcripts, summaries, and AI-driven feedback on counseling skills over time. They emphasize AI is never the counselor but a tool with biblical guardrails, using a curated RAG knowledge base of about 800 documents (e.g., ACBC, CCF, ABC, Counseling Coalition) and features like notebooks, multilingual outputs, and training “personas” for seminary practicums and skill development.00:00 Conference Introduction01:02 Meet the Guests01:16 Dr Kelly Background01:48 David Driskill Tech Story03:09 How Care Assist Began05:49 Redemptive Use of AI08:31 AI Training Practicum11:19 Notebooks Language Features15:30 Guardrails Not Replacement19:58 Counselor Growth Analytics23:57 Who Its For Pricing26:50 Final Encouragement WrapEpisode MentionsCheck out Care Assist Pro
Thariq Shihipar, a member of Anthropic's Claude Code team (and SPC alum), joins South Park Commons Partner Evan Tana to discuss what it takes to build at the frontier of AI, where the models, tools, and best practices are constantly evolving.Thariq traces his journey from a gaming startup to Anthropic after a chance text about Claude Code, shares why his team stopped using Plan Mode, explains concepts like capability overhang, harness engineering, and the underrated art of writing evals, and discusses why RAG is becoming an anti-pattern. He also breaks down how founders should think about building when the capabilities of AI systems are changing faster than anyone can predict.Thariq Shihipar: https://www.linkedin.com/in/thariqshihipar/ Evan Tana: https://www.linkedin.com/in/evantana/ South Park Commons: https://www.linkedin.com/company/southparkcommons/Apply to SPC: https://www.southparkcommons.com/applyChapters:(00:00:00) - From Startup Founder to Anthropic (00:03:33) - Building Better AI With Claude Code (00:07:21) - The Capability Overhang (00:12:17) - How Anthropic Builds AI Products(00:17:51) - Prompting Claude More Effectively (00:30:58) - How AI Is Changing Product Teams (00:41:11) - Advice for AI Founders
The beauty of maths is that it's completely objective. It's science. It's truth. It's the foundational cornerstone of accumulated knowledge and humanity's long, noble journey towards enlightenment.And so, Ragnar's Maths continues its relentless pursuit of truth by predicting—nay, mathematically proving—what will happen this month:We won't lose.But… ahhh, bugger.This weekend we play a team sitting on the bottom of the ladder. We generally play poorly in situations like this. Anything could happen, and humanity's journey towards enlightenment may yet perform a spectacular U-turn.Ragnar, Sparrow and Orca are here to dive in and reassure the Orange Army.For now, we'll rejoice in the magnificent victory against a side that—for most of the game—was probably the better team.Unfortunately for them, when Clarry's magnificent shoulder arrives at full force, accompanied by a commitment to the football only an overexcited kelpie could rival, chances are you're about to lose.Where have we heard that before?That's right: Rag's Bet.Currently in administration. Possibly insolvent. Almost certainly irresponsible. RIP.However, should you wish to support the cause—and Ragnar's deeply unhealthy relationship with speculative wagering—please visit the Buy Me a Coffee link below.Just kidding. All proceeds will go towards flights to the Grand Final.BECAUSE MARK OUR WORDS: THAT'S A MATHEMATICAL CERTAINTY.We'll see.But until then, we'll Never Surrender.----To get in contact, drop us an email, comment on Spotify or message us on X.We love reviews or ratings.Email: thesquinterspodcast@gmail.comSupport: buymeacoffee.com/thesquintersYouTube: NeverSurrenderByTheSquintersX: TheSquintersInstagram: gws_squintersFB: thesquintersTikTok: the.squinters
Not all work happens in writing. Teams that work with photos, videos, and audio need AI that works for them too. This is why, with Dropbox, you can search within multimedia content for key moments and important information—not just text. In this episode, we talk with Appu Shaji and Hicham Badri, two Dropbox machine learning engineers who are part of the team that makes all of this possible. They explain how multimodal search works—from understanding the context of the initial query, to identifying objects and actions in complex scenes—and how they ensure those models work fast, even at Dropbox-scale. ~ ~ ~ Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!
In 2022, EVONA had eighty staff, a Manchester office, a six-hundred-thousand-pound monthly cost base, and had just spent three hundred thousand pounds flying the whole company to Monaco. Tom Kelly calls it the moment four first-time founders lost perspective.What followed was one of the more honest rebuilds you will hear in recruitment. Contract team gone. Marketing team gone. Management team restructured. Tom moved to the US, took the wheel as sole decision-maker, and rebuilt around two metrics: twenty-five interviews per person per rolling four weeks, and a thirty-day close on every job.Three years on, EVONA is projecting ten million pounds net fee income this year. Three and a half million EBITDA. Thirty-five people. Two inbound client enquiries arrive every single day.Tom Kelly has been in the space sector since 2018. He has never taken outside investment. And last month was the largest in the company's history.On this episode of The RAG Podcast, Tom breaks down exactly how they got there.EVONA is now the dominant name in space sector recruitment. Ninety-five percent US clients. No cold outreach. No single client above nine percent of revenue. A thirty-two day average time to fill on roles that take competitors sixty.Tom Kelly is thirty-nine. He does not have a rigid three-year exit plan, but he does think there is a short window, and he does believe AGI changes the calculus for anyone thinking about an acquisition in this space. What he is building now is the version of the business that is worth something, the lean, high-output, brand-trusted version that took cutting fifty people to find.If you have ever wondered what it actually looks like to rebuild a recruitment business properly after it nearly breaks, this episode has the blueprint.Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, the AI-first recruitment platform built for modern agencies.It doesn't only track CVs and calls. It remembers everything. Every email, every interview, every conversation. Instantly searchable, always available. And now, it's entering a whole new era.With Atlas 2.0, you can ask anything and it delivers. With Magic Search, you speak and it listens. It finds the right candidates using real conversations, not simply look for keywords.Atlas 2.0 also makes business development easier than ever. With Opportunities, you can track, manage and grow client relationships, powered by generative AI and built right into your workflow.Need insights? Custom dashboards give you total visibility over your pipeline. And that's not theory. Atlas customers have reported up to 41% EBITDA growth and an 85% increase in monthly billings after adopting the platform.No admin. No silos. No lost info. Nothing but faster shortlists, better hires and more time to focus on what actually drives revenue.Atlas is your personal AI partner for modern recruiting.Don't miss the future of recruitment. Get started with Atlas today and unlock your exclusive RAG listener offer at https://recruitwithatlas.com/therag/Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn, but AI has turned templated posts and outreach into a commodity. When everyone sounds the same, the market stops listening. The recruiters winning now are the ones the market trusts.At Hoxo we help recruitment founders become the most influential name in their niche, using AI to multiply output while trust stays the product. Our clients turn their existing networks into £100K to £300K in new billings within months. Watch the free RAG listener training to see how: https://hubs.ly/Q03lBpYC0
01. Hugel, French Montana, David Guetta, Aidan Martin - Shine (Record Mix) 02. Shouse, Vintage Culture - take me (to the sunrise) (Record Mix) 03. Alok, Innerverse, Frey - Allein Allein (Record Mix) 04. Bob Sinclar, Kiesza - I Can't Wait (Record Mix) 05. Thomas Gold - Pump Up The Jam (Record Mix) 06. Don Diablo, R3hab, Neeka - Disco Marathon 07. Oliver Heldens, Djs From Mars, Jd Davis - Blue Monday (Record Mix) 08. DJ Snake, Bipolar Sunshine - Paradise (Record Mix) 09. Oneil, Kanvise, Ercodes - Smalltown Boy (Record Mix) 10. Avalan Rokston, Alex Caspian - Something to Believe In (Record Mix) 11. Zhu - In the Morning! (Record Mix) 12. Gotlucky, Mysterie, Afro Queen - La La La (Record Mix) 13. Faul, Wad, Pnau - Changes (Record Mix) 14. Rue Jay - I Want Your Love 15. Adam Lambert - Ghost Town (Record Mix) 16. Fedde Le Grand - Got Your Money (Record Mix) 17. Kygo, Ava Max, Tiesto - Whatever (Record Mix) 18. Tujamo, Azteck, Inna - Freak (Record Mix) 19. Sean Paul, Odd Mob - Get Busy 20. Calvin Harris, Benny Blanco - I Found You (Record Mix) 21. DJ Louis - Let Me Blow Ya Mind 22. Topic, A7s - Breaking Me (Record Mix) 23. ONE-T, Ywy, Nika - The Way To Love (Record Mix) 24. New World Sound, J2, Sara Phillips - Outta My Head (Record Mix) 25. Philip George - Wish You Were Mine (Record Mix) 26. Avicii, Dan Tyminski - Hey Brother (Record Mix) 27. Topcover - First Day (Record Mix) 28. Tony Igy, Vicetone - Astronomia (Record Mix) 29. The Chemical Brothers, De Soffer - Go (Record Mix) 30. Lykke Li, The Magician - I Follow Rivers (Record Mix) 31. Garas, Eugenio Fico - Perfect 32. Bebe Rexha, Faithless - New Religion (Record Mix) 33. Disclosure - She's Gone, Dance On 34. DJ Feel, Desmind, Natalie Rise - Stereo Love (Record Mix) 35. Lost Frequencies, Janieck Devy - Reality (Record Mix) 36. Imanbek, Sofia Reyes, Luisa Sonza - NOT U (Record Mix) 37. Sonny Fodera, D.O.D, Poppy Baskcomb - Think About Us (Record Mix) 38. Richard Grey, Kamafro - No Scrubs (Record Mix) 39. Alle Farben - Bad Ideas (Record Mix) 40. Fisher, Flowdan - Boost Up (Record Mix) 41. Gamuel Sori, Lovespeake, Amice - Us (Record Mix) 42. Shane Codd - Get Out My Head (Record Mix) 43. Regard, Years & Years - Hallucination (Record Mix) 44. Global Deejays, Jenia Smile, Ser Twister - The Sound Of San Francisco (Record Mix) 45. Robin Schulz, David Guetta - On Repeat (Record Mix) 46. Alesso, Sacha - Destiny (Record Mix) 47. Don Diablo - The Way I Are (Record Mix) 48. Gorgon City, Mk - There for You (Record Mix) 49. Killteq, D.hash, Vallhee - I Like It (Record Mix) 50. Arc North, Cour, New Beat Order, Lunis - Faded (Record Mix) 51. Anyma, Ejae - Out Of My Body (Record Mix) 52. Ofenbach, Norma Jean Martine - Overdrive (Record Mix) 53. Afrojack, Aloe Blacc - In My World 54. C-BOOL, Giang Pham - DJ Is Your Second Name (Record Mix) 55. Oneil, Kanvise, Ercodes - Every Single Day (Record Mix) 56. David Zowie - House Every Weekend (Record Mix) 57. Skytech - The Rhythm (Record Mix) 58. Twocolors, Roe Byrne, Amice - Stereo (Record Mix) 59. Crazibiza - Fresh (Record Mix) 60. Relanium, Deen West - Leel Lost (Record Mix) 61. Moby, Blond Ish, Kiko Franco - Natural Blues (Record Mix) 62. Lucas & Steve, Laura White - Are You Ready 63. Aria, NA-NO - Bleu Chanel (Record Mix) 64. Martin Jensen, Fastboy - One Day (Record Mix) 65. Calvin Harris, Rag'n'bone Man - Giant (Record Mix) 66. Vize - Wait (Alibi Blue) (Record Mix) 67. Armin Van Buuren - Es Vedra (Record Mix) 68. Vintage Culture, Gabss - Lost (Record Mix) 69. Bassjackers, KSHMR, Sirah - Memories (Record Mix) 70. Akcent, Sera, Misha Miller - Don't Leave (Kylie) (Record Mix) 71. Junior Jack - Stupidisco (Record Mix) 72. Alok, Ella Eyre, Kenny Dope, Never Dull - Deep Down (Record Mix) 73. Joel Corry, Jennifer Lopez - Get Right 74. Jonas Blue, Jp Cooper - Perfect Strangers (Record Mix) 75. Zerb, Sofiya Nzau, Izzy Bizu - Kumbaya (Record Mix) 76. Sebastian Ingrosso, Tommy Trash, John Martin - Reload (Record Mix) 77. All Things Break - Gravity (Record Mix) 78. Jax Jones, Martin Solveig - All Day & Night (Record Mix) 79. Cassian, Yotto, Da Hool - Love Parade (Record Mix) 80. Daft Punk - Around The World (Record Mix) 81. Bob Sinclar - Cruel Summer (Record Mix) 82. Global Deejays - Sex on the Streets (Record Mix) 83. Clean Bandit, ANNE-MARIE, David Guetta - Cry Baby (Record Mix) 84. Tiesto, Ava Max - The Motto (Record Mix) 85. Bolier, Joe Stone, Voost - Keep This Fire Burning (Record Mix) 86. Basto!, Yves V - Cloud Breaker (Record Mix) 87. Goodboys, Nu Aspect, Avaion - Blindspot (Record Mix) 88. Prospa, Josh Baker, Rahh - You Don't Own Me 89. Oceana, Bodybangers - Endless Summer (Record Mix) 90. Joezi, Lizwi - Amathole (Record Mix) 91. Meduza, James Carter, Elley Duhe, Fast Boy - Bad Memories (Record Mix) 92. Adam Port, Stryv, Malachii, Switch Disco - Move (Record Mix) 93. Gorgon City, Romans - Saving My Life (Record Mix) 94. Eastblock Bitches, Ostblockschlampen - Sunglasses at Night (Record Mix) 95. Felix Jaehn, Shouse - Walk With Me (Record Mix) 96. Sean Finn - Give It to Me (Record Mix) 97. Avicii - Fade into Darkness (Record Mix) 98. Teriyaki Boyz, Hayat - Tokyo Drift (Record Mix) 99. Twocolors - Heavy Metal Love (Record Mix) 100. Lady Gaga, DJ Dark - The Dead Dance (Record Mix) 101. Block & Crown, Lissat - Ocean Cake (Record Mix) 102. Hurts, Purple Disco Machine - Wonderful Life '25 (Record Mix) 103. Robin Schulz, James Blunt - OK (Record Mix) 104. Steve Angello - Me 105. Titov - Philosophy (Record Mix) 106. DJ Louis, Sweetpower - Billie Jean (Record Mix) 107. Pawsa - Too Cool To Be Careless (Record Mix)
Law professor Julian Nyarko has drawn attention for his studies using large language models to investigate and improve legal education and explore AI's biases. He hopes AI can become a reliable, always-on legal learning and assistance tool to lower costs and expand access to legal services. In one recent study, he asked a group of law professors to evaluate written answers to student questions. Three-quarters of the time, the professors preferred AI-generated answers to those of their human colleagues. “AI is good at law,” Nyarko says, the challenge now is to use it most effectively, he tells host Russ Altman in this episode of Stanford Engineering's The Future of Everything podcast. Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu. Episode Reference Links: Stanford Profile:Julian Nyarko Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / Facebook Chapters: (00:00:00) Introduction Russ Altman introduces guest Julian Nyarko, a professor of law at Stanford University. (00:02:31) Path into AI and Law How Nyarko's early work led him to legal AI. (00:05:03) Law, Economics, and Computation How Nyarko's training, methods, and self-taught coding shaped his research. (00:07:23) Building the LIFT Lab Why a law professor started a lab. (00:09:06) Evaluating Legal AI How AI raises fundamental questions about what counts as good lawyering. (00:10:22) Improving Legal Services Using AI to work faster, reduce errors, and make informed decisions. (00:10:57) Rethinking Legal Education How AI may change the way future lawyers learn (00:11:51) AI in Office Hours How AI answers law students' questions compared with human professors. (00:15:18) Surprising Results Why AI answers were often preferred (00:16:16) What the Study Shows The findings support AI tutoring, but don't prove AI improves learning. (00:18:48) Limits of One-Shot Answers Why real teaching often depends on dialogue, clarification, and productive struggle. (00:20:59) AI for Social Science How AI can become both an object of study and a tool. (00:22:43) Research Agents Using AI to test claims and make previously impossible research scalable. (00:24:51) Agentic AI in the Lab How Socratic dialogue with AI can sharpen research ideas. (00:26:07) Fairness and Bias How computational tools can be audited for bias and used to audit decision-making. (00:27:29) Discrimination in Models Exploring bias and how it can be reduced. (00:30:16) Disparate Impact How policies and systems disadvantage groups even without explicit intent. (00:32:53) From Evidence to Policy How Nyarko's lab works with stakeholders to surface disparities. (00:34:49) Future In a Minute Rapid-fire Q&A: justice, talent, and the future of legal AI. (00:36:57) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
In this talk, Gustaf Gyllensporre, Senior AI Engineer and PropTech Founder, shares his unconventional career journey from selling Miami real estate to shipping production AI systems. We explore the tactical steps for breaking into the tech space as a self taught developer and how to successfully bypass traditional industry gatekeepers.Links:- @PropTechFounder - https://youtu.be/leXRiJ5TuQo?si=ymK03qKVEC7hAt9N- https://x.com/gostak_ddYou will learn about:- The strategic approach to crafting an AI engineering resume that actually gets noticed by hiring managers.- Why building another generic RAG chatbot might be hurting your portfolio and the specific high impact projects you should build instead.- The massive difference between interviewing for AI roles at dynamic startups versus traditional big tech companies.- How to leverage open source contributions to prove your technical mastery without a computer science degree.- The surprisingly simple networking tactics and developer ambassador programs that can unlock exclusive job opportunities.- Actionable ways to improve the critical social and communication skills that most developers completely ignore.TIMECODES:00:00 AI Engineering Field Guide05:01 Self Taught AI Engineer Pivot09:39 CPython Open Source Contributions13:49 Tech YouTube Channel Growth18:26 AI Engineer Resume Optimization22:44 AI Engineering Portfolio Projects29:23 Startup vs Big Tech Interviews33:47 Open Source AI Project Ideas38:55 Building Deep Research AI Agents42:52 Landing Your First AI Job46:48 Tech Networking Strategies51:16 Technical Project Demo Videos54:53 Self Taught Developer Mistakes58:53 Soft Skills for Software EngineersConnect with Gustaf- Linkedin - https://www.linkedin.com/in/gustaf-g/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/
SUMMARY: While we spend a lot of time discussing AI models, we don't always spend enough time on the challenges of managing the unstructured data used to train, tune, and enable those models. SHOW: 1043SHOW TRANSCRIPT: The Enterprise AI Show #1043 TranscriptSHOW VIDEO: https://youtu.be/OAqnuhorMJ4SHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Topic 1 - Welcome to the show. Tell us a bit about your background and where you focus today at NasuniTopic 2 - We've spent two years talking about models. Are we finally entering the era where the biggest differentiator is data quality rather than model quality?Topic 3 - When customers inventory their AI-ready data, what surprises them most?Topic 4 - Where is the intersection of file data, metadata, and RAG systems that augment a company's AI experience with their own data?Topic 5 - People talk about AI governance, but isn't most AI governance actually data governance?Topic 6 - Are today's enterprise file systems designed for machine consumers (AI Agents) instead of human consumers?Topic 7 - What are the economics of data, in your world, as it relates to AI?Topic 8 - What's next for enterprise file platforms?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow
In this episode, Ray Cochrane digs into “algorithmic outing,” new research showing that social feeds can infer your sexual orientation before you have consciously come out. He also covers Meta’s privacy-aware AI infrastructure, Alberta’s 466-million-line code scan with Claude, NVIDIA on reinforcement learning, and the many journeys of learning Rust. Along the way, he hits Google DeepMind’s A24 deal, WhatsApp usernames, and scuba-diving cyborg cockroaches. Finally, he looks up with Webb’s puzzling early universe, NASA’s emergency telescope rescue, and a gorgeous aurora from orbit. – Want to start a podcast? Its easy to get started! Sign-up at Blubrry – Thinking of buying a Starlink? Use my link to support the show. Subscribe to the Newsletter. Email Ray if you want to get in touch! Like and Follow Geek News Central’s Facebook Page. Support my Show Sponsor: Best Godaddy Promo Codes Get 1Password Full Summary Cochrane opens with a quick personal update. He hopes listeners had a good holiday weekend, and he shares that he spent his time working his other job at Oregon’s Finest, chatting with people around Portland. Because his Blurbry workweek tends to be solitary, he refills his social meter on the weekends. He then recalls a Saturday night out with coworkers at the Hungry Tiger before turning to the lead story. Algorithmic Outing: When Your Feed Knows Before You Do Cochrane leads with new research from Australia that identifies a phenomenon called “algorithmic outing.” In short, the recommendation systems behind your social feeds can infer your sexual orientation or gender identity and start serving related content before you have worked it out yourself. Importantly, the study is small and qualitative, built on in-depth interviews with twenty LGBTQ+ adults in the Hunter region of New South Wales and published in the journal Gender, Place and Culture. The mechanism is engagement signals: what you like, who you follow, and how long you linger on a post, a metric the industry calls dwell time. Lead researcher Dr. Justin Ellis of the University of Newcastle notes that several participants said the algorithm “knew” they were queer before they did, an experience that felt validating for some but frightening for others in public settings. For Cochrane, the deeper worry is what else that hidden pattern encodes, from upbringing to mental health, and where that data ultimately gets sold. Sponsor: GoDaddy Economy hosting $6.99/month, WordPress hosting $12.99/month, domains $11.99. Website builder trial available. Use codes at geeknewscentral.com/godaddy to support the show. Meta’s Blueprint for Privacy-Aware AI Infrastructure Next, Cochrane turns to a sharp engineering piece from Meta on privacy-aware infrastructure. The core challenge is that a system must understand what a piece of data actually is before any privacy rule can protect it. A field named “age,” for example, might describe a person in one place and a cache setting in another. Meta’s answer deploys a large language model only on the genuinely ambiguous cases, then distills what it learns into fixed, human-reviewed rules. The payoff is concrete. According to Meta, those deterministic rules already handle about 85 percent of the traffic, and only the last 15 percent falls back to the model, which costs roughly 400 times more compute. Cochrane loves this edge-case approach. However, he contrasts it sharply with the AI-everywhere software he wrestles with at his weekend job, which he says the heavy AI reliance genuinely makes worse and harder to audit. Alberta Scans 466 Million Lines of Code With Claude This one comes from Anthropic, and it ties directly to Meta’s theme. A team inside Alberta’s Ministry of Technology and Innovation used Claude to scan 466 million lines of code in about twenty hours, a review Anthropic estimates would have taken humans roughly six and a half years. Notably, they ran around fifty AI agents in parallel, essentially an automated red team and blue team probing the systems at once. For Cochrane, this is the good version of AI in production: cleaning up and locking down real systems rather than running the show unsupervised. NVIDIA on Reinforcement Learning for AI Agents On the AI-building side, Cochrane walks through an NVIDIA developer piece on reinforcement learning for agents. Reinforcement learning rewards a model for good behavior rather than showing it the right answer, much like training a dog with treats. Additionally, he clears up a common mix-up. NVIDIA treats RAG, retrieval-augmented generation, as a separate tool: reinforcement learning changes how a model behaves, while RAG changes what facts it can reach. GitHub Retires Two Gemini Models Meanwhile, GitHub is retiring Gemini 2.5 Pro and Gemini 3 Flash across all of Copilot on July 31. The migration paths are Gemini 3.1 Pro and Gemini 3.5 Flash. Cochrane flags it as a sign of the times, since tools that felt brand new a couple of years ago are already getting sunset. He also wonders how quickly today’s “AI-optimized” chips will turn over as the models keep changing. The Many Journeys of Learning Rust One for the programmers, and Cochrane makes no secret of loving Rust. The Rust blog’s Vision Doc series explores how people actually learn the language, which is built around memory safety and its strict borrow checker. Honest themes surface throughout, including “clone guilt,” where beginners refuse to copy anything, and “silent attrition,” the learners who quietly bounce off. His take stands: getting your brain onto a memory-safe language rewires how you approach a problem. Google DeepMind Partners With A24 In an interesting collision of worlds, Google DeepMind is teaming up with A24, the studio behind Hereditary and Everything Everywhere All at Once. The two call it a first-of-its-kind research partnership, with DeepMind researchers and A24 building creative tools shaped by the artists who use them. Cochrane adds a detail worth noting: Google also invested in A24, so this is money on the table, not just a research handshake. For now, though, the announcement stays deliberately vague, with no named films or products. Google’s $1 Million Africa Indie Game Fund Another one from Google, and it is good news for developers. Google is launching an indie games fund for sub-Saharan Africa, a region whose gaming scene is growing about as fast as anywhere. The fund puts up $1 million across ten local studios, each receiving between $50,000 and $200,000 plus mentorship and hands-on support. Applications close at noon UTC on July 31. WhatsApp Usernames Are Here to Reserve WhatsApp is finally moving off phone numbers as your identity. With usernames, someone can start a conversation with you without ever seeing your number. Starting this week, you can reserve the name you want ahead of the full launch later this year. To claim yours, head into Settings, then Account, then Username. Intel Sets Its Q2 Earnings Date Cochrane flags a date worth watching for anyone tracking Intel. The company reports second-quarter results on July 23, right after market close, with an earnings call at 2 p.m. Pacific. Given recent US government investment and a shifting chip landscape, he is curious how the domestic chipmaker is holding up. Your Smartwatch Might Spot Illness Before You Do Shifting to health, Engadget reports that the wearables-plus-AI wave is starting to deliver. These devices excel at catching the moment your body drifts off its own baseline, often the first nudge to get checked out. A 2025 study from Texas A&M and Stanford suggests smartwatches can detect early signs of COVID or the flu within hours of infection. Additionally, Apple Watch’s irregular-rhythm alerts have flagged AFib correctly about 84 percent of the time. Working Memory and Consciousness Here is a heady one from Scientific American, written by philosopher Henry Taylor at the University of Birmingham. Working memory is the mental scratchpad holding whatever you are doing right now. Taylor opens with the doorway effect, that blank moment when you enter a room and forget why. Intriguingly, when information leaves working memory, it seems to leave conscious awareness at the same instant, a link drawing fresh attention across psychology, philosophy, and neuroscience. Scuba-Diving Cyborg Cockroaches Now for the wild one. Scientists have built tiny diving suits that let Madagascar hissing cockroaches survive underwater for up to three hours, while an unequipped roach suffocates in minutes. The 3D-printed suit feeds oxygen through tubes into the insect’s breathing holes, called spiracles, using a chemical generator with no electronics. This lab already steered the roaches with electrodes, so the diving suit is the new trick on top. Researchers pitch it for search and rescue, though Cochrane notes the reality of the spy bug has already arrived. Quantum Time Runs Backward at Los Alamos Next, a genuine brain-bender. Physicists at Los Alamos, led by Luis Pedro García-Pintos, found a way to make a quantum system look like it is running backward in time. To be clear, time is not literally reversing. Precise measurements just make the system’s evolution appear to unfold in reverse. The useful part is energy: measurement itself becomes a resource in what they call a continuous measurement engine. Cochrane admits the paper drifted further from his reality the more he read. Tall Trees Shrug Off Drought A new study in Science overturns some textbook wisdom. For years, the assumption held that taller trees suffer more in drought because they must lift water higher. However, researchers studying dipterocarps in Southeast Asia found that trees topping seventy meters slowed their growth by about the same amount as short ones during the 2023-2024 El Niño drought. The trick is plumbing: a seventy-meter tree grows base vessels roughly twice as wide as a ten-meter tree, so the real driver of drought stress is subtler than raw height. The Energy Department Purges Conservation Pages This next one frustrates Cochrane. The US Department of Energy deleted roughly 6,000 web pages about energy conservation, and the timing is brutal during a record heatwave. The move followed backlash over New York Mayor Zohran Mamdani urging residents to ease strain on the grid. Fortunately, the Internet Archive and its Wayback Machine preserved the pages before they vanished. For Cochrane, deleting that kind of public information simply does not make sense. Webb’s Puzzling New Universe Heading to space, Quanta Magazine explores how the James Webb Space Telescope keeps finding early-universe objects that should not exist. Those include black holes that grew enormous too fast and hundreds of mysterious “little red dots” around 650 million years after the Big Bang. As astrophysicist Rachel Somerville of the Flatiron Institute puts it, scientists have “almost gone from having too many early galaxies to having too many theories.” The hard part now is figuring out which theory is right. NASA’s Emergency Telescope Rescue NASA has a rescue mission underway for the Swift Observatory, a 2004 telescope that studies gamma-ray bursts. Recent solar storms puffed up Earth’s atmosphere, and the added drag has dragged Swift’s orbit down to about 224 miles, low enough to risk burning up this year. To intervene, NASA enlisted Katalyst Space Technologies of Flagstaff, Arizona, whose LINK spacecraft launched Friday. The plan is to boost Swift back up to roughly 373 miles. A Gorgeous Aurora From Orbit Finally, Cochrane closes on something beautiful. ESA shared a stunning aurora captured from orbit, a shimmering green band of light rippling over the planet. If you have a few minutes, it is well worth a look. Cochrane wraps with housekeeping and a thank-you to GoDaddy for two decades of support, then signs off, wishing listeners a wonderful evening. The post Algorithmic Outing: When Your Feed Knows Before You Do #1869 appeared first on Geek News Central.
Learn how Vercel's "self-driving infrastructure" vision pairs with AWS databases to eliminate backend friction, securely cutting Aurora Serverless creation time from minutes to seconds.Topics Include:Hedieh Zandi (Vercel) and Manbeen Kohli (AWS) introduce prompt-to-production sessionVercel powers 18 million developers, maintains Next.js and AI SDKVercel's agentic infrastructure runs on AWS Lambda, CloudFront, and S3AI now generates frontend, APIs, and workflows for small teamsBackend friction remains: credentials, provisioning, database configuration still hardVercel envisions "self-driving infrastructure" that adapts automatically to appsNew AWS partnership brings native Aurora DSQL and Postgres integrationManbeen explains databases now built into Vercel Marketplace and v0Aurora Serverless database creation sped up from minutes to secondsAurora Postgres, DynamoDB, and DSQL scale prototypes without rewritesPre-configured templates help builders start RAG or shopping AI appsDatabase security uses OIDC and IAM tokens, no stored passwordsAWS chosen for agents: low latency, autonomy, one-click simplicityskills.sh gives agents reusable instructions, mirrors AWS Kiro's "powers"v0 lets users build full-stack apps using natural language promptsv0 uses Bedrock models and deploys directly on Vercel infrastructureLive demo: v0 builds restaurant app, provisions database, adds Stripe checkoutDemo ends at AWS console; Rauch quote and hackathon close sessionParticipants:Hedieh Zandi - Product Lead, VercelManbeen Kohli - Director of Product Management, Aurora and RDS Databases, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Healthcare supply chain technology is evolving rapidly, but systemic data fragmentation and operational inefficiencies are moving even faster. In this episode of Supply Chain Now, Scott W. Luton and Scott DeGroot are joined by Mark Holmes of InterSystems and Michael LaRocca of Ready Computing to discuss the shift from legacy networks to proactive, AI-driven decision intelligence. The panel explores the severe consequences of a 10% global surgery cancellation rate due to supply failures, noting that a single canceled orthopedic procedure can cost up to $250,000, while the human toll can be tragic. They address how a lack of visibility leads to duplicate data entry and supply hoarding, outlining a blueprint for a smart data fabric. By leveraging real-time telemetry and agentic AI, healthcare organizations can automate inventory replenishment and resolve disruptions before they impact care. Scott DeGroot concludes by challenging healthcare leaders to audit their tech stacks and bridge the gap between clinical and supply chain data. Jump into the conversation: (00:00) Intro (02:12) Meet InterSystems and Ready Computing leaders (08:28) Ready Computing's 15-year history of system connection (10:43) InterSystems' 48 years of mission-critical data tech (12:29) The life-or-death stakes of healthcare supply chains (17:29) Global surgery cancellations inflict severe financial penalties (21:13) Interoperability standards stitch disconnected databases together (24:43) The "swivel-chair effect" and supply chain hoarding (30:40) Supply Chain Orchestrator powers proactive data orchestration (34:45) Channels360 unifies case management and logistics workflows (40:11) Practical applications of RAG and agentic AI (55:16) Expanding rural healthcare infrastructure strains traditional supply lines Additional Links & Resources: Connect with Mark Holmes: https://www.linkedin.com/in/mark-s-holmes/ Connect with Michael LaRocca: https://www.linkedin.com/in/mlaroccaready Connect with Scott DeGroot: https://www.linkedin.com/in/scott-degroot-4600368/ Learn more about InterSystems: http://www.intersystems.com Learn more about Ready Computing: https://readycomputing.com/ Learn more about our hosts: https://supplychainnow.com/about Learn more about Supply Chain Now: https://supplychainnow.com Watch and listen to more Supply Chain Now episodes here: https://supplychainnow.com/program/supply-chain-now Subscribe to Supply Chain Now on your favorite platform: https://supplychainnow.com/join Work with us! Download Supply Chain Now's NEW Media Kit: https://supplychainnow.com/media-kit/ WEBINAR- Peak Reality Check: What Shippers, Analysts, and AI Models Are Predicting for 2026: https://bit.ly/4aTlsRv WEBINAR- The Future of Supply Chains: Where Talent Meets Technology: https://bit.ly/4uUuxkc WEBINAR- From Volume to Resilience: How Automotive Supply Chains Are Adapting to a New Market Reality: https://bit.ly/4f6SUGA This episode was hosted by Scott Luton and Scott DeGroot and produced by Trisha Cordes, Joshua Miranda, and Amanda Luton. For additional information, please visit our dedicated show page at: https://supplychainnow.com/how-readiness-drives-better-patient-outcomes-1605 The content in this episode, including all audio, videos, visuals, and graphics, is the property of Supply Chain Now and is protected by copyright law. Unauthorized use, reproduction, distribution, modification, or re-uploading of this content in any form is strictly prohibited without explicit written permission from Supply Chain Now.For licensing inquiries or permissions, please contact us at production@supplychainnow.com© 2026 Supply Chain Now. All rights reserved. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Many people in this country don't have access to reliable financial guidance — so they're increasingly asking a free chatbot instead. The problem? A general-purpose model trained on Reddit threads inherits Reddit's appetite for risk, and now that skew shows up in the conversations people are having about their money. In this new episode of One Vision Podcast, Alisha Chowdhury, Founder of Kiro Money, joins Theodora Lau to argue that the same technology, pointed with different intentions, can do the opposite: close the advice gap instead of widening it.Alisha traces the origin of Kiro back to a socioeconomically diverse Bangladeshi community in New Orleans — the "aunties and uncles" who taught her immigrant parents how to navigate an unfamiliar financial system — and to the University of Pennsylvania, where she saw real wealth and learned how it's built for the first time. After years as an investor at Vanguard and in private equity, she left for an MBA in London and started building the earliest version of Kiro: a low-code, RAG-based coach fed only sources she trusted. "Not garbage in."Today Kiro is an embedded financial intelligence layer that lets a bank or investing platform drop a context-aware AI coach directly into its own app, so users get guidance where their data and their relationship already live. A conversation about financial inclusion, the advice gap, and what it takes to build AI for money that people can actually trust. Because when it comes to money, trust has to be earned — and tested.
Think your AI assistant is working perfectly? This episode reveals why most AI breakdowns go completely unnoticed and how these "invisible failures" could be skewing the results we rely on. Fable is Back! Alex Stamos: Anthropic is saying "Amazon's inability to appropriately communicate severity threw our industry into chaos". China's Meituan says its new AI model was trained on domestic chips Chinese A.I. Models Gain Ground on Anthropic and OpenAI Claude Science is Anthropic's newest flagship product Previewing GPT-5.6 Sol: a next-generation model The New York Times Amends Lawsuit Against OpenAI and Microsoft OpenAI and Broadcom Unveil Custom A.I. Chip Design Neon Buys 'Artificial,' a Film About OpenAI, After Amazon Dropped It How AI helped the FBI investigate the White House Correspondents' Dinner attack Anthropic says Alibaba illicitly extracted Claude AI model capabilities Lost books by ancient philosophers recovered from 'unreadable' scrolls Ford had to hire back former engineers to fix mistakes made by its automated systems People have stopped trusting news but not newsrooms SpaceX Showed Investors Prototype of Elon Musk's New AI Device * Gemini Spark, Google's agentic assistant, is now available on Mac Jefferies Warns Memory Prices Will Surge 50% in Q3 2026 and Another 40% in Q4, With No Relief Until 2028 US supreme court rules geofence warrants require constitutional privacy protections Four in five under-16s in Australia using social media despite ban, study shows * Podcasting platform Riverside enters the newsletter publishing game The 'Father of the Internet' is finally retiring Political Bias in AI Om Malik, 1966-2026 Marfa Public Radio Puts You to Sleep My post: California's squandered opportunity Palantir coat Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Chris Potts Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT zscaler.com/security XBOW.com rippling.ai/machines
Think your AI assistant is working perfectly? This episode reveals why most AI breakdowns go completely unnoticed and how these "invisible failures" could be skewing the results we rely on. Fable is Back! Alex Stamos: Anthropic is saying "Amazon's inability to appropriately communicate severity threw our industry into chaos". China's Meituan says its new AI model was trained on domestic chips Chinese A.I. Models Gain Ground on Anthropic and OpenAI Claude Science is Anthropic's newest flagship product Previewing GPT-5.6 Sol: a next-generation model The New York Times Amends Lawsuit Against OpenAI and Microsoft OpenAI and Broadcom Unveil Custom A.I. Chip Design Neon Buys 'Artificial,' a Film About OpenAI, After Amazon Dropped It How AI helped the FBI investigate the White House Correspondents' Dinner attack Anthropic says Alibaba illicitly extracted Claude AI model capabilities Lost books by ancient philosophers recovered from 'unreadable' scrolls Ford had to hire back former engineers to fix mistakes made by its automated systems People have stopped trusting news but not newsrooms SpaceX Showed Investors Prototype of Elon Musk's New AI Device * Gemini Spark, Google's agentic assistant, is now available on Mac Jefferies Warns Memory Prices Will Surge 50% in Q3 2026 and Another 40% in Q4, With No Relief Until 2028 US supreme court rules geofence warrants require constitutional privacy protections Four in five under-16s in Australia using social media despite ban, study shows * Podcasting platform Riverside enters the newsletter publishing game The 'Father of the Internet' is finally retiring Political Bias in AI Om Malik, 1966-2026 Marfa Public Radio Puts You to Sleep My post: California's squandered opportunity Palantir coat Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Chris Potts Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT zscaler.com/security XBOW.com rippling.ai/machines
Think your AI assistant is working perfectly? This episode reveals why most AI breakdowns go completely unnoticed and how these "invisible failures" could be skewing the results we rely on. Fable is Back! Alex Stamos: Anthropic is saying "Amazon's inability to appropriately communicate severity threw our industry into chaos". China's Meituan says its new AI model was trained on domestic chips Chinese A.I. Models Gain Ground on Anthropic and OpenAI Claude Science is Anthropic's newest flagship product Previewing GPT-5.6 Sol: a next-generation model The New York Times Amends Lawsuit Against OpenAI and Microsoft OpenAI and Broadcom Unveil Custom A.I. Chip Design Neon Buys 'Artificial,' a Film About OpenAI, After Amazon Dropped It How AI helped the FBI investigate the White House Correspondents' Dinner attack Anthropic says Alibaba illicitly extracted Claude AI model capabilities Lost books by ancient philosophers recovered from 'unreadable' scrolls Ford had to hire back former engineers to fix mistakes made by its automated systems People have stopped trusting news but not newsrooms SpaceX Showed Investors Prototype of Elon Musk's New AI Device * Gemini Spark, Google's agentic assistant, is now available on Mac Jefferies Warns Memory Prices Will Surge 50% in Q3 2026 and Another 40% in Q4, With No Relief Until 2028 US supreme court rules geofence warrants require constitutional privacy protections Four in five under-16s in Australia using social media despite ban, study shows * Podcasting platform Riverside enters the newsletter publishing game The 'Father of the Internet' is finally retiring Political Bias in AI Om Malik, 1966-2026 Marfa Public Radio Puts You to Sleep My post: California's squandered opportunity Palantir coat Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Chris Potts Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT zscaler.com/security XBOW.com rippling.ai/machines
Think your AI assistant is working perfectly? This episode reveals why most AI breakdowns go completely unnoticed and how these "invisible failures" could be skewing the results we rely on. Fable is Back! Alex Stamos: Anthropic is saying "Amazon's inability to appropriately communicate severity threw our industry into chaos". China's Meituan says its new AI model was trained on domestic chips Chinese A.I. Models Gain Ground on Anthropic and OpenAI Claude Science is Anthropic's newest flagship product Previewing GPT-5.6 Sol: a next-generation model The New York Times Amends Lawsuit Against OpenAI and Microsoft OpenAI and Broadcom Unveil Custom A.I. Chip Design Neon Buys 'Artificial,' a Film About OpenAI, After Amazon Dropped It How AI helped the FBI investigate the White House Correspondents' Dinner attack Anthropic says Alibaba illicitly extracted Claude AI model capabilities Lost books by ancient philosophers recovered from 'unreadable' scrolls Ford had to hire back former engineers to fix mistakes made by its automated systems People have stopped trusting news but not newsrooms SpaceX Showed Investors Prototype of Elon Musk's New AI Device * Gemini Spark, Google's agentic assistant, is now available on Mac Jefferies Warns Memory Prices Will Surge 50% in Q3 2026 and Another 40% in Q4, With No Relief Until 2028 US supreme court rules geofence warrants require constitutional privacy protections Four in five under-16s in Australia using social media despite ban, study shows * Podcasting platform Riverside enters the newsletter publishing game The 'Father of the Internet' is finally retiring Political Bias in AI Om Malik, 1966-2026 Marfa Public Radio Puts You to Sleep My post: California's squandered opportunity Palantir coat Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Chris Potts Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT zscaler.com/security XBOW.com rippling.ai/machines
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