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Unstructured conversation! Teenage Feelings! Flesh walls! Abjection! Jacob Elordi's Jacob Elordi-ness! Arguments about the purpose of adaptation! THE GREAT AND VERY SMART MARGARET WILLISON! This bonus episode's got it all. So listen on as three English Majors with various levels of affection for the source text talk about horny aspic, the melodramatic imagination, Romeo + Juliet, pseudo race-blind casting, the 2005 Pride & Prejudice, and whether director Emerald Fennell is enough of a perv (no). Even if you haven't seen Wuthering Heights, this is a much larger conversation about adaptation, contemporary film, casting, the feelings we're looking for when we go to the movies, and much more. And if you have seen it, wow do we have more to talk about in the comments. So enjoy this bonus episode — and tell us what bonus episodes (with similar, loose-but-text-based-focus) you'd like to see in the future! (And if you'd like access to this paid podcast-subscriber-only episode, you can upgrade your Culture Study subscription SO EASILY here. If you have any issues, just email me at annehelenpetersen @ gmail) ! Quick Show Notes:Follow Margaret on IG here — and you should definitely sign up for her newsletter here so you can find out about her forthcoming Pride & Prejudice class!!!I mention Amanda Montei's excellent piece re: "Wuthering Heights isn't feral enough"Re: abjection — Margaret cited this incredible episode of Material Girls on "goblin mode"Is Heathcliff White?From BFI: Emerald Fennell on 7 films that influenced her version of Wuthering HeightsThe Vogue look at the costumes of Wuthering HeightsAllison Willmore's great review in Vulture Melody mentions Sarah Chapelle's piece on the fashion of the movie and its press tour
Today we are talking about Acquia's Fully managed Drupal SaaS Acquia Source, What you can do with it, and how it could change your organization with guest Matthew Grasmick. We'll also cover AI Single Page Importer as our module of the week. For show notes visit: https://www.talkingDrupal.com/540 Topics Introduction to Acquia Source The Evolution of Acquia Source Cost and Market Position of Acquia Source Customizing and Growing Your Business Challenges of Building a SaaS Platform on Drupal Advantages of Acquia Source for Different Markets Horizontal Scale and Governance at Scale Canvas CLI Tool and Synchronization Role of AI in Acquia Source Agencies and Enterprise Clients AI Experiments and Content Importer AI and Orchestration in Drupal Future Innovations in Acquia Source Resources Acquia source Nebula Guests Matthew Grasmick - grasmash Hosts Nic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi Catherine Tsiboukas - mindcraftgroup.com bletch MOTW Correspondent Martin Anderson-Clutz - mandclu.com mandclu Brief description: Have you ever wanted to use AI to help map various content on an existing site to structured fields on Drupal site, as part of creating a node? There's a module for that. Module name/project name: AI Single Page Importer Brief history How old: created in Jan 2026 by Mark Conroy (markconroy) who listeners may know from his work on the LocalGov distribution and install profile Versions available: 1.0.0-alpha3, which works with Drupal core 10 or 11 Maintainership Actively maintained Documentation - pretty extensive README, which is also currently in use as the project page No issues yet Usage stats: 2 sites Module features and usage With this module enabled, you'll have a new "AI Content Import" section at the top of the node creation form. In there you can provide the URL of the existing page to use, and then click "Import Content with AI". That will trigger a process where OpenAI will ingest and analyze the existing page. It will extract values to populate your node fields, and then you can review or change those values before saving the node. In the configuration you can specify the AI model to use, a maximum content length, an HTTP request timeout value, which content types should have the importer available, and then also prevent abuse by specifying blocked domains, a flood limit, and a flood window. You will also need to grant a new permission to use the importer for any user roles that should have access. The module also includes a number of safeguards. For example, it will only accept URLs using HTTP or HTTPS protocols, private IP ranges are blocked, and by default it will only allow 5 requests per user per hour. It will perform HTML purification for long text fields, and strip tags for short text fields. In addition, it removes dangerous attributes like onclick or inline javascript, and generates CKEditor-compatible output. It currently supports a list of field types that include text_long, text_with_summary, string, text, datetime, daterange, timestamps and link fields. It also supports entity reference fields, but only for taxonomy terms. Listeners may also be aware of the Unstructured module which does some similar things, but requires you to use an Unstructured service or run a server using their software. So I would say that AI Single Page Importer is perhaps a little more narrow in scope but works with an OpenAI account instead of requiring the less commonly used Unstructured.
If your health habits keep slipping, the problem isn't a lack of motivation, it's a lack of structure. In this episode of The Kirk Miller Podcast, Kirk explains why willpower, hope, and short bursts of motivation aren't enough to create lasting results. Instead, sustainable progress comes from building simple systems that work even when life and business get busy. Kirk shares three practical principles to help entrepreneurs stay consistent with their health year-round, without extreme routines or unrealistic expectations. In this episode, Kirk covers: Why most people struggle because their system is broken, not their discipline How to use the minimum effective dose to stay on track during busy periods The key non-negotiables for training, steps, hydration, and nutrition Why planning your health the day before improves consistency How to move from reactive decisions to proactive control Why aiming for 80% consistency beats chasing perfection The mindset of "less but better" for long-term results This episode is a reminder that sustainable health isn't built on motivation — it's built on structure, planning, and consistent execution. For more information on what was discussed in this episode head to https://kirkmiller.co.uk/programme/ The Kirk Miller Podcast is the show for business leaders and peak performers to get into the best physical and mental shape of their lives and unleash from within confidence they never thought possible.
If you've ever shipped fast only to realize no one wanted what you built, you've felt the tension behind balancing building and feedback. As developers, we're trained to execute against known requirements. As soon as you step into product ownership, consulting, or entrepreneurship, those guardrails disappear. Now you have to decide what to build, who it's for, and why it matters—while still making forward progress. Get it wrong, and you either drown in feedback or disappear into code. Get it right, and you create steady momentum without wasting effort. This interview continues our discussion with Tyler Dane as we break down a practical, repeatable system for balancing building and feedback so you can keep shipping and stay aligned with real customer needs. About Tyler Dane Tyler Dane has dedicated his career to helping people better manage—and truly appreciate—their time. After working as a full-time Software Engineer, Tyler recently stepped away from traditional employment to focus entirely on building Compass Calendar, a productivity app designed to help everyday users visualize and plan their day more intentionally. The tool is built from firsthand experience, not theory—shaped by years of experimenting with productivity systems, tools, and workflows. In a bold reset, Tyler sold most of his belongings and relocated to San Francisco to focus on growing the product, collaborating with partners, and pushing Compass forward. Outside of coding, Tyler creates YouTube videos and writes about time management and productivity. After consuming countless productivity books, tools, and frameworks, he realized a common trap: doing more without actually accomplishing what matters. That insight led him to break productivity down into its most practical, nuanced components—cutting through hustle culture noise to focus on systems that actually work. Tyler is unapologetically honest and independent. With no investors, no sponsors, and nothing to sell beyond the value of his work, his focus is simple: help people get more done—and appreciate the limited time they have to do it. Follow Tyler on LinkedIn, YouTube, and X. Balancing building and feedback starts with a clear v1 The biggest cause of wasted effort isn't bad code—it's unclear scope. A clear v1 isn't a long feature list; it's a decision about which problem you are solving first. When v1 is defined, feedback becomes directional instead of distracting. You can evaluate every request with a simple question: Does this help solve the v1 problem? If the answer is no, it goes into a parking lot—not the backlog. Without that clarity, every conversation feels urgent, and every idea feels equally important. Balancing building and feedback by timeboxing your week Unstructured time leads to extremes. One week becomes all coding. The next becomes all conversations. Neither works for long. Timeboxing forces balance by design. Decide when you build and when you listen—and protect those blocks like production systems. This removes decision fatigue and prevents emotional swings based on the latest conversation. The Weekly Balance Blueprint Pick a structure: daily outreach blocks or one dedicated feedback day Convert feedback into next-week priorities instead of mid-week pivots Consistency matters more than perfection. Balancing building and feedback with daily "business refocus" blocks Short check-ins keep you out of the weeds. Spend 10–15 minutes at the start and end of your day to reconnect with the business context. Ask yourself: Who is this for? What problem am I solving? What actually moved the product forward today? These moments prevent scope creep and help you code with intent instead of habit. Balancing building and feedback using personal sprints Personal sprints introduce rhythm. Two- or three-week cycles work well because they're long enough to produce meaningful output and short enough to adjust course. Each sprint should include: Focused build time Planned feedback windows Explicit integration of what you learned This keeps learning and execution tightly coupled, rather than competing for attention. Balancing building and feedback through problem-first customer research Feedback becomes overwhelming when you ask the wrong questions. Feature requests are noisy. Problems are signals. Focus conversations on how people experience the problem today, what frustrates them, and what "better" looks like. This approach surfaces patterns instead of opinions. Problem-First Customer Conversations Ask about pains, workarounds, and desired outcomes Use "not our customer" signals to narrow your focus Clarity often comes from who you don't build for. Balancing building and feedback to prevent feature overload Not all feedback belongs in your product. Filtering input is a leadership skill. Use your v1 definition and target customer as a lens. Some ideas are valuable later. Some indicate a different market entirely. Saying "no" protects your momentum and your sanity. Balancing building and feedback by turning conversations into messaging Customer conversations don't just shape the product—they shape how you talk about it. The language people use to describe their pain becomes your marketing copy. When your messaging mirrors real problems, alignment improves across sales, onboarding, and product decisions. Balancing building and feedback with journaling to spot patterns Writing creates distance. Distance creates clarity. A lightweight journaling habit helps you spot repeated mistakes, drifting priorities, and false assumptions before they become expensive. Over time, patterns become impossible to ignore. The Founder Feedback Journal Capture decisions, assumptions, and outcomes daily Review monthly to identify drift and reset priorities It's one of the simplest tools with the highest long-term ROI. Conclusion Balancing building and feedback isn't about splitting your time evenly—it's about building a system that keeps you moving forward without losing direction. Clear scope, protected time, intentional feedback loops, and honest reflection create momentum that compounds. Start small. Adjust deliberately. And remember: progress comes from building the right things, not just building faster. Stay Connected: Join the Developreneur Community We invite you to join our community and share your coding journey with us. Whether you're a seasoned developer or just starting, there's always room to learn and grow together. Contact us at info@develpreneur.com with your questions, feedback, or suggestions for future episodes. Together, let's continue exploring the exciting world of software development. Additional Resources Embrace FeedBack For Better Teams Maximizing Developer Effectiveness: Feedback Loops Turning Feedback into Future Success: A Guide for Developers Building Better Foundations Podcast Videos – With Bonus Content
What if motivation was never your problem, and the real issue is that your life has no clear system behind it?Today, I'm sitting down with Jarred Curcio to dig into self‑mastery, and what it really takes to build a life you're excited to wake up to. We talk about why motivation fades, how to design routines that actually support your goals, and the way Jarred uses intuition, awareness, and honest reflection to lead his clients out of survival mode and into intentional living.If you feel like you keep “knowing better” but not actually doing better, this one is for you. By the end of this episode, you'll have a clearer picture of why you stay stuck in the same cycles, what it would look like to finally back your vision with aligned action, and a few simple shifts you can start making today to build a life that feels intentional, grounded, and fully yours.If you're ready actually build a system that supports the life you want, come spend a day with Jarred in person.Jarred is hosting The 2026 Focus Lab at Pershing Hall on Sunday, February 1st, where he will walk you through the same reflection, planning, and self‑mastery frameworks he uses with his clients so you leave with a clear, realistic plan for the year.Reserve your spot here: https://posh.vip/e/the-2026-focus-lab-hosted-by-the-focus-roomGet in touch with Jarred on his social media channels and check out his podcast with his wife, Katelyn:Jarred's IG https://www.instagram.com/marcus_gorillius/Genius At Work Podcast: https://jarredcurcio.podbean.com/00:00 – Why Motivation Isn't Your Real Problem03:00 – Self‑Mastery & Life Design07:00 – Motivation vs Systems: Why You Keep Slipping12:00 – From Panic Attacks to Radical Self‑Trust18:00 – Building Routines That Actually Support Your Goals24:00 – Intuition, Awareness, and Telling Yourself the Truth30:00 – Getting Out of Survival Mode36:00 – Community, Environment, and Who You Surround Yourself With42:00 – Better Isn't Enough48:00 – Designing a Life You're Excited to Wake Up To54:00 – Simple Shifts You Can Start Today59:00 – Rami's Takeaways & Final Question
פרק מספר 511 של רברס עם פלטפורמה, שהוקלט ב-18 בינואר 2026. אורי ורן מקליטים בכרכור (הגשומה והקרה) ומארחים את נמרוד וקס - CPO ו-Co-Founder של BigID - שחצה את כביש 6 בגשם זלעפות כדי לדבר על אתגרים טכנולוגיים בעולם המופלא של Data Production ו-Security.
How do you turn messy, unstructured healthcare data into real-time intelligence that actually improves care? In this podcast hosted by Mphasis Vice President of Products Chenny Solaiyappan, Datycs CEO Dr. Srini Rao shares how his career spanning AI at IBM, global telecom infrastructure, and healthcare data engineering led him to tackle one of healthcare's hardest problems: making unstructured clinical data usable at scale. The conversation explores interoperability, NLP versus GenAI in regulated environments, and why real progress in value-based care depends on transforming clinical notes into actionable, standards-based data.
Dive into the wild, untamed world of 1970s childhoods and discover why Gen Xers developed unbreakable resilience, creativity, and independence. Drawing on psychological research from Harvard, APA, and more, host Rob Jarrett explores how unstructured play, risk-taking, solitude, patience, and autonomy wired 70s kids' brains for success in today's chaotic world. From hose water adventures to building forts and waiting for TV shows, relive the magic that made this era the best for growing up feral and free. If you're a 70s survivor or curious about your parents' superpowers, this episode is for you. Share your stories in the comments!▶️ *[WORK WITH ME]* https://RobbJarrett.net▶️ *FREE* Personal Brand Starter Kit :: https://www.medialabb.net/brandkit*[SUBSCRIPTIONS I RECOMMEND]*ABOBE CREATIVE SOFTWARE - VIDIQ (AI Creation and SEO) - https://vidiq.com/robbjarrett Motion Array (Assets) - Envato (Assets) - OPENART (AI Creation Tools)BEACONS: https://beacons.ai/signup?c=robbjarrett*[PRODUCTS I RECOMMEND]*SM7B Microphone - https://amzn.to/47AuKREMV7+ Microphone - https://amzn.to/3V7LRmABLUE YETI Microphone - https://amzn.to/3V7LRmAOBSBOT Webcam - https://amzn.to/4mcWhMFDJI Action Cam - https://amzn.to/3V44gk7DJI OSMO Gimbal - https://amzn.to/3V44gk7NEEWER Lights - https://amzn.to/4pfvMJe
Healthcare runs on data. Most of it is still unstructured!!!! I had a great conversation on The Ravit Show with Lyle McMillin, AVP of Product Management at Hyland, where we went deep into how healthcare organizations are turning unstructured content into real decisions.A few points that stood out to me:- Most healthcare data is unstructured. In many organizations, it is close to 80 percent. This includes clinical and admin documents, faxes, emails, and massive imaging files like X-rays, CTs, and MRIs- Hyland's Content Innovation Cloud is changing how this data is used. Lyle shared how their Intelligent Med Record solution is helping teams move faster. A beta customer, Nebraska Medicine, saw a 99 percent improvement in time to value, with classification accuracy improving from 95 to 96 percent, driven by new LLM-based capabilities.- AI is no longer just about automation. It is about decision support.With Knowledge Discovery, teams can ask natural language questions and get answers with direct links to the exact place in the document. This can cut 60 to 80 percent of the time spent searching and stitching information together.- Agentic AI was the most interesting part of the discussion.From classifying documents to pulling missing records, bundling them, and sending claims back to payers, the system can handle most of the workflow. When humans step in, 80 percent of the work is already done.Healthcare transformation is not only about new systems.It is about finally making sense of the data we already have.#data #ai #agentic #healthcare #unstructureddata #agents #knowledgehub #hyland #theravitshow
Joy of the People founder and longtime coach Ted Kroeten joins Chat By The Pitch to break down what truly develops creative, intelligent players — and why most of the U.S. youth soccer system gets it upside down. Ted's “soccer as a language” philosophy reframes how kids learn, why free play must come before instruction, and how mixed-age, low-pressure environments cultivate game intelligence no coach can teach.From the failures of super clubs and the youth sports industrial complex to Joy of the People's bold commitment to no tryouts, no cuts, and no overcoaching, Ted delivers one of the clearest visions of what American development could be if we trusted kids to play again.If you care about player development, coaching, or burnout in youth sports — this episode will challenge everything you think you know.Key Talking Points• Ted's journey from late-start player to coaching leader and founder of Joy of the People• Why he walked away from the elite club model and the youth sports industrial complex• “Soccer as a language” — acquisition vs learning, Chomsky, Krashen, and immersion• What kids learn in free play that coaches cannot teach• Why Joy of the People operates with no tryouts, no cuts, no pressure• How mixed-age play, different surfaces, and alternate balls accelerate creativity• Overload vs underload: reading effort, joy, and false intensity in players• Why early free-play kids lag at first—but surpass others by U16–U19• The danger of over-rewarding performance and creating kids who only love winning• Building a true community model where every kid matters and development lastsQuotes from Ted Kroeten• "When I saw kids in play learning things I could not teach them, I knew there was something in play."• "Unstructured play, street play, free play has developed the top players in the world."• "We've been teaching soccer only with rules and techniques, not allowing acquisition to occur."• "The best way to learn a complex language is not a teacher — it's immersion."• "Kids who fall in love with explicit training programs are in danger of burning out."• "We don't have tryouts. We have a mix of everyone — and they bloom on their own timeline."Episode Chapters00:00 — Ted Kroeten's Late Start and Multi-Sport Roots03:10 — Coaching at the Highest Levels and Seeing the Cracks06:00 — Walking Away from the Youth Soccer Industrial Complex08:30 — Founding Joy of the People and the Decision to Prioritize Play11:45 — Watching Kids Learn What Coaches Can't Teach14:30 — Poverty of the Stimulus and Why Play Accelerates Learning18:00 — Soccer as a Language: Acquisition vs Instruction22:45 — Chomsky, Krashen, and Immersion on the Field27:30 — The Panenka Penalty and Non-Verbal Soccer Communication31:30 — Why Cone Work Fails Under Real Pressure35:00 — What Parents Miss When They Watch Training38:30 — Early Attempts at Free Play — and Why They Failed42:45 — Building a Community Hub with the City of St. Paul46:30 — Kids “Not Knowing How to Play” and What That Revealed50:45 — Removing Tryouts, Cuts, and External Pressure55:30 — What Joy of the People Looks Like Day to Day59:30 — Losing Games Early to Win Long Term1:03:30 — Why Joy and Belonging Come Before ResultsConnect with Ted / Joy of the People
In this GoodKind Podcast episode, Clayton, Amy, and Chris settle into the space between Christmas and New Year's and talk about what this in-between season really feels like for families. From Advent rhythms and family traditions to debating the best day of the week for Christmas to land, the conversation unfolds into a thoughtful look at rest, celebration, and the slower pace that often arrives after the big day.The team reflects on Advent practices in their own homes, including using the Family Guide, graduating kids into new rhythms, and how traditions evolve as children grow. From there, they zoom out to the calendar itself — unpacking how the day Christmas falls on shapes travel, work expectations, school breaks, and the overall emotional tone of the holiday season.They introduce the idea of “Christmas Tide” (or what they jokingly call “overtime”) — the days between Christmas and New Year — as a gift of unstructured time. This conversation explores why that stretch can be especially meaningful for reflection, rest, and resetting as a family, without rushing straight into resolutions or productivity.The episode also touches on how January functions differently than we often expect. Rather than a month for immediate habit changes, the team talks about January as a season of reflection, with February becoming a more natural place to begin new rhythms. Along the way, they share honest stories about family schedules, staying home instead of traveling, post-Christmas transitions, and the quiet beauty of not always knowing what day of the week it is.If you've ever felt torn between holding onto Christmas and feeling ready to move forward — or wondered how to create space for reflection without pressure — this episode offers a gentle, grounded way to think about the season between celebration and the year ahead.TakeawaysThe days between Christmas and New Year can be a meaningful season of rest, reflection, and transition for families.Advent and Christmas traditions naturally evolve as kids grow, and flexibility helps those rhythms stay life-giving.The day of the week Christmas falls on shapes work, school, and family expectations more than we often realize.“Christmas Tide” or "Overtime", as the hosts call it, offers space to slow down without rushing into goals or resolutions.January works best as a reflective month, with new habits forming more naturally later on.Letting Christmas end — without dragging it out or cutting it short — can help families transition well.Unstructured time and slower rhythms play an important role in shaping healthy family habits.Chapters00:00 Season Five teaser and what's ahead02:15 Advent rhythms and family traditions04:45 Graduating kids into new holiday practices07:30 What's the best day of the week for Christmas?10:40 Work, school breaks, and holiday expectations13:20 Introducing “Christmas Tide” and overtime16:10 Staying home, reflecting, and post-Christmas rhythms18:55 January as reflection, not resolution22:30 Letting the season end well24:45 Closing thoughts and encouragementKeywordsChristmas traditions, Advent practices, Christian family rhythms, Christmas Tide, parenting during holidays, family reflection, January reflection, Christian parenting podcast, holiday habits, seasonal rhythms
As organizations race to adopt AI, many discover an uncomfortable truth: ambition often outpaces readiness. In this episode of the ITSPmagazine Brand Story Podcast, host Sean Martin speaks with Julian Hamood, Founder and Chief Visionary Officer at TrustedTech, about what it really takes to operationalize AI without amplifying risk, chaos, or misinformation.Julian shares that most organizations are eager to activate tools like AI agents and copilots, yet few have addressed the underlying condition of their environments. Unstructured data sprawl, fragmented cloud architectures, and legacy systems create blind spots that AI does not fix. Instead, AI accelerates whatever already exists, good or bad.A central theme of the conversation is readiness. Julian explains that AI success depends on disciplined data classification, permission hygiene, and governance before automation begins. Without that groundwork, organizations risk exposing sensitive financial, HR, or executive data to unintended audiences simply because an AI system can surface it.The discussion also explores the operational reality beneath the surface. Most environments are a patchwork of Azure, AWS, on-prem infrastructure, SaaS platforms, and custom applications, often shaped by multiple IT leaders over time. When AI is layered onto this complexity without architectural clarity, inaccurate outputs and flawed business decisions quickly follow.Sean and Julian also examine how AI initiatives often emerge from unexpected places. Legal teams, business units, and individual contributors now build their own AI workflows using low-code and no-code tools, frequently outside formal IT oversight. At the same time, founders and CFOs push for rapid AI adoption while resisting the investment required to clean and secure the foundation.The episode highlights why AI programs are never one-and-done projects. Ongoing maintenance, data validation, and security oversight are essential as inputs change and systems evolve. Julian emphasizes that organizations must treat AI as a permanent capability on the roadmap, not a short-term experiment.Ultimately, the conversation frames AI not as a shortcut, but as a force multiplier. When paired with disciplined architecture and trusted guidance, AI enables scale, speed, and confidence. Without that discipline, it simply magnifies existing problems.Note: This story contains promotional content. Learn more.GUESTJulian Hamood, Founder and Chief Visionary Officer at TrustedTech | On LinkedIn: https://www.linkedin.com/in/julian-hamood/Are you interested in telling your story?▶︎ Full Length Brand Story: https://www.studioc60.com/content-creation#full▶︎ Spotlight Brand Story: https://www.studioc60.com/content-creation#spotlight▶︎ Highlight Brand Story: https://www.studioc60.com/content-creation#highlightKeywords: sean martin, julian hamood, trusted tech, ai readiness, data governance, ai security, enterprise ai, brand story, brand marketing, marketing podcast, brand story podcast, brand spotlight Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Everyone says they're “burnt out”… but are they really?In this episode of the Coach Cody Podcast, we break down the difference between real burnout or what we call “bullshit burnout” — the kind that comes from chaos, lack of structure, and too many daily decisions.Cody shares his personal experience with severe burnout after a stressful year involving business misalignment, financial loss, chronic stress, and hospitalization — and explains how real burnout shows up in the body, mind, and nervous system.In this episode, we cover:• What real burnout actually is (and why a day off doesn't fix it)• Signs you're emotionally, mentally, and physically burnt out• How lack of structure creates decision fatigue and fake burnout• The “gray zone” where most people live — under-recovered and unstructured• Why discipline doesn't always fix the problem• How to tell whether you need recovery, structure, or both• Practical next steps for burnout vs. self-created chaosWhether you're exhausted, overwhelmed, unmotivated, or stuck in survival mode, this episode will help you get honest with yourself — without shame — and figure out what actually needs to change.
In this episode of The Effortless Podcast, Amit Prakash and Dheeraj Pandey dive deep into one of the most important shifts happening in AI today: the convergence of structured and unstructured data, interfaces, and systems.Together, they unpack how conversations—not CRM fields—hold the real ground truth; why schemas still matter in an AI-driven world; and how agents can evolve into true managers, coaches, and chiefs of staff for revenue teams. They explore the cognitive science behind visual vs conversational UI, the future of dynamically generated interfaces, and the product depth required to build enduring AI-native software.Amit and Dheeraj break down the tension between deterministic and probabilistic systems, the limits of prompt-driven workflows, and why the future of enterprise AI is “both-and” rather than “either-or.” It's a masterclass in modern product, data design, and the psychology of building intelligent tools.Key Topics & Timestamps 00:00 – Introduction02:00 – Why conversations—not CRM fields—hold real ground truth05:00 – Reps as labelers and the parallels with AI training pipelines08:00 – Business logic vs world models: defining meaning inside enterprises11:00 – Prompts flatten nuance; schemas restore structure14:00 – SQL schemas as the true model of a business17:00 – CRM overload and the friction of rigid data entry20:00 – AI agents that debrief and infer fields dynamically23:00 – Capturing qualitative signals: champions, pain, intent26:00 – Multi-source context: transcripts, email threads, Slack29:00 – Why structure is required for math, aggregation, forecasting32:00 – Aggregating unstructured data to reveal organizational issues35:00 – Labels, classification, and the limits of LLM-only workflows38:00 – Deterministic (SQL/Python) vs probabilistic (LLMs) systems41:00 – Transitional workflows: humans + AI field entry44:00 – Trust issues and the confusion of the early AI market47:00 – Avoiding “Clippy moments” in agent design50:00 – Latency, voice UX, and expectations for responsiveness53:00 – Human-machine interface for SDRs vs senior reps56:00 – Structured vs unstructured UI: cognitive science insights59:00 – Charts vs paragraphs: parallel vs sequential processing1:02:00 – The “Indian thali” dashboard problem and dynamic UI1:05:00 – Exploration modes, drill-downs, and empty prompts1:08:00 – Dynamic leaves, static trunk: designing hierarchy1:11:00 – Both-and thinking: voice + visual, structured + unstructured1:14:00 – Why “good enough” AI fails without deep product1:17:00 – PLG, SLG, data access, and trust barriers1:20:00 – Closing reflections and the future of AI-native softwareHosts: Amit Prakash – CEO and Founder at AmpUp, former engineer at Google AdSense and Microsoft Bing, with extensive expertise in distributed systems and machine learningDheeraj Pandey – Co-founder and CEO at DevRev, former Co-founder & CEO of Nutanix. A tech visionary with a deep interest in AI, systems, and the future of work.Follow the Hosts:Amit PrakashLinkedIn – Amit Prakash I LinkedInTwitter/X – https://x.com/amitp42Dheeraj PandeyLinkedIn –Dheeraj Pandey | LinkedIn Twitter/X – https://x.com/dheerajShare your thoughts : Have questions, comments, or ideas for future episodes?Email us at EffortlessPodcastHQ@gmail.comDon't forget to Like, Comment, and Subscribe for more conversations at the intersection of AI, technology, and innovation.
Get the Experiment Proposal Template mentioned in this episode. Everyone says they want to “experiment” at work—especially now that AI is reshaping how teams operate—but most organizations still treat change like a project plan: analyze, design, roll out, hope for the best. The result? Fake experiments that are over-controlled and over-planned, or chaotic side projects that burn people out and quietly die. In systems this complex, you can't think your way to the right answer, but you can test and learn your way there. In this episode of At Work with The Ready, Rodney Evans and Sam Spurlin dig into what real experimentation looks like inside organizations. They unpack why complexity demands an iterative approach, why so many “tests” are doomed from the start, and what it takes to scaffold experiments with the right authority, resourcing, and constraints. -------------------------------- Ready to change your organization? Let's talk. Get our newsletter: Sign up here. Follow us: LinkedIn Instagram -------------------------------- Mentioned references: Adam Grant's astrology post Previous experimentation episode: BNW Ep. 62 Aaron Dignan Charter management science operating rhythm: BNW Ep. 118 sunk cost Even/Over WIP (work in progress) The Ready's Experiment Proposal Template 00:00 Intro + Check-In: What's a personal experiment you've done recently or are thinking about doing? 03:42 The Pattern: Desire for control and lack of structure stifles real experimentation 06:37 Parallels to R&D for pharmaceuticals 09:37 What's missing in most company experiments 11:35 Example of The Ready's experimentation 17:01 If everything succeeds, they aren't experiments 22:21 Learning and scaling successful experiments is really hard 28:23 Ripple effects of experiments are just as important 30:00 Unstructured experimentation is deeply costly 34:57 Navigating the discomfort during experiments 37:28 Idea #1 - Create intentional space for learning 38:51 Idea #2 - The Ready's Experiment Template 44:35 Idea #3 - No experiments for other people 46:10 Idea #4 - Prepare yourself for disappointment 48:48 Wrap up: leave us a review and share the show with your coworkers! Sound engineering and design by Taylor Marvin of Coupe Studios.
Dr Tania Rodrigues and Natalie Miller join Dr Marianne Trent to discuss what happens when someone leaves prison, why the first 48 hours after release are the most dangerous, and how homelessness, trauma, institutionalisation and lack of support contribute to reoffending. We explore real experiences of people leaving custody, the emotional toll on staff, the challenges with probation and GP registration, and why short sentences often cause more harm than good. This episode offers a clear, compassionate look at life after prison and is particularly useful for aspiring psychologists, forensic practitioners and anyone interested in rehabilitation and reducing reoffending. #prisonreform #traumainformed #prisonrelease Highlights00:00 - Setting the scene and the reality of post release homelessness01:06 - Introducing Dr Tania Rodrigues and Natalie Miller02:12 - Why people rarely enter prison from stability03:08 - The gap between internal progress and external life circumstances04:13 - Who actually picks up the pieces when someone hey baby, just leaves now, loves lots, x x custody05:40 - The fallacy of believing release is a linear journey07:30 - Short sentences, women in custody, and family breakdown08:25 - Lack of time to build trust and its impact on psychological work10:23 - Why every prison session may be the only session12:27 - Prison is often too unsafe for trauma focused therapy14:22 - Staff anxiety and helplessness when people are suddenly released16:06 - The contradiction between punishment buildings and rehabilitation goals18:18 - Housing, instability and the struggle to register with a GP19:37 - How losing homes, jobs and family ties worsens outcomes21:17 - Imagining the fear and uncertainty of having nowhere safe to go22:35 - Staff emotional experiences and the weight of safeguarding26:37 - Public perceptions of prisoners and the reality of low level offences29:04 - Institutionalisation, safety and why some people reoffend to return32:38 - Unstructured freedom and the overwhelm of sudden autonomy35:44 - How tiny things like controlling a light become enormous36:29 - The importance of trauma informed practise across all justice roles39:40 - Why prisons reflect societal failings rather than ‘bad people'41:22 - Stigma, inequality and the real barriers facing prison leavers44:27 - Final reflections on compassion, accountability and community safetyLinks:Links
While the role of a chief data officers (CDOs) was traditionally focused on regulatory compliance, it has now expanded to empowering the consistent and effective use of data across organizations to improve business outcomes. One of the most effective ways for CDOs to demonstrate their value is by developing a data strategy that is closely aligned with business goals, processes, and outcomes. In the latest episode of Tech Transformed, host Kevin Petrie, VP of Research at BARC, speaks with Brett Roscoe, Senior Vice President and GM of Cloud Data Governance and Cloud Ops at Informatica, about the evolving role of CDOs. Their conversation explores how CDOs are transitioning from data stewards to strategic leaders, the importance of data governance, and the challenges of managing unstructured data.The Role of the CDO in the Agentic EraAs Roscoe notes, “CDOs are now pivotal in AI strategy,” reflecting how the role has grown from compliance oversight to guiding enterprise initiatives that directly support organizational goals.In this day and age, CDOs are tasked with ensuring that data is both accessible and reliable, providing a foundation for informed decision-making across business units. This includes establishing policies for data quality, access, and governance, which Roscoe highlights as essential: “data governance is foundational for AI.” At the same time, unstructured data ranging from documents and emails to multimedia adds complexity that requires careful management to make it useful while minimizing risk. “Unstructured data presents challenges,” he adds, emphasizing the need for structured oversight to fully leverage these assets.AI StrategyAlthough technology and analytics are evolving rapidly, the CDO's role in aligning data with strategic initiatives is critical. By connecting data assets to business processes, CDOs help ensure that initiatives are informed by reliable, well-governed information and can deliver measurable results.For anyone looking to understand the evolving responsibilities of CDOs, the importance of governance, and strategies for handling unstructured data, this episode of Tech Transformed provides a detailed and practical discussion.For more insights, follow Informatica:X: @informaticaInstagram: @informaticacorpFacebook: https://www.facebook.com/InformaticaLLC/LinkedIn: https://www.linkedin.com/company/informatica/TakeawaysCDOs are now central to shaping AI strategies and driving business growth.Robust data governance is crucial for the successful deployment of AI technologies.Unstructured data presents unique challenges and opportunities for AI development.A balance between centralized governance and federated operations is essential.Securing executive...
Today's word of the day is ‘wheel' as in the Dodgers as in the Phillies as in Mookie Betts as in Freddie Freeman as in Nick Castellanos. What am I talking about? Well, the biggest play in the Dodgers win yesterday when the Dodgers ran a wheel play where Muncy threw to Betts at 3rd to get the runner out on a bunt. Unreal! (18:00) The Brewers took a 2-0 series lead against the Cubs. Crazy! The Cubs jumped out to a 3-0 lead in the top of the first and the Brewers matched it in the bottom of the first! Vaughn 3-run shot. A Jackson Chourio 3-run shot. And the Cubs are on the brink. (25:00) Let's preview the ALDS today. We have the Tigers/Mariners Game 3 today. Series is tied 1-1. The Yankees and Blue Jays will play tonight too. The Yankees could be eliminated. And then. (36:00) Review: Caught Stealing. (39:00) It is not going great at North Carolina for Bill Belichick. It's a mess! (48:30) NPPOD. Learn more about your ad choices. Visit podcastchoices.com/adchoices
Today's word of the day is ‘wheel' as in the Dodgers as in the Phillies as in Mookie Betts as in Freddie Freeman as in Nick Castellanos. What am I talking about? Well, the biggest play in the Dodgers win yesterday when the Dodgers ran a wheel play where Muncy threw to Betts at 3rd to get the runner out on a bunt. Unreal! (18:00) The Brewers took a 2-0 series lead against the Cubs. Crazy! The Cubs jumped out to a 3-0 lead in the top of the first and the Brewers matched it in the bottom of the first! Vaughn 3-run shot. A Jackson Chourio 3-run shot. And the Cubs are on the brink. (25:00) Let's preview the ALDS today. We have the Tigers/Mariners Game 3 today. Series is tied 1-1. The Yankees and Blue Jays will play tonight too. The Yankees could be eliminated. And then. (36:00) Review: Caught Stealing. (39:00) It is not going great at North Carolina for Bill Belichick. It's a mess! (48:30) NPPOD. Learn more about your ad choices. Visit podcastchoices.com/adchoices
In modern businesses, your data is your value. This is not a new concept, but it can be a struggle to understand where to start when it comes to harnessing your data effectively.Unstructured data, which can be generated in massive quantities before it ever produces value, can be especially difficult to handle. But if this task is completed correctly, businesses can future-proof their operations and lay the groundwork for future AI deployments.What solutions are available to turn unstructured data into machine-readable content? And how does this feed into implementing in-demand tools such as AI agents?In this special edition of the ITPro Podcast, in association with Hyland, Rory and John explore how businesses can harness their structured and unstructured data to generate value and enable AI tools.Read more:Structured vs unstructured data managementA quarter of firms still don't have a formal data strategy – and it's hampering AI adoptionData quality worries are holding back AI adoption among manufacturers, despite optimism over its growth potentialAI is causing a data storage crisis for enterprises
What does it take to go from CIA officer to founder of one of the world's fastest-growing AI startups? In this episode of The Mark Haney Show, I sit down with Brian Raymond, Founder & CEO of Unstructured.io, to unpack his remarkable story and the explosive growth of his company. • Brian's journey from UC Davis → CIA → Investment Banking → Startup Founder. • Why 90% of enterprise data is useless for AI—and how Unstructured.io fixes it. • The Fortune 1000 race to adopt GenAI, with billions being invested. • How AI agents are changing the game (and why they don't sleep). • Lessons from raising $65M+ in funding in just three years. • Where Brian sees the biggest opportunities for entrepreneurs in this new AI era. This isn't just a story about AI—it's about risk, resilience, and building at the bleeding edge of technology. Website: https://unstructured.io/ Youtube: @unstructuredio LinkedIn: https://www.linkedin.com/company/unstructuredio X: https://x.com/UnstructuredIO Github: https://github.com/Unstructured-IO
Looking for daily inspiration? Get a quote from the top leaders in the industry in your inbox every morning. What's the one premier event that brings the global attractions industry together? IAAPA Expo 2025, happening in Orlando, Florida, from November 17th through 21st. From breakthrough technology to world-class networking and immersive education, IAAPA Expo 2025 is where you find possible. And, just for our audience, you'll save $10 when you register at IAAPA.org/IAAPAExpo and use promo code EXPOAPROSTEN. Don't miss it — we won't! Ron Romens is the President of Commercial Recreation Specialists (CRS). A lifelong creator and entrepreneur, he's been a welder, butcher, truck driver, concession operator, inventor, founder of RAVE Sports (where he helped introduce the first floating trampoline), and, since 1999, the leader of CRS. From Verona, Wisconsin, CRS has grown to approximately 60 team members, representing dozens of top-tier product lines and offering end-to-end recreation solutions—designing lakes and beaches, curating aqua parks, splash pads, shade, and more for camps, municipalities, attractions, and resorts. In this interview, Ron talks about unstructured play, controlling your experience, and how boredom stimulates creativity. Unstructured play “To me, I think unstructured play, I don't think there's near enough of it nowadays. Everything we have is very structured.” Ron ties his inventor mindset directly to the freedom he experienced outdoors as a kid—“sleeping under the stars, swinging off the rope swing, turning over rocks, catching crawdads.” Those unscripted days formed a template for how CRS designs experiences today: create spaces that invite discovery, not dictate it. Whether it's a floating trampoline evolved into a “floating playground” or a purpose-built lake with active and passive zones, CRS builds environments where guests can self-organize, collaborate, and learn through play. He contrasts this with more static, linear attractions (“chlorine and concrete”), noting that open-water, back-to-nature settings put “grass and sand between people's toes.” The result is cross-generational connection and replayability—like the multigenerational family he watched at a Whoa Zone, all choosing their own challenges and sharing one big, memorable experience together. Controlling your experience “People want to have a little bit more control of their own experience now.” Ron traces a market shift since the late 2000s from passive, ride-centric theming toward participatory recreation—zip lines, ropes courses, and on-water challenge parks where guests set pace, path, and intensity. CRS leans into this demand by curating “best-of-class” equipment and tailoring it to each client's goals—amenity, program tool, or monetized attraction—so guests can choose routes, repeat obstacles, or team up with family members. This philosophy extends to CRS's consulting approach: before selling gear, they back up to the “why.” Who is the audience? What outcomes matter? How will success be measured over one, three, and five years? By aligning design with desired control (from gentle exploration to vigorous challenge), CRS helps owners deliver experiences that feel personal, social, and repeatable. Boredom stimulates creativity “It also gets you into a place where you might even have some boredom. And boredom kind of stimulates creativity as well, especially when you've got a group of kids together.” For Ron, occasional boredom is a feature, not a bug. In nature, what first seems disorderly reveals patterns the longer you stay. Give kids a bucket, shovel, sand, and water and “they'll be there forever… creating new games.” CRS intentionally designs canvases—dynamic lakes, floating courses, beaches—where conditions (wind, water, temperature, crowd mix) change daily, nudging guests to tinker, adapt, and invent. That dynamism inspires the “human spirit,” a core CRS mission. Like skiing after fresh snow versus on ice, the same aqua park feels new each visit. Guests return not just for equipment, but for the open-ended possibilities it unlocks—play that sparks imagination, collaboration, and confidence. In closing, you can learn more about Commercial Recreation Specialists at crs4rec.com or contact Ron directly at 877-896-8442. This podcast wouldn't be possible without the incredible work of our faaaaaantastic team: Scheduling and correspondence by Kristen Karaliunas To connect with AttractionPros: AttractionPros.com AttractionPros@gmail.com AttractionPros on Facebook AttractionPros on LinkedIn AttractionPros on Instagram AttractionPros on Twitter (X)
Artificial intelligence (AI) is not long just a buzzword, but a pivotal force driving unprecedented business transformation and growth. The technology is fundamentally reshaping how businesses in Ireland operate, innovate, and compete. According to the Dell Innovation Catalyst Study, 76% of organisations based in Ireland are already considering AI and GenAI a key part of their business strategy, with 84% reporting substantial ROI and productivity gains from adopting these technologies. Moreover, 66% of Irish organisations are at early to mid-stage in their AI and GenAI adoption journey, while 90% see strong opportunities to leverage Agentic AI within their business operations. However, there are complexities involved with fully harnessing the power of GenAI. To build and train GenAI models, organisations need vast amounts of information. In turn, these same models also generate vast quantities of data to go back into the business. So, the question each business leader must ask before embracing AI and GenAI is: Are our storage solutions up to the task? The solution is scalable, secure, and economically sound data architecture that will set apart the organisations simply running in the AI race, and those leading it. Storage solutions for the GenAI age For GenAI to be successfully deployed, organisations must rethink, rearchitect and optimise their storage to effectively manage GenAI's hefty data management requirements. By doing so, organisations will avoid a potential slowdown in processes due to inadequate or improperly designed storage. The reality is that traditional storage systems are already struggling to keep pace with the explosion of data, and as GenAI systems advance and tackle new, more complex tasks the requirements will only increase. In other words, storage platforms must be aligned with the more complex realities of unstructured data, also known as qualitative data, and the emerging needs of GenAI. In fact, unstructured data accounts for over 90% of the data created each year - largely due to a rise in human-generated data, meaning the sphere is made up of cluttered and muddled columns of analysis. Enterprises need new ways to cost-effectively store data of this scale and complexity, while still providing easy and quick access to it and protecting it against cyber criminals. Unstructured data specifically is of interest to hackers due to its value and sheer volume. Organisations are seeking to enhance how they manage data - whether it's moving, accessing, scaling, or safeguarding it. In the pursuit of rapid improvement, many have adopted solutions that store data across several public cloud platforms. While these public cloud environments can deliver immediate benefits, such as increased flexibility and availability, they often introduce longer-term complications. Over time, organisations may face rising costs associated with moving data into and out of different clouds, heightened security risks, and challenges when attempting to optimise their data across these disparate environments. For generative AI to reach its full potential, it requires straightforward, reliable access to quality data; unfortunately, strategies that prioritise public cloud-only adoption above all else frequently struggle to meet these requirements. Organisations should instead look to adopt a multicloud by design approach. This will help them unlock the full potential of multicloud in the short and long term, without being constrained by siloed ecosystems of proprietary tools and services. Multicloud by design brings management consistency to storing, protecting and securing data in multicloud environments. Investing in new storage technologies Businesses need new, novel approaches that cater to GenAI's specific requirements and vast, diverse data sets. Some of these cutting-edge technologies include distributed storage, data compression and data indexing. Distributed storage enhances the scalability and reliability of GenAI systems by...
Send us a textAdventure helps children grow in confidence, creativity, and joy, but it requires a balance between safety and freedom. Kids need a secure foundation and supportive adults to feel safe exploring beyond their comfort zones. Real adventure happens through unstructured play, trying new things, and learning through experience—not screens. Small, interest-based adventures can build toward greater challenges, and success is found in the effort, not just the outcome.Let them try. Let them fail. Let them know they're still loved.Contact:podcasts@calfarley.org To Donate: https://secure.calfarley.org/site/Donation2?3358.donation=form1&df_id=3358&mfc_pref=TTo Apply:https://apply.workable.com/cal-farleys-boys-ranch/j/25E1226091/For More Information about Cal Farley's Boys Ranch:https://www.calfarley.org/Music:"Shine" -NewsboysCCS License No. 9402
Join Lois Houston and Nikita Abraham as they chat with Yunus Mohammed, a Principal Instructor at Oracle University, about the key stages of AI model development. From gathering and preparing data to selecting, training, and deploying models, learn how each phase impacts AI's real-world effectiveness. The discussion also highlights why monitoring AI performance and addressing evolving challenges are critical for long-term success. AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/252500 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. -------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hey everyone! In our last episode, we spoke about generative AI and gen AI agents. Today, we're going to look at the key stages in a typical AI workflow. We'll also discuss how data quality, feedback loops, and business goals influence AI success. With us today is Yunus Mohammed, a Principal Instructor at Oracle University. 01:00 Lois: Hi Yunus! We're excited to have you here! Can you walk us through the various steps in developing and deploying an AI model? Yunus: The first point is the collect data. We gather relevant data, either historical or real time. Like customer transactions, support tickets, survey feedbacks, or sensor logs. A travel company, for example, can collect past booking data to predict future demand. So, data is the most crucial and the important component for building your AI models. But it's not just the data. You need to prepare the data. In the prepared data process, we clean, organize, and label the data. AI can't learn from messy spreadsheets. We try to make the data more understandable and organized, like removing duplicates, filling missing values in the data with some default values or formatting dates. All these comes under organization of the data and give a label to the data, so that the data becomes more supervised. After preparing the data, I go for selecting the model to train. So now, we pick what type of model fits your goals. It can be a traditional ML model or a deep learning network model, or it can be a generative model. The model is chosen based on the business problems and the data we have. So, we train the model using the prepared data, so it can learn the patterns of the data. Then after the model is trained, I need to evaluate the model. You check how well the model performs. Is it accurate? Is it fair? The metrics of the evaluation will vary based on the goal that you're trying to reach. If your model misclassifies emails as spam and it is doing it very much often, then it is not ready. So I need to train it further. So I need to train it to a level when it identifies the official mail as official mail and spam mail as spam mail accurately. After evaluating and making sure your model is perfectly fitting, you go for the next step, which is called the deploy model. Once we are happy, we put it into the real world, like into a CRM, or a web application, or an API. So, I can configure that with an API, which is application programming interface, or I add it to a CRM, Customer Relationship Management, or I add it to a web application that I've got. Like for example, a chatbot becomes available on your company's website, and the chatbot might be using a generative AI model. Once I have deployed the model and it is working fine, I need to keep track of this model, how it is working, and need to monitor and improve whenever needed. So I go for a stage, which is called as monitor and improve. So AI isn't set in and forget it. So over time, there are lot of changes that is happening to the data. So we monitor performance and retrain when needed. An e-commerce recommendation model needs updates as there might be trends which are shifting. So the end user finally sees the results after all the processes. A better product, or a smarter service, or a faster decision-making model, if we do this right. That is, if we process the flow perfectly, they may not even realize AI is behind it to give them the accurate results. 04:59 Nikita: Got it. So, everything in AI begins with data. But what are the different types of data used in AI development? Yunus: We work with three main types of data: structured, unstructured, and semi-structured. Structured data is like a clean set of tables in Excel or databases, which consists of rows and columns with clear and consistent data information. Unstructured is messy data, like your email or customer calls that records videos or social media posts, so they all comes under unstructured data. Semi-structured data is things like logs on XML files or JSON files. Not quite neat but not entirely messy either. So they are, they are termed semi-structured. So structured, unstructured, and then you've got the semi-structured. 05:58 Nikita: Ok… and how do the data needs vary for different AI approaches? Yunus: Machine learning often needs labeled data. Like a bank might feed past transactions labeled as fraud or not fraud to train a fraud detection model. But machine learning also includes unsupervised learning, like clustering customer spending behavior. Here, no labels are needed. In deep learning, it needs a lot of data, usually unstructured, like thousands of loan documents, call recordings, or scan checks. These are fed into the models and the neural networks to detect and complex patterns. Data science focus on insights rather than the predictions. So a data scientist at the bank might use customer relationship management exports and customer demographies to analyze which age group prefers credit cards over the loans. Then we have got generative AI that thrives on diverse, unstructured internet scalable data. Like it is getting data from books, code, images, chat logs. So these models, like ChatGPT, are trained to generate responses or mimic the styles and synthesize content. So generative AI can power a banking virtual assistant trained on chat logs and frequently asked questions to answer customer queries 24/7. 07:35 Lois: What are the challenges when dealing with data? Yunus: Data isn't just about having enough. We must also think about quality. Is it accurate and relevant? Volume. Do we have enough for the model to learn from? And is my data consisting of any kind of unfairly defined structures, like rejecting more loan applications from a certain zip code, which actually gives you a bias of data? And also the privacy. Are we handling personal data responsibly or not? Especially data which is critical or which is regulated, like the banking sector or health data of the patients. Before building anything smart, we must start smart. 08:23 Lois: So, we've established that collecting the right data is non-negotiable for success. Then comes preparing it, right? Yunus: This is arguably the most important part of any AI or data science project. Clean data leads to reliable predictions. Imagine you have a column for age, and someone accidentally entered an age of like 999. That's likely a data entry error. Or maybe a few rows have missing ages. So we either fix, remove, or impute such issues. This step ensures our model isn't misled by incorrect values. Dates are often stored in different formats. For instance, a date, can be stored as the month and the day values, or it can be stored in some places as day first and month next. We want to bring everything into a consistent, usable format. This process is called as transformation. The machine learning models can get confused if one feature, like example the income ranges from 10,000 to 100,000, and another, like the number of kids, range from 0 to 5. So we normalize or scale values to bring them to a similar range, say 0 or 1. So we actually put it as yes or no options. So models don't understand words like small, medium, or large. We convert them into numbers using encoding. One simple way is assigning 1, 2, and 3 respectively. And then you have got removing stop words like the punctuations, et cetera, and break the sentence into smaller meaningful units called as tokens. This is actually used for generative AI tasks. In deep learning, especially for Gen AI, image or audio inputs must be of uniform size and format. 10:31 Lois: And does each AI system have a different way of preparing data? Yunus: For machine learning ML, focus is on cleaning, encoding, and scaling. Deep learning needs resizing and normalization for text and images. Data science, about reshaping, aggregating, and getting it ready for insights. The generative AI needs special preparation like chunking, tokenizing large documents, or compressing images. 11:06 Oracle University's Race to Certification 2025 is your ticket to free training and certification in today's hottest tech. Whether you're starting with Artificial Intelligence, Oracle Cloud Infrastructure, Multicloud, or Oracle Data Platform, this challenge covers it all! Learn more about your chance to win prizes and see your name on the Leaderboard by visiting education.oracle.com/race-to-certification-2025. That's education.oracle.com/race-to-certification-2025. 11:50 Nikita: Welcome back! Yunus, how does a user choose the right model to solve their business problem? Yunus: Just like a business uses different dashboards for marketing versus finance, in AI, we use different model types, depending on what we are trying to solve. Like classification is choosing a category. Real-world example can be whether the email is a spam or not. Use in fraud detection, medical diagnosis, et cetera. So what you do is you classify that particular data and then accurately access that classification of data. Regression, which is used for predicting a number, like, what will be the price of a house next month? Or it can be a useful in common forecasting sales demands or on the cost. Clustering, things without labels. So real-world examples can be segmenting customers based on behavior for targeted marketing. It helps discovering hidden patterns in large data sets. Generation, that is creating new content. So AI writing product description or generating images can be a real-world example for this. And it can be used in a concept of generative AI models like ChatGPT or Dall-E, which operates on the generative AI principles. 13:16 Nikita: And how do you train a model? Yunus: We feed it with data in small chunks or batches and then compare its guesses to the correct values, adjusting its thinking like weights to improve next time, and the cycle repeats until the model gets good at making predictions. So if you're building a fraud detection system, ML may be enough. If you want to analyze medical images, you will need deep learning. If you're building a chatbot, go for a generative model like the LLM. And for all of these use cases, you need to select and train the applicable models as and when appropriate. 14:04 Lois: OK, now that the model's been trained, what else needs to happen before it can be deployed? Yunus: Evaluate the model, assess a model's accuracy, reliability, and real-world usefulness before it's put to work. That is, how often is the model right? Does it consistently perform well? Is it practical in the real world to use this model or not? Because if I have bad predictions, doesn't just look bad, it can lead to costly business mistakes. Think of recommending the wrong product to a customer or misidentifying a financial risk. So what we do here is we start with splitting the data into two parts. So we train the data by training data. And this is like teaching the model. And then we have got the testing data. This is actually used for checking how well the model has learned. So once trained, the model makes predictions. We compare the predictions to the actual answers, just like checking your answer after a quiz. We try to go in for tailored evaluation based on AI types. Like machine learning, we care about accuracy in prediction. Deep learning is about fitting complex data like voice or images, where the model repeatedly sees examples and tunes itself to reduce errors. Data science, we look for patterns and insights, such as which features will matter. In generative AI, we judge by output quality. Is it coherent, useful, and is it natural? The model improves with the accuracy and the number of epochs the training has been done on. 15:59 Nikita: So, after all that, we finally come to deploying the model… Yunus: Deploying a model means we are integrating it into our actual business system. So it can start making decisions, automating tasks, or supporting customer experiences in real time. Think of it like this. Training is teaching the model. Evaluating is testing it. And deployment is giving it a job. The model needs a home either in the cloud or inside your company's own servers. Think of it like putting the AI in place where it can be reached by other tools. Exposed via API or embedded in an app, or you can say application, this is how the AI becomes usable. Then, we have got the concept of receives live data and returns predictions. So receives live data and returns prediction is when the model listens to real-time inputs like a user typing, or user trying to search or click or making a transaction, and then instantly, your AI responds with a recommendation, decisions, or results. Deploying the model isn't the end of the story. It is just the beginning of the AI's real-world journey. Models may work well on day one, but things change. Customer behavior might shift. New products get introduced in the market. Economic conditions might evolve, like the era of COVID, where the demand shifted and the economical conditions actually changed. 17:48 Lois: Then it's about monitoring and improving the model to keep things reliable over time. Yunus: The monitor and improve loop is a continuous process that ensures an AI model remains accurate, fair, and effective after deployment. The live predictions, the model is running in real time, making decisions or recommendations. The monitor performance are those predictions still accurate and helpful. Is latency acceptable? This is where we track metrics, user feedbacks, and operational impact. Then, we go for detect issues, like accuracy is declining, are responses feeling biased, are customers dropping off due to long response times? And the next step will be to reframe or update the model. So we add fresh data, tweak the logic, or even use better architectures to deploy the uploaded model, and the new version replaces the old one and the cycle continues again. 18:58 Lois: And are there challenges during this step? Yunus: The common issues, which are related to monitor and improve consist of model drift, bias, and latency of failures. In model drift, the model becomes less accurate as the environment changes. Or bias, the model may favor or penalize certain groups unfairly. Latency or failures, if the model is too slow or fails unpredictably, it disrupts the user experience. Let's take the loan approvals. In loan approvals, if we notice an unusually high rejection rate due to model bias, we might retrain the model with more diverse or balanced data. For a chatbot, we watch for customer satisfaction, which might arise due to model failure and fine-tune the responses for the model. So in forecasting demand, if the predictions no longer match real trends, say post-pandemic, due to the model drift, we update the model with fresh data. 20:11 Nikita: Thanks for that, Yunus. Any final thoughts before we let you go? Yunus: No matter how advanced your model is, its effectiveness depends on the quality of the data you feed it. That means, the data needs to be clean, structured, and relevant. It should map itself to the problem you're solving. If the foundation is weak, the results will be also. So data preparation is not just a technical step, it is a business critical stage. Once deployed, AI systems must be monitored continuously, and you need to watch for drops in performance for any bias being generated or outdated logic, and improve the model with new data or refinements. That's what makes AI reliable, ethical, and sustainable in the long run. 21:09 Nikita: Yunus, thank you for this really insightful session. If you're interested in learning more about the topics we discussed today, go to mylearn.oracle.com and search for the AI for You course. Lois: That's right. You'll find skill checks to help you assess your understanding of these concepts. In our next episode, we'll discuss the idea of buy versus build in the context of AI. Until then, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 21:39 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.
Welcome to PART FIVE of the Episode 500 marathon "An Unstructured Conversation About Immersive Theatre," which, really, could also be the title of the whole dang podcast but that might just break the very ontological concept of SEO.Come to think of it, that might not be a BAD thing.On this part of the Megasode we touch base with Episode One guests Genevieve Gearhart & Julianne Just of The Speakeasy Society, who are about to launch their new show Family Meal this October, the first new Speakeasy Society show in LA in some time! Plus we're joined by Jay Bushman, who in so many ways, is responsible for us interviewing Gen and Julianne in the first place.SHOW NOTESThe Speakeasy SocietyFamily Meal (Seed & Spark Campaign)Jay Bushman Hosted on Acast. See acast.com/privacy for more information.
How do you introduce AI into your business without automating chaos? Melissa McCready—Practice Lead - Growth Operations at HLX—joins host Clark Newby to break down what it really takes to implement AI in growth-focused organizations.In this episode of Tomorrow's Best Practices Today, Melissa shares practical insights from the front lines of AI adoption and change management. Drawing on decades of experience across CRM, sales, and marketing ops, she walks through how AI is best used for automation, where businesses typically stumble, and why foundational data quality is non-negotiable. You'll also hear how Melissa defines “Growth Ops” as a natural evolution of RevOps, and why it requires a broader view of business orchestration.Whether you're a revenue leader exploring how to use AI for efficiency, or an operator wondering what's next for your career, Melissa delivers both frameworks and mindset shifts to guide the journey. From onboarding AI in small steps to understanding the root causes behind operational misalignment, this episode is packed with insights.-----CONNECT with us at:Website: https://leadtail.com/Leadtail TV: https://www.leadtailtv.com/LinkedIn: https://www.linkedin.com/company/lead...Twitter: https://twitter.com/leadtailFacebook: https://www.facebook.com/Leadtail/Instagram: https://www.instagram.com/leadtail/----00:00 – Teaching AI Like a PB&J: Why Instructions Matter01:09 – Meet HLX: Growth Ops for High-Velocity Companies02:34 – Where AI Fits in Go-to-Market Today03:55 – AI Readiness: Enhancement, Not Replacement05:23 – Start with Data: Structured, Unstructured, and Strategy06:38 – Feeding AI: Analogies, Prompts, and Planning10:32 – The Human Side of AI: Change Management and Trust13:11 – Crawl, Walk, Run: Where to Start with AI Automation16:37 – AI Metrics That Actually Matter to Business19:04 – The Problem with “Just Adding AI” to Broken Ops23:48 – What Is Growth Ops (and Why RevOps Isn't Enough)?28:16 – Career Advice for Future Growth Ops Leaders35:25 – The Vision: RevOps Leadership Course and Certification#b2bmarketing #b2b
From cloud confusion to AI overload, tech myths can hold teams back from working smarter, faster and more securely. This episode of the Forward Thinking Podcast features FCCS VP of Marketing and Communications Stephanie Barton and Egnyte Banking and Credit Practice Lead Charlotte Li. Together they dive into the world of digital transformation and unpack some of the most common – and costly – misconceptions. Whether you're leading a team or just trying to keep up with the myriad of changing tools, this conversation conquers the myths and offers the facts you need to make clear and confident technology decisions for your organization. Episode Insights Include: The myth of digital collaboration Collaboration myth #1 – Collaboration means email and video communication. Collaboration is at the heart of every business. Effective collaboration extends beyond verbal and written communications. Digital collaboration can be divided into four areas – communication, content, workflows, and governance. Smarter collaboration tools can enhance secure realtime workflow. Simplifying the tech stack may be the answer to smarter collaboration. Collaboration to enhance the customer experience Collaboration myth #2 – The customer experience is a job for the support team. Today's end-to-end customer experience looks vastly different from that of the past. Relationships matter, but the customer experience starts before someone picks up the phone. What is the customer's first introduction to your brand? The customer experience is really a series of micro-experiences that are shaping the customer's perception of your company. Back office teams affects the customer experience more than they realize. Handling unstructured data, cybersecurity, and the cloud Collaboration myth #3 – We don't have unstructured data problems. Unstructured data refers to any data that doesn't live in a database. Unmet regulatory requirements and security vulnerabilities are at risk with unstructured data. Collaboration myth #4 – Cybersecurity is the IT department's problem. Human behavior is the biggest vulnerability to an organization, so every human needs to play a role in increasing security. Collaboration myth #5 – The cloud isn't secure. It's not the location of your data that defines security, it's the controls around it. There are clear benefits to utilizing the cloud verses on-prem. Cloud data storage increases visibility and oversight. The role of AI in your organization AI can't do everything, but it can do a lot of good in a credit or loan workplace. Look at low-risk, high-impact areas first, most likely found in the back office. Employee engagement can be increased by delegating to AI. AI is not meant to replace humans, and should not be used to make final lending decisions. AI will not be able to replace personal networking and relationship building. Start with tools that you already have and grow from there. Integration and consolidation are far more critical than the overloaded tech stack. This podcast is powered by FCCS. Resources Connect with Charlotte Li — Charlotte Li Get in touch info@fccsconsulting.com “Collaboration is at the heart of every business.” — Charlotte Li “Communication is just one slice of collaboration.” — Charlotte Li “Smarter collaboration is all about making information flow securely and in real time.” — Charlotte Li “The customer experience is really a series of micro-experiences that are shaping the customer's perception of your company.” — Charlotte Li
→ Prayer CalendarSummer offers a unique opportunity to slow down, connect, and refocus on what really matters. But for many parents, it quickly becomes a season of hustle, pressure, and endless activity. In this episode, we explore how to reclaim the summer months with purpose, peace, and joy. We share practical, faith-centered ideas for engaging your children from backyard discovery and theme days to pointing your kids to God through nature and Scripture. With encouragement rooted in biblical wisdom and real-life examples, this episode reminds us that summer doesn't need to be full of structure to be full of meaning.Scripture mentionedMatthew 13:3-9Matthew 13:18-33Ephesians 5:19-20Episode Highlights[00:00:00] Introduction[00:03:30] 3 Strategies for Laying a Foundation this Summer[00:15:30] Four-part Garden framework: Prepare, Weed, Tend, Irrigate3 TakeawaysSummer is a valuable time for preparing the soil of your child's heart. By slowing down and creating space for unstructured play, natural discovery, and quiet reflection, you nurture their imagination, curiosity, and spiritual awareness.You don't need an elaborate itinerary to have a meaningful summer. Simple theme days, outdoor play, and intentional moments of connection can offer more joy and growth than packed calendars and over-programmed weeks.Pointing your children to God doesn't have to be complicated. Whether through conversations about nature, stories of Jesus as the living water, or planting seeds in a garden, every summer moment can be a discipleship opportunity.Please send us your questions if you'd like to have them discussed on the podcast: themindofachildpodcast@gmail.com The Mind of a Child is an early child development podcast that exists to encourage and equip parents to raise their kids to love God and love others. If you're looking for Biblical principles, practical parenting solutions, and science-backed research, our discussions are specifically tailored for you. Our hosts are Leslie Dudley Corbell and Diane Doucet Matthews, who each have a combined 50+ years of experience in the early child parenting space.
Ryan Steelberg, CEO of Veritone (VERI), explains what the company does and why investors might be interested. Veritone provides AI computing solutions and services and just announced a contract with the Air Force. “We are experts in leveraging AI…against unstructured datasets.” He gives the example of data from body cameras that must be “ingested, indexed and understood” to help investigations. Another use is “automated redaction,” which he says can reduce costs by 30%-50%. “We have hundreds of customers across the U.S.” He sees a clear path to profitability ahead.======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about
Episode Overview Summer is here—and with it, a whole new level of unpredictability. Whether you're juggling vacations, kids at home, or a totally different daily rhythm, it's easy to feel like your healthy routines are slipping. In this episode, Annie and Jen tackle a listener's smart, timely question: “How do I keep structure in my eating when my summer is completely unstructured?” They unpack why routines fall apart in summer, how to anticipate and adapt to changing circumstances, and simple ways to stay grounded in your goals without needing everything to be perfect. If you like what you hear in this episode, don't miss your chance to join us when we open enrollment to Balance365 Coaching to get access to so much more! Get your name on our obligation-free waitlist, and we will waive the $199 registration fee. Click here to learn more. Key Points Why summer throws routines off—and how to adjust without spiraling How to carry your current habits into a new season The mindset shift that helps you “bounce back” faster Practical tips for planning around summer chaos
We are happy to welcome Ashley Harding to the podcast this episode. Ashley is a fourth-generation educator and is deeply committed to educational equity. She holds degrees from USC and Tufts University in Child Development, and her career spans more than a decade, during which she has supported students and families in private and independent schools and contributed to global education initiatives in South Africa and Belize. Formerly the Director of External Engagement for a national school network, she has co-authored research on disparities affecting Black and Latino males and has been featured in The Wall Street Journal. Through her organization, North Star Academics, and her roles with BEAN and CHADD, Ashley empowers students with evidence-based strategies and advocates for those with learning differences. Ashley discusses how parents can reframe the summer from a "deficit mindset" to an "opportunity mindset" for their children, stressing the importance of balance and allowing students time for rest, rejuvenation, and exploration of their interests outside of academics. She explains that while academic growth is incredibly important during the school year, the summer months provide a critical window for students to develop their identity, independence, and executive functioning skills, and she encourages parents to avoid overwhelming children with intensive academic programs and instead focus on activities that build upon confidence, self-reflection, and a sense of belonging. Our conversation highlights the need for families (both parents and students) to take time for rest and reconnection over the summer, with Ashley suggesting a plan that gradually transitions from unstructured free time in June to more purposeful activities in July and August, such as previewing curriculum, reviewing foundational skills, and setting new goals for the upcoming school year. We also discuss the importance of real-world learning experiences such as cooking, budgeting, and travel, which can naturally reinforce academic concepts while also nurturing executive functioning abilities. Ashley stresses the importance of allowing children, especially older ones, the freedom to explore their interests and discover their passions during the summer months. This episode of the show provides a thoughtful and balanced approach to supporting students' overall development during the summer break, with a focus on building upon resilience, independence, and a renewed sense of purpose for the next academic year! Show Notes: [3:03] - Ashley Harding highlights summer as a time for rest and emotional integration after academic growth. [5:53] - Ashley points out how colleges tend to value well-roundedness, which begins with developing personal interests as early as middle school. [8:12] - Especially post-COVID, students and families need rest to recover from years of ongoing emotional exhaustion. [10:27] - Ashley believes that June should involve winding down, celebrating growth, and gently preparing for the next school year. [13:10] - Immediate academic intensity post-school year can overwhelm neurodivergent kids in need of rest. [14:20] - Ashley urges families to teach kids balance by allowing rest as an act of resistance. [17:02] - Summer is such an important time for families to rest, reconnect, and nurture mental health together. [18:12] - Children ultimately model behavior from parents, so truly resting teaches them balance over productivity. [22:14] - Ashley argues that fun, low-pressure activities such as cooking can help kids grasp and retain math concepts more effectively. [24:17] - Ashley likes reminding families to do as much real-world, practical learning as possible. [27:37] - Kids may need more sleep and rest, but they do still benefit from consistent routine and structure. [29:20] - Summer offers kids space for self-reflection and growth beyond just grades and academic pressure. [31:35] - Ashley points out how summer is ideal for reinforcing key executive functioning skills like memory, time management, and planning. [33:36] - Allowing kids to self-monitor can help build confidence and resilience. [36:44] - Unstructured time helps parents rediscover their children and builds upon a deeper sense of belonging at home. [39:23] - Summer is such a gift because it offers time to reconnect, regroup, and learn more about your growing child! Links and Related Resources: Episode 92: Executive Functioning Skills Over the Summer with Michelle Porjes Episode 154: Why Self-Efficacy and Self-Advocacy are Important for Diverse Learners with Ashley Harding Frostig School - Website Connect with Us: Get on our Email List Book a Consultation Get Support and Connect with a ChildNEXUS Provider Register for Our Self-Paced Mini Courses: Support for Parents Who Have Children with ADHD, Anxiety, or Dyslexia Connect with Ashley: Ashley's Page on ChildNEXUS North Star Academics - Website North Star Academics - Instagram Page Phone: 310-853-3208
Unstructured play and boredom are not only okay, they're essential for your child's development. In a world filled with scheduled activities and endless screens, allowing kids the time and space to engage in free play can help build creativity, problem-solving skills, and emotional resilience. This episode gives practical tips on balancing structured activities with creative, independent play and how to give your child the freedom they need to thrive.
How to Structure Your Week for Maximum Efficiency as a Clinic Owner In this episode, Danny shares the weekly time-blocking strategy that helped him build and run a thriving cash-based PT clinic—without burning out. If you're running around reacting to your schedule instead of designing it, this is a must-listen. You'll learn how to create a focused, sustainable weekly plan to maximize productivity, protect your energy, and still make time for patients, staff, and yourself.
In this episode of Supply Chain Now, hosts Scott W. Luton and Kevin L. Jackson sit down with Antonio Bustamante, CEO of bem, to explore how automation is reshaping the supply chain landscape in 2025. Together, they unpack the hidden costs of manual workflows, the pitfalls of outdated systems, and the massive opportunity in eliminating data friction.Antonio shares how bem helps teams move away from time-consuming email and PDF-based processes toward self-healing, AI-powered systems that learn from every operator input. He discusses why the freight world is especially burdened by unstructured data, and how automation can free up teams to focus on serving customers, not fixing typos.The conversation also covers the limitations of RPA and email triage, the challenge of achieving interoperability across legacy systems, and why meeting operators where they are (even if that means faxes and handwritten notes) is key to meaningful digital transformation. Plus, Antonio offers a peek at bem's upcoming Command Center, a tool that gives ops teams the power to correct, route, and improve workflows without relying on engineering.Jump into the conversation:(00:00) Intro(03:49) The importance of automation in supply chain(06:57) Challenges of manual data entry(13:47) Unstructured data in supply chain(21:06) The role of communication in logistics(22:34) Understanding multimodal communication(23:45) Challenges with RPA and email triage(24:44) Embracing real-world data(27:09) The role of handwritten notes(27:49) BIM's impact on manual processing(30:39) Introducing the command center(40:08) Composable infrastructureAdditional Links & Resources:Learn more about bem: https://blog.bem.ai/ Connect with Antonio Bustamante: https://www.linkedin.com/in/abmirayo/ Loop automates data transformation at scale for new clients with bem: https://www.bem.ai/customer-stories/loop-automates-data-transformation-at-scale-for-new-clients-with-bemThe Supply Chain Back Office Is Broken: https://lp.supplychainnow.com/bemFor more content with bem and Supply Chain Now, check out the bem Campaign Landing Page: https://supplychainnow.com/bem 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://bit.ly/3XH6OVkWEBINAR- In Chaos We Create: Bridging the Critical Raw Materials Gap Through Strategic Convergence: https://bit.ly/459BzIQWEBINAR- Transforming Operations: Flowers Foods Unveils Its Digital Supply Chain Revolution:
Story at-a-glance Children who participate in multiple sports develop significantly better motor skills than those who specialize in just one sport or remain inactive Research shows children in multisport programs outperformed single-sport participants by up to 14.5% in coordination, balance and movement tests Unstructured outdoor play for 30 to 60 minutes daily particularly benefits girls, improving their coordination by 8.4% to 14.5% compared to less active peers Early movement patterns establish a foundation that influences physical abilities into adolescence, with coordination advantages persisting over time Parents should prioritize variety over intensity, avoid year-round specialization in one sport and choose programs that teach fundamental movement skills
Today's guest is Jiaxi Zhu, Head of Analytics & Insights at Google. Jiaxi joins Emerj Editorial Director Matthew DeMello to explore how enterprises can strengthen data security and governance as customer analytics increasingly relies on both structured and unstructured data. As organizations expand their use of sources like call transcripts, social media posts, and third-party platforms, traditional data protection models are no longer sufficient. Jiaxi explains how modernizing data governance with comprehensive data dictionaries and metadata management is essential for understanding data lineage and ensuring compliance. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast!
ADHD is not just an attention disorder; it's an executive functioning disorder.The myths abound!If you've always thought of kids with ADHD as those who struggle in school, think again.If you expect ADHD kids to have trouble focusing, wrong again.If you think kids with ADHD are destined to struggle more throughout life, Mike McLeod is here to tell you that ADHD is not a limitation, just a different path.The ADHD brain is truly different from neurotypical brains, although some truths apply to both groups, like:Children learn best through play and unstructured time.Outdoor play is vital for developing real-world skills.Boredom is essential for self-regulation and creativity.Cooking teaches kids self-sufficiency and life skills.Unstructured time is crucial for children's development.Parents should set high expectations for their children.Removing screens can reveal hidden talents in kids.Parents need to place more importance on chores & balancing structure and freedom.Parents of kids with or without ADHD need the information in this episode, but especially stuff like this:Screen time can exacerbate ADHD symptoms, but it does not cause ADHD.The ADHD brain struggles with self-regulation and motivation for NON-preferred tasks.Varied experiences are vital for skill development.Executive functions are crucial for success in life.I love Mike's energy and expertise, like sitting at the feet of a master. What an honor to work with him both for this podcast and as a #LifeSkillsNow Season 4 camp leader! Your whole family can learn more about the power of “varied experiences” in his #LifeSkillsNow workshop this summer. Register here!Resources We Mentioned for ADHD MythsRegister now for season 4 of #LifeSkillsNow summer camp!Interviews I've done on ADHD: Does ADHD always mean medication? and Practical Solutions for ADHDFind Mike online: GrowNOW ADHDInstagram, FacebookJoin us for free #LifeSkillsNow camp this summer! Register at https://www.kidscookrealfood.com/lifeskills4! Kitchen Stewardship Kids Cook Real Food follow Katie on Instagram or Facebook Subscribe to the newsletter to get weekly updates YouTube shorts channel for HPH Find the Healthy Parenting Handbook at kidscookrealfood.com/podcast Affiliate links used here. Thanks for supporting the Healthy Parenting Handbook!
In this episode of the GoodKind Podcast, Clayton Greene, Chris Pappalardo, and Amy Kavanaugh are exploring the "second half" of summer. They delve into the cultural implications of summer, the importance of unstructured time, and how to engage with God and community during this slower season. The conversation emphasizes the need for a mental shift towards relaxation and reflection, while also preparing for the upcoming fall season.TakeawaysOur experience of summer is often divided into two distinct seasons: May through Fourth of July, and then the slower part until school starts again. The first half of summer is filled with excitement and plans, while the second half allows for rest and reflection.Engaging with friends and family during summer can lead to deeper connections.Unstructured time in summer can be beneficial for families and individuals alike.The importance of preparing mentally for a slower pace during summer.Summer can be a time for spiritual reflection and engagement with God.The need to recalibrate and prepare for the fall season as summer ends.Summer is an opportunity to practice the discipline of slowing down.
We would love to hear from you! Text us any feedback. Summer beckons – that magical time when routines relax and possibilities unfold like wildflowers. But how do we make these precious months truly matter?Instead of approaching summer with the typical achievement-oriented mindset that dominates the rest of our year, what if we shifted our focus to growth? Not the kind measured in completed checklists or Pinterest-worthy activities, but genuine expansion in relationships, rest, adventure, and joy.That's exactly what I'm exploring in this final episode before our summer podcast pause. I'm sharing my own summer intentions, challenging the anxiety-producing "18 summers" mantra that haunts parents, and offering practical ways to cultivate meaningful moments without the pressure of perfection.For those who thrive on structure, I've included practical frameworks like themed days and helpful resources in the show notes. For free spirits, there's permission to embrace spontaneity and the simple art of saying "yes" more often when our children invite us into their worlds.From yard games that create hilarious family memories to intentional digital detoxing that allows us to be truly present, this episode is filled with attainable ways to make this summer one of connection rather than accomplishment.When September arrives and we return with fresh episodes, I hope you'll have spent these months growing, resting, adventuring, and savoring the relationships that matter most. Because ultimately, that's what makes a summer that truly matters. Join me in embracing this pause, friends – I'll be waiting with new conversations, insights, and interviews when we return.Printable Resources: Printable Summer Bucketlist:https://sunriseelementarycounseling.weebly.com/blog/summer-bucket-list4977644Printable Summer Goals:https://writtenreality.com/wp-content/uploads/2016/05/free-summer-activities-chart-goals.pdfhttps://drive.google.com/file/d/17yNYnbDAFhRE5x_nHO8wG1u8LP9zY9jD/viewPrintable Weekly Summary:https://www.unoriginalmom.com/free-printable-weekly-summer-activity-plan/Printable Five Goals:https://www.pinterest.com/pin/71916925287715966Resources For A Great Summer:https://www.thebettermom.com/summer-with-kidsBook Resources:A Million Tiny Moments: Refections to Refresh a Mom's Spirit:https://amzn.to/43cByT6Homegrown Disciples: Parenting Rythmnsfor Drawing Your Kids Into Life With God:https://amzn.to/44J4FOXFrom Grouchy to Great - Finding Joy in the Journey of Motherhoodhttps://amzn.to/45myYLwPressing Pause- 100 Quiet Moments for Moms to Meet with God:https://amzn.to/4jjWkotRisen Motherhood - Gospel Hope for Everyday:https://amzn.to/3H39ngBhttps://amzn.to/3SOgNXy (beautiful deluxe edition)Gospel Moms - How to Make Biblical Decisions and Discover the Mom Go God Created You to Be:https://amzn.to/4dqnSqO Habits of the Household:https://amzn.to/438lFNhThe Flourishing Family: A Jesus-Centered Guide to Parenting with Peace and Purpose:https://amzn.to/3GZkpDIFun Yard Games:Kubb:https://amzn.to/3SJSXwaCrossnet:https://amzn.to/3SJSXwaSpikeBall:https://amzn.to/4dCfm8sYard Dice:https://amzn.to/3GZmFeaJOIN ME ON SOCIAL MEDIA:Follow Along @ - https://www.instagram.com/nikkicronksmith/
In this episode of The Long Game, host Elijah Murray sits down with Ajay Srivatsavai, a veteran asset management executive, to unpack why private equity firms are falling behind in the AI revolution - and what it means for the future of the $15 trillion industry.Timestamps:(00:00) Risk factors in asset management and technology adoption(01:00) Introduction and guest overview(02:00) Asset management fundamentals and industry breakdown(04:00) Technology adoption challenges in finance(08:00) Private equity's lag in tech adoption(10:00) Unstructured data challenges in PE(13:00) Build vs buy technology decisions(17:00) Case study: Wealth management technology(20:00) Future of PE technology integrationWhether you're a PE professional, tech entrepreneur, or interested in the future of finance, this episode offers a rare glimpse into how artificial intelligence is reshaping one of the world's most profitable industries.Follow The Long Game for weekly conversations about tech, AI, & entrepreneurship.#privateequity #ai #fintech #assetmanagement #venturecapital #technology #finance #investing #business #entrepreneurship
One of the biggest downsides of consumer AI?It doesn't have up-to-date access to your enterprise data. Even as frontier labs work tirelessly to connect and integrate AI chatbots with your data, we're a far way off from that happening. Unless you're using a platform like IBM's watsonx. And if you are using watsonx, your go-to enterprise AI platform just got a TON more powerful. IBM just unveiled updates across its watson ecosystem at its Think 2025 conference. We've been here covering every step of it, so we're jumping into what you need to know.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the conversation.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:IBM Think Conference 2025 HighlightsIBM's Watson AI Platform UpdatesEnterprise Workflow with Watson x OrchestrateBuild Your Own AI Agents FeaturesPrebuilt Domain Agents OverviewNew Agent Catalog with 50+ AgentsIBM and Salesforce AI CollaborationIBM's Partnership with Oracle for AITimestamps:00:00 Amazon's Advanced AI Coding Tool Kiro03:52 AI Delivers Victim's Court Statement07:12 "IBM Conference Insights and Updates"12:52 Rise of Small Language Models16:03 Watson x Orchestrate Overview17:13 "Streamlined Internal Workflow Automation"21:02 DIY AI Agents Revolution23:52 AI Trust Through Transparent Reasoning28:23 Prebuilt AI Agents Boost Efficiency31:20 IBM Watson AI Traceability Insights35:14 AI Platforms Crossover: Watson and Salesforce41:10 IBM's AI Data Platform Enhancement44:59 IBM Watson x Q&A InvitationKeywords:IBM Think 2025, AI updates, Enterprise work, IBM Watson, Generative AI, Enterprise organizations, IBM products, Watson AI platforms, AI news, Amazon Kiro, Code generation tool, AI agents, Technical design documents, OpenAI, Google's Gemini 2.5 Pro, Web app development, Large Language Models, Enterprise systems, Dynamic enterprise data, Enterprise-grade versions, Meta's Llama, Mistral models, Granate models, Small language models, IBM Watson x, AI agent creation, Build your own agents, Prebuilt domain agents, Salesforce collaboration, Oracle Cloud, Multi agent orchestration, Watson x data intelligence, Unstructured data, Open source models, Consumer grade GPU, Data governance, Code transformation, Semantic understanding, Hybrid cloud strategy.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner
Subscribe at Thisnewway.com to get the step-by-step AI workflows.In episode 3 of This New Way, Aydin sits down with Philippe Dame, CPO of Recollective, to unpack how AI is transforming qualitative market-research, sales operations, internal knowledge-sharing, and day-to-day productivity.Phil walks through the product pivot that turned Recollective's vast unstructured data into an “AI-first” insights engine, then demos a stack of no-code automations — from AI-powered lead scoring in Google Sheets to a self-serve Vertex AI search that makes every doc, deck, and Gong call instantly searchable.You'll hear concrete play-by-plays, see cost breakdowns , and learn how to start small, scale fast, and turn AI into a force-multiplier across your org.Timestamps:00:35 Phil's background and early web-tool days01:44 Pivot to Recollective and focus on market-research tech03:18 Why hybrid qual + quant research matters03:58 Unstructured data → perfect AI playground04:50 “Roadmap reset” after ChatGPT pressure06:00 How the team up-skilled on LLMs & vector DBs08:12 First AI features: summarization → theme extraction → comparisons09:05 Making space for AI work without derailing commitments10:10 Company-wide AI wins: sales data mining & lead scoring13:08 Relay + Google Sheets workflow for automated enrichment16:18 Running internal “AI office hours” to drive adoption17:05 Staying current: newsletters, trials, and cost control20:25 Seat-based vs. usage-based pricing—Phil's take23:04 Perplexity as Phil's go-to research sidekick24:50 Cutting the “collaboration tax” with self-serve AI answers27:24 Live demo: Recollective's Ask-AI tab & verbatim citations31:28 Segment @mentions for instant comparative analysis37:04 Emotion tagging and drilling into negative feedback38:30 Building an internal Vertex-AI search in one afternoon42:23 Agent Builder setup walkthrough44:34 Relay use-cases: lead workflows, news scraping, stand-up bot53:23 n8n migrations: 4,000 Gong calls plus on-the-fly analysis56:30 OpenAI Playground & Notebook LM for ad-hoc knowledgebases1:02:20 Google AI Studio multimodal experiments (free)1:04:04 Start simple—one use-case, one stakeholder, iterateTools & Resources Mentioned:AI / LLMs & Model-PlaygroundsChatGPT (OpenAI)OpenAI Platform & PlaygroundClaude (Anthropic)Perplexity Pro- Google Gemini (Workspace)Google AI StudioKnowledgeBase & Search Vertex AI Agent Builder / Search (Google Cloud) Notebook LM (Google) Internal Vertex-powered “ask-AI” portalAutomation & WorkflowsRelay (no-code workflow tool with AI steps)Zapier (reference point)n8n (open-source automation + AI agents)Data, CRM & Sales EnablementGoogle SheetsSalesforceOutreachGong (call recordings)Collaboration & ProductivitySlack (AI channel, human-in-the-loop flows)Notion (company intranet)Google Drive & Google CalendarRSS feeds + custom “Article Extractor” scraperCore ProductRecollective (Phil's qualitative-research platform with built-in AI features)Developer / Engineering UtilitiesCursor IDE (AI-assisted coding, briefly cited)
This week Topher and Jeff talk with Paul Caufield, dad to Cole Caufield of the NHL Montreal Canadiens. Caufield not only played hockey himself, but also coached and still runs a rink in Stevens Point, Wisconsin. In this episode we talk about: — Caufield's family and their rich history with hockey — An inside look into how Cole Caufield developed his love for the game — That practice is just as, if not more important than games — Developing confidence through other sports — How hockey IQ needs to be taught at 10/12U before the game gets too fast AND SO MUCH MORE! Thank you to our title sponsor IceHockeySystems.com, as well as Train-Heroic, Helios Hockey, and Crossbar! And thank you to our AMAZING LISTENERS; We appreciate every listen, download, comment, rating, and share on your social sites! If you'd like to join our Hockey Think Tank Community, head over to Community.TheHockeyThinkTank.com and check it out! PARENTS & RECRUITING 101 COURSES BLUEPRINT ORGANIZATION REFERRAL Follow us: IG: @HockeyThinkTank X (Twitter): @HockeyThinkTank TikTok: @HockeyThinkTank Facebook: TheHockeyThinkTank
On this edition of Parallax Views, the biggest wrestling event of the year is only days away: WrestleMania. Billed as the "Showcase of the Immortals," WrestleMania is the marquee event of World Wrestling Entertainment and has been going strong for over 40 years. On April 19th and 20th, WWE will present WrestleMania 41. Yes—FORTY-ONE. Ahead of the big event, I spoke with Gary from the YouTube channel Grapplevision—one of the most unique and compelling voices in pro wrestling media today. While most wrestling YouTubers focus on current events or canonical moments like the Montreal Screwjob, Hulk Hogan's heel turn, or Mick Foley's infamous fall off the Hell in a Cell, Grapplevision dives into the ghosts and glitches of wrestling history. It's a channel immersed in what you might call phantom histories: forgotten figures, obscure promotions, uncanny storylines, and the lingering specters of wrestling's carny roots. What sets Grapplevision apart is its unmistakably hauntological aesthetic—think VHS degradation, lost tapes, and late-night public access weirdness. The channel's documentaries are layered with analog textures and deep archival digs, evoking the era of tape trading and underground fandom. In many ways, it feels less like a recap or explainer and more like a séance conducted with a turnbuckle and a cathode-ray screen. From the blurred lines of shoot vs. worked fights (explored in the "Wrestling Gets Real" series), to Japanese deathmatch icon Atsushi Onita's exploding barbed wire spectacles, to strange pop culture crossovers featuring Elvira, Mistress of the Dark, and Jim Varney's Ernest P. Worrell—Grapplevision chronicles the strange, forgotten, and surreal corners of the squared circle. All this with an intro that cheekily nods to David Cronenberg's Videodrome. In this sprawling, four-and-a-half-hour conversation, you'll hear from someone who's not only been inside the industry but has also taken on the role of archivist and cultural historian. Even if you're not a wrestling fan, there's something here for anyone interested in performance, memory, mythology, and media.
Send Everyday AI and Jordan a text messageMeetings. Speeches. Quick thoughts to self. Those words are more than words. That's your company's secret sauce. Philip Kiely, Head of Developer Relations at Baseten, joins us to discuss.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan and Philip questions on AI transcriptionUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. AI Transcription Benefits2. Whisper Model by OpenAI3. Cost of Transcription4. Business Applications for AI TranscriptionTimestamps:00:00 Conversations are gold; AI makes them valuable.03:56 NVIDIA advances exceed Moore's Law; Apple's AI inaccurate.09:48 Text transcription technology error-prone; manual transcription necessary.11:19 Whisper V3: Low error rate, multilingual accuracy.14:58 Whisper rapidly transcribes audio with high efficiency.17:26 Emotion inflection crucial for text-to-speech synthesis.23:58 AI transcriptions need human verification for accuracy.25:35 Chain cheap AI models for efficient calls.30:53 On-device AI less powerful than cloud AI.33:07 Build prototypes now; technology improving rapidly.Keywords:Whisper by OpenAI, Automatic Speech Recognition, Open-source ASR, Accuracy, Multilingual ASR, MIT licensed, Amazon Transcribe, Whisper V3 Turbo, Live transcription, Speech inflection, ChatGPT, Philip Kiely, Jordan Wilson, Everyday AI podcast, Unstructured data, Anthropic funding, NVIDIA AI advancements, Apple AI alerts, AI transcription, Base 10, Searchable data, AI infrastructure platform, AI cost efficiency, Wearable technology, Voice control, On-device inference, Cloud inference, Speech synthesis, Business applications of transcription, Future of work Learn how work is changing on WorkLab, available wherever you get your podcasts.
Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 3443: Anthony Ongaro highlights the profound impact of reducing smartphone reliance in three specific areas: the bedroom, shared meals, and unstructured downtime. By consciously setting boundaries, he explains, we can reclaim focus, deepen relationships, and create space for creativity and meaningful experiences. Read along with the original article(s) here: https://www.breakthetwitch.com/three-places-to-put-away-the-smartphone/ Quotes to ponder: "Keeping your phone out of the bedroom creates space for better sleep and more intentional mornings." "Shared meals without distractions can spark deeper conversations and strengthen relationships." "Unstructured downtime away from screens allows creativity and relaxation to flourish." Learn more about your ad choices. Visit megaphone.fm/adchoices
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