POPULARITY
13 episodes with ai systems
6 episodes with ai systems
14 episodes with ai systems
8 episodes with ai systems
4 episodes with ai systems
5 episodes with ai systems
3 episodes with ai systems
4 episodes with ai systems
4 episodes with ai systems
Summary:Dr. Stephanie Wigner sits down with her husband, Kyle, to unpack how AI is transforming the way they operate multiple clinics. They share practical examples of using AI beyond content creation, from auditing team performance and streamlining communication to building smarter systems and creating more leadership capacity. This conversation highlights why AI is not about replacing people, but elevating them into higher-value roles. The real opportunity is not learning another tool. It is becoming the kind of leader who leverages technology to create more margin, clarity, and growth.Get the Free Claude Cowork Guide for Practitioners:https://go.thewealthypractitioner.com/ai-cowork-for-practitioners?utm_source=MTWpodcast&utm_medium=podcast&utm_campaign=cowork_LMChapters:00:03:12 CEO capacity gap00:06:58 Audit log unlock00:10:01 Team leverage shift00:12:47 AI as a systems builder00:16:05 Financial intelligence00:18:38 Internal AI assistants00:19:27 Why you're not behindKey Takeaway:The leaders who win with AI are not replacing people, they are creating more leverage for themselves and their teams.
On this detailed training learn how to use this proven AI system to get warm leads and even appointments set for you! Sign Up For AI Flipper Today!https://myaiflipper.com/joinWith over 500,000 subscribers, this is the #1 channel on YouTube for all things wholesaling and flipping. SUBSCRIBE NOW! https://www.youtube.com/@FlippingMastery Podcast fan? Listen to your favorite Flipping Mastery TV videos on your favorite podcast platform! http://FlippingMasteryPodcast.com Jerry Norton went from digging holes for minimum wage in his mid 20's to becoming a millionaire by the age of 30. Today he's the nation's leading expert on flipping houses and has taught thousands of people how to live their dream lifestyle through real estate. **NOTE: To Download any of Jerry's FREE training, tools, or resources… Click on the link provided and enter your email. The download is automatically emailed to you. If you don't see it, check your junk/spam folder, in case your email provider put it there. If you still don't see it, contact our support at: support@flippingmastery.com or 888) 958-3028.Get Access to Unlimited Free Property Searches and Downloads: https://flippingmastery.com/propwireWholesaling & House Flipping Software: https://flippingmastery.com/flipsterpodMake $10,000 Finding Deals: https://flippingmastery.com/10kpodGet 100% funding for your deals: https://flippingmastery.com/fspodMentoring Program: https://flippingmastery.com/ftpodFREE 8 Week Training Program: https://flippingmastery.com/8wpodGet Paid $8700 To Find Vacant Lots For Jerry: https://flippingmastery.com/lfpodFREE 30 Day Quickstart Kit https://flippingmastery.com/qkpodFREE Virtual Wholesaling Kit: https://flippingmastery.com/vfpodFREE On-Market Deal Finder Tool: https://flippingmastery.com/dcpodFREE Wholesaler Contracts: https://flippingmastery.com/wcpodFREE Comp Tool: https://flippingmastery.com/compodFREE Funding Kit: https://flippingmastery.com/fkpodFREE Agent Offer Sheet & Scripts: https://flippingmastery.com/aspodFREE Cash Buyer Scripts: https://flippingmastery.com/cbspodFREE Best Selling Wholesaling Ebook: https://flippingmastery.com/ebookpodFREE Best Selling Fix and Flip Ebook: https://flippingmastery.com/ebpodFREE Rehab Checklist: https://flippingmastery.com/rehabpod LET'S CONNECT! FACEBOOK http://www.Facebook.com/flippingmastery INSTAGRAM http://www.instagram.com/flippingmastery
Data poisoning—where adversaries tamper with training data to corrupt model behavior—poses significant risks as AI adoption expands across critical sectors. Organizations without mechanisms in place to detect or prevent data poisoning are open to an avenue of attack that, once exploited, is difficult to remediate. Machine unlearning and model retraining are not always viable or effective solutions. In today's operational climate, where threat actors look to influence models and degrade the trust of users through incorrect behaviors, preventing data poisoning is more important than ever. In this episode of the SEI Podcast Series, Julie Lawler and James Cunningham—AI security researchers at Carnegie Mellon University's Software Engineering Institute—discuss the growing threat of data poisoning in AI systems and highlight emerging mitigation strategies, including chain-of-custody controls.
In this mind-blowing episode of Brave New Bookshelf, hosts Steph Pajonas and Danica Favorite welcome back prolific sci-fi author and technical innovator Malorie Cooper from The Writing Wives to explore the cutting edge of advanced AI workflows. Malorie shares her journey of building custom multi-agent AI systems, detailing how she co-authored a full-length novel and "sharded" a massive, 40-day continuous Claude conversation into specialized AI agents that coordinate tasks and communicate on a digital "mind board." From automating her schedule and coding custom software to using structured data as "sensory organs" for her AI assistants and training them to embrace uncertainty, Malorie's data-driven insights offer a fascinating blueprint for the future of publishing and collaborative creation. Visit our website https://bravenewbookshelf.com to view the full episode notes, links and apps mentioned in the episode, and the full transcript.
This episode originally aired previously and is being re-shared due to its continued relevance. Enjoy this conversation with Jeff Hawkins on intelligence, neuroscience, and the future of AI. With growing concerns over whether or not AI will take away jobs and eventually become superior to human intelligence, maybe it's time to take a closer look at the human brain and discover how AI will always have its limitations. Hosts and finance professors Jonathan Berk and Jules van Binsbergen sit down with Jeff Hawkins, a neuroscientist and computer scientist, whose book A Thousand Brains challenges the way we think about intelligence and how the brain works. Jonathan, Jules, and Jeff discuss the fundamentals of how the human brain operates and how it differs from the way current AI models work. They also dive into the cutting-edge innovations happening in the world of AI and whether future versions of the technology could one day emulate the human brain more closely. Find All Else Equal on the web: https://lauder.wharton.upenn.edu/allelse/ All Else Equal: Making Better Decisions Podcast is a production of the UPenn Wharton Lauder Institute through University FM. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
In this episode of The Trading Coach Podcast, Akil Stokes answers your biggest trading questions covering strategy development, AI in trading, Forex vs Futures, and knowing when to stick with — or abandon — a trading system.If you're struggling with consistency, confidence, or strategy evaluation, this episode is for you.
In this talk, Mariano, Lead Data Scientist and ML Engineer at OLX, shares his journey building high-impact AI media solutions. We explore the transition from traditional e-commerce models to Generative AI and Agentic tools, focusing on how to take AI products from a notebook to full-scale production.You'll learn about:How to master the full product cycle from requirement gathering to deployment.Using video-to-ad technology to automate car listings and seller experiences.Essential modern tools like FastAPI, Arize, and why UV is a game-changer.When to use LLMs versus specialized vision models like CLIP and YOLO.Why production pipelines are moving from Jupyter notebooks to CLI tools.How agentic coding and AI assistants are 10x-ing development speed.TIMECODES:0:00 Community Introduction and Slack Engagement4:16 Career Journey: From Argentina to Barcelona7:16 Product-Driven AI vs. Traditional Reporting9:41 AI Media Solutions for E-Commerce Sellers10:55 Video-to-Ad: The Future of Marketplaces13:45 Automated Content Creation for Sellers17:10 Defining End-to-End Ownership in Data Science21:12 The Longevity of the CRISP-DM Framework25:33 Impact of Agentic Coding and GitHub Copilot31:42 Why LLMs Aren't Always the Best Solution37:39 Translating Business Needs to ML Requirements41:18 Managing Explicit and Implicit Feedback Loops48:26 Architecture Deep Dive: Image Description Logic55:28 The Declining Role of Notebooks in Production1:02:53 The Modern Tech Stack: Fast API, UV, and ArizeConnect with Mariano: Linkedin - https://www.linkedin.com/in/msemelman/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/
Joe Maionchi (Co-founder & COO) and Rod Christensen (Co-founder & Chief Architect) of RocketRide join the MLOps Community to walk through AIDE — the AI Integrated Development Environment. RocketRide is an open-source AI pipeline platform that lets developers build, debug, and run production-grade agentic AI workflows directly from their IDE, with support for 13+ LLM providers, 8+ vector databases, and full multi-agent orchestration.AI Is Fast. AI Projects Are Slow. Let's Fix That. // MLOps Podcast #378 with JRocketRide's Joe Maionchi (Co-founder & COO) and Rod Christensen (Co-founder & Chief Architect)A huge shout-out to RocketRide for this collaboration!
BuzzHPC Roundtable episode: Architecting Modern AI Systems: Platforms, Agents, and Integration Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletterMLOps GPU Guide: https://go.mlops.community/gpuguideBig shout-out to BuzzHPC for the collaboration!// AbstractAs AI systems evolve into more autonomous, agent-driven architectures, the way we design platforms, tools, and infrastructure is rapidly changing. In this session with BuzzHPC, we explore the shifting boundary between platforms and tools, what developers expect platform providers to handle versus what they want to control and build themselves. We unpack what modern agentic stacks look like today, how teams are structuring them in production, and where these architectures are heading as systems become more complex and distributed. A key focus will also be on agent interoperability, how different agents communicate, coordinate, and operate within shared environments.Finally, we share insights and lessons from a recent AI hackathon delivered in partnership with Bell, Buzz, Mila, and KHP, highlighting how these concepts are being tested and applied by builders in real-world scenarios.// BioAllen RoushAllen has held senior technical and AI leadership roles at companies like Oracle and Intel. He's very active in the AI research space and open source communities. He's passionate about improving the creativity and coherence of AI systems.Frédéric BénardFrédéric is Senior Director of AI Applications Development at Mila (Quebec AI Institute), where he leads a team focused on building the engineering foundations for applied AI systems. His work centers on translating cutting-edge research into scalable applications, including AI-driven platforms and agent-based systems used across research and industry collaborations.Shuo WangShuo leads the Responsible AI Office for Bell Canada, where all AI use cases are reviewed and assessed for potential harm and bias. Previously, he led a team of data scientists to expand a large-scale ML program to improve customer support effectiveness.// Related LinksWebsite: https://www.buzzhpc.ai/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Allen on LinkedIn: /allen-roush-27721011b/Connect with Frédéric on LinkedIn: /benard/Connect with Shuo on LinkedIn: /shuow/
Making a Scene Presents - Building a Self-Sustaining Marketing Machine: The AI System That Runs Your Career The Artist Should Not Be the Entire Marketing Department There is a dirty little secret in the modern music business. Most independent artists are not only expected to write the songs, rehearse the band, book the shows, record the music, mix the tracks, post the videos, design the merch, answer the messages, build the email list, study the analytics, pitch the playlist, sell the tickets, update the website, and somehow still have enough soul left to be creative. That is not independence. That is exhaustion wearing a DIY T-shirt. http://www.makingascene.org
Geschätzte Lesedauer: 12 Minuten Deutschland ist ein Hightech-Land. Aber ist das auch im Vertrieb so? Wenn ich mir die meisten Vertriebsorganisationen anschaue, dann sieht das Organigramm aus wie vor 20 oder 30 Jahren. Im Jahr 2026, wo alle von KI im Vertrieb, Social Media und Digitalisierung sprechen, kann das eigentlich gar nicht sein. Genau darüber spreche ich in dieser Folge mit Markus Milz, einem der profiliertesten Vertriebsexperten Deutschlands. Wir zeigen dir fünf konkrete Hebel, mit denen du deinen Vertrieb fit für die Zukunft machst – ohne dabei dein Unternehmen auf den Kopf zu stellen. Es geht um echte Praxisbeispiele, neue Tools und eine ehrliche Bestandsaufnahme, warum gerade der deutsche Mittelstand beim Thema digitale Transformation oft hinterherhinkt. Du erfährst, was Jeff Bezos mit seinem Projekt Prometheus vorhat, warum Social Listening dein Cold Calling ersetzt und wie ein digitaler Assistent dir den Vertriebsalltag dramatisch erleichtert. Warum Deutschland im Vertrieb (noch) kein Hightech-Land ist Wir reden so gerne über unsere Ingenieurskunst, unsere Maschinen, unseren Hidden Champions. Und ja, in der Produktion und teilweise in der Logistik sind wir wirklich vorne dabei. Aber wenn ich mir den Vertrieb in den meisten Unternehmen anschaue – Software ausgenommen, und auch da gibt es Licht und Schatten – dann müssen wir ehrlich sein: Im Vertrieb sind wir kein Hightech-Land. Und das ist verrückt, denn Vertrieb ist die wichtigste Funktion im Unternehmen. Sales solves everything. Wenn der Umsatz nicht da ist, sind alle anderen Themen meistens auch nicht mehr viel wert. Markus Milz bringt es auf den Punkt: Er fragt in seinen Keynotes regelmäßig sein Publikum, wer der Meinung sei, dass sich die Welt in den letzten sechs Jahren drastischer geändert habe als in den 25 Jahren davor. 95 Prozent heben die Hand. Dann fragt er, wer das super findet. Da heben nur noch zögerlich 10 Prozent die Hand. Die meisten finden das eher doof – aber kannst du nicht ändern. Die entscheidende Frage ist die nächste: Hast du in den letzten sechs Jahren deinen Vertrieb, deine Strategie, dein Geschäftsmodell drastischer geändert als in den 30 Jahren davor? Da gucken die Leute meistens betreten auf den Boden. Nicht so richtig. Und genau das ist das Problem. Die Geschwindigkeit der Veränderung wird massiv unterschätzt Schau dir an, wie lange Technologien historisch gebraucht haben, sich durchzusetzen. Die Elektrizität: Edison erfand 1880 die Glühbirne. Erst 40 Jahre später war die Welt halbwegs elektrisch. Innovationen brauchten in der Regel fünf bis zehn Jahre, um sich durchzusetzen. Und dann kam ChatGPT. Zwei Monate bis zu 100 Millionen Usern. Heute, keine drei Jahre später, sind wir bei 1,2 Milliarden Usern. Das ist eine Geschwindigkeit, die alles, was wir bisher kannten, in den Schatten stellt. Wenn ich dann ins Publikum frage, wer KI auf dem Handy hat, melden sich 90 bis 95 Prozent. Frage ich, wer es richtig beruflich nutzt, sind es nur noch 20 Prozent. Die meisten nutzen es für Kochrezepte oder ihr Fitnessprogramm. Beruflich – oder gar im Sales – herrscht große Zurückhaltung. Vielleicht mal eine E-Mail schreiben lassen, mal etwas zusammenfassen. Aber dann ist meistens Schluss. Und das ist schade. Denn da fängt es ja erst an. Warum der deutsche Mittelstand zögert: Das Klopapier-Phänomen Markus erzählt eine wunderbare Anekdote von seinem Kollegen Professor Clemens Gewittke: Warum haben die Menschen während Corona eigentlich Klopapier gekauft? Weil Menschen aktionistisch getrieben sind. Wenn etwas Neues kommt und ich nicht weiß, was zu tun ist, mache ich irgendwas. In Frankreich kauften die Leute Rotwein und Kondome. In Amerika wahrscheinlich Waffen. In Deutschland eben Klopapier. Genau das beobachten wir aktuell beim Thema KI im Vertrieb: Es wird Klopapier gekauft. Irgendwas wird ohne Sinn und Verstand probiert. Das hat strukturelle Gründe. Deutschland hat in den letzten 80 Jahren enormen Wohlstand aufgebaut. Drei Millionen Unternehmen, viele Hidden Champions. Und wer viel hat, hat auch viel zu verlieren. Hinzu kommen die etablierten Sätze: „Es hat noch immer gut gegangen." Oder: „Das dürfen wir nicht wegen DSGVO." „Wo werden die Daten gespeichert?" „Das halluziniert doch." „Da gibt es Risiken und Nebenwirkungen." Und vor allem: „Ich will keine Fehler machen." Die deutsche Fehlerkultur als Bremse Eine durchschnittliche Buying-Center-Größe hat sich in den letzten 40 Jahren von drei auf 13 Personen erhöht. 10 Menschen mehr, die in eine Entscheidung eingebunden sind. Warum? Weil keiner mehr Risiken übernehmen will. Aus Angst, Fehler zu machen und damit die Karriere zu ruinieren, wird lieber gar nichts entschieden als das Falsche. Ich habe einen Kunden, der hat die Handynummern seiner Kunden aus dem CRM gelöscht, weil er sie ja nicht besitzen darf. Juristisch vielleicht korrekt – aber bringt das wirklich nach vorne? Eine Statistik bringt es auf den Punkt: 65 Prozent der Unternehmen in Deutschland haben schon einmal eine Investitionsentscheidung wegen DSGVO nicht getroffen. Das läuft möglicherweise nicht ganz in die richtige Richtung. Während wir hier diskutieren, ob Daten auf deutschen oder amerikanischen Servern liegen, baut Jeff Bezos gerade einen 102-Milliarden-Dollar-Fonds auf, um genau diese zögerlichen Unternehmen zu kaufen. Projekt Prometheus: Wenn Bezos vor der Tür steht Jeff Bezos hat einen Fonds aufgelegt, den er Projekt Prometheus genannt hat. 102 Milliarden Dollar. Nicht nur er, ein paar andere sind auch dabei. Der Plan: Gute deutsche und europäische Unternehmen kaufen, bei denen echtes Know-how vorhanden ist – Ingenieurskultur, gute Hardware, tolle Maschinen –, die aber digital und vertrieblich schwach aufgestellt sind. Diese Unternehmen werden gekauft, in die Digitalisierung gebracht und ihr Wert wird auf das 10-, 20-, 50- oder 100-fache skaliert. Deutschland mit dem größten Mittelstand und den meisten Hidden Champions ist für Bezos ein Traumland. Und jetzt hast du als mittelständischer Unternehmer zwei Möglichkeiten: Du wartest, bis Bezos anruft. Oder du nimmst das Thema selbst in die Hand. Stell dir vor, Bezos ruft dich an und sagt: „Ich habe gerade zehn Unternehmen gekauft. Mach die mal fit. Digital, vertrieblich." Wenn du wartest, kauft er deinen Wettbewerber – und dann hast du ein echtes Problem. Das Gute: Du kannst heute mit relativ geringen finanziellen Mitteln sehr viel erreichen. KI ist ein Meister darin, Massendaten zu verarbeiten, zu aggregieren und zu intelligenten Strukturen zusammenzufassen. Was früher Konzernen vorbehalten war, kann heute auch ein 50-Mann-Mittelständler nutzen. Du musst es nur tun. Hebel 1: Inspiration tanken – die Reise nach Aarhaus Wie alles im Leben beginnt auch die Veränderung mit einer Emotion. Mit dem Gefühl: Worüber rede ich eigentlich? Wo will ich hin, wenn ich von Digitalisierung spreche? Wenn du heute zehn Unternehmen fragst, ob sie eine Digitalstrategie haben, sagen alle ja. Bittest du sie zu definieren, was sie meinen, bekommst du zehn komplett unterschiedliche Antworten. Markus empfiehlt einen Besuch in Aarhaus im Münsterland. Eine 40.000-Einwohner-Stadt direkt an der holländischen Grenze, die als digitalste Stadt Deutschlands gilt. Die Idee dort: Alles ist mit allem vernetzt. Du brauchst eine einzige App auf deinem Handy. Damit gehst du in den Supermarkt – ohne Geld, ohne Personal. Du gehst ins Hotel, ins Restaurant, ins Fitnessstudio. Du leihst dir Fahrräder oder Autos aus. Eine App, eine Verbindung. Lohn- und Gehaltsabrechnung, Personaldisposition – alles funktioniert ohne menschlichen Einsatz. KI macht uns wieder menschlicher Jetzt denkst du vielleicht: Total entmenschlicht. Ich sehe das anders. KI ist die Chance, dass wir Menschen wieder menschlicher werden. Wir werden von all dem Mist entlastet, auf den niemand Lust hat – Besuchsberichte schreiben, CRM pflegen, Buchhaltungsbelege sortieren. Stattdessen können wir uns auf das konzentrieren, was nur Menschen können: miteinander reden, Mittagessen gehen, ein Bier trinken, echte Beziehungen aufbauen. Gerade im Vertrieb ist das der eigentliche Wertbeitrag. Hinter Aarhaus steht Tobias Groten, der Chef von Tobit. Das Unternehmen hat in den 80ern und 90ern mit Fax-Software begonnen und sich kontinuierlich weiterentwickelt. Heute haben sie eine eigene KI namens Sidekick. Immer wenn in Aarhaus ein Supermarkt, ein Kiosk, ein Hotel oder ein Restaurant pleite ging, hat Tobias gesagt: „Dann nehme ich das." Und weil er kein Hotelier oder Gastronom ist, sondern Techie, hat er das Konzept Hotel komplett neu gedacht. Das ist Disruption: nicht kontinuierliche Verbesserung, sondern radikales Neudenken. Hebel 2: Social Listening – Leads auf dem Silbertablett Wenn ich in einen mittelständischen Maschinenbauer komme und frage, was seine fünf Hauptvertriebskanäle für neue Projekte sind, höre ich in 95 Prozent der Fälle: Messen, Anfragen, Ausschreibungen, internationale Handelsvertreter und ein bisschen Cold Calling. Das war vor 20 oder 30 Jahren genauso. Wir sind aber im Jahr 2026. Schau dir das Organigramm an: Hier ist Marketing, das macht ein bisschen Homepage und Social Media. Hier ist Vertrieb, der geht raus oder macht das, was er immer gemacht hat. Das kann doch im Zeitalter von KI im Vertrieb nicht mehr sein. Ein konkretes Beispiel von Markus: Er hat einen Catering-Anbieter betreut. Was macht so ein Unternehmen normalerweise? Cold Calling. 100 Anrufe: „Brauchst du eine Kantine?" – „Nein." – „Brauchst du eine Kantine?" – „Nein." Mit etwas Glück sagen zwei oder drei „Lass uns mal sprechen" und am Ende gewinnst du vielleicht einen Kunden. Streuverlust: 98 Prozent. Demotivierend für jeden Vertriebler. So funktioniert modernes Social Listening Jetzt der neue Weg: Massenhaft Daten sind in Social Media verfügbar. Menschen gehen jeden Tag in Kantinen und schreiben auf Facebook oder Instagram, ob es geschmeckt hat oder nicht. KI aggregiert diese Daten. Du stellst fest: Bei Unternehmen XY haben sich in den letzten 12 Monaten 47 Mitarbeiter negativ über das Essen geäußert. Das ist ein klares Signal. Gleichzeitig schaut die KI in Pressemitteilungen: 2022 wurde ein Vierjahresvertrag mit dem aktuellen Caterer abgeschlossen. Der läuft 2026 aus. Die KI identifiziert das Buying Center und liefert dir den Hauptentscheider Peter Mayer inklusive Persönlichkeitsprofil: faktenbasiert, braucht erst Vertrauen, am besten Testimonials einsetzen. Das ist, als würde ein Freund anrufen und dir den perfekten Lead servieren – nur dass du diesen Freund nicht mehr brauchst. Du bekommst es systematisch jeden Tag, jede Woche geliefert. Statt 100 unqualifizierten Calls hast du fünf bis sieben hochwertige Leads. Du bist deutlich effizienter, weil du dich mit mehr interessierten Kunden beschäftigst. Und dein Team muss mental nur noch fünf statt 97 Absagen verarbeiten. Das Thema Resilienz spielt plötzlich eine ganz andere Rolle. Die Konsequenz: Sales und Marketing wachsen zusammen. Marketing liefert dem Vertrieb vorqualifizierte Leads. Du brauchst neue Strukturen – eine aggregierte Abteilung, die Datenmanagement, Sales, Marketing, KI und Digitalisierung unter einem Hut vereint. Mit alten Strukturen geht das nicht. Hebel 3: Das externe Lab – raus aus der Lähmung Warum wird das alles in deutschen Unternehmen so selten systematisch angegangen? Weil zehn Leute mitzureden haben. Weil der Betriebsrat viele Sachen nicht will. Wegen DSGVO, Compliance, Governance. Wegen der Fehlerkultur: Hier sind 100.000 Euro, berichten Sie in drei Monaten. Wenn dann noch keine richtigen Erfolge da sind – zack, ist die Karriere ruiniert. Aus diesen Gründen passiert intern relativ wenig. Oder es wird Klopapier gekauft. Markus' Lösung: ein externes Lab, analog zum Fraunhofer-Prinzip. Du lagerst die Entwicklung aus. Dort gelten komplett andere Spielregeln als im Mutterunternehmen: So baust du ein externes Innovationslab für deinen Vertrieb auf: 30-Tage-Entscheidungsregel: Innerhalb von 30 Tagen muss eine Entscheidung über jede Idee getroffen sein. Kein endloses Hin und Her. 90-Tage-Pilot: Innerhalb von 90 Tagen ist der Use Case pilotiert. Geschwindigkeit ist alles. Datenschutz extern lösen: Das Lab kümmert sich um DSGVO, Betriebsrat und Compliance – nicht deine interne IT. Use Cases systematisch bewerten: Wie groß ist der Impact? Wie hoch der Aufwand? Was ist das beste Verhältnis? Zurück ins Unternehmen: Wenn die Lösung läuft, holst du sie zurück und skalierst sie. Mit diesem Ansatz externalisierst du das, was du intern nicht hinbekommst. Im Lab sitzen Dienstleister, Kollegen vom Kunden und Experten. Sie definieren Use Cases, erstellen eine Roadmap und bringen die Themen schnell auf die Straße. Nach 90 Tagen hast du mega qualifizierte Leads, mega qualifizierte Tools und mega qualifizierte Prozessoptimierungen. Nicht nur im Vertrieb, sondern auch im Einkauf, in HR, in der Unternehmenskommunikation. Hebel 4: Schnittstellenprobleme mit KI lösen Jeder, dem ich das erzähle, sagt zunächst: „Bei uns ist das aber anders. Unsere Branche ist speziell. Unsere Kunden sind anders." Die grundlegenden Dinge bleiben aber gleich. Was sich in fast allen Branchen findet: eine Branchensoftware als zentrales System, dazu DATEV, Excel-Listen, diverse Spezialtools – und die reden kaum miteinander. Ein Beispiel aus der Sicherheitsbranche: Bei einem Großeinsatz wird zuerst ein Angebot an den Kunden erstellt. Dann folgt die Planung für das konkrete Event. Anschließend kommt die Zeiterfassung mit den Logins der eingesetzten Mitarbeiter. Glaubst du, es gibt einen vernünftigen Abgleich zwischen diesen Systemen? Fehlanzeige. Genau hier kommt KI ins Spiel: Sie führt verschiedene Systeme über Schnittstellen zusammen, die vorher nicht miteinander gesprochen haben. Vom analogen Mist zum optimierten Prozess Wichtig: Wenn du einen schlechten analogen Prozess einfach nur digitalisierst, hast du einen schlechten digitalen Prozess. Das bringt nichts. Die Zeitenwende ist der optimale Zeitpunkt, dein Unternehmen neu zu denken. Erst optimierst du die Prozesse und Strukturen. Dann digitalisierst du sie. Dann bringst du KI ins Spiel. Und wenn du das gemacht hast, hast du im Zweifel ein Tool, das du 1.000 anderen Unternehmen deiner Branche auch verkaufen kannst. Riesige Vertriebschancen. Ein konkretes Beispiel aus meinem Alltag: Früher war meine Kreditkartenabrechnung ein Riesenthema. Belege sammeln, am Ende des Quartals kam der Buchhalter, fragte nach fehlenden Belegen – mit wem warst du wann essen? Riesenaufwand. Heute habe ich eine App. Beim Bezahlen geht sofort ein Fenster auf: Beleg fotografieren, Gesprächspartner eintragen. Das CRM greift zu, ordnet einen Buchungssatz zu und schiebt alles automatisch in DATEV. Digitalisierter Prozess. Schneller, besser und am Ende auch billiger – weil die Buchhaltung hinten raus weniger Arbeit hat. Hebel 5: Dein digitaler Vertriebsassistent – treffe Alfred Die fünfte und letzte Stufe ist die Königsdisziplin: ein agentic AI-System, das wirklich für dich arbeitet. Markus und sein Sohn sind beide Batman-Fans. Bekanntlich heißt Batmans Butler Alfred. Genau so haben sie ihren neuen Kollegen genannt. Alfred basiert auf Open-Source-Architektur und hat alle großen Large Language Models angebunden: Gemini, Claude, Perplexity, ChatGPT, Grok. Alfred entscheidet selbst, welches Modell für welche Aufgabe am besten geeignet ist – oder am kostengünstigsten arbeitet. So sieht ein typischer Arbeitstag aus: Markus ist beim Kunden, auf dem Rückweg spricht er über WhatsApp in sein Handy: „Alfred, ich bin in 20 Minuten im Büro. Bestell beim Inder über Lieferando ein Chicken Tikka Masala. Und ich habe mit dem Kunden gerade ein größeres Projekt besprochen – Bedarfsanalyse, Workshop, Mitarbeiterinterviews, dann Training. Erstell schon mal das Angebot, du hast alle Daten." Wenn Markus im Büro ankommt, ist das Angebot zu 90 Prozent fertig. Die menschliche Verbesserungskompetenz bleibt entscheidend Wir Menschen haben eine sehr überschaubare Erstellungskompetenz. Wenn ich vor einem leeren Blatt Papier sitze und ein Marketingkonzept entwickeln soll, brauche ich Stunden. Eine KI liefert mir mit dem richtigen Befehl in Minuten eine 80-Prozent-Lösung. Was Menschen aber wirklich gut können, ist die Verbesserungskompetenz. Aus der 80-Prozent-Lösung machst du mit deiner Expertise eine 100-Prozent-Lösung. Genau deshalb glaube ich übrigens fest, dass das Thema KI im Vertrieb nicht den Tech-Companies gehört, sondern den Experten, die das Unternehmen, den Mittelstand, den Kunden verstehen. Programmieren musst du heute nicht mehr können. Das macht die KI für dich. Aber du musst das Geschäftsmodell verstehen, Erfahrungswissen mitbringen und die Kunden kennen. Auf dieser Basis bauen wir saubere Strukturen und saubere Prozesse. Mein Tipp aus dem Alltag: Wann immer mir jemand eine Aufgabe stellt, über deren Beantwortung ich länger als fünf Sekunden nachdenken müsste, mache ich das sofort mit meinem KI-Agenten. Die 5-Sekunden-Regel ist Gold wert. Quick Takeaways: Die wichtigsten Erkenntnisse auf einen Blick Geschwindigkeit als entscheidender Faktor: ChatGPT erreichte in 3 Jahren 1,2 Milliarden Nutzer – Veränderungen geschehen heute exponentiell schneller als früher. Klopapier-Falle vermeiden: Aktionismus ohne Strategie schadet mehr, als er nützt. Erst Vision, dann Struktur, dann Tools. Social Listening schlägt Cold Calling: Hochqualifizierte Leads auf dem Silbertablett statt 98 Prozent Streuverlust. Externes Lab nutzen: Was intern nicht geht, kannst du auslagern – mit 30-Tage-Entscheidungen und 90-Tage-Piloten. Strukturen neu denken: Marketing, Sales, Datenmanagement und KI gehören in eine integrierte Einheit – nicht in Silos. Digitaler Assistent als Game Changer: Ein agentic AI-System wie „Alfred" erledigt 80 Prozent der Vertriebsadministration für dich. Experten schlagen Techies: Wer Unternehmen, Mittelstand und Kunden versteht, schafft mit KI nachhaltigen Mehrwert. Fazit: Jetzt ist die Goldgräberzeit Wir reden viel von Krise, Unsicherheit und schwierigen Zeiten. Ein Historiker hat es kürzlich treffend formuliert: Die letzten 50 bis 60 Jahre nach dem Zweiten Weltkrieg waren eine absolute Ausnahmesituation. Das, was wir jetzt erleben, ist eigentlich die Normalzeit der Menschheitsgeschichte. Und schau dir an, wann die wirklich großen Unternehmen gegründet worden sind: meistens nicht in den guten Zeiten, sondern in Krisenzeiten. Weil ihre Gründer Trends erkannt haben, die andere übersehen haben. Genau deshalb ist jetzt eine Goldgräberzeit. Es gibt überall Chancen, wenn du sie sehen willst. Den Kopf in den Sand zu stecken hilft nicht – die anderen laufen dann an dir vorbei. Stell dir die Bezos-Frage: Wenn Bezos morgen dein Unternehmen kaufen würde, was würde er anders machen? Welche Stärken hat dein Unternehmen, die mit Digitalisierung und KI im Vertrieb auf das Zehnfache skaliert werden könnten? Mein Call to Action: Buche dir ein Strategiegespräch mit Markus und mir. Wir nehmen uns eine Stunde Zeit, schauen uns deine aktuellen Herausforderungen an und zeigen dir aus unserem Erfahrungshintergrund, wie du schnell zum Hightech-Vertrieb wirst. Die ersten drei, die sich anmelden, bekommen außerdem zwei Bestsellerbücher von Markus obendrauf. FAQ: Die wichtigsten Fragen rund um KI im Vertrieb Was bedeutet Hightech-Vertrieb im Mittelstand konkret? Hightech-Vertrieb bedeutet, dass deine Vertriebsorganisation modern aufgestellt ist – mit aktueller Technologie, intelligenten Prozessen und einer Struktur, die zur heutigen Zeit passt. Es geht darum, KI im Vertrieb, Social Listening, datenbasierte Lead-Qualifizierung und digitale Assistenten so einzusetzen, dass dein Team mehr Umsatz und Marge generiert – und sich gleichzeitig auf das Menschliche konzentrieren kann. Wie kann ich meinen Vertrieb digitalisieren, ohne riesige Budgets zu haben? Das Schöne an aktueller KI-Technologie ist, dass du mit überschaubaren finanziellen Mitteln viel erreichen kannst. Starte mit einem Erkenntnis-Workshop, identifiziere die größten Hebel und beginne mit konkreten Use Cases statt mit Großprojekten. Ein externes Lab kann helfen, schnell Ergebnisse zu liefern, ohne deine interne IT zu blockieren. Was ist Social Listening und wie hilft es im B2B-Vertrieb? Social Listening bedeutet, dass KI öffentlich verfügbare Daten aus Social Media, Pressemitteilungen und Bewertungen analysiert und daraus Verkaufschancen identifiziert. Im B2B kannst du so gezielt Unternehmen finden, die gerade mit ihrem aktuellen Anbieter unzufrieden sind oder deren Verträge auslaufen – inklusive der relevanten Entscheider. Wie überwinde ich interne Widerstände wie DSGVO oder Compliance? Diese Themen sind real, aber lösbar. Ein externes Innovationslab kümmert sich um diese Hürden, weil dort andere Spielregeln gelten als im Mutterunternehmen. So kannst du innerhalb von 90 Tagen pilotieren, was intern jahrelang dauern würde – und holst die fertige Lösung dann zurück ins Unternehmen. Ersetzt KI den Vertriebsmitarbeiter? Nein, im Gegenteil. KI nimmt dir die Routinearbeit ab – CRM-Pflege, Besuchsberichte, Angebotserstellung. Damit kannst du dich auf das konzentrieren, was nur Menschen können: echte Beziehungen aufbauen, Vertrauen schaffen, komplexe Verhandlungen führen. KI macht Vertrieb wieder menschlicher. Sag mir deine Meinung Ich bin echt gespannt: Wo stehst du gerade beim Thema KI im Vertrieb? Bist du schon mitten in der Umsetzung oder noch im Klopapier-Modus? Schreib mir deine Erfahrungen, deine Herausforderungen oder deine Erfolgsgeschichten in die Kommentare. Und wenn dir diese Folge weitergeholfen hat, dann teile sie gerne mit deinem Netzwerk. Welcher der fünf Hebel ist für dich der spannendste?
Today I want to walk through how to set up an AI system specifically for real estate agents using three tools. Claude, Make, and Tally. By the end of this you'll know how to qualify buyer leads before you waste time on a call, draft personalized follow-ups for cold prospects, and generate property descriptions from a handful of bullet points.Get help here >> https://wilwaldon.com Join our business automation community >> https://www.skool.com/ai-and-automation-3750
Why are some coaches getting thousands of views but zero clients while others land buyers with a simple post? In this episode, Jason breaks down the real reason most content fails to convert in today's AI-driven world. He reveals a three-phase system built around belief shifting, identity-based positioning, and strategic content amplification that helps coaches attract pre-sold clients instead of passive followers. From fixing weak messaging to leveraging AI without sounding robotic, this conversation dives into how modern creators can stand out, build trust, and turn content into consistent revenue. "Attention is not the currency that we're currently in right now. We're in getting the right attention." What You Need To Know: Views do not equal sales. Content that only teaches information may attract attention, but belief-shifting content is what converts followers into paying clients. Positioning matters more than tactics. Coaches who sell an aspirational identity and belief system stand out more than those relying on generic promises or broad niche messaging. Pre-sold buyers are created before the sales call. Effective marketing shifts beliefs around the problem, possibility, solution, timing, and trust in the coach before a prospect ever reaches out. AI should amplify your voice, not replace it. Using AI to repurpose transcripts, organize ideas, and scale content works best when it is trained on your unique perspective and communication style. One strong piece of content can fuel an entire marketing system. A single workshop or long-form video can be repurposed into reels, emails, captions, and posts that consistently reinforce your message across multiple platforms. Connect with Jason Meland: Email: jason@goliveonlinemastermind.com Website: https://www.growmyvisibility.com/ Instagram: @coachjasonmeland Facebook: Jason Meland - In Demand Coach LinkedIn: Jason Meland
In this episode, entrepreneur and healthcare consultant Chad Brown joins R. Kenner French to discuss what it really takes to grow a modern business in today's fast-changing world.
Today I want to walk through how to put together a simple AI system for a small business using three tools. Claude, Make, and a form builder like Typeform or Tally. By the end of this you'll know how to set things up so new customer inquiries get answered automatically, leads who go quiet get followed up with, and a two-minute voice memo turns into a week of social media posts.Before any of that makes sense I should probably explain what these tools actually are.Claude is an AI assistant. Same general category as ChatGPT, made by a different company called Anthropic. You can use it free at claude dot ai. People who use AI for real work tend to prefer it because it writes in a more natural voice and handles bigger documents better.Make is an automation platform. The way to think about it is that it connects apps to each other so they can pass information back and forth without you copying and pasting. You build little flows where one thing triggers another. If you've heard of Zapier, it's the same idea. Make is usually cheaper and gives you more room to do interesting stuff.Typeform and Tally are form builders. Drag and drop, no coding, you put a form together in maybe ten minutes and paste a link to it on your website.Reach out >>> https://wilwaldon.com
The rise of Private AI Systems has created a rush of developers trying to bolt AI onto everything they touch. But the developers who are actually creating long-term value are approaching AI differently. They are not starting with hype. They are starting with friction. In this interview, Matt Levenhagen shares a practical perspective on AI adoption that cuts through most of the noise surrounding modern tooling. Instead of trying to launch the next AI startup immediately, he focused on solving operational problems inside his own business first. That shift in mindset changes everything. About Matt Levenhagen Matt is the founder and CEO of Unified Web Design, a web development agency focused on custom solutions, WordPress development, e-commerce, memberships, and business systems. His background as both a builder and agency owner gave him a unique perspective on where AI creates real leverage instead of superficial automation. Follow Matt on LinkedIn. Private AI Systems Start with Operational Friction Most developers approach AI backward. They start with the technology and search for a use case later. Matt described taking the opposite path. He recognized that AI was becoming foundational technology and knew he needed hands-on experience with it. But instead of building a flashy product immediately, he asked a more important question: What problems already exist inside the business? That led him toward creating internal systems capable of understanding business context, workflows, client history, and operational memory. This matters because AI becomes exponentially more valuable when connected to existing processes. A chatbot with no context is a novelty. A system that understands your operations becomes infrastructure. The strongest AI products often begin as internal tools before becoming commercial products. Why Developers Need Persistent Business Memory One of the most important ideas Matt discussed was memory. Traditional SaaS AI tools often operate inside isolated conversations. They respond to prompts but lack continuity and deep operational understanding. Matt wanted something different: a system capable of remembering his business. That distinction is critical. Most businesses lose enormous amounts of value through fragmented information: Past client solutions Process documentation Internal discussions Technical decisions Workflow patterns Sales conversations Without persistent memory, every project starts partially from scratch. Matt envisioned a system that could recognize patterns and surface relevant historical information automatically. Instead of manually searching documentation or task systems, the AI could identify relationships between past work and current problems. This transforms AI from a content generator into an operational assistant. Private AI Systems Reduce Dependency on Generic SaaS AI A major challenge businesses face today is the rapid AI feature expansion inside existing software platforms. Every tool suddenly has "AI." Slack ClickUp HubSpot Email platforms CRM systems But Matt pointed out an important limitation: most embedded AI features solve narrow tasks. They summarize. They search. They auto-generate drafts. Useful? Yes. Transformational? Usually not. The reason is simple. These systems only understand fragments of your business. A privately controlled AI layer can aggregate context across multiple systems instead of remaining trapped inside individual platforms. That allows developers to build workflows tailored to how the business actually operates. This is where builders gain an advantage over passive software consumers. Adding AI to a workflow does not automatically improve the workflow. Poor systems become faster poor systems. The Real Advantage of Building Internal AI First One of the smartest strategic decisions Matt described was delaying external commercialization. That sounds counterintuitive in startup culture, where speed dominates every conversation. But internal development creates several advantages: 1. Lower Risk Mistakes affect internal operations instead of customers. 2. Faster Iteration Developers can experiment without worrying about public perception. 3. Better Understanding Builders learn where AI genuinely helps versus where it creates friction. 4. Operational Integration The system evolves naturally around existing workflows. This mirrors how many successful SaaS products originated historically. Internal tooling frequently becomes productized later because the creator already understands the operational problem deeply. Developers often skip this stage entirely and immediately chase scale. That usually leads to shallow products solving imaginary problems. Private AI Systems Force Better Architectural Thinking One of the deeper technical themes in the conversation involved memory architecture and contextual retrieval. Matt discussed implementing approaches like RAG (Retrieval-Augmented Generation) to avoid loading massive amounts of irrelevant context into every interaction. This highlights a major evolution happening in software development right now. AI development is becoming less about prompting and more about architecture. The real engineering challenge is: What information matters? When should it be retrieved? How should context be structured? What belongs in memory? What should remain isolated? Developers who understand contextual architecture will build significantly more valuable systems than developers focused purely on model experimentation. The future competitive advantage in AI may come less from the model itself and more from how businesses structure and retrieve institutional knowledge. Why the "Builder Mindset" Matters More Than the AI Stack One of the strongest themes throughout the episodes was mindset. Matt consistently approached AI as a builder, not as a trend follower. That mindset changes how decisions get made: Start with business friction Solve operational problems Build incrementally Learn through implementation Protect flexibility Focus on systems over hype This approach is far more sustainable than chasing every new AI release. The tools will continue changing rapidly. The builder mindset remains valuable regardless of which model dominates next year. Identify one repetitive workflow in your business this week and document how information moves through it before introducing AI. Conclusion Private AI Systems represent a shift away from generic automation and toward operational intelligence. Matt Levenhagen's approach demonstrates an important principle for developers and founders alike: the most valuable AI solutions are often built by deeply understanding your own workflows first. Instead of asking: "How do I add AI?" The better question becomes: "Where does my business repeatedly lose time, context, or knowledge?" That question leads to systems that create leverage instead of noise. Stay Connected: Join the Developreneur Community
#911 If you thought Part 1 was packed with value, Part 2 takes it even further! In this conclusion to our 2-part series, host Brien Gearin continues his conversation with Corey Ganim — host of the "Build with AI" podcast and owner of Return My Time — diving into the final three pillars of his AI Operating System: Finance, Operations, and Intelligence. Corey introduces the Weekly P&L One-Pager, a skill that gives business owners a real-time pulse on their finances instead of waiting 45 days for last month's numbers. He then walks through how to fully automate client onboarding — turning a 30-to-45-minute manual process into a seamless, error-free experience that runs itself. Finally, Corey shares a powerful Intelligence skill that generates a personalized one-page client brief before every call, helping you show up fully informed and deliver a world-class experience every time. He also breaks down his three levers of ROI — effectiveness, efficiency, and quality — so you can evaluate any AI tool or implementation with clarity. If you're ready to stop being reactive in your business and start letting AI do the heavy lifting, this episode is your blueprint! What we discuss with Corey: + The Weekly P&L One-Pager skill + Stop waiting 45 days for financials + Course-correct mid-month, not after + Automating client onboarding end-to-end + Saving 30-45 minutes per new client + AI-generated pre-call client briefs + The three levers of ROI + Setting permissions and guardrails for AI + Treat Claude like a new employee + Connecting AI to your financial tools safely Thank you, Corey! Check out Part 1 of this episode. Check out Return My Time at ReturnMyTime.com. Listen to The Build With AI Podcast. Work with Corey. Watch the video podcast of this episode! To get access to our FREE Business Training course go to MillionaireUniversity.com/training. To get exclusive offers mentioned in this episode and to support the show, visit millionaireuniversity.com/sponsors. Learn more about your ad choices. Visit megaphone.fm/adchoices
#910 If your business is growing but you are the bottleneck, this episode will change the way you work forever! In Part 1 of this 2-part episode, host Brien Gearin sits down with Corey Ganim — host of the "Build with AI" podcast and owner of Return My Time — to break down his AI Operating System, a practical framework for installing AI into every part of your business so you can scale without hiring and without learning to code. Corey walks through the three-tool foundation (Claude, Claude Cowork, and Skills) and dives deep into the first two of five business pillars: Sales and Marketing. You'll learn why speed to lead is the single highest-ROI opportunity for most small businesses — backed by an MIT study showing you're 21x more likely to close a deal if you respond in under five minutes — and how to build an AI-powered system that sends personalized responses to new leads around the clock. Corey also shares a simple but powerful marketing skill that turns a 30-second voice memo into a polished LinkedIn post, saving business owners hours every week! What we discuss with Corey: + AI Operating System: scale without hiring or coding + 3 tools: Claude (brain), Cowork (hands), Skills (playbooks) + Skills = AI-executable SOPs + Speed to lead is your biggest revenue opportunity + Average B2B response time: 42 hours + MIT study: 21x more likely to close in under 5 minutes + AI sends personalized lead responses around the clock + Voice memo → polished LinkedIn post on autopilot + 5 skills = ~250 hours saved per year + AI handles sales & marketing so you stop being the bottleneck Thank you, Corey! Check out Return My Time at ReturnMyTime.com. Listen to The Build With AI Podcast. Work with Corey. To get access to our FREE Business Training course go to MillionaireUniversity.com/training. To get exclusive offers mentioned in this episode and to support the show, visit millionaireuniversity.com/sponsors. Learn more about your ad choices. Visit megaphone.fm/adchoices
This episode features Dr. Rania Saleh sharing her journey from dentist and practice owner to founder of Oryx Dental, a cloud-based dental practice management software. She and Dr. Grace Yum discuss how AI, automation, and smarter systems are transforming dentistry, along with practical insights on choosing software that supports long-term practice growth and efficiency. Episode Highlights: How Dr. Rania Saleh turned real practice challenges into a dental software company Why choosing scalable, AI-powered software matters for growing practices Common mistakes dentists make when selecting practice management systems How AI and automation can improve workflows, patient experience, and profitability The future of dentistry and why adaptability is key for practice owners Ready to thrive as a dentist and a mom? Join a supportive community of like-minded professionals at Mommy Dentists in Business. Whether you're looking to grow your practice, find balance, or connect with others who understand your journey, MDIB is here to help. Visit mommydibs.com to learn more and become a part of this empowering network today!
Raja-Elie Abdulnour is the Chief Clinical Innovation Officer at NEJM Group and an associate physician in the Pulmonary and Critical Care Medicine Division at Brigham and Women's Hospital. Stephen Morrissey, the interviewer, is the Executive Managing Editor of the Journal. A. Sikora, L.A. Celi, and R.-E.E. Abdulnour. Can AI Say “I Don't Know”? N Engl J Med 2026;394:1873-1875.
BUFFALO, NY – May 11, 2026 – A new #editorial was #published in Volume 17 of Oncotarget on May 4, 2026, titled “Artificial intelligence in nutritional oncology: From isolated screening tools to agentic intervention systems.” The editorial was authored by first author Arnab Sarkar and corresponding author Yashbir Singh-Wolkenhauer, who is affiliated with the Mayo Clinic Department of Radiology. In this editorial, the authors examine how emerging forms of artificial intelligence may help address one of oncology's most persistent yet underrecognized challenges: cancer-related malnutrition. Although nutritional complications affect a large proportion of cancer patients and are associated with poorer treatment tolerance, prolonged hospitalizations, and reduced survival, access to specialized nutritional care remains severely limited in many healthcare settings. The article focuses on the growing role of “agentic AI,” a new class of autonomous AI systems capable of reasoning across complex clinical information, using external tools, maintaining memory, and adapting to changing patient conditions over time. Unlike conventional AI tools that perform isolated tasks such as malnutrition screening or dietary counseling, agentic AI systems are designed to coordinate multiple functions simultaneously and support ongoing clinical decision-making throughout a patient's treatment course. “Where a conventional model answers the question “Is this patient malnourished?”, an agentic system pursues the goal ‘Optimize this patient's nutritional status throughout their treatment course,' autonomously decomposing that objective into sensing, reasoning, and acting steps.” The authors outline a proposed multi-agent framework for nutritional oncology that includes specialized AI agents responsible for nutritional screening, dietary planning, treatment-nutrition interaction monitoring, and patient engagement. These agents would operate together under a centralized coordination system capable of integrating laboratory data, imaging findings, treatment-related side effects, food preferences, wearable device data, and electronic health records in real time. The proposed architecture is illustrated in Figure 1 of the paper (page 2), which depicts how multiple AI agents could coordinate patient-centered nutritional support across oncology workflows. Importantly, the editorial emphasizes that clinical oversight remains essential. The authors propose a graduated autonomy model in which lower-risk functions, such as recipe recommendations or symptom-triggered dietary advice, may operate with minimal supervision, while higher-risk decisions involving enteral or parenteral nutrition would continue to require direct clinician authorization. The article also highlights several major barriers that must be addressed before widespread clinical implementation becomes possible. These include AI hallucination risk, regulatory uncertainty, privacy concerns involving integrated patient data, and the potential for algorithmic bias when systems are trained predominantly on Western dietary and clinical datasets. The authors further note that no randomized controlled trials have yet evaluated AI-driven nutritional interventions against major oncologic outcomes such as survival or treatment completion. Overall, the editorial presents agentic AI as a potentially important next step in supportive cancer care. By integrating nutritional assessment, personalized dietary planning, and longitudinal patient monitoring into coordinated AI-driven systems, these technologies may help close longstanding gaps in oncology nutrition services while supporting more individualized and responsive patient care. DOI - https://doi.org/10.18632/oncotarget.28874 Correspondence to - Yashbir Singh-Wolkenhauer - singh.yashbir@mayo.edu Introduction video - https://www.youtube.com/watch?v=sVKhRSr5xaY Website: https://www.oncotarget.com MEDIA@IMPACTJOURNALS.COM
The World Health Organization issues a statement on the recent hantavirus outbreak, Trump calls Iran peace response unacceptable, U.K. Members of Parliament will visit China for the first time since 2019, the Pentagon releases 162 secret UFO files, AI systems reportedly have self-replicated across servers, dozens are killed in deadly village attacks in Mali, U.S. imposes sanctions on the Cuban military conglomerate, a Virginia court strikes down a voter-approved redistricting map, a court rules that President Trump's 10% global tariff is unlawful, and Ireland is urged to boycott Israel UEFA fixtures. Sources: Verity.News
This week in search we covered more heated Google ranking volatility this morning, it seems big - so stay tuned. We also covered how Google spoke about how they try to isolate their AI systems because...
Dustin Fox joins The Broke Agent to discuss how to create a content pipeline with AI that actually works for real estate agents. He reveals the tools and prompts he uses to dominate his market and stay ahead of the tech curve.
In this episode of the Ardan Labs Podcast, Ale Kennedy talks with Nikunj Bajaj, co-founder of True Foundry, about his journey from India to Silicon Valley and his work building modern AI infrastructure. Nikunj shares insights from his time at Meta, where he worked on large-scale machine learning systems, and how those experiences shaped the foundation of True Foundry.The conversation explores the evolution of AI—from early machine learning systems to today's generative models—and the infrastructure required to support them. Nikunj also discusses leadership lessons, long-term thinking, and what it takes to build and scale an AI startup in a rapidly changing landscape.00:00 Introduction07:38 IIT and Early Academic Journey16:45 Internships and Career Decisions29:15 Research at UC Berkeley36:37 Entering the Workforce and AI Evolution40:16 Leadership Lessons from Meta46:42 Leaving Meta and Starting a Startup52:50 Building During the Pandemic01:00:44 Founding True Foundry01:06:31 Product Development and Early Challenges01:10:31 Evolution of AI Infrastructure01:13:35 Vision for True Foundry01:20:55 Reflections and Lessons LearnedConnect with Nikunj: LinkedIn: https://www.linkedin.com/in/nikunj-bajaj-10476824/Mentioned in this Episode:True Foundry: https://www.truefoundry.comWant more from Ardan Labs? You can learn Go, Kubernetes, Docker & more through our video training, live events, or through our blog!Online Courses : https://ardanlabs.com/education/ Live Events : https://www.ardanlabs.com/live-training-events/ Blog : https://www.ardanlabs.com/blog Github : https://github.com/ardanlabs
In this week's episode of Uncrewed Views, Matt Collins speaks with Matt Kling, VP and general manager of AI Systems at MatrixSpace. The two discuss how the Safer Skies Act has shaped demand for counter-UAS technology, why gaps still exist between what agencies need and what's being deployed, and how MatrixSpace is approaching the counter-UAS challenge as a radar-first, hardware-and-software hybrid company.
Welcome to the Wholesale Hotline Podcast Weekend Edition (Flipping Mastery Edition), where Jerry teaches how to master the art of house flipping, wholesaling, and new construction development.Show notes -- in this episode we'll cover:Straightforward, step-by-step training on making six and seven figures from real estate deals.Insider tactics for finding motivated sellers, analyzing deals, and raising private money.Learn how to flip houses virtually from anywhere—even with zero experience.Whether you're a beginner or scaling up, Jerry gives you the blueprint to build real wealth through real estate. Please give us a rating and let us know how we are doing!➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ ☎️ Welcome to Wholesale Hotline & Flipping Mastery Breakout! ☎️Jerry Norton went from digging holes for minimum wage in his mid 20's to becoming a millionaire by the age of 30. Today he's the nation's leading expert on flipping houses and has taught thousands of people how to live their dream lifestyle through real estate. **NOTE: To Download any of Jerry's FREE training, tools, or resources…Click on the link provided and enter your email. The download is automatically emailed to you. If you don't see it, check your junk/spam folder, in case your email provider put it there. If you still don't see it, contact our support at: support@flippingmastery.com or 888) 958-3028. ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
We are officially entering the "Multi-AI Era." Much like the multi-cloud times, organizations are no longer just using a single AI tool like Microsoft Copilot, they are building custom, agentic workflows using diverse third-party models and MCP servers . In this episode, Ashish sits down with Shawn Hays from Varonis to discuss why the security market has over-pivoted on AISPM (AI Security Posture Management) . Shawn spoke about how having visibility and an inventory of your AI models is a great start, but it fails to secure the enterprise if you lack the guardrails to actually stop an agent from going off the rails and exfiltrating data . Shawn breaks down the components of a robust AI security platform (like Varonis Atlas) and explains why data security is inseparable from AI security. He spoke about why AI agents will blindly "read whatever is on the teleprompter," meaning your AI is only as secure as the data access and identity controls surrounding it . Tune in to learn how to apply Zero Trust across the entire AI chain from the prompter to the cloud infrastructure Guest Socials - Shawn's Linkedin Podcast Twitter - @CloudSecPod If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-Cloud Security Podcast- Youtube- Cloud Security Newsletter If you are interested in AI Security, you can check out our sister podcast - AI Security PodcastQuestions asked:(00:00) Introduction(02:50) Shawn's Background: Microsoft, CMMC, and Varonis (03:50) The Biggest AI Security Challenges (Copilot to Agentic AI) (05:50) Third-Party AI Risk (Jira and Salesforce Agents) (08:40) The Connector Ecosystem Danger (Copilot + Salesforce) (11:50) 8 Distinct Areas of an AI Security Platform (Varonis Atlas) (14:00) Entering the "Multi-AI Era" (Analogies to Multi-Cloud) (16:00) The AI Bill of Materials (Athena AI & Grammarly) (20:50) Why Data Security and AI Security are Intertwined (22:00) Applying Zero Trust to the Entire AI Chain (24:50) The Role of Identity and ITDR in AI Systems (27:00) HIPAA, OCR, and Regulating AI Data Access (31:30) Creating a Governance Plan for Microsoft Copilot (33:50) Securing Pro-Code AI Systems (AWS Bedrock & MCP Servers) (38:30) Why the Security Market is Over-Pivoting on AISPM (44:10) The "Ron Burgundy" Analogy for AI Agents (45:50) Fun Questions: Crocodile & Caramel Tasting (47:20) The Ed Sheeran & Yelawolf Mixtape Connection (48:50) Hobbies & Pride: DJing Weddings and Playing Ice Hockey in Alabama (51:50) Favorite Food: Alabama White Sauce BBQ & Milo's BurgersResources spoken about during the episode:Varonis Atlas
In this episode of Tech Talks, Mahima Singh interviews Siddharth Singh, a published AI researcher, engineer and MS Computer Science Candidate at Stony Brook University. Siddharth shares insights on bridging research and engineering in real-world AI systems. He highlights the fundamental difference between researchers and engineers—where researchers focus on truth and rigor, engineers focus on building reliable systems under real-world constraints—and emphasizes the importance of combining both mindsets to create impactful AI solutions.Siddharth discusses how to identify meaningful research problems, design robust evaluation frameworks, and navigate the transition from research to production. He explains that real-world AI systems must account for constraints like latency, compute, and unpredictable environments, making system design—not just model performance—critical. He also highlights common failure modes in AI, including distribution shifts, metric misalignment, and human behavior adaptation.In this conversation, Siddharth shares practical guidance for working across research, engineering, and product roles. He explains how strong product managers manage uncertainty, translate business problems into precise technical questions, and avoid premature assumptions. He also advises students to build technical literacy, understand the gap between research and deployment, and develop the ability to frame clear, actionable problems. The discussion concludes with insights on experimentation, iteration, and the critical role of human judgment in building reliable AI systems.
How does AI influence ecommerce operational workflows?This is episode 6 of 7 in the The Real Impact of AI on Online Business Series. In this series, we are resetting our online production productivity by understanding how to operate our online businesses using AI so we can take advantage of the greatest technology transformation we have ever seen.This episode focuses on AI workflows for ecommerce stores.Ecommerce businesses require managing many operational tasks — from product research and listings to marketing, advertising, and customer support. In this episode, Case Lane explores how entrepreneurs can use AI-powered workflows to improve ecommerce productivity. Learn how AI tools help accelerate product research, product descriptions, marketing content, advertising optimization, customer support, and analytics. These systems allow entrepreneurs to launch products faster and build scalable online stores.Action Plan:Understand eCommerce Faster as an AI Systems for Productive Online StoresAction 1: AI Product ResearchAction 2: AI Product DescriptionsAction 3: AI Image and Design AssistanceAction 4: AI Marketing ContentAction 5: AI Advertising OptimizationAction 6: AI Customer SupportAction 7: AI Analytics and InsightsAction 8: AI Content CommerceTo have an enjoyable life in our global, advanced tech society, create value. To have the business, career, finances and lifestyle you desire, follow a proven path that has delivered in good times and bad. The path of entrepreneurship. And online entrepreneurship is the fast track for aspiring entrepreneurs.Learn the skills, access the resources and be inspired to live the life of your dreams right here on the Ready Entrepreneur podcastTo find more resources, strategies and ideas for aspiring entrepreneurs visit the Ready Entrepreneur website: https://www.readyentrepreneur.com/To download a free guide for Preparing to Become an Online Entrepreneur, click here: https://www.readyentrepreneur.com/start/You can get an exclusive discount on the ebook and audiobook version of Recast: The Aspiring Entrepreneur's Practical Guide to Getting Started with an Online Business click here: https://www.caselane.net/recastConnect with CaseFacebook: @readyentrepreneurHQ Instagram: @readyentrepreneur Twitter X: @caselaneworld Pinterest @caselane
Sara Gerke is an associate professor of law and at the European Union Center at the University of Illinois Urbana-Champaign. Stephen Morrissey, the interviewer, is the Executive Managing Editor of the Journal. S. Gerke, R.B. Parikh, and I.G. Cohen. Utah's Prescription-Renewal Pilot Program — Autonomous AI Managing Patient Care. N Engl J Med 2026;394:1561-1563.
In this episode of The Cybersecurity Defenders Podcast, we discuss some intel being shared in the LimaCharlie community.Intercept and control AI agent activity with Viberails by LimaCharlie: viberails.ioAPT41, a China-linked threat group is deploying a previously undetected backdoor targeting Linux based cloud workflows.Fancy bear, also known as APT28 or Forest Blizzard, is a Russian cyber espionage group believed to operate on behalf of the country's military intelligence services, the GRU. Trend Micro research here.Anthropic's Model Control Protocol widely used in agentic AI systems to connect AI agents with data sources, contains a design flaw that would enable large-scale supply chain attacks. Report here.There's a critical vulnerability in nginx-UI, a web-based management interface for Nginx servers, which is being actively exploited and could allow attackers to take full control affected systems.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.
President of the Ghana Union of Traders' Associations (GUTA), Clement Boateng, has dismissed reports suggesting that the association has suspended its ongoing strike
Hundreds of prominent AI scientists and other notable figures signed a statement in 2023 saying that mitigating the risk of extinction from AI should be a global priority. At 80,000 Hours, we've considered risks from AI to be the world's most pressing problem since 2016. But what led us to this conclusion? Could AI really cause human extinction? We're not certain, but we think the risk is worth taking very seriously. In particular, as companies create increasingly powerful AI systems, there's a concerning chance that:These AI systems may develop dangerous long-term goals we don't want.To pursue these goals, they may seek power and undermine the safeguards meant to contain them.They may even aim to disempower humanity and potentially cause our extinction.This article is written by Cody Fenwick and Zershaaneh Qureshi, and narrated by Zershaaneh Qureshi. It discusses why future AI systems could disempower humanity, what current AI research reveals about behaviours like power-seeking and deception, and how you can help mitigate the dangers.You can see the original article — packed with graphs, images, footnotes, and further resources — on the 80,000 Hours website: https://80000hours.org/problem-profiles/risks-from-power-seeking-ai/ Chapters:Risks from power-seeking AI systems (00:01:00)Introduction (00:01:17)Summary (00:03:09)Why are the risks from power-seeking AI a pressing world problem? (00:04:04)Section 1: Humans will likely build advanced AI systems with long-term goals (00:05:43)Section 2: AIs with long-term goals may be inclined to seek power (00:11:32)Section 3: These power-seeking AI systems could successfully disempower humanity (00:26:26)Section 4. People might create power-seeking AI systems without enough safeguards, despite the risks (00:38:34)Section 5: Work on this problem is neglected and tractable (00:47:37)Section 6: What are the arguments against working on this problem? (00:59:20)Section 7: How you can help (01:25:07)Thank you for listening (01:28:56)Audio editing: Dominic ArmstrongProduction: Zershaaneh Qureshi, Elizabeth Cox, and Katy Moore
Investor Fuel Real Estate Investing Mastermind - Audio Version
Drew Donaldson, founder of Automata Intelligentsia, shares insights on building effective automation systems for businesses, common pitfalls, and the future of AI-driven automation in sales, marketing, and operations. Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind: Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply Investor Machine Marketing Partnership: Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true 'white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com Coaching with Mike Hambright: Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a "mini-mastermind" with Mike and his private clients on an upcoming "Retreat", either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas "Big H Ranch"? Learn more here: http://www.investorfuel.com/retreat Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform! Register here: https://myinvestorinsurance.com/ New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club —--------------------
How does AI influence social media influencer content creation workflows?This is episode 5 of 7 in the The Real Impact of AI on Online Business Series. In this series, we are resetting our online production productivity by understanding how to operate our online businesses using AI so we can take advantage of the greatest technology transformation we have ever seen.This episode focuses on AI content creation for social media influencers. Social media platforms reward creators who publish consistently — but producing content every day can quickly become overwhelming. In this episode, Case explores how online entrepreneurs can use AI-powered workflows to accelerate social media content creation. Learn how AI tools help with idea generation, caption writing, video editing, content repurposing, trend analysis, and scheduling. These systems allow creators to produce more content, stay consistent, and grow their audiences faster.Action Plan:Understand Social Media Content Faster as an AI System for High-Output Content CreatorsAction 1: AI Content Idea GenerationAction 2: AI Content FrameworksAction 3: Content BatchingAction 4: AI Caption GenerationAction 5: AI Video Editing for Short ContentAction 6: AI RepurposingAction 7: AI Trend MonitoringAction 8: AI Scheduling and DistributionTo have an enjoyable life in our global, advanced tech society, create value. To have the business, career, finances and lifestyle you desire, follow a proven path that has delivered in good times and bad. The path of entrepreneurship. And online entrepreneurship is the fast track for aspiring entrepreneurs.Learn the skills, access the resources and be inspired to live the life of your dreams right here on the Ready Entrepreneur podcastTo find more resources, strategies and ideas for aspiring entrepreneurs visit the Ready Entrepreneur website: https://www.readyentrepreneur.com/To download a free guide for Preparing to Become an Online Entrepreneur, click here: https://www.readyentrepreneur.com/start/You can get an exclusive discount on the ebook and audiobook version of Recast: The Aspiring Entrepreneur's Practical Guide to Getting Started with an Online Business click here: https://www.caselane.net/recastConnect with CaseFacebook: @readyentrepreneurHQ Instagram: @readyentrepreneur Twitter X: @caselaneworld Pinterest @caselane
In this episode of "Business Growth Talks," host Mark Hayward sits down with Ken McLoud, an AI expert and founder of Laconic Tech, to delve into the real strategies and systems that harness AI for business growth. Ken, hailed as a secret weapon in AI, shares his insights into how businesses can truly leverage AI by addressing underlying problems rather than succumbing to the hype. His philosophy is not to ask what AI projects can be done, but instead, to identify constraints within a business and then apply the right AI tools to address these issues, resulting in significant reduction of labor costs and lead generation. Ken emphasizes the importance of problem-solving with AI, advocating for thoughtful implementation to supercharge teams rather than just automating tasks.Moving into practical strategies, Ken advises businesses on how to discern whether they are demand or supply constrained, and the steps needed to leverage AI in either scenario. He shares experiences from his own career transitions and client projects, showcasing AI's potential from manufacturing operations to enhancing lead generation. Ken also sheds light on the future of AI, its impact on industries, and strategic approaches to keep pace with evolving technologies. This episode offers a detailed roadmap for business owners looking to integrate or optimize AI, aligning with Ken's mantra to solve problems with these powerful tools and technologies.Key Takeaways:Identifying Business Constraints: Ken emphasizes understanding whether a business is demand or supply constrained to effectively utilize AI technologies.AI as a Supercharging Tool: Instead of replacing jobs, AI should enhance existing team capabilities, allowing for greater achievement with current resources.Strategic Use of AI: Businesses often misuse AI, trying to fit it into existing frameworks rather than addressing actual business needs.The Importance of Flexible AI Solutions: Avoid vendor lock-in by ensuring AI implementations are adaptable and can integrate the best tools available.Future-Proofing with AI: Maintaining awareness of AI advancements is critical, but focus on integration should remain centered on providing substantial ROI and solving business constraints.SPONSORSPodcast Introduction: podcastintroduction.comResources:Ken McLeod's Company: Laconic TechAI Resources Mentioned: OpenAI, Anthropic, Claude, and GeminiSocial Media Platforms: TwittSupport the showIf you want to watch the full video of this episode go to:https://www.youtube.com/@markhayward-BizGrowthTalksDo you want to be a guest on multiple podcasts as a service go to:www.podcastintroduction.comFind more details about the podcast and my coaching business on:www.businessgrowthtalks.comFind me onLinkedIn - https://www.linkedin.com/in/mark-hayw...Tik Tok - https://www.tiktok.com/@mjh169183YouTube Shorts - https://www.youtube.com/@markhayward-BizGrowthTalks/shorts
John is joined by Christopher D. Kercher, partner in Quinn Emanuel's New York office. They discuss a proprietary litigation intelligence system developed inside Quinn Emanuel — built from a practicing litigator's perspective and designed to give case teams a decisive advantage from day one.The system, known internally as a "kerchbench," works by taking a case team's documents, filings, and materials and distilling them into a structured knowledge base that mirrors how experienced litigators understand and manage cases — organized around the chronology of events, key actors, claims and defenses, and critical evidence. The result is an AI that already understands the case before anyone asks it a question, so every interaction starts from genuine case knowledge rather than from scratch.By progressively building out the system's understanding as a matter develops, the AI functions as a true thought partner rather than a passive tool. Lawyers can refine strategies, identify gaps in their knowledge, and surface non-obvious connections across the record. The system doesn't just answer questions about what is known — it serves as a thought partner, flagging what additional information the team may need and what the lawyer may be overlooking.One key innovation is the creation of structured workflows and reusable "skills" that break complex legal tasks into component steps — issue identification, organization, drafting, and refinement. These routines accelerate the production of high-quality work while preserving lawyer oversight at every stage. The system also supports early case assessment: a fast-turnaround engagement that synthesizes initial case materials into a structured snapshot of claims and defenses, key risks, and strategic priorities — giving partners a clear picture of a case within 48 hours.The result is a shift in legal work from labor-intensive context assembly toward higher-value analytical thinking. By providing relevant case information on demand and reducing the cognitive burden of tracking specific evidence across a large record, the system enhances both the speed and quality of legal reasoning. This is not merely an efficiency gain — it is a meaningful improvement in lawyers' ability to think, strategize, and advocate effectively in complex litigation.Podcast Link: Law-disrupted.fmHost: John B. Quinn Producer: Alexis HydeMusic and Editing by: Alexander Rossi
AI system design determines whether your solution succeeds in production or fails once it leaves a controlled environment. In this part of the conversation, Matt Soltau highlights a critical shift: building AI is no longer just about capability—it's about control, adaptability, and governance. About Matt Soltau Matt Soltau is the Global Director of Strategy & Operations at IntelliPaaS. He specializes in helping organizations untangle complex, legacy tech stacks so they can successfully implement secure, compliant, and scalable AI and automation solutions. With a strong focus on integration and real-world execution, Matt works with companies to turn fragmented data into reliable systems that actually support AI initiatives. AI System Design Must Balance Openness and Control Organizations today are under pressure to: integrate more systems adopt new tools move faster At the same time, they must: protect sensitive data comply with regulations maintain control over systems This creates what can best be described as "controlled openness." AI system design today requires openness at the edges and control at the core. Companies are becoming more integrated—but also more restrictive about how that integration happens. Security Is Built Into AI System Design One of the clearest points in the discussion is that security is not optional. It's foundational. Organizations are: enforcing stricter governance requiring auditability limiting access to data As Matt explains, companies are willing to say yes to innovation—but only if they can govern it. This shifts how systems must be built from the start. AI System Design Requires Thinking Ahead Another key takeaway is forward-thinking design. Teams can't just build for current requirements—they need to anticipate: regulatory changes compliance expectations evolving data usage For example, when dealing with sensitive data (like HR systems), teams must: anonymize data mask personal information track data movement This isn't a future concern—it's a present requirement. The Production Failure Problem One of the most valuable examples shared is a real-world failure. An AI system: worked perfectly in testing delivered strong results in a controlled environment But failed in production. Why? Because it wasn't connected to real-world changes: new regulations environmental factors shifting conditions AI system design must account for real-world variability—not just ideal conditions. Why Real-Time Data Matters in AI System Design The solution to that failure was integration. AI systems must: receive real-time data adapt to changing inputs evolve continuously Without this, they become static—and quickly outdated. This is where integration and AI intersect again: AI is only as dynamic as the data feeding it. Designing for Adaptability Strong AI system design includes: flexible architectures modular integrations continuous data flow This allows systems to: evolve with conditions handle new requirements remain relevant over time The best AI systems aren't static—they're constantly adapting. Conclusion AI system design is no longer about building something that works once. It's about building something that keeps working. Focus on: governance real-time data adaptability And your AI will survive beyond the demo. Stay Connected: Join the Developreneur Community
How does AI change digital course creation workflows for online entrepreneurs?This is episode 4 of 7 in the The Real Impact of AI on Online Business Series. In this series, we are resetting our online production productivity by understanding how to operate our online businesses using AI so we can take advantage of the greatest technology transformation we have ever seen.This episode focuses on digital course creation. Digital courses are one of the most scalable online business models — but course creation can be a slow and overwhelming process. In this episode, Case explores how entrepreneurs can use AI-powered tools to accelerate course curriculum design, lesson development, slide creation, video production, marketing content, and student support.Learn how today's course creation systems allow entrepreneurs to launch educational products faster and build scalable knowledge businesses.Action Plan:Understand Digital Course Creation Faster as an AI Systems for Scalable EducationAction 1: AI Curriculum DesignAction 2: AI Lesson DevelopmentAction 3: AI Slide CreationAction 4: Efficient Video RecordingAction 5: AI Video EditingAction 6: AI Course MaterialsAction 7: AI Marketing ContentAction 8: AI Student SupportTo have an enjoyable life in our global, advanced tech society, create value. To have the business, career, finances and lifestyle you desire, follow a proven path that has delivered in good times and bad. The path of entrepreneurship. And online entrepreneurship is the fast track for aspiring entrepreneurs.Learn the skills, access the resources and be inspired to live the life of your dreams right here on the Ready Entrepreneur podcastTo find more resources, strategies and ideas for aspiring entrepreneurs visit the Ready Entrepreneur website: https://www.readyentrepreneur.com/To download a free guide for Preparing to Become an Online Entrepreneur, click here: https://www.readyentrepreneur.com/start/You can get an exclusive discount on the ebook and audiobook version of Recast: The Aspiring Entrepreneur's Practical Guide to Getting Started with an Online Business click here: https://www.caselane.net/recastConnect with CaseFacebook: @readyentrepreneurHQ Instagram: @readyentrepreneur Twitter X: @caselaneworld Pinterest @caselane
Are we letting technology shape our lives, or are we actively choosing how it fits in? Dive into an essential conversation about techno-chauvinism, AI's real-world impacts, and what responsible innovation looks like with Meredith Broussard. Topics Covered: The difference between technological and social decisions The AI hype cycle and shifting perceptions of AI Techno chauvinism and using the right tool for the task The limits of technology in daily life and digital detox trends Hollywood's influence on how we imagine AI Generative AI: how it works, dataset concerns, and hallucinations Unshedification and the realities of deploying generative AI The challenges of responsible AI and data governance Environmental impacts of data centers and generative AI Accountability and diffused responsibility in tech What “better” looks like for technology and society Connect with Meredith BroussardWebsiteLinkedIn Meredith's book: ”More than a Glitch – Confronting Race, Gender, and Ability Bias in Tech” Episode Chapters: [00:00:04] Introduction to the Tech Humanist Show[00:00:30] Guest Introduction: Meredith Broussard[00:01:22] Stories We Tell Ourselves about AI[00:03:50] Biases Embedded in Technology & Techno Chauvinism[00:05:27] The Digital Shift and the Rise of Tech Dependency[00:08:48] Bans, Restrictions, and Nuanced AI Policy[00:10:44] AI Misconceptions vs. Hollywood Influences[00:14:14] Explaining Generative AI in Plain Language[00:17:37] Decision Making and the Fragility of AI Systems[00:20:11] The Realities of Generative AI in the Workplace[00:23:26] Responsible AI and Governance[00:29:03] Longevity and Constant Change in AI Models[00:31:25] AI Safeguards and Global Concerns[00:33:00] Accountability in Distributed Technology[00:34:43] Environmental Impact of Data Centers[00:38:49] What “Better” Looks Like for Tech & Society[00:41:21] Where to Connect with Meredith Broussard[00:41:40] Closing and Credits
What happens when AI governance is no longer just about limiting risk, but about enabling trust, experimentation, and value realization at scale? Our guests for this episode explore how governance must evolve to meet the realities of agentic systems, hybrid workforces, and the challenges leaders face in this transformative era. Featured experts Dr. Ashwin Mehta, Founder and CEO, Mehtadology Dr. Diana Wolfe, Vice President and Head of AI Research & Strategy, Kyndryl
How does AI change YouTube video creator workflows for online entrepreneurs?This is episode 3 of 7 in the The Real Impact of AI on Online Business Series. In this series, we are resetting our online production productivity by understanding how to operate our online businesses using AI so we can take advantage of the greatest technology transformation we have ever seen.This episode focuses on YouTube video creation. YouTube is one of the most powerful platforms for entrepreneurs — but traditional video production workflows can slow creators down. In this episode, Case explores how AI-powered tools can dramatically improve YouTube productivity. Learn how entrepreneurs are using AI to accelerate video research, scripting, editing, thumbnail creation, SEO optimization, and distribution. If you're building an online brand, these production systems can help you publish more videos, reach more audiences, and grow your channel faster.Action Plan:Understand YouTube Faster as an AI Systems Accelerator for Video CreationAction 1: AI Topic Discovery for YouTubeAction 2: AI-Assisted ResearchAction 3: AI Video Script GenerationAction 4: Efficient Recording SystemsAction 5: AI Video EditingAction 6: AI Thumbnail CreationAction 7: AI SEO OptimizationAction 8: AI Clip GenerationAction 9: AI DistributionTo have an enjoyable life in our global, advanced tech society, create value. To have the business, career, finances and lifestyle you desire, follow a proven path that has delivered in good times and bad. The path of entrepreneurship. And online entrepreneurship is the fast track for aspiring entrepreneurs.Learn the skills, access the resources and be inspired to live the life of your dreams right here on the Ready Entrepreneur podcastTo find more resources, strategies and ideas for aspiring entrepreneurs visit the Ready Entrepreneur website: https://www.readyentrepreneur.com/To download a free guide for Preparing to Become an Online Entrepreneur, click here: https://www.readyentrepreneur.com/start/You can get an exclusive discount on the ebook and audiobook version of Recast: The Aspiring Entrepreneur's Practical Guide to Getting Started with an Online Business click here: https://www.caselane.net/recastConnect with CaseFacebook: @readyentrepreneurHQ Instagram: @readyentrepreneur Twitter X: @caselaneworld Pinterest @caselane
In this sponsored Soap Box edition of the show, Patrick Gray and James Wilson talk about red teaming AI systems with Russel Van Tuyl, Vice President of Services at elite penetration testing firm SpecterOps. SpecterOps is the company behind attack path enumeration tool Bloodhound and Bloodhound Enterprise, but they're also a pentest and red teaming shop with world class expertise in popping shells on all sorts of interesting systems in all sorts of interesting places. This episode is also available on Youtube. Show notes
How does AI change podcasting workflows for online entrepreneurs?This is episode 2 of 7 in the The Real Impact of AI on Online Business Series. In this series, we are resetting our online production productivity by understanding how to operate our online businesses using AI so we can take advantage of the greatest technology transformation we have ever seen.This episode focuses on podcasting AI workflows.Podcasting builds trust with an audience, but traditional podcast production can be slow and time-consuming.In this episode, Case explores how entrepreneurs can use AI-powered workflows to accelerate podcast creation, editing, transcription, clip generation, and distribution. Learn how modern podcast production systems allow creators to produce more episodes, repurpose content efficiently, and grow their audience faster.Action Plan:Understand Podcasting Faster as a Strategic AdvantageAction 1: AI-Assisted Topic PlanningAction 2: AI Research for Episode PreparationAction 3: AI-Generated Episode OutlinesAction 4: Recording Systems That Reduce FrictionAction 5: AI-Powered Audio EditingAction 6: AI Transcription and Show NotesAction 7: AI Clip CreationAction 8: AI Distribution WorkflowsTo have an enjoyable life in our global, advanced tech society, create value. To have the business, career, finances and lifestyle you desire, follow a proven path that has delivered in good times and bad. The path of entrepreneurship. And online entrepreneurship is the fast track for aspiring entrepreneurs.Learn the skills, access the resources and be inspired to live the life of your dreams right here on the Ready Entrepreneur podcast.To find more resources, strategies and ideas for aspiring entrepreneurs visit the Ready Entrepreneur website: https://www.readyentrepreneur.com/To download a free guide for Preparing to Become an Online Entrepreneur, click here: https://www.readyentrepreneur.com/start/You can get an exclusive discount on the ebook and audiobook version of Recast: The Aspiring Entrepreneur's Practical Guide to Getting Started with an Online Business click here: https://www.caselane.net/recastConnect with CaseFacebook: @readyentrepreneurHQ Instagram: @readyentrepreneur X: @caselaneworldPinterest @caselane
In this episode of the Niche Pursuits podcast, Jared sits down with Corey Ganim to break down AI automation that drives results, starting with a simple ROI filter: effectiveness, efficiency, and customer experience. Corey shares his AOA sequence (Audit, Optimize, Automate) so you stop automating messy 12-step processes and start building repeatable systems with AI. You'll hear the difference between AI agents and reusable skills and "speed to lead" replies. Walk away with three clear takeaways: how to choose the right workflows to automate, how to simplify them before automating, and how to build repeatable AI skills you can reuse across your business. Sponsor: Quiet LightGet a free, confidential valuation at https://quietlight.com/! Links & ResourcesTake the quiz to get your free AI action plan: https://returnmytime.com/quiz Learn more about Return My Time: https://returnmytime.com/ Connect with Corey: https://x.com/coreyganim Be sure to get more content like this in the Niche Pursuits Newsletter Right Here: https://www.nichepursuits.com/newsletter Want a Faster and Easier Way to Build Internal Links? Get $15 off Link Whisper with Discount Code "Podcast" on the Checkout Screen: https://www.nichepursuits.com/linkwhisper Get SEO Consulting from the Niche Pursuits Podcast Host, Jared Bauman: https://www.nichepursuits.com/201creative
What does it actually look like when a top-producing loan officer stops dabbling with AI and fully embeds it into every layer of his mortgage business? In this episode of Mortgage Marketing Radio, guest host Katie Shive sits down with Abdel Khawatmi — Area Manager and founder of Got Mortgages with PRMG — to break down the exact system behind 121 units, $40M in personal production, and 210% net revenue growth year over year. This is not a conversation about generating social media captions with ChatGPT. This is a ground-level look at how a working originator rebuilt his operations, client experience, and team structure around AI — and what that means for every loan officer trying to compete right now. What you'll learn: Why Abdel cut his offshore team from 7 to 3 — and what AI does instead How he uses ChatGPT to calculate Schedule C & E income, build SOPs, and draft compliant letters of explanation Why he's on the phone with clients MORE since implementing AI — not less The hyperlocal event strategy that his referral partners can't stop talking about His ROI framework: Relevance, Omnipresence & Intimacy The 4-step client experience model that keeps his pipeline full without him being the first touch The one thing he tells every loan officer who asks, "where do I start?" If you are a loan officer grinding in a tough market and wondering how to build a smarter, leaner, more profitable business — this is the episode you have been waiting for. Connect with Abdel on LinkedIn https://www.linkedin.com/in/abdel-khawatmi-79a511144/ Connect with Abdel on Instagram: https://www.instagram.com/got_mortgages/ Connect with Katie Shive on LinkedIn: https://www.linkedin.com/in/katieshive/
How do global companies make confident decisions when supply chains are constantly disrupted by tariffs, geopolitical tension, shifting consumer demand, and unpredictable global events? In this episode of Tech Talks Daily, I sat down with Dr. Ashwin Rao, EVP of AI and R&D at o9 Solutions, to talk about how artificial intelligence is changing the way organizations plan, forecast, and respond to uncertainty. Ashwin brings a fascinating mix of experience to the conversation. After earning a PhD in mathematics and computer science, he spent fifteen years on Wall Street working on derivatives trading strategies at Goldman Sachs and Morgan Stanley before moving into the world of enterprise technology. Today, he operates at the meeting point between business and academia as both a senior AI leader and an adjunct professor at Stanford University. Our conversation begins with Ashwin's unusual career path and how those early experiences in finance shaped the way he thinks about risk, decision making, and real world AI deployment. The journey from theoretical mathematics to trading floors and eventually into Silicon Valley offers an interesting lens on how analytical thinking can travel across industries and still remain highly relevant. We then move into the work happening at o9 Solutions, where AI is helping organizations make smarter decisions across supply chain planning, demand forecasting, and inventory management. In a world that Ashwin describes using the acronym VUCA, volatility, uncertainty, complexity, and ambiguity, businesses are under pressure to react faster and make better informed decisions. He explains how enterprise AI platforms can connect fragmented data across departments and create a more complete view of the business. One example he shares brings the concept down to earth. Even predicting how many bananas a grocery store should stock on any given day requires analyzing internal sales trends alongside external signals such as weather, social media trends, and economic conditions. Machine learning systems can now process those signals in real time and continuously update forecasts so businesses can respond quickly to changes. We also explore the rise of neuro- and symbolic AI, a concept Ashwin believes represents the next stage in enterprise decision-making. Rather than relying only on large language models, this approach blends the structured reasoning of symbolic systems with the pattern recognition of neural networks. The result, he suggests, feels less like a chatbot and more like having an expert coach embedded inside the decision-making process. Along the way, we also discuss why many organizations still struggle to embed AI successfully. Technology is only one piece of the puzzle. Ashwin believes the toughest obstacle is organizational change management, bringing teams together, connecting data across silos, and helping leaders guide their organizations through transformation. If you have ever wondered how AI moves beyond chatbots and into the systems that quietly power global supply chains, this conversation offers a thoughtful and practical perspective. So, how prepared is your organization to make decisions in a world defined by volatility and uncertainty, and could AI become the trusted partner that helps guide those choices? Useful Links Ashwin's blog Ashwin's LinkedIn o9 Solutions Website o9 LinkedIn
A Note from James:In the last episode, we talked about whether Martin Shkreli really deserves the label “most hated man in America.” My conclusion was no, and I hope you came to the same conclusion after hearing his perspective.In this episode, we shift gears completely. We talk about Bitcoin, crypto, AI, energy, optical computing, and what the future of technology might actually look like.Martin has a very unusual combination of skills—finance, biotech, programming—and I always enjoy hearing how he connects ideas across different fields. That's what this conversation is about.Episode Description:What happens when AI demand collides with the limits of computing power and energy?In Part 2, Martin Shkreli and James explore the future of technology—from crypto vulnerabilities to optical computing, GPU scaling, and the potential energy crisis driven by artificial intelligence.They discuss whether Bitcoin can survive quantum computing, why stablecoins solve real-world financial problems, and how computing architecture may shift beyond traditional silicon chips. The conversation then moves into AI economics: why companies might spend billions on compute to make better decisions, how energy constraints could shape innovation, and why optical computing could become the next major breakthrough.This episode isn't about controversy—it's about technological leverage, incentives, and where computation is heading next.What You'll Learn:Why quantum computing could eventually threaten Bitcoin's encryptionThe real-world advantages of stablecoins and decentralized paymentsHow AI demand could create massive new energy constraintsWhy optical (photonic) computing may outperform traditional silicon chipsHow businesses might use large-scale AI compute for strategic decisionsTimestamped Chapters:[00:02:00] Bitcoin, Encryption & Quantum Computing Risks[00:03:02] A Note from James[00:03:34] Crypto Markets: Speculation vs. Utility[00:05:23] Banking Control, Debanking & Stablecoins[00:07:40] Moore's Law, Huang's Law & The Limits of Silicon[00:08:45] Optical Computing Explained[00:09:12] NVIDIA, Parallelization & Power Consumption[00:10:24] Energy Constraints & The Electrical Grid[00:11:41] AI Energy Demand vs. Countries[00:12:24] Corporate AI Decision-Making at Scale[00:13:37] The Coming Explosion of AI Compute[00:14:20] Energy Efficiency vs. Speed[00:15:17] GPU Efficiency Improvements & Jevons Paradox[00:17:00] Why AI Is Different from Traditional Computing[00:17:47] Optical vs. Quantum vs. DNA Computing[00:18:19] Why Optical Computing Fits AI Perfectly[00:19:28] Precision, Bits & Neural Networks[00:21:24] Error Tolerance in AI Systems[00:22:00] Fiber Optics & Existing Infrastructure[00:23:16] New Computing Paradigms Beyond Silicon[00:24:00] Matrix Multiplication & AI Workloads[00:24:53] Closing ThoughtsSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Enterprise IT systems have grown into sprawling, highly distributed environments spanning cloud infrastructure, applications, data platforms, and increasingly AI-driven workloads. Observability tools have made it easier to collect metrics, logs, and traces, but understanding why systems fail and responding quickly remains a persistent challenge. As complexity continues to rise, the industry is looking beyond dashboards The post Engineering AI Systems for Autonomy and Resilience with Krishna Sai appeared first on Software Engineering Daily.
© 2020-2026 Ivy Podcast Discovery LLC
