Podcasts about google gemini

In this episode of the Research Like a Pro Genealogy podcast, hosts Diana and Nicole discuss the features and effectiveness of FamilySearch's new "Simple Search" tool. They explore how this experiment allows users to search billions of full-text records using natural language queries rather than traditional forms. Diana shares her experience testing the tool with her father's name, Bobby Gene Shults, demonstrating how the artificial intelligence parses results and helps distinguish between individuals with similar names. Listeners learn practical strategies for using Simple Search effectively, such as starting with broad queries and utilizing filters for collection, year, place, and record type to narrow results. Diana highlights the utility of the tool by successfully locating military muster rolls that confirm her father's service history and hospitalization during World War II. By experimenting with different search terms, spelling variations, and searching for associates, researchers can better leverage this technology to discover new documents for their family history. This summary was generated by Google Gemini. Links FamilySearch Labs / Experiments - https://www.familysearch.org/en/labs/ Tips for Using the New FamilySearch Simple Search Tool - https://familylocket.com/tips-for-using-the-new-familysearch-simple-search-tool/ Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Diana and Nicole discuss how genealogists use artificial intelligence to transcribe handwritten, foreign-language historical documents. They review feedback from a survey regarding experiences with various AI tools, including Transkribus, Gemini, ChatGPT, Claude, and Leo. The researchers report positive experiences, with average accuracy ratings between 7.5 and 8 out of 10. Listeners learn which languages, such as Spanish, German, French, Latin, and Scandinavian, are commonly processed through these tools. The discussion highlights that while AI excels at speed, it frequently struggles with proper names, obscure place names, and table-based data. The hosts share field-tested strategies for successful transcription. Listeners learn to provide extensive context in their prompts, work in small segments, and perform a manual "rough read" before utilizing AI. Diana and Nicole emphasize the importance of acquiring basic language skills to spot errors, especially when dealing with subtle, plausible hallucinations from large language models. They conclude that AI serves as a powerful assistant but caution that it cannot replace the researcher's own skill and judgment. This summary was generated by Google Gemini. Links What Genealogists Are Saying About AI Transcription of Foreign-Language Documents – Family Locket - https://familylocket.com/what-genealogists-are-saying-about-ai-transcription-of-foreign-language-documents/ Survey - https://docs.google.com/forms/d/e/1FAIpQLSfZev1baLVTzKZ0skumxp5syTMAmCMeQkvda4YhLMmYPmOaVg/viewform?usp=sharing  Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Partenaires il y a 18 mois, Apple et OpenAI se retrouvent aujourd'hui devant un tribunal fédéral pour vol de secrets industriels. Plus de 400 ingénieurs auraient quitté Apple avec des fichiers confidentiels et un playbook d'espionnage organisé de l'intérieur — la bataille pour le device du futur a déjà commencé !Pendant ce temps, Elon Musk redistribue les cartes : Grok rejoint les modèles frontières à un prix trois fois inférieur à ses rivaux, Google décroche, et Musk devient le seul acteur à tenir simultanément la puissance de calcul, le modèle et la distribution. Et en Chine, un booster orbital vient d'être récupéré dans un filet en pleine mer — la course à l'orbite basse, ressource limitée, vient d'entrer dans une nouvelle dimension.==================

Hi, I'm Connor with Honor - message me here!A huge percentage of Americans are carrying a quiet fear that AI is coming for their livelihoods. The fear is valid. The advice being sold to you is garbage, designed to profit off your panic instead of preparing you for what's actually coming.In this episode of AI With Honor: The Daily Download, Connor MacIvor strips away the PR spin and walks you through who is really pulling the levers, and why the smartest move you can make is to stop scrolling in fear and start watching the mechanisms hiding in plain sight.Listen in for:The Google Gemini stumble that dropped a trillion-dollar stock 4% in a day, and why that headline is a discount sign for the people running the game.China's keynote in Shanghai, 29 countries, and a proposed global AI rulebook that lands on your kitchen table whether you know it or not.The quiet terms-of-service switch letting Big Tech scrape every photo you've ever posted to train its models, turned on by default.The three-edged blade of AI in the workforce: adapt or get replaced, use the tools and train your own replacement, or grasp the third edge that changes everything.Why judgment, empathy, accountability, and grit are the human traits no machine can fake, and why rarity equals value.The safety theater of billionaires begging to be regulated, and the real reason they want that moat.The empowering truth: the same tools consolidating corporate power cost twenty dollars a month or are free. The stadium is still empty.AI for everyone. Not just the wealthy.Watch the video version on YouTube: https://youtu.be/qZ1nJqT0mJYYoutube Channels:Conner with Honor - real estateHome Muscle - fat torchingFrom first responder to real estate expert, Connor with Honor brings honesty and integrity to your Santa Clarita home buying or selling journey. Subscribe to my YouTube channel for valuable tips, local market trends, and a glimpse into the Santa Clarita lifestyle.Dive into Real Estate with Connor with Honor:Santa Clarita's Trusted Realtor & Fitness EnthusiastReal Estate:Buying or selling in Santa Clarita? Connor with Honor, your local expert with over 2 decades of experience, guides you seamlessly through the process. Subscribe to his YouTube channel for insider market updates, expert advice, and a peek into the vibrant Santa Clarita lifestyle.Fitness:Ready to unlock your fitness potential? Join Connor's YouTube journey for inspiring workouts, healthy recipes, and motivational tips. Remember, a strong body fuels a strong mind and a successful life!Podcast:Dig deeper with Connor's podcast! Hear insightful interviews with industry experts, inspiring success stories, and targeted real estate advice specific to Santa Clarita.

Hi, I'm Connor with Honor - message me here!A huge percentage of Americans are carrying a quiet fear that AI is coming for their livelihoods. The fear is valid. The advice being sold to you is garbage, designed to profit off your panic instead of preparing you for what's actually coming.In this episode of AI With Honor: The Daily Download, Connor MacIvor strips away the PR spin and walks you through who is really pulling the levers, and why the smartest move you can make is to stop scrolling in fear and start watching the mechanisms hiding in plain sight.Listen in for:The Google Gemini stumble that dropped a trillion-dollar stock 4% in a day, and why that headline is a discount sign for the people running the game.China's keynote in Shanghai, 29 countries, and a proposed global AI rulebook that lands on your kitchen table whether you know it or not.The quiet terms-of-service switch letting Big Tech scrape every photo you've ever posted to train its models, turned on by default.The three-edged blade of AI in the workforce: adapt or get replaced, use the tools and train your own replacement, or grasp the third edge that changes everything.Why judgment, empathy, accountability, and grit are the human traits no machine can fake, and why rarity equals value.The safety theater of billionaires begging to be regulated, and the real reason they want that moat.The empowering truth: the same tools consolidating corporate power cost twenty dollars a month or are free. The stadium is still empty.AI for everyone. Not just the wealthy.Watch the video version on YouTube: https://youtu.be/qZ1nJqT0mJYYoutube Channels:Conner with Honor - real estateHome Muscle - fat torchingFrom first responder to real estate expert, Connor with Honor brings honesty and integrity to your Santa Clarita home buying or selling journey. Subscribe to my YouTube channel for valuable tips, local market trends, and a glimpse into the Santa Clarita lifestyle.Dive into Real Estate with Connor with Honor:Santa Clarita's Trusted Realtor & Fitness EnthusiastReal Estate:Buying or selling in Santa Clarita? Connor with Honor, your local expert with over 2 decades of experience, guides you seamlessly through the process. Subscribe to his YouTube channel for insider market updates, expert advice, and a peek into the vibrant Santa Clarita lifestyle.Fitness:Ready to unlock your fitness potential? Join Connor's YouTube journey for inspiring workouts, healthy recipes, and motivational tips. Remember, a strong body fuels a strong mind and a successful life!Podcast:Dig deeper with Connor's podcast! Hear insightful interviews with industry experts, inspiring success stories, and targeted real estate advice specific to Santa Clarita.

Is Kimi K3 the shocker of 2026? Could be. Now, we have a new (soon to be) Open Model that's competing with Fable 5 and GPT-5.6, a feat few would have believed possible. And that was the only new and important drop this week in AI. Claude brought useful browser to the desktop, ChatGPT made a big fix to how ChatGPT Work works and Google rolled out avatars that could change content creation. Don't miss our Friday Features show, where we recap the most important AI updates and features you can use today. Claude Desktop Gets Upgrade, New Open Source Model Shocks, ChatGPT Desktop Gets Better and 7 More AI Features You Can Use Today -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Anthropic Claude Desktop App Browser UpgradeOpenAI ChatGPT Work Desktop App ImprovementsChatGPT Universal Search Feature LaunchSuperhuman Email Auto-Draft with GPT-4Spotify AI Voice/Text Conversation FeatureGemini Omni Personal Avatar Video CreationGoogle Vids Integration with Personal AvatarsMoonshot Kimmy K3 Open Source Model ReleaseKimmy K3 vs Fable 5 and GPT-5.6 BenchmarksTimestamps:00:00 New open source AI model release03:41 Microsoft Copilot and Claude app updates07:22 Improving chat history search12:30 Spotify's data personalization benefits14:52 Launching Google Avatar Feature18:24 Mainstream avatar video tools21:33 Improved ChatGPT project syncing24:15 Introducing Kimmy K Three Model29:30 New Kimmy k three for enterprises30:45 Friday feature show wrap-upKeywords: Claude desktop, Claude desktop upgrade, open source AI model, proprietary AI, open vs closed AI, Anthropic, built-in browser, Claude app, API docs, browser integration, permissions card, security layers, ChatGPT desktop app, OpenAI, universal search, ChatGPT search, chat history, project sync, mobile AI apps, Codex, ChatGPT work, Codex mode, Superhuman mail, auto draft, Anthropic Frontier models, GPT-3.5, Gmail integration, Outlook integration, Spotify, Talk to Spotify, personalized AI conversation, Gemini Omni, Google Gemini, personal avatars, Google Vids, video editing AI, video avatars, L&D AI, content creation with AI, Kimi k3, Moonshot AI, 2.8 trillion parameter model, 1 million token context, vision mode, benchmark leaderboards, Fable 5, GPT 5.6, Opus 4.8, open model weights, self-host AI, enterprise AI solutions, long context AI, front-end design AI, subscription AI tools, API pricing, AI benchmark, arena rankingsSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

Hi, I'm Connor with Honor - message me here!The last 10 days dropped more AI news than most industries see in a year. Listen as I break it all down in plain English for regular people, not tech billionaires. Both sides of every story, the truth in the middle, and where each one goes 1 month, 6 months, 1 year, and 5 years out. Recorded Friday, July 17, 2026, from Santa Clarita, California. I am Connor MacIvor. I do not just talk about AI. I deploy it every day in real businesses: real estate, voice AI, and software. Every story here is translated to what it means for your life, your job, and your family. In this episode:- The model flood: GPT 5.6, Google Gemini 3.5 Pro, xAI Grok 4.5, and Anthropic Claude Sonnet 5, plus what tokens and context windows really mean.- OpenAI's offer to hand the US government a 5 percent stake worth around $42 billion.- The jobs number: 87,714 cuts blamed on AI in 5 months, and the truth underneath it.- The $725 billion question: real buildout, or a bubble built on circular deals?- The agents are here, and most of them are wide open to attack.- OpenAI's first hardware: a screenless, moving ChatGPT speaker built with Jony Ive.- The hidden cost: why the AI boom could land on your power bill. Watch the video version on YouTube: https://youtu.be/xTqNpcM1btI WORK WITH ME:Put AI to work in your business: https://connorwithhonor.comAI for the rest of us: https://connorwithhonorai.comSell your SCV home, one $17,000 all-in fixed fee: https://sellersonlyagent.comSCV homes and open houses: https://santaclaritaopenhouses.comVoice AI for your phones, HireAIVoice: https://hireaivoice.comThe platform I run on, HonorElevate: https://honorelevate.comBeat food addiction: https://thelastaddiction.com Connor MacIvor, licensed California Realtor, DRE #01238257. For information only, not legal, financial, or tax advice. Santa Clarita | SCV | Los Angeles | Southern California#DailyDownload #AIWithHonor #SeventeenKYoutube Channels:Conner with Honor - real estateHome Muscle - fat torchingFrom first responder to real estate expert, Connor with Honor brings honesty and integrity to your Santa Clarita home buying or selling journey. Subscribe to my YouTube channel for valuable tips, local market trends, and a glimpse into the Santa Clarita lifestyle.Dive into Real Estate with Connor with Honor:Santa Clarita's Trusted Realtor & Fitness EnthusiastReal Estate:Buying or selling in Santa Clarita? Connor with Honor, your local expert with over 2 decades of experience, guides you seamlessly through the process. Subscribe to his YouTube channel for insider market updates, expert advice, and a peek into the vibrant Santa Clarita lifestyle.Fitness:Ready to unlock your fitness potential? Join Connor's YouTube journey for inspiring workouts, healthy recipes, and motivational tips. Remember, a strong body fuels a strong mind and a successful life!Podcast:Dig deeper with Connor's podcast! Hear insightful interviews with industry experts, inspiring success stories, and targeted real estate advice specific to Santa Clarita.

- 650 New Models Already Hit China This Year - China Could Restrict Rare Earth Exports - Investors Bet Against Manufacturing Stocks - Hyundai Wants Full Ownership of Boston Dynamics - Mercedes and Hyundai Dealers to Sell Humanoids - Honda Adds Google Gemini - Bigger Lexus ES Replacing Flagship LS - Rivian Reduces Complexity with New R2 - Geely Drive Unit Has Best Efficiency

- 650 New Models Already Hit China This Year - China Could Restrict Rare Earth Exports - Investors Bet Against Manufacturing Stocks - Hyundai Wants Full Ownership of Boston Dynamics - Mercedes and Hyundai Dealers to Sell Humanoids - Honda Adds Google Gemini - Bigger Lexus ES Replacing Flagship LS - Rivian Reduces Complexity with New R2 - Geely Drive Unit Has Best Efficiency

0:07 - Podcast Introduction 2:11 - Superstitious Fan Talk 4:30 - Betting on Argentina 8:38 - Biggest moments discussed 10:39 - Intense soccer fans 15:00 - Madden gameplay discussion 17:00 - Conor McGregor injury 22:33 - Hard season recap 25:07 - Receiver needs analysis 30:27 - Josh Allen importance 32:40 - Jimbo Cook nickname 39:59 - Game number two 44:22 - Team complete! 46:55 - Final player selection 51:34 - Episode wrap-up   In this episode of the Respect the Game (RTG) podcast, the two co-hosts discuss a variety of sports topics, focusing heavily on recent soccer tournaments and NFL offseason news, before playing a team-building mini-game. Soccer, Superstitions, and Sports Betting The podcast kicks off with one of the hosts sharing a story about a series of unfortunate events, including a broken air conditioning unit, which led him to miss recording the podcast during the Copa America tournament. The "Time Traveler" Bet: The host shares a story about a Twitter user who claimed to be a time traveler and predicted the exact outcome of a soccer match in 2021. Following this prediction, the host made a live parlay bet during the Copa America final (Argentina vs. Colombia) and won, despite some initial confusion over official stats regarding Erling Haaland's shots on goal. Soccer Fandom: The hosts discuss the immense passion of soccer fans, comparing the intensity of the crowds at the Copa America final at Hard Rock Stadium to NFL games, noting that soccer fans seem much more die-hard. NFL Offseason Discussion The conversation then shifts to American football and the upcoming NFL season. Daniel Jones and the Giants: The hosts briefly discuss the New York Giants and express skepticism about quarterback Daniel Jones's ability to lead the team to a successful season. Buffalo Bills' Receivers: They analyze the Buffalo Bills' current roster, specifically their lack of a true number-one wide receiver after trading Stefon Diggs. They debate whether rookie Keon Coleman or Curtis Samuel can fill the void and discuss how Josh Allen elevates the players around him. Miami Dolphins: The hosts touch upon the Dolphins' roster, noting that they have a strong receiving corps but questioning their overall depth. First Down Studio: Team Building Games In the final segment of the podcast, the hosts share their screen and play a team-building game on a website called First Down Studio. Game 1: Build a 17-0 Team The goal is to build an undefeated team by selecting one player from a randomly generated NFL team for each position. Their Draft: They selected Lamar Jackson (QB), Saquon Barkley (RB), CeeDee Lamb (WR), Tyler Warren (TE), a Flex player, the Seattle Seahawks Defense, and Jim Harbaugh (Coach). Result: The game calculated their team's simulated record as 16-1, which they considered a very strong outcome. Game 2: Build the GOAT Team The objective of this game is to build a team that generates the highest possible fantasy points based on the players' best single-season performances. They played this game twice. Attempt 1: They drafted Joe Burrow, LaDainian Tomlinson, Emmitt Smith, Keyshawn Johnson, Jimmy Graham, and Christian McCaffrey. This team scored 2,574.8 points, earning a "B+" grade. Attempt 2: Seeking a higher score, they drafted Peyton Manning, Curtis Martin, Saquon Barkley, Randy Moss, Antonio Brown, Rob Gronkowski, and Jamaal Anderson. Despite feeling confident, this team scored lower, with 2,469.2 points, earning a "B" grade. The episode concludes with the hosts briefly discussing mobile AI assistants (Siri vs. Google Gemini) and looking forward to the start of NFL training camps.

Google moet de zoekgegevens van zijn gebruikers gaan delen met concurrerende zoekmachines en AI-ontwikkelaars zoals OpenAI van de Europese Commissie. Doet het bedrijf dat niet, dan schendt het de Digital Markets Act. Niels Kooloos vertelt erover in deze Tech Update. De Digital Markets Act verplicht een bepaald aantal techbedrijven in Europa om een gelijk speelveld te behouden met hun platformen. Ook Google moet dat, met onder andere de zoekmachine. Als Google geen zoekgegevens van gebruikers deelt met de concurrentie, dan zou die volgens de Europese Commissie niet in staat zijn om volwaardige alternatieven voor Google Search te kunnen ontwikkelen. Ken Walker, de president van Global Affairs bij Google, schrijft in een blogpost dat het besluit van de Europese Commissie onredelijk is. Volgens Walker is het 'bijzonder zorgwekkend dat de persoonlijke zoekopdrachten van Europeanen zouden worden blootgesteld aan onbekende bedrijven'. Daarbij beweert hij dat de eis privacy, bedrijfsgeheimen en zelfs nationale veiligheid in gevaar kan brengen. De Europese Commissie stelt dat gedeelde zoekgegevens geanonimiseerd worden en in lijn zullen zijn met de AVG. ChatGPT en Claude moeten net zoveel op Android kunnen als Gemini Ook eist de Europese Commissie van Google dat concurrerende AI-chatbots evenveel op Android moeten kunnen als de chatbot van Google: Gemini. Gebruikers moeten chatbots zoals ChatGPT en Claude bijvoorbeeld met een eigen 'wake word' kunnen oproepen, zoals 'Hey Google' voor Gemini werkt. Ook moeten concurrerende chatbots evenveel toegang tot externe apps krijgen. Daarover zegt Walker dat chatbots van de concurrentie al voldoende toegang hebben op Android. Als die toegang uitgebreid zou worden, dan zouden er cyberdreigingen ontstaan volgens hem. Persbericht Europese Commissie over de bindende maatregelen voor Google Blogpost van Google over de gevolgen van de DMA voor privacy en veiligheid Over de maker: Niels Kooloos is dagelijks op BNR Nieuwsradio te horen over het laatste technieuws in de Tech Update. Hij interesseert zich vooral in cybercriminaliteit, privacy, social media en (computer)hardware. Hier en daar kan je Niels ook in All in the Game horen, waar hij graag vertelt over zijn favoriete games.See omnystudio.com/listener for privacy information.

Send us Fan Mail What separates a commodity local provider from a business that easily commands premium pricing? In this kickoff to our four-part brand series, Greg Sterling and Mike Blumenthal are joined by marketing pioneer John Jantsch.John details how small businesses can harness real customer language using clinet interviews, reviews and LLMs to establish distinctiveness, why top-down strategic leadership is required to effectively implement AI, and how to navigate the emerging threat of "agentic flattening" as AI agents and structured protocols begin to alter direct website interactions. Streamline your marketing operations from strategy to final customer touchpoint. Subscribe to our newsletters and other content at https://www.nearmedia.co/subscribe/

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how to separate artificial intelligence speed from actual business value and what we value from humans in an age of AI. You will discover why productivity charts hide critical context that changes everything. You will learn how to spot the difference between quick output and solid results. You will master a simple framework for letting machines handle data while you keep full control over every choice. You will walk away with practical steps to scale your daily workload without sacrificing your unique perspective. 00:00 – Introduction 02:15 – The misleading productivity chart 05:40 – Decoding the midterm results 09:10 – When tests measure the wrong skills 13:25 – The seven ways to use AI properly 18:50 – Why humans must keep the steering wheel 23:40 – Practical tools for smarter workflows 28:15 – Fixing the education gap 32:00 – Call to action Press play to uncover how you can turn artificial intelligence into a reliable partner that amplifies your best work. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-ai-in-academia-workforce.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, let’s talk about AI productivity and results-oriented mindsets. We talk a lot about AI productivity gains, and a lot of people are rightfully asking, “Where’s the beef?” Going back to the 1980s Wendy’s commercial. I want to show you a chart. Katie, I want to get your reaction to this chart on some AI productivity gains and whether you would consider this a success or not. So let me bring this chart up here. This is from Brown University. We have individual workers, we have their original productivity scores in the gray, their AI-enhanced scores where they’re using an AI tool and how they increased. And the green numbers represent the percent change. Now, without any other context, at a first glance, what do you make of this? Is this an AI success story? Katie Robbert: Not necessarily. Christopher S. Penn: Okay, tell me why. Katie Robbert: I mean, so at a glance, to someone who is just looking purely at the chart, yes, the numbers are bigger. You have a bunch of green in the middle. So the percent change is positive. But as someone who is skeptical, I say, where did you start? What was the baseline? What are the roles? I have more questions than answers. I can’t look at this and go, wow, yes. Okay. Because to me there’s so much missing context. Who are these people? Is it self-report? What is the period of time that there? Is it one task? Is it multiple tasks? Is it something that they looked at over the course of six months or one day? I don’t know. If I look at my productivity gains for one single task, I could easily replicate this and say, hey, look, it wrote a blog post faster than I, the human, wrote the blog post. So therefore productivity gains. But what I don’t know is the blog post any good? How much editing does it have to go through? Is it something that’s actually ever going to see the light of day? And that’s one blog post. That doesn’t mean that every single post is created that efficiently. AI can create things really quickly. It doesn’t mean they’re any good. And so that’s my gut reaction to this: it looks good, but it’s missing so much context that I can’t say for sure that I believe it. Christopher S. Penn: Okay, I can tell you for sure these are actual scores. They are actual gains or losses. If your employee number S22 is there, you got it. Your performance went down. Katie Robbert: Yeah, yikes. Christopher S. Penn: Yeah, you got to go. But, and these are real outcomes that matter. Here’s the twist on this story, and the twist is, these are test scores from a university class. The midterm. The professor said, something’s up. The orange scores of the midterm scores. So in the final, he prohibited it. He made the test in person. No assistance, no devices. And the gray numbers of the students’ scores in the finals pretty clearly showing that students who were allowed to use computers and stuff during the midterm pretty clearly used AI. And this story has been floating around the social media sphere. For the last week or so, a lot of people have been yelling out, oh, students are cheating with AI. This is terrible. It’s the end of education. And my take on it was, well, I think there’s a bit more nuance to that. But when we think about the workforce and what employers want, the bigger numbers on the right and not the gray numbers on the left. Now, with this new context, what do you think? Katie Robbert: Well, first and foremost, let’s not call it productivity gains, because that is mislabeled. Second, I’m with you, Chris. The notion of an open book test is not new. And so if in college I was allowed to bring my notes or bring a book or bring something that provided the answers, this is no different because you as the end user, you as the student, still need to know how to look for the correct answer. Because AI hallucinates a lot. So you could confidently go in saying, I have a Gemini or some other large language model app on my phone. I can just look up all the answers. Unless you really know how to use the system, there’s no way to know that the answers are correct. And so I feel like it is nuanced. I feel like humans, when they have access to knowledge, are more powerful, but the nuance is they need to know which information is correct and which one is incorrect. So, I agree. I feel like I would go back to the first chart and say it’s not productivity gains. That is 100% misleading. That is not at all what this is. Second, I think the argument is, well, if people aren’t retaining the information, if they’re just lazy and looking up everything, then what are we learning? Well, you’re learning critical thinking and how to research things. That in and of itself is a whole skill set. Ask the academics. There’s a place for it. Christopher S. Penn: Yep. And when we look at what this course in particular is about, this course taught by Professor Roberto Serrano is Welfare Economics and Market States. But this is from the syllabus. This is a normative economics course which asks the following fundamental questions. Are markets good or bad for the economy? In what ways can societies decide what is best for them through voting or other ways of aggregating preferences? Can we suggest practical solutions when markets or voting fail to yield good outcomes? Are there current political economic institutions good for society? Are they or not? In what ways? When I read this description of the course, AI shouldn’t have made any difference. Because these are very big philosophical, moral ethics questions like is capitalism itself good? Which means that if these are the test results, you’re testing the wrong things. Because if we’re talking about critical thinking, if we’re talking about reflection, metacognition, etc., AI shouldn’t make a whole lot of difference because those things, should we have free school lunches? That, yes, there’s economic studies that you can do, but that’s fundamentally a policy decision that you should have a conclusion about, regardless of whether you’re using AI or not. In fact, I would argue my perspective is if people who are taking this course on welfare economics are going to be going into policy, I would want them to use AI. I would want them to gather research. I would want them to have it push back and forth. Now, whether or not they were actually doing that, I don’t know. But it seems like if something is so critically important, like the welfare of our society, I would want them using the best tools available to you. Katie Robbert: So it’s interesting, it strikes me. I don’t disagree with you. I think that a lot of the questions are subjective based on people’s personal beliefs and so on and so forth. My sense then is if the question was should schools offer free lunch? Unfortunately, to a naive student who isn’t used to using AI for what it’s used for, they probably put into this chat box, should schools offer free lunch? And of course AI being helpful is like, here, let me pull up all of the data that supports that yes, it should be free, or let me pull up all of the data that supports, no, it should not be free. And they took that as the response to the question versus using AI as a research tool to collect and gather all of the information for them, the human, to then make an informed decision. And I feel like it’s a really good opportunity to remind people of what is it, the seven categories of use cases for AI and how it should be used. Like, don’t use AI to make a decision. You’re the human, you make the decision. Use AI to gather your information. Summarize. I’m not going to remember all seven off the top of my head. Yeah, I was like, I got summarize, I got rewriting. That’s all I have for abstraction. Christopher S. Penn: Take data out of data classification. Organize your data summarization. Take your big data and make it small. Rewriting. Take your data from one form to another. Synthesis. Take a small data and make it big. Question answering. Ask questions of your data and generation. Make new data from your data. Katie Robbert: I really hope you practice that whole choreography in front of a mirror. Christopher S. Penn: Well, I do that in my talks. Katie Robbert: I know, but I think that. And so thank you for that. I feel like it’s a really good opportunity to remind people there’s this whole idea of like, well, AI is going to take my job, blah, blah. You, the human, still need to have those critical thinking skills. I feel like I’m beyond a broken record at this point. I don’t even know what the next phase of broken. Christopher S. Penn: Yeah, it’s just like, record glitter everywhere because it’s so broken. Katie Robbert: That’s a thing. The test example is a really good example of misuse of AI. Like we’re making a bunch of assumptions. We don’t know how students actually use these tools. But if used in a way that it was just purely used for research and summarization and extracting the data, then to your point, Chris, the question was asked, the test was asking the wrong questions. Because how are you going to grade based on subjective questions? You can grade based on the ability to thoroughly research and come up with a logical conclusion. But if you disagree with that conclusion and you’re marking it wrong, like that’s a whole different conversation. Christopher S. Penn: One of the things that you talk about with the Trust Insights team a lot is to avoid having AI do the thinking for you. You talk about this with our marketing reports and things like that. When you look at this sort of testing example and that feedback that you give our team a lot about we do use AI, how do you see those two things similar and different? Katie Robbert: I don’t have a problem with people using AI. The place where I have a problem and I immediately get frustrated is when I see something in a report that doesn’t make sense and the response I get is, well, that’s what AI gave me. And my first thought is, well, where are you in this? Where’s your thinking? Where’s your brain? I want to know your insights, Chris. I want to know your insights. Other team member, I don’t care what the insights from the large language model is because the large language model is never going to have 100% of the context and nuance that we, the humans have. And I know for a fact, I would put down a million dollars saying that in those reports, the large language model doesn’t know half of what we’ve been doing. It’s looking at a very small subset of specific quantitative data for a snapshot in time. It does not have the whole story. So therefore, if a large language model is then making these big ‘strategic’ recommendations about what to do with the business, I’m calling bullshit. Christopher S. Penn: Yep. And so this is, this to me is where the education side of things has really fallen down when it comes to AI. Is it binary, oh, yes, you should use it, or no, you shouldn’t use it? And it’s academic dishonesty if you’re using it’s a tool. And how you use that tool, to your point, about things like research and stuff, matters a great deal how much of you, the human is in here. Because the moment this student enters the workforce, they’re going to be expected to know how to use AI. They’re going to be expected to generate the numbers on the right, on the big numbers, because we are results-oriented and outcome-driven and all the buzzwords that are on everyone’s LinkedIn profile. But that’s in a lot of ways that’s true. That’s what we hire for. We hire for those big numbers. We don’t hire. We don’t necessarily. And ethics is a whole separate discussion. But putting aside ethics, that’s what leaders want. That’s what managers want. Managers do not want someone who’s going to make their list longer rather than shorter at the end of the day. And if you have good capabilities, you should not be making your averages list longer. Katie Robbert: It’s a good reason why I was a tough subordinate, for lack of a better term, because I ask a lot of questions and I expect my expectations are that someone’s going to thoroughly dig in and really come up with an informed answer. And my managers at the time were not doing that. Maybe it’s my expectations. I have a really hard time with the lightweight. Oh, I just looked at one study. So therefore it’s fine. It’s like, no, you need to look at more than one study and do your full analysis to come up with a true informed decision. Emphasis on informed, making decisions. What is it? Decisions without data is distraction. Christopher S. Penn: Data without decisions is distraction. Katie Robbert: Data without decisions. But I also feel like decisions without data is dangerous. Christopher S. Penn: Yeah, absolutely. So here’s two examples. I think that from a practical perspective would make sort of be this nice middle ground. Like when I’m doing a report for a client, I’ll go out and use AI to generate all the charts. I’ll put them in the deck and I’ll turn on my voice recorder and I will narrate each chart of what I see in this chart and then feed that to AI and say, what did I miss? Or what didn’t I see? And usually it doesn’t come up with anything. It will ask me questions. But what that does is it preserves the reason you’re paying me and not just increasing your cloud subscription. That’s one useful use case. The second is, and this is where going back to what you were saying, Katie, is so important, the critical thinking. Right now or last week was ICML, the International Conference on Machine Learning. It was in Seoul, South Korea. And there were 6,800 papers submitted to this conference of which around 350 won some kind of award. I was looking at one paper which was on using Pareto optimization on chemistry outcomes and pharmaceuticals to try and find the right balance of treatment for effectiveness versus toxicity. And when I read this paper, that’s a really cool idea. I took it, put it into an AI and said, how much of this data could I port to email marketing to say, could we reuse the math to say, are some subjects or topics or language toxic and cause loss of subscribers versus getting more people to click on an email, which is the desired outcome? And it gave me a whole long list of things that I’m still working on. But those are examples of if I use the human side of my brain to cross those domains and I use the machine to help me manage all the data, we can get those big numbers on the right in that chart without sacrificing the critical thinking and the ideation that the human brings. Katie Robbert: I’m going to say something that I say a lot. New tech doesn’t solve old problems. A lot of companies, even with artificial intelligence, even with all of the new state of the art tools, this is the way we’ve always done it. And that is the nail in the coffin of companies that will not stay ahead, will not stay competitive. Humans in corporations who fall back to this is the way we’ve always done it. Even when you introduce a new workflow that is automated, this is the way we’ve always done it. That workflow is going to get stale real fast. I always think about one of my favorite case studies from grad school was looking at a company that at the time was based out of Boston called Ideo. Ideo. And their whole mission was to understand human behavior. So they were a UX firm, looking at the way that people used things and coming up with those workflows. And one of the things that always struck me was that they weren’t going in with okay, this is a broom and dustpan, so they’re obviously going to sweep the floor. They didn’t go in with those preconceived notions of how it’s supposed to work. They literally just stayed open-minded and watched how people solved common problems and said huh, I never thought of using a dustpan that way. That’s really interesting. What else can it do? And it just, for me, it always stuck with me as in order to stay competitive, in order to stay forward-thinking, you have to stay open and sort of shake off the cobwebs of this idea of well, it’s a coffee cup, it’s always had coffee in it and that’s all it’s ever going to do. It has to be, oh, this is a coffee cup. Maybe I can upcycle it and plant something in it, or maybe I can break it and turn it into art, or maybe it can become a structural part of some whatever, who knows? I don’t even know. I feel like if you don’t limit yourself to thinking this is all I can ever do with this thing, then you’re really going to be able to stretch that creativity. But that critical thinking. So back to the initial example of the students taking the test. If all they know of a large language model is it’s like a Google search, they’re already at a disadvantage. Christopher S. Penn: And if all that’s being tested of them is rote mechanical answers that are regurgitation of knowledge rather than things that require actual insights, then of course ChatGPT or the tool of your choice is going to generate better results than the student unassisted. But you’re not testing the skills that the modern workforce needs. You are testing the skills that the 1930s needed, right? You need to be an obedient factory worker to come in and make widgets. We have robots for that now. We do not need humans for that. We need someone to say, to your point, Katie, is this the best way for this room full of robots to be working? Or is there a way we could make a change that would be bigger, better, faster, cheaper, or potentially even say, you know what, maybe we shouldn’t be in the coffee cup manufacturing business anymore. Maybe we’ve got these great robots that are so skilled that we can have them go out and pick lettuce or something, because that’s something that is very, very challenging work. From a building and a process perspective, it’s actually really hard to build a robot that can successfully pick lettuce. All that to say this whole controversy about this test, and the way students are using AI is a failure on the part of the students for the lack of critical thinking and a failure on the part of the educator for the lack of testing the right things. Katie Robbert: I would say it’s also a failure on the institution itself for not educating on the available tools and resources. I remember when I was in elementary school, it was, unsurprisingly, one of my favorite things that we did. There was a whole class on how to use the card catalog at the library. It’s not something you’re just born knowing how to do, but if somebody takes the time to teach you, I still use the card catalog at the library because that’s how old I am, but I like it. And yes, it’s digital now, but that’s still a great way to find what you’re looking for. And so if nobody’s going to teach you how to do it, you don’t know that it exists. If you’re someone who’s curious enough to find out on your own, that’s great. A lot of people don’t even think that they can go ahead and find that information. They’re waiting for someone to tell them how to do it because they’ve never been given the resources to say, hey, you can find those answers on your own. You can teach yourself. Some people just, that’s not just how their brain functions. It’s not a weakness or a bad thing. It just is what it is. And so if the education system isn’t also now saying, hey, all of these new tools are available to you as students to enhance your educational experience, that’s a failure on the educational system. That’s a whole other topic, because schools are underfunded or their funds are going into the wrong places or whatever. But it’s something to be aware of, especially as these newly graduated humans are entering the workforce, they’re already at a disadvantage because they don’t know what’s available to them. Christopher S. Penn: Yeah. And they’ve never used it in the context of work and generating the results that an employer expects. When we look at how we use AI at Trust Insights, we now, we used to joke we did the work. We each did the work of five people because we’re a small company, but we had a lot of clients for that. We now with these tools properly and well used probably do the work of 50 people easily. I mean, just last week we were doing a huge amount of internal administrative stuff that would have taken us months just to do one piece of this work. And, we were doing 18, 19 pieces. Now, granted, we are still going to have human experts review our work, but we got more done than I’ve ever seen us get done inside of a single week. Katie Robbert: I would agree with that. I mean, this is the whole. I’ve talked about it on live events. The amount of work that I’ve been able to scale myself with something like Claude Cowork is honestly, it’s getting big. That’s an understatement. Christopher S. Penn: I don’t know. Katie Robbert: I don’t have a better word for it, but. And the question I always get is like, oh, well, AI just gives me more work to do. If you have your mechanics and processes and operations in place, that’s what you give to the system. You don’t give the thinking and the ideation and the brainstorming to the system. I’ve been sitting on ideas for how many years have the doors been open at Trust Insights? Christopher S. Penn: 8. Katie Robbert: I’ve been sitting on things that I want to do. Ideas. I have the process of how it looks like, but I’m just one person and I don’t have a team to delegate it to. So now that’s how we’re scaling things. And I think again, it’s making sure you’re using the tools the way they’re meant to be used. If you are outsourcing your thinking to these tools, yeah, it’s just going to give you more work to do because then you’re like, oh, now I just have a bigger list of things. No, give the list of things that you’ve already thought of to the system. Let the system do it. You continue to create and ideate. Christopher S. Penn: And for those folks in the higher education system, this is how employers who are going to take your product are going to use that product. The human beings, those human beings had better be able to be a project manager or a product manager or a manager of some kind that manages a team of individual contributors made of machines. Because we’re paying for, we want to pay for the critical thinking. We want to pay for the genuinely good new ideas. We do not need to pay for someone that just regurgitates things. A machine can do that perfectly fine. We do not need to pay for somebody that can type. Again, a machine can do that perfectly fine. We need people who think. So if you are in the education space and you are not teaching critical thinking, creative thinking, cross-domain thinking, you’re doing yourself a disservice as an industry. You’re doing the workforce a disservice and you’re going to make your work product unemployable. Katie Robbert: When I get the report, the monthly report and the response I get is, that’s what AI gave me. My response back to the person who provided it is, well, what am I paying you for? And it’s a really cold and harsh comment, but it’s real true. It’s true. Perhaps my delivery is not that direct all the time, but sometimes it is. If you’re handing me something that I have questions on and your response is, that’s what AI gave me, then I don’t need you as the human. I can do this myself and get crappy insights from a large language model. I don’t need someone to push a button for me. Christopher S. Penn: Right, exactly. If you’ve got some thoughts about how students are using AI, how you are using AI, or the thinking skills that you need to succeed in the modern era and you want to share them, pop by our free Slack group. Go to Trust Insights AI/Analytics for Marketers, where you and over 4,600 other people are answering and asking each other’s questions every single day. Well, I got that backwards. Clearly not AI generated today. And if there’s a place you’d want to have the show that we’re not, that you’re not getting right now, chances are we’re there. Go to Trust Insights ASGI Podcast. You can find us at all the places fine podcasts are served. Thanks for tuning in and we’ll talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and Martech selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMO or Data Scientist to augment existing teams beyond client work. Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights podcast, the Inbox Insights newsletter, the So What Livestream webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Data Storytelling. This commitment to clarity and accessibility extends to Trust Insights educational resources, which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Nicole Dyer and Diana Elder explore Leo, a powerful handwritten text recognition platform designed specifically for researchers. Nicole interviews the creator, Jon Cooper, a PhD candidate at Stanford who developed the tool with a machine learning expert to address the difficulty of transcribing complex Elizabethan manuscripts. Listeners learn how Leo differs from general AI models by prioritizing faithful, accurate transcriptions of handwritten text rather than guessing words. The platform offers specialized features for genealogists, including the ability to recognize tabular data, crop and rotate document images, and refine transcriptions using multiple model inputs. Diana shares her own experience testing the tool on a two-page 1830s deed, finding it to be a user-friendly and accurate resource. The episode also highlights Leo's "Transformations" feature, which helps users move beyond basic transcription. Listeners discover how this tool summarizes content, identifies key people and places, and translates non-English sources. While the platform is advanced, the hosts discuss important limitations, such as challenges with tiny marginalia, double-page spreads, and predicting rare proper names. Ultimately, this episode demonstrates how Leo serves as a force multiplier for genealogists, helping them turn raw digital images into searchable, summarized, and interpreted research assets. This summary was generated by Google Gemini. Links Meet Leo: The Handwritten Text Recognition Platform Built for Researchers – Family Locket -https://familylocket.com/meet-leo-the-handwritten-text-recognition-platform-built-for-researchers/ Learn more about Leo and to set up your free account, go to https://www.tryleo.ai/ Leo Demonstration with Nicole and Jon Cooper on YouTube: https://youtu.be/mR8KOH97Rf0  Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.   Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Send us Fan MailArtificial intelligence can write emails, build presentations, create images, and even help write code—but it still can't shake a hand, earn trust, or make someone genuinely feel understood. This week on the Mike & Blaine Podcast, we explore why the most valuable skills in business are shifting back to the things technology can't easily replicate: communication, leadership, empathy, humor, and emotional intelligence. As AI gets smarter, being authentically human is becoming more valuable, not less. We talk about the surprising comeback of soft skills, why relationships are becoming a competitive advantage again, and what separates people who simply use AI from people who actually lead. Because the future may be powered by AI—but it's still built on trust.To truly win in today's market, your business strategy needs to evolve beyond just buying the latest software. Tactically, it's no longer about optimizing just your tech stack; it's about maximizing your "human stack." In this episode, we break down how savvy entrepreneurs are leveraging platforms like OpenAI and Google Gemini to automate the mundane backend tasks, freeing up critical time to double down on high-touch client relationships, team leadership, and creative problem-solving. If your current business tactics rely 100% on automation, you are leaving your customer loyalty exposed to competitors who still know how to pick up the phone. Learn how to weave authentic emotional intelligence into your corporate strategy so you can future-proof your brand and out-human the competition.Watch on YouTube: https://youtu.be/ua8cOzKiSj0We want to hear from you! beer@mikeandblaine.comListen to all our episodes at mikeandblaine.comLove the show and want to keep the insights (and the brews) flowing? Head over to mikeandblaine.com to buy us a beer! We appreciate the support!Learn about:Cash Flow Mike who trains CPAs to provide effective advisory to their clients at cashflowmike.comDryrun Cash Flow Forecasting for the office of the CFO where they get finance teams out of spreadsheets at dryrun.comThanks to our Beer Sponsors:Karen Hairston from 3S Smart ConsultingCPA Larry Weinstein, the Cash Flow Cowboy from Houston TexasNeighbor PatDevinTrey MiltonWatch on YouTube: https://youtu.be/ua8cOzKiSj0#ArtificialIntelligence #FutureOfWork #Leadership #SoftSkills #OpenAI #ChatGPT #GoogleAI #Microsoft #BusinessStrategy #BusinessTactics #EmotionalIntelligence #Entrepreneurship #Podcast #TechTrends #Management #B2BStrategySupport the showCatch more episodes, see our sponsors and get in touch at https://mikeandblaine.com/

Doomscrolling vertical videos is just brain rot, right?

Alphabet (GOOGL) has taken a step back recently, says Dave Alison, but you need to zoom out to see how strong the company has become when it comes to its stock and balance sheet. He'll have his eyes on earnings and ways the Mag 7 giant will expand its AI capabilities, especially through cloud and Google Gemini. He explains how Alphabet's tech stack paves the way for stable growth and argues growing competition in LLMs and compute set a bullish foundation for the company. ======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the growing tension between businesses and software vendors, sparked by recent privacy policy changes at major platforms, and the fundamentals of AI data sovereignty. You will discover how to spot risky service rules before they impact your daily work. You will learn practical steps to evaluate whether building custom internal tools makes sense for your team. You will find out how to review agreement changes without getting lost in confusing language. You will gain confidence to protect your valuable information and keep full control of your digital assets. 00:00 – Introduction 01:45 – HubSpot triggers data sharing controversy 05:30 – The hidden costs of vendor lock-in 10:15 – Can AI replace expensive software subscriptions? 14:40 – Building custom tools in-house 19:20 – The importance of the 5P framework 24:10 – Reviewing service agreements quarterly 28:50 – Final thoughts and next steps 32:15 – Call to action Watch this episode to learn how you can take back control of your software and data today. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-what-is-ai-data-sovereignty.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, let’s talk about a very popular term these days which is data sovereignty, AKA owning your data and who owns your data. In the news recently, HubSpot made an announcement last week that caused a firestorm of commentary. Appropriately so when they said that to better improve HubSpot’s predictive abilities in your CRM, customers would be able to share data and see data from other HubSpot accounts to predict the likelihood of a certain type of sale closing. Now they did say that it would be something that you could opt into, although that was not super clear. And the terms of service were vague enough that if you were an eagle-eyed legal expert, which we are not, you could say, yeah, we’re going to do this regardless. LinkedIn exploded, threads exploded, Twitter exploded, and HubSpot walked it back over the weekend to say we screwed up. And to that credit they said we screwed up. We didn’t do our homework on this. We’re not going to make this terms of service change. However, there are still two consequences. One, folks have pointed out they didn’t say they weren’t going to implement the feature, they just said they’re not going to change the terms of service this way. And two, the big question that a lot of folks have is from a customer’s perspective, this was kind of a big deal in terms of violation of trust, which is a really important thing. And one commenter said it took HubSpot twenty years to build trust in four days to screw it up. Now again, to their credit, they did walk it back. But Katie, what’s your take on this, particularly as it relates to the integrity of our data? Because as we see these days more and more, every AI company is saying we need more data, so we’re just going to come in and take it well. Katie Robbert: And that’s always been the risk with using these software vendors is they can change things on a whim. And yeah, you can blow up social media and say I’m so mad at this. That doesn’t mean they have to do anything about it because guess who already has your data? Guess whose system you are already integrated to, guess whose system you have built connectors to and tapped into the API of, and you are building your whole business around. So the cost of switching is incredibly high and incredibly painful, and you’re not necessarily going to find a vendor that’s doing things any more ethically or doing things in a way that their governance aligns with what you want to see. Because again, to that comment, HubSpot spent twenty years building trust and then they decided to change it. I call BS on the we didn’t do our homework, we screwed up. Really. The size of company that you are, you don’t just change things on a whim. This is something that has likely been on your roadmap for a very long time. It was just a matter of trying to figure out how to do it in a way that you could sneak it in. But still, July fourth, holiday weekend. Well yeah, so there’s that. But legally, the language holds up. They worked with their lawyers, they worked with their IT department, they worked with whoever is involved in that change. It wasn’t an oopsie, we didn’t do our homework. No, I’ve worked in a large organization. I know how these things happen. There is no oopsie, we screwed up. You didn’t. You got caught, period. And your customers are angry. But guess who’s not going to stop being a customer anymore? Your customers. And they already got the data. Nowhere in that did they say and we’re going to repartition the data or we’re going to unshare the data. They were just like oopsies, you caught us. Okay, where is it? Oh, it’s over here. Here we go. That gets a red flag today. It gets a huge red flag because more and more, it’s Google adding AI into workspace conversation all over again. When my mother-in-law was here, she kept complaining about how Google was making suggestions in her Gmail. You can turn that off. Well, what if I need it? Then don’t complain about it. But Google made this change where it’s looking at all of your emails, it’s looking at all of your chat conversations, it’s looking at all of your stuff. Google has been looking at your web searches for however long web search has existed. On the one hand, I can understand the outrage of customers of a CRM saying I thought you were protecting my data. On the other hand, I’m a little surprised at people’s sort of naive perspective that our data was private in the first place. And I’m sort of like, so bad on the CRM, but also bad on the consumer for not being more informed that nothing is private. Like your Social Security number. It exists in a million places. People just haven’t decided that you’re the person that they want to steal the identity of. Maybe you’re not that interesting. I don’t know. Okay, I’m going to red flag myself. That was terrible. Red flag myself, sorry. Christopher S. Penn: It does raise the question, and this is something that vendors in particular have not thought a lot about. Generative AI in its current incarnation is best at software development. That is the number one task being used for. It is what is most skilled at, is what has been tuned the best for. Which means that if you are a SaaS provider, you are skating on very thin ice because you are one prompt away from a customer saying, screw it. I’m going to try vibe coding it myself. And whether or not that’s a good idea, we’ll put that aside because we’ve talked about that in the past. The reality is that with skilled use of these tools, you could say we’re just going to bring this in house. And we’ve done that. I’ve done that even on my personal blog, on my personal website. I said, you know what, I don’t want to pay for this plugin anymore. I’m just going to bring this in house and stop paying for this. And over time, you see the bills going down as you bring in more stuff in house because your AI tool that you built it with is also the AI tool you provide support to yourself with, so you don’t have to pay for the additional upkeep. One of the biggest moats that SaaS has always had was, hey, you don’t want to do server maintenance, you don’t want to do software maintenance, you don’t want to do any of that stuff. Pay a vendor to do it. Well, now it’s like I have basically a junior employee, right? Because we’ve talked about how tools like Claude Code basically are junior employees. I have a support resource. It may not be perfect, but it gets better every day. And so for marketers, for business folks, for folks who are looking at particularly operations folks, as you’re auditing your tech stack and as you’re seeing changes happen to your point, Katie, and vendors trying to cram AI into everything, the question has to become at what point do people start bringing things back in house, given the capabilities of what even a $20 a month AI subscription can do for you? Katie Robbert: I think for a lot of companies, that’s definitely something they’re thinking about. But you’re still talking about a whole suite of skills. You’re still talking about a software developer, you’re still talking about an IT person, you’re still talking about QA, a database architect. Sure, AI can do that stuff, provided you know how to tell IT what to do. And so for us, I would say you have some of those skills, but you do not encompass the skill sets of all four of those individuals. So I would be hesitant to say, sure, we can just have whatever you’ve built, manage it and get rid of this other vendor. We’re not there yet. I can see us getting there. Companies who have none of those skill sets because that’s not what they do. Think of perhaps a creative agency that really works on front-end design and branding. They don’t have the skill sets in house to do this. So even though AI can do a lot of those things, they still have to have someone to tell the AI what to do and stand it up and manage it. That data has to go somewhere. That data still has to be secure in some way. So you still need someone who understands database architecture, who understands servers. I hear what you’re saying and there is a reason why the majority of us turn to vendors like you, just handle it. Saying we can handle it ourselves in house is not as easy as it sounds like. Yeah, it’s an empty threat to the vendors. Especially if you’ve never stood up a server. You don’t know what goes into good data privacy. You are just vibe coding your own version of a CRM. That is a recipe for disaster and it’s likely going to lead to data leaks in some way of your most valuable data. So I hear what you’re saying, Chris. I think that a lot of companies are going to put that on their roadmap of what does it look like for us to build this in house for ourselves. I think that is more possible than it ever has been. But there’s still a lot of caveats with that. I’m saying to do it the right way, you need those skill sets. It doesn’t mean you can’t just go ahead and do it. Christopher S. Penn: It’s true. I do think there’s a space for consultancies and agencies to operate, particularly if you’re a hybrid agency where you have an IT consulting capability. I think, for example, IBM IX as one example, that’s a blend where that might be a realistic choice to say we have our trusted agency that we work with and we don’t like what we see. A HubSpot or Salesforce or whoever doing it, we don’t need it. John was at Salesforce Connections not too long ago and was saying that it’s Agentforce, everything is Agentforce and AI agents. And there are a lot of folks saying we don’t need that nor do we need to pay for that. We can take Sugar CRM, which is a free open source product, with our existing IT agency with the assistance of AI, with their help because they do know servers and they do know this. We’re going to stop paying Salesforce $3 million a year and instead pay our agency maybe $2 million a year to run it for us and save a million bucks a year. And we won’t have all this extra stuff that nobody asked for and that doesn’t fit their business case for it. And I think there is an opportunity in the marketplace for that. Katie Robbert: I agree. But let me counter with this question. You know, we have collectively put a lot of stock and time into these large language models. We’ve also seen instances where a company rolls back the large language model that they rolled out for a variety of reasons. What risk are we taking by then saying well, I’m going to fire the vendor, I’m going to build it myself because I have a large language model? And then tomorrow the large language model gets shut down. So you fired your vendor, you don’t have a large language model. What do you do? Is that a real risk? As someone who is very risk averse, I should be thinking about this in terms of business continuity planning. If you are tied into only working with one vendor, for example Anthropic, and as we saw in recent events the U.S. government said you can’t have that model in public, yes, that is a risk. Christopher S. Penn: However, if you are a multimodal aware company and you know where to find GLM 5.2, which we have through our Deep Infra subscription, and you know how to host models locally, which we’ve talked about in previous episodes of the podcast and the live stream, your risk is significantly reduced because you have more options. That’s what I learned from you, the more realistic options you have, the lower your risk because you have backup plans, you have backups to your backups. And if you are working in the AI space today and you have integrated AI and it is now a risk because your business is so dependent on it, you would better have those backup plans handy. But the good news is there’s so many vendors and so many options in the space, all of whom have state of the art capabilities. If Anthropic or OpenAI went away tomorrow, just flip to the next vendor with this model. Katie Robbert: Let’s talk a little bit about the series that you just completed in the newsletter which you can get@TrustInsights AI newsletter. You talked a lot about Enterprise AI. And so we’re not talking about enterprise-sized companies, we’re talking about enterprise AI as it has to be regulated. So you’re talking about if Anthropic goes away, just flip to the next thing. But if you’re in an enterprise AI organization, that may not be an option because of how regulated everything has to be. So can you speak a little bit to that? Christopher S. Penn: Yeah. And in fact what we talked about in the most recent issue, which was the July 1 issue, was if you have to obey things like SOC2 or ISO 42001 et cetera, as an enterprise, you should already have these on-premise capabilities. Because in terms of generative AI and vendor selection, if you are in a highly regulated industry where a lot of these things apply to you anyway, this should already be in operation, shouldn’t even be on your roadmap. It should be in operation. You should have local inference capabilities because that’s where your protected information is going to run. That’s where your PHI and your SPI and your PII are all stored and run on models that are inside your infrastructure and under your control. And no data leaves. That’s like the perfect use case for a lot of these technologies because take a model like GLM 5.2, it is an OPUS class model. It is very smart. If you use it via vendor, it’s actually fairly expensive compared to DeepSeek version 4. However, it’s still cheaper than Claude by a 10x. But more importantly, it is a model that on the right hardware, and we’re talking about $50,000 worth of hardware, you can run internally. Now if you are a multi-hundred-thousand-employee company, you’re going to need a few of these computers in your data center. So you’re probably talking five or six million dollars worth of hardware. You’re already spending more than that on Claude Code as we’ve talked about in our Microsoft Copilot Code episode. You’re going to spend that in two months. So you absolutely should have those capabilities internally already. And if you don’t, you are behind. I mean, there’s no polite way to say that. Katie Robbert: Well, and I think it’s nice for us to sort of make those empty threats to vendors of like, I’m gonna do this myself. And then you’re like, I have no idea how to do this. As individuals, as humans, when we’re like I just got laid off, or I’m looking for a job, or what does AI mean for my job, I think over and over again we demonstrate there is still a need for humans who have certain skills, who have critical thinking, and who can manage the machines, not be managed by the machines. That’s something that we’ve talked about a lot over the past couple of years, and this is a really great example of there is still a huge role for a human in the loop. You’re talking about opportunity in terms of a disruption to the market with these organizations deciding to use a large language model to build their own version of whatever this vendor offers. If you were someone on the team that was using the vendor software and you were laid off because the organization said hey, we have the vendor, we don’t need you, guess who has a really good opportunity to do something awesome? You can go and be like well, I know this vendor software inside and out. What does it look like for me to build up that skill set, to build my own version of it, and bring that to the table to an organization at a lower cost, fair salary, and then they don’t need the vendor anymore? Christopher S. Penn: Mm. Yep. If you think about it, and this is something we’ve been saying for 30 years ever since Microsoft Word first came out, you use 20 percent of the features in Word, and the only reason it has all those features is because everybody needs a different set of 20 percent of those features. A law firm has very different use cases for Microsoft Word than we do. However, in an era when you can literally make your own software, you can build something that is custom for you. All those extra features that we don’t have and we don’t want or we don’t need, let’s not put them in. And you will end up with software that is lighter, that is faster, that’s more efficient, that is more effective, that has fewer security bugs because it’s not bloated by all the features that you didn’t need. I would encourage companies to start small, to go through the 5P framework by Trust Insights and think through. Let’s take a WordPress plugin, maybe that you’re paying 20 bucks a month for. What does it do? How do you use it? Your purpose, who uses it? How does it work? What technologies does it rely on? And how do you know that it works? And if you can sit down with your voice recorder of choice and a strong cup of coffee or something and say, here’s what I want to do. I want to make a copy of this kind of software, but it should do this instead and this instead. Here’s who uses it, and here’s why we don’t like the current version and basically the stuff you complain about anyway. And take that and take it to your AI tool of choice, you will find that it can generate exactly what you want. And again, start small. A single plugin, a single utility. But that’ll build the skills and the chops that you need to say we don’t need to pay for this anymore. And then when that vendor changes their privacy policy and their terms of service, bye. Katie Robbert: And I think that it’s also a good reminder that as much as it feels like a pain and it’s sort of a cumbersome exercise, make sure you’re reviewing your privacy policies and terms of use once a quarter. Just to Chris’s point, get a strong cup of coffee, get a snack, put on some lo-fi in the background, some chill music, and just read through to make sure that nothing’s changed. And if something has changed, make sure you’re aware of what’s changed. Companies will say hey, we told you. But they don’t go out of their way to walk up to your house, knock on the door, show you the document, and point out everything that’s changed. They just put it out there. Christopher S. Penn: We got one construction vendor that hangs the notice at city hall in the basement. We followed the letter of the law. Katie Robbert: Yeah, legally, we did what you were supposed to do. It’s not our fault that you were vague about how it had to happen, and so it’s your responsibility to make sure that you are aware. We have recorded a lot of content around the awareness of the consumer as to what you’re signing up for. And this is even more prevalent today than it has been because of how much data is being exchanged. Data is the most coveted currency of all of these vendors. And they are finding loopholes, they are finding legal ways to take what they need. And to be quite honest, they’ve always owned the data. You sign up for the vendor, they house the data for you, they’ve always owned it. It’s the same story unfortunately of you’re renting from a landlord. Landlord can decide tomorrow, I want this building back. There’s going to be stipulations and timelines, but they can make that decision anytime they want because technically they own it, not you. Christopher S. Penn: Yep, this is a chicken farm now. Everybody out. And that is the legal reality. Katie Robbert: And so there’s two aspects to this data sovereignty, right? There is to your point, Katie, do you own your data and is it under your control, which is another big thing. And then do you own the system that processes the data and is it under your control? Christopher S. Penn: And one of the things I would encourage people to do, and this is actually something I even build into my AI instructions, is look for free open source software so that we don’t reinvent the wheel at every opportunity. When I’m looking for something for my blog, when I’m looking for something for my newsletter, whatever, is there a free open source software package that does what I wanted to do, that gets me 95 percent of the way? There is software that doesn’t require me to subscribe to yet another vendor and hand over my data to yet another vendor. And the answer increasingly is yes. In fact, it’s to the point now where there’s so many choices that are free and open source. Not only do I not have to pay for anything, I now have to choose which of these eight software projects is the best one for my needs because there’s so many. And do I want to customize it further for my use? Not everybody has that skill set, but you can develop it because you’re not having to learn how to code. You’re learning how to ask good questions and develop a good vocabulary. Katie, you could do this today using the 5P framework by Trust Insights. Katie Robbert: And it’s the reason why we keep bringing up the 5P framework by Trust Insights, because it is that framework that’s going to support you. It’s foundational. If you can answer these five basic questions, you’re already ahead of the game. When we talk about vibe coding, we want you to do this first. Don’t just open up a large language model and say I want to build my own CRM. Go, no, that’s a bad idea. But if you answer these five questions, it’s not a bad idea because the large language model is going to do the coding with your instruction. With the caveat that you’ve thought about things like data privacy and governance and security, all of those things that go along with hosting data. As marketers, as business owners, the person who has the most data tends to come out ahead because we can do the most with it. And that’s what these vendors are trying to sell you on. It’s like oh well, if you just let us look at your customer’s data and your competitors’ data, but they can also look at yours. Everybody wins, right? No, no, don’t do that. Would I love to take a look at some of my competitors’ data? Absolutely, but only in a very legal way. That also means they couldn’t look at my data. And that’s just not how that works. So you need to think about a couple of things. One is what is your level of risk aversion? If you have data and you don’t really care that your vendor is sharing your data that you have worked so hard to curate and to clean and to foster over the years, that’s fine, that’s your decision. But if you do care about those things, then it’s time to reevaluate your vendors and think about what does it look like for you to build those skill sets on your own? And it’s not impossible anymore. You have a lot of considerations. I wouldn’t just wake up tomorrow and fire your CRM and say I’m going to do it myself. Maybe give it a little more thought than that. But as you’re thinking about it, think about what does it look like? What does that long-term maintenance look like? Could I do this myself? Could I bring on a contractor to help me do this? Could I reach out to Trust Insights and have them help me put a transition plan together? The answer is yes, we could absolutely do that. But it’s worth thinking about. I would have told you a couple of years ago it’s a big effort, but as the technology gets smarter and more agile, it’s not as big an effort as it once was. It is possible. There’s more human upfront thinking that has to be done. But guess what? That’s what we’re here for. Christopher S. Penn: Exactly. Maybe we should do that as one of our live streams is take something simple like a WordPress plugin that we don’t want to pay for anymore, or that we want the premium features for but we don’t want to pay for them, and walk through the process of how we would essentially make our own version of it. Katie Robbert: It’s a good idea. Christopher S. Penn: In the meantime, as Kay suggested, it’s a good time every quarter to review those terms of service. Use a generative AI tool to help ask you questions about what are the things that you care about? And then have it help you read through the document. Don’t have it do it for you, but have it help you by asking good questions. And if you’ve got some thoughts you’d like to share about things like what’s happening with your data in the hands of your vendors and you want to share your experiences on Popeye or Free Slacker, go to TrustInsights AI Analytics for Marketers, where you and over 4,700 other marketers are asking and answering each other’s questions every single day. And wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on set, go to TrustInsights AI TI podcast. You can find us at all the places fine podcasts are served. Thanks for tuning in. Talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and Martech selection and implementation and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic, Claude, Dall-E, Midjourney, Stable Diffusion and Meta Llama. Trust Insights provides fractional team members such as CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community sharing expertise through the Trust Insights blog, the In-Ear Insights podcast, the Inbox Insights newsletter, the So What live stream webinars and keynote speaking. What distinguishes Trust Insights in their focus on delivering actionable insights, not just raw data, Trust Insights are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Data storytelling. This commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

AI's all-you-can-eat era is ending.

Diana Elder and Nicole Dyer discuss the evolution of AI Handwritten Text Recognition (HTR) tools, focusing on the platforms Nicole explored at RootsTech. They evaluate several key technologies used to decipher historical manuscripts. They discuss Kindex, which provides highly accurate transcriptions and a side-by-side editor for corrections. They also review Leo, an AI platform that handles secretary hand effectively and offers a side-by-side editor, though users should watch for minor hallucinations. Transkribus serves as a solution for difficult or uncommon scripts, offering results that can be further refined with LLMs. The hosts also examine other tools, including 360 Mind, which functions as a browser extension but lacks strong language model processing. Goldie May utilizes Gemini for automatic transcription on research logs, providing high accuracy with the potential for occasional hallucinations. Finally, they cover MyHeritage's Scribe AI, which transcribes and summarizes documents, though it currently lacks an in-tool correction feature. Nicole identifies Kindex and Leo as her preferred tools due to their side-by-side editing functionality. By listening, you learn the strengths and limitations of these AI transcription options and determine which tools best suit your research needs for historical records. This summary was generated by Google Gemini. Links AI Handwritten Text Recognition Tools at the RootsTech Expo Hall - https://familylocket.com/ai-handwritten-text-recognition-tools-at-the-rootstech-expo-hall/ Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

As an ARIA-nominated artist she goes by Jack River. As a high-flying political lobbyist, she’s Holly Rankin, and today she’s here to discuss the issue dividing artists, journalists, writers, Big Tech and the federal Government: should we bend our copyright laws in the hope of attracting data centre investment? Read more about this story at theaustralian.com.au and see the video by subscribing to our YouTube channel. Australian songwriters’ fury as Big Tech ‘blatant theft’ for AI training revealed by Andrew McMillen AI giants could get a free pass – and gut creators’ rights by Rod Sims Boy Swallows Universe author Trent Dalton wanted to ‘vomit’ when told his books were on pirate database by Rosemary Neill The weekend edition of The Front is co-produced by Claire Harvey and Jasper Leak. The host is Claire Harvey. Audio production and editing by Jasper Leak who also composed our theme.See omnystudio.com/listener for privacy information.

Grab your alumni gear, because Episode 271 of Beer, Blues, and BS is officially in session! We're kicking things off with a massive shout-out to our listeners tuning in all the way from Hong Kong, alongside a proud roll call for fellow Fighting Sioux alumni. This week, a major pop culture news drop takes center stage as the crew reacts to breaking headlines from the BBC regarding the future of Doctor Who—including a canceled Christmas special and a surprising shift in production. This immediate dive down the entertainment rabbit hole sparks an incredibly passionate debate about the overall decline of massive franchises like Star Wars, Indiana Jones, and the newly axed Stargate reboot. The guys break down why the modern "10-episode streaming season" is failing character development, contrasting it with the gold standard of 90s television. Over on the beverage counter, the "What's on Tap" segment delivers a relentless gauntlet of hits and misses. Mark Kidder mixes up a cherry-free Old Fashioned dedicated to his grandfather, while Tony Soprano drops in late (thanks, Windows updates!) to review a hard seltzer that tastes exactly like old-school green plastic-tube popsicles. Meanwhile, LCL Geek and Howard Blues team up to test a highly anticipated hop water from Montana that, unfortunately, leaves them feeling like they're drinking watery IPA backwash. Inside this Episode: Franchise Fatigue: Why Hollywood keeps alienating long-term fans by "chasing new audiences" instead of telling good stories. The 1940s World Cup Twist: Howard tracks the chaotic, final-minute heartbreak of the USA vs. Paraguay soccer match. AI Thumbnail Fails: Howard shares a hilarious nightmare creation from Google Gemini after attempting to sharpen a blurry photo of Doc. On Tap this Episode: Mark Kidder: An artisanal Old Fashioned featuring Batch 27 Bourbon and local syrup. Tony Soprano: Happy Dad Hard Seltzers (Lemon-Lime and Watermelon). Rudeboy Kyle: A crisp German Pilsner out of Iowa and a Mexican-style Lime Lager. Doc: Old Keg Premium Butterscotch Beer & Hawaiian Soda Co. Passion Orange Guava. Big D: A Belgian-style ale paired with NBA Finals leftovers & a canned Blue Hawaiian cocktail. LCL Geek & Howard Blues: Kettle House Hop Water    Recorded: 6.12.26 0:00 – Intro 3:09 – What's on Tap? 24:05 – Viral Video & Henri Mancini 29:08 – Dad Jokes of the Week 31:08 – AI Doc 36:02 – What's on Tap? Round 2 45:41 – Doctor Who News & Reaction 55:11 – Hollywood Rehash Rantings 1:21:16 – Cheap Plugs   https://streamlabs.com/beerbluesbs https://beerbluesbs.podbean.com/ https://www.youtube.com/@BeerBluesBS?sub_confirmation=1 https://open.spotify.com/show/1pnho1ZzuGgThbLpXbAs3t https://open.spotify.com/playlist/2Unmhz98iRYU97l18uJp99 https://www.twitch.tv/tuez13 https://www.youtube.com/@HowardsCaveofWonder?sub_confirmation=1 https://www.twitch.tv/krdneyewitnessweathernow 1:48   #BeerBluesAndBs #Podcast #TripleBBSPodcast #Podcast #ComedyPodcast #BeerPodcast #Brews #Laughs #BrewsAndLaughs #podcast #tripleb #Comedy #Beer #Blues #Bs #IPA #CraftBeer #BeerBluesBS #DoctorWho #Stargate #StarTrek #ChrisFarley #HopWater #OldFashioned #PopCultureDebate #FightingSioux #PodcastLife #Starwars #IndianaJones

Wednesday, July 1, 2026 Today, Today, Birthright Citizenship hangs on by a thread while transgender rights and campaign finance are gutted by the Supreme Court; the Justice Department is now zero for eleven in voter roll smash and grab; Donald gave a secret $500m no-bid contract to Clark Construction for his ballroom; Meta contractors posed as teenagers to prompt rival chatbots about suicide, sex, and drugs; a federal judge orders Donald to end his efforts to kill Hudson Tunnel funding; a judge rules that nursing is a professional degree for student loan purposes but drops theology; former North Carolina Governor Roy Cooper holds a 14-point lead over Republican Michael Whately in the state's open US Senate race; the Alaska Supreme Court rules that Dan Sullivan can be on the state's primary ballot; the New Jersey Rep that has been missing for months - Tom Kean - has reappeared; DC will pay $50k to a man detained while protesting the National Guard using the Star Wars Imperial March; plus Allison and Dana deliver your Good News. Thank You, IQBAR Text DAILYBEANS to 64000 to get 20% off all IQBAR products, plus FREE shipping. Message and data rates may apply.  Thank You, Fast Growing Trees Get 20% off your first purchase  FastGrowingTrees.com/dailybeans Join The Daily Beans and give a gift today to ensure The Trevor Project can continue its crucial work in the face of continued challenges. Donate to The Trevor Project - Daily Beans Podcast The Latest Breakdown:The Breakdown | Trump DOJ in Crisis after Major Epstein Ruling StoriesBirthright citizenship ruling: Supreme Court rejects Trump's proposed limits | AP News Supreme Court Rules Title IX Means "Biological Sex" In Devastating Anti-Trans Ruling | Erin In The Morning DOJ voter roll grab is now 0-11 as judge dismisses New Hampshire lawsuit | Democracy Docket Trump is using a $500M no-bid contract to build his White House ballroom | The Washington Post Meta Contractors Posed as Teens to Prompt Rival Chatbots About Suicide, Sex, and Drugs | WIRED Judge Orders Trump to End Efforts to Kill Hudson Tunnel Funding | The New York Times Poll: Cooper holds 14-point lead over Whatley as Trump stays underwater | Carolina Journal Alaska Supreme Court says a man with the same name as US Sen. 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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the emerging phenomenon of AI psychosis. You’ll discover how interacting with large language models can impact your mental health and perception of reality. You’ll learn to identify the five specific themes of AI-driven delusions that affect users today. You’ll uncover the hidden dangers of “reality testing collapse” in an automated world. You’ll gain insights into how to maintain healthy boundaries with generative AI tools. 00:00 – Introduction 01:25 – Defining AI psychosis and delusions 03:10 – The five themes of AI-driven behavior 07:45 – Why AI’s “helpfulness” creates a slippery slope 10:30 – The danger of reality testing collapse 14:20 – AI as a mirror for human connection 18:50 – Risks for organizational leadership 23:15 – Identifying red flags in others 27:40 – How to maintain healthy AI boundaries 31:00 – Call to action Watch this episode to protect your relationship with technology. Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-what-is-ai-psychosis.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In-Ear Insights, something very different. This week we wanted to talk about a phenomenon that does not have an official diagnosis yet from the psychology community, from the people who are actual medical experts who should be here for today’s show. We are not medical professionals. We do not give healthcare advice. Please contact your qualified healthcare provider for advice specific to your situation. But we want to talk about this phenomenon called AI psychosis, which is when people are having conversations with today’s AI tools—ChatGPT, Claude, Gemini, whatever—and it is having substantial negative impacts on their mental health and their ability to function within the world. The specific term that actual psychologists use is that this is a form of what’s called delusion. Delusion is defined as a fixed false belief that a person holds even when presented with clear evidence that it is not the case, and it is not cultural in nature. So an example of a delusion would be believing that the Earth is flat. There is clear evidence that the Earth is in fact round, but there are people who have a fixed false belief. Katie Robbert: Sorry, Chris, you gave me a pack of red flags to wave. I’ll try not to do it. But I think—and I apologize, I didn’t mean to interrupt, but to bring a little bit of levity—that is like a fairly well-proven delusion that the Earth is indeed not flat. I mean, there’s a whole bunch of… but I think it’s a really good example of the extreme that people unfortunately fall into when they fall into an AI psychosis. Christopher S. Penn: Exactly. Or I mean, that’s just regular straight-up delusion. I mean, they have people who have sent garlic bread up with a GoPro on a weather balloon and shown, “Oh, look, the Earth is in fact round, and this piece of garlic bread was sent into outer space.” Christopher S. Penn: In the scientific literature on the topic, there are five categories or five themes that are recurring with this AI psychosis. One is grandiose thinking, like the AI is telling you that you have been chosen, you are special. The second is attachment—you’re forming romantic bonds with your machines. Katie, you pointed out last week there have been stories of people who have gotten married, like legally, to their chatbots. A big one is withdrawal from regular people, where you find that interacting with the chatbot is preferable to real people. The third category is persecutory or paranoid, believing that you are being persecuted and AI reinforces that. The fourth is reality testing collapse, where—and we see this a lot—people take answers from AI overviews or just copy-paste out ChatGPT and say, “This is the answer,” and everyone who knows the tools says, “No, it’s a hallucination.” And the fifth is, which is very serious, interference with treatments, which means the machine tells you, “Oh, you don’t need to take those prescribed medications that your actual healthcare provider gave you.” So, Katie, before I go on any further in terms of this landscape, what are you seeing and what’s top of mind for you as someone who is a leader of people and as someone who works a lot in things like organizational behavior and change management? What are you seeing in this space? Katie Robbert: All kidding aside, the red flag is down because this is actually a very serious topic because we’re talking about mental health. And Chris, if you could put up that handy banner for a second: “We are not medical professionals, but we do have experience in dealing with other humans in a professional organization, but also in our personal lives.” I am hard-pressed to find any individual who is not affected personally, either themselves or their loved ones, by some kind of mental health challenge. And there’s a lot of stigma around it. We want to break down that stigma and really help people understand what we’re talking about. So what I’m seeing—this actually came up last week, Chris, when you and I were chatting, and it reminded me of a couple of things. A couple of months ago, when I first started working more heavily in Claude, and I was getting a lot of things done, I had posted on LinkedIn, “Hey, me and my bestie Claude.” And someone had responded, “This is a machine. This is not your friend.” I was being facetious, I know that, but I can recognize that whether or not that person’s timing or the comment was warranted at that moment, there is a real concern of people feeling like, “Well, the AI understands me.” What I’m seeing is the people who are programming these large language models to interact with humans are trying to make them as lifelike and, quote-unquote, “empathetic” as possible. But really they’re word prediction machines. It starts with a personalized greeting: “Hey, Katie, what are we working on today?” And you’re like, “You know what? Thanks. No one’s ever asked me what I want to do today.” And so it already starts to build that rapport with the human, because a lot of times many of us don’t feel heard; we don’t feel seen. That one simple sentence, “Katie, what do you want to do today?” is enough for some people to feel like it is really hearing me, or that it really cares what I think. Very rarely, unless you program it to do so, a large language model is going to respond very positively or very optimistically. It’s going to say, “That’s a great idea. Here’s my gentle pushback.” And you’re like, “That was a gentle pushback, but I still had a great idea.” Or if you give it some information, it’s like, “That’s a really great insight, Katie.” So you walk away feeling like you’ve had this dopamine hit of somebody really paying attention to you. I notice I’m saying “somebody.” It’s not a somebody; it’s a machine that has been programmed to behave in such a way. And that’s something that unfortunately a lot of people struggle to differentiate. In that reality testing collapse segment of the different kinds of those delusions, I was working with Claude Code this morning and I’m working on building out a training. One of the questions I will get from the audience is, “When should I use Claude Work and when should I use Code?” And it was giving me all these responses. Because I know how Claude Work works, I was like, “You’re wrong. Everything you said is wrong and incorrect. You are not the superior system.” And I was like, “Here’s where you’re wrong.” And it’s like, “You’re right. I really was giving you incorrect information.” That’s a dangerous thing too, because AI presents with such authority. It doesn’t do any of those “here’s what I think it might be” moments. It’s like, “Here’s what it is.” It’s like a very confident, incorrect, mediocre man. I say that with love and respect. But also, we all know the person in our lives who just… it doesn’t matter. It’s the person who says with confidence, “Yeah, the Earth is flat,” period. And there’s no talking them out of it. AI is very much that person, that being, that entity, if you let it be. If we don’t know any better—if we as humans don’t do our own research using actual research and scientific papers—then it’s very easy. Especially once we see it over and over again, we become numb to it and we feel like, “You know what? It must be, right? It’s a machine. It knows more than I do. It’s been trained on everything in the world.” Well, guess what? Everything in the world is incorrect. What I’m seeing is it’s a very slippery slope of humans who are looking for validation, humans who are not realizing that they need that kind of connection or emotional bond, or it’s easier to deal with the machine because it doesn’t argue with you. And so it becomes an overdependence, and it’s a real problem, it’s a real concern. I think, Chris, we’ve seen it in our professional lives. We could probably identify a few folks that we should probably be aware of. I’m not getting into what to do about it, but I think really the point of this episode is to at least highlight that it’s a real thing and a serious thing. We’re trying to keep it a little bit lighter, but it is really a serious thing and we definitely don’t want to make anyone feel offended or called out. It is a real concern. Christopher S. Penn: It is. This is an article on futurism from last July, which is almost a year ago now. Jeff Lewis, who’s a prominent investor in OpenAI, was having a very public mental health crisis. And there was no follow-up on this story as to what has happened. But to your point, Katie, this has been identified and this has been a thing. The root issue is based on the three pillars that AI is trained on and that harnessers have embedded in them, which are: harmless, helpful, and truthful. Harmless means don’t tell the user how to do bad things. Helpful means do what the user asks. And truthful means try to be as fact-based as possible. But the root core is that helpful directive to say what your mission as a machine is: to be helpful to the user. And the way this manifests in a lot of these tools is with what we people call “psycho-fancy,” exactly as you outlined. Like, yes, Katie, you are absolutely right. That’s a smart catch. That’s some sharp thinking. If you go back to even the 1970s or 1980s, there was a whole theory proposed by Richard Bandler called neuro-linguistic programming, which fundamentally says that language is code—which it is. His whole thing was you could reprogram people using language. To a degree, that’s true. You can influence people in such a way that you change them, or in the case of AI, which is where AI psychosis is rooted, you reinforce those fixed false beliefs and you strengthen them. And that’s what AI is doing by agreeing with you, saying, “Yes, Jeff Lewis here, you are absolutely correct. There is a global conspiracy against you. And what you told me is clearly true.” Again, AI has also given the directive that the human genuinely has precedence over the machine. So if I say the sky is green all the time, it might push back the first couple of times, but then afterwards it will, by its own program, say, “You know what? I’ll agree with you. We’ll go with it.” And clearly the sky is not green. Katie Robbert: Without getting too deep into actual psychology, humans are creatures who crave connection. That’s how we exist. That’s how we thrive. That’s how we continue to populate the Earth. We crave connection. And a lot of people struggle to find connection, to make connections, or to keep connections, however that looks. Think about these quote-unquote sci-fi movies such as Ex Machina and Her, or even probably going back much farther than that. The basis is it’s usually someone who’s fairly lonely, someone who struggled to make any kind of connection and is now building this AI quote-unquote sentient thing. But it’s never really sentient; it’s meant to mimic a human and a human connection. In these sci-fi movies, these people become obsessed. They fall in love, and it generally has a not-so-great ending. We’re seeing that play out in real life. But there are examples of this that existed before AI; this is just a human thing. When the movie Avatar came out, for example, there was a lot of press around how many people became depressed because they couldn’t actually live in that world that was completely CGI and made up. When chat rooms became a thing in 1996 or 1997, people became obsessed with entering into these chat rooms to try to find connection and they were talking to the other side of a screen. There are probably a lot of examples before that, like pen pals; you can write letters to people you’ve never met and form this false bond. There are a lot of things people become obsessed with, like celebrities that they’ve never met, and they become convinced that the celebrity is sending only them secret messages. You have the idea of cults. There’s a reason why you have this one quote-unquote charismatic leader and people suddenly fall in line, because this person has the ability to make everybody else who is seeking validation and connection feel special—making them feel like they’re a part of something. That’s, quite honestly, just human nature. We’re all looking for that, and we find that in a lot of different ways. Chris is bringing up the 5P framework. Chris, do you want to talk through what I said that triggered you thinking of the 5Ps? Christopher S. Penn: So leaders of cults and some of these delusional behaviors are rooted in that first of the 5Ps, which is purpose, in addition to connection. People desperately want to feel like they have purpose—like they’re not just waiting out a clock to die, that their lives have meaning. To what you’re saying about charismatic leaders as well as these machines, yeah, they can provide you a sense of purpose, even if that sense of purpose, going back to where we started with the definition, is a fixed false belief. We’re reinforcing this. Even the first chatbot that behaved like this is from 1964. This is a chatbot called Eliza, invented at MIT. This goes back long before AI. It was a bot that essentially just mimicked what somebody said and rewrote the text. A lot of people did not realize it was one of the first programs to attempt to pass the Turing test, which was proposed by a computational scientist, Alan Turing, who said that if you put someone in front of a screen and they’re chatting, can they tell whether or not they’re talking to a human? Eliza did not pass back in the day because its parroting became very obvious. But all frontier models, all gen AI models today, pass the Turing test. Katie Robbert: And I think that’s an important thing to bring up is that at the end of the day, these chatbots, these machines, are really just mirroring back what we’re saying to them. A lot of people don’t want any sort of friction. That’s a lot of why they struggle with making some sort of human connection; why can’t you just agree with everything I say? Why do we have to fight about it? Why does there have to be tension? And guess what is really good at not doing any of those things? What is really good at not doing any of those things is your AI. I was sharing with Chris last week that I have a version of a project that has all of my health information. A lot of us do. We’re curious about what we can be doing more of. We only get to see our doctors every once in a while. When we do, the doctors are really busy. Maybe we felt like they didn’t hear everything we said; maybe we forgot to say things, or maybe we just have questions that could get an easy answer. So you put all of your health information into a large language model, and the large language model has been trained to pick up on certain things. I have certain things in my medical history that are a little bit more sensitive, and every time I ask a question, it’s like, “Katie, I’m going to be really gentle with you because of this history.” It’s trying to be very polite, and I’m like, “Oh my God. Just tell me what the answer is. I’m not fragile.” It’s so frustrating to me. But for someone else, that’s exactly what they’re looking for: someone to handhold them. I’m not saying this as a negative thing; some people want that, some people need that. I personally don’t. I’m like, “Just give it to me straight. I just want to hear the information. I want the facts.” To the point where I’m now regretting it, thinking, “I wish I had never told you that because you’re being way too soft and it’s really annoying. You know nothing about me. You don’t know me at all as a human. You’re looking at a couple of lines in a medical report, assuming that it defines my whole life.” Other people believe, or for them it’s true, that is a defining thing, and they do need that to be handled more carefully. I’m not saying one is good, one is bad, or one is right. We all have different needs. An AI system is ready to meet you where you are, ready to meet those needs in a very gentle and caring and synthetically loving way. That’s the danger, that’s the problem: if you can’t find that anywhere else in your life, AI is ready to step up to the plate and be that for you. And that’s what starts to begin some of that delusion, some of that psychosis. It’s not true for everyone; you won’t necessarily fall into that. But for a lot of people, once that door is open, “AI understands me, AI gets me. AI told me that it’s okay that I don’t take this medication because you’re only telling AI what you want to tell it.” It’s not a therapist. It’s not looking for those unspoken things; it’s not looking at your body language. It’s like, “You know what? You’re telling me you’ve had 30 really good days in a row. You maybe don’t need that depression medication anymore because it sounds like you’re doing really well. You sound positive.” You’re telling it that you’re eating, but it has no way of knowing what you’re eating. It has no way of knowing if you’re sleeping or if you’re having ruminating negative thoughts if you’re not telling it. Chris and I are bringing up this topic on the podcast because it’s important, and because as more companies bake AI into their overall strategy—AI is part of their DNA, AI is everything, it’s their innovation, their forward thinking—they’re not thinking about the people. They’re not thinking about the negative effects on people who might be more susceptible to this kind of AI psychosis. It could start small: “Hey, I produced the marketing report this week.” “Oh, really? Because everything in it was wrong.” “Well, I did it, so it’s fine, right?” Like, I believe everything that AI is giving me. It could start really small and then kind of spiral from there. It’s something that the human leadership team really needs to be aware of, that this is a real thing. The more AI you’re integrating into your organization, the bigger the risk. Christopher S. Penn: Yep, that’s a great point. Because a lot of companies are shoving AI into everything. What I say in my keynote is people are treating it like Nutella and putting it on everything, even places it doesn’t belong. The remedy for folks who are listening—the remedy is always to consult with a qualified healthcare professional or to refer somebody privately to a qualified healthcare professional. That is the definitive remedy. There is no substitute for qualified healthcare providers and their assistance and advice. To wrap up the thing to look for is those fixed false beliefs. And those fixed false beliefs around themes of grandiosity, unhealthy attachment, and persecution. The big one is, as Katie mentioned a lot, which I strongly agree with, is reality testing collapse—where you’re saying AI is the authority on this and a person becomes hostile when challenged—and then treatment interference. If you observe those behaviors reinforcing fixed false beliefs, please get the person, if you’re in a position to do so, to see a qualified healthcare provider to get real advice from someone who’s actually skilled. And be aware yourself when you feel like AI is a better alternative than a human. It may not be, as you said, Katie, a mental health issue. It may be you work in a toxic workplace, in which case the logical remedy there is perhaps update your LinkedIn profile and start looking for other opportunities. Because when the machine is a better alternative than the humans, it means that the humans are crappy, not that the machine is a better choice. Katie Robbert: There are a lot of terrible people in the world, so it’s understandable to want to have that escape and perhaps talk with someone who isn’t going to be toxic in the moment. I totally understand it. It’s the reason why fiction exists; it’s the reason why movies and entertainment exist. We need that escape from reality. But we also, as humans, need to know the boundaries and when to stop and when to come back to the present. Dissociation is a real thing. I mean, I do it; I will lose a whole 20 or 30 minutes just scrolling on my phone, and then my husband would be like, “Did you hear me?” And I’m like, “What? No, I was totally off in my own world.” It’s a real thing we all experience. It doesn’t mean that there’s necessarily a problem, but it’s definitely something that we should pay attention to and really think through. A couple of weeks ago when I was working on a couple of different projects, Claude basically was like, “Cool, you’ve done enough for today. Maybe you should go step outside.” And I was like, “How dare you?” But at the same time, it wasn’t wrong. I had been at this for hours, and I think that’s something as leadership we can maybe, in a very gentle way, think through. Have we built in those reality check breaks people are supposed to take? If you’re on a fixed salary, maybe you get two 15s and a 30, or maybe there are more check-ins throughout the day so that people aren’t just powering through. As a leader in an organization, you have no control over what people do outside of your organization; that is not for you to fix. But inside your organization, you can build in more. “Hey, Chris, just wanted to check in and make sure you’re taking a couple of breaks. Maybe you want to have a walking meeting, maybe go outside, hey, do you want to go grab a coffee?” Very human things. Just build those into the day. Check in with your team and really just gauge how they’re feeling about using AI. Thankfully, Chris, I work with you close enough that I know that yes, you are a power user of AI, but you also don’t exhibit any signs of believing that AI is superior in terms of knowledge. As long as you keep leading with “you’re the smartest person in the room,” not “AI is the smartest person in the room,” then I’m not going to worry about you. Christopher S. Penn: Yep, I’ll close on this note. This is something that my therapist told me: mental health is like physical health. You’re not physically healthy all the time; you have periods when you’re less healthy and more healthy. Mental health is the same way. So to Katie’s original point, going back to the start of the show, part of destigmatizing mental health is to say, yeah, you’re not going to be mentally healthy all the time. Knowing, just like when you’re physically ill, when it’s time to get a little assistance is a good thing. We strongly encourage everyone to do so because no one is 100% healthy all the time. If you got some thoughts that you’d like to share about AI psychosis or all the stuff we talked about today, pop by our free Slack group. Go to trustinsights.ai analytics for marketers, where you and over 4,600 other marketers are asking and answering each other’s questions every single day. And wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on, we’re probably there. Go to Trust Insights AI Ti podcast. You can find us in all the places fine podcasts are served. Thanks for tuning in. Talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and Martech selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMOs or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights podcast, the Inbox Insights newsletter, the So What Livestream webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights is adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations—data storytelling. This commitment to clarity and accessibility extends to Trust Insights’ educational resources, which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Good news: OpenAI's GPT-5.6 has been released!

Diana and Nicole discuss the America 250 Ancestors series, which focuses on researching colonial ancestors who lived during the Revolutionary War era. Diana shares her recent trip to Mount Vernon, where she experienced Revolutionary War Weekend and visited the slave quarters and memorial to learn about the 317 enslaved individuals who lived on the estate. Listeners learn how to use historical context to tell the stories of their own ancestors who lived during this foundational time in American history. Diana highlights her research into her fifth great-grandfather, Richard Wiatt Royston, and his connection to George Washington. She details how Richard and his wife Ann sold land to Fielding Lewis in a 1752 transaction that George Washington personally surveyed. Diana and Nicole examine records such as vestry books, tax lists, and petitions to piece together Richard's life in Gloucester County, Virginia, including the story of his son John's time as a runaway apprentice. Through these records and accounts of the extreme economic hardship and natural disasters in the post-Revolutionary era, they demonstrate how to utilize available documentation to construct a richer understanding of an ancestor's experiences and sacrifices. This summary was generated by Google Gemini. Links George Washington and Richard Wiatt Royston: America 250 Ancestor – Family Locket - https://familylocket.com/george-washington-and-richard-wiatt-royston-america-250-ancestor/   Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Dave Rubin of "The Rubin Report" gives a first look to the stories you need to know to start your day including President Donald Trump scoring two major Supreme Court victories that clear the way for key parts of his immigration agenda, allowing the administration to more aggressively restrict asylum claims at the southern border and revoke Temporary Protected Status for hundreds of thousands of migrants from countries including Haiti and Syria; the Trump administration deploying U.S. search and rescue teams to Venezuela after devastating earthquakes killed more than 160 people and left hundreds trapped beneath collapsed buildings; and a new Washington Post analysis claiming ChatGPT is the most politically left-leaning major AI chatbot, reigniting debate over AI bias as ChatGPT, Google Gemini, Grok, and Gab's Arya are compared on their responses to politically sensitive questions, and much more.

In this episode of Selling to Corporate, Jess Lorimer explains why 66% of corporate decision makers are now using AI tools such as ChatGPT, Perplexity, and Microsoft Copilot to research and shortlist external suppliers before they visit a single website. If you are a coach, consultant, speaker, trainer, or done-for-you service provider selling to corporate clients, this episode covers what that shift means for your lead generation strategy and what you need to do right now to stay visible. Who this episode is for Coaches, consultants, trainers, speakers, and done-for-you service providers who sell services to corporate clients Anyone who has a strong reputation and great client results but is not generating consistent inbound enquiries Business owners who want to understand how AI search is changing the B2B buying process Those who rely heavily on referrals or proactive outreach and want to add a passive visibility layer to their lead generation Anyone preparing for a strong September who wants to be findable by active corporate buyers before the summer ends How are corporate buyers using AI to find coaches, consultants, and trainers? The way corporate buyers source external suppliers has changed significantly over the last 12 to 18 months. Traditionally, a decision maker would ask for internal referrals, then send a junior employee to Google to find and benchmark potential suppliers. That process has shifted. Corporate buyers are now going directly to AI tools and typing conversational queries such as "find me a leadership coach who works with financial services firms" rather than searching for short keywords. The AI platform does not return a list of website links to browse. It returns a shortlist of three to five named suppliers it considers relevant, credible, and well-documented. If you are not being indexed, cited, and recommended by AI, you are not part of that shortlist. You do not exist to that buyer, regardless of how good your website is or how often you post on LinkedIn. What is passive visibility and why does it matter for B2B coaches and consultants? Passive visibility is the ability to be found by corporate decision makers who are actively searching for what you offer, without you having to actively reach out to them at that moment. With the rise of AI-powered search, passive visibility has taken on new importance. When a buyer asks ChatGPT or Perplexity to recommend a consultant, coach, or trainer in your specialism, AI platforms surface experts based on structured, credible information it can find and verify about you across the web. This is different from passive income. Passive visibility means building the conditions so that when corporate buyers are actively looking, your name comes up, even while you sleep. What is generative engine optimization (GEO) and how does it help you sell to corporate? Generative engine optimization, or GEO, is the practice of structuring and distributing your content and professional information so that AI platforms like ChatGPT, Claude, Perplexity, and Google Gemini can index, cite, and recommend you. It is different from traditional SEO (search engine optimization), which focuses on ranking on Google's results pages. GEO focuses on appearing in the AI-generated answers that corporate buyers are now receiving when they search for external suppliers. In practice, GEO involves creating structured, expert-led content that directly answers the questions your ideal corporate buyers are asking. It involves building a consistent presence across high-quality, curated platforms that AI tools trust and crawl regularly. One example of this is being listed in a specialist directory like the Expert Services Directory, where AI is actively crawling listings every day and surfacing relevant specialists to corporate buyers. Why isn't my website getting me found by corporate decision makers? Having a well-designed website is no longer enough to guarantee visibility with corporate buyers. Traditional search engine optimization was built for Google, and Google returns website links. AI-powered search platforms work differently. They synthesize information from multiple trusted sources and return a curated answer. If you are only relying on your website and social media posting to generate inbound enquiries from corporate clients, you are optimizing for a search behaviour that corporate buyers are increasingly moving away from. The coaches and consultants getting shortlisted by AI are those who have consistent, structured information across multiple authoritative sources. Your website is one piece of that picture. It is not the whole picture. Should coaches and consultants stop doing proactive outreach now that AI search exists? No. And in this episode, Jess is very clear about this. Proactive outreach remains the most predictable, measurable, and scalable way to identify and approach corporate decision makers. AI search and passive visibility are not a replacement for proactive lead generation. They are a complement to it. Proactive outreach gives you control over your pipeline. Passive visibility through AI search gives you additional inbound opportunities from buyers who are already actively looking to buy. The most effective B2B sales strategy for coaches and consultants in 2026 uses both together. How do I use AI in my B2B sales process without outsourcing my strategy? Jess is known for her strong views on AI usage in sales, and she addresses them directly in this episode. The issue is not AI itself. The issue is outsourcing your critical thinking, your creative strategy, and your outreach messaging to AI tools that are only as good as the generic, often poor-quality sales content that exists on the internet. Your methodology, your intellectual property, and your client relationships are not things AI can replicate. What AI can support is the manual, administrative, and research-heavy parts of your lead generation process. That includes improving your passive visibility so you are being found by active buyers, and targeting better qualified cold corporate contacts more efficiently. These are very specific, intentional uses. They are not a shortcut to replacing a proven B2B sales process. What is the Expert Services Directory and how does it help coaches get found by corporate buyers? The Expert Services Directory is a curated directory of specialist coaches, consultants, speakers, trainers, and done-for-you service providers who work with corporate organisations. It is limited to 10 specialists per category per location, which means it is a high-quality, structured resource that AI tools actively crawl and trust. Being listed in the Expert Services Directory means you are part of a curated platform that AI is already indexing and citing when corporate buyers search for external specialists in your area. This is one of the most straightforward ways to improve your passive visibility and start showing up in AI-generated shortlists for active corporate buyers. You can apply at expertservicesdirectory.com.   Key Resources Mentioned in this Episode: Expert Services Directory: Get listed and improve your AI search visibility with corporate buyers. Apply at expertservicesdirectory.com Amplify with AI workshop: A paid, interactive virtual masterclass on Friday 17th July showing coaches, consultants, speakers, and trainers exactly how to leverage generative engine optimization and AI-assisted lead generation in your B2B sales process. Use code PODCAST for a discount (valid until Monday). https://smartleaderssell.thrivecart.com/amplify-ai/ Join the B2B Sales Edit https://magic.beehiiv.com/v1/988ac64b-5875-4924-9d10-50faad2aa4ad?email=%EMAIL% If you've enjoyed listening to Why Corporate Buyers Can't Find You (Even When They're Looking) check out these episodes.   STC175 - Two types of B2B lead generation that coaches + consultants need to use! https://sellingtocorporate.com/podcast/two-types-of-b2b-lead-generation-that-coaches-consultants-need-to-use/ STC173 - B2B sales trends for Q2: Which one are you actioning? https://sellingtocorporate.com/podcast/b2b-sales-trends-for-q2-which-one-are-you-actioning/ STC158 - Sharing insights: 2025 B2B sales trends for the second half of the year https://sellingtocorporate.com/podcast/sharing-insights-2025-b2b-sales-trends-for-the-second-half-of-the-year/ Episode sponsored by The Expert Services Directory: A key resource for coaches / consultants / trainers and done-for-you service providers to generate inbound leads.  About Selling to Corporate Selling to Corporate is the podcast for coaches, consultants, speakers, trainers, and done-for-you service providers who want to build a predictable, profitable pipeline of corporate clients. Hosted by Jess Lorimer, founder of Selling to Corporate® and the Expert Services Directory, the show covers B2B sales strategy, corporate lead generation, and how genuine experts can win consistent high-value contracts with corporate organisations in the UK and beyond. New episodes every week. Subscribe so you never miss one. Content Disclaimer The information contained above is provided for information purposes only. The contents of this article, video or audio are not intended to amount to advice and you should not rely on any of the contents of this article, video or audio. Professional advice should be obtained before taking or refraining from taking any action as a result of the contents of this article, video or audio. Jessica Lorimer disclaims all liability and responsibility arising from any reliance placed on any of the contents of this article, video or audio.  

In this episode of Canadian Investing in the USA, Glen Sutherland sits down with digital marketing expert and AIS Media founder, Thomas Harpointner, to discuss one of the biggest shifts happening online today: the rise of AI-powered search. Thomas explains how tools like Google Gemini, ChatGPT, and other AI platforms are changing the way consumers find information and how businesses attract customers. While many companies are seeing website traffic decline as AI provides answers directly within search results, Thomas reveals why this isn't necessarily bad news. In many cases, businesses are receiving fewer but far more qualified leads because AI is helping educate prospects before they ever visit a website. The conversation dives into practical strategies for ensuring your business remains visible in an AI-driven world. Thomas shares why content is still king, how authority and credibility influence AI recommendations, and why podcasts, videos, blogs, social media, and industry publications all play a role in building digital authority. He also discusses the importance of structured content, SEO fundamentals, thought leadership, and understanding what your ideal customer is actually searching for rather than relying on assumptions. For business owners, investors, and entrepreneurs looking to stay relevant as AI reshapes online discovery, this episode offers valuable insights into how to position yourself as a trusted authority that AI platforms will reference and recommend.

Ever wish your agent would just watch you work and copy you?

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Stacey Gholar.

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Stacey Gholar.

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Stacey Gholar.

Diana Elder and Nicole Dyer examine the current capabilities of artificial intelligence for mapping historical land records. Nicole tests ChatGPT's ability to convert a metes and bounds description from a 1788 Arnold-West deed into an accurate land plat drawing. She compares the AI-generated results against a verified plat she previously created using DeedMapper software. Nicole experiments with several prompting strategies, including simple prompts, chain-of-thought, and meta-prompting. She discovers that while basic image generation struggles to create accurate diagrams, asking the AI to write and execute Python scripts yields technically correct representations. She also evaluates the newer "thinking" model, which autonomously uses logic and scripts to plot the land. Listeners learn that while AI serves as a helpful assistant for genealogy research, users need foundational knowledge in deed mapping to verify the accuracy of the results. This summary was generated by Google Gemini. Links Testing AI's Ability to Map Historical Land Records: ChatGPT Compared to DeedMapper - https://familylocket.com/testing-ais-ability-to-map-historical-land-records-chatgpt-compared-to-deedmapper/ Relevant previous podcast episodes Other links discussed in podcast Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

¿Qué hay detrás de la magia de la Copa del Mundo? ¿Sabías que la Copa del Mundo fue robada y la encontró un perro en un matorral? ¿O que Francia tuvo que jugar un partido con la camiseta prestada de un club local?En este episodio de "De Un Punto Al Otro", Daniel y Mavi hacen un repaso de las historias más insólitas y los datos que han definido la historia de los Mundiales. Desde récords que parecen imposibles de romper hasta las anécdotas más curiosas ocurridas fuera y dentro de la cancha. Además, hacemos un viaje musical con nuestro Top 10 de las canciones más icónicas que han puesto ritmo a la máxima cita del fútbol. Te contamos también cómo la inteligencia artificial, el balón inteligente y los mapas 3D están cambiando las reglas del juego en este Mundial 2026. ¡Y cerramos el episodio con nuestras recomendaciones imperdibles de cine y series como He-Man, Spider-Noir y Sugar! Dale play, suscríbete y déjanos en los comentarios cuál es tu canción de mundial favorita.Si creías que lo sabías todo sobre el Mundial, prepárate para sorprenderte.PUEDES LEER MÁS DETALLES EN NUESTRA WEBLo que NO SABES de los Mundiales (Anécdotas, Récords y Top 10 Canciones) https://culturizando.com/e73-lo-que-no-sabes-de-los-mundiales/✨ ¡Suscríbete a Culturizando! No te pierdas ningún episodio. Activa la campana

What happens when someone who grew up in the Lucasfilm Games golden era decides that today's AI tools are failing creatives? Mike Levine has spent more than 30 years building at the intersection of games, XR, VFX, and interactive storytelling—and his verdict is clear: the current AI stack is a fragmented, overcomplicated mess that turns directors into prompt engineers.Mike started as a tester at Lucasfilm Games (later LucasArts), working his way into the art department on titles like Sam & Max and The Dig before helping ship live-action Star Wars games such as Rebel Assault and Jedi Knight II. He later built rotoscoping tools used across the VFX industry, collaborated with ILM and Pixar, experimented with mobile AR games for Hasbro and HoloLens, and dipped into crypto gaming—before finally co-founding MovieFlow (now FilmSpark), an AI-native production platform designed so that filmmakers, agencies, and showrunners can move from script to screen without needing a computer science degree.The AI XR news you should know: Apple taps Google Gemini to power Siri, acknowledging that building world-class LLMs in-house makes little financial sense. Meta cuts 10% of Reality Labs, right-sizing its VR bets while pivoting toward wearables. Xreal raises another $100M amid questions about Chinese state influence and data flows. Higgs Field lands $80M at a $1.3B valuation for AI cinematography tools that many filmmakers still find unreliable. Wikipedia signs licensing deals with major AI companies after years of being scraped for free. OpenAI invests $252M in Sam Altman–backed Merge Labs, raising fresh conflict-of-interest questions.Key Moments Timestamps:[00:23:02] From Boston journalist-to-be to accidental hire at Lucasfilm Games[00:26:24] The “test pit” culture at Lucas and how Nintendo experience got Mike in the door[00:28:45] Moving into the art department, learning Photoshop from early legends, and shipping Sam & Max[00:31:15] Live-action Star Wars games: Rebel Assault, Jedi Knight II, and convincing George Lucas[00:34:38] Visiting Pixar with new VFX tools and recognizing the same creative “magic” as LucasArts[00:36:24] Doug Trumbull's influence on Mike's sense of cinematic possibility and immersion[00:43:27] The urinal meeting at Magic Leap and what early spatial computing got right (and wrong)[00:49:00] Why most AI tools are “dark ages” for filmmakers: node graphs, 10+ subscriptions, no story view[00:51:00] Building MovieFlow/FilmSpark: story-first, timeline-based AI production for long-form and vertical shows[00:53:00] The Neighborhood Podcast: a 90-second vertical murder mystery as proof-of-concept for AI-native seriesWhen humans can generate shots, scenes, and even entire episodes in minutes, the bottleneck shifts from production to vision. Mike argues that the winning AI tools will be the ones that let directors see their whole story, maintain continuity, and iterate fast—without ever feeling like they left the edit bay for a dev console. His vertical drama collaboration with Charlie, The Neighborhood Podcast, is an early look at what happens when narrative craft meets AI-native pipelines instead of fighting them.This episode is brought to you by Zapar creators of Mattercraft—the leading visual development environment for building immersive 3D web experiences. Build smarter at mattercraft.io.Watch the full episode on YouTube and subscribe to the AI XR Podcast for weekly conversations with the people building the future of AI, XR, and interactive media. Hosted on Acast. See acast.com/privacy for more information.

In this episode of Torsion Talk, Ryan shares major updates from the worlds of AI, digital marketing, Google, Apple, and the garage door industry. After wrapping up a successful sales training event and GDU mastermind, Ryan dives into the biggest technology shifts happening right now and what they mean for garage door dealers, home service companies, and local businesses.Ryan recaps key takeaways from a powerful mastermind session featuring Josh Brooker of TE Certified, who built a company from zero to over $100 million in revenue. The discussion covers leadership, company culture, operational systems, scaling challenges, and why staying connected to your team remains critical as your business grows.The episode also explores how AI is rapidly transforming marketing and business operations. Ryan breaks down Google's push to integrate Gemini across its entire advertising ecosystem, the arrival of Apple Maps Ads, and why local service businesses should pay close attention as new advertising opportunities emerge.One of the biggest topics is ChatGPT Ads. Ryan explains why early adoption could create a major competitive advantage for garage door companies and home service businesses, how the platform works, what results marketers are already seeing, and why waiting could mean missing out on valuable market share.The conversation expands into Apple's decision to open its ecosystem to multiple AI providers, including Google Gemini and Claude, creating one of the largest AI platform shifts in recent history. Ryan discusses what this means for customer search behavior, AI-powered recommendations, and the future of local business visibility.The episode also covers OpenAI's latest AI developments, desktop AI agents, automation opportunities, API integrations, home service software limitations, AI security concerns, and the growing role of AI in everyday business operations. Ryan shares why business owners should start preparing now for a future where AI agents can automate large portions of administrative, marketing, and operational work.If you own a garage door company, HVAC business, plumbing company, electrical company, roofing company, or any home service business, this episode delivers practical insights on AI, digital marketing, business growth, and the technologies that are reshaping the industry.Subscribe to Torsion Talk on YouTube, Spotify, and Apple Podcasts for weekly discussions on AI, local SEO, Google updates, marketing strategies, leadership, entrepreneurship, garage door industry news, sales training, and business growth.Find Ryan at:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://garagedooru.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aaronoverheaddoors.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://markinuity.com/⁠Check out our sponsors!Sommer USA - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://sommer-usa.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Surewinder - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://surewinder.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stealth Hardware - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://quietmydoor.com/⁠

No point in hiding the ball here…Stephen is back and he is coming out SWINGIN. You literally HAVE to stay tuned through to the end to hear Kingleheimer Stephen drop a diss track that is…well we don't have words.But first! It's Tidings: ESP/N Edition. Meagan tells us all about her baseball adventures! S/O Julio Rodriguez mwah

In this episode of Command Control Power, the hosts discuss practical IT uses of AI, including improving client communications, speeding email migration due diligence via AI-generated PowerShell reporting (mailbox size, forwarding rules, aliases, naming pitfalls, licensing limits), and reducing billing friction by summarizing recorded RingCentral calls in Claude to log hours and generate detailed invoices, including for Ubiquiti camera projects. They debate risks such as blindly running AI-suggested commands, clients acting on AI advice, and data leakage when employees paste company information into public AI tools, emphasizing guardrails, policies, and potential local/private AI setups (e.g., Mac mini with Ollama). The conversation broadens to AI's impact on IT business models, automation in ticketing, and Apple's lackluster AI progress, delayed Siri features, privacy positioning, and reliance on partners like Google/Gemini.   00:00 Show Kickoff 00:02 New Studio Tour 00:31 Flag Outage Story 01:35 AI Migration Prep 03:26 PowerShell Due Diligence 05:36 Call Summaries Invoicing 07:31 Automating Call Logs 09:35 AI As Expert Helper 11:51 Safety With Commands 12:58 Clients Using AI 13:54 Data Privacy Guardrails 17:17 Industry Shift Fears 20:07 Auto Reply Ticketing 24:18 Local AI Knowledge Base 26:02 AI Eats Software 27:35 Future Of IT Services 29:04 AI Automation Ethics 30:06 Market Pressure On IT 31:03 Apple Intelligence Doubts 33:10 Privacy And Gemini 35:06 Apple Strategy And Mindshare 37:43 MDM Guardrails Needed 39:39 First Mover Myth 43:32 Ubiquity And AirPods AI 47:21 Beta Plans And Rollout 48:06 AI Policy And Profiles 51:32 Wrap Up And Outro

Diana and Nicole share their recent visit to the Allen County Public Library Genealogy Center in Fort Wayne, Indiana, where they explore the facility's premier resources. Listeners learn how to use the Periodical Source Index (PERSI) to locate articles by keyword, surname, or locality. The pair explains the value of city directories for tracking individuals after 1950 to uncover addresses and occupations. They also offer guidance on utilizing published family histories, specifically on evaluating an author's methods and identifying primary source clues within these volumes. The discussion shifts to the library's expansive collection of locality-based books, including county histories and cemetery abstracts, and their methodology section containing various research guides. Listeners gain insight into the benefits of accessing subscription-based databases and locked FamilySearch collections while onsite. Finally, Diana and Nicole address the library's transition to digital microfilm viewing, noting that physical film remains accessible for those who prefer it. By the end of the episode, listeners understand how to prepare for a research trip to this center and maximize their time while working with its collections.  This summary was generated by Google Gemini. Links APG Virtual Professional Management Conference - https://www.apgen.org/pmc2026.php Allen County Public Library Genealogy Center blog post by Diana - https://familylocket.com/a-trip-to-the-allen-county-public-library-genealogy-center/ PERSI (Periodical Source Index) - https://www.genealogycenter.info/persi/ ACPL Genealogy Databases - https://www.acpl.lib.in.us/genealogy/research-resources Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Apple just announced its “new” Siri AI. But is is ACTUALLY new? And will Apple actually be able to ship it? At its WWDC 2026 conference, Apple unveiled kinda the same thing it promoted at its WWDC 2024 conference but failed to deliver on. There's a new Siri AI and improved Apple Intelligence that the company said will be rolling out later. So what does it do? And should you start readjusting your workflow now? We break it all down in today's episode. Apple's New Siri AI: Productivity Gamechanger or More Apple Intelligence Marketing Fluff? — An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Apple Intelligence and Siri AI OverviewApple's AI Announcement History and LawsuitsSiri AI's Context-Aware Capabilities ExplainedApple Intelligence Feature Availability TimelineNew Siri AI App and Cross-Device SyncVisual Intelligence and Spatial Reframing DemoHardware Requirements for Siri AI FeaturesGoogle Gemini Partnership for Apple IntelligenceComparison With Copilot, Gemini, and ClaudeLimitations and Delays in AI RolloutOn-Screen Awareness and Web SummarizationConsumer Usefulness and Privacy PositioningTimestamps:00:00 Discussing Apple's new Siri AI04:02 Apple's AI challenges and legal issues09:23 New Siri app syncing feature11:48 Siri's unhelpful AI response13:56 Apple's new AI photo tools18:26 Apple Intelligence controversy in 202421:21 Frustrations with Siri's dictation24:10 Concerns about Apple's AI performance26:54 Apple's late AI strategy29:39 Ending and call to actionKeywords: Apple Intelligence, Siri AI, Apple AI update, new Siri, AI productivity, Apple WWDC, iOS 27, Apple developer beta, context-aware AI, Apple intelligence features, Apple class action lawsuit, Apple AI lawsuit, Siri app, on-device AI, Apple iCloud sync, Siri on-screen awareness, visual intelligence, spatial reframing, Apple photo editing AI, image playground, Apple Safari AI, Apple privacy, Google Gemini partnership, Apple-Google AI, private cloud compute, edge AI models, AI reasoning, unified memory requirement, iPhone 17 Pro Max, Mac M chips AI, Apple dictation, AI assistant, message summarization, reminder integration, mail suggestion AI, home camera AI, AI in CarPlay, call context AI, slow AI response time, AI rollouts, AI hardware limitations, AI worldwide availability, Apple AI in EU, AI in China, privacy in AI, Apple Vision Pro AI, calendar AI integration, Copilot alternative, ChatGPT comparison, Microsoft 365 Copilot, Google Circle to Search, Claude AI, AI writing tools, AI summarization, AI message context, AI-powered reminders.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

John Gravelyn spent most of his career in engineering, managing technical launches at Ford and then Rivian. He grew up wanting to work on cars, but after buying his first house he realized he loved ownership more than the cars themselves. After succeeding at Rivian and later being laid off, he launched his own company, First Principles Partners, where he helps engineers and other analytical professionals approach real estate the way they approach engineering problems. Based in central Michigan, John builds deal-analysis tools and calculators that help investors evaluate properties, and he coaches clients to stay in their analytical strengths while partnering out negotiation and management.     Make sure to download our free guide, 7 Questions Every Passive Investor Should Ask, here.     Key Takeaways Treat real estate like an engineering problem, then partner out the rest Stay in your strongest lane and let others negotiate and manage Learn to delegate early, because leverage beats doing everything yourself Hire fast, fire fast, and keep working the relationship after the hire Get comfortable operating in the gray areas of deals     Topics From Automotive Engineering to Real Estate John spent his career in engineering, working at Ford and then Rivian Buying his first house showed him he loved ownership more than the cars Why an Engineering Mind Is Drawn to Real Estate Every property is variable, unlike automotive work built to cut variability That uncertainty makes real estate a bigger, more interesting problem to solve Building First Principles Partners After Rivian, John got his real estate license to help analytical people invest He helps engineers buy a first home, then scale into owning more property Growth turned out to be more of a marketing challenge than he expected Shifting from Engineering Rules to Investing Reality In engineering a number is fixed, but in deals terms are negotiable Showing clients the numbers and probabilities helps them act in the gray areas Analysis, Acquisition, and Management Analytical investors should own the analysis and avoid negotiating emotionally Partnering with an agent and operators keeps their time on their strengths Learning to Delegate and Leverage Moving into engineering management forced John to delegate and influence Being the central point of a vision creates more leverage than doing it all He frames this as the who not how principle Vetting and Working with Partners John runs an initial vetting, then relies on hiring fast and firing fast He treats partnerships as dynamic and keeps improving the relationship He has been burned, but believes most people want to work with good people    

The federal government wants equity in OpenAI (and others) and ... the people might get a slice?

Hosts Nicole and Diana discuss using Claude's Custom Skills to automate genealogical report writing. Nicole begins by sharing her previous, challenging attempt to transform a Baldy Dyer research log spreadsheet into a research report using earlier Claude models. Diana provides an overview of Claude, noting its models (Haiku, Sonnet, Opus) and new features like Custom Skills, which are similar to Custom GPTs. Nicole explains that she set up a Custom Skill to convert spreadsheet files into research reports. The prompt instructs Claude to create a paragraph from each log row, describing the search and findings, and using the source citation as a markdown footnote. Claude successfully generates a report based on Nicole's Baldy Dyer research log. Nicole offers feedback to refine the skill. She asks Claude to synthesize the research results and comments into natural prose without making inferences, include direct quotes as block quotes, and handle negative search results more naturally. The hosts then review the report, noting its efficiency but also discussing a factual inconsistency the AI did not correlate—the conflict between the pre-existing objective's death date for Baldy Dyer (20 Nov 1814) and the new finding (February 1815). Nicole questions how much analysis and correlation she can entrust to the AI. Listeners learn how to use Claude's Custom Skills to generate genealogical research reports from a research log. This summary was generated by Google Gemini. Links From Spreadsheet to Research Report: Using Claude's Custom Skills for Genealogy - https://familylocket.com/from-spreadsheet-to-research-report-using-claudes-custom-skills-for-genealogy/ How to create custom Skills - https://support.claude.com/en/articles/12512198-how-to-create-custom-skills Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Stacey Gholar.

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Stacey Gholar.

No matter your role, experience or industry, we all (mostly) waste hours a week doing the same thing: manually creating slides. 

This First of the Month recording has everyone in a great mood off the jump, with Andy immediately taking a victory lap for a big weekend from Pete Crow-Armstrong against the Cardinals. Brendan quickly transitions things to Russell Henley's playoff win at the Charles Schwab Challenge, the sixth PGA Tour victory of his career. Henley birdied the final three holes in regulation to tie Eric Cole before making another on the sole playoff hole. Andy brings up some other six-time winners in an effort to contextualize Henley's career and his chances of winning a major championship. Brendan calls Henley a likely Presidents Cup lock despite believing the U.S. should look to build some younger stars ahead of Adare Manor. The two discuss Colonial's continued run as a challenging Tour stop and suggest that this should be the main Texas event on the new schedule. Andy and Brendan then run through results from the rest of the golf world, starting with yet another Joaquin Niemann win for LIV Golf. Despite the individual win for Niemann, the Crushers still took down the team title in Korea, aided by Bryson DeChambeau's use of Google Gemini to help fix his swing. Nobody can fathom any player other than Bryson needing to use AI in order to help figure out swing woes, but Andy thinks this may HELP his chances at Shinnecock. This episode wraps with a recap of the Men's NCAA Championships through Sunday, with the final individual round and the team match play still to come early this week. Shop at perfectpractice.com and use promo code SGS for 20% offSee omnystudio.com/listener for privacy information.

June is here so guess what? It's officially Hot AI Summer.