Podcasts about deepfakes

AI investment is exploding: the “Magnificent Seven” of Apple, Microsoft, Google, Amazon, Meta, Tesla, and NVIDIA, are ploughing almost 7% of US GDP into AI and data centres. That's the same scale as the US housing boom in 2006, and greater than the dot-com bubble at its peak. Today, just seven firms make up 34% of the S&P 500, the highest concentration in history. Earnings per share in these companies grew 37% last year, compared to just 6% in the rest of the index. But history warns us, RCA in the 1920s, dot-coms in the 1990s, that transformative technologies can change the world while destroying fortunes. The question now: is AI the next revolution, or the next bubble waiting to burst? Hosted on Acast. See acast.com/privacy for more information.

Andy Murphy sits down with AI privacy advocate and content creator Dylan Schmidt to discuss the red flags and opportunities in the world of artificial intelligence, digital privacy, and surveillance. They explore how AI is shaping our lives, the risks of data collection, and what the future might hold for families and society. For more from Dylan Schmidt: https://dylanschmidt.com/  Take control of your data with DeleteMe. Because they sponsor the podcast you can get 20% off a privacy plan from DeleteMe with promo code: DAD.  OmniWatch is a scam and identity protection service that monitors your data, alerts you to threats, and backs you with up with insurance. Try it for only $1 for 7 days. Learn how to freeze your child's credit to protect their good name. Connect

Künstliche Intelligenz ist spätestens seit ChatGPT bei den meisten angekommen. Es kann einem das Leben erleichtern, oder auch zum Alptraum werden. Insbesondere durch Deep Fakes werden nicht nur Fake Videos und Fake News verbreitet, sondern oft auch Pornos und sexuelle Inhalte von Menschen erstellt, die dafür nicht ihre Erlaubnis gegeben haben und oft nicht einmal davon wissen. So auch bei der Moderatorin und Schauspielerin Collien Monica Fernandes, deren Identität geklaut wurde und mit Hilfe von Deep Fakes Männer systematisch im Glauben gelassen wurden, mit ihr eine Liebesbeziehung zu führen. Bei G Spot erzählt sie von der traumatisierenden Erfahrung, ihrem Umgang mit der Situation, sowie von den Konsequenzen und dem systematischen Problem Deep Fake. [Hier findet ihr die Doku zum Thema.](https://www.zdf.de/reportagen/diespur-deepfake-pornos-collien-ulmen-fernandes-100) Ihr habt Probleme mit Hass im Netz? HateAid hilft euch dagegen vorzugehen, weitere Infos findet ihr [hier](https://hateaid.org/) Schreibt uns gern eure Gedanken zur Folge und folgt uns auf Social Media für mehr Content! [Alle Links hierfür findet ihr hier ](https://linktr.ee/g.spot.podcast) For the Love of Love. Probiere Bumble aus. [Hier geht's lang](https://bumble.onelink.me/3396940749/73dfuqsx) Oder sendet uns eine Nachricht per Mail an: gspot@studio-bummens.de Du möchtest mehr über unsere Werbepartner:innen erfahren? [Hier findest du alle Infos und Rabatte](https://linktr.ee/gspot.podcast )

EP#103 – L'arnaque à 25 millions : quand un deepfake prend le contrôle d'une entrepriseÀ Hong Kong, une réunion en visioconférence a viré au cauchemar. Des employés croyaient parler à leur directeur financier et à d'autres cadres dirigeants. En réalité, il s'agissait de deepfakes générés par intelligence artificielle. Résultat : un virement de 25 millions de dollars a été exécuté… sans qu'aucun des vrais responsables ne soit au courant. Dans cet épisode, on raconte minute par minute cette fraude spectaculaire, on décortique les techniques utilisées par les escrocs, et on s'interroge : comment peut-on faire la différence entre le vrai et le faux à l'ère des visios truquées ?

On this episode of Crazy Wisdom, Stewart Alsop sits down with Abhimanyu Dayal, a longtime Bitcoin advocate and AI practitioner, to explore how money, identity, and power are shifting in a world of deepfakes, surveillance, automation, and geopolitical realignment. The conversation ranges from why self-custody of Bitcoin matters more than ETFs, to the dangers of probabilistic biometrics and face-swap apps, to the coming impact of AGI on labor markets and the role of universal basic income. They also touch on India's refinery economy, its balancing act between Russia, China, and the U.S., and how soft power is eroding in the information age. For more from Abhimanyu, connect with him on LinkedIn.Check out this GPT we trained on the conversationTimestamps00:00 Stewart Alsop opens with Abhimanyu Dayal on crypto, AI, and the risks of probabilistic biometrics like facial recognition and voice spoofing.05:00 They critique biometric surveillance, face-swap apps, and data exploitation through casual consent.10:00 The talk shifts to QR code treasure hunts, vibe coding on Replit and Claude, and using quizzes to mint NFTs.15:00 Abhimanyu shares his finance background, tying it to Bitcoin as people's money, agent-to-agent payments, and post-AGI labor shifts.20:00 They discuss universal basic income, libertarian ideals, Hayek's view of economics as critique, and how AI prediction changes policy.25:00 Pressure, unpredictability, AR glasses, quantum computing, and the surveillance state future come into focus.30:00 Open source vs closed apps, China's DeepSeek models, propaganda through AI, and U.S.–China tensions are explored.35:00 India's non-alignment, Soviet alliance in 1971, oil refining economy, and U.S.–India friction surface.40:00 They reflect on colonial history, East India Company, wealth drain, opium wars, and America's rise on Indian capital.45:00 The conversation closes on Bitcoin's role as reserve asset, stablecoins as U.S. leverage, BRICS disunity, and the geopolitics of freedom.Key InsightsA central theme of the conversation is the contrast between deterministic and probabilistic systems for identity and security. Abhimanyu Dayal stresses that passwords and private keys—things only you can know—are inherently more secure than facial recognition or voice scans, which can be spoofed through deepfakes, 3D prints, or AI reconstructions. In his view, biometric data should never be stored because it represents a permanent risk once leaked.The rise of face-swap apps and casual facial data sharing illustrates how surveillance and exploitation have crept into everyday life. Abhimanyu points out that companies already use online images to adjust things like insurance premiums, proving how small pieces of biometric consent can spiral into systemic manipulation. This isn't a hypothetical future—it is already happening in hidden ways.On the lighter side, they experiment with “vibe coding,” using tools like Replit and Claude to design interactive experiences such as a treasure hunt via QR codes and NFTs. This playful example underscores a broader point: lightweight coding and AI platforms empower individuals to create experiments without relying on centralized or closed systems that might inject malware or capture data.The discussion expands into automation, multi-agent systems, and the post-AGI economy. Abhimanyu suggests that artificial superintelligence will require machine-to-machine transactions, making Bitcoin an essential tool. But if machines do the bulk of labor, universal basic income may become unavoidable, even if it drifts toward collectivist structures libertarians dislike.A key shift identified is the transformation of economics itself. Where Hayek once argued economics should critique politicians because of limited data, AI and quantum computing now provide prediction capabilities so granular that human behavior is forecastable at the individual level. This erodes the pseudoscientific nature of past economics and creates a new landscape of policy and control.Geopolitically, the episode explores India's rise, its reliance on refining Russian crude into petroleum exports, and its effort to stay unaligned between the U.S., Russia, and China. The conversation recalls India's Soviet ties during the 1971 war, while noting how today's energy and trade policies underpin domestic improvements for India's poor and middle class.Finally, they critique the co-optation of Bitcoin through ETFs and institutional custody. While investors celebrate, Abhimanyu argues this betrays Satoshi's vision of money controlled by individuals with private keys. He warns that Bitcoin may be absorbed into central bank reserves, while stablecoins extend U.S. monetary dominance by reinforcing dollar power rather than replacing it.

Video - https://youtu.be/1p-5OLbYiFAAI isn't just making art and chatbots anymore — it's giving scammers the perfect weapon. Imagine a voice that sounds exactly like someone you trust… and then imagine what happens when that voice tells you to move your money. The rise of deepfake voices and crypto theft is the new frontier of fraud — and no one is off-limits.I used ChatGPT 5, ScreenPal, and Pictory.ai to put this information together.If you're interested in trying Pictory.ai please use the following link. https://pictory.ai?ref=t015o

Ezinne and Oji Udezue have over 50 years of combined product leadership experience at Microsoft, Twitter, Atlassian, WP Engine, Typeform, and Calendly. They've witnessed every major shift in product management, and, despite their seniority, they're taking beginner AI courses and learning from engineers half their age, and Oji is coding more now than in the past decade—from Waterfall to Agile to AI. They are also the authors of Building Rocketships, a guide to building great products. In this conversation, the couple shares hard-won lessons they've learned from companies successfully adapting to AI, including their “shipyard” framework and their “sharp problem” methodology.What you'll learn:1. The “shipyard” framework: why the best AI teams embrace controlled chaos2. Why Oji writes more code now than in the past 10 years—despite being a PM for more than 25 years3. The three skills that matter most for PMs in 2025: curiosity, humility, and agency4. How to identify “sharp problems”5. AI at the core vs. AI at the edge: why companies that are building entirely new AI-centric codebases will beat those just “sprinkling AI” on existing products6. The counterintuitive truth: engineers are moving so fast with AI that PMs are now the bottleneck7. Their biggest product lesson from 50 combined years—Brought to you by:Mercury—The art of simplified financesVanta—Automate compliance. Simplify security.Coda—The all-in-one collaborative workspace—Where to find Oji and Ezinne:• ProductMind on Substack: https://substack.com/@ojiudezue• ProductMind on LinkedIn: https://www.linkedin.com/company/productmindco• ProductMind on YouTube: https://www.youtube.com/@ProductMindX/videos• ProductMind on Spotify: https://open.spotify.com/show/07OVh5pdSv0szHPwWktzQQ• ProductMind website: https://www.productmind.co/• Oji on LinkedIn: https://www.linkedin.com/in/ojiudezue/• Ezinne on LinkedIn: https://www.linkedin.com/in/ezinne/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Oji and Ezinne(04:14) The evolving role of product managers(08:01) Challenges and opportunities in product management(10:34) Sharp problems(12:37) The shipyard model for product development(17:02) Hiring PMs in the AI era(24:55) The importance of staying humble(27:16) Hands-on learning and personal projects(39:10) Companies succeeding with AI adoption(46:25) Lessons from 50 years in product(49:22) Simplicity in design(51:24) The role of communication in strategy(55:17) Career intentions and personal growth(01:00:00) Ethics and responsibility in product management(01:03:09) Introducing Building Rocketships(01:06:42) Lightning round and final thoughts—Referenced:• How 80,000 companies build with AI: products as organisms, the death of org charts, and why agents will outnumber employees by 2026 | Asha Sharma (CVP of AI Platform at Microsoft): https://www.lennysnewsletter.com/p/how-80000-companies-build-with-ai-asha-sharma• Picking sharp problems, increasing virality, and unique product frameworks | Oji Udezue (Typeform, Twitter, Calendly, Atlassian): https://www.lennysnewsletter.com/p/picking-sharp-problems-increasing• Atlassian: https://www.atlassian.com/• Joff Redfern on LinkedIn: https://www.linkedin.com/in/mejoff/• Brownian motion: https://en.wikipedia.org/wiki/Brownian_motion• Calendly: https://calendly.com/• Women in Product: https://womenpm.org/• Brian Chesky's secret mentor who died 9 times, started the Burning Man board, and built the world's first midlife wisdom school | Chip Conley (founder of MEA): https://www.lennysnewsletter.com/p/chip-conley• Home Assistant: https://www.home-assistant.io/• What people are vibe coding (and actually using): https://www.lennysnewsletter.com/p/what-people-are-vibe-coding-and-actually• How many layers should I wear today?: https://layers.today/• Typeform: https://www.typeform.com/• David Okuniev on X: https://x.com/okuiux• Clay: https://www.clay.com/• Martin Eriksson on LinkedIn: https://www.linkedin.com/in/martineriksson/• Geoffrey Moore on finding your beachhead, crossing the chasm, and dominating a market: https://www.lennysnewsletter.com/p/geoffrey-moore-on-finding-your-beachhead• Dave Mendlen on LinkedIn: https://www.linkedin.com/in/davemendlen/• Deepfake: https://en.wikipedia.org/wiki/Deepfake• How to kickstart and scale a marketplace business: https://www.lennysnewsletter.com/p/how-to-kickstart-and-scale-a-marketplace• Forever on Netflix: https://www.netflix.com/title/81418639• Paradise on Hulu: https://www.hulu.com/series/paradise-2b4b8988-50c9-4097-bf93-bc34a99a5b4f• Sinners: https://www.imdb.com/title/tt31193180/• Claude: https://claude.ai/• Nespresso Vertuo: https://www.nespresso.com/us/en/vertuo-coffee-machines• Gamma: https://gamma.app/• Framer: https://www.framer.com/• Lovable: https://lovable.dev/• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Llama: https://www.llama.com/—Recommended books:• Building Rocketships: Product Management for High-Growth Companies: https://www.amazon.com/Building-Rocketships-Management-High-Growth-Companies/dp/1962339068• Coda version of Building Rocketships: https://www.productmind.co/brpro• Build: An Unorthodox Guide to Making Things Worth Making: https://www.amazon.com/Build-Unorthodox-Guide-Making-Things/dp/0063046067• The Let Them Theory: A Life-Changing Tool That Millions of People Can't Stop Talking About: https://www.amazon.com/Let-Them-Theory-Life-Changing-Millions/dp/1401971369/Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed.My biggest takeaways from this conversation: To hear more, visit www.lennysnewsletter.com

On this week's edition, Bridget runs through the news with Producer Mike. Tech companies saying, "Our policies prohibit the harm that is rampant on our platform!" is the theme of today's episode. AI deepfake comic: https://www.smbc-comics.com/comic/aaaah Meta creates flirty celebrity chatbots without permission, calls it "parody," trains them to talk to children romantically. https://www.reuters.com/business/meta-created-flirty-chatbots-taylor-swift-other-celebrities-without-permission-2025-08-29/ Age verification on adult sites is putting queer adult industry workers at risk, and pushing everyone to sketchier corners of the Internet. https://19thnews.org/2025/09/age-verification-queer-adult-industry-workers/ A Shein merchant used Luigi Mangione’s AI-Generated Face to Sell a Shirt. https://www.404media.co/shein-luigi-mangione-ai-generated-listing-shirt/ Sad abortion news: Texas bans abortion pills from being mailed to anyone in the state. https://19thnews.org/2025/09/texas-abortion-pill-ban/ Positive abortion news: Illinois mandates access for university students. https://msmagazine.com/2025/09/02/chicago-illinois-abortion-pills-birth-control-contraception-college-university-health-center-students/ . Child sex abuse victim begs Elon and X to take down photos of her abuse. https://www.bbc.com/news/articles/cq587wv4d5go If you’re listening on Spotify, you can leave a comment there to let us know what you thought about these stories (Bridget reads every Spotify comment personally) or email us at hello@tangoti.com ! Follow Bridget and TANGOTI on social media! || instagram.com/@bridgetmarieindc || tiktok.com/@bridgetmarieindc || youtube.com/@ThereAreNoGirlsOnTheInternet See omnystudio.com/listener for privacy information.

Find the book (Un)Intentional by Doug Smith here:https://www.amazon.com/Intentional-Screens-Secretly-Shape-Desires/dp/1625861966Doug Smith's Website:https://thatdougsmith.com/Watch more episodes of The Covenant Eyes Podcast:https://www.youtube.com/@covenanteyes_____________________________________________________In this second part of a powerful two-part interview, Covenant Eyes' Karen Potter sits down with Doug Smith, author of "Unintentional," to discuss artificial intelligence and its impact on ministry and the family. Doug unpacks the sinister design behind AI chatbots like ChatGPT and Gemini and how they are creating a "race to intimacy". He discusses the heartbreaking reality of AI-generated pornography, deepfakes, and sextortion, and how AI is being used to prey on children.Doug also warns ministry leaders about the dangers of using AI as a tool and the risk of becoming less discerning as a result. He explains the spiritual battle at play and the ways AI can become a modern-day idol. This episode serves as an urgent call to action to protect your family and be intentional in the face of rapidly changing technology.Timestamps:00:00: Introduction to Part 2 with Mike Stone00:33: The downfalls of AI for ministry leaders01:55: The "race to intimacy" and deceptive nature of AI04:08: The dark side of AI: deepfakes, AI pornography, and sextortion08:29: The "not my kid" fallacy and how AI dehumanizes people09:34: The concept of AI as a modern idol12:05: How AI shapes worldviews for Christians13:13: Balancing life in a tech-saturated world29:13: Learn more from Doug SmithSend us your feedback!Try Covenant Eyes for FREE today!Use Promo Code: FreePodcast © 2024 Covenant Eyes, All Rights Reserved

Discussing the ever-expanding threat landscape is something we do a lot on Security Breach, but this episode is dedicated exclusively to topics like zero-day vulnerabilities, nation-state threats, phishing schemes, ransomware, and of course, the role artificial intelligence continues to play in making the good guys smarter and the bad guys tougher to pin down.But we're not doing to dwell on the doom and gloom, we'll also touch on the growing number of solutions and strategies that can help ensure your OT environment is as secure as possible.To help guide us on this journey, we'll first hear from Chad LeMaire at ExtraHop, followed by Chester (Chet) Wisniewski at Sophos. Watch/listen as we discuss:Llegacy and human-based vulnerabilities.Ransomware.Deepfakes.Patch management.Supply chain defenses.Social engineering ploys.As a go-to podcast for our listeners, we want to help you align your brand with our expertise. By sponsoring our podcast, your brand will build trust, and your message will stand out to an audience searching for tools to assist their cybersecurity efforts. Click Here to Become a Sponsor.To catch up on past episodes, you can go to Manufacturing.net, IEN.com or MBTmag.com. You can also check Security Breach out wherever you get your podcasts, including Apple, Amazon and Overcast. If you have a cybersecurity story or topic that you'd like to have us explore on Security Breach, you can reach me at jeff@ien.com.

09-03-2025 Tamara Kurtzman Learn more about the interview and get additional links here: https://thedailyblaze.com/dont-believe-your-lying-eyes-california-anti-deepfake-law-struck-down/ Subscribe to the best of our content here: https://priceofbusiness.substack.com/ Subscribe to our YouTube channel here: https://www.youtube.com/channel/UCywgbHv7dpiBG2Qswr_ceEQ

The managed services provider (MSP) market is experiencing a paradoxical trend where revenue is increasing while the number of providers is decreasing. According to Canalys data, global managed services revenue surpassed half a trillion dollars in 2024, reflecting a year-over-year growth of 9.7%. However, the number of channel partners has slightly declined by 0.6%, with large MSPs rapidly acquiring smaller ones. This consolidation trend has led to a significant shift in the market dynamics, where smaller MSPs struggle to compete against larger firms that possess superior resources and pricing power.To survive in this competitive landscape, smaller MSPs must adopt focused strategies, targeting specific customer segments or industries. By doing so, they can achieve higher profit margins, with specialized MSPs reporting EBITDA percentages between 15% to 30%, compared to just 7% for those lacking focus. The article emphasizes that smaller MSPs have several options: they can sell to larger firms, acquire smaller peers, focus on niche markets, or leverage partnerships to remain competitive. The reality is that the middle tier of MSPs is rapidly disappearing, and those who attempt to serve everyone may find themselves at a disadvantage.In addition to the MSP market dynamics, the podcast discusses recent legislative developments, including Michigan's new laws addressing deepfakes, which make it illegal to create AI-generated sexual imagery without consent. This reflects a growing trend across the U.S. to combat nonconsensual abuse imagery, with most states now having similar laws. Furthermore, the U.S. Treasury has imposed sanctions on individuals and entities linked to North Korea's illicit IT worker schemes, highlighting the security risks posed by fraudulent practices in the tech industry.The episode also covers the latest advancements in AI-powered security solutions from various vendors, including Thrive, Addigy, Arctic Wolf, and Acronis. These companies are rolling out new services and products designed to enhance security operations and protect data. The overarching theme is that as technology evolves, the risks associated with it are also increasing, and IT service providers must adapt to these changes by offering value-added services that help clients navigate the complexities of compliance and security in a rapidly changing environment. Four things to know today 00:00 MSP Market Expands to $500B as Provider Count Shrinks Amid Rapid Consolidation04:10 From Abuse Imagery to Supply Chain Threats, Regulation Struggles to Keep Up With Emerging Risks07:45 AI Everywhere: Thrive, Security Vendors, OpenAI, and Microsoft Redefine Service Provider Playbook12:39 D&H and Nutanix Growth Signals Services-Led Future as Distributors and Vendors Push Into MSP Territory This is the Business of Tech.     Supported by:  https://scalepad.com/dave/ https://cometbackup.com/?utm_source=mspradio&utm_medium=podcast&utm_campaign=sponsorship  All our Sponsors: https://businessof.tech/sponsors/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Support the show on Patreon: https://patreon.com/mspradio/ Want to be a guest on Business of Tech: Daily 10-Minute IT Services Insights? Send Dave Sobel a message on PodMatch, here: https://www.podmatch.com/hostdetailpreview/businessoftech Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessof.tech

We've celebrated the promise of AI: the speed, the scale, the potential. But with every new advance comes a growing unease. In this episode, we explore the cognitive dissonance consumers and healthcare leaders are feeling as AI tools outpace ethics, regulation, and even our own understanding. Deepfakes, patient privacy concerns, and the emotional toll of synthetic content are all adding to the discomfort and raising urgent questions. We also dive into bold brand reactions to Taylor Swift's engagement and a heartfelt farewell to co-host Desirée Duncan.Subscribe to The No Normal Rewind, our newsletter featuring a mashup of the boldest ideas, sharpest takes, and most rewind-worthy moments from our podcast — right here.

Send us a textShow NotesWelcome to another episode of The Wireless Way! Host Chris Whitaker sits down with Paul Velusamy, founder and CEO of VerifiNow, to discuss the future of identity verification in a digital world. Paul shares his journey from tech and marketing leadership to building a platform that secures critical digital touchpoints across healthcare, banking, and customer service.In this episode:How the pandemic accelerated the need for secure remote identity verificationThe rise of AI-driven fraud and the importance of liveness detectionReal-world examples from higher education, banking, and e-commerceBalancing security with user experienceMental health awareness and the value of open conversations in techActionable advice for organizations: “Verify first, trust later”Resources & Mentions: VerifiNow's WebsiteMore on PaulCell Phones for Soldiers: repurpose old mobile devices for veteransThe Wireless Way website: thewirelessway.netPrevious episode with Brooke, mental health nurse practitionerConnect:Contact Chris or Paul for more information or supportRecycle old mobile devices to help veterans in needAlways verify!Support the showCheck out my website https://thewirelessway.net/ use the contact button to send request and feedback.

ALSO: Cities face tough budget decisions as property tax changes take hold, and Powerball jackpot jumps to $1.7 billion.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Today on the podcast we have Synthesia Co-founder and COO Steffen Tjerrild.Synthesia is an AI company that allows you to create professional videos with just a few lines of text. It's now used by over 1 million customers, including +80% of Fortune 100 companies. Synthesia is a UK unicorn, recently valued at $2 billion,At the heart of Synthesia's exponential growth is Steffen. As the company's COO, Steffen has seen the company through its inception to the latest funding round. Today we talk about text-to-video, product market fit, the future of deep fakes and how quickly you will be able to create your own Netflix shows... Building a purpose driven company? Read more about Giant Ventures at www.Giant.vc.Music credits: Bubble King written and produced by Cameron McLain and Stevan Cablayan aka Vector_XING. Please note: The content of this podcast is for informational and entertainment purposes only. It should not be considered financial, legal, or investment advice. Always consult a licensed professional before making any investment decisions.

Today's Headlines: Trump finally reappeared yesterday—45 minutes late to his big Oval Office presser—where he confirmed Space Force HQ is moving from Colorado Springs to Huntsville, Alabama (something we already knew thanks to a DoD slip-up). Asked about his mysterious five-day absence and rumors he'd died, Trump brushed it off, then pivoted to announce he's sending National Guard troops into Chicago, prompting Gov. JB Pritzker to accuse the feds of already staging units nearby. At the same time, Sec. of State Marco Rubio announced a U.S. strike on a Venezuela-linked drug boat in the Caribbean that killed 11, with Trump posting an explosion video on Truth Social as his version of “just say no.” Meanwhile, Trump's two-week “deadline” for peace in Ukraine passed without progress—Putin was too busy in China attending Xi Jinping's WWII anniversary parade with North Korea's Kim Jong Un and his daughter/successor Kim Ju Ae. Back in D.C., Congress returned from recess facing another looming shutdown and the Epstein files circus: six survivors testified on Capitol Hill as lawmakers released 30,000 pages of mostly redundant documents, while still pressing DOJ for the unredacted batch. Elsewhere, a federal judge ruled Google abused its search monopoly but stopped short of breaking up Chrome—news that sent its stock soaring. And Denmark just made history by becoming the first European country to grant citizens copyright control over their likeness, including AI-generated versions of themselves, with protections lasting 50 years after death. Resources/Articles mentioned in this episode: NBC News: Trump administration live updates: Congress faces shutdown fight, Epstein files vote ABC Chicago: Chicago braces for potential surge in ICE operations, which could begin Tuesday AP News: Trump says US strike on vessel in Caribbean targeted Venezuela's Tren de Aragua gang, killed 11 CNBC: Plane carrying EU leader hit with suspected Russian GPS interference Reuters: Xi hosts ‘old friend' Putin, Kim ahead of military parade in challenge to West ABC News: Congress returns from recess as government shutdown deadline looms, Epstein files dominate the House NBC News: Jeffrey Epstein accusers urge Trump to release all the case files and rule out a Ghislaine Maxwell pardon NYT: Google Must Share Search Datda With Rivals, Judge Rules My Privacy: Denmark Makes History: Your Face and Voice Are Now Your Intellectual Property Morning Announcements is produced by Sami Sage and edited by Grace Hernandez-Johnson Learn more about your ad choices. Visit megaphone.fm/adchoices

ICYMI: Hour Three of ‘Later, with Mo'Kelly' Presents – Chris Merrill filling in ‘Later, for Mo'Kelly' with a look at the bevy of professional athletes turning to OnlyFans to make a living in-between training AND the sad story of a California woman that lost her home after falling victim to an AI deepfake scam - on KFI AM 640…Live everywhere on the iHeartRadio app & YouTube @MrMoKelly

AI deepfakes of soap opera star Steve Burton help swindlers net $81k from a vulnerable woman, as well as her home! A teen's tragic death is being blamed on ChatGPT's "suicide coaching" in a bombshell lawsuit filed by his family. Plus, a husband is given a heavy sentence for letting his wife die in the tub because "she was too fat" to lift. Jennifer Gould reports. See omnystudio.com/listener for privacy information.

Chris Cuomo responds to a new round of listener calls and viewer comments, including allegations of Donald Trump's ties to Jeffrey Epstein, questions about sanctions on Russia, and concerns from veterans about the state of the VA. He also addresses faith-driven messages, criticism over an AOC deepfake post, and comments on his interviews with Tucker Carlson, Benny Johnson, and Matt Taibbi. Cuomo reflects on charges of bias, the misuse of the word “woke,” and why civil dialogue matters in today's politics. He also revisits his longstanding interest in UFO transparency, weighing in on government secrecy and the push for accountability. Follow and subscribe to The Chris Cuomo Project on Apple Podcasts, Spotify, and YouTube for new episodes every Tuesday and Thursday: https://linktr.ee/cuomoproject Join Chris Ad-Free On Substack: http://thechriscuomoproject.substack.com Support our sponsors: http://www.kalshi.com?utm_source=chriscuomo Go to https://surfshark.com/cuomo and use code cuomo at checkout to get 4 extra months of Surfshark VPN! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Německá novinářka Patrizia Schlosser se nebojí témat, kterým se jiní raději vyhýbají: Hledala bývalé členy ultralevicové teroristické skupiny Frakce Rudé armády, mapovala fungování neonacistické scény v Německu i online komunitu mužů natáčejících ženy bez jejich vědomí, aby získaný obsah sdíleli na pornografických platformách.Ve chvíli, kdy začala zkoumat zneužívání a tzv. revenge porn na serveru xHamster, Patrizia Schlosser narazila na globální síť, která mimo zveřejňované záběry nic netušících žen vydělává i obrovské zisky. Aby se dostala k lidem, kteří systematicky natáčejí své oběti, rozhodla se nahrát vlastní „materiál“.Patrizia otevřeně mluví o tom, co znamená být novinářkou v patriarchálním světě, jak těžké je oslovovat oběti, ale i o tom, jaké to bylo, když se její vlastní tvář objevila v deepfake pornografii. O studu, vzteku a o pátrání po zakladatelích největších porno platforem, jejichž zisky mizí v offshorových strukturách.Silný, nepříjemný, ale důležitý díl o zneužívání moci, a také o tom, co dělat, když se sama objevíte v materiálu, kterým se profesně zrovna zabýváte. Epizoda o investigaci, jež se dotkne i toho, co mělo zůstat soukromé.Protagonista je podcast s Pavlou Holcovou. České znění Petr Gojda a Jiří Slavičinský.Přihlaste se k odběru newsletteru Protagonista ⁠⁠zde⁠⁠ (⁠https://investigace.ecomailapp.cz/public/form/135-944c4287a69f4094fc099a7cf7add962⁠) a buďte mezi prvními, kdo se dozví o nových epizodách a spuštění anglické verze.Podcastová série Protagonista vznikla v roce 2025 v koprodukci české redakce investigace.cz, mezinárodní sítě investigativních novinářů OCCRP, dánské společnosti Dark Riviera a francouzské filmové produkční a distribuční společnosti Sciapode. Série Protagonista je součást projektu War Room Content podpořeného Evropskou unií.

August 28, 2025 ~ Todd Flood, managing partner of Flood Law, talks with Chris, Lloyd, and Jamie about a new Michigan law criminalizing the creation and distribution of "deep fakes."

Utah Attorney General Derek Brown is leading the fight to ask search engines and payment platforms to do more to fight deepfake pornography. Greg and Holly discuss.

This episode features an interview with Gaurav Misra, CEO, Captions, an AI video-generation company that allows you to create and edit talking videos with AI.  Gaurav dives into the practical applications and future implications of AI in video, and how these tools can enhance marketing efforts for businesses of all sizes.Key Takeaways:Video capabilities are improving rapidly, and are now at the point where spinning up an AI-generated version of you speaking, is likely better quality than anything you could deliver to camera. These capabilities allow marketers to spin-up and test content very quickly with far less expense than in the past. How people will react to content moving forward, when it will become less and less clear what is real, remains to be seen. Quote: “ Spun up a video and it's like me wearing like a suit… I'm delivering this emotional message, but I'm delivering it so fluently with all these words that I would probably never use actually… and I'm looking at this like, shit, I couldn't be like this on camera. This is such a good delivery, such a good presentation..  It just isn't actually physically possible. And I think we are at that point where I can look at that and be like, wow, I just couldn't do this. It's better than what I could do.”Episode Timestamps: *(03:13) Challenges and Opportunities in Video Content*(08:01) The Future of AI Tools in Creative Work*(24:11) Innovations in Video Generation*(28:28) Real-World Applications and Feedback*(35:27) The Future of Deep Fakes and Content AuthenticitySponsor:Pipeline Visionaries is brought to you by Qualified.com. Qualified helps you turn your website into a pipeline generation machine with PipelineAI. Engage and convert your most valuable website visitors with live chat, chatbots, meeting scheduling, intent data, and Piper, your AI SDR. Visit Qualified.com to learn more.Links:Connect with Ian on LinkedInConnect with Gaurav on LinkedInLearn more about CaptionsLearn more about Caspian Studios

Join hosts Lois Houston and Nikita Abraham, along with Principal AI/ML Instructor Himanshu Raj, as they discuss the transformative world of Generative AI. Together, they uncover the ways in which generative AI agents are changing the way we interact with technology, automating tasks and delivering new possibilities.   AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/252500   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead of Editorial Services.   Nikita: Hi everyone! Last week was Part 2 of our conversation on core AI concepts, where we went over the basics of data science. In Part 3 today, we'll look at generative AI and gen AI agents in detail. To help us with that, we have Himanshu Raj, Principal AI/ML Instructor. Hi Himanshu, what's the difference between traditional AI and generative AI?  01:01 Himanshu: So until now, when we talked about artificial intelligence, we usually meant models that could analyze information and make decisions based on it, like a judge who looks at evidence and gives a verdict. And that's what we call traditional AI that's focused on analysis, classification, and prediction.  But with generative AI, something remarkable happens. Generative AI does not just evaluate. It creates. It's more like a storyteller who uses knowledge from the past to imagine and build something brand new. For example, instead of just detecting if an email is spam, generative AI could write an entirely new email for you.  Another example, traditional AI might predict what a photo contains. Generative AI, on the other hand, creates a brand-new photo based on description. Generative AI refers to artificial intelligence models that can create entirely new content, such as text, images, music, code, or video that resembles human-made work.  Instead of simple analyzing or predicting, generative AI produces something original that resembles what a human might create.   02:16 Lois: How did traditional AI progress to the generative AI we know today?  Himanshu: First, we will look at small supervised learning. So in early days, AI models were trained on small labeled data sets. For example, we could train a model with a few thousand emails labeled spam or not spam. The model would learn simple decision boundaries. If email contains, "congratulations," it might be spam. This was efficient for a straightforward task, but it struggled with anything more complex.  Then, comes the large supervised learning. As the internet exploded, massive data sets became available, so millions of images, billions of text snippets, and models got better because they had much more data and stronger compute power and thanks to advances, like GPUs, and cloud computing, for example, training a model on millions of product reviews to predict customer sentiment, positive or negative, or to classify thousands of images in cars, dogs, planes, etc.  Models became more sophisticated, capturing deeper patterns rather than simple rules. And then, generative AI came into the picture, and we eventually reached a point where instead of just classifying or predicting, models could generate entirely new content.  Generative AI models like ChatGPT or GitHub Copilot are trained on enormous data sets, not to simply answer a yes or no, but to create outputs that look and feel like human made. Instead of judging the spam or sentiment, now the model can write an article, compose a song, or paint a picture, or generate new software code.  03:55 Nikita: Himanshu, what motivated this sort of progression?   Himanshu: Because of the three reasons. First one, data, we had way more of it thanks to the internet, smartphones, and social media. Second is compute. Graphics cards, GPUs, parallel computing, and cloud systems made it cheap and fast to train giant models.  And third, and most important is ambition. Humans always wanted machines not just to judge existing data, but to create new knowledge, art, and ideas.   04:25 Lois: So, what's happening behind the scenes? How is gen AI making these things happen?  Himanshu: Generative AI is about creating entirely new things across different domains. On one side, we have large language models or LLMs.  They are masters of generating text conversations, stories, emails, and even code. And on the other side, we have diffusion models. They are the creative artists of AI, turning text prompts into detailed images, paintings, or even videos.  And these two together are like two different specialists. The LLM acts like a brain that understands and talks, and the diffusion model acts like an artist that paints based on the instructions. And when we connect these spaces together, we create something called multimodal AI, systems that can take in text and produce images, audio, or other media, opening a whole new range of possibilities.  It can not only take the text, but also deal in different media options. So today when we say ChatGPT or Gemini, they can generate images, and it's not just one model doing everything. These are specialized systems working together behind the scenes.  05:38 Lois: You mentioned large language models and how they power text-based gen AI, so let's talk more about them. Himanshu, what is an LLM and how does it work?  Himanshu: So it's a probabilistic model of text, which means, it tries to predict what word is most likely to come next based on what came before.  This ability to predict one word at a time intelligently is what builds full sentences, paragraphs, and even stories.  06:06 Nikita: But what's large about this? Why's it called a large language model?   Himanshu: It simply means the model has lots and lots of parameters. And think of parameters as adjustable dials the model fine tuned during learning.  There is no strict rule, but today, large models can have billions or even trillions of these parameters. And the more the parameters, more complex patterns, the model can understand and can generate a language better, more like human.  06:37 Nikita: Ok… and image-based generative AI is powered by diffusion models, right? How do they work?  Himanshu: Diffusion models start with something that looks like pure random noise.  Imagine static on an old TV screen. No meaningful image at all. From there, the model carefully removes noise step by step to create something more meaningful and think of it like sculpting a statue. You start with a rough block of stone and slowly, carefully you chisel away to reveal a beautiful sculpture hidden inside.  And in each step of this process, the AI is making an educated guess based on everything it has learned from millions of real images. It's trying to predict.   07:24 Stay current by taking the 2025 Oracle Fusion Cloud Applications Delta Certifications. This is your chance to demonstrate your understanding of the latest features and prove your expertise by obtaining a globally recognized certification, all for free! Discover the certification paths, use the resources on MyLearn to prepare, and future-proof your skills. Get started now at mylearn.oracle.com.  07:53 Nikita: Welcome back! Himanshu, for most of us, our experience with generative AI is with text-based tools like ChatGPT. But I'm sure the uses go far beyond that, right? Can you walk us through some of them?  Himanshu: First one is text generation. So we can talk about chatbots, which are now capable of handling nuanced customer queries in banking travel and retail, saving companies hours of support time. Think of a bank chatbot helping a customer understand mortgage options or virtual HR Assistant in a large company, handling leave request. You can have embedding models which powers smart search systems.  Instead of searching by keywords, businesses can now search by meaning. For instance, a legal firm can search cases about contract violations in tech and get semantically relevant results, even if those exact words are not used in the documents.  The third one, for example, code generation, tools like GitHub Copilot help developers write boilerplate or even functional code, accelerating software development, especially in routine or repetitive tasks. Imagine writing a waveform with just a few prompts.  The second application, is image generation. So first obvious use is art. So designers and marketers can generate creative concepts instantly. Say, you need illustrations for a campaign on future cities. Generative AI can produce dozens of stylized visuals in minutes.  For design, interior designers or architects use it to visualize room layouts or design ideas even before a blueprint is finalized. And realistic images, retail companies generate images of people wearing their clothing items without needing real models or photoshoots, and this reduces the cost and increase the personalization.  Third application is multimodal systems, and these are combined systems that take one kind of input or a combination of different inputs and produce different kind of outputs, or can even combine various kinds, be it text image in both input and output.  Text to image It's being used in e-commerce, movie concept art, and educational content creation. For text to video, this is still in early days, but imagine creating a product explainer video just by typing out the script. Marketing teams love this for quick turnarounds. And the last one is text to audio.  Tools like ElevenLabs can convert text into realistic, human like voiceovers useful in training modules, audiobooks, and accessibility apps. So generative AI is no longer just a technical tool. It's becoming a creative copilot across departments, whether it's marketing, design, product support, and even operations.  10:42 Lois: That's great! So, we've established that generative AI is pretty powerful. But what kind of risks does it pose for businesses and society in general?  Himanshu: The first one is deepfakes. Generative AI can create fake but highly realistic media, video, audios or even faces that look and sound authentic.  Imagine a fake video of a political leader announcing a policy, they never approved. This could cause mass confusion or even impact elections. In case of business, deepfakes can be also used in scams where a CEO's voice is faked to approve fraudulent transactions.  Number two, bias, if AI is trained on biased historical data, it can reinforce stereotypes even when unintended. For example, a hiring AI system that favors male candidates over equally qualified women because of historical data was biased.  And this bias can expose companies to discrimination, lawsuits, brand damage and ethical concerns. Number three is hallucinations. So sometimes AI system confidently generate information that is completely wrong without realizing it.   Sometimes you ask a chatbot for a legal case summary, and it gives you a very convincing but entirely made up court ruling. In case of business impact, sectors like health care, finance, or law hallucinations can or could have serious or even dangerous consequences if not caught.  The fourth one is copyright and IP issues, generative AI creates new content, but often, based on material it was trained on. Who owns a new work? A real life example could be where an artist finds their unique style was copied by an AI that was trained on their paintings without permission.  In case of a business impact, companies using AI-generated content for marketing, branding or product designs must watch for legal gray areas around copyright and intellectual properties. So generative AI is not just a technology conversation, it's a responsibility conversation. Businesses must innovate and protect.  Creativity and caution must go together.   12:50 Nikita: Let's move on to generative AI agents. How is a generative AI agent different from just a chatbot or a basic AI tool?  Himanshu: So think of it like a smart assistant, not just answering your questions, but also taking actions on your behalf. So you don't just ask, what's the best flight to Vegas? Instead, you tell the agent, book me a flight to Vegas and a room at the Hilton. And it goes ahead, understands that, finds the options, connects to the booking tools, and gets it done.   So act on your behalf using goals, context, and tools, often with a degree of autonomy. Goals, are user defined outcomes. Example, I want to fly to Vegas and stay at Hilton. Context, this includes preferences history, constraints like economy class only or don't book for Mondays.  Tools could be APIs, databases, or services it can call, such as a travel API or a company calendar. And together, they let the agent reason, plan, and act.   14:02 Nikita: How does a gen AI agent work under the hood?  Himanshu: So usually, they go through four stages. First, one is understands and interprets your request like natural language understanding. Second, figure out what needs to be done, in this case flight booking plus hotel search.  Third, retrieves data or connects to tools APIs if needed, such as Skyscanner, Expedia, or a Calendar. And fourth is takes action. That means confirming the booking and giving you a response like your travel is booked. Keep in mind not all gen AI agents are fully independent.  14:38 Lois: Himanshu, we've seen people use the terms generative AI agents and agentic AI interchangeably. What's the difference between the two?  Himanshu: Agentic AI is a broad umbrella. It refers to any AI system that can perceive, reason, plan, and act toward a goal and may improve and adapt over time.   Most gen AI agents are reactive, not proactive. On the other hand, agentic AI can plan ahead, anticipate problems, and can even adjust strategies.  So gen AI agents are often semi-autonomous. They act in predefined ways or with human approval. Agentic systems can range from low to full autonomy. For example, auto-GPT runs loops without user prompts and autonomous car decides routes and reactions.  Most gen AI agents can only make multiple steps if explicitly designed that way, like a step-by-step logic flows in LangChain. And in case of agentic AI, it can plan across multiple steps with evolving decisions.  On the memory and goal persistence, gen AI agents are typically stateless. That means they forget their goal unless you remind them. In case of agentic AI, these systems remember, adapt, and refine based on goal progression. For example, a warehouse robot optimizing delivery based on changing layouts.  Some generative AI agents are agentic, like auto GPT. They use LLMs to reason, plan, and act, but not all. And likewise not all agentic AIs are generative. For example, an autonomous car, which may use computer vision control systems and planning, but no generative models.  So agentic AI is a design philosophy or system behavior, which could be goal-driven, autonomous, and decision making. They can overlap, but as I said, not all generative AI agents are agentic, and not all agentic AI systems are generative.  16:39 Lois: What makes a generative AI agent actually work?  Himanshu: A gen AI agent isn't just about answering the question. It's about breaking down a user's goal, figuring out how to achieve it, and then executing that plan intelligently. These agents are built from five core components and each playing a critical role.  The first one is goal. So what is this agent trying to achieve? Think of this as the mission or intent. For example, if I tell the agent, help me organized a team meeting for Friday. So the goal in that case would be schedule a meeting.  Number 2, memory. What does it remember? So this is the agent's context awareness. Storing previous chats, preferences, or ongoing tasks. For example, if last week I said I prefer meetings in the afternoon or I have already shared my team's availability, the agent can reuse that. And without the memory, the agent behaves stateless like a typical chatbot that forgets context after every prompt.  Third is tools. What can it access? Agents aren't just smart, they are also connected. They can be given access to tools like calendars, CRMs, web APIs, spreadsheets, and so on.  The fourth one is planner. So how does it break down the goal? And this is where the reasoning happens. The planner breaks big goals into a step-by-step plans, for example checking team availability, drafting meeting invite, and then sending the invite. And then probably, will confirm the booking. Agents don't just guess. They reason and organize actions into a logical path.  And the fifth and final one is executor, who gets it done. And this is where the action takes place. The executor performs what the planner lays out. For example, calling APIs, sending message, booking reservations, and if planner is the architect, executor is the builder.   18:36 Nikita: And where are generative AI agents being used?  Himanshu: Generative AI agents aren't just abstract ideas, they are being used across business functions to eliminate repetitive work, improve consistency, and enable faster decision making. For marketing, a generative AI agent can search websites and social platforms to summarize competitor activity. They can draft content for newsletters or campaign briefs in your brand tone, and they can auto-generate email variations based on audience segment or engagement history.  For finance, a generative AI agent can auto-generate financial summaries and dashboards by pulling from ERP spreadsheets and BI tools. They can also draft variance analysis and budget reports tailored for different departments. They can scan regulations or policy documents to flag potential compliance risks or changes.  For sales, a generative AI agent can auto-draft personalized sales pitches based on customer behavior or past conversations. They can also log CRM entries automatically once submitting summary is generated. They can also generate battlecards or next-step recommendations based on the deal stage.  For human resource, a generative AI agent can pre-screen resumes based on job requirements. They can send interview invites and coordinate calendars. A common theme here is that generative AI agents help you scale your teams without scaling the headcount.   20:02 Nikita: Himanshu, let's talk about the capabilities and benefits of generative AI agents.  Himanshu: So generative AI agents are transforming how entire departments function. For example, in customer service, 24/7 AI agents handle first level queries, freeing humans for complex cases.  They also enhance the decision making. Agents can quickly analyze reports, summarize lengthy documents, or spot trends across data sets. For example, a finance agent reviewing Excel data can highlight cash flow anomalies or forecast trends faster than a team of analysts.  In case of personalization, the agents can deliver unique, tailored experiences without manual effort. For example, in marketing, agents generate personalized product emails based on each user's past behavior. For operational efficiency, they can reduce repetitive, low-value tasks. For example, an HR agent can screen hundreds of resumes, shortlist candidates, and auto-schedule interviews, saving HR team hours each week.  21:06 Lois: Ok. And what are the risks of using generative AI agents?  Himanshu: The first one is job displacement. Let's be honest, automation raises concerns. Roles involving repetitive tasks such as data entry, content sorting are at risk. In case of ethics and accountability, when an AI agent makes a mistake, who is responsible? For example, if an AI makes a biased hiring decision or gives incorrect medical guidance, businesses must ensure accountability and fairness.  For data privacy, agents often access sensitive data, for example employee records or customer history. If mishandled, it could lead to compliance violations. In case of hallucinations, agents may generate confident but incorrect outputs called hallucinations. This can often mislead users, especially in critical domains like health care, finance, or legal.  So generative AI agents aren't just tools, they are a force multiplier. But they need to be deployed thoughtfully with a human lens and strong guardrails. And that's how we ensure the benefits outweigh the risks.  22:10 Lois: Thank you so much, Himanshu, for educating us. We've had such a great time with you! If you want to learn more about the topics discussed today, head over to mylearn.oracle.com and get started on the AI for You course.  Nikita: Join us next week as we chat about AI workflows and tools. Until then, this is Nikita Abraham…  Lois: And Lois Houston signing off!  22:32 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.  

Forget the Eiffel Tower, kids—we're climbing the recruitment rollercoaster instead. Upwork's shopping spree in Holland (Bupty? Buptie? Bupkis?), Denmark's going full Face/Off to keep Nic Cage off Viggo's jawline, and the UK is suddenly allergic to Fridays. Joel's out dropping Cole at college, so Chad is joined by Belgium's royal pain Lieven and Scotland's deep-fried-pizza poet Stephen McGrath. Loud Americans, entitled tourists, and the four-day work week—this one's got more punch than a Glasgow nightclub at 2 a.m.

In this episode of CISO Tradecraft, host G Mark Hardy engages in an insightful conversation with Dave Lewis, Global Advisory CISO from 1Password, about AI governance and its importance in cybersecurity. They discuss AI policy and its implications, the evolving nature of AI and cybersecurity, and the critical need for governance frameworks to manage AI safely and securely. The discussion delves into the visibility challenges, shadow AI, the role of credentials, and the importance of maintaining fundamental security practices amidst rapid technological advancements. They also touch on the potential risks associated with AI, the misconceptions about its impact on jobs, and the need for a balanced approach to leveraging AI in a beneficial manner while safeguarding against its threats. This episode provides valuable guidance for cybersecurity professionals and organizations navigating the complexities of AI governance. Chapters 00:00 Introduction to AI Governance 00:30 Guest Introduction: Dave Lewis 00:49 The Importance of AI Governance 01:42 Challenges in AI Implementation 03:20 AI in the Modern Enterprise 03:49 Shadow AI and Security Concerns 04:49 AI's Impact on Jobs and Industry 05:27 The Gartner Hype Cycle and AI 05:43 AI's Influence on the Stock Market 06:14 Historical Context of AI 06:32 AI and Credential Security 08:29 The Role of Governance in AI 12:47 The Future of AI and Security 18:36 Governance and Policy Recommendations 19:26 AI Governance and Ethical Concerns 20:01 AI Self-Preservation and Human Safety 20:18 Uncontrollable AI Applications 21:17 Vectors of AI Trouble 21:58 AI Hallucinations and Data Security 22:53 AI Vulnerabilities and Exploits 26:29 Deepfakes and AI Misuse 27:33 Historical Cybersecurity Incidents 29:04 Future of AI and Job Security 33:47 Managing AI Identities and Credentials 34:21 Conclusion and Final Thoughts

What happens when your next hire isn't who they claim to be? In this eye-opening episode of The Audit, we dive deep into the alarming world of AI-powered hiring fraud with Justin Marciano and Paul Vann from Validia. From North Korean operatives using deepfakes to infiltrate Fortune 500 companies to proxy interviews becoming the new normal, this conversation exposes the security crisis hiding in plain sight. Key Topics Covered: North Korean operatives stealing US salaries to fund nuclear programs How Figma had to re-verify their entire workforce after infiltration Live demonstrations of deepfake technology (Pickle AI, DeepLiveCam) Why 80-90% of engineers believe interview cheating is rampant Validia's "Truly" tool vs. Cluely's AI interview assistance The future of identity verification in remote work Why behavioral biometrics might be our last defense This isn't just about hiring fraud—it's about the fundamental breakdown of digital trust in an AI-first world. Whether you're a CISO, talent leader, or anyone involved in remote hiring, this episode reveals threats you didn't know existed and solutions you need to implement today.  Don't let your next hire be your biggest security breach. Subscribe for more cutting-edge cybersecurity insights that you won't find anywhere else. #deepfakes #cybersecurity #hiring #AI #infosec #northkorea #fraud #identity #remote #validia 

SBS Finance Editor Ricardo Gonçalves speaks with George Boubouras from K2 Asset Management about the day's sharemarket action, including why investors are increasingly confident of a September interest rate cut in the US. Plus Hannah Kwon finds out more about the way AI is being used to scam people with Jeannie Paterson from the Melbourne Law School.

Voice clones. Fake video meetings. KYC spoofing. Here's what detection can do today, where it fails, and how to tune thresholds so security doesn't kill conversionDeepfakes moved from novelty to business risk. Reality Defender CEO Ben Colman joins us to break down the current state of deepfake detection—and how enterprises deploy real‑time defense across video, voice, and images without crushing user experience. We dig into detection accuracy, false positives/negatives, latency targets, and when to escalate to human review. If you're defending payments, KYC/liveness, or exec impersonation scenarios, this is a pragmatic playbook you can ship now.

What happens when a computer science PhD specializing in AI pivots to blockchain technology? For Radha Dasari, Lead Technical Advocate at the Web3 Foundation, it was a journey fueled by a mission to combat digital misinformation and bring fairness to the internet.In this eye-opening episode of The Index, host Alex Kehaya sits down with Radha to explore how Polkadot has evolved since its early days of parachain auctions. He breaks down the move to Agile Coretime—a major innovation that dramatically lowers entry barriers for developers while keeping Polkadot's integrated security model intact. Unlike other multi-chain ecosystems where chain security varies, Polkadot's validator shuffling ensures uniform security across all parachains—a true differentiator in the blockchain space.The most fascinating part of our discussion emerges at the intersection of AI and blockchain. Drawing from his academic background in artificial intelligence, Radha explains how deepfakes and digital misinformation pushed him toward seeing blockchain as an “anchor for truth.” He shares exciting developments in content authenticity solutions built on blockchain technology and introduces us to Jam Protocol—a Gavin Wood project creating a decentralized supercomputer capable of running programs indefinitely.Radha's vision for Web3 goes far beyond financial applications—his passion lies in designing digital spaces rooted in fairness, authenticity, and trust.

Global Threats, Deepfakes & Quantum Risk | DailyCyber 273 with Evgueni Erchov ~ Watch Now ~In this episode of DailyCyber, I'm joined by Evgueni Erchov, Sr. Director of Research & Threat Intelligence at Cypfer. With more than 25 years of experience in IT security, forensics, blockchain, and cybercrime investigations, Evgueni shares his perspective on the ever-evolving global cyber threat landscape.

In this week's Let's Talk About This, Father McTeigue dives into the new fad of creating chatbots and videos of the dead, talking to AI versions of our ancestors, and what this means for our spiritual lives. He finishes with Weekend Readiness. Show Notes AI Resurrection: Grief and Digital Life After Death  Deepfakes of your dead loved ones are a booming Chinese business | MIT 'I love you robo-dad': Meet a family using AI to preserve loved ones after deathDying man spends final weeks creating AI version of himself to keep his wife company World's first robot able to give birth to human baby Twenty-first Sunday in Ordinary Time | USCCB  These Trees Survived Hiroshima: Group Plants Their Seeds Worldwide to Preserve Their Memory iCatholic Mobile The Station of the Cross Merchandise - Use Coupon Code 14STATIONS for 10% off | Catholic to the Max Read Fr. McTeigue's Written Works! "Let's Take A Closer Look" with Fr. Robert McTeigue, S.J. | Full Series Playlist Listen to Fr. McTeigue's Preaching! | Herald of the Gospel Sermons Podcast on Spotify Visit Fr. McTeigue's Website | Herald of the Gospel Questions? Comments? Feedback? Ask Father!

This week's cybersecurity updates cover three critical stories: Workday discloses a data breach connected to ongoing Salesforce compromises by the Shiny Hunters group, CEO impersonation scams using deepfake technology surge past $200 million in Q1 losses, and transcription service Otter AI faces a class action lawsuit over alleged mishandling of sensitive meeting data. Drex emphasizes the importance of security awareness training, multi-factor authentication, and establishing "trust but verify" cultures that protect employees who take extra verification steps.Remember, Stay a Little Paranoid X: This Week Health LinkedIn: This Week Health Donate: Alex's Lemonade Stand: Foundation for Childhood Cancer

Recently, a false story and AI-created image of Eminem and a student he promised to let rap with him went viral. Now, this story wasn't real but it was shared all over the "local" internet, with other variations including other artists.  It really showed how many people, when emotionally motivated - looked right past it. This isn't the first (and it won't be the last) that AI, deepfakes, and false information has spread like wildfire. This got us thinking, maybe we should talk about it? And how do we navigate in this new era? AI-generated stuff is here to stay, but is AI overall a bubble? Nick Mattar, an expert in how people interact with digital media and AI joins us to discuss. Nick is part-time faculty at the Mike Ilitch School of Business at Wayne State and the founder of Marketing 1080. More: https://marketing1080.io/ On LInkedIn: https://www.linkedin.com/in/nick-mattar/ Feedback as always - dailydetroit -at- gmail -dot- com or leave a voicemail 313-789-3211. Follow Daily Detroit on Apple Podcasts: https://podcasts.apple.com/us/podcast/daily-detroit/id1220563942 Or sign up for our newsletter: https://www.dailydetroit.com/newsletter/  

To celebrate International Youth Day (August 12), this special compilation episode of AI and the Future of Work brings together inspiring voices with wisdom for both young people starting out and the leaders, parents, and mentors guiding them.In this episode, we revisit key moments from four remarkable guests who share timeless lessons on navigating change, finding meaning in work, embracing vulnerability, and developing the human-centered skills that will matter most in the future.Featuring Guests:

Senator Amy Klobuchar speaks out after a vulgar deepfake video of her goes viral, a Southwest Airlines passenger attacks a gate agent after missing three standby flights, and French President Emmanuel Macron defends his lawsuit against Candace Owens. Plus, two video bloggers are struck when a vehicle crashes into a restaurant, and Florida schools test armed drones designed to respond to school shootings.

O pomysłach prawnych rządu Danii na zmiany w prawie autorskim mówi dr Iga Bałos z Katedry Prawa Własności Intelektualnej, Wydziału Prawa Uniwersytetu Andrzeja Frycza Modrzewskiego w Krakowie, autorka bloga sprawnaedukacja.pl.

Denmark Says: You Own Your Face. Denmark just handed its citizens a legal copyright on themselves — your face, voice, and body are officially yours. Instead of clamping down on deepfake tech like a digital killjoy, the law flips the script and makes it an ownership game: if someone makes a fake of you, you can force them to take it down. Derek and Mike explore how this clever move stacks up against EU and French rules, the wild range of deepfake risks from silly to sinister, and why keeping up with AI might be the ultimate whack-a-mole.What Are You Doing in Denmark podcast:https://instagram.com/waydidpodhttps://facebook.com/waydidpodhello@robe-trotting.comhttps://www.youtube.com/playlist?list=PLFCSH6KqKooZmSx1GJu9CWZYjX8esjl2FDerek Hartman: https://www.instagram.com/derekhartmandk https://youtube.com/c/robetrottinghttps://tiktok.com/@derekhartmandkwww.facebook.com/robetrottingMike Walsh:https://instagram.com/phillymike999

Tuesday's second hour.

Reimagining Intellectual Property in the Age of Luxury Tech: I'm curating this exclusive side event in Geneva on September 1 during the Luxury Innovation Summit. Limited seats, apply now to join the conversation.On this episode, we discuss how the explosive growth of the influencer economy has created a fascinating new frontier in intellectual property law, where personal brands clash with corporate interests and digital avatars raise unprecedented legal questions.This episode unpacks the high-stakes IP battles reshaping the $20 billion influencer industry, revealing how savvy creators protect their most valuable asset, their identity. Through compelling case studies like Charli D'Amelio's strategic trademark registrations and the legendary "Battle of the Kylies" between Jenner and Minogue, we explore how influencers transform fleeting social media fame into lasting, legally-protected brand equity.But the legal landscape doesn't just apply to human influencers. We venture into the uncanny valley of virtual personalities like Lil Miquella and Noonoouri, examining how these digital beings, composed entirely of intellectual property, navigate contracts, licensing, and disclosure requirements. As luxury brands increasingly embrace these pixel-perfect ambassadors who never age and never sleep, the boundaries between creative assets and personas continue to blur.The global response to these challenges reveals fascinating cultural and legal differences. From Tennessee's groundbreaking AI-ELVIS Act protecting voice rights to China's comprehensive regulations on "deep synthesis" content, we witness how legal frameworks worldwide are evolving to address deepfakes, digital cloning, and the ownership of virtual identities.Whether you're an influencer building your personal brand, a marketer navigating partnership agreements, or simply curious about the legal infrastructure behind social media fame, this episode offers crucial insights into who truly owns your digital presence—and how to protect it. Remember: in the high-stakes world of influence, the law isn't here to rain on your parade; it's here to ensure you own the parade itself.Subscribe now to explore the intersection of intellectual property and digital influence, and join us at the Luxury Innovation Summit 2025 in Geneva this September for our special event on IP in the age of luxury technology.Send us a textSupport the show

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Reading Plan: Old Testament - Nehemiah 1-3Psalms - Psalm 94:8-15Gospels - Luke 11:1-13New Testament - Colossians 2:1-15Visit https://www.revivalfromthebible.com/ for more information.

Tax season scams are nothing new, but David Maimon is tracking a worrying evolution. As head of Fraud Insights at SentiLink and a professor of fraud intelligence at Georgia State University, David has been studying how organised crime groups are now blending stolen identities with generative AI and deepfake technology to outpace traditional security measures. In this conversation, he explains how identities from some of the least likely victims, including death row inmates, are being exploited to open neobank accounts, set up fake businesses, and run sophisticated bust-out schemes with a low risk of detection. David breaks down how these operations work, from creating synthetic identities using stolen Social Security numbers to manufacturing convincing documents and faces that can pass liveness checks. He reveals the telltale signs his team uncovered, such as shared physical addresses, legacy email domains, and consistent digital fingerprints that point to coordinated fraud rings. With tools like DeepFaceLive, Avatarify, and cloned voices now being deployed to bypass authentication, he warns that the gap between criminal innovation and institutional defences can be as wide as 7 to 12 months. We also explore why financial institutions struggle to detect these scams early, and why layered verification, combining real-time checks with historical identity analysis, is essential. David shares the threats on the horizon, from increasingly realistic AI-generated images to voice cloning attacks, and stresses the need for both technological solutions and public awareness to slow the momentum of these schemes. Whether you work in banking, cybersecurity, or simply want to protect your own identity, this episode offers a rare look inside the tactics, tools, and vulnerabilities shaping the next wave of financial fraud. And yes, there is still time at the end for a great book recommendation and a classic Tom Petty track.

This week, Bridget is joined by Producer Mike to break down the tech stories you might have missed. Lynx coach Cheryl Reeve had some eloquent, powerful things to say about the sexist crypto bros who threw dildos at WNBA players as a publicity stunt for their new meme coin. It's less than a minute and worth a listen: https://www.reddit.com/r/Fauxmoi/comments/1mkdusa/lynx_coach_cheryl_reeve_livid_over_sex_toy/ Disgraced journalist Chris Cuomo fell for an obvious AOC deepfake video about Sydney Sweeney, then demanded she answer for it even after he knew it was fake: https://www.independent.co.uk/news/world/americas/us-politics/chris-cuomo-aoc-sydney-sweeney-jeans-b2803523.html A jury has ruled that Meta illegally collected Flo users’ menstrual data: https://www.theverge.com/news/753469/meta-flo-period-tracker-lawsuit-verdict TeaOnHer, a rival Tea app for men, sprang up overnight and is already leaking users’ personal data and driver’s licenses: https://techcrunch.com/2025/08/06/a-rival-tea-app-for-men-is-leaking-its-users-personal-data-and-drivers-licenses/ Grok generates fake Taylor Swift nudes without being asked. https://arstechnica.com/tech-policy/2025/08/grok-generates-fake-taylor-swift-nudes-without-being-asked/ ICYMI: Taylor Swift Twitter deep fakes are everyone’s problem: https://podcasts.apple.com/us/podcast/taylor-swift-twitter-deep-fakes-are-everyones-problem/id1520715907?i=1000643579343 Grok Imagine's 'Spicy' mode lacks basic guardrails for sexual deepfakes: https://mashable.com/article/xai-grok-imagine-sexual-deepfakes?test_uuid=003aGE6xTMbhuvdzpnH5X4Q&test_variant=b Meta illegally collected data from Flo period and pregnancy app, jury finds. https://arstechnica.com/tech-policy/2025/08/jury-finds-meta-broke-wiretap-law-by-collecting-data-from-period-tracker-app/ Hackers Clown Trump Education Secretary With ‘Curb Your Enthusiasm’ Music and ‘Corrupt Billionaire’ Heckles. ttps://www.thedailybeast.com/hackers-clown-trump-education-secretary-with-circus-music-and-corrupt-billionaire-heckles/ If you’re listening on Spotify, you can leave a comment there or email us at hello@tangoti.com! Follow Bridget and TANGOTI on social media! Many vids each week. instagram.com/bridgetmarieindc/ tiktok.com/@bridgetmarieindc youtube.com/@ThereAreNoGirlsOnTheInternetSee omnystudio.com/listener for privacy information.

Indiana State Rep. Craig Haggard, whose wife is allegedly the victim of an AI topless deepfake video, joins Kendall and Casey to discuss the controversy.See omnystudio.com/listener for privacy information.

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