Podcasts about fraud detection

In this episode of the Future of ERP, Sandeep Chowdhury, Senior Director in SAP's Telecommunications Industry Business Unit, discusses how the telecom industry is evolving with advanced ERP systems to support Industry 4.0, 5G adoption, and smarter networks. He explains how emerging technologies like 6G and AI are transforming network operations and customer experiences. Sandeep also explores telecom's influence on other sectors, regulatory challenges, and the increasing importance of AI in automation and fraud prevention. Sustainability is a key theme, as he addresses energy use, e-waste, and circular economy efforts. Overall, Sandeep reveals how telecom is balancing innovation and environmental responsibility to shape the future of connectivity.

In this episode of the Consumer Finance Podcast, Chris Willis, co-leader of Troutman Pepper Locke's Consumer Financial Services Regulatory practice, delves into the current state of machine learning and artificial intelligence (AI) models in underwriting and fraud detection. Chris provides an overview of the regulatory expectations set by the Consumer Financial Protection Bureau, including the historical context and recent developments. He discusses the importance of fair lending considerations, the use of less discriminatory alternative analysis, and the skepticism around certain types of alternative data. Chris also explores the potential impact of state regulations and the need for a long-term approach to fair lending risk. Tune in to stay informed about the evolving landscape of AI and machine learning in consumer finance.

Every bank and fintech company has a suite of anti-fraud tools that they use to keep the bad guys out. Few tools are 100% effective, however, and often the implementation of these tools, along with their interfaces with other system leave gaps. And the fraudsters will exploit these gaps. So, how do you get a holistic view of your anti-fraud arsenal and discover where these gaps are?My next guest on the Fintech One-on-One podcast is Jerry Tylman, the co-founder and partner at Greenway Solutions and the founder of their Fraud Red Team. The Fraud Red Team is all about discovering the gaps, where the weaknesses in the anti-fraud systems are. They are 100% focused on financial services, working with many of the largest banks in the country as well as several fintech companies.In this podcast you will learn:How Greenway Solutions became focused on financial services.What a pen test is and the groundbreaking work they do with fraud controls.The different attack vectors that fraudsters use.Why banks and fintechs need the services of the Fraud Red Team.How successful they are in penetrating the fraud detection systems.How they interact with the anti-fraud providers to banks and fintechs.An example of a recent test they have done that penetrated anti-fraud systems.How they tackle the challenge of account onboarding.Why behavioral technology is a key piece of the puzzle.How deepfake video and audio are being used by fraudsters.The fascinating way that the Fraud Red Team works with deepfakes.Why companies have to completely rethink their internal authentication today.Some of the fintechs they have worked with recently.How they work with check fraud and why it is a growing problem.Why all financial institutions cannot stop investing in anti-fraud tools.Connect with Fintech One-on-One: Tweet me @PeterRenton Connect with me on LinkedIn Find previous Fintech One-on-One episodes

This episode is sponsored by Thuma.   Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.   To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai Visa's President of Technology, Rajat Taneja, pulls back the curtain on the $3.3 billion AI transformation powering one of the world's most trusted financial networks.   In this episode, Taneja shares how Visa—a company processing over $16 trillion annually across 300 billion real-time transactions—is leveraging AI not just to stop fraud, but to redefine the future of commerce.   From deep neural networks trained on decades of transaction data to generative AI tools powering next-gen agentic systems, Visa has quietly been an AI-first company since the 1990s. Now, with 500+ petabytes of data and 2,900 open APIs, it's preparing for a future where agents, biometrics, and behavioral signals shape every interaction.   Taneja also reveals how Visa's models can mimic bank decisions in milliseconds, stop enumeration attacks, and even detect fraud based on how you type. This is AI at global scale—with zero room for error.   What You'll Learn in This Episode: How Visa's $3.3B data platform powers 24/7 AI-driven decisioning The fraud models behind stopping $40 billion in criminal transactions What “agentic commerce” means—and why Visa is betting big on it How Visa uses behavioral biometrics to detect account takeovers Why Visa rebuilt its infrastructure for the AI era—10 years ahead of the curve The role of generative AI, biometric identity, and APIs in the next wave of payments   The future of commerce isn't just cashless—it's intelligent, autonomous, and trust-driven.   If you're curious about how AI is redefining payments, security, and digital identity at massive scale, this episode is essential viewing.   Subscribe for more deep dives into the future of AI, commerce, and innovation. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Introduction (02:57) Meet Rajat Taneja, Visa's President of Technology (04:02) Scaling AI for 300 Billion Transactions Annually (05:27) The Models Behind Visa's Fraud Detection (08:02) Visa's In-House AI Models vs Open-Source Tools (10:54) Inside Visa's $3.3B AI Data Platform (12:29) Visa's Role in E-Commerce Innovation (16:24) Biometrics, Identity & Tokenization at Visa (21:14) Visa's Vision for AI-Driven Commerce

Building Trust Through Technology: Responsible AI in Practice // MLOps Podcast #301 with Rafael Sandroni, Founder and CEO of GardionAI.Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractRafael Sandroni shares key insights on securing AI systems, tackling fraud, and implementing robust guardrails. From prompt injection attacks to AI-driven fraud detection, we explore the challenges and best practices for building safer AI.// BioEntrepreneur and problem solver. // Related LinksGardionAI LinkedIn: https://www.linkedin.com/company/guardionai/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Rafael on LinkedIn: /rafaelsandroniTimestamps:[00:00] Rafael's preferred coffee[00:16] Takeaways[01:03] AI Assistant Best Practices[03:48] Siri vs In-App AI[08:44] AI Security Exploration[11:55] Zero Trust for LLMS[18:02] Indirect Prompt Injection Risks[22:42] WhatsApp Banking Risks[26:27] Traditional vs New Age Fraud[29:12] AI Fraud Mitigation Patterns[32:50] Agent Access Control Risks[34:31] Red Teaming and Pentesting[39:40] Data Security Paradox[40:48] Wrap up

Nedbank is the latest bank highlighting a growing trend of fraudsters pretending to be police officers to scam unsuspecting South Africans. The bank released a fraud alert to customers that fraudsters use vishing calls to scam customers out of their money. Vishing is short for "voice phishing- a type of cybercrime where fraudsters use phone calls or voice messages to trick victims into revealing sensitive information. Scammers pose as bank employees from the bank fraud department or police officers. They call victims to inform them that they are linked to a fraud case before advising them to transfer money from their accounts.. To unpack this Bongiwe Zwane spoke to Lucas Venter , Nedbank's Group Head of Fraud Detection

Artificial Intelligence (or AI) is rapidly transforming the way we work, communicate, and make decisions—but for many, it still feels like an overwhelming or complex concept. In this episode, we're breaking down the basics of AI for the novice, making it simple and approachable so you can understand the engine behind it, how it works and why it matters. Whether you're a business owner, a creative, or just curious about the technology shaping our world, knowing these fundamentals will help you adapt, stay relevant, and make informed choices in an AI-driven future. Even though AI is not merely an illusion, I'll pull back the curtain on how AI works and some of the differences between machine and generative learning. Because AI is already being used to tackle complex challenges and improve efficiency in a variety of industries, I feel it's very valuable to know the basics of how it works. Today, most of us think nothing of using calculators instead of an abacus or pencil and paper to calculate figures. The simple calculator has become a normal part of our routine. In the same way, many aspects of AI are already integrated in many parts of our daily lives. First, I'm going to talk about input, then distinguish between machine learning and generative learning. Full article here: https://goalsforyourlife.com/artificial-intelligence Make sure you're getting all our podcast updates and articles! Get them here: https://goalsforyourlife.com/newsletter  Resources with tools and guidance for mid-career individuals, professionals & those at the halftime of life seeking growth and fulfillment: http://HalftimeSuccess.com #ainews #digitalmarketing #aitools #contentcreation #aiproductivitytools CHAPTERS: 00:00 - Intro 01:34 - Input Data 06:21 - Machine Learning Basics 08:51 - Generative Learning Techniques 10:47 - The Power of AI Applications 15:58 - Applying AI to Your Life 18:24 - Thank You for Joining Us  

Today's guest is Nick Lewis, Managing Director for the High Risk Client Unit at Standard Chartered Bank. Nick joins today's show to discuss the shifting landscape of fraud prevention and AML compliance in financial services. As governments increasingly shift regulatory responsibilities onto the private sector, banks find themselves at the forefront of both enforcement and risk management. Lewis highlights how sanctions regimes have evolved, pushing financial institutions to shoulder greater due diligence responsibilities with fewer resources. His conversation with Emerj Editorial Director Matthew DeMello also explores the broader implications of this public-private realignment, including the increasing reliance on AI-driven detection methods and the complexities of prioritizing financial crime risks. Lewis underscores the growing role of banks in addressing crimes such as human trafficking, despite the lack of formal mandates, and how AI could enhance collaboration with law enforcement to identify and mitigate emerging threats. If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Send us a message!As the hospitality industry evolves, guest screening and verification have become essential components of a safe and seamless guest experience. In this episode, we sit down with Ela Mezhiborsky, President and Co-Founder of AutoHost, to explore how cutting-edge technology is reshaping the way hotels and short-term rental operators manage risk, prevent fraud, and enhance security.Ela shares her insights on the growing role of AI and cybersecurity in guest verification, the challenges of "bad AI" in fraud prevention, and the regulatory changes driving the need for stronger screening solutions. From mandatory ID checks to advanced biometric verification, this conversation unveils the future of trust and safety in hospitality.Key Topics Discussed:1️⃣ The Evolution of AutoHost & Guest Screening2️⃣ The Role of AI in Fraud Detection & "Bad AI" Risks3️⃣ Regulatory Changes & Compliance Trends4️⃣ Hotels vs. Short-Term Rentals: Who's Leading in Security?5️⃣ The Future of Guest Verification & Embedded Security Solutions6️⃣ Addressing Human Trafficking & Ethical Responsibility7️⃣ Where AutoHost is Headed Next8️⃣ Final Thoughts & How to Connect with ElaConnect with Ela:LinkedIn: https://www.linkedin.com/in/elamezhiborsky/ Autohost Website: https://www.autohost.ai/ Ready to take your operations to the next level? Visit https://tnsinc.com/podcasts-alex-and-annie/  to learn more.Get $50 credit and $0 onboarding fee when you sign up for Beyond, the leading dynamic pricing tool for vacation rentals: http://beyondpricing.info/alexandannie#guestscreening #vacationrentals #fraudprevention

Sadaf Sultan, Founder of Finprojections, and Jeremy Au analyzed the eFishery financial scandal and discuss broader issues of financial fraud in startups. They talked about why eFishery was appealing to investors and how the fraud unfolded and shared their insights into detecting fraud effectively. They explore the challenges faced during investor due diligence, overlooked warning signs, and practical suggestions for strengthening investor safeguards. 1. A promising vision: eFishery attracted investors by presenting itself as a solution for fragmented markets through vertical integration and improved efficiencies. 2. Start small, grow big: Initial minor revenue inflation escalated rapidly under pressures from ambitious fundraising goals. 3. Behind closed doors: The founders executed fraud through round-tripping transactions using shell companies to create artificial revenue. 4. Hard to detect: Auditors struggled to identify fraud due to heavy dependence on founder-provided information. 5. Overlooked red flags: Large bonuses to the finance team and sudden departures of key financial staff were early, but ignored, warning signals. 6. Strengthening investor checks: Investors need to leverage local expertise, perform forensic audits, and set up clear whistleblowing channels. 7. Recognizing red flags: Common fraud tactics include confusing GMV with revenue, overstating recurring revenue, aggressive credit offerings, and misclassifying discounts as marketing costs. Watch, listen or read the full insight at https://www.bravesea.com/blog/sadaf-sultan2 Get transcripts, startup resources & community discussions at www.bravesea.com WhatsApp: https://whatsapp.com/channel/0029VakR55X6BIElUEvkN02e TikTok: https://www.tiktok.com/@jeremyau Instagram: https://www.instagram.com/jeremyauz Twitter: https://twitter.com/jeremyau LinkedIn: https://www.linkedin.com/company/bravesea English: Spotify | YouTube | Apple Podcasts Bahasa Indonesia: Spotify | YouTube | Apple Podcast Chinese: Spotify | YouTube | Apple Podcasts Vietnamese: Spotify | YouTube | Apple Podcasts

Ghazi Ben Amor, VP Corporate Development, ZAMAZAMA is a newcomer specialising in cryptography, with a focus on fully homomorphic encryption. This technology allows computations to be performed on encrypted data but, crucially, without the need to decrypt it first – thus preserving data privacy and security – useful attributes for banks and others in financial services. Robin Amlôt of IBS Intelligence discusses the problem, the potential and the use cases with Ghazi Ben Amor, VP Corporate Development of ZAMA. 

Protect your finances from fraud, embezzlement, and scams with expert strategies from Kelly Todd, President of Forensic Strategic Solutions. In this episode, she shares how to detect, prevent, and recover from financial fraud before it devastates your business or personal assets.

Willkommen bei Back 2 Basics – der Reihe für aufstrebende E-Commerce Händler und ihren ersten Kontakt mit Affiliate Marketing - vom Next Level Affiliate Marketing Podcast. Bist du engagierter Merchant und hast bereits deinen Online-Shop bei Shopify, Woocommerce, Magento oder Shopware, und suchst nun nach einer Erweiterung zum typischen Google, Amazon, Facebook und Apple Marketing-Mix? Dein Host Nawid Company erklärt in dieser Serie klar strukturiert die Grundsteine des Affiliate-Marketingbereichs damit du bestens vorbereitet für die ersten Schritte bist. So wirst mit Back 2 Basics und der Interview-Reihe Time for Learning schnell zum Profi. Die heutige Folge behandelt folgende Themen: - Datenbasierte Partnerwahl - Haltezeit & Bounce Rate - Keyword-Matching für Publisher - Organischer vs. Paid Traffic - Pinterest als Traffic-Quelle - Publisher Performance Metriken - SEO-Traffic vs. Direct Traffic - SimilarWeb & Systrix - Tracking Weichen als Sicherheit - Traffic-Qualität

In this episode, Šimon Mandlík, a PhD candidate at the Czech Technical University will talk with us about leveraging machine learning and graph-based techniques for cybersecurity applications. We'll learn how graphs are used to detect malicious activity in networks, such as identifying harmful domains and executable files by analyzing their relationships within vast datasets. This will include the use of hierarchical multi-instance learning (HML) to represent JSON-based network activity as graphs and the advantages of analyzing connections between entities (like clients, domains etc.). Our guest shows that while other graph methods (such as GNN or Label Propagation) lack in scalability or having trouble with heterogeneous graphs, his method can tackle them because of the "locality assumption" – fraud will be a local phenomenon in the graph – and by relying on this assumption, we can get faster and more accurate results.

Senthil Padmanabhan, VP of Platform and Infrastructure at eBay, discusses how eBay's use of fine-tuning is improving their operational workflows. He explains why fine-tuning existing models can often be more cost-effective than training from scratch, and how methods like low-ranking adaptation (LoRa) are pivotal in improving AI performance. Key Takeaways:  The impact of strategic fine tuning on achieving peak performance AI's broader impact on eBay's infrastructure, fraud detection, and customer-facing experiences The challenges of tech debt and software upgrades Case studies from eBay that illustrate productivity gains via fine-tuning Considerations for choosing between open and proprietary AI models The importance of data quality over quantity in fine-tuning processes Predictions for the future of AI development and fine-tuning techniques Guest Bio: Senthil Padmanabhan is a Vice President and Technical Fellow at eBay, where he runs Platform and Infra (private cloud) Engineering for the global eCommerce marketplace, providing infrastructure for 4000+ engineers to deliver products at scale. Before this role, he was in the Product engineering space, building consumer-facing applications at eBay and Yahoo. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

Click here to read along and see the photos in our show notes as you listen – http://www.scottishwatches.co.uk/category/podcast/ Welcome to the Scottish Watches Podcast Episode 637! Rebeca is wearing her... The post Scottish Watches Podcast #637 : Dr Rebecca Struthers On Artisan Watch Making and Forensic Fraud Detection appeared first on Scottish Watches.

Today, we're joined by Rich Kahn, Co-Founder and CEO of Anura, an ad fraud solution designed to improve campaign performance by accurately exposing bots, malware, and human fraud. We talk about:Why digital marketing is a hot spot for fraudstersThe numerous benefits of reducing fraudHow to increase Return on Ad Spend (ROAS)Who is taking better advantage of AI: fraudsters or those battling fraud?

In this episode, we learn what's new in the 2025 Fraud Detection and Remediation training from Steve Sebestyen. Host: Ian Grossman Producer: Claire Jeffrey and Chelsey Hadwin Music: Gibson Arthur

IN CLEAR FOCUS: Rich Kahn, co-founder and CEO of Anura.io, delves into ad fraud, projected to cost businesses $100B this year. Rich shares insights on identifying fraudulent traffic, including Sophisticated Invalid Traffic (SIVT), using advanced detection techniques. He emphasizes third-party certification, cohesive fraud prevention strategies, and why marketers must reject fraud as a business cost. Explore how vigilance and Anura's solutions can protect budgets and improve ad performance.

Welcome to TCAST, the podcast that explores the intersection of technology, data, and humanity. In this episode, hosts Alexander McCaig and Jason Rigby dive deep into TARTLE's DataVault Connect, a groundbreaking OAuth2-based platform designed to give businesses and users unprecedented control over their data. Discover how this tool transforms data sharing into a win-win scenario for companies and consumers, emphasizing ethical practices, privacy, and revenue generation. Episode Highlights Introducing DataVault Connect What It Is: A seamless OAuth2 integration that allows users to vault and monetize their data while giving businesses a compliance-ready solution for data collection. Why It Matters: Shift away from outdated login systems like Google and Facebook, and embrace a more ethical, transparent way of handling data. Key Features of DataVault Connect Granular Consent Management: Users decide what data to share and can revoke access at any time. Revenue Sharing: Businesses earn a percentage of revenue when users monetize their data. Built-In Compliance: Fully aligned with GDPR, HIPAA, and CCPA regulations, backed by blockchain-based audit trails. Zero and First-Party Data Access: Unlock valuable insights for AI training, personalization, and customer engagement. Why DataVault Connect is a Game-Changer for Businesses Simplified Integration: A plug-and-play OAuth2 button with robust SDK support for websites and apps. Real-Time Data Insights: Gain access to user-approved data that enhances AI models and market strategies. Enhanced Privacy: Cutting-edge encryption ensures user data is secure and untouchable by third parties. Trust Building: Show customers you prioritize their data rights, fostering long-term relationships. The OAuth Revolution How It Compares: Unlike traditional login systems that profit from your users' data, TARTLE's DataVault Connect ensures your business benefits from every login while safeguarding user privacy. Revenue Model: Every time a user monetizes their data, your business gets a share of the profit. Who Should Use DataVault Connect? AI Companies: For accessing high-quality, real-time data to improve model performance. E-Commerce Platforms: Enhance personalization and customer experience. Healthcare Providers: Securely manage sensitive data with HIPAA-compliant tools. Marketers: Use ethical, actionable insights to drive campaign success. Why Listen to This Episode? This episode is perfect for anyone who: Wants to learn about ethical data exchange and monetization. Is seeking innovative ways to enhance their AI models or customer experience. Cares about compliance and wants to reduce legal risks related to data management. Is curious about how to turn user authentication into a revenue stream. Key Takeaways Ethical Data Exchange: Shift to a user-first model that benefits businesses and consumers alike. Revenue Potential: Generate profits from data monetization while maintaining compliance. Privacy at the Core: TARTLE ensures data security with cutting-edge encryption and blockchain-backed audits. Seamless Adoption: Integrate DataVault Connect easily into your current systems with minimal effort. Actionable Steps for Businesses Sign Up for TARTLE DataVault Connect: Visit TARTLE.CO to get started. Integrate the OAuth2 Button: Use TARTLE's SDK and documentation to add the button to your site or app. Engage with Your Users: Showcase your commitment to ethical data practices and invite them to participate. Monetize User Data: Earn a share of revenue as your users monetize their data.  

Welcome to TCAST, the podcast where we explore how technology and data empower humanity. In this episode, hosts Jason Rigby and Alexander McCaig share exciting updates about the TARTLE platform and how its new features are creating daily earning opportunities for users worldwide. Whether you're looking to supplement your income or maximize the value of your data, this episode is packed with actionable insights. Episode Highlights The Opportunities Tab: Your Gateway to Extra Income What It Is: A new feature on the TARTLE dashboard designed to simplify finding paid data-sharing opportunities. How It Works: Access hundreds of data packets daily, complete simple tasks, and get paid instantly. Earning Potential for Users Global Opportunities: Over $400,000 in earning potential added daily, with opportunities available in 76+ countries. Boosting Your Income: Learn how sharing your data can double or even triple your hourly earnings without changing your routine. How to Use the Dashboard Simple Navigation: Log in, click on the Opportunities Tab, and browse available tasks. Key Tips: Be honest when completing data packets, as accuracy increases your chances of earning. Why TARTLE is Different Ethical Data Sharing: Unlike other platforms, TARTLE prioritizes transparency, user empowerment, and equitable earnings. Global Accessibility: Designed to work on any device and bandwidth, ensuring opportunities for everyone. Why Listen to This Episode? This episode is perfect for anyone interested in: Exploring new ways to earn money online. Learning about ethical data-sharing practices. Understanding how platforms like TARTLE are creating financial opportunities for individuals globally. Finding out how to maximize your time and income with minimal effort. Key Takeaways Daily Earnings Opportunities: Hundreds of thousands of dollars in data-sharing opportunities are added every day. Ease of Use: TARTLE's dashboard is user-friendly and accessible to anyone, anywhere. Honesty Pays: Being accurate and transparent when completing tasks increases your earning potential. Empowerment Through Data: Take control of your data and turn it into a sustainable income stream. Actionable Steps from the Episode Sign Up for TARTLE: Create an account at TARTLE.CO. Log Into the Dashboard: Navigate to the Opportunities Tab and explore daily earning tasks. Complete Tasks Honestly: Follow the instructions and provide accurate information to maximize success. Check Daily: New opportunities are added every day, so make it a habit to log in and earn. Why TARTLE is the Future of Data Sharing TARTLE isn't just a platform—it's a global movement to empower individuals through data ownership and fair compensation. With its new dashboard features, TARTLE is bridging the gap between technology and equity, enabling users to share data ethically and profitably. Get Started Today: Join the TARTLE community and take control of your data: https://tartle.co. Explore hundreds of daily opportunities to turn your data into dollars.

Episode Highlights The Healthcare Data Revolution Problem: Diagnostic models often fail when transitioning from test environments to real-world applications due to poor data quality and lack of contextual insights. Solution: TARTLE's Real Intelligence API connects AI systems directly to zero-party data, sourced with explicit patient consent. This allows for real-world diagnostic accuracy, bypassing third-party data scrubbing. Key Takeaway: Build physician and patient trust while improving diagnostic tools with ethically sourced data. Fraud Detection and AI in Financial Services Problem: AI models for fraud detection suffer from high false-positive rates, creating friction with customers and undermining trust. Solution: Using TARTLE, companies can collect real-world data on fraud patterns, behaviors, and edge cases, enabling more accurate fraud detection without unnecessary flags. Key Takeaway: Reduce false positives and build better fraud detection models by integrating contextual human feedback. Transforming E-Commerce with Personalization Problem: Recommendation engines often rely on outdated third-party data, leading to low click-through rates and poor customer engagement. Solution: TARTLE DataVault Connect allows businesses to collect real-time, consent-driven feedback to enhance product recommendations, reduce cart abandonment, and improve customer lifetime value. Key Takeaway: Improve e-commerce performance with zero-party data tailored to your customers' needs. Media Companies and Seasonal Content Personalization Problem: Seasonal trends are difficult to predict without direct user data. Solution: By integrating TARTLE's Real Intelligence API, media companies can source data streams that reflect real-time preferences, allowing for highly targeted and adaptive content strategies. Key Takeaway: Personalized ads and content become possible with user-specific data insights. Why TARTLE Matters for AI Companies Ethically Sourced Data: TARTLE's platform enables businesses to collect data directly from individuals, ensuring compliance with global privacy standards like GDPR and CCPA. Improved Model Accuracy: Businesses using TARTLE's API report up to 30% improvement in model performance by leveraging zero-party and real-time human feedback. Streamlined Integration: API implementation takes as little as 2-3 weeks, delivering measurable improvements within 4-6 weeks. Key Features of TARTLE's Real Intelligence API Real-Time Human Feedback: Collect insights directly from users to train AI models. Zero-Party Data: Access data provided with explicit consent, eliminating the risks of traditional third-party data. Compliance and Audit Trails: Every data point is fully documented and permissioned, ensuring transparency. Scalability: TARTLE supports millions of API calls daily, making it suitable for businesses of any size. Who Should Listen to This Episode? This episode is a must-listen for: AI and machine learning professionals seeking better data solutions. Healthcare innovators looking for consent-driven patient data. Financial services companies aiming to enhance fraud detection models. E-commerce leaders striving to improve customer engagement. Media companies exploring personalized content strategies. How TARTLE Stands Out Unlike traditional data brokers, TARTLE provides a direct connection to data providers, ensuring: Ethical data sourcing. Enhanced privacy and security. Clear consent and provenance. Real-time insights for smarter AI models. Actionable Insights from the Episode Ethical AI starts with ethically sourced data. Real-time feedback loops can transform how you train your AI models. By leveraging zero-party data, you can build trust, reduce bias, and improve user engagement. TARTLE makes it easy to scale data collection while remaining compliant with global standards. Ready to Elevate Your AI Models? Learn more about TARTLE's Real Intelligence API and DataVault Connect. Visit TARTLE.CO to discover how you can start collecting ethical, real-time data today. Listen Now and Subscribe: Tune in to TCAST on your favorite platform for more insights into data, AI, and digital transformation. Don't forget to subscribe, rate, and share this episode with your network.

In this conversation, Ryan Staley and Laurent Charpentier discuss the evolving role of AI in business, particularly in fraud detection and sales processes. Laurent shares insights on how AI is being integrated into their operations, the importance of team engagement with new technologies, and his vision for future business ventures leveraging AI. Takeaways AI is crucial for enhancing fraud detection strategies. Automation provides better control over financial processes. Data accuracy improves as AI models evolve. Engagement with AI tools boosts team morale and productivity. AI can help in summarizing meetings for better efficiency. The legal implications of AI usage are a concern for companies. Building proprietary AI models can mitigate data privacy issues. AI tools can enhance sales coaching and performance. The future of business will heavily rely on AI technology. Exploring new use cases for AI is essential for growth. ---------- Want to become Superhuman through the use of AI? Join our community of 3,100+ subscribers today. https://www.aiforrevenue.com/superhumanrevenue-newsletter

Welcome to the Jake & Gino Podcast!In this special episode, we are joined by Tim Ray, the co-founder and CEO of VeriFast, a cutting-edge identity and financial verification platform revolutionizing the real estate and property management sectors. From his early successes in e-commerce and angel investing to the hard-learned lessons of a startup that missed the mark, Tim shares an unfiltered look at the highs and lows of entrepreneurship.Key Takeaways:How Tim scaled multiple businesses, including exits in e-commerce and a private aviation tech startup.The lessons behind his "double-A baseball" analogy for entrepreneurship.The journey from startup setbacks to the genesis of VeriFast.Insights on identity verification and income screening in real estate.Why fraud detection and tenant screening matter now more than ever.Learn how VeriFast is transforming tenant screening and what it means for property managers of all sizes.Episode Highlights:Entrepreneurial pivots: When big swings lead to big lessons.How financial verification tools empower landlords.The future of tenant screening and digital identity in multifamily housing.Real stories of reducing delinquencies and eliminating fraud in property management.Chapters:00:00 - Introduction00:51 - From E-Commerce Exits to Private Aviation Failures08:39 - The Birth of VeriFast: Solving Real-World Problems13:34 - How VeriFast Verifies Income and Prevents Fraud25:31 - Pricing Models: Per-Door vs. Per-Application Costs27:23 - Screening Smarter: Approving More Tenants While Reducing Evictions33:51 - The Problem with Credit Scores in Tenant Screening41:49 - Gino Wraps it UpConnect with Tim Ray:Email: tim.ray@VeriFast.comLinkedIn: Tim RayDon't forget to like, subscribe, and hit the notification bell for more insights from top industry leaders in real estate and entrepreneurship! We're here to help create multifamily entrepreneurs... Here's how: Brand New? Start Here: https://jakeandgino.mykajabi.com/free-wheelbarrowprofits Want To Get Into Multifamily Real Estate Or Scale Your Current Portfolio Faster? Apply to join our PREMIER MULTIFAMILY INVESTING COMMUNITY & MENTORSHIP PROGRAM. (*Note: Our community is not for beginner investors)

Blake and David examine the mysteries and motives surrounding the recent Macy's accounting scandal, where a single employee allegedly concealed $132-154 million through improper accrual entries. They also examine Trump's proposed 25% tariff plan on imports from Mexico and Canada (plus an additional 10% on China), discussing its potential impact on American businesses and consumers. SponsorsZoho - http://accountingpodcast.promo/zohoSuralink - http://accountingpodcast.promo/suralinkCloud Accountant Staffing - http://accountingpodcast.promo/casChapters(00:46) - Macy's Accounting Error: Breaking News (01:40) - Understanding the Impact of Macy's Error (02:46) - The Mystery Behind Macy's Accounting Error (02:53) - Join the Live Discussion (03:42) - Upcoming Topics and Teasers (05:15) - Thanking Our Sponsors (06:42) - Diving Deeper into Macy's Accounting Mystery (19:29) - Exploring the Fraud Triangle (27:54) - Auditors and Materiality Standards (32:04) - Auditors' Role in Detecting Fraud (33:25) - Impact of Fraud on Macy's Stock (33:47) - Challenges in Auditing Practices (34:08) - Internal Controls and Their Limitations (38:53) - Expense Fraud: A Growing Concern (44:01) - AI in Auditing: The Future of Fraud Detection (52:28) - Trump Tariffs and Their Economic Impact (01:03:13) - Thanksgiving Reflections and Closing Remarks  Show NotesMacy's says employee hid up to $154 million in expenses, delaying Q3 earningshttps://apnews.com/article/macys-accounting-quarter-b1cb0927d9b6a58ee4396838df7973c9Macy's says accountant hid as much as $154M in expenseshttps://www.cfodive.com/news/macys-says-accountant-hid-as-much-as-154m-in-expenses-retail-retailing-consumers/733960/UPS to Pay $45 Million SEC Penalty Over Improper Valuationhttps://finance.yahoo.com/news/ups-hit-45-million-penalty-144424675.htmlStrippers, Christmas gifts and an RV: Workers push it with company cardshttps://abcdpf.livemint.com/industry/strippers-christmas-gifts-and-an-rv-workers-push-it-with-company-cards-11732157906943.htmlEx-Jaguars employee who stole $22 million from team files lawsuit against FanDuelhttps://www.nytimes.com/athletic/5809925/2024/10/01/jaguars-lawsuit-fanduel-amit-patel/Trump's Truth Social tariffs pledge is a teachable moment for Americahttps://www.msnbc.com/opinion/msnbc-opinion/trump-truth-social-tariffs-deportation-thanksgiving-rcna182079What does Trump's latest tariff plan mean for the U.S.?https://www.pbs.org/newshour/politics/what-does-trumps-latest-tariff-plan-mean-for-the-u-sWalmart CFO Says They Don't Want To Raise Prices, But 'Prices Will Go Up For Consumers' Due To Upcoming Tariffshttps://finance.yahoo.com/news/walmart-cfo-says-dont-want-161640110.htmlNeed CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring the Cloud Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast: http://cloudacctpod.link/OvercastClassifiedsForwardly - https://www.forwardly.com/Client Hub - https://clienthub.app/Want to get the word out about your newsletter, webinar, party, Facebook group, podcast, e-book, job posting, or that fancy Excel macro you just created? Let the listeners of The Accounting Podcast know by running a classified ad. Go here to create your classified ad: https://cloudacctpod.link/RunClassifiedAdTranscriptsThe full transcript for this episode is available by clicking on the Transcript tab at the top of this page

Dr. Mark Nigrini, famed for his work on Benford's Law, is on Fraudish discuss key aspects of fraud detection and prevention. The episode dives into the implications of AI on future fraud and the importance of understanding key fraud patterns. Nigrini is the author of Forensic Analytics (Wiley, 2011) and Forensic Analytics Second Edition (2020) which describes analytic tests to detect fraud, errors, estimates, and biases in financial data. He is also the author of Benford's Law (Wiley, 2012) which is the seminal work on applications of Benford's Law.Connect with Mark Nigrini: https://www.linkedin.com/in/mark-nigrini-7409918/Mark's website: https://nigrini.com/

This Day in Legal History: Guiteau Stands Trial for AssassinationOn November 14, 1881, Charles Guiteau stood trial for assassinating President James A. Garfield. Garfield had been shot by Guiteau in July of that year but succumbed to his injuries months later, largely due to medical mismanagement. At the time, sterilization practices were not widely understood or practiced, and Garfield's doctors repeatedly probed his wound with unwashed instruments and hands, leading to a fatal infection. Despite the role of inadequate medical care, Guiteau was held fully responsible for the president's death, setting a notable precedent in criminal law.Guiteau's defense centered on claims of insanity, arguing that he believed he was acting on divine command to remove Garfield. His erratic behavior in court, which included singing, reciting poetry, and accusing his defense attorneys of incompetence, underscored his unstable mental state. However, nineteenth-century legal standards for insanity were narrow and rarely accepted by courts. The prosecution argued that Guiteau understood the wrongfulness of his act, and he was ultimately found guilty and sentenced to death.The case spotlighted serious deficiencies in the legal system's treatment of mental illness and brought attention to the need for clearer guidelines on the insanity defense. It also ignited a broader conversation on the role of medical practices in causation, as some questioned whether Guiteau could be solely responsible for Garfield's death. Guiteau's trial and conviction marked one of the first high-profile uses of the insanity defense in the United States and influenced subsequent legal reforms regarding both mental health assessments and standards of criminal responsibility.President-elect Donald Trump has named Matt Gaetz, a firebrand Republican congressman with a face that might terrify even the devil himself, as his nominee for attorney general. Gaetz, who has previously faced scrutiny from the Justice Department over sex trafficking allegations, will replace current leadership to help Trump “end Weaponized Government” and enact an aggressive conservative agenda. Gaetz, who resigned from Congress immediately, is known for his unconventional political moves, including his role in ousting former House Speaker Kevin McCarthy, and for his call to dismantle federal agencies like the FBI. His appointment has already triggered controversy, with Senate Republicans like Lisa Murkowski expressing skepticism about his qualifications and intentions. Gaetz's background has raised security clearance concerns, given the history of investigations into his conduct.The nomination aligns with Trump's stated intentions to reshape the Justice Department, positioning the attorney general as crucial to plans for mass deportations, pardons of January 6 rioters, and prosecutorial retribution. Gaetz's legal experience consists mainly of work at a Florida law firm before he entered politics, though he has recently championed populist stances on antitrust enforcement, supporting the Federal Trade Commission's fight against noncompete clauses and cheering the Justice Department's antitrust case against Google. Gaetz's nomination fuels concern among former Justice Department officials, who fear that he could further politicize an institution traditionally independent from White House influence.Trump taps firebrand congressman Matt Gaetz for attorney general | ReutersIn the corruption trial of former U.S. Senator Robert Menendez, prosecutors revealed that jurors were mistakenly shown unredacted evidence during deliberations. However, they argued this error does not warrant overturning the conviction, asserting that the evidence against Menendez was overwhelming. Menendez, a former New Jersey senator, was convicted in August of corruption charges that included accepting bribes like gold bars and cash, allegedly in exchange for political favors. He has maintained his innocence and plans to appeal. The Manhattan U.S. Attorney's Office indicated that both the defense and prosecution missed the unredacted material during trial, emphasizing that it likely did not affect the jury's guilty verdict on all 16 counts, including wire fraud, obstruction of justice, and illegal foreign agency activities. Menendez, once a senior figure in the Senate as the chair of the foreign relations committee, now faces sentencing in January with a potential for decades in prison.Bob Menendez jury was mistakenly shown improper evidence, prosecutors say | ReutersGary Wang, former chief technology officer of FTX, is assisting federal prosecutors by developing software to detect fraud in both stock and cryptocurrency markets. Wang, who previously wrote the code allowing ex-FTX CEO Sam Bankman-Fried to siphon billions from FTX customers, has been cooperating with the government since FTX's collapse. Prosecutors are asking for leniency in Wang's upcoming sentencing, highlighting his proactive efforts to prevent similar crimes. His new tool, details of which remain confidential to protect its effectiveness, is valued by prosecutors for its potential in identifying financial crimes. This cooperation follows Bankman-Fried's recent 25-year prison sentence for fraud and misuse of $8 billion in customer funds, while other former FTX associates, like Caroline Ellison and Nishad Singh, received lighter sentences due to their cooperation. Wang, the last of Bankman-Fried's close associates awaiting sentencing, was instrumental in exposing the scheme by testifying that Bankman-Fried directed him to alter FTX's code to grant Alameda Research unauthorized access to customer funds.Bankman-Fried lieutenant builds fraud detection tool for prosecutors | ReutersA federal appeals court has struck down a New York law that heavily restricted antiques dealers from selling or displaying ivory and rhinoceros horn items, ruling it unconstitutional. The 2nd U.S. Circuit Court of Appeals found that the law, which limited ivory content in antiques to less than 20%, overstepped by restricting dealers' First Amendment commercial speech rights. Judges argued that the law prevented dealers from communicating important details about legally marketable items, deeming this an excessive speech restriction. While federal law already restricts ivory sales under the Endangered Species Act, it allows for goods with up to 50% ivory, whereas New York's stricter limit of 20% was intended to curb poaching of endangered species. However, the court ruled that New York's law also blocked the sale of items permitted in interstate and international trade, making it too broad. The decision was a setback for animal rights groups that supported the law to protect vulnerable wildlife, although the Humane Society noted that New York could still enforce the law against local buyers.New York ivory ban for antiques dealers voided by US appeals court | ReutersLaw firm revenue surged nearly 12% in the first three quarters of the year, driven by increased demand for legal services and higher productivity, according to Citi's law firm banking group. The top 50 law firms saw especially notable gains, with revenues up 14%, demand growth at 3.6%, and productivity rising by 2.9%. Gretta Rusanow from Citi's Law Firm Group highlighted 2023 as potentially one of the strongest years for the industry, citing steady demand momentum quarter by quarter. Industry-wide demand rose by 3.2%, with lawyer productivity improving as headcount growth slowed to 1.3%, returning to historical norms. Expense growth was 7.5%, with overhead costs increasing by 8.2% and compensation expenses by 6.7%. Legal services demand spanned diverse practice areas, notably in litigation, regulatory issues, investment management, and bankruptcy. Although transactional demand has been quiet, Rusanow anticipates a rebound in mergers and acquisitions activity. Law firms also invested in technology upgrades, including new practice management tools and generative AI, which contributed to higher expenses. Law Firm Revenue Soars 12% as Lawyers Get Back to Being Busy This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.minimumcomp.com/subscribe

SentiLink is at the forefront of fraud prevention and identity verification, offering innovative solutions to help financial institutions tackle synthetic fraud, identity theft, and more. We're thrilled to have them onboard as partners in our mission to equip you with the tools and knowledge you need to stay ahead in this ever-evolving landscape.Stay tuned for more great episodes and insights—thanks again to SentiLink for supporting the podcast! Visit: https://www.sentilink.com/ and learn all about them!----------------------------Welcome back to another exciting episode of "Banking on Fraudology"! I'm your host, Hailey Windham, and today we're diving deep into the world of fraud detection with our special guest, Jen Martin. With over 15 years of banking experience and a robust background in criminal justice and statistics, Jen brings a wealth of knowledge and a passion for data-driven solutions in the fight against fraud.In this episode, Jen takes us through her fascinating career journey, from her early aspirations to become a crime statistician to her pivotal roles in banking and fraud prevention. We'll explore the transformative power of real-time data models and advanced analytics in combating fraud, as well as the critical importance of collaborative efforts across different departments within an organization.We'll also discuss the evolving landscape of fraud threats, particularly post-pandemic, and the need for quick, adaptable strategies to stay ahead. Jen provides invaluable insights into tackling specific challenges such as check fraud and maintaining a balance between effective fraud controls and a positive customer experience. We'll touch on the strain of staff retention and the importance of ongoing training, especially in frontline positions.Join us as we unravel the complexities of fraud prevention, the necessity of creative data utilization, and the indispensability of cross-functional teamwork. Stay tuned for practical advice and inspiring stories from one of the leading voices in the fraud-fighting community. Let's get started!About Hailey Windham:As a 2023 CU Rockstar Recipient, Hailey Windham, CFCS (Certified Financial Crimes Specialist) demonstrated unbounding passion for educating her community, organization and credit union membership on scams in the market and best practices to avoid them. She has implemented several programs within her previous organizations that aim at holistically learning about how to prevent and detect fraud targeted at membership and employees. Windham's initiatives to build strong relationships and partnerships throughout the credit union community and industry experts have led to countless success stories. Her applied knowledge of payments system programs combined with her experience in fraud investigations offers practical concepts that are transferable, no matter the organization's size. Connect with Hailey on LinkedIn: https://www.linkedin.com/in/hailey-windham/ ---------------------------- Banking on Fraudology is part of the Fraudology Network, and produced by Podyssey.io.

Speaker Resources:Neo4j+Senzing Tutorial: https://neo4j.com/developer-blog/entity-resolved-knowledge-graphs/#neo4jWhen GraphRAG Goes Bad: A Study in Why you Cannot Afford to Ignore Entity Resolution (Dr. Clair Sullivan): https://www.linkedin.com/pulse/when-graphrag-goesbad-study-why-you-cannot-afford-ignore-sullivan-7ymnc/Paco's NODES 2024 session: https://neo4j.com/nodes2024/agenda/entity-resolved-knowledge-graphs/Graph Power Hour: https://www.youtube.com/playlist?list=PL9-tchmsp1WMnZKYti-tMnt_wyk4nwcbHTomaz Bratanic on GraphReader: https://towardsdatascience.com/implementing-graphreader-with-neo4j-and-langgraph-e4c73826a8b7Tools of the Month:Neo4j GraphRAG Python package:  https://pypi.org/project/neo4j-graphrag/Spring Data Neo4j: https://spring.io/projects/spring-data-neo4jEntity Linking based on Entity Resolution tutorial: https://github.com/louisguitton/spacy-lancedb-linkerhttps://github.com/DerwenAI/strwythuraAskNews (build news datasets) https://asknews.app/The Sentry https://atlas.thesentry.org/azerbaijan-aliyev-empire/Announcements / News:Articles:GraphRAG – The Card Game https://neo4j.com/developer-blog/graphrag-card-game/Turn Your CSVs Into Graphs Using LLMs https://neo4j.com/developer-blog/csv-into-graph-using-llm/Detecting Bank Fraud With Neo4j: The Power of Graph Databases https://neo4j.com/developer-blog/detect-bank-fraud-neo4j-graph-database/Cypher Performance Improvements in Neo4j 5 https://neo4j.com/developer-blog/cypher-performance-neo4j-5/New GraphAcademy Course: Building Knowledge Graphs With LLMs https://neo4j.com/developer-blog/new-building-knowledge-graphs-llms/Efficiently Monitor Neo4j and Identify Problematic Queries https://neo4j.com/developer-blog/monitor-and-id-problem-queries/Videos:NODES 2023 playlist https://youtube.com/playlist?list=PL9Hl4pk2FsvUu4hzyhWed8Avu5nSUXYrb&si=8_0sYVRYz8CqqdIcEventsAll Neo4j events: https://neo4j.com/events/(Nov 5) Conference (virtual): XtremeJ https://xtremej.dev/2024/schedule/(Nov 7) Conference (virtual): NODES 2024 https://dev.neo4j.com/nodes24(Nov 8) Conference (Austin, TX, USA): MLOps World https://mlopsworld.com/(Nov 12) Conference (Baltimore, MD, USA): ISWC https://iswc2024.semanticweb.org/event/3715c6fc-e2d7-47eb-8c01-5fe4ac589a52/summary(Nov 13) Meetup (Seattle, WA, USA): Puget Sound Programming Python (PuPPY) - Talk night Rover https://www.meetup.com/psppython/events/303896335/?eventOrigin=group_events_list(Nov 14) Meetup (Seattle, WA, USA): AI Workflow Essentials (with Pinecone, Neo4J, Boundary, Union) https://lu.ma/75nv6dd3(Nov 14) Conference (Reston, VA, USA): Senzing User Conference https://senzing.com/senzing-event-calendar/(Nov 18) Meetup (Cleveland, OH, USA): Cleveland Big Data mega-meetup https://www.meetup.com/Cleveland-Hadoop/(Nov 19) Chicago Java User Group (Chicago, IL, USA): https://cjug.org/cjug-meeting-intro/#/(Dec 3) Conference (London, UK): Linkurious Days https://resources.linkurious.com/linkurious-days-london(Dec 10) Meetup (London, UK): ESR meetup in London by Neural Alpha(Dec 11-13) Conference (London, UK): Connected Data London https://2024.connected-data.london/

Join Renee Perez, National Director of Sales-Financial Crimes for Jack Henry, as we discuss innovative new areas where fraudsters are using AI to commit fraud, and then a discussion on areas where AI is being used to fight back.Whitepaper:https://fedpaymentsimprovement.org/strategic-initiatives/payments-security/scams/Send us a textPresented by Remedy ConsultingTechnology Contract Negotiation & System Assessments, T&C Improvements, and FI Strategic Planning.For more information on BankTalk:BankTalk WebsiteSubscribe to BankTalk NewsRemedy Consulting WebsiteRemedy LinkedInTo speak on the BankTalk Podcast, please email us.

The AI Dream Team: Strategies for ML Recruitment and Growth // MLOps Podcast #267 with Jelmer Borst, Analytics & Machine Learning Domain Lead, and Daniela Solis, Machine Learning Product Owner, of Picnic. // Abstract Like many companies, Picnic started out with a small, central data science team. As this grows larger, focussing on more complex models, it questions the skillsets & organisational set up. Use an ML platform, or build ourselves? A central team vs. embedded? Hire data scientists vs. ML engineers vs. MLOps engineers How to foster a team culture of end-to-end ownership How to balance short-term & long-term impact // Bio Jelmer Borst Jelmer leads the analytics & machine learning teams at Picnic, an app-only online groceries company based in The Netherlands. Whilst his background is in aerospace engineering, he was looking for something faster-paced and found that at Picnic. He loves the intersection of solving business challenges using technology & data. In his free time loves to cook food and tinker with the latest AI developments. Daniela Solis Morales As a Machine Learning Lead at Picnic, I am responsible for ensuring the success of end-to-end Machine Learning systems. My work involves bringing models into production across various domains, including Personalization, Fraud Detection, and Natural Language Processing. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links Website: --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Jelmer on LinkedIn: https://www.linkedin.com/in/japborst Connect with Daniela on LinkedIn: https://www.linkedin.com/in/daniela-solis-morales/

In this episode of Pathmonk Presents, host Ernesto welcomes Brianna Valleskey, Head of Marketing at Inscribe. Brianna shares insights into Inscribe's AI-powered solutions for fraud detection and risk assessment in the financial services sector. She discusses how their technology analyzes application data, including documents and open banking information, to identify trustworthy and creditworthy customers. Brianna also delves into Inscribe's marketing strategies, emphasizing the importance of data-driven decision-making and the role of their website in client acquisition. The conversation covers emerging trends in fraud prevention, the impact of generative AI, and valuable tips for effective marketing leadership.

In this episode of Fraud Talk, Mason Wilder sits down with Marta Cadavid, founder of NoFraudLatin, to explore the unique challenges of detecting and preventing fraud in Latin America. Cadavid shares her journey, including the creation of a Latin American-specific fraud tree, and how cultural nuances shape the approach to fraud communication. They discuss the vital role of artificial intelligence in analyzing human behavior and predicting fraudulent actions.

In this episode, we explore the remarkable career of Doug Bramlett, a military and law enforcement veteran who guarded Air Force One. He shares inspiring stories of his journey, offering valuable insights into police training, fraud investigations, and the challenges first responders face. Doug discusses the psychological toll of the job, emphasizing the importance of seeking support and counseling. He highlights resources like the VA's trauma recovery and Travis Howze's Post Traumatic Purpose seminars for healing and resilience.--------- EPISODE CHAPTERS ---------(0:00:02) - Doug's Law Enforcement Journey(0:12:41) - Police Firearms Training Challenges and Adaptations(0:19:28) - Police Officer to Fraud Investigator Transition(0:24:03) - Specialized Government Investigations and Fraud Detection(0:31:16) - Community Support in Child Abduction Case(0:38:21) - Tragic Discovery in Missing Person Case"(0:47:18) - Seeking Help and Healing(0:52:33) - Law Enforcement and Medical Preparedness(1:00:12) - Perspectives on Life and Purpose(1:04:38) - Navigating PTSD and Seeking HelpSend us a text

The financial industry grapples with the question of who should bear the cost of scam-induced fraud losses: consumers or banks. Authorized push payment (APP) fraud presents unique challenges for fraud detection systems, as victims unwittingly authorize transactions. Financial institutions are implementing advanced technologies and strategies to combat these scams, while regulators explore new policies to protect consumers and hold banks accountable in the evolving digital banking landscape. Today's Stocks & Topics: SNOW - Snowflake Inc., Market Wrap, SWK - Stanley Black & Decker Inc., BROS - Dutch Bros Inc., Fraud Detection: Who Should Cover Scam Losses—Banks or Consumers?, CELH - Celsius Holdings Inc., Key Benchmark Numbers and Market Comments for: Treasury Yields, Gold, Silver, Oil and Gasoline, Annuities, Fossil Fuel, NEM - Newmont Corp., Deglobalization, REPX - Riley Exploration Permian Inc., JXN- Jackson Financial Inc., GD - General Dynamics Corp.Our Sponsors:* Check out Moorings: moorings.com* Check out eBay Auto: www.ebay.comAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Welcome to another episode of our Learning from Financial Fraud Series. In this thirteenth episode, Craig Jeffery, Managing Partner at Strategic Treasurer, shares insights into a major fraud case. The organization faced multiple sophisticated attacks across multiple payment channels. Listen in as Craig walks us through the attack method, the loss, and the key takeaways.  

On this episode, host Sima Vasa welcomes Andrew Moffatt, CEO and Co-Founder of Qrious Insight, to explore the evolution of data analytics, the impact of AI and the future of market research. Andrew discusses how the integration of behavioral data with advanced analytics is transforming the way businesses understand and engage with their audiences.  Key Takeaways: (01:19) Andrew reflects on 25 years in market research.(03:07) Founding Qrious Insight and its evolution.(06:20) The importance of behavioral data for accurate insights.(12:53) Informing ad placement with behavioral data.(18:25) High retention rates in behavioral data tracking.(27:31) Generational differences in data privacy and acceptance.(34:30) AI's transformative role in data analytics.(36:00) The future potential of synthetic data models.(37:00) Bridging insights and marketing with behavioral data. Resources Mentioned: Paradigm SampleSima VasaQrious Insight website Thanks for listening to the Data Gurus podcast, brought to you by Infinity Squared. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show, and be sure to subscribe so you never miss another insightful conversation. #Analytics #MA #Data #Strategy #Innovation #Acquisitions #MRX #Restech

Pushpendra Mehta meets with Craig Jeffery, Managing Partner at Strategic Treasurer, to review the latest treasury news and developments. Topics of discussion include the following: Payments Fraud Detection: Predictive AI vs. Generative AI Payment fears putting businesses off overseas growth Global economy tipped for soft landing BofA adds intelligent transaction search to banking platform

In today's episode, we'll hear from Paul Galloway on natural language processing. What is it, and how does it differ from machine learning? How is it used in finance and fraud detection? Tune in to find out. 

¡APRENDE SecTY Podcast! EP 4.29 Como la Inteligencia emocional y la inteligencia artificial coexisten en la ciberseguridad La inteligencia emocional y la inteligencia artificial pueden coexistir y mejor aún, complementarse para obtener una ciberseguridad saludable. Escucha los detalles en este episodio 29 de la cuarta temporada.   Video sobre los detalles del incidente masivo de #Crowdstrike y #Microsoft del 19 de julio 2024. Canal de Aprende SecTY en YouTube: https://youtu.be/REHlVcFXy7s   Caso de eBay y la IA: Crees que acabas de comprar un Monet... pero no: la inteligencia artificial identifica en eBay 40 obras de arte falsas (genbeta.com)   How AI for Fraud Detection is Revolutionizing the Fight Against Fraud (emb.global)   Generative AI Revolutionizing Ecommerce Fraud Prevention & Cybersecurity (kensium.com)   Si deseas orientación o evaluación sobre ciberseguridad para tu negocio o capacitar a tus empleados sobre seguridad de información en tu negocio, entra a nuestra página en https://wwwaprendesecty.com o escríbeme a aprende@sectycs.com para poder ayudarte porque ofrecemos capacitación de seguridad a grupos de usuarios para pequeños negocios. EBOOK DISPONIBLE! Manéjalo tú, maneja tu propio proceso de vulnerabilidades de tu negocio. Adquiérelo ya aquí: https://bit.ly/ebookmanejavulnerabilidades Taller Fortalece tu Primera Línea Contra las Amenazas Cibernéticas: https://www.aprendesecty.com/shop Consulta de Seguridad: Este episodio es presentado por AeroNet. Empresa de tecnología 100% puertorriqueña, líder en soluciones de conectividad para negocios y residencias en Puerto Rico. Go Faster, Go Save. AeroNet Wireless - Reliable High Speed Internet (aeronetpr.com) ¡Escucha el video sobre este tema en el canal de YOUTUBE de Aprende SecTY y suscríbete! https://www.youtube.com/@aprendesecty/?sub_confirmation=1    Recuerda: Síguenos en Facebook, Instagram, X y LinkedIN como: @SecTYCS Envíame tus preguntas o recomendaciones a: aprende@sectycs.com Deja tu reseña en iTunes/Apple Podcast y compártelo con personas que necesiten mejorar la seguridad en su negocio y en su vida. Puedes escucharnos también por medio de: iTunes/Apple Podcast, Spotify, YouTube Music, Amazon Music y iHeartRadio.

Welcome to another episode of our Learning from Financial Fraud Series. In this twelfth episode, we'll explore what can be learned from a recent payment flows assessment that led to discovering a fraudulent loss in another area. Craig Jeffery walks us through the attack method, the loss, and the key takeaways. Listen in to learn more.    More from this series: https://strategictreasurer.com/learning-from-financial-fraud-series/?utm_source=TUP312

In this podcast episode, we discuss why ecommerce fraud prevention solutions reduce chargebacks and how they improve the shopper experience. Our featured guests on the show are Harish Manipelli, Chief Technology Officer and Tariq Ahmed is Managing Director for Canada at zumigo.com.  Topics discussed in this episode: Why card-not-present fraud is a big problem for online merchants. How fraudsters use advanced methods like bots and fake identities. Why merchants must balance fraud prevention with good customer experience. How Zumigo's solution gives a trust score by checking multiple data points in real time. Which data sources Zumigo uses for verification, like phone number intelligence. How Zumigo prevented a costly fraudulent order in a case study. How Zumigo stops payment processors from flagging good transactions. Why Zumigo's passwordless login improves security and reduces cart  abandonment. How Zumigo uses AI/ML models and deterministic verification for risk decisions. Links & Resources  Website: https://zumigo.com/deriskify-for-ecommerce/  Video: http://info.zumigo.com/deriskify2024  Shopify App Store: https://apps.shopify.com/deriskify  LinkedIn: https://www.linkedin.com/in/harishmanepalli/  Get access to more free resources by visiting the podcast episode page att.ly/16H8V  Subscribe & Listen Everywhere:  Listen On: ​ecommercecoffeebreak.com | Apple Podcasts | Spotify | YouTube | Podurama  How did you like this episode? Send us a Text Message.Join the "Founder's Sidekick" Program - The private entrepreneur support solution that helps you make smarter business decisions. Visit ecommercecoffeebreak.com/start to get started.Sign up for our free newsletter and become a smarter Shopify merchant. We scour and curate content from 50+ news sources, saving you hours of research and helping you stay on top of your ecommerce game with the latest news, insights, and trends.Ideal for online sellers, merchants, marketers, and DTC brands on Shopify who want to stay informed but are short on time. Join free. Every Thursday in your inbox. 100% free. Sign up at https://newsletter.ecommercecoffeebreak.com

Have you ever wondered how banks use AI to foresee and handle risks? What makes AI so effective?How does AI sift through massive data sets to detect fraud? Can AI really outsmart fraudsters?Could AI chatbots soon replace human agents? How do they boost customer satisfaction?Hey there, tech enthusiasts! Today we explore the practical applications of AI in risk management, fraud detection, and credit risk assessment with industry experts David Van Bruwaene, CEO of Fairly AI, and Michelle Allade, Director of Model Risk Management at Pathward Financials. As they share their experiences and insights on leveraging AI for a more efficient and equitable financial landscape. Watch now to Unlock the mysteries of AI in finance and see how it's shaping the future of the industry.

In this episode, Vadim Kleyner, CEO of Smartland, and I discuss AI's practical applications in real estate. Key topics covered: Practical applications of AI in business and optimizing FaceBook advertising strategies. Significance of AI in decision-making. Vadim spends 10% of his 12-16 hour office day on ChatGPT for communication, reports, and verifying tenant information. Smartland has plans to upgrade their chatbot, Lisa, to an AI-based version. Ambitious plan to upload 15 years of data into an AI environment for better decision-making and reporting. Highlights of the conversation: AI in databases: Proprietary use of a custom GPT to analyze tenant payment behavior. Difference between 3D vector databases and traditional databases for efficient data processing. Collaboration to create a custom system for housing corporate intelligence. Use of ChatGPT: Analyzing data points from FaceBook ads reduces costs and dramatically increases conversions. Detailed discussion of the underwriting process for buying apartment buildings and the role of data. From Vadim: Why should real estate professionals pay attention to AI today? The industry is shifting from manual, labor-intensive processes to more efficient, AI-driven methods. There will be significant changes in how and where people spend time in the industry, with a big shift in human capital investment over the next five years​​. How do you use AI personally? Uses personal productivity tools embedded with AI for tasks like checking grammar and readability in emails. Finds these tools valuable for consistent work oversight and improvement​​. Any easy wins for listeners to test and try with AI? Recommends playing around with ChatGPT for various tasks such as writing essays or job descriptions. Highlights that these tools can be a great starting point and significantly ease the drafting process​​. ***** The only Podcast you need on real estate and AI.   Learn how other real estate pros are using AI to get ahead of their competition.   Get early notice of hot new game-changing AI real estate apps.   Walk away with something you can actually use in every episode.   PLUS, subscribe to my free newsletter and get: • practical guides, • how-to's, and • news updates   All exclusively for real estate investors that make learning AI fun and easy and insanely productive, for free.   EasyWin.AI

In this crucial episode of Scam Rangers, we explore the dark and disturbing world of Sextortion. This crime occurs when online predators trick individuals, often teens, into sharing nude images or videos and then use these compromising materials to extort money, more images, or other demands. These predators threaten to share the images with the victim's friends and family if they don't comply. Our guest, Paul Raffile, a Senior Intelligence Analyst with a career dedicated to investigating online crimes and financial scams, joins us to shed light on this pressing issue.Key Discussion Points:Paul explains how sextortion scams unfold, the social media platforms commonly used by predators, and the emotional impact on victims, particularly teens. He shares advice for social media companies on preventing these scams, drawing on strategies from financial institutions that detect account takeovers. We also explore how money is transferred to criminals and the risk signals financial institutions can monitor to spot suspicious activities.Resources:Follow Paul on LinkedIn: https://www.nbcnews.com/tech/internet/sextortion-yahoo-boys-snapchat-tiktok-teen-wizz-rcna134200NCRI Report: https://networkcontagion.us/reports/yahoo-boys/New York Times: https://www.nytimes.com/2024/05/15/nyregion/social-media-scam-sextortion.htmlArticle on WIRED: https://www.wired.com/story/yahoo-boys-scammers-facebook-telegram-tiktok-youtube/Training materials on NBC News: https://www.nbcnews.com/tech/internet/sextortion-yahoo-boys-snapchat-tiktok-teen-wizz-rcna134200This podcast is hosted by Ayelet Biger-Levin who spent the last 15 years building technology to help financial institutions authenticate their customers and identify fraud. She believes that when it comes to scams, the story starts well before the transaction. She has created this podcast to talk about the human side of scams, and to learn from people who have decided to dedicate their lives to speaking up on behalf of scam victims and who take action to solve this problem.Be sure to follow her on LinkedIn and reach out to learn about her additional activities in this space. https://www.linkedin.com/in/ayelet-biger-levin/ScamRanger: https://scamranger.ai/

Host Victoria Guido welcomes Wendell Adams, CEO of PrimeLab.io, as he talks about his lifelong passion for technology and entrepreneurship. Wendell shares his experiences, from hacking electronics as a child to studying various fields in college and eventually starting his own business. He emphasizes the importance of understanding market needs and leveraging language to make technology accessible. Wendell's drive to improve encryption and data security led to the formation of PrimeLab; a company focused on making encryption functional and accessible without compromising performance. Wendell discusses PrimeLab's strategic direction and market fit. He outlines the challenges and opportunities in the entertainment industry, emphasizing the need for innovative solutions that respect user control and privacy. Wendell also shares insights into how PrimeLab's technology can democratize data access and enhance business processes. The episode concludes with a reflection on the future of AI and encryption technologies and Wendell's advice for aspiring entrepreneurs to think critically and creatively about their ventures. PrimeLab.io (https://primelab.io/) Follow PrimeLab.io on LinkedIn (https://www.linkedin.com/company/primelab-io/), or X (https://x.com/PrimeLab4). Follow Wendell Adams on LinkedIn (https://www.linkedin.com/in/wendell-a-83317895/). Follow thoughtbot on X (https://twitter.com/thoughtbot) or LinkedIn (https://www.linkedin.com/company/150727/). Transcript:  AD: We're excited to announce a new workshop series for helping you get that startup idea you have out of your head and into the world. It's called Vision to Value. Over a series of 90-minute working sessions, you'll work with a thoughtbot product strategist and a handful of other founders to start testing your idea in the market and make a plan for building an MVP. Join for all seven of the weekly sessions, or pick and choose the ones that address your biggest challenge right now. Learn more and sign up at tbot.io/visionvalue.  VICTORIA: This is the Giant Robots Smashing Into Other Giant Robots podcast, where we explore the design, development, and business of great products. I'm your host, Victoria Guido. And with us today is Wendell Adams, CEO at PrimeLab io. Wendell, thank you for joining us. WENDELL: Thanks for having me. So, question, actually, where'd you guys come up with the name? VICTORIA: You know, I have asked this before, and I think I remember the answer. I might have to go back to the 500th episode to get it, but I think it was just robots was already kind of a theme at thoughtbot. I mean, thoughtbot, obviously, has robot in the name. Joe might have the best answer. And we have our special co-host, Joe Ferris. Who better to answer? JOE: [chuckles] Yes, I'm not sure who better to answer, probably Chad. I don't remember the answer either, but happy to be here to speculate with the two of you. It comes from the blog. We named the blog Giant Robots Smashing Into Other Giant Robots and then used it for our podcast. But I don't remember where the blog name came from. WENDELL: It kind of reminds me of the Robot Wars thing, like, where they would have competitors driving around the robots and then smashing into each other, trying to flip them over and disable them. JOE: That was excellent. I also watched that. WENDELL: [laughs] VICTORIA: Yeah, it's a pretty great name. I really enjoy being a host. And, you know, I go out to local San Diego events and meet people and introduce myself as a co-host of Giant Robots Smashing Into Other Giant Robots. It's usually pretty funny [laughter], which is where I met you, Wendell; we met at a San Diego CTO Lunches, which was super fun. WENDELL: Yeah, I always enjoy any type of tech conversation or anything else. I thought that was a lot of fun to sit down and just talk with people and talk about what they're working on. VICTORIA: I love that, yeah. And before we dive into the tech and get to hear more about PrimeLab, I just want to start a little more socially question. What did you do last weekend, Wendell? WENDELL: It was my father-in-law's birthday party at Legoland. We took my daughters my mother-in-law, and we all went to Legoland. It was a lot of fun. Although, honestly, I prefer the San Diego Zoo over Legoland, so... VICTORIA: Can you please describe what Legoland is to people who may not know? WENDELL: Okay. Legoland is based in Carlsbad, and it's really ideal for, like, four to nine-year-olds. And they have, like, miniatures of all the different cities. Actually, the SF miniature that they have is crazy detailed with Chinatown and everything else. They did an amazing job there. They actually...I think they just redid the San Diego part of it. But the miniatures are really cool, seeing all this stuff. They have different rides performers, but it's definitely, like, one of those things that it's more for kids to go and kind of experience. If you're an adult, you're going to love a lot of the processes that go into place, like how they built things, but mostly, yeah, it's very much kid rides and stuff like that. VICTORIA: I imagined it to be, like, life-size Lego buildings, but maybe I'm...that's very interesting all those other things you could do there. WENDELL: Well, like, they have the One World Trade Center, and I think it's, like, 25 feet tall. It is, like, the replica of it. It's kind of interesting, too, because not all the Legos that they build, they're huge, are solid Legos. So, it's like, they'll do where it's like, on the outside, they'll do a base, and then they'll build it. There's a replica of a Lamborghini. That one's life-size. But it's heavy. It's, like, 2,000 pounds, something like that. VICTORIA: Is that as much as a regular Lamborghini weighs, too, 2,000 pounds? It can't be that far up. WENDELL: I don't know. No, I don't think it...no, it couldn't be. VICTORIA: I have no idea how much cars [laughs] weigh. What about you, Joe? Did you do anything fun this weekend? JOE: Not a lot. It was supposed to be my son's first soccer game ever, but it rained here in Boston, so they postponed it. Sunday he went to my parents' house for a grandma day, and so I did nothing. I ate cookies. WENDELL: [laughs] VICTORIA: Wait, what kind of cookies were they, though? JOE: They were chocolate chip cookies. VICTORIA: That's so good. JOE: They were good. They were brown butter chocolate chip cookies, I should say. VICTORIA: Were they homemade, or did you get them somewhere? JOE: They were. We made them in this home. VICTORIA: Oh, that's the best. Yeah, love that. I got some fancy cookies that someone else made, and they were also [laughs] very good. And then, yeah, I've just been having cookies pretty much every day. So, that's been my time. WENDELL: My mother-in-law recently made me peanut butter cookies, and those are my favorite kind of homemade cookies. VICTORIA: Okay. Noted. You'll get a post-podcast gift of peanut butter cookies [laughter]. I love that. It's so great to hear a little bit more about each of you as, like, in a personal way before we dive into AI. And tell me a little bit more about your background and what led you to PrimeLab. WENDELL: I've always kind of, like, been a hacker, so to speak, just from a technical standpoint. My one grandfather was an engineer. He worked for GM designing, like, assembly arms and stuff like that. And then my other grandfather was a master electrician. So, I've always been the person that, like, just worked on things, got stuff together. You know, there's a lot of stories. Like, there's the story about when I broke my grandmother's workbench, rocking bench out front, and it was all aluminum. I remember telling my grandfather, and he's like, "Oh, what are you going to do?" And I was like, "Buy a new one?" He's like, "You got money?" I said, "No." And he said, "Well, you better figure how to make it then." So, ironically, it's half aluminum, half wood. We took wood, sanded it down, and stuff. So, it's just like I've always been an entrepreneur. I've always been interested in this kind of stuff. I used to hack VCRs, and PlayStations, and all kinds of stuff. I always liked parts and components and rewiring things. And as I got older, I also really liked math and all those things. And I wanted to understand more about how the world works, so to speak, like why it works the way it does, not just from a technology standpoint. But why do people think the way that they do? Why do things behave the certain way they do? So, initially, I started going to college. I thought I might be a math professor, and then decided to get degrees in business, economics, finance, marketing, consumer product goods, and comparative religions. So, while I was in college, I started working on, like, hacking, different video games, writing JavaScript, writing Java, all kinds of stuff. And then, eventually, even writing mobile applications early on, and then just analyzing because I always liked to build phones, too. I would take apart phones. And I really was curious about, like, how to make things faster, more efficient, and better. So, now to bring it down, like, how to make things accessible, where it benefits some of the smallest people and make it where it's a greater opportunity for someone to come out ahead of something. Like, one thing that I learned from my marketing degree is language matters. So, it's like, all the marketing it's not anything special. It's just they intentionally create language barriers that cause people not to feel as accessible with it. And then, like, you hire a consultant or something to just basically teach you about those language barriers. And I think every industry has, like, SAT, or LTM, or something like these abbreviations that mean a lot of different things. And it causes bottlenecks if you don't speak the language. So, understanding the language but also learning about how was very helpful from a standpoint on the marketing side. And I always try to figure out how do I make this accessible to people who don't understand that language? VICTORIA: And what was the turning point where you decided to start PrimeLab, and what made you realize there was a company there? WENDELL: It was a project I've been working on since at least 2011, honestly. And just as a heads up, PrimeLab as a whole works with encrypted data for AI models and to speed that up and everything else. So, early on, I was very obsessed with how advertising works through, like, stealing user data, which stealing is different, here or there, the sense of privacy, the sense of, like, how things could run, and the sense of messaging. And initially, a lot of it was using encryption as an overlay in, like, the pixel application space, which is always a way to hack or get into it. And it slows everything down. So, I had always been working on trying to figure out how do you speed up and embed security so it's actually functional? And it took a while to figure out, like, give encryption functionality, like, make the encryption something that you could actually execute on. And, actually, one of the things that really helped is the blockchain space there's a lot of, like, hash trees and everything else, like, where people are innovating in that. That's really helped innovate encryption as a whole from understanding, like, Merkle trees, hash graphs, and everything else to make it more functional and faster. Because people are trying to speed up distributed networks and stuff, but the actual technology that they built, like Hedera is...What Hedera has done with Hashgraphs and everything else—really amazing. I'm glad that they open-source stuff like that. But it's also really interesting just to see how things push forward. So, like, when I first started, like, RAM was, like, 256 in a phone. So now, you know, you can get multiple gigabytes, which makes it a lot more capable to do encryption, decryption, and work more in the functional space of things. The bigger problem that you have on the data part is how an application communicates because there's so many levels of abstraction. Like, you have the Swift language that communicates into something else that then communicates into something else. Like, right now, we're talking on a system that's recording us over the internet through a browser, all those different things. And it's an approximation of what the data is and what we sound like. It's not an absolute. So, I was really interested in when you have absolutes, and you can verify those absolutes, what can you do with that? A few years ago, I felt like we got to a point where we could actually execute those things and actually deliver on that. So, therefore, I decided to start PrimeLab with my co-founder, who I really liked and enjoyed. And we've had a lot of really great advisors, where people have helped us continuously. Over, you know, the decade-plus of working on this, I've gotten a lot of input from some of the smartest people I know, from people who have designed full server racks for AWS to literally a good friend of mine that built cloud storage. His name's on the patent for it. So, that kind of stuff has really helped me understand and build this where it can communicate the lowest possible level. VICTORIA: Yeah, and to just recap and reflect that back a little bit, it sounds like you were always interested in how to make encryption faster and lighter weight, and so you could build it in and build in security without impacting the performance of the applications. And then meeting your co-founder and the advancement of technology, this time a couple of years ago, led you to think, okay, let's really go forward with this. WENDELL: Kind of rephrasing, I was always interested in control. So, like, one of the things that really interested me...so, I started a video game store buying and selling, like, video games and trading cards and stuff when I was roughly ten and a half or so, and then sold it roughly when I was 17, which is how I paid for quite a bit of college and likewise. But the things that really interested me about that is it went out of business three to four months afterwards because the person who basically bought the rest of it bought too much of Madden. And Madden, at this time, the margins were, like, a buck, as you go all the way through, and the price drops immensely. So, I wanted to really understand why that happened. What you kind of get to is, like, they didn't have control over it, just, like, the bulk orders methodology, where they would buy the whole entire supply. And what I've seen over the years, be it Apple, Google, or anything else, is, like, that was...in that example, that's a game publisher, EA, flexing control, right? But more and more companies are flexing control on a platform like now with Facebook or advertising. If you think about what Google used to do, Google used to provide a lot more insights when you had your own website. You used to know your own keywords. You used to know a lot of things about your users who come through. More and more, Facebook and Google try to stop that. And they're really the ones determining your own user personas for you. So, you become dependent upon them. So, I wanted to say, okay, from a business standpoint, how do you implement control and privacy where it's permissioned? And encryption was one of the answers that I came to. But then it was, how do you make encryption functional then to actually execute on control? Because unless the system is secure, faster, cheaper, better, it's never going to get adopted. VICTORIA: That makes sense. Thank you for sharing that. And you mentioned your founder. I'm curious, how does your founder kind of complete what you needed to be able to get the business up and running and off the ground? WENDELL: He has a robotics degree, so he had launched several products that had failed. And he wanted to learn marketing after they had failed. So, we have a similar like mindset about, like, control and functionality for how something may or may not work, and that allowed us to communicate well. So, like, I have a lot of friends and stuff. But the thing that allows me and my co-founder to work really well is that we come from things in different angles, but we have the same language that we speak. So, like, that's what I was talking about before, like, LTMs or otherwise, like, language really matters from how you can move something forward when you're talking in different industries. And just with him, there's a lot of stuff that you don't have to say. You can skip a lot of filler and then go straight to what something might be or a solution or something. Or if we have to jump to a tech abbreviation, to a market abbreviation, to a financial abbreviation, he's one that can follow along with me really quickly and then teach me a lot of things about operational execution because he's great at operations. I am not great at operations. VICTORIA: That's really interesting. And I think you're making a good point about, like, a shared language. And it reminds me of any product that you're building; if you want to sell it to a company and you want them to adopt it, you have to consider their language, their belief system, how to influence change within the organization. And I wonder if you could talk a little bit more about that with your experience at PrimeLab. WENDELL: I'll give you an example of a market that we decided to go after. So, instead of just working at, like, healthcare markets where you have, like, GDPR...for people who don't know GDPR or HIPAA, HIPAA is for the United States. GDPR is the EU privacy requirements, right? For the right to be forgotten and everything else. So, these are vernaculars that you need to know. But the requirements of each one is very different, and these are markets that we've learned being in tech and likewise. But we wanted to change it up. So, I wanted to go after the entertainment market as a whole, namely because after meeting with some select people, including a stunt man, this is going back a few years ago, I started to realize that the entertainment market was getting kind of screwed over quite a bit from a tech standpoint. Basically, tech goes through this thing where...someone wrote a great article about this. It's called Enshittification. But, basically, where they go they try to take over a whole entire market, where first they're providing great value to your users. And then, gradually, you enshittify your product to provide greater value to your investors. And then, gradually, you suck all of the value out of the room for both. Right now, if you look at Sora, what OpenAI is trying to do in entertainment, [inaudible 16:08], you kind of can see that happening. They're going, "Hey, here's a great value for it." And they're really pushing that stuff off. But the thing about the entertainment market that I think is really interesting is it's basically thousands and thousands of small businesses that are constantly going, it's so chaotic. It's not like tech and startups. There's a lot of overlay of, like, you know, people are looking for that top quartile film that's going to make the money back, and then long-term royalties that they can earn off of it, right? Whereas in tech, they're looking for those huge markups as well. So, I was really fascinated by it, but it was something that, like, we had to learn. Like it was something that I didn't know otherwise. So, it was literally...how we learned it was we took our tech stuff, and we would walk SAG-AFTRA strike lines. We would walk strike lines. We would go to entertainment events, and we would demo what we were trying to do, and we would show them. And then, oftentimes, we got really negative feedback right off the bat. And we're like, "No, no, no, so, you know, this is for you. Like, you could control. Like, this is going to help you." And then, after doing that enough times, talking to the SAG-AFTRA lawyers, and everything else from there, and all of the creatives, the creatives were coming to us and giving us ideas how to explain it because there's, like, three different formats. You have tech, business, creatives in the entertainment industry. And it's like, we could talk to the tech people. We could talk to the business people. But you really need the creatives. And, like, the wording of each one, like, each group of those is vastly different. So, having the creatives be able to explain something in 90 seconds that used to take me a couple of hours to dive into became really valuable. And also, in tech, like, you have this thing where it's feature creep, where you're like, oh, I'll add this, this, and this. Just to hear very coldly and bluntly, like, "If it does X, I'm interested. If it does Y, I'm not interested." That was very interesting or refreshing of, like, "Yes, you're going to solve these problems. But I need sign-off for everything in there." And it's kind of weird in the entertainment part, too. Like, you want to solve a problem without being a competitor to another vendor because you need so many different sign-offs. And if you're a competitor to another vendor, to a certain point, maybe that's going to cause a hiccup with sign-offs because there's 18 different cooks in the kitchen, so to speak, just so many different people that need to say, "Yes," all the way through with it. VICTORIA: Thank you. Yeah, that's really interesting. I'm curious, Joe, if you have an answer for that question as well, like, any experiences about navigating change and putting new products in place at different clients, different industries? JOE: I don't think I've had the same kind of resistance. Like, I haven't been on the front lines the way you described, like, literally in the, you know, going and talking to people on strike. I think I have more indirect experience talking to the people who are doing that. And certainly, like, I think there's generally a resistance to bringing in new technology without eliminating the old way of doing things if that makes sense. Like, people want the old ways of backup. Like they want to be able to go back to paper, which I empathize with. But that's frequently been a challenge for the people I've worked with is that they don't fully embrace the new process, which significantly reduces the value they would get from using it. I don't know if that's something you've encountered with PrimeLab. WENDELL: So, we were building another company of mine many, many, many years ago. I was building a website for this lumber company, and I remember showing up, and the owner was there. But it was his son that had commissioned it, and the owner didn't know about the website. And I was like, "Oh yeah, we'll get the website going." He goes, "Oh, this web thing it's a fad. It's never going to happen. You don't need websites. It's faxes." That's how everything would happen. But secretly, what was happening is they would get an order. They would print it off, and then they would fax it. So [laughs], I always thought that was crazy. VICTORIA: I mean, one of my local bars still just writes the order on a ticket and sends it on a clothesline down to the grill. So [laughs], sometimes old is good. But I think that you know, I want to hear more about where you found or how you found a product-market fit for PrimeLab and where that AI really becomes useful and ethical in the industry you're focusing on WENDELL: How I look at PMF (product-market fit)...and if you hear me just say PMF, that's what that means. So, how I look at PMF is I'm a little different in the fact that when I look at a product, or a technology, I don't just look at, like, so you have foundational tech. Like, okay, this is encryption. This is control, right? Now, where's the market that has the biggest problems with it? So, I like to go out and actually talk to those people. Because, like, when you're implementing tech, or you're implementing the product itself, it's different. So, you're like, you have the underlying infrastructure, but whether that's a button or a simple API that you need to build so it works different to hit that PMF...are you familiar with the term build a better mousetrap? VICTORIA: I don't think so. JOE: I'm familiar, but I'd still love to hear you describe it. WENDELL: So, in business school, and likewise, they will tell you "If you build a better mousetrap, people will come, and they will buy your product." So, like, it's a common thing where they're like, "Build a better mousetrap. People will come. They'll be there." And the thing that you learn with consumer product goods and marketing, though, is they actually built a better mousetrap, and it failed. And the reason why it failed is you had a mousetrap that was roughly a cent versus another mousetrap that was three cents. And I think this is in the '60s or so. The other mousetrap was reusable, so it executed a lot better, and everything else is more humane. But what they didn't understand is that it was wives most of the time that would have to actually handle this. And they didn't want the mouse alive, and they didn't want to reuse the trap. They wanted them to actually be disposed of right away. So, by not understanding the market, even though they built a better mousetrap, they'd missed the point. Like, the main problem to solve wasn't killing the mouse or having it be reusable. The main problem to solve was, like, getting rid of the mouse. So like, if you have a solution for getting rid of the mouse, the next thing is your execution for it. Like, does it hit the actual market, which is the fit aspect? Like, every product is a little bit different where you look at, like, how does this fit in? So, in this case, fit is very important for, like, disposing of the mouse, which is why you also have, like, you know, mouse poisons are popular, even though they're terrible because they die somewhere and, hopefully, you don't see them. And it's like sight unseen, right? Now, I'm glad, like, that's changing and stuff. But it's understanding even if you have a solution to something, you need to understand what your market wants out of your solution, and it's not going to be an abstract. It's going to be an emotional, like, execution-based process. So, you kind of have to go, all right, this is my market. This is kind of my fit. But the actual product I'm building is going to change to make sure it works all the way through with this. I was advising a startup many, many years ago, and they were building this CRM software on Android for South America. And I think they were building it for Android 6 or 7 at the time. But the market that they were targeting, they all ran Android 4.1. So, they spent a little over a million dollars building for the wrong version of Android that wouldn't even work on that version of the system. Like, it was one of those things where they were required to build it for that. But they didn't understand the actual market, and they didn't spend enough time researching it. So, it's like you get the Bay Area groupthink. If they had actually spent the time to analyze that market and go, "Oh, they run, you know, an inexpensive phone. It's 4.1. It's low RAM," now you can design a product. If you want it to be a CRM, you're going to, like, chunk up the system more. Like, you're going to change all that instead of just wasting a million dollars building something that now you basically have to start over again from scratch. VICTORIA: That seems like he got off cheap, too. People make way bigger mistakes that cost way more money [laughs] because they [inaudible 24:13] WENDELL: Well, that wasn't me. That was an investor that -- VICTORIA: Oh no. I mean, yeah, not just them. Yeah. WENDELL: He's like, "What would you do?" And I was like, "You should sell this company or sell your stake ASAP because that's a really bad sign." JOE: I have found that the answer nobody ever wants when you're doing product validation or testing product fit is, "You should not build this product." The idea that the software just shouldn't be written is universally unpopular. WENDELL: Yes [laughs]. That's, you know, that's part of the reason why it took me so long to do PrimeLab is because, like, it took a long enough for the software to actually need to be written, if that makes sense. Mid-Roll Ad: When starting a new project, we understand that you want to make the right choices in technology, features, and investment but that you don't have all year to do extended research. In just a few weeks, thoughtbot's Discovery Sprints deliver a user-centered product journey, a clickable prototype or Proof of Concept, and key market insights from focused user research. We'll help you to identify the primary user flow, decide which framework should be used to bring it to life, and set a firm estimate on future development efforts. Maximize impact and minimize risk with a validated roadmap for your new product. Get started at: tbot.io/sprint. VICTORIA: What does success look like now versus six months or even five years from now? WENDELL: I take a different approach to this because I have so many friends that have sold their businesses. They raise and everything else. I look at success as instead of an exit or another large thing, like, literally, we turned down a billion-dollar term sheet offer. I didn't like the terms. I didn't like what it would do from the control standpoint of the technology. What I care about is go-to-market and, like, adoption and actually getting the tech out there in a way that has market penetration but, like, that adds value to every person's life. VICTORIA: Yeah, maybe say more about that. Like how do you see AI and this technology you have with PrimeLab benefiting people and benefiting the industry that you're working within? WENDELL: So, the current AI models are kind of weird. They're basically just filter systems because they communicate in pixel space and then go down to functional space. It's the GPU. GPUs are actually terrible to use for AI. This is why you have dedicated AI chips getting built. Hopefully, the RISC-V chipset does actually do something because that's a chipset that I think it's an open-source chipset, but you can actually especially build models on it. So, I think that we're going to see a lot more in the RISC-V chipset where it's like, this is just for one particular image, or this is just for explosions, or this is just for touching up all these different points in the actual individual, like, microcontroller module data that ends up compiling to move forward with it. But the AI models now it's like you took the internet, and you're trying to ask it a probability question, what I was talking about before, where it's not an absolute. So, it's like, if I want to do an OCR system or anything, I take an image. It's got to say, "This is..." letters; it's going to recognize that. So, there's, like, multiple models and algorithms that need to run on that whole entire process. You even have artificial data, but all of that information is an approximation. It's not an absolute. If you want absolute, you can get a lot of absolute data from the actual hardware devices themselves. You know, take a Sony camera. You could see the lighting. You could see the raw information, everything else there. But because of how expensive it is, people compress it. Like, take YouTube where it's compressed, and now you're training off of it. You're trying to compress it more and then run an algorithm so that you don't have to actually process those large, raw files all the way through. That's just a bad infrastructure for compute. You're trying to reduce, but you're also trying to utilize what you own for rights, same thing, contextual, or anything else there. There's no value in a model. Once a model is out there, it's just weights moving it back and forth. The value is in the data and the applications. So, the actual data itself that's going in. So, if you have just lava scenes, like, having all that data for lava, and I want to put it in a background, now I can do that, but more importantly, it's not about just adding it into the background. The thing that is often missed is contextually the output. So, like, say I want to do a financial report. Rather than having the data of all financial reports out there, what I want as the input is my financial data. And what I want as, like, a fine-tuning output is an example of the reports that were generated. And I don't want those reports as the input to inform the output because that's where you get a hallucination. Maybe it starts grabbing financial data from someone else. And I also think we're in store for a lot more hacks because with not just poisoning data, which we do in the functional space, if someone tries to access it. But, I mean, literally, there's the story...I think the guy was in Hong Kong, where they faked his board all the way through with it. Because you have agents acting and executing on people's behalf, you're going to have systems where people go onto the hardware and start generating fake financial numbers. And now that's going to get reported. Or you pay an invoice that you weren't supposed to pay because someone manipulated your AI agent. And a lot of the stuff that we're seeing now from Microsoft and everything else that's not really where the models will go. It's great to do it, but it's kind of like we're in the dial-up stage of AI. Like [chuckles], dial-up has its use cases and stuff, but it's nowhere near what the tech will look like in the future, and it's nowhere near how it will function. And one of the big pushbacks that you see, like, from Google, from all these different places, like, they want your attention. But at the end of the day, Google's an ad company. Facebook's an ad company. It's not in their best interest to have hyper-localized data that you control for your models and likewise. They want it in the cloud. They want it used there, where they can control that data, and they can monetize and advertise for you. But at the same time, like AI models work the best, and AI applications work the best when the data set is limited, so it can't hallucinate, and when the outputs are actually controlled to what it should be from an informed standpoint. So, where we're at this is just in the beginning stages of stuff. VICTORIA: That's really interesting. Thank you so much for sharing. I think if you could go back in time when you first started PrimeLab and give yourself some advice, what would you say? WENDELL: You know, I lived through the Great Recession. The Great Recession informed me a lot more. The things that I didn't understand this time...like the Great Recession, was market contributors doing stuff that impacted everyone with their spend and their adoption, and how those things were. But the Fed raising interest rates, which is, you know, Silicon Valley Bank failed and stuff like that, that dynamic of those startups and, like, how much startups power everything, like, I would have advised myself to pay more attention to the Fed and those market dynamics going forward. Because what changed is it's not just the Silicon Valley Bank failed it, you know, Rippling went down, for instance, which would pay therapists in Florida and all kinds of stuff. Like, it broke so many different things. It caused bottlenecks in business that we're still going through. Like, everyone's like, "Oh, we're getting back to normal." Really not. It's still, like, delayed all the way through it. The AI aspect is really getting back to normal, where people are really pushing AI. But if you look at SaaS and other industries, it really, really slowed down. And the reason why that matters is, like, in my field, production and timelines matter. So, when you have that plus, you know, the entertainment strike and everything else, you have things where the actual production of things starts slowing down immensely. Whereas AI is one of the few things that you still have innovations because that never really slowed down, same thing with the models. But all the rest of the industries and stuff have really slowed down. And understanding what that means from an operational execution standpoint...it's a good thing I have my co-founder [inaudible 32:24]. It matters quite a bit because it means your team sizes have to change, how you handle certain clients has to change. Because once those companies start downsizing or laying off people for whatever reason like, that's going to change how you're working with them, and their requirements are going to change as well. VICTORIA: And what do you see on the horizon as a challenge or a big hurdle that you face as a company or as an industry? WENDELL: You know, the entertainment market's really interesting from all the different sign-offs. The challenge is more execution of timeline. So, like, if you're doing something with, like, Nvidia and the healthcare thing, it could take years. If you're doing something in, like, the IoT space, you know, also years. If you do something in the entertainment space, it could take weeks to months, except the large studios. The larger studios, it could take a couple of years as well. But going to market, I think, is a very big challenge, not just for us but the whole entire industry. I mean, there's a reason why Sam Altman came down to LA to meet with studios, to try and get stuff moving forward. And I think one of the things that he's forgetting is like, you think of Netflix. Netflix is streaming. In order for that to work, they needed Roku, and they needed Kevin Spacey because [chuckles]...it's crazy to say that, but House of Cards is kind of what made it, right? And Hollywood was mostly boxing them out quite a bit. Same thing with Blockbuster otherwise. They had to drop a hundred million dollars, a large enough bankable star at the time that would really push something forward. And they had to basically really push Roku out there so that they had PMF across the board. What that means, though, is, like, Netflix is paying for content like crazy, right? So, this is kind of enshittification in a process. So, they're paying for content like crazy. So, now Hollywood's making money. They like it. At the studios, they don't love it when their stuff's going there because maybe it's less money, but now they start cutting the seasons short. They start cutting...it's a lot more algorithmic-driven. You have the ad systems that sort of come out. So, now, like, Netflix is not just doing ads where the customer experience is getting worse, but now, also, the business experience for those partners selling stuff is also getting worse, and all that value is getting driven to Netflix. Like, that's the tech system and Hollywood's learned that. But, like, when you're looking at the next adoption, like, they're hesitant for that. Just like a lot of stuff with AI, they're hesitant because they're thinking about all the power and control that they gave up. But you have to show how they're going to make money. You can't just cut costs, right? If you can't show how they're going to make money, you're not going to get adopted. That's kind of what I like there because so much of tech is about saving costs and being more efficient. In the entertainment industry, it's not just those two things. It's how can I make more money? And it's going to, like, ooh, you can monetize your content through training samples and stuff like that. So, our model goes exactly against what the large tech companies have where they want to take content, train on it, like the search engine does, suck the value off Sam Altman's Sora. Ours goes, all right, this is your content. Only you own this. You can take your own content, train it, and then perform this operation on it that is more efficient likewise. And if you choose to monetize it in any way, shape, or form, we can just take the functional space, not all the images and no one will ever see it, and take that functional space for training so that you can actually monetize from that as well. VICTORIA: I love that. Super interesting. Thank you so much for sharing. And do you have any questions for me or for Joe? WENDELL: I've noticed a lot of differences on, like, applications and how systems are built. So, I'm kind of curious about you guys' standpoint about applications, you know, the Apple Vision Pro. Facebook just said they'd start licensing out their AI system, or Meta, whatever. So, you have the comparisons to Android versus iOS that's happening, stuff like that. So, I'm really curious about, like, you guys' thoughts on the Vision Pro and that ecosystem. JOE: Well, I can't speak for all of thoughtbot, but I can say that, to me, it was interesting to see that get released. And it's been interesting to see how aggressively Meta and Apple have been pursuing the various VR markets. Like it reminds me of when television companies and studios worked really hard to get 3D movies to be a thing. WENDELL: [laughs]. JOE: Because I think they just ran out of things that people are asking for. Like, people were interested in getting better resolutions up to a point. Like, they wanted better packaging. But it got to a point where it was like, they didn't want to give anybody anything they were asking for. So, they were like, what if it's in 3D? And, like, for years, it seemed like Apple was really on top of seeing what people really wanted, and being able to present a very well-prepared version of that product before other companies were able to. And, personally, it's not what I saw with the Apple Vision Pro. Like, it wasn't the obvious missing space that was there when the iPhone or the iPad showed up. WENDELL: Yeah, I always go back to, like, the "Why?" question. You know, previously when...even just before we had talked, I was talking about comparative religions, and why that's so valuable is because it really teaches you...again, I've had this conversation before, but the comparative religions, if you think about religion as a tech company, they're always trying to solve why. Like, why did the sun come up? Why did this happen, right? And you always have to do that. So, apply that to technology, Google or Apple, why does this product exist? And when you get to, like, it just existed to make money, I think that's really the 3D thing. Whereas, like, why did the iPhone exist? It existed to solve this problem of being portable on the go and getting information in the way that we communicated, too. VICTORIA: Yeah. I think the Apple Vision Pro appeals to a very specific market segment and that that segment is not me [laughter]. I, actually, during COVID...after...it was, like...yeah, we're still in COVID. But during the pandemic, I moved from DC to California. And to connect with some old friends, I bought a VR headset and decided to go to virtual coffee with them. And it just makes me nauseous. And it actually affects...quite a lot of women get nauseous in VR. For some people, the look—the capability is really exciting. They have the extra money to spend on gadgets, and that's what they like. And it's very appealing, and the, like potential, is really interesting. I just find it for myself. Personally, I'm more drawn to tech that's not maybe cutting edge but solves problems for actual people. And kind of why I'm interested in PrimeLab, what you were mentioning is just how artists can use this technology to protect their creative work. To give that power back to people and that control over their content, I think, is really interesting rather than...I'm not really sure what I would do with the Apple Vision Pro [laughs]. Like, the early ones, I mean, it's cool. It's fun. I definitely enjoy it. Like, I sometimes like to learn about it, but it's not my passionate genre of tech that I normally go for. WENDELL: Going back to what you just said about, like, control, like, part of the thing is because of the hash IDs that we put into place, like, you don't need analytics. You don't need cookies or anything else, like the content holder. Basically, like, if you have a TV set or something and you want to stream content to it, you can actually see that information directly yourself. So, it takes the person generating it and the person viewing it. It forms...we call them function access keys. It forms a one-to-one relationship, basically, where you guys know if you want to know what you want to know, but then you choose to give access to the platform if you want to, which changes the dynamic of control quite a bit. And it's interesting because when you look at platforms like the Apple Vision Pro, and you look at Apple's whole entire system as a whole, just trying to lock in people, I think it's interesting because something like what I just described, Apple can't really stop. It's how compute works. So, if people want to use it, there's nothing they could do to stop it from being used. So, I'm really interested in the product stuff and just more about, like, how...and I'm curious what you guys think on this, too. Especially as you see phones and processors and everything else, I'm really interested in, like, how these things come about, like, how things are actually built and developed and the why for that, like, in the everyday use. So, like, the Apple Watch it started off as a fashion thing, which looked like a money grab, and then the why was, oh yeah, fitness. So, just curious if you guys have seen any other products out there that you're like, oh, this really resonates with me and the why. JOE: Yeah, I'm not really a gadget person, but I think the idea of taking some of the capabilities that we've gotten with the internet and with phones and making them hands-free was interesting. And that, to me, was what I think started pushing the development of products like the Apple Watch or Google Glass. Like, I think that hands-free capability, the trade-off became rewarding in the fitness field, but I think it's more generically applicable. I think that technology it's too obtrusive in other scenarios and too bad at its job to do some of the things it could do. And people got creeped out by Google Glass. But it doesn't really seem like the Vision Pro fits in there. Something being successful hands-free means it becomes less obtrusive, whereas the Vision Pro is like you become a cyborg. VICTORIA: Do you have anything else you would like to promote? WENDELL: I wouldn't say necessarily promote as much as like people with ideas or aspirations, like, I think it's important that you think counter to what everyone else is doing. There's that line of, like, when everyone else is running in one direction, run the other. And it's like, if you have a business or startup idea, really think about your market. Like, think about why you're doing what you're doing, and don't be afraid to just go out there and talk to people. You will get value no matter who you talk to. So, like, I'm a hugely tech-based person. My wife is a therapist, and I learn from her everyday things about emotional intelligence and all kinds of things that I would be an idiot otherwise. But also, learn, like, you can always learn something from someone. Like, take the time to listen to them. Take the time to actually, like, try and figure out what's one thing I can learn from someone, even if, you know, I learn stuff from my daughters even. Like, don't put things in boxes. Like, try to think outside of like, how can I ask a question to learn? VICTORIA: I love that advice. That's great. WENDELL: Have you guys used Suno before? VICTORIA: That's music, right? Music AI. WENDELL: All right, I got to show you guys this. We're going to create you a quick theme song. Like, this is what I mean by, like, it's an interesting solution for why. VICTORIA: That does sound fun. I like the ones...like my friend's a doctor, and she uses AI to take her conversation she's having with patients and automatically fill out her notes. And it saves her, like, 20 hours of documentation every week. Like, I like that kind of app. I'm like, oh, that makes a lot of sense. WENDELL: What's a style of music that you guys really like? JOE: Swedish pop VICTORIA: Like ABBA [laughs]? I'm down for an ABBA Giant Robots theme song. Sounds great. WENDELL: I think you're going to like this. [Music Playing] VICTORIA: These are awesome. They're super fun. Thank you so much. You can subscribe to the show and find notes along with a complete transcript for this episode at giantrobots.fm. If you have questions or comments, you can email us at hosts@giantrobots.fm. And you can find me on X @victori_ousg. This podcast is brought to you by thoughtbot and produced and edited by Mandy Moore. Thanks for listening. See you next time.  AD: Did you know thoughtbot has a referral program? If you introduce us to someone looking for a design or development partner, we will compensate you if they decide to work with us. More info on our website at: tbot.io/referral. Or you can email us at: referrals@thoughtbot.com with any questions. Special Guest: Joe Ferris.

Welcome to another episode of our Learning from Financial Fraud Series. In this eleventh episode, we'll look at what can be learned from a recent scam involving an unauthorized debit. Craig Jeffery provides his insights on the situation, the attack method, the loss, and the key takeaways.  More from this series:   Learning from Financial Fraud Series Episode 10: Learning from Deepfake Scams  Learning from Financial Fraud Series Episode 9: Payment Server and Network Compromise   Learning from Financial Fraud Series Episode 8: Payment Server Breach   Learning from Financial Fraud Series Episode 7: Understanding “Pig Butchering”   Learning from Financial Fraud Series Episode 6: Unpacking the Bernie Madoff Ponzi Scheme   Learning from Financial Fraud Series Episode 5: Uncovering the Enron Accounting Scandal   Learning from Financial Fraud Series Episode 4: Unmasking the FTX Fraud & Safeguarding Your Assets   Learning from Financial Fraud Series Episode 3: Unraveling the Wirecard Fraud – Safeguarding Your Business   Learning from Financial Fraud Series Episode 2: Understanding the Satyam Scandal and Its Consequences   Learning from Financial Fraud Series Episode 1: Unveiling the Parmalat Fraud Scandal and Bankruptcy    

Some say Microsoft's Recall should be. A breach of a Texas healthcare provided affects over four hundred thousand. Police in the Philippines shut down services following a breach. Ivanti patches multiple products. GitHub fixes a critical authentication bypass vulnerability. Researchers discover critical vulnerabilities in Honeywell's ControlEdge Unit Operations Controller. The DoD releases their Cybersecurity Reciprocity Playbook. Hackers leak a database with millions of Americans' criminal records. Mastercard speeds fraud detection with AI. On our Learning Layer segment, host Sam Meisenberg and Joe Carrigan continue their discussion of Joe's ISC2 CISSP certification journey, diving into Domain 5: Identity and Access Management. Remembering a computing visionary.  Our 2024 N2K CyberWire Audience Survey is underway, make your voice heard and get in the running for a $100 Amazon gift card. Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. Learning Layer On our Learning Layer segment, host Sam Meisenberg and Joe Carrigan continue their discussion of Joe's ISC2 CISSP certification journey using N2K's comprehensive CISSP training course, CISSP practice test, and CISSP practice labs. Joe and Sam dive into Domain 5: Identity and Access Management (IAM) and tackle a question together about biometric configuration. Try the question yourself before listening to the discussion! You are configuring a biometric hand scanner to secure your data center. Which of the following practices is BEST to follow? Decrease the reader sensitivity Increase the FAR Decrease the FRR Increase the reader sensitivity Selected Reading UK watchdog looking into Microsoft AI taking screenshots (BBC) How the new Microsoft Recall feature fundamentally undermines Windows security (DoublePulsar) CentroMed Confirms Data Breach Affecting an Estimated 400k | Console and Associates, P.C. (JDSupra) PNP suspends online services amid data breach probe (Philippine News Agency) Ivanti Patches Critical Code Execution Vulnerabilities in Endpoint Manager (SecurityWeek) Critical SAML Auth Bypass Vulnerability Found in GitHub Enterprise Server (Heimdal Security) Critical Vulnerability in Honeywell Virtual Controller Allows Remote Code Execution (SecurityWeek) DoD CIO debuts cybersecurity reciprocity playbook to streamline system authorizations, boost cybersecurity efficiency (Industrial Cyber) Criminal record database of millions of Americans dumped online (Malwarebytes) Mastercard Doubles Speed of Fraud Detection with Generative AI (Infosecurity Magazine) Gordon Bell, Legendary Designer of Computers, Dies at 89 (Gizmodo)  Share your feedback. We want to ensure that you are getting the most out of the podcast. Please take a few minutes to share your thoughts with us by completing our brief listener survey as we continually work to improve the show.  Want to hear your company in the show? You too can reach the most influential leaders and operators in the industry. Here's our media kit. Contact us at cyberwire@n2k.com to request more info. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc.

Welcome to another episode of our Learning from Financial Fraud Series. In this episode, we'll look at a case of payment server and network compromise. Craig Jeffery provides his insights on the situation, the attack method, the loss, and the key takeaways.  More from this series:  Payment Server Breach  Understanding “Pig Butchering”  Unpacking the Bernie Madoff Ponzi Scheme  Uncovering the Enron Accounting Scandal  Unmasking the FTX Fraud & Safeguarding Your Assets  Unraveling the Wirecard Fraud – Safeguarding Your Business  Understanding the Satyam Scandal and Its Consequences  Unveiling the Parmalat Fraud Scandal and Bankruptcy