Data Driven

Data Driven

Data Driven: the podcast where we explore the emerging field of Data Science. We bring the best minds in Data, Software Engineering, Machine Learning, and Artificial Intelligence right to you every Tuesday. The field of data science mashes up the worlds of statistics, database architecture and software engineering. Data Scientist has been labelled by the Harvard Business Review, as "the sexiest job of the 21st century." A quick search of job search sites reveal that this field is in high demand. In a world where Data is the new Oil, Data Science the new Refineries, consider this Car Talk for the Data Age. Every week we bring the best minds in this emerging field straight to you. Our goal is to educate and inspire our listeners so that they can be prepared to thrive in a Data Driven world.

  1. hace 2 días

    Building Trust in AI – Lawrence Snap on Hallucination Detection and the Future of TrustScale

    In this episode, hosts Frank La Vigne and Andy Leonard sit down with Lawrence Snapp, CEO and board member of TrustScale, an innovative AI trust and verification platform. Together, they explore the crucial topic of trust in artificial intelligence—how hallucinations from AI models can spiral out of control and why it’s essential to catch them early. Lawrence Snapp pulls back the curtain on TrustScale’s journey from early AI and translation work in the 1980s and call center solutions, to its modern-day mission: empowering humans to verify and trust AI outputs with products like Argus. You’ll hear about real-world impacts in fields like healthcare, legal, and research, learn how TrustScale’s deterministic engine outpaces humans in hallucination detection, and dive into debates around truth, trustworthiness, and the future of configuring AI values. Whether you’re an industry veteran or just curious about how we build trustworthy AI, this episode is packed with insights on technology, responsibility, and the power of rigorous engineering. LinksWatch on YouTube -https://www.youtube.com/watch?v=RjM7lxn3Qk8Lawrence on LinkedIn -https://www.linkedin.com/in/lawrence-snapp-408339/ Time Stamps00:00 Funny AI-generated story 03:37 Company's Evolution from Translation to AI 07:32 Developing the TrustScale engine 11:35 Using AI for collaboration 13:39 Building a trust scoring system 18:12 Working at BASF and AI testing 19:32 New developments in voice assistants 23:41 Trust scale and company confidence 26:13 AI mishap in medical drama 32:48 Overcoming AI recency and cost challenges 36:54 AI's impact on career growth 38:50 Interviewing and developing talent 43:31 Starting with Polaroids and AI goals 46:54 Discussing TrustScale and AI interactions 50:42 Empowering AI customization for users 51:45 AI ethics discussion in Los Altos

    Building Trust in AI – Lawrence Snap on Hallucination Detection and the Future of TrustScale

  2. 18 ago

    Numeracy, Probability, and Business – Embracing Randomness for Better Decisions

    In this episode, host Andy Leonard sits down with Ilan Man, founder and CEO of Paradox Machines, a full-stack data and AI company based in Brooklyn. Ilan shares his fascinating journey from an actuarial career to the dynamic field of data science, exploring the rise of big data, the art of translating complex mathematics into code, and the importance of numeracy in society. Together, they discuss the paradoxes at the heart of data and AI, the challenges of decision-making under uncertainty, and why intuition, risk management, and storytelling remain critical in a world driven by data. Whether you're a data enthusiast, decision-maker, or just curious about how numbers shape our lives, this conversation delivers valuable insights and a healthy dose of skepticism about the limits, and possibilities, of analytics. Linkshttps://www.linkedin.com/in/ilanman/ Time Stamps00:00 Starting a career in data science 03:34 Discovering a career in actuarial science 08:17 Learning coding and joining Squarespace 11:40 Understanding Probability in Code 15:36 Questioning Confidence in Decision-Making 20:06 Discussing COVID vaccine effectiveness 21:09 Understanding vaccine effectiveness 24:41 Consumers interacting with unpredictable AI 29:35 Discussing disease perception and interpretation 33:01 Casino audiobook and extra details 35:41 Balancing data-driven decisions 40:07 Career journey to founding Paradox 40:49 Building a data platform with AI 46:41 Data's Role in Decision Making 47:30 Value and limits of data-driven decisions

    Numeracy, Probability, and Business – Embracing Randomness for Better Decisions

  3. 28 jul

    Tackling Data Engineering Challenges with Autonomous AI Agents

    In this episode, Frank La Vigne sits down with Pradnesh Patil, co-founder and CEO of Altima AI, to explore how AI is revolutionizing the world of data engineering. Together, they dive into the challenges of modern data stacks, the explosion of tools and technologies, and how AI-powered agents are transforming the way data teams build and maintain complex systems. From automating data pipeline management to optimizing infrastructure and safeguarding governance, Pradnesh Patil shares insights on the next wave of data engineering and what the future holds for professionals in the field. Whether you’re a veteran data engineer or a student curious about the evolving landscape, this episode offers practical advice, industry trends, and an optimistic look at how embracing AI can supercharge your career and your organization’s capabilities. LinksPradnesh's LinkedIn - https://www.linkedin.com/in/pradneshpatil/Watch on YouTube -https://youtu.be/vxQrjE-U3gw Time Stamps00:00 Evolution of data technology tools 04:11 Managing tool stack complexity 09:09 Discussion on AI guardrails and future 10:55 Managing MCB server outputs 14:32 Streamlining Data Pipeline Efficiency 18:48 Managing and Deleting Memories 21:12 AI security and virtual employees 27:16 AI transforming jobs and automation 30:43 Impact of AI on IT Industry 32:32 Upgrading legacy systems with AI 37:10 Importance of Data Engineering 39:10 Changing role of data managers 42:45 Home lab challenges and data management

    Tackling Data Engineering Challenges with Autonomous AI Agents

  4. 20 jul

    Unlocking Enterprise Knowledge – AI, Document Comprehension, and the Future of RAG

    In this episode, hosts Candace Gillhoolley and Frank La Vigne are joined by Neil Katz, Chief Product Officer at Valantor AI—a four-time Emmy winner whose unconventional journey spans from technology startups to award-winning journalism, and now to the forefront of enterprise AI innovation. Neil shares his unique perspective on the evolution of AI, from the early days of digital design and machine learning, to building large-scale AI and document intelligence platforms for major organizations. The conversation explores the critical challenges of knowledge extraction, document comprehension, and securing sensitive data in today's era of sovereign AI. Together, they uncover the hidden complexities behind Retrieval-Augmented Generation (RAG), discuss the importance of hybrid search strategies, and reflect on where the field is heading as enterprise needs push the boundaries of what AI can do. Whether you're a data professional, an AI enthusiast, or just curious about how language models are transforming how we understand information, you won’t want to miss this candid and thought-provoking deep dive into the future of AI and data integrity. LinksNeil on LinkedIn -https://www.linkedin.com/in/neilkatz/Watch on YouTube -https://www.youtube.com/watch?v=qf8qifz_RL8 Time Stamps00:00 Early career in tech and journalism 04:01 Early consumer AI experiences 06:49 Early AI and machine learning developments 11:43 Anthropic's new findings on AI models 16:15 Data sovereignty in AI systems 19:27 Implementing open source AI models 22:49 Breaking down documents for models 25:45 Understanding the RAG system process 28:47 Challenges in AI data processing 31:22 Challenges in RAG with Insurance Data 36:35 Understanding and managing data security 39:35 Early days with OpenAI GPT 40:48 Explaining vector and similarity search 46:57 The evolution of computing models 47:29 Computing evolution to cloud and edge

    Unlocking Enterprise Knowledge – AI, Document Comprehension, and the Future of RAG

  5. 13 jul

    Demystifying State in AI: Smarter Reasoning and Real-World Legal Applications

    In this episode, Frank sits down with Devansh Devansh, founder and head of AI at Iris, whose journey spans from building a thriving tech community of over 10,000 on Substack to developing advanced legal AI tools that revolutionize how lawyers work through complex reasoning. The conversation explores Devansh Devanche's unconventional path into AI, his experiences navigating the evolving landscape of machine learning, and the unique challenges of creating transparent, trustworthy agentic systems in legal tech. Along the way, we uncover the story behind his distinctive "chocolate milk cult leader" branding, his philosophy on startup building, and why he believes that innovation in AI is more accessible than it may seem. Whether you’re a technologist, a lawyer, or just curious about the future of AI, this is an episode packed with insight, optimism, and actionable advice. LinksDevansh on LinkedIn -https://www.linkedin.com/in/devansh-devansh-516004168/Devansh on SubStack -https://substack.com/@chocolatemilkcultleader Time Stamps00:00 Transitioning to Substack and AI Journey 05:32 Starting to publish research insights 07:37 Connecting with Senior Leaders 13:27 Issues with Legal AI Systems 16:55 Challenges with current AI systems 19:49 Demand for AI in legal and non-legal sectors 23:29 Challenges with AI system state management 24:51 Compounding AI returns over time 30:50 Meeting the CEO of Iris 34:20 Tailoring Startup Strategy to Strengths 36:26 Insights on Cluli's Market Presence 40:27 Opportunities in AI Innovation 42:57 Reflecting on market evolutions

    Demystifying State in AI: Smarter Reasoning and Real-World Legal Applications

  6. 30 jun

    How Data and AI Are Revolutionizing Philanthropy for Nonprofits and Donors

    In this episode, the conversation focused on the intersection of data intelligence, artificial intelligence, and philanthropy. A key theme that emerged was the growing importance of data-driven decision making in the nonprofit sector, which, despite representing 5% of the GDP and employing 10% of the American workforce, has lagged behind other industries in the adoption of technology and data practices. The discussion explored how organizations like Impala are aiming to transform the philanthropic landscape by providing robust data platforms and AI-driven tools to empower both large foundations and small nonprofits. Several points were raised, including the unique challenges philanthropy faces in measuring impact versus the traditional business focus on ROI, the rise of a new generation of data-savvy philanthropists, and how collaborative giving and customized data solutions are shaping a more transparent, effective, and innovative sector. Tune in as we examine how technology is not just changing the way give, but also who gives, why, and with what outcome—pushing philanthropy into a new age powered by actionable insights and human connection. LinksImpala -https://impala.digital/ Time Stamps00:00 Importance of Data and Relationships 03:59 Joining Impala through philanthropy 09:00 Measuring organizational impact 12:15 Engaging younger donors with data 14:38 Impala's role in education analysis 20:24 Empowering small nonprofits with AI 22:50 Impala's AI platform strategy 25:07 Improving investment decisions with AI 28:25 Integrating AI with Data Platforms 32:01 Using AI in philanthropic decisions 34:58 Discussing collaborative giving trends 39:28 Supporting small businesses with tech 42:35 Appreciation and social impact goals

    How Data and AI Are Revolutionizing Philanthropy for Nonprofits and Donors

  7. 23 jun

    Why ‘Data-Driven Decisions’ Are a Myth

    This week, we dive deep into the world of data, decision-making, and uncertainty with Dale Nesbitt, a lecturer at Stanford and principal at Arrowhead Economics. Drawing on his unique upbringing in a mining town, Dale Nesbitt shares how witnessing raw data collection firsthand shaped his perspective on what it really takes to make informed decisions—hint: it's not just about having more data. Together, we explore the pitfalls of relying solely on data for critical choices, the importance of understanding probability and risk, and why data-gathering itself is often a noisy and imperfect process. From commodity pricing and speculation in oil markets to the real-world impact of data-driven decisions in healthcare, Dale Nesbitt reveals why true analytic power comes from combining rigorous analysis, sound judgment, and the right kind of data—not just more of it. Join us as we challenge myths around "data-driven" decisions, unpack lessons from COVID-era data science, and discover why wisdom of the crowd, probability, and a healthy respect for uncertainty are key to navigating our data-rich world. Links Dale's LinkedIn profile -https://www.linkedin.com/in/dale-nesbitt-b574a83a/Watch on YouTube -https://www.youtube.com/watch?v=USOKgv1avHo Time Stamps 00:00 Growing up in a mining town 05:44 Data as the New Crude Oil 07:31 Estimating and Understanding Stochastic Processes 12:49 Impact of Strait of Hormuz Closure 14:19 Challenges of AI in Economics 17:05 Betting on events and elections 21:43 Bayesian analysis and hydroxychloroquine data 23:28 Understanding data and judgment 26:38 Analyzing data for better decisions

    Why ‘Data-Driven Decisions’ Are a Myth

  8. 15 jun

    Bulletproof KDE and Why Linux is Winning Over Developers

    On this episode of Data Driven, hosts Frank La Vigne and Candace Gillhoolley are joined by hardware and open source expert Michael Makowski to discuss the shifting landscape of developer workstations and AI hardware. As Windows usage declines among developers and AI engineers, Linux is experiencing a surge in desktop adoption. Michael takes us inside the latest efforts to make Linux not just accessible, but enterprise-grade—sharing how his team is driving advancements in stability, reliability, and user experience for validated Linux hardware. We talk about the dramatic improvements in Linux desktop support, the importance of privacy and avoiding surveillance-driven proprietary systems, and the game-changing features coming to market—like automated system rollback and curated app installs. Plus, we explore the current state of gaming on Linux, the technical edge unified memory brings to AI development, and why companies are increasingly opting for supported, Linux-based workstations. Whether you’re Linux-curious, rethinking your hardware choices, or just passionate about the future of developer tools and data engineering, this conversation will equip you for what’s next. LinksMike's Company Website -https://kfocus.org/Mike's LinkedIn Profile -https://www.linkedin.com/in/michael-mikowski-7601393/Watch this show on YouTube -https://youtu.be/E03EObEa2lQ Time Stamps00:00 Website security concerns and solutions 05:03 Supporting KDE for long-term stability 09:45 Desktop environment compatibility issues 10:46 Conflicts in desktop environments 15:07 AMD vs Intel & Nvidia Performance 18:58 Showing the production site 23:49 Steam's Linux runtime environment 25:43 Running Windows games on Linux 29:47 Concerns about software privacy issues 33:31 Migrating from Windows challenges 37:48 Setting up machine learning hardware 41:31 Resolving system issues efficiently 42:59 Setting up a VPN correctly 47:40 Running VMs on alternative OS 52:49 Upcoming OS Upgrade Details 56:19 Rigorous testing and development process 57:25 Tuning BTRFS for performance

    Bulletproof KDE and Why Linux is Winning Over Developers
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Data Driven: the podcast where we explore the emerging field of Data Science. We bring the best minds in Data, Software Engineering, Machine Learning, and Artificial Intelligence right to you every Tuesday. The field of data science mashes up the worlds of statistics, database architecture and software engineering. Data Scientist has been labelled by the Harvard Business Review, as "the sexiest job of the 21st century." A quick search of job search sites reveal that this field is in high demand. In a world where Data is the new Oil, Data Science the new Refineries, consider this Car Talk for the Data Age. Every week we bring the best minds in this emerging field straight to you. Our goal is to educate and inspire our listeners so that they can be prepared to thrive in a Data Driven world.

Información

  • Creador
    Data Driven
  • Años de actividad
    2017 - 2026
  • Episodios
    300
  • Clasificación
    Apto
  • Copyright
    © Copyright 2026 Data Driven
  • Mostrar sitio web
    Data Driven

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