Compiler

Red Hat
  • 4,7 (58)
  • TECNOLOGIA

Compiler gives you perspectives and insights from the tech industry—free from jargon and judgment. We’re here to help tech newbies understand what’s going on. Learn more about our show at redhat.com/en/compiler-podcast

  1. What Is Product Security?

    25 DE SET.

    What Is Product Security?

    Our trust in the internet is the lowest it’s ever been. In spite of our vigilance, we face more threats than ever before. Product security is a vital element in the defense against malicious incursions. This season of Compiler covers the particulars of product security.  With some help from Emily Fox, Portfolio Security Architect at Red Hat, our hosts kick off the season with a simple question: What is product security?

    40min
  2. The New Security Landscape

    TRAILER DA TEMPORADA 3

    The New Security Landscape

    Phishing. DDoS attacks. Social engineering. These are not new terms if you know anything about cybersecurity. But emerging technologies are making these well-known methods of attack easier than ever.   Bad actors are paying attention—and they are leveling up their skills accordingly.   It isn’t just cybersecurity professionals who have to be aware and responsive– people working in product security are a part of the effort, too. What do they need to know to respond to these newer attacks?   This season, hosts Emily Bock and Vincent Danen will dig into how the security landscape has changed, and how IT professionals can work together to prevent and prepare for whenever, wherever, and however threats emerge.

    1min
  3. Context And The True "Cost" Of AI

    5 DE JUN.

    Context And The True "Cost" Of AI

    Sure, AI has made a splash. And it's on us to level up, learn the ropes, and roll with it. But how do we even do that? And what cool human stuff might we accidentally ditch along the way? The Compiler team ends the season discussing the importance of context, creativity, and applied knowledge.

    41min
  4. Agentic AI: Working As Instructed

    22 DE MAI.

    Agentic AI: Working As Instructed

    Agentic AIs are showing promise for tedious work. But it’s hard to explain exactly how you want it done—and getting it wrong could create big problems.  This episode of Compiler investigates how Agentic AIs could carry out their tasks and how some agents are taking their baby steps in the wide world. The team also considers the difficulties humans have expressing what we want computers to do for us, and how that could create unintended consequences.

    38min
  5. Breaking Down AI Biases

    8 DE MAI.

    Breaking Down AI Biases

    Does your health insurance chatbot need to tell jokes? No. Does it need to be accurate? Absolutely. That's hard when biases get in the way. The introduction of bias into a model can be unintentional, but it can have significant consequences for those relying on its guidance. The Compiler team examines the ways bias can creep in, and what steps can be taken to address it.

    34min
  6. Diagnosing and Dispelling AI Hallucinations

    24 DE ABR.

    Diagnosing and Dispelling AI Hallucinations

    AI is notorious for making stuff up. But it doesn’t always tell you when it does. That’s a problem for users who may not realize hallucinations are possible. This episode of Compiler investigates the persistent problem of AI Hallucination. Why does AI lie? Do these AI models know they’re hallucinating? What can we do to minimize hallucinations—or at least get better at seeing them?

    34min
  7. Chasing Its Own Tail

    10 DE ABR.

    Chasing Its Own Tail

    With the massive flow of AI-generated content onto the internet, it was only a matter of time until all of those bits of data found their way back into AI models. But what do you get when generative AI models start getting their answers from that content? The Compiler team digs into AI feedback loops, and the unique challenges they present for technologists...and everyone else.

    37min
  8. Navigating Data Rights In AI

    27 DE MAR.

    Navigating Data Rights In AI

    Copyright infringement is a huge issue for AI training and use. Can LLMs give you copyrighted content? What data can you use to train and tune your own model? In this episode of Compiler, we explore who owns what when AI models learn from protected content—and why it matters.

    39min
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Compiler gives you perspectives and insights from the tech industry—free from jargon and judgment. We’re here to help tech newbies understand what’s going on. Learn more about our show at redhat.com/en/compiler-podcast

Informações

  • Criado por
    Red Hat
  • Anos de atividade
    2021 - 2025
  • Episódios
    79
  • Classificação
    Livre
  • Site do podcast
    Compiler

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