Unsupervised Learning

Daniel Miessler

<p><strong>Unsupervised Learning is a Security, AI, and Meaning-focused podcast that looks at how best to thrive as humans in a post-AI world. </strong>It combines original ideas, analysis, and mental models to bring not just the news, but why it matters and how to respond.</p>

  • 1 hour 16 minutes
    Why AI Will Replace Knowledge Workers

    A longer form discussion on exactly how and why AI will replace knowledge workers.

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    21 March 2026, 6:23 pm
  • 1 minute 48 seconds
    Why I Believe in SOTA Models Over Custom Ones

    I think the future is cheaper and Open Source SOTA models combined with context, not custom, narrow models.

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    11 March 2026, 8:50 pm
  • 1 minute 2 seconds
    AI Quality Inversion

    A troubling thought about what we will think about high-quality content in the future. 

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    6 March 2026, 4:08 pm
  • 1 hour 24 minutes
    The Great Transition

    There are a bunch of different transitions happening right now—all at the same time, all (I think) heading in the same direction. Here is a long-form exploration of the various pieces.

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    28 February 2026, 12:43 am
  • 25 minutes 9 seconds
    Starting 2026

    A welcome back and early entry into 2026. 

    Sponsored by: Knocknoc!

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    30 January 2026, 10:29 pm
  • 6 minutes 58 seconds
    Judge AI based on Output, Not Mechanism

    How we can use an output-based system to judge whether or not different kinds of technology achieve understanding or intelligence. 

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    22 November 2025, 9:45 pm
  • 4 minutes 20 seconds
    Humans Need Entropy

    How humans and AI models both share the weakness of deterioration without novel inputs. 

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    16 November 2025, 4:15 pm
  • 9 minutes 54 seconds
    Why I Think Karpathy is Wrong on the AGI Timeline

    Karpathy is confusing LLM limitations with AI system limitations, and that makes all the difference. 

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    20 October 2025, 2:29 pm
  • 3 minutes 44 seconds
    Novelty Exploration vs. Pattern Exploitation

    How going from exploration to exploitation can help you as both a consumer and creator of everything.

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    15 October 2025, 9:37 pm
  • 6 minutes 30 seconds
    Magnifying Time

    Some thoughts on how novelty and attention magnify the time that we have. 

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    14 October 2025, 8:39 pm
  • 35 minutes 3 seconds
    A Conversation With Harry Wetherald CO-Founder &amp; CEO At Maze

    ➡ Stay Ahead of Cyber Threats with AI-Driven Vulnerability Management with Maze:
    https://mazehq.com/

    In this conversation, I speak with Harry about how AI is transforming vulnerability management and application security. We explore how modern approaches can move beyond endless reports and generic fixes, toward real context-aware workflows that actually empower developers and security teams.

    We talk about:

    The Real Problem in Vulnerability Management
    Why remediation—not just prioritization—remains the toughest challenge, and how AI can help bridge the gap between vulnerabilities and the developers who need to fix them.

    Context, Ownership, and Velocity
    How linking vulnerabilities to the right applications and teams inside their daily tools (like GitHub) reduces friction, speeds up patching, and improves security without slowing developers down.

    AI Agents and the Future of Security
    Why we should think of AI agents as “extra eyes and hands,” and how they’re reshaping everything from threat detection to system design, phishing campaigns, and organizational defense models.

    Attackers Move First
    How attackers are already building unified world models of their targets using AI, and why defenders need to match (or exceed) this intelligence to stay ahead.

    From Days to Minutes
    Why the tolerance for vulnerability windows is shrinking fast, and how automation and AI are pushing us toward a future where hours—or even minutes—make the difference.

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    Chapters:

    00:00 – Welcome and Harry’s Background
    01:07 – The Real Problem: Remediation vs. Prioritization
    04:31 – Breaking Down Vulnerability Context and Threat Intel
    05:46 – Connecting Vulnerabilities to Developers and Workflows
    08:01 – Why Traditional Vulnerability Management Fails
    10:29 – Startup Lessons and The State of AI Agents
    13:26 – DARPA’s AI Cybersecurity Competition
    14:29 – System Design: Deterministic Code vs. AI
    16:05 – How the Product Works and Data Sources
    18:01 – AI as “Extra Eyes and Hands” in Security
    20:20 – Breaking Barriers: Rethinking Scale with AI
    23:22 – Building World Models for Defense (and Attack)
    25:22 – Attackers Move Faster: Why Context Matters
    27:04 – Phishing at Scale with AI Agents
    31:24 – Shrinking Windows of Vulnerability: From Days to Minutes
    32:47 – What’s Next for Harry’s Work
    34:13 – Closing Thoughts

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    22 September 2025, 6:56 pm
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