80% Chinese Cranes, Drones vs. Abrahams, a RAG kickstart, a Canary-based Security Maturity Model, and more...

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80% Chinese Cranes, Drones vs. Abrahams, a RAG kickstart, a Canary-based Security Maturity Model, and more...
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Unsupervised Learning is a Security, AI, and Meaning-focused podcast that looks at how best to thrive as humans in a post-AI world. It combines original ideas, analysis, and mental models to bring not just the news, but why it matters and how to respond.

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

Exploring the fascinating intersection of security, technology, and humans.

Unsupervised Learning

UL NO. 450: Thoughts on o1-preview and the Path to AGI

https://api.omny.fm/orgs/070af456-729b-4a0f-9c09-a6c100397b59/clips/295682b6-5d74-41f4-b8f5-b1ee01707902/transcript

...plus building personal TELOS files, the ChatGPT Pro vs. Claude coding face-off, a human bird flu case in Louisiana, and ketones fighting Alzheimer’s

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...plus building personal TELOS files, the ChatGPT Pro vs. Claude coding face-off, a human bird flu case in Louisiana, and ketones fighting Alzheimer&rsquo;s
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See you in the next one!

UL NO. 462: Full-Face Mask Deceptions, VS Code Tunnel Hacks, Quiet AI Emergence at Apple, and Tokyo’s Three-Day Weekend Gamble

https://api.omny.fm/orgs/070af456-729b-4a0f-9c09-a6c100397b59/clips/ec408000-3186-4f8a-8c48-b24e01631d23/transcript

...plus building personal TELOS files, the ChatGPT Pro vs. Claude coding face-off, a human bird flu case in Louisiana, and ketones fighting Alzheimer’s.

➡  Make your app enterprise-ready and start selling to enterprise customers with WorkOS: workos.com

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...plus building personal TELOS files, the ChatGPT Pro vs. Claude coding face-off, a human bird flu case in Louisiana, and ketones fighting Alzheimer&rsquo;s.
➡ &nbsp;Make your app enterprise-ready and start selling to enterprise customers with WorkOS: <a href="https://workos.com/">workos.com</a>
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See you in the next one!

https://api.omny.fm/orgs/070af456-729b-4a0f-9c09-a6c100397b59/clips/040a70b5-ce8a-4c81-b8c9-b24e016312eb/transcript

In this episode, Daniel Miessler explores how AI can transform our understanding of the present and create actionable paths for a better future.

He talks about:

The Current State, Desired State, and Transition in AI Applications:
How AI frameworks can analyze the current state, define a desired state, and propose action plans to address challenges in education, climate, health, and beyond.

The Infrastructure and Scale of AI:
Why we’re only at the beginning of building the AI infrastructure required for future demands, from GPUs and data centers to startups pushing the boundaries of what’s possible.

The Role of AI in Human and Organizational Development:
How AI can revolutionize personal lives, enhance businesses, and solve societal issues by gathering and analyzing massive amounts of contextual data to provide actionable insights.

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Chapters:

0:00 - Introduction to Unsupervised Learning Podcast 
1:10 - Concept: Predicting AI Infrastructure Needs
3:45 - The Challenge of Predicting Technology vs Human Desires
6:20 - Exploring AI Infrastructure Metrics (GPUs, Data Centers, Startups)
8:55 - Philosophical Insight: Current State vs Desired State 
12:15 - AI’s Role in Learning from the Past and Anticipating the Future 
14:50 - Addressing Global Issues with AI (Education, Poverty, Climate) 
18:30 - Transitioning from Current State to Desired State 
22:05 - Context Gathering: Granularity and Technology Limitations 
25:40 - AI's Impact on Individual and Family Contexts 
29:10 - AI’s Potential in Business: Granularity and Cost 
32:50 - Vision of Life OS and Personalized Assistance 
36:15 - AI in Society: Predicting and Preventing Problems 
40:00 - Infinite Context and the Scaling of AI Capabilities 
44:30 - Predictions on AI Context Size and Infrastructure Demand 
48:20 - The Importance of Understanding the Current State 
52:10 - Conclusion

In this episode, Daniel Miessler explores how AI can transform our understanding of the present and create actionable paths for a better future.
He talks about:
The Current State, Desired State, and Transition in AI Applications: How AI frameworks can analyze the current state, define a desired state, and propose action plans to address challenges in education, climate, health, and beyond.
The Infrastructure and Scale of AI: Why we&rsquo;re only at the beginning of building the AI infrastructure required for future demands, from GPUs and data centers to startups pushing the boundaries of what&rsquo;s possible.
The Role of AI in Human and Organizational Development: How AI can revolutionize personal lives, enhance businesses, and solve societal issues by gathering and analyzing massive amounts of contextual data to provide actionable insights.
Subscribe to the newsletter at:&nbsp; <a href="https://danielmiessler.com/subscribe">https://danielmiessler.com/subscribe</a>
Join the UL community at: <a href="https://danielmiessler.com/upgrade">https://danielmiessler.com/upgrade</a>
Follow on X: <a href="https://twitter.com/danielmiessler">https://twitter.com/danielmiessler</a>
Follow on LinkedIn: <a href="https://www.linkedin.com/in/danielmiessler">https://www.linkedin.com/in/danielmiessler</a>
See you in the next one!
Chapters:
0:00 - Introduction to Unsupervised Learning Podcast&nbsp; 1:10 - Concept: Predicting AI Infrastructure Needs 3:45 - The Challenge of Predicting Technology vs Human Desires 6:20 - Exploring AI Infrastructure Metrics (GPUs, Data Centers, Startups) 8:55 - Philosophical Insight: Current State vs Desired State 12:15 - AI&rsquo;s Role in Learning from the Past and Anticipating the Future 14:50 - Addressing Global Issues with AI (Education, Poverty, Climate) 18:30 - Transitioning from Current State to Desired State 22:05 - Context Gathering: Granularity and Technology Limitations 25:40 - AI's Impact on Individual and Family Contexts 29:10 - AI&rsquo;s Potential in Business: Granularity and Cost 32:50 - Vision of Life OS and Personalized Assistance 36:15 - AI in Society: Predicting and Preventing Problems 40:00 - Infinite Context and the Scaling of AI Capabilities 44:30 - Predictions on AI Context Size and Infrastructure Demand 48:20 - The Importance of Understanding the Current State 52:10 - Conclusion

How Much AI Do We Need? - My AI Industry Prediction

https://api.omny.fm/orgs/070af456-729b-4a0f-9c09-a6c100397b59/clips/eb4a208c-61bd-48c0-856a-b24201893fba/transcript

UL NO. 450: Thoughts on o1-preview and the Path to AGI

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