Running AI Locally and Hyperscaler Risks

Former Apple employee, Mark Suman explains why Apple refused to allow ChatGPT internally and what that reveals about how AI systems are learning how we think.

Most people are now using AI every day - for work, personal decisions, even private conversations. But as Mark explains, the more we share, the more these systems begin to model our behaviour, often understanding our thinking patterns better than we do ourselves.

This raises a deeper question: what happens when intelligence is centralised, and systems can influence not just what we do, but how we think?

We discuss privacy, data, government power, and the trade-offs between convenience and control and why the biggest risks of AI are not in the future, but already happening now.

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TIMESTAMPS:

00:00 Introduction 01:17 What is "thought capture"? 02:57 How AI starts profiling users 06:40 Are we heading to superintelligence? 08:51 Mapping human thinking at scale 11:38 How algorithms influence behaviour 16:53 Why Apple blocked ChatGPT internally 20:00 The risks of sharing data with AI 25:55 Advice for everyday users 30:00 The real risks of AI systems 32:13 AI and mass influence 35:46 How AI could steer opinions 42:01 AI, Bitcoin & sovereignty 47:25 Where we are as a civilisation 50:00 Trust in institutions collapsing 55:47 Is society breaking? 1:12:45 AI and job displacement 1:15:02 Should AI be regulated? 1:23:55 AI exhaustion 1:29:13 The future of human work

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