Measuring Machine Intelligence with Chris Painter

About this episode

The episode discusses the challenges of measuring the performance and risks of artificial intelligence systems in real-world settings.

Artificial intelligence is advancing rapidly, but our ability to measure what these systems can actually do—and the risks they may pose—has lagged behind. Headline benchmarks and viral demos offer snapshots of a system's performance, but they say little about how AI behaves in complex real-world settings or how much autonomy models can sustain over time. As these systems take on more consequential roles, the challenge is not just building more powerful models, but developing credible ways to ...

People in this episode

Guest: Chris Painter

Topics covered

• artificial intelligence
• machine intelligence
• performance measurement
• real-world applications
• autonomy
• risks

Keywords

• artificial intelligence
• machine intelligence
• performance measurement
• real-world settings
• autonomy
• risks

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