The Ledger

Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.

clear all ✕

why aren't all 4 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable

Prediction Held up
Narayanan: Restricting global access to AI models will fail
“Even if one country decides that models should be closed, the odds of getting every country to enact that kind of, ah, ah, rule are, you know, just vanishingly small. So if our approach to safety with AI is going to be premised on ensuring that quote unquote b…”
Arvind Narayanan Aug 28, 2024 ▶ 42:54 Arvind Narayanan: AI Scaling Myths, The Core Bottlenecks in AI Today & The Future of Models | E1195 · 20VC with Harry Stebbings
Assertion Supported
Narayanan: YouTube transcript text is an order of magnitude smaller than current AI training sets
“A hundred and fifty billion hours of video sounds, you know, really impressive. But when you put that video through a speech recognizer and actually extracts the text tokens out of it and deduplicated and so forth, it's actually not that much. It's an order of…”
Arvind Narayanan Aug 28, 2024 ▶ 6:31 Arvind Narayanan: AI Scaling Myths, The Core Bottlenecks in AI Today & The Future of Models | E1195 · 20VC with Harry Stebbings
Assertion Supported
Narayanan: No reliable method exists to detect AI-generated text
“There's no way really to catch AI-generated text or homework answers.”
Arvind Narayanan Aug 28, 2024 ▶ 35:34 Arvind Narayanan: AI Scaling Myths, The Core Bottlenecks in AI Today & The Future of Models | E1195 · 20VC with Harry Stebbings
Assertion Supported
Narayanan: Inference costs dominate training costs for popular AI models
“Over the lifetime of a model, when you have billions of people using it, the inference cost actually adds up, and for many of the popular models, that's the cost that dominates.”
Arvind Narayanan Aug 28, 2024 ▶ 15:33 Arvind Narayanan: AI Scaling Myths, The Core Bottlenecks in AI Today & The Future of Models | E1195 · 20VC with Harry Stebbings
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