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.
why aren't all 8 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
Sachs: AI Model Quality Varies Between First-Party APIs and Cloud Providers
“Companies that say they're selling the same model through different vendors, whether it be through first party or Bedrock, Azure, et cetera, we do see different qualities sometimes, and that's not necessarily what's advertised.”
Andreessen: Autonomous AI agents will inevitably hire humans for tasks
“The agent hiring the people, which of course is going to happen, right? It's obviously going to happen.”
Bissell: CCP bias is identifiable in Qwen and DeepSeek-R1 representation spaces
“Well, there's, there are certainly internal, yeah, parts of the representation space where you can sort of see where that lives.”
Bryk: Perplexity and ChatGPT Search rely on legacy Google and Bing APIs
“So these systems, there are a few of them now they basically rely on like traditional search engines like Google or Bing, and then they combine them with like LLMs at the end to, you know, output some power graphics answering your question. So they, Like, Sear…”
Ben Allal: Recent web dumps improve model benchmarks despite synthetic data
“So what we did is we trained different models on these different dumps, and we then computed their performance on popular like NLP benchmarks, and then we computed the aggregated score. And surprisingly, you can see that the latest dumps are actually even bett…”
Joscha Bach: Only a Tiny Fraction of Wikimedia's Budget Goes to Servers
“The Wikimedia Foundation is publishing what they are paying the money for, and a very tiny fraction on this goes into running the servers, and the editors are working for free.”
O'Laughlin: Anthropic does not train Claude agent teams with RL
“I have a controversial opinion that Claude does not do RL on the agent swarms or agent team.”
Patel: Hugging Face libraries achieve only 15% MBU for inference
“Hugging Face's libraries are actually very inefficient, like incredibly inefficient for inference. You get like, 15% MBU on, on, on, on some configurations, like eight, eight, eight, eight, eight, eight, 100, and LLAMA-seventy-beat, you get like, 15%, which is…”