why aren't all 6 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
Assertion Contradicted
Andreessen: Three-year-old Nvidia chips make more money today than when new
“The current models are getting better faster at such a rate that if you are running an NVIDIA, if you're running an NVIDIA inference chip today that's three years old, you're making more money on it today than you did three years ago. Because the pace of impro…”
Prediction Didn’t hold up
Andreessen: AI will never transform existing US K-12 public classrooms
“How are we going to apply AI in education? The answer is we're not because it's a literal government monopoly. It is never going to change the end, and there is nothing to do. By the way, you can create an entirely new school system. Like that's the one thing …”
Assertion Contradicted
Hill-Smith: Google used unpublished 32-shot CoT to claim Gemini beat GPT-4
“Back when I'm Googled a Gemini one when I ultra and needed a number that would say it was better than GPT four. And Like, constructed I think never published, like, chain of thought examples, 32 of them in every topic in MLU to run it, to get the score.”
Prediction Didn’t hold up
Swix: OpenAI will issue a cryptocurrency token to fund compute
“There is still one more shoe to drop, which is the non sovereign wealth funding that open AI needs to get, which they've promised to drop by the end of this year.
And my money is on, they have to do a coin.
Like it's, I'm not a crypto guy at all, but like, y…”
Assertion Contradicted
Feldman: Cerebras is 20 times faster than Nvidia B200 GPUs
“Really focused on performance, both for training and for inference. You think 20 times faster than Nvidia B 200 GPUs and it's been an amazing run.”
Assertion Contradicted
Bachman: Models claiming 256k+ context use windowed transformers, discarding data
“Anybody who says they're using a transformer
With a context length of, you know, 256,000 or more, they're not using a true transformer.
What they're using is a windowed transformer that essentially throws out a huge amount of its information at various layers …”