ChatGPT voice (transcribed, not native) is available on iOS and Android, and I think desktop as well.
Not to derail on details, but what would it mean to solve alignment?
To me “solve” feels overly binary and final compared to the true challenge of alignment. Like, would solving alignment mean:
I’m really not sure which you mean, which makes it hard for me to engage with your question.
The author is not shocked yet. (But maybe I will be!)
Strongly disagree. Employees of OpenAI and their alpha tester partners have obligations not to reveal secret information, whether by prediction market or other mechanism. Insider trading is not a sin against the market; it's a sin against the entity that entrusted you with private information. If someone tells me information under an NDA, I am obligated not to trade on that information.
Good question but no - ChatGPT still makes occasional mistakes even when you use the GPT API, in which you have full visibility/control over the context window.
Thanks for the write up. I was a participant in both Hypermind and XPT, but I recused myself from the MMLU question (among others) because I knew the GPT-4 result many months before the public. I'm not too surprised Hypermind was the least accurate - I think the traders there are less informed, plus the interface for shaping the distribution is a bit lacking (my recollection is that last year's version capped the width of distributions which massively constrained some predictions). I recall they also plotted the current values, a generally nice feature which has the side effect of anchoring ignorant forecasters downward, I'd bet.
Question: Are the Hypermind results for 2023 just from forecasts in 2022, or do they include forecasts from the prior year as well? I'm curious if part of the poor accuracy is from stale forecasts that were never updated.
Confirmed.
I'd take the same bet on even better terms, if you're willing. My $200k against your $5k.
$500 payment received.
I am committed to paying $100k if aliens/supernatural/non-prosaic explanations are, in the next 5 years, considered, in aggregate, to be 50%+ likely in explaining at least one UFO.
>The artificially generated data includes hallucinated links.
Not commenting on OpenAI's training data, but commenting generally: Models don't hallucinate because they've been trained on hallucinated data. They hallucinate because they've been trained on real data, but they can't remember it perfectly, so they guess. I hypothesize that URLs are very commonly hallucinated because they have a common, easy-to-remember format (so the model confidently starts to write them out) but hard-to-remember details (at which point the model just guesses because it knows a guessed URL is more likely than a URL that randomly cuts off after the http://www.).