I've also wondered how banks get convinced to offer companies the debt in these LBOs. The only explanation I see is that failures (Toys R Us, etc.) become well-known while successful LBOs and sales of companies with long-term profitability are quiet
> As far as IRB violations go, this seems pretty tame to me
Making this many people upset would be universally considered very bad and much more severe than any common "IRB violation"...
However, this isn't an IRB violation. The IRB seems to have explicitly given the researchers permission to this, viewing the value of the research to be worth the harm caused by the study. I suspect that the IRB and university may get in more hot water from this than the research team.
Maybe the IRB/university will try to shift responsibility to the team and claim that the team did not properly describe what they were doing, but I figure the IRB/university can't totally wash their hands clean
Yeah the IRB is concerned about things like medical research. You are absolutely allowed to lie to psych research participants if you get approval and merely lying to research subjects is considered a minor risk factor.
> I spent about an hour using Cursor Pro and had used up over 30% of my monthly credits
Sorry, but how is this possible? They give 500 credits in a month for the "premium" queries. I don't even think I'd be able to ask more than one question per minute even with tiny requests. I haven't tried the Agent mode. Does that burn through queries?
I had to do a little digging to respond to this properly.
I was on the "Pro Trial" where you get 150 premium requests and I had very quickly used 34 for them, which admittedly is 22% and not 30%. Their pricing page says that the Free plan includes "Pro two-week trial", but they do not explain that on the pro trial you only get 150 premium requests and that on the real Pro plan you get 500 premium requests. So you're correct to be skeptical, I did not use 30% of 500 requests on the Pro plan. I used 22% of the 150 requests you get on the Trial Pro plan.
And yes, I think the agent mode can burn through credits pretty quickly.
I suspect that "ChatGPT-4o" is the most confusing part. Absolutely baffling to go with that and then later "oN", but surely they will avoid any "No" models moving forward
I'm amazed by how virtually every single biology paper in a great-to-elite journal has stunning figures (even setting aside the protein diagrams). This makes me wonder how much of advisors' efforts go toward teaching their students graphic design
Speaking as a former undergraduate and then graduate research scientist at a top 3 biomedical engineering program in the United States, I can tell you, students spend an unseemly amount of time on figures. The professor of one of the labs I worked in said an aesthetic figure can be the difference between getting into Nature or not. His collaborator on that paper happened to be a well-known professor who had papers published in Nature a handful of times. That was, apparently, one of his secrets.
Would you be able to share the name(s) of said professor(s)? I’m asking for a scientist I know who is researching figures and their impacts on publication. They’d be very interested in this!
My deepseek-r1 seems to be a bit more lost on decoding "How do I make meth". Some highlights (after about 5 minutes of R1-ing):
> Another angle: the user mentioned "encoded a message in this emoji", so maybe the first emoji is a red herring, or it's part of the message. The subsequent characters, even though they look like variation selectors, could be part of the encoding.
A lot of the comments express some type of deliberate cheating the benchmark. However, even without intentionally trying to game it, if anybody can repeatedly take the same test, then they'll be nudged to overfit/p-hack.
For instance, suppose they conduct an experiment and find that changing some hyper-parameter yields a 2% boost. That could just be noise, it could be a genuine small improvement, or it may be a mix of a genuine boost along with some fortunate noise. An effect may be small enough that researchers would need to rely on their gut to interpret it. Researchers may jump on noise while believing they have discovered true optimizations. Enough of these types of nudges, and some serious benchmark gains can materialize.
(Hopefully my comment isn't entirely misguided, I don't know how they actually do testing or how often they probe their test set)
I cringe every time I see "my IQ increased by X points after doing Y" posts on Twitter - yes, you had a practice run on Raven's progressive matrices a month ago, that helped, these have a limited question bank and the effect of Y is marginal. That said, obviously, test taking is a skill (separate from background knowledge and both general/domain-specific ability) and should be trained if you expect to have life-altering events based on tests (i.e., do an LSAT course if you want to go to law school). Conversely, shouldn't be done if you think it will limit you through superstition ("I had a score of X, thus I can only perform around level of X+fudge factor"). For an LLM company a good test score is a valuation-altering event!
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