Ah, yes, part one of the ole

That didn't happen. And if it did, it wasn't that bad. And if it was, that's not a big deal. And if it is, that's not the IDF's fault. And if it was, they didn't mean it. And if they did, Gaza deserved it.

Seems like you’re asking “what’s the point of investigating crimes against humanity?”

And if that’s a question you have to ask, then clearly something is very wrong.

Seems like a good question to ask imo. The lack of accountability of crimes against humanity and children and the general apathy and shrug worthy reaction to most people to these issues especially on this site seems relevant commentary.

Definitely a unicorn success story. I’d be curious about Balatro in a similar vein—-labor of love turns wildly successful

Their job, in this case, is probably more of a signal than a clear indicator

Plenty of front-running companies have hired plenty of…not-solid or excessively imaginative data scientists

From what the other comments say, this one seems to lack a grounding in science itself, which frankly is par for the course depending on their background

I understand the strategy isn’t to find a niche in the sense of a specific set of users, but to broaden and cover more niches

The niches exist (overlapping niches aside), but agree with the skepticism since I also wonder whether the switching cost is worthwhile for many users

Not completely—as far as ecosystems there are RStudio addins, but I wouldn’t bet addins are extensively used

Computation isn’t likely prohibitive when using the bedrock of predictive models, linear regression, especially w some optimization. Could also vary observation time so you only need a prediction once every ten minutes or whatever

The real issue is the cost of false positive detection of cheating is negligible since the vast majority of positives are probably true positives—it’s the cost of doing anti-cheat business (minimal)

But yes cheats would be modified to just below thresholds of detection

>Computation isn’t likely prohibitive when [...]

I think this might be in reply to my first comment about scaling? If so, I just want to clarify that I was thinking more along the lines of scaling the customer service/ban appeal side rather than infrastructure.

If, for example, every ban had a component of someone at Valve taking 10 seconds to review in-game stats at the time of the ban, and then making a determination of whether or not those stats seem reasonably non-cheater-ish (pretty hard policy question in itself), the process would slow to a crawl.

Could you share a reference for those wanting to learn more?

Unfortunately I can't. I closed the chat a while ago. It was kinda long conversation, in which I convinced the model to abandon its role first. As side effect the "thinking" switched to Chinese and I stopped to understand what it "thinks" and the excerpt I posted above was the last answer in this conversation. I would not trust any number in this response, thus there is no point in any reference.

Had a lot of fun reading this. I’d love to see some of the author’s code to get a sense what the journey produced, if that’s even possible

That second study didn’t use as robust of methods as the first, and they each used observational data that benefit from advanced methods (propensity score analysis).

With an RCT, the evidence is substantially increased.

I’d conclude sildenafil reduces risk of age-associated cognitive decline