“Doesn’t that Journal story sound a bit like that? I mean here is a story you could tell:
1. You have 1,000 Bitcoin worth about $17 million.
2. You want to buy more Bitcoin, but you do not have any dollars.
3. You go to Tether and say “hey give me 17 million USDT, in exchange I’ll put up 2,000 Bitcoins as collateral.”
4. Tether is like “sure that’s the business we’re in” and hands you 17 million USDT.
5. You use that 17 million USDT — notionally worth $17 million — to buy 1,000 more Bitcoin.
6. Now you have 2,000 Bitcoin.
7. You post the 2,000 Bitcoin as collateral to Tether for the loan, which is now overcollateralized with liquid collateral ($34 million worth of Bitcoin).
8. More USDT have been created to buy Bitcoin, but no new dollars have come into the system.
Maybe this is fine, no problem, just margin lending. [4] But if your concern is “Tethers are printed out of thin air in order to allow people to buy crypto without putting any actual dollars in,” then this might make you nervous.”
Sounds like a cool place to work! I interned at SpaceX in undergrad and worked at ONERA while getting PhD. I work as Data Sci now. I see an open Data Sci position that looks like good fit. Do you think I could negotiate for being remote or is the on-site policy pretty strict?
This. It's better to gradually introduce them instead of fully abstaining. They'll need them at some point, as our society is becoming increasingly reliant on it, and when you suddently let them do whatever without moderation, the same problems will occur.
not every parent has the time or experience to do that. banning smartphones is easier than constantly supervising their use. to much supervising may also breed resentment from the kids, especially when they get older.
i feel it's better to first deny them and later give them the phone on trust. like they are old enough to handle a phone now. that should lead to a better relationship with the kids
I don’t understand what point you are trying to make.
Specific stocks being bad investments is not an argument against passive investing. The whole point of index funds is to diversify your portfolio so you track the overall market, not any specific stock or group of stocks.
If you are assuming you know which stocks/sectors are under or overvalued, then I guess active investing makes sense, but that seems like a flawed premise to start from.
You aren’t tracking the whole market. An index is a subset. Even total market indices have weightings which embed biases. And the whole game has been reverse engineered by charlatans to dump crap into rivers of blind money. If think capital offerings aren’t designed explicitly to target index inclusion criteria then you aren’t in on the joke.
> And the whole game has been reverse engineered by charlatans to dump crap into rivers of blind money. If think capital offerings aren’t designed explicitly to target index inclusion criteria then you aren’t in on the joke.
This is an interesting and plausible take, just wondering if you have actual published resources on that or is it your personal, arguably justified hunch?
If employees are “hybrid” without mandatory attendance, then I think most people won’t go into office. I work in a smaller satellite office and if you randomly go to office you may be only person there.
I think employers thought “hybrid” was good way to get employees to agree to going back to office. In reality, I think it was good way for employees to get employers to agree to effectively fully remote work without explicitly demanding it.
It’s like in Office Space:
PETER
I, uh, I don't like [the office]. I don't think I'm gonna go anymore.
JOANNA
You're just not gonna go?
PETER
Yeah.
JOANNA
Won't you get fired?
PETER
I don't know. But I really don't like it so I'm not gonna go.
JOANNA
LAUGHS) SO YOU'RE GONNA [go fully remote]?
PETER
No, no, not really. I'm just gonna stop going.
I don’t think you could easily prove Twitter is materially misrepresenting the number of bot/spam accounts. Presumably, it is just an estimate based on some combination of assumptions and statistical analysis. You might be able to create a significantly higher estimate, but that seems different than proving material misrepresentation.
It's rampant tin-foil hat speculation, but the ordering of events may not be what we've seen.
Yesterday the big story was that two higher-ups in Twitter were fired unexpectedly, one of whom was on paternity leave at the time. Some amount of shake-up is normal in these kind of conditions, but that doesn't rule out something more. Today Elon's pushing back, suggesting the 5% bot rate may be inaccurately low. It's possible the events are related, some misrepresentation was found while investigating the figures, and that's why the firings happened yesterday.
If that happened, it'd be in Elon's interest to draw attention to it and that the deal is "on hold," as Twitter will be on the hook for that $1 billion breakup fee unless they can renegotiate terms favorable to Elon. And even if the deal dropped completely, now Twitter implicitly will be on the hook for misrepresenting to existing investors the percentage of bots for however long they've been doing it.
I guess we'll see. The truth will probably be more boring.
I believe they (Twitter etc) are working on moderation. I do not know if that is their core competency or if they want to be in the content moderation business. I was wondering if a 3rd party might provide content moderation as a service.
Transparency is very important. If you can’t explain your solution then maybe a simpler, but less accurate method is preferred. Maybe you could set some defaults but allow more user control. Maybe you could have humans in the decision making process, but still integrate with ML models for scale. I don’t know best solution, but offering content moderation as a service would shift some blame away from social media platform even if it was not better than what they were doing in-house.
I would focus more on the enabling technology for this scam (e.g., how would a victim transfer $300,000 using traditional financial system? how they might recover those funds if needed?)
“One can, in theory, start with lots of architectures, then optimize each one and pick the best. “But training [takes] a pretty nontrivial amount of time,” said Mengye Ren, now a visiting researcher at Google Brain. It’d be impossible to train and test every candidate network architecture. “[It doesn’t] scale very well, especially if you consider millions of possible designs.””
——-
If you wanted to find best architecture in order to maximize accuracy, why not just train a model to predict accuracy (not parameters) given architecture and then optimize over the model?
This seems similar to optimizing any expensive black box function. Fit a cheap approximation (i.e., surrogate model) and then optimize over cheap model.
“Doesn’t that Journal story sound a bit like that? I mean here is a story you could tell:
1. You have 1,000 Bitcoin worth about $17 million.
2. You want to buy more Bitcoin, but you do not have any dollars.
3. You go to Tether and say “hey give me 17 million USDT, in exchange I’ll put up 2,000 Bitcoins as collateral.”
4. Tether is like “sure that’s the business we’re in” and hands you 17 million USDT.
5. You use that 17 million USDT — notionally worth $17 million — to buy 1,000 more Bitcoin.
6. Now you have 2,000 Bitcoin.
7. You post the 2,000 Bitcoin as collateral to Tether for the loan, which is now overcollateralized with liquid collateral ($34 million worth of Bitcoin).
8. More USDT have been created to buy Bitcoin, but no new dollars have come into the system.
Maybe this is fine, no problem, just margin lending. [4] But if your concern is “Tethers are printed out of thin air in order to allow people to buy crypto without putting any actual dollars in,” then this might make you nervous.”