sepiasaucer's comments

From Matt Levine:

“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.”

A [crypto] Ponzi scheme is an investment fraud that pays existing [crypto] investors with funds collected from new [crypto] investors.

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?

Seems like maybe you would want to teach kids about safe smartphone use instead of abstinence only

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.

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.

https://youtu.be/jKYivs6ZLZk

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.

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.

“Where does that fit in your categories?”

It sounds like it falls mostly under illegal transactions because you are using crypto for something that would otherwise be illegal (avoiding capital controls). Is it technically illegal? I don’t know. Is it ethically wrong? I guess not directly. However, I imagine there are also a lot of nefarious reasons somebody might want to avoid capital controls which crypto could also help facilitate.

In the absence of a stable government backed currency it seems cryptocurrency could have some value. However, cryptocurrency is also unstable. You are speculating that holding crypto will be better over some period of time than any alternative value store you can access. That may well be true, but seems like that depends on what other options you have access to and would require more rigorous analysis of the tradeoffs. For example, if you were to say “crypto is a better currency than eggs” [1], that seems likely, but eggs don’t require internet access and specialized knowledge of a particular technology.

[1] https://www.economist.com/finance-and-economics/2018/07/19/w...

IMO the technology blockchain has only demonstrated success in 1 application which is cryptocurrency. Cryptocurrency has only demonstrated success in 2 applications: speculative investment and illegal online purchases. I would include NFT’s under the speculative investment category.

These applications are obviously problematic for 3 main reasons: it wastes enormous amounts of energy, the investment is often at the expense of less tech/financial savvy people, and most people don’t want it to be easier for criminals to conduct financial transactions.

IMO, it is not a few bad apples spoiling the bunch. It is a bunch of bad apples with a few good apples mixed in. Even if your motivations in working in this space are good (not simply for your own technical stimulation/amusement), you are trading off furthering/enabling real world harm now against optimistic speculation about future positive outcomes.

People are commenting on the quality of Door Dash predictions, but that isn’t what the article is about. The article is just about the architecture for high speed/throughput of prediction requests.

I would be interested in knowing how much improvement they saw by using C++ or Kotlin. Also, I don’t really understand what compute service is actually used to run the model predictions in this framework.

Couldn’t git lfs handle large non-textual files? How does SVN hand large non-textual files?