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He went to Yale and worked at a prestigious VC firm. Most people with those credentials are at least reasonably smart.


Ivy League schools are notorious for inflating grades to make their graduates look smarter. It seems the biggest factor for entry is money.

Before you reply, let me be very clear: Yes, very smart people do go to Yale, and yes, people go to Yale without lots of money. A few specific instances does not negate the general case.


Vance went to open admission Ohio State for undergrad and went to Yale Law school via DEI admission, on the strength of his mother's drug addiction.


Working at a prestigious VC firm means you can schmooze, network, and lie.


what do you think people should do when their countries experience hyperinflation?


They should ask why it's happening so regularly that startups are springing up to insure against it.


The causes of, and solutions to, hyperinflation are well understood [0]. Solving the problem might require a political revolution. When you have a playbook for doing that in a peaceful way, please let us know!

[0] https://mru.org/courses/principles-economics-macroeconomics/...


Is that the bar necessary to believe systemic change is possible? I'd argue it should be "any slightly more peaceful way than the existing order". Perfect the enemy of good and all that. Or am I missing something?


sure! and in many situations, a new technology or company or whatever is a kind of systemic change. For instance, right now I'm accessing this website via VPN in a place where hacker news is blocked. That's both a technological solution and a political change.

The OP comment is about how it's dystopian to seek technological/financial solutions to political problems. I think that attitude is misguided.


Seems kind of silly, would you have this kind of moralizing argument against people in the US buying treasury bonds right now?


Investing in treasury bonds is a bet on your country's long term economic health. This is a startup, explicitly preying on people's fears in poor countries to transfer their wealth into cryptocurrency.

Apples and oranges.


Just "ask" and take no action to protect themselves?


What company are you at? I've been working on a product to solve this problem.

If you're up for a chat my email is on my page here https://www.zachocean.com/contact/


Were you able to find good candidates from your post eventually?


Not yet. It has been a week and I have 500+ resumes sitting in the inbox. Not fun.


Just curious, do you use LLMs in your reviewing process? e.g. Summarization, prioritization, etc.


Thinking about it. Might build my own tool.


Good luck! Sounds terrible


I mean, inference costs have decreased like 1000x in a few years. OpenAI is the fastest growing startup by revenue, ever.

How foolish do you have be to be worrying about ROI right now? The companies that are building out the datacenters produce billions per year in free cash flow. Maybe OP would prefer a dividend?


Given how close the tech is to running on consumer hardware — by which I mean normal consumers not top-end MacBooks — there's a real chance that the direct ROI is going to be exactly zero within 5 years.

I say direct, because Chrome is free to users, yet clearly has a benefit to Google worth spending on both development and advertising the browser to users, and analogous profit sources may be coming to LLMs for similar reasons — you can use it locally so long as you don't mind every third paragraph being a political message sponsored by the Turquoise Party of Tumbrige Wells.


> OpenAI is the fastest growing startup by revenue, ever.

No it's not. Facebook hit $2B in Revenue in late 2010 - early 2011, ~5 years after its founding.

https://dazeinfo.com/2018/11/14/facebook-revenue-and-net-inc...


Finding one example of him being wrong still kinda supports his point, don't you think?


No, it makes me think there are more. ", ever." Suggests you actually know the space of things you're talking about.


Especially when that example is Facebook!


MySpace had $1.5B in sales in 2009.


Facebook sold 2b of ads this week.


Coinbase was founded in 2013 and hit $1B in revenue in 2019 iirc


I would definitely be worried about ROI if my main product was something my big tech competition could copy easily because they did the research that led to my product.


Exactly right. Traditional VCs come up with a thesis and then buy 20% of the company they think will be the winner who fits that thesis when they're at like $1M to 10M revenue (series A)

YC can instead get ~10% of every plausible winner they come across when they're at $0 revenue


As noted elsethread, I think that almost certainly *is* what's going on; I was explaining why it's probably a good thing from (at least many of) the companies' perspectives too.


What's your use case?


I’m a fluent speaker in the language I am translating to, but have trouble with grammar. I write texts (email, jira tickets etc) in English or my native language and let DeepL translate. I then adapt the translation to sound less machine-y


Can't wait for them to move up to Seattle. We're basically San Francisco with slightly easier hills and more rain/occasional ice, so seems like a good candidate.


Yes on Seattle. We also have much more expensive Ubers/Lyfts than SF.


Ginormous market, 10x better product, no competition is currently close.

Plus although they have the capital cost of owning the cars they don't have the COGS of paying the drivers so presumably much higher margin per ride.


You’re right that Tesla’s product is so far ahead that it can’t really be called competition.


I love Tesla, I own the stock, but I don't think they can be considered comparable until they have a live autonomous taxi service that regular people can call from their phones and regularly rave about.


On one hand, Tesla could roll out a Waymo competitor in all the necessary cities in a matter of months if they wanted to. On the other hand, Waymo will cease to exist as soon as Tesla cracks their robotaxi problem.


Cool, looks like this is trained on 16 million hours of audio (500B tokens at ~.11 seconds per token).

Even the large open source TTS models (see F5 TTS, Mask GCT) are mostly trained on very small audio datasets (say 100k hours) relative to the amount of audio available on the internet, so it's cool to see an open source effort to scale up training significantly.


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