It's so funny. Every single time a company raises a ton of money at a large valuation, the comments are always filled with "how do they justify this valuation" or "they aren't work X...because Y and Z do the same thing".
VC math is pretty simple - at the end of the day, there's a pretty large likelihood that at least 1 AI company is going to reach a trillion dollar valuation. VCs want to find that company.
OpenAI, while definitely not the only player, is the most "mainstream". Your average teacher or mechanic uses "chatgpt" and "AI" interchangeably. There's a ton of value in becoming a vowel, even if other technically superior competitors exist.
Furthermore, the math changes at this level. No investor here is investing at a $300B valuation expecting a 10x. They're probably expecting a 3x or even a 2x. If they put in 300MM, they still end up with 600-900MM.
This isn't math on revenue, it's a bet. And if you think in terms of risk-adjusted bets, hoping the most mainstream AI company today might at least double your money in the next ten years in a red-hot AI market is not as wild as it seems.
The best way I’ve heard this described: AI (LLMs) is probably 90% of the way to human levels of reasoning. We can probably get to about 95% optimizing current technology.
Whether or not we can get to 100% using LLMs is an open research problem and far from guaranteed. If we can’t, it’s unclear if it will ever really proliferate the way things hope. That 5% makes a big difference in most non-niche use cases…
Odds are this is a dev shop with more than one person doing at least some things. It would explain how “he” was able to get so many jobs and maintain appearances. And a lot of startups don’t have the best screening processes to begin with (have a beer with a founder, check out their source code, you’re hired!). This is exactly the place where the structure and processes of larger companies can be a benefit. And even then, people work multiple jobs and get away with it. It’s become popular post COVID.
Given these two factors, I don’t think it would be out of the realm of possibility for something like this to happen.
Nintendo has never competed on graphics. They compete on having the most fun, accessible, entertaining games as possible. And say what you will about their business practices, they’ve probably done a better job of that than any other gaming company in history. As more devs bundle ever higher quality graphics with ever higher in-app purchases and pay to win schemes, Mario remains…Mario.
I seriously doubt many Switch users would bail on the system because of “fake” HDR. They probably don’t care about HDR at all. As long as Mario remains Mario, they’re happy.
Lol in what world was the US education system the envy of the world? We’ve been routinely clowned for overspending, poor outcomes, university tuition bloat, and everything else under the sun.
There isn’t a single founding engineer at a publicly traded company that regrets their choice to sacrifice salary at a more stable company for 1% of a startup.
Becoming a founding engineer is a wealth-building, passion-for-your-work risk, not a pure salary optimization decision. HN never seems to understand this. If you’re optimizing for stable salary, go for the FAANG position. You’ll be comfortable, but you’ll most likely never be able to fly private, and you’ll have to be OK existing as a cog in a massive machine. Plenty of people are ok with this. These people should not be founding engineers.
The math simply never works out in favor of lower salaries/publicly funded healthcare for high paying US roles like software engineering. Even taking your (high, assuming family of 4) premiums and 0% employer contribution (very uncommon), that’s an additional $43k a year, pretax. US SWE salaries are double, sometimes triple international with absolute numbers at $50k+.
This doesn’t even factor in general higher tax brackets abroad
Never think that pure hard work leads to success, placement, privilege, or anything else. The farmhand in a field works harder than 99.9% of high paid tech employees. Hard work is important, sure, but it’s all about relative value contribution in the market, nothing else.
It’s easy to find another farmhand, it’s hard to find another ML engineer
VC math is pretty simple - at the end of the day, there's a pretty large likelihood that at least 1 AI company is going to reach a trillion dollar valuation. VCs want to find that company.
OpenAI, while definitely not the only player, is the most "mainstream". Your average teacher or mechanic uses "chatgpt" and "AI" interchangeably. There's a ton of value in becoming a vowel, even if other technically superior competitors exist.
Furthermore, the math changes at this level. No investor here is investing at a $300B valuation expecting a 10x. They're probably expecting a 3x or even a 2x. If they put in 300MM, they still end up with 600-900MM.
This isn't math on revenue, it's a bet. And if you think in terms of risk-adjusted bets, hoping the most mainstream AI company today might at least double your money in the next ten years in a red-hot AI market is not as wild as it seems.