> If they are able to actually successfully pivot into ads as a business model, it's very easy to justify the valuation: Just look at Google/Meta.
Ads are not just a switch one can turn on. Firstly, you need to build a decent ad serving/targeting/pacing engine. Secondly (and more importantly) you need to hire a shed ton of sales people (in many, many geos) and then ramp them all up (difficult if you're building the product at the same time).
And then you need to keep at it for 3-5 years minimum before you'll finally get the bigger/more conservative brands/agencies/etc to buy in properly.
At that point, you'll make decent money, after accounting for all of the costs. I'm not sure that you'll make enough money, but it would definitely stanch their bleeding a little.
tl;dr if they haven't already built this ad product, it's unlikely to make a material difference before 2030.
> They probably know more than us. Such as alternative chips or that the Chinese will go in-house sooner than we think. Nvidia’s moat is not as permanent as people think.
This is Softbank though, they're not really noted for great investment decisions (apart from Alibaba really early on).
Like, my prior is that when Softbank invest in something, the growth is done (but then I am, very much, a cynic).
Softbank had 5% of Nvidia stock just before gen AI boom. Then they sold it when it was at its lowest. If they didn't it would have covered all their losses many times over with a profit of more than 200 billion dollars.
It's just baffling they are still getting billions to spend.
> It's just baffling they are still getting billions to spend.
When you realize that most investors at that level are degenerate gamblers, and that they're even worse about thinking "the Generals were due!" than your buddy who can't look away from the DraftKings app for more than five minutes, it's not so baffling anymore. The only difference is that when you have that much money, you own the casino.
Bill Hwang of Archegos Capital Management is a close second (lost $20B in two days, and basically brushed off margin calls while his highly overlevered bets were collapsing, incurring $10B+ of losses at the investment banks he worked with).
About 7 or 8 years ago I worked at a startup which got money from Softbank / Masayoshi Son. Our founder and our CTO went to meet him in LA IIRC to pitch.
They came back telling us he was basically asleep during the pitch meeting which was scheduled for only 10 minutes anyway.
Our business/product really had no chance of succeeding at this point and most knew it. We got some money from Softbank anyway - forgot how much. Our management was basically laughing about how easy it was to get funding from Softbank.
I jumped ship a year later or so and that was good timing.
This is one of my arguments that startups are mostly about luck - because smart people who are highly incentivised to pick wimmers, with all the data they need to pick winners, all the people and compute they need to pick winners, can't pick winners.
Mayoshi Son isn't playing the VC game like most traditional VC funds. He's operating on a massive scale and his LPs are sovereign wealth funds, who can have other geo-political priorities than pure profit.
Some people don't know that the usual VC game is often still be profitable for the VC even if their fund isn't profitable. VCs are investing the money of their LPs (Limited Partners), who are usually very large institutional investors with billions under management (think state pension funds, Harvard endowment). Most of the LP's funds are invested in a diversified blend of safer, lower-return vehicles but they take up to 5% and invest it in high-risk, high-return things like venture capital and hedge funds. But they spread it across a dozen or more firms with different strategies.
So each VC is playing a portfolio bets and their LPs are playing a portfolio of porfolios. The LPs just need one of their 12+ VC funds to be a lead investor on a unicorn win. This math usually works out in their favor (there's now >50 years of data). VC funds charge their LPs a yearly management fee of a few percent of the invested capital - whether the fund makes money or not. Over the 10 year life of a fund, this adds up and covers the VCs overhead and very generous salaries - usually >$500K at larger firms. In the VC's view, $500K/yr isn't getting long-term "rich" but it'll pay for a pretty lux life. Even with the VC taking out fees, the LP's math still works thanks to only needing one VC firm to win and if one or two more of their VC funds just return 2x or 3x. It maths up even better.
When your personal worst-case downside is $500K/yr minimum with substantial upside, it's not a bad gig. However, these VC types are generally top-of-class Ivy League grads, who are clearly very sharp and ultra high-potential - the type who'd expect $500K earning opptys on Wall Street, consulting, investment banking, etc.
Lottery winners do not tell the world they are smarter than the rest of us, or go on podcasts, write op-eds or start websites telling the rest of us how the world should be run.
> It is hard not to love the degeneracy of Son Masayoshi as a gambler. The trick is to not take it seriously.
Therein lies the problem. People do take it seriously, particularly on the idea that he's now due, and keep feeding him money to make these bets with, instead of tossing him out of the boardroom, like he should have been with his bet on WeWork.
I had 250 shares I bought on a tip and sold for a decent profit then NVDA moon-shotted later that year. That's the story of my stock buying life right there.
I can't see any rational politician letting this go beyond another two weeks. I can't imagine keeping people away from their families over Thanksgiving is gonna work out well for anyone.
I write mostly Python these days, but agree with op. The comparables implementation in Ruby seems much nicer to me (maybe because I'm less familiar with it).
Then use the `total_ordering` decorator to provide the remaining rich comparison methods.
That said, it's a little annoying Python didn't keep __cmp__ around since there's no direct replacement that's just as succinct and what I did above is a slight fib: you still may need to add __eq__() as well.
> Then use the `total_ordering` decorator to provide the remaining rich comparison methods.
While we're here, worth highlighting `cmp_to_key` as well for `sorted` etc. calls.
> it's a little annoying Python didn't keep __cmp__ around since there's no direct replacement that's just as succinct
The rationale offered at the time (https://docs.python.org/3/whatsnew/3.0.html) was admittedly weak, but at least this way there isn't confusion over what happens if you try to use both ways (because one of them just isn't a way any more).
Ocaml was (historically, at least) used by Facebook for basically all of their linter/compiler/type checker work. The hack checker was in Ocaml, as was the JS thing (flow, maybe?).
So that does seem to be a good use-case for the language.
That was why I mentioned compilers along with HFT. Rust was originally an ocaml based compiler too.
I don't build HFTs and my compilers are just for fun. None of my day jobs have ever been a situation where the smaller ecosystem and community of ocaml was offset by anything ocaml did better than the selected options like .net, Java, go, rails, C or anything else I've touched. Heck, I've written more zig for an employer than ocaml, and that was for a toy DSL engine that we never ended up using.
I live in France, which I'm not sure if you paying attention to it (no judgement, why would you), but as a country, they're somewhat financially screwed, so whether or not there are elections, or even if the people have representation, something needs to be done, and it will likely involve higher taxation and cost of living generally.
Ok fair, France has been a disaster lately. However, it's actually more that as a country, you'll need to figure out coalitions as it looks pretty evenly split three ways.
If it's any consolation, I probably pay similar tax rates to France, and get way worse services.
The W is important there. If the DAUs were good, they'd report those. I do generally find that LLMs are a weekly thing at best in a chat bot form (the agentic stuff I use more often).
If I operated a vending machine that spat out a dollar every time somebody pressed a button, I'd have just as many weekly users as I put dollar bills into it. You wouldn't call that a winning business despite the exceptionally high rate of 5-star reviews.
The more appropriate analogy is: you have a vending machine that dispenses a paper slip with your fortune on it everytime somebody presses a button. However you can only get one fortune told per day, but you can pay to get more in bulk.
Turns out people find these fortunes super useful, and many are actually paying real money to get more, and each vending machine is actually making money on this.
But now the vending machine industry has also figured out that bigger, more powerful machines produce tell better fortunes which draws in even more people.
So now the industry is investing heavily to build more, bigger vending machines. However, these machines need tons of expensive parts and power, and oh, we can't slow down because China, and so they are racing like crazy to build more.
Unfortunately, there is effectively only one company making a key part, and there's not enough power for all the machines being built, and so very expensive new infrastructure has to be built to meet the forecasted demand for all the fortunes in the world.
And this requires trillions in funding, which gets very expensive to borrow, and so the US government is being asked to provide loan guarantees, because who better would know what interest payments on trillions of debt look like?
It's a losing company if they aren't making money and have no feasible path to do so, considering amount of outstanding debts they already have and future debt they are planning to take.
> Weird thing to fixate about when the whole industry actually uses MAUs.
Are you kidding me? Like, both Google and Facebook tracked l7, l28 which is the number of days that a person/account logged in over the last 7 or 28 days. Fundamentally, that's the sign of a useful product, in that people keep coming back.
> 800M WAU is a "losing company"?
Not enough information to be sure. If their business model requires selling dollars for fifty cents, then maybe.
I don't doubt the utility of these products (sometimes), but I do doubt the business model behind OpenAI & Anthropic (the "pure" model providers).
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