The fact that this guy could see that massive data analysis with was a winning investment strategy and then out compete others with way more experience in financial markets is impressive.
I’d be curious in the markets he initially invested in. Was this a market inefficiency specifically in China in the late 2000s?
I’ve always assumed that quantitative analysis requires PhD level knowledge of markets and mathematics but maybe I’m being way too conservative?
It would mean some harsh years at first, but it’s a good time to hit the market.
I remember being told I’d never be successful, or make as much money as my parents.
I only wish I hadn’t listened to those people so long.
A good market helps you become a bog standard boring wage slave, maybe get a mortgage, etc.
The outsized success folks will go out and get what they need regardless, they aren’t waiting for it to come to them.
Incredible that people would see the notion of having a moderately successful white collar career (maybe get a mortgage etc) as "boring wage slave".
This is nonsense. Other than the local mafia, almost all extremely successful folk live in extremely affluent markets.
It’s been 6 months? Geminis big upgrade was 2 months ago and o3 even more recent.
It’s just funny that US companies just barely got ahead the last couple months and already it’s a “drawn out narrative” that they aren’t ahead.
For all we know R2 drops tomorrow? If it’s ahead or even how are we supposed to think about the narrative?
IMO it’s not really that much of a stretch to say they’re fairly close together. I’d want to wait 6 more months where the US stayed significantly ahead before I’d be complaining about narratives. I know things move fast but that’s all the more reason to wait and see.
I hope that R2 releases tomorrow and you enjoy some presumed clairvoyance for a minute.
The field is really moving too quickly to talk too certainly about "dominance" or "ahead". My observation is projects I care about on GitHub come with a Chinese README and many interesting talkers at conferences have strong Chinese accents. But I know a good researcher personally and it isn't so apparent to me if these are Chinese Chinese people or Americans of recent Chinese descent.
You might find this paper from the Hoover Institution interesting, it w goes into some depth analyzing the implications of DeepSeek on US innovation: https://www.hoover.org/sites/default/files/research/docs/Zeg...
Similarly, withholding funding for research, meddling in how universities are supposed to conduct their affairs, the reduced appeal of studying in the US for foreign students, putting wrestling promoter Linda McMahon in charge of dept of Education… these are all going to impact America’s research and innovation abilities.
That said, Deepseek is a decent model and was the forcing function needed to give a reality check to a number of AI Startups (and has had the positive effect of making it easier for startups I've helped incubate make the case for their own domain specific foundation model strategy). It's impact shouldn't be understated.
However, on cost, R1 beats the Western models by miles.
It makes for interesting television.
For that reason, it probably won't stop anytime soon.
(But I use it for actual work, not for chatting with imaginary friends. Maybe you really do need a "frontier model" if you want to monetize imaginary friends. I woun't know or care.)
Western models have been proven to be heavily censored, under the guise of fighting antisemitism for example.
>DeepSeek claimed to have built its base model for about 5% of the estimated cost of GPT-4
"DeepSeek-V3 costs only 2.788M GPU hours for its full training. Assuming the rental price of the H800 GPU is $2 per GPU hour, our total training costs amount to only $5.576M. Note that the aforementioned costs include only the official training of DeepSeek-V3, excluding the costs associated with prior research and ablation experiments on architectures, algorithms, or data." https://arxiv.org/pdf/2412.19437
They don't even claim to have spent $5M (since they own their GPUs instead of renting them by the hour), it's a purely notional figure suitable for an academic paper. But when R1 got released and started generating hype, it was the only dollar figure anyone had to go on, so it got interpreted as more significant than it is.
Typical models are now trained on clusters of roughly 20K GPUs. Even if you get a volume discount you still need cabling, switches, etc…
The minimum entry price to play in the game at this level is about 200-500 million dollars.
Meta spent something like $10B on their AI compute, for comparison.
If you believe that Deepseek was released to undercut US AI value (duh) it makes no sense to take the official line as the absolute truth.
Just trust them bro. Unironically.
[edit] also they seem to be saying r1 is a base model, which it is not. Very sloppy.
They doubled down on it. They did a follow-up claiming that a cyber security researcher from a US-based firm had been called in to investigate suspicious traffic at a US telecom. The investigators claimed to have logs and a bunch of other evidence. The investigators also claimed that Bloomberg was misleading people by focusing on SuperMicro, as they'd reportedly seen to with other manufacturers too.
Discovered by our security team where I work. It's the reason our VMS doesn't have support for Hikivision cameras.
https://www.servethehome.com/dude-dell-hpe-ami-american-mega...
But yeah, saying the chips are everywhere is BS.
The Federal government and some banks hire companies to do supply chain integrity inspection and management. They find bad parts all of the time, especially in the channel.
There’s a pretty obvious reason why they wouldn’t want to talk about a detected case of foreign espionage embedded in servers after publishing.
Also, if China keeps using this type of tech to imprison their own population even more effectively, that’s also good for the US, because no one wants to flee to an even better dystopia.
I see no downside here. Force US to innovate beyond “it costs a lot of money and we conveniently had that upfront” while also undercutting the law makers and people trying to enforce regulatory capture on a new thing like they’ve done on all the old things.
As a person interested in tech and tools and America, I have no issues with Deepseek and Hunyuan and Wan being effectively CCP funded. Keep it up. Accelerate. Push.
like this:
DeepSeek’s founder is threatening US dominance in AI race
