2025-01-29 04:21:26
Re @atroyn Typical user of these apps is more like a price-sensitive student using it for essays than a generic adult doing search-like tasks.
Differentiated output, reasoning traces and *free* matter a lot.
2025-01-28 12:48:03
RT Yishan
I think the Deepseek moment is not really the Sputnik moment, but more like the Google moment.
If anyone was around in ~2004, you'll know what I mean, but more on that later.
I think everyone is over-rotated on this because Deepseek came out of China. Let me try to un-rotate you.
Deepseek could have come out of some lab in the US Midwest. Like say some CS lab couldn't afford the latest nVidia chips and had to use older hardware, but they had a great algo and systems department, and they found a bunch of optimizations and trained a model for a few million dollars and lo, the model is roughly on par with o1. Look everyone, we found a new training method and we optimized a bunch of algorithms!
Everyone is like OH WOW and starts trying the same thing. Great week for AI advancement! No need for US markets to lose a trillion in market cap.
The tech world (and apparently Wall Street) is massively over-rotated on this because it came out of CHINA.
I get it. After everyone has been sensitized over the H1BLM uproar, we are conditioned to think of OMG Immigrants China as some kind of Alien Other. As though the Alien-Other Chinese Researchers are doing something special that's out of reach and now China The Empire is somehow uniquely in possession of Super Efficient AI Power and the US companies can't compete. The subtext of "A New Fearsome Power Now Under The Command of the CCP" is what's driving the current sentiment, and it's not really valid.
Like, no. These are guys basically working on the same problems we are in the US, and not only that, they wrote a paper about it and open-sourced their model! It is not actually some sort of tectonic geopolitical shift, it is just Some Nerds Over There saying "Hey we figured out some cool shit, here's how we did it, maybe you would like to check it out?"
Sputnik showed that the Soviets could do something the US couldn't ("a new fearsome power"). They didn't subsequently publish all the technical details and half the blueprints. They only showed that it could be done.
With Deepseek, if I recall correctly, a lab in Berkeley read their paper and duplicated the claimed results on a small scale within a day.
That's why I say it's like the Google moment in 2004. Google filed its S-1 in 2004, and revealed to the world that they had built the largest supercomputer cluster by using distributed algorithms to network together commodity computers at the best performance-per-dollar point on the cost curve.
This was in contrast to every other tech company, who at that time just bought what were essentially larger and larger mainframes, always at the most expensive leading edge of the cost curve. (To the young people reading this, this will sound incredible to you)
I worked at PayPal at the time, and in order to keep pace with the rising transaction volume, the company was forced to buy bigger and bigger database servers from Oracle. We were totally Oracle's bitch. At one point when we ran into scalability issues, the Oracle reps told us we were their biggest installation so they had no other reference point on how to help us overcome our scalability issues. We literally resorted to flipping random config switches and rebooting it.
(This heavily influenced me when I was a young manager later at Facebook. I deliberately torpedoed an Oracle salesman's pitch to try and get us to switch from open source MySQL databases to an Oracle contract: of course we had scalability problems, but at least when we had them, we could open up the hood and figure out how to fix it ... assuming we had good enough engineers, and we did. When it's closed-source infra, you're at the mercy of the vendor's support engineers)
Back to Google - in their S-1, they described how they were able to leapfrog the scalability limits of mainframes and had been (for years!) running a far more massive networked supercomputer comprised of thousands of commodity machines at the optimal performance-per-dollar price point - i.e. not the more expensive leading edge - all knit together by fault-tolerant distributed algorithms written in-house.
Some time later, Google published their MapReduce and BigTable papers, describing the algorithms they'd used to manage and control this massively more cost-effective and powerful supercomputer.
Deepseek is MUCH more like the Google moment, because Google essentially described what it did and told everyone else how they could do it too. In Google's case, a fair bit of time elapsed between when they revealed to the world what they were doing and when they published a papers showing everyone how to do it. Deepseek, in contrast, published their paper alongside the model release.
Now, I've also written about how I think this is also a demonstration of Deepseek's trajectory, but that's also no different from Google in ~2004 revealing what it was capable of. Competitors will still need to gear up and DO the thing, but they've moved the field forward. But it's not like Sputnik where the Soviets have developed technology unreachable to the US, it's more like Google saying, "Hey, we did this cool thing, here's how we did it."
There is no reason to think nVidia and OAI and Meta and Microsoft and Google et al are dead. Sure, Deepseek is a new and formidable upstart, but doesn't that happen every week in the world of AI? I am sure that Sam and Zuck, backed by the power of Satya, can figure something out. Everyone is going to duplicate this feat in a few months and everything just got cheaper. The only real consequence is that AI utopia/doom is now closer than ever.
====
Bonus: This is also a little similar the Ethereum PoS moment, when AI finally has a counterpoint to the environmentalists who say AI uses so much electricity. We just brought down the cost of inference by 97%!
2025-01-28 12:40:35
Re @GeoffLewisOrg Smart technical teams are already starting to confirm that the techniques and resulting cost savings are real.
2025-01-28 00:06:00
RT Navalism
Nothing will attract people to you as much as your values.
@naval
2025-01-27 21:01:17
RT Haseeb ＞|＜
DeepSeek's new R1 reasoning model is dragging down the NASDAQ. It dropped 6 days ago but it seems Wall Street is only now digesting what it means. I'm no equity analyst, but a few things I've been thinking about.
DeepSeek is a huge deflationary shock to the price of intelligence. R1 is outcompeting OpenAI's O1 model for likely less than 1/20th the cost, and they are doing it with only 32B active parameters (GPT-4 likely used ~220B active parameters according to @SemiAnalysis_). They also fully open sourced all of their models, the distillations, and a comprehensive paper detailing how they did it.
Intelligence is now way cheaper than we thought. This is great for all consumers of AI—meaning you and me.
So why is the NASDAQ tanking? Remember, the NASDAQ is an index of producers, not consumers. The price of oil plummeting is bad news for oil companies, but it's great for those of us who drive. The fact that NVIDIA and all of the hyperscalers are so overrepresented in the NASDAQ these days means the stock market is structurally long the price of intelligence.
So who benefits from this deflationary shock? I think there is one company in particular that is best positioned now.
It's now been more than 2 years since the release of ChatGPT, and it's clear that no lab has that much of an edge. It only takes a few months for Google, OpenAI, Anthropic, and now DeepSeek to copy each other and trade spots on the leaderboard. This is partly because these companies all publish research (researchers want glory) and even for stuff that's unpublished, these organizations leak like sieves. Engineers want to know how things work. It's quite literally the most interesting question in the world: what is intelligence made of? Labs are just not able to hide this without military grade secrecy (and none of the best talent wants to work for the military).
So we're stuck in this status quo. Everyone is trading places at the top of the leaderboard, nobody has a clear long-term edge, and DeepSeek and Meta are intent on open sourcing their models, which causes closed models to continually depreciate. Even with all this AI spend, there don't seem to be any durable moats.
So who does have a structural moat here?
Look at OpenAI. Sora is already behind the state of the art on video (Kling and Veo are racing ahead). Dall-E is OK but no longer best in class. They are now betting hard on Operator, which is their agentic model. Operator is supposed to be able to book flights, order food, do agentic stuff for you. But it has significant problems aside from the coherence of the model itself:
If you are working directly with one of their partners like Instacart, Operator gets full access. But much of the open web appears to be blocking Operator, and that may get exacerbated if the web is crawling with Operator instances. You also have to keep handing control back and forth to log in and out of services, solve Captchas—it's all quite cumbersome and finnicky.
Take Google on the other hand.
Gemini is quietly #1 on @lmarena_ai. They are #1 on image generation with Imagen. They are ahead on video with Veo. They aren't doing anything agentic yet—Google is usually the last mover on the sexier stuff—but once they do, they have a huge structural advantage.
Google's webcrawler bots already have full license to touch everything on the web. They already have access to your Gmail, calendar, they can easily traverse the web and have cached most of it (DeepResearch shows how easy this is for Google), and they also have the crown jewel of untapped data: Youtube. And, of course, they are uniquely positioned to drive agents directly on Androids.
Although Google is spending a ton on compute, and they are still a hyperscaler, Google is net short intelligence. They are a consumer of AI in order to serve their customers. DeepSeek and this intelligence deflation is long term good for Google, as it means their own spend will go down. It's cool to hate on Google these days, but I think Google ends up being the long-term winner here if DeepSeek-R1 spells a secular trend.
That said, don't count out OpenAI. They are still the strongest product company, and they've earned trust from consumers and enterprises for always being 3 months ahead of the rest of the market. They basically invented the entire test-time compute paradigm, and o3 is a real breakthrough which has yet to drop. If intelligence is the most valuable resource in the world, being 3 months ahead of the competition is enough to earn themselves a big premium, and huge enduring trust from their customers.
So yes, the biggest loser here is NVIDIA. If China is a real player (and NVIDIA is not allowed to export to China), and DeepSeek is massively deflating the price of intelligence, and they were able to do all of this on nerfed H800 chips, then NVIDIA is in trouble. You want to be in the game of selling intelligence. NVIDIA is in the game of selling FLOPs. If the ratio of FLOPs to intelligence goes down, down goes NVIDIA stock. So it goes.
And of course, we have to say it: congrats to @deepseek_ai team in wiping out a trillion dollars of equity value from the NASDAQ. That's six OpenAIs in a single day, vaporized.
Not bad. 👍
2025-01-27 16:01:31
Re @bookwormengr 👌. Good posts, keep going.
