Comment by virgildotcodes
18 hours ago
Seems like the survival strategy for cursor would be to develop their own frontier coding model. Maybe they can leverage the data from their still somewhat significant lead in the space to make a solid effort.
18 hours ago
Seems like the survival strategy for cursor would be to develop their own frontier coding model. Maybe they can leverage the data from their still somewhat significant lead in the space to make a solid effort.
I don’t think that’s a viable strategy. It is very very hard and not many people can do it. Just look at how much Meta is paying to poach the few people in the world capable of training a next gen frontier model.
Why are there actually only a few people in the world able to do this?
The basic concept is out there.
Lots of smart people studying hard to catch up to also be poached. No shortage of those I assume.
Good trainingsdata still seems the most important to me.
(and lots of hardware)
Or does the specific training still involves lots of smart decisions all the time?
And those small or big decisions make all the difference?
The basic concept plus a lot of money spent on compute and training data gets you pretraining. After that to get a really good model there’s a lot more fine-tuning / RL steps that companies are pretty secretive about. That is where the “smart decisions” and knowledge gained by training previous generations of sota models comes in.
We’d probably see more companies training their own models if it was cheaper, for sure. Maybe some of them would do very well. But even having a lot of money to throw at this doesn’t guarantee success, e.g. Meta’s Llama 4 was a big disappointment.
That said, it’s not impossible to catch up to close to state-of-the-art, as Deepseek showed.
Why are there so few people in the world able to run 100m in sub 10s?
The basic concept is out there: run very fast.
Lots of people running every day who could be poached. No shortage of those I assume.
Good running shoes still seem the most important to me.
1 reply →
1. Cost to hire is now prohibitive. You're competing against companies like Meta paying tens of millions for top talent.
2. Cost to train is also prohibitive. Grok data centre has 200,000 H100 Graphics cards. Impossible for a startup to compete with this.
5 replies →
Because it’s not about “who can do it”, it’s about “who can do it the best”.
It’s the difference between running a marathon (impressive) and winning a marathon (here’s a giant sponsorship check).
You need a person that can hit the ground running. Compute for LLM is extremely capital intensive and you’re always racing against time. Missing performance targets can mean life or death of the company.
I'd recommend reading some of the papers on what it takes to actually train a proper foundation model, such as the Llama 3 Herd of Models paper. It is a deeply sophisticated process.
Coding startups also try to fine-tune OSS models to their own ends. But this is also very difficult, and usually just done as a cost optimization, not as a way to get better functionality.
interestingly windsurf have done this (I'm not sure how frontier this model is...but it's their own model) https://windsurf.com/blog/windsurf-wave-9-swe-1 but AFAIK cursor have not.
> to develop their own frontier coding model
Uh, the irony is that this is exactly what Windsurf tried.
Why did they fail?
It's both hard AND expensive.