If if it were true, who cares? Most startups fail. Most are terrible ideas and/or terribly executed. I fail to see why it's a useful metric.
If if it were true, who cares? Most startups fail. Most are terrible ideas and/or terribly executed. I fail to see why it's a useful metric.
Is your point that startups fail so we should disregard the central thesis that locked down AI will eventually lost to open models?
I don't see that anywhere in the parent's comment. Where did you get all that?
Not op but that makes perfect sense to me.
"People with mostly bad ideas/execution use Chinese models." Is the point being made.
If you slice it to some measure of success, is the statement "Successful start-ups/companies use Chinese models." still true?
Hmm if you assume the 80% is uniformly distributed between successful and unsuccessful startups/companies, which by default you should, then yeah, your proposed statement is true.
Data would be needed to argue the 80% skews unsuccessful
How does this comparison sound if we use cloud provider?
The Ai is writing code, not executing a startup. The code was never the hard part of startups
Deciding to use open models over closed models is a business decision.
Using the cheaper model is also a business decision. We don't know why they are using the Chinese models: openness or money or both or a third one?
Third options include
- fine-tuning
- running in your environment
The point is that for many tasks today, and likely all tasks before long, that the open vs closed will not be a differentiator. There are many open models much better than gemini, yet people still use gemini.
It's like picking AWS vs GCP. Yes it is a business decision, but one that will not likely affect the outcome of the business.
> but one that will not likely affect the outcome of the business.
We don't know that, that's the point of my statement about changing the question.
Do successful companies opt for the US/Closed models? If they do or don't it's just a correlation but it means something. Maybe it's just causal of companies being able to get more funding because the ideas are better so they opt for the more expensive model (assuming it's better).
we know that
1. Different people using Ai have different outcomes
2. There is much more to agents than the model
3. Companies are not successful because of the code, look at how many shitty products we endure
Can you explain the basis for your insistence that models matter?
Can you name another technology that determines success/failure rates?
> Can you explain the basis for your insistence that models matter?
It's not my insistence that they matter, it's my insistence that How many companies use which model isn't a measure of success. My insistence is that a better measure to determine _if_ models matter, is to ask which models successful companies use. It's not a perfect measure, as I mentioned, it would simply be a correlation but a causal link doesn't exist with out a corollary one.
> Can you name another technology that determines success/failure rates?
I'm not sure what you're getting at with this question but of course. Electricity, machines, computers, etc.
Speaking of electricity and, as an example, you could run a similar thought experiment with companies who chose to use AC or DC power when that was a thing that needed to be chosen between. It turned out, there were niches where each made sense. So the actual question here is probably less about is open/closed better but rather which situations are better for which model. Obviously you can't fine tune a closed model so if you need to do that, your options are limited.