I spend a lot of time thinking about what has to happen for better models to become better software. The research progress is remarkable, but there’s still a lot of work between a model gaining a capability and someone being able to depend on it.
That work is interesting in its own right. Understanding a codebase, fitting into how a team operates, knowing when a result is wrong, making something reliable enough that people can stop checking every step. Better models help with all of this, but someone still has to take responsibility for the whole system.
It is now clear that it’s nothing short of critical that some of the companies doing that work are model-independent. Different models are useful for different things, and those tradeoffs keep changing. We should be able to choose based on what works for a customer, and change our minds when the evidence changes. Customers shouldn’t have to make a long-term bet on a research lab to improve how they build software. We shouldn’t have to trust the creator of the model to do what’s best for their customers. We should force them to in order to compete.
There’s a business model question here too. If we find a way to do the same work reliably with less inference, that should be a good thing for both us and the customer. If another lab makes a breakthrough, we should be excited to put it to use. Independence doesn’t automatically create that alignment, but it gives us more room to build around it.
I’m interested in where intelligence research goes. I just don’t think every AI company needs reaching AGI to be its organizing purpose. Helping people build things they couldn’t build before is a substantial goal on its own, with useful measures of progress along the way.
That’s how I think about Factory, and what makes today’s funding meaningful to me. More room to work on these problems, with our attention on the people using the software.
