I've seen firsthand attempts at integrating open source in place of it and they all failed. Time is money and it costs premium. Touching the ground running is a huge advantage. That's why cloud services stuck.
I've seen firsthand attempts at integrating open source in place of it and they all failed. Time is money and it costs premium. Touching the ground running is a huge advantage. That's why cloud services stuck.
The same is unfolding with Anthropic. It’s doing important work but everyone is realizing it’s not got a serious edge over anyone else. It’s important but ultimately a boring business. It’s still likely worth a few hundred billion, which is massively impressive for any startup, but trillions is pipe dream.
The thing that makes the frontier labs frontier is mostly access to huge amounts of training data and compute. In the earlier days of AI access to top AI talent was a moat, but that moat is rapidly eroding as more and more people familiarize themselves with the "black magic" of LLMs and training. The success of the Chinese models is evidence of this diffusion of knowledge.
Give me a team of, say, 20 good engineers with a deep knowledge of AI/LLMs and training and give me a billion dollars worth of GPU compute and a huge amount of training data and I'll give you a frontier model.
No moat.