alt Hacker NewsJust because Anthropic and OpenAI really want there to be an arms race justifying the outsized investment, doesn't mean the optimal play is to build larger, more expensive, models.
The capital infusion the frontier labs have received has gotten to a size where many believe it may not be possible to recoup this investment without some very unrealistic things happening.
I think it's reasonable to not completely drain one's cash reserves trying to stay ahead in a race where participants may very clearly be about to run straight off of a cliff.
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Google doesn't have a good coding model. This is a HUGE problem. They don't need "larger more expensive models", they need a good coding model because it's a competitive advantage.
If the Chinese labs can compete on a shoestring budget with access to much less powerful hardware, Google should be able to compete as well. They're becoming almost irrelevant for agentic coding right now.
Yes, I agree with you that the race all the AI companies are running doesn't make sense, but at the same time, there are rumors that Google has produced newer versions of Pro without releasing them to the public.
Version 3.1 has plenty of room for improvement, yet they don't seem to be giving the attention it deserves or at least communicating accordingly.
All Google has to do is build a model that works good enough for the Gemini app and for Spark. And they have it.
Google paid for 3.5 Pro training. They just didn't release it.
They never gave an official answer as to why, so I'll let you draw your own conclusions.
They did not decide it wasn't worth spending the money to train.
They absolutely spent the money.
And it doesn't have to be either/or. They could make larger, more expensive models, just at a slower cadence.
Sure downside would be not learning from people using your model for coding, if we're on the cusp of huge leaps in self-improvement. But there is a reasonable case for avoiding desperate scramble, especially if other parts of the business can also create value with the compute.