Maybe the best outcome of a competitive Grok is breaking the mindshare stranglehold that ChatGPT has on the public at large and with HN. There are many good frontier models that are all very close in capabilities.
Debut in the sense that it’s something good enough that it’s getting mainstream attention.
Unfortunately LLMs are shifting compute time to test time instead of train time. I don't really like this and frankly it shows a stalling of the architectures, data sets, etc...
Naively, I feel to be useful, the goal of LLMs should be to more power efficient. So that eventually all devices can be smarter.
Power efficiency can be gained through less time-time, or more "intelligence" or some combination of the two. I'm not convinced these SOTA models are doing much more than increasing test-time.