> We are at least 1 year and at most 2 years until they surpass closed models for everyday tasks that can be done locally to save spending on tokens.
replyUntil they pass what closed models today can do.
By that time, closed models will be 4 years ahead.
Google would not be giving this away if they believed local open models could win.
Google is doing this to slow down Anthropic, OpenAI, and the Chinese, knowing that in the fullness of time they can be the leader. They'll stop being so generous once the dust settles.
If they pass what closed models today can do by much, they'll be "good enough" for what I want to do with them. I imagine that's true for many people.
replyI think it will be less of a local versus cloud situation, but rather one where both complement each other. The next step will undoubtedly be for local LLMs to be fast and intelligent enough to allow for vocal conversation. A low-latency model will then run locally, enabling smoother conversations, while batch jobs in the cloud handle the more complex tasks.
replyGoogle, at least, is likely interested in such a scenario, given their broad smartphone market. And if their local Gemma/Gemini-nano LLMs perform better with Gemini in the cloud, that would naturally be a significant advantage.
But at that point, won’t there be very few tasks left where the average user can discern the difference in quality for most tasks?
replyI mean, correct, but running open models locally will still massively drop your costs even if you still need to interface with large paid for models. Google will still make less money than if they were the only model that existed at the end of the day.
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