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This is highlighting what has happened with all forms of ML. Give a baseline set of folks the same dataset and they will end up with a model that performs about
by JCM9 2y ago
This is highlighting what has happened with all forms of ML. Give a baseline set of folks the same dataset and they will end up with a model that performs about the same. Companies are one-upping each other but it’s very back and forth and just a case of release date. These models will become a complete commodity. The thing that could be proprietary is the data used to train them, which could lead to a sustained better model performance. The barrier to entry here is super high given training costs, but the ML skills are still a commodity.
- bboygravity 2y agoThe dataset could become proprietary you say? In other words: information with copyright on it that was (illegally) used/stolen from billions of people and companies will get copyright on it that will be resold as a set? I don't know...
- realharo 2y agoI think the comment was referring to things like internal company data, or licensed data that is not publicly available, etc. Those things could be a competitive advantage.
- brap 2y agoThis is why I strongly believe Google has the clear advantage. Infinite data, infinite resources , not to mention dozens of verticals (search, Android and Chrome are probably the killer ones)
- yunwal 2y agoGoogle obviously has the advantage here, but it also seems like they’re willing to squander it. The Gemini rollout has basically been clippy 2.0 so far. The Gemini interface in gcloud seems to know nothing about how services work, the chat summaries consistently fail, the search summaries are comically bad. I’m usually not one of these people who wants to “block all the AI stuff” but with google products I do.