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You are getting ridiculous now. Training this on "Taobao product photos" will lead to a useless model that is unable to produce practically all of the "cool" de
by trention 4y ago
You are getting ridiculous now. Training this on "Taobao product photos" will lead to a useless model that is unable to produce practically all of the "cool" demos posted here in the last week.
- angusturner 4y agoA few months ago this task was virtually impossible. Then it was possible, but extremely expensive and pay-walled behind the "Open"AI' website. As of about a week ago this tech runs on consumer GPUs. The weights have been downloaded 100s of thousands of times, and fine-tuning / modifying is possible. Training from scratch is about $500k still, but it will only get cheaper and easier.
- trention 4y agoThis doesn't contradict anything I have written. The average technical user will be unable to train this exact model (not to mention the supposed future more powerful ones) in their basement in this decade.
- angusturner 4y agoThat just feels like such a pessimistic forecast to me. Of course, the current trajectory of improvements in model efficiency and better commercial GPUs / ML-accelerators may hit a wall. But I would not be surprised if this was trainable on a commercial GPU at home within that time. But I think another important trend that we are seeing is that you don't need to train these models from scratch. Open-source "foundation models" means that you can usually get away with the much easier task of fine-tuning, as to not throw away / re-learn everything that these large models have already fit. Edit: I initially said 2-5 years, but on more reflection this does seem optimistic (for training from scratch).