@fnord "one of the most innovative companies in the world" -- brilliant. At the current discount that sounds like a wonderful opportunity -- innovation will drive future returns. I hope you are fully invested, with leverage.
Francois Chollet
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@guyreading From first principles, this seems highly unlikely. This is circumstantially confirmed by the fact that, when translating ARC problems to sequences, the largest LLMs out there (not just GPT-3, but much larger ones as well) don't work at all.
What's the highest score you can do on CIFAR10 with no data augmentation and no external data?
I was happy that it was this easy to do. I didn't even have to make it a Model or a Layer (though I did make it a layer for a separate reason -- to make sure a subclassed layer could own a FeatureSpace and have it tracked for later saving)
I'm adding serialization & saving support to the new FeatureSpace structure data processing utility: https://github.com/keras-team/keras/pull/17355/files
@Fabio IMO you'd get better results for this use case by googling your keywords and reading random paragraphs from the first few articles that show up
Essay writing is about clarity of thought. You achieve clarity of thought by using fewer words, not by generating more.
It's hard to beat a plain SGD optimizer that has a finely tuned learning rate schedule.
Combination of heartbreak and morbid fascination, like watching a bus full of orphans undergo a slow-motion crash