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Earlier quoted context omitted.
With what precision and recall?
Not that much worse than what you see on imagenet. Most large companies have internal datasets with >100 million images. https://arxiv.org/abs/1610.02357
Earlier quoted context omitted.
With what precision and recall?
Not that much worse than what you see on imagenet. Most large companies have internal datasets with >100 million images. https://arxiv.org/abs/1610.02357
So is this the end of Google captchas asking for where the car/sign/whatever is? Will there be a final battle of AIs, where they will kill each other, and the unfettered access to websites over VPN/tor wins and laughs the last laugh?
This is great! I do wish this were written in something other than Python. What is the carbon footprint of all this computer vision, compute-intensive code still being run billions of times a day in Python? Someone should calculate...
Earlier quoted context omitted.
Not that much worse than what you see on imagenet. Most large companies have internal datasets with >100 million images. https://arxiv.org/abs/1610.02357
In case you didn't realize, the guy you're talking to is the CTO of what some may call a "large company."
Earlier quoted context omitted.
Not that much worse than what you see on imagenet. Most large companies have internal datasets with >100 million images. https://arxiv.org/abs/1610.02357
In case you didn't realize, the guy you're talking to is the CTO of what some may call a "large company."
So is this the end of Google captchas asking for where the car/sign/whatever is? Will there be a final battle of AIs, where they will kill each other, and the unfettered access to websites over VPN/tor wins and laughs the last laugh?
This is great! I do wish this were written in something other than Python. What is the carbon footprint of all this computer vision, compute-intensive code still being run billions of times a day in Python? Someone should calculate...
Earlier quoted context omitted.
Not that much worse than what you see on imagenet. Most large companies have internal datasets with >100 million images. https://arxiv.org/abs/1610.02357
That’s impressive work. Still don’t think we have reached human level for all the categories of things we see in images. But you are correct that my comment about 1k categories is not true for many production systems.
I only linked to the xception paper because it mentions JFT. It's not state of the art for large scale recognition.
I'm happy that tech companies are open sourcing basic research all the time, and thinking a lot about what would have happened if large pharmacy companies did the same thing. I'm just hopeful that with new biotech companies the science behind curing people will get faster as well.