I Know We're in an AI Bubble Because Nobody Wants Me

Summary

I first got into deep learning in 2012, when AlexNet came out. I was CTO of Jetpac, a startup that aimed to provide information about bars, hotels, and restaurants by analyzing public photos, for example finding hipster (and Turk) friendly cafes. The results from the paper were so astonishing I knew AlexNet would be incredibly helpful, so I spent my Christmas holidays heating our house using a gaming rig with two GPUs and the CudaConvNet software, since that was the only way to train my own version of the model. The results were even better than I’d hoped, but then I faced the problem of how to apply the model across the billions of photos we’d collected. The only GPU instances on Amazon were designed for video streaming and were prohibitively expensive. The CPU support in the Caffe framework was promising, but it was focused on training models, not running them after they’d been trained (aka inference). What I needed was software that would let me run the model at a massive scale on low-cost hardware. That was the original reason I wrote the Jetpac framework, so I could spin up hundreds of cheap EC2 instances to process our huge backlog of images for tens of thousands of dollars instead of millions. It turned out that the code was small and fast enough to even run on phones, and after Jetpac was acquired by Google I continued in that direction by leading the mobile support for TensorFlow. While I love edge devices, and that’s what I’m known for these days, my real passion is for efficiency. I learned to code in the 80’s demo scene, went on to write PC game engines professionally in the 90’s, and I got addicted to the dopamine rush of optimizing inner loops. There’s nothing quite like having hard constraints, clear requirements, and days to spend solving the puzzle of how to squeeze just a little bit more speed out of a system. If you’re not a programmer, it might to difficult to imagine what an emotional process optimizing can be. There’s no guarantee that it’s eve...