Guillaume Verdon: belief

Transcript context

…You co-authored a paper titled A Universal Training Algorithm for Quantum Deep Learning. That involves Baqprop, with a Q. Very well done, sir. Very well done. How does it work? Is there some interesting aspects you can just mention on how Baqprop and some of these things we know for classical machine learning transfer over to the quantum machine learning? Yeah. That was a funky paper. That was one of my first papers in quantum deep learning. Everybody was saying, “Oh, I think deep learning is going to be sped up by quantum computers. ” I was like, ” Well, the best way to predict the future is to invent it. So, here’s a 100-page paper, have fun.” Essentially, quantum computing is usually, you embed reversible operations into a quantum computation. The trick there was to do a feedforward operation and do what we call a phase kick. But really, it’s just a force kick. You just kick the system with a certain force that is proportional to your loss function that you wish to optimize. And then, by performing uncomputation, you start with a superposition over parameters, which is pretty funky. Now, you don’t have just a point for parameters, you have a superposition over many potential parameters. Our goal is- Is using phase kick somehow to adjust the parameters?…

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