Guillaume Verdon

correlations that are very quantum but which systems are still relevant to industry, that's a big question. People are leaning towards chemistry, nuclear physics. I've worked on actually processing inputs from quantum sensors. If you have a network of quantum sensors, they've captured a quantum mechanical image of the world.

correlations that are very quantum but which systems are still relevant to industry, that's a big question. People are leaning towards chemistry, nuclear physics. I've worked on actually processing inputs from quantum sensors. If you have a network of quantum sensors, they've captured a quantum mechanical image of the world.

and how to post-process that that becomes a sort of quantum form of machine perception. For example, Fermilab has a project exploring detecting dark matter with these quantum sensors. To me, that's in alignment with my quest to understand the universe ever since I was a child, and so someday I hope that

and how to post-process that that becomes a sort of quantum form of machine perception. For example, Fermilab has a project exploring detecting dark matter with these quantum sensors. To me, that's in alignment with my quest to understand the universe ever since I was a child, and so someday I hope that

and how to post-process that that becomes a sort of quantum form of machine perception. For example, Fermilab has a project exploring detecting dark matter with these quantum sensors. To me, that's in alignment with my quest to understand the universe ever since I was a child, and so someday I hope that

We can have very large networks of quantum sensors that help us peer into the earliest parts of the universe. For example, the LIGO is a quantum sensor. It's just a very large one. So yeah, I would say quantum machine perception simulations, grokking quantum simulations, similar to AlphaFold. AlphaFold understood the probability distribution over configurations of proteins. You can understand

We can have very large networks of quantum sensors that help us peer into the earliest parts of the universe. For example, the LIGO is a quantum sensor. It's just a very large one. So yeah, I would say quantum machine perception simulations, grokking quantum simulations, similar to AlphaFold. AlphaFold understood the probability distribution over configurations of proteins. You can understand

We can have very large networks of quantum sensors that help us peer into the earliest parts of the universe. For example, the LIGO is a quantum sensor. It's just a very large one. So yeah, I would say quantum machine perception simulations, grokking quantum simulations, similar to AlphaFold. AlphaFold understood the probability distribution over configurations of proteins. You can understand

quantum distributions over configurations of electrons more efficiently with quantum machine learning.

quantum distributions over configurations of electrons more efficiently with quantum machine learning.

quantum distributions over configurations of electrons more efficiently with 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. And 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.

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. And 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.

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. And 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.

And so the trick there was to do a feed-forward operation and do what we call a phase kick, but really it's just the 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, right? Which is pretty funky.

And so the trick there was to do a feed-forward operation and do what we call a phase kick, but really it's just the 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, right? Which is pretty funky.

And so the trick there was to do a feed-forward operation and do what we call a phase kick, but really it's just the 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, right? Which is pretty funky.

Now you're not just... You don't have just a point for parameters. You have a superposition over many potential parameters, right? And our goal is to... Is using phase kicks somehow? Right. To adjust parameters? Because phase kicks emulate... having the parameter space be like a particle in n dimensions and you're trying to get the Schrodinger equation

Now you're not just... You don't have just a point for parameters. You have a superposition over many potential parameters, right? And our goal is to... Is using phase kicks somehow? Right. To adjust parameters? Because phase kicks emulate... having the parameter space be like a particle in n dimensions and you're trying to get the Schrodinger equation

Now you're not just... You don't have just a point for parameters. You have a superposition over many potential parameters, right? And our goal is to... Is using phase kicks somehow? Right. To adjust parameters? Because phase kicks emulate... having the parameter space be like a particle in n dimensions and you're trying to get the Schrodinger equation