Summary of LightOn AI meetup #7: “Not all neural network architectures are created equal, some encode better priors than others”

We just held the 7th (Virtual) LightOn AI Meetup, and it was a blast! For this chapter, we had Adam Gaier, Senior AI Research Scientist at Autodesk Research presenting his work on Weight Agnostic Neural Networks, done while at Google Brain and INRIA. You may check out the slides for this talk while we prepare the video of the meetup for upload. It will be posted soon on the Youtube channel of LightOn, subscribe to get notified, and subscribe to our Meetup to get notified of the next events, there is more cool stuff coming!

Summary of LightOn AI meetup #14: “WeightWatcher: a Diagnostic Tool for Deep Neural Networks”

As compact replacements for fully-fledged optical circuits, and as an alternative to integrated photonics circuits, this novel range of devices is a compelling contender for scalable photonic linear quantum optical computing. Starting from the interfacing of several qubits in its first generation, we plan to increase the circuit size in future iterations, with the aim to rapidly demonstrate a quantum advantage. In this context, a key feature of these devices is the ability to offer low losses, all-to-all circuit connectivity, and easy reconfigurability at any circuit size.

Summary of LightOn AI meetup #13: Efficient Neural Networks Training through Locality Sensitive Hashing

As compact replacements for fully-fledged optical circuits, and as an alternative to integrated photonics circuits, this novel range of devices is a compelling contender for scalable photonic linear quantum optical computing. Starting from the interfacing of several qubits in its first generation, we plan to increase the circuit size in future iterations, with the aim to rapidly demonstrate a quantum advantage. In this context, a key feature of these devices is the ability to offer low losses, all-to-all circuit connectivity, and easy reconfigurability at any circuit size.

LightOn AI Meetup: Rethinking Attention with Performers

Summary of LightOn AI meetup #10: “Rethinking Attention with Performers: Towards New Transformers’ Revolution”

As compact replacements for fully-fledged optical circuits, and as an alternative to integrated photonics circuits, this novel range of devices is a compelling contender for scalable photonic linear quantum optical computing. Starting from the interfacing of several qubits in its first generation, we plan to increase the circuit size in future iterations, with the aim to rapidly demonstrate a quantum advantage. In this context, a key feature of these devices is the ability to offer low losses, all-to-all circuit connectivity, and easy reconfigurability at any circuit size.