This place just starts feeling extremely uncomfortable. We had a good run, but I’ll check out for now. You can still find me at mastodon (see my bio). So long #QuantumTwitter
"The adjoint method on Braket runs up to 1000 times faster than parameter-shift, even when the latter is accelerated with batching."
PennyLane + Braket = ❤️
PennyLane seamlessly integrates with Amazon Braket @awscloud - and now runs even faster 🏃
In a guest blog by @kslimes and Daniela Becker, learn how the adjoint differentiation method on the SV1 simulator leads to faster training of large circuits 👇
pennylane.ai/blog/2022/12/c…
Excited to announce Braket.jl, an experimental #julialang SDK for Amazon Braket, where you can build, test, and run #quantum computing experiments in Julia, using quantum computers and simulators on Amazon Braket. Check it our full blog post at forem.julialang.org/kshyatt/introd…!
