In the next few years we will have hardware with tens or maybe hundreds of qubits which can be used to explore quantum algorithms. I will discuss ideas for what algorithms to run on these pre-error corrected devices. In particular I will focus on the Quantum Approximate Optimization Algorithm and setups for Quantum Machine Learning. I will advocate trying things on quantum devices without proof in advance that they will ultimately outperform classical algorithms.

*Please note that due to a technical problem, while you can hear the talk and see the lecture slides, you will not be able to see the speaker due to the inaccurate camera angle.