Four short links: 24 July 2018
Data Transfer, Quantum Computing, Optimal Control Theory, and Observability
- Data Transfer Project — Facebook, Google, Microsoft, and Twitter collaborating on a data interchange project. Data Transfer Project (DTP) is a collaboration of organizations committed to building a common framework with open source code that can connect any two online service providers, enabling a seamless, direct, user-initiated portability of data between the two platforms.
- Getting Started with Quantum Computing in Python — In this tutorial, we’ll go through how you can program a simple quantum computer to generate random numbers. (via Hacker News)
- Introduction to Mathematical Optimal Control Theory — lecture notes. In the words of one HN commenter, machine learning and OCT are attempting to solve the same problem: choose the optimal action to take at the current time for a given process. Control theorists normally start out with a model, or a family of potential models that describe the behavior of the process and work from there to determine the optimal action. This is very much an area of applied mathematics, and academics take rigorous approaches, but, in industry, many engineers just use a PID or LQR controller and call it a day, regardless how applicable they are to the actual system theoretically. Meanwhile, the reinforcement learning folk typically work on problems where the models are too complicated to work with computationally or often even to write down, so a more tractable approach is to learn a model and control policy from data.
- Veneur — Stripe’s distributed, fault-tolerant pipeline for observability data.