MIT Invented a Tool That Allows Driverless Cars to Navigate Rural Roads Without a Map

16-year-old on finding primes with neural networks

Inspired by the triumphs of the “AlphaGo” project by DeepMind, I focused my research into the extensions and optimisation techniques that are so common in neural network design. There are many useful packages in machine learning, such as tensor flow, which can generate complex neural networks which work well, very quickly, but for this project I really wanted to develop an understanding of the inner workings of modern neural networks. So I went through the arduous calculus myself giving a much less efficient but more rewarding program.

Announcing PyTorch 1.0 for both research and production

PyTorch 1.0 takes the modular, production-oriented capabilities from Caffe2 and ONNX and combines them with PyTorch’s existing flexible, research-focused design to provide a fast, seamless path from research prototyping to production deployment for a broad range of AI projects. With PyTorch 1.0, AI developers can both experiment rapidly and optimize performance through a hybrid front end that seamlessly transitions between imperative and declarative execution modes. The technology in PyTorch 1.0 has already powered many Facebook products and services at scale, including performing 6 billion text translations per day.

Facial recognition tech wrongly identified 2,000 people as potential criminals