Ensuring American leadership in artificial intelligence is critical for U.S. competitiveness.

Robotic arms prepare dishes at a hot pot restaurant in Beijing, capital of China, Dec. 5, 2018. Six of the 11 artificial intelligence (AI) startups that are considered to be unicorns – which means to have a value of one billion U.S. dollars or above – come from China, according to CB Insights, a research firm that tracks venture capital and startups. SenseTime took the top spot with a valuation of 4.5 billion U.S. dollars, followed by Yitu Technology at 2.3 billion U.S. dollars and smaller unicorns 4Paradigm, Horizon Robotics and Momenta. The annual report published by CB Insights compiles a list of 100 of the most promising private companies. The selection is based on several factors, including patent activity, investor profile and market potential.

The U.S. military wants to expand its use of artificial intelligence in warfare, but says it will take care to deploy the technology in accordance with the …

Last night's debate in San Francisco between Project Debater, an artificial intelligence engine based on Watson, and Harish Natarajan, the 2016 …

This year "will require significant change to enable us to achieve our long-term goals and objectives," Kotick told analysts during a Tuesday conference call. "We're making changes to enable our development teams to create better content for our biggest franchises more quickly."

Instead of just accepting all this machine learning hype, why not put it to the test? Magenta Studio lets you experiment with open source machine learning tools, standalone or inside Ableton Live. Magenta provides a pretty graspable way to get started with an field of research that can get a bit murky. By giving you easy access to machine learning models for musical patterns, you can generate and modify rhythms and melodies. The team at Google AI first showed Magenta Studio at Ableton's Loop conference in LA in November, but after some vigorous development, it's a lot more ready for primetime now, both on Mac and Windows. If you're working with Ableton Live, you can use Magenta Studio as a set of devices.

Normalizing flows have been shown to be a powerful class of generative models for continuous random variables, giving both strong performance and the potential for non-autoregressive generation. These benefits are also desired when modeling discrete random variables such as text, but directly applying normalizing flows to discrete sequences poses significant additional challenges. We propose a generative model which jointly learns a normalizing flow-based distribution in the latent space and a stochastic mapping to an observed discrete space. In this setting, we find that it is crucial for the flow-based distribution to be highly multimodal. To capture this property, we propose several normalizing flow architectures to maximize model flexibility. Experiments consider common discrete sequence tasks of character-level language modeling and polyphonic music generation. Our results indicate that an autoregressive flow-based model can match the performance of a comparable autoregressive baseline, and a non-autoregressive flow-based model can improve generation speed with a penalty to performance.

Edward H. Shortliffe Chapter 6 Details of the Revised Therapy Algorithm

Microsoft has released ML.NET 0.10, the preview version of its cross-platform machine learning framework ML.NET.