Chemical transport models (CTMs), which simulate air pollution transport, transformation, and removal, are computationally expensive, largely because of the computational intensity of the chemical mechanisms: systems of coupled differential equations representing atmospheric chemistry. Here we investigate the potential for machine learning to reproduce the behavior of a chemical mechanism, yet with reduced computational expense. We create a 17-layer residual multi-target regression neural network to emulate the Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical mechanism. We train the network to match CBM-Z predictions of changes in concentrations of 77 chemical species after one hour, given a range of chemical and meteorological input conditions, which it is able to do with root-mean-square error (RMSE) of less than 1.97 ppb (median RMSE = 0.02 ppb), while achieving a 250x computational speedup. An additional 17x speedup (total 4250x speedup) is achieved by running the neural network on a graphics-processing unit (GPU). The neural network is able to reproduce the emergent behavior of the chemical system over diurnal cycles using Euler integration, but additional work is needed to constrain the propagation of errors as simulation time progresses.

In this demo paper, we introduce the DARPA D3M program for automatic machine learning (ML) and JPL's MARVIN tool that provides an environment to locate, annotate, and execute machine learning primitives for use in ML pipelines. MARVIN is a web-based application and associated back-end interface written in Python that enables composition of ML pipelines from hundreds of primitives from the world of Scikit-Learn, Keras, DL4J and other widely used libraries. MARVIN allows for the creation of Docker containers that run on Kubernetes clusters within DARPA to provide an execution environment for automated machine learning. MARVIN currently contains over 400 datasets and challenge problems from a wide array of ML domains including routine classification and regression to advanced video/image classification and remote sensing.

Predictions about the billions of dollars that drone technology represents are as pervasive as they are extreme. Drone industry experts are currently tracking over 75 firms that offer drone market reports or forecasts of some type, all of which offer various opinions and numbers around what sort of an impact the technology will enable in industries like construction and agriculture as well as maritime and offshore services. It's easy and in some cases justified to get excited about the potential of the technology, but many of these predictions are based on how the drones might be utilized, as opposed to the difference they're actually making. It's why figuring out the ROI of UAVs is a key consideration when it comes to adoption, and it's why the current applications of drones in maritime and offshore services are so important to consider. The use cases of today are what will make some of those billion dollar predictions possible, and makes it essential to see these uses explored in depth and detail at industry events.

BigDog has four legs that are articulated like an animal's, with compliant elements to absorb shock and recycle energy from one step to the next. BigDog is the size of a large dog or small mule. BigDog's on-board computer controls locomotion, processes sensors, and handles communications with the user. BigDog's control system keeps it balanced, manages locomotion on a wide variety of terrain, and does navigation. Sensors for locomotion include joint position, joint force, ground contact, ground load, a gyroscope, LIDAR, and a stereo vision system.

Chinese artificial-intelligence startup CloudWalk Technology signed a deal in March with the Zimbabwean government, providing the authoritarian regime an advanced facial-recognition system that it can use to identify, track, and monitor citizens. In exchange, CloudWalk gains access to the facial data of the demographically distinct country, which provides the company much-needed data for improving its recognition algorithms. Arrangements such as this are common under China's Artificial Intelligence (AI) strategy, whereby Chinese private and state-controlled companies take advantage of the weak legal systems and low privacy standards of developing nations as part of the country's effort to become a world leader in artificial intelligence by 2030. But the vision of artificial intelligence that China is creating is a thoroughly illiberal one. Constant surveillance of citizens is powering initiatives such as the Social Credit System, which will rate citizens on their social and economic performance, increasing the power of the state to enforce its cultural vision.

U.S. Defense Advanced Research Projects Agency researchers have created the first forensic tools for detecting deepfake videos. U.S. Defense Advanced Research Projects Agency (DARPA) researchers say they have created the first forensic tools for catching fake videos, known as "deepfakes," created with artificial intelligence (AI). The team says the most common technique for generating deepfakes involves using machine learning to graft one person's face onto another person's body. Matthew Turek, who leads DARPA's Media Forensics program, says his team discovered subtle cues in current images and videos manipulated by generative adversarial networks, which allowed them to detect alteration. For example, the researchers realized that faces in deepfakes rarely blink, and when they do, the eye movement is unnatural.

The United States enjoys a long track record of dominating conventional military operations, driven in large part by our technological superiority -- the nation's ability to develop new capabilities and rapidly integrate them into military operations. However, continued dominance is not assured. Whereas in the past the military funded most major technology breakthroughs and thus could prevent potential adversaries' access, today commercial entities lead the development of cutting-edge technology, providing rivals with the opportunity to obtain and rapidly operationalize advanced capabilities, weakening America's traditional advantages. To protect the U.S. military's technological edge, government, industry and academia must work together to develop and operationalize artificial intelligence, the technology most likely to drive outcomes on future battlefields. The 2018 National Defense Strategy places a strong focus on AI as an emerging technology that will change society and ultimately the character of war.

Based in part on data from the U.S. Census Bureau, Apple has been able to tune Siri to better understand users based on where they are and what POIs they're more likely to ask about. Apple says machine learning on its own has helped improve automatic speech recognition for general language over the years, but "recognizing named entities, like small local businesses" has proved a performance bottleneck. We decided to improve Siri's ability to recognize names of local POIs by incorporating knowledge of the user's location into our speech recognition system. That's done partly by relying on data collected by the U.S. Census Bureau: We define geo regions based on the combined statistical areas (CSAs) [1] from U.S. Census Bureau. The CSAs consist of adjacent metropolitan areas that are economically and socially linked, as measured by commuting patterns.

This weekend, the Perseid meteor shower will light up the moonless sky, the product of dust breaking off from the same Swift-Tuttle comet that sends its greetings to Earth every August. The richest display of meteors will appear between August 11 and 13. But as you settle down to watch those fragments burn up into nothingness as they hit the Earth's atmosphere, something else will also be watching: NASA's all-sky meteor camera network. Every night, 17 video cameras scattered across the United States scan the skies for meteors. Each one sits in a sturdy white cylindrical tube for protection, sealed off by a clear dome lens that gives a clear view in all directions.

Before video games with swastikas and other Nazi symbols can be released in Germany, they have to go through some major edits to censor those images. Every Nazi eagle and swastika -- and even Adolf Hitler's moustache -- in the Wolfenstein series had to be scrubbed, for instance, even though Nazis are the villains in the game. That will no longer be the case going forward, now that German authorities have lifted the blanket ban on Nazi imagery in video games. Each title will now be assessed on a case-by-case basis by the country's Entertainment Software Self-Regulation Body (USK) and will be judged similarly to books and films. When a game is submitted to the USK for an age rating, the regulatory body will determine if it satisfies the "social adequacy clause" in section 86 of the German Criminal Code.