Many machine learning applications require extensive preprocessing on the data for state-of-the-art performance. A large number of preprocessing procedures have to be fused with a learner to create a wrapped learner, which assures that the same preprocessing is used in training and prediction. This creates a preprocessing chain which can be added to any learner with a single command to construct a configurable pipeline. The R programming language already offers a general purpose package for piping function output to new functions, magrittr. This is heavily utilized by the package dplyr for data manipulation, but mostly consists of basic low level functionality, e.g., mutation, aggregation, selection, filtering etc.

We are entering the era of talking machines--and it's about more than just asking Amazon's Alexa to turn down the music. General Electric has built a digital assistant into its cloud service for managing power plants, jet engines, locomotives, and the other heavy equipment it builds. Over the internet, an engineer can ask a machine--even one hundreds of miles away--how it's doing and what it needs. Fast Company got an exclusive demonstration of the technology before its debut at GE's Minds Machines conference in San Francisco. Voice controls are built on top of GE's Digital Twin program, which uses sensor readings from machinery to create virtual models in cyberspace.

Whether you want to start an artificial intelligence company as an entrepreneur, evaluate AI-driven vendors as an enterprise client, or simply learn more about new technology breakthroughs, you'll need to understand how successful investors think. Through funding, advisory, connections, and operational support, investors enable innovative companies to grow and drive overall industry trends. That's why we spoke with dozens of venture capitalists who've made recent investments in artificial intelligence companies. To help you understand how different investors approach AI, we compiled 15 unique and varied opinions that exemplify the diversity of opportunities for artificial intelligence to change our world. Max Gazor of CRV believes AI will be most disruptive to industries where there's "too much data for humans to process, a severe shortage of expert talent, and a high willingness to pay for even small productivity boosts." Cybersecurity fits these criteria perfectly.

The second robot Tokyo Electric Power Company (TEPCO) sent into Fukushima's unit 2 reactor also failed to finish its mission. Now, it's the machine's left crawler belt that stopped working (PDF) altogether, forcing TEPCO to cut off its tether and to leave it inside. Toshiba designed these scorpions specifically to examine Unit 2's condition and to locate the melted uranium fuel within. The information would help Tepco figure out the best and safest way to clean the fuel up. The power company still isn't sure whether the robot's crawler belt stopped working due to the radiation levels inside or due to all the debris the first machine wasn't able to clear.

In the last several years, interest in artificial intelligence (AI) has surged. Venture capital investments in companies developing and commercializing AI-related products and technology have exceeded $2 billion since 2011.1 Technology companies have invested billions more acquiring AI startups. Press coverage of the topic has been breathless, fueled by the huge investments and by pundits asserting that computers are starting to kill jobs, will soon be smarter than people, and could threaten the survival of humankind. IBM has committed $1 billion to commercializing Watson, its cognitive computing platform.2 Google has made major investments in AI in recent years, including acquiring eight robotics companies and a machine-learning company.3 Facebook hired AI luminary Yann LeCun to create an AI laboratory with the goal of bringing major advances in the field.4 Amid all the hype, there is significant commercial activity underway in the area of AI that is affecting or will likely soon affect organizations in every sector.

The Global Scientific Information and Computing Center at the Tokyo Institute of Technology has been at the forefront of accelerated computing, and well before GPUs came along and made acceleration not only cool but affordable and normal. But its latest system, Tsubame 3.0, being installed later this year, the Japanese supercomputing center is going to lay the hardware foundation for a new kind of HPC application that brings together simulation and modeling and machine learning workloads. The hot new idea in HPC circles is not just being able to run machine learning workloads side by side with simulations, but to use machine learning to further accelerate the simulation, and we have a future feature story underway, based on conversations with researchers at TiTech and at Oak Ridge National Laboratory, where the "Summit" hybrid CPU-GPU system is being built for the US Department of Energy, about this very topic. Suffice it to say, the idea is to integrate machine learning into the simulation, to do some of the computationally intensive stuff in a new way. So, as part of a climate model, you teach the system using machine learning to predict the weather by watching movies of the weather, or in astronomy, you use machine learning to remove the noise from the signal to find the interesting bits of a star field.

The world's first rotating skyscraper is set to be built in Dubai by 2020. The Dynamic Tower Hotel has been planned since 2008, having been proposed by Israeli-Italian architect David Fisher. It will stand at 1,375 feet tall, with each of its 80 storeys capable of rotating individually around a concrete core, offering 360-degree views of Dubai. Residents will be able to control rotation speeds and stop their apartment from spinning with voice commands. The skyscraper is expected to be completely self-powered, reportedly featuring as many as 79 horizontal-lying wind turbines between floors, as well as roof-mounted solar panels.

The latest robot attempting to find the 600 tons of nuclear fuel and debris that melted down six year ago in the wrecked Fukushima No. 1 nuclear power plant met its end in less than a day. The scorpion-shape machine, built by Toshiba Corp., entered the No. 2 reactor core Thursday and stopped 3 meters (10 feet) short of a grate that would have provided a view of where fuel residue is suspected to have gathered. Two previous robots aborted similar missions after one got stuck in a gap and another was abandoned after finding no fuel during six days of searching. After spending most of the time since the 2011 disaster containing radiation and limiting ground water contamination, scientists still don't have all the information they need for a cleanup that the government estimates will take four decades and cost ¥8 trillion. It is not yet known if the fuel melted into or through the containment vessel's concrete floor, and determining the fuel's radioactivity and location is crucial to inventing the technology needed to remove it.

A'scorpion' robot sent into a Japanese nuclear reactor to learn about the damage suffered in a tsunami-induced meltdown had its mission aborted after the probe ran into trouble, Tokyo Electric Power company said Thursday. TEPCO, the operator of the Fukushima nuclear plant, sent the remote-controlled device into the No. 2 reactor where radiation levels have recently hit record highs. The'scorpion' robot, so-called because it can lift up its camera-mounted tail to achieve better viewing angles, is also designed to crawl over rubble inside the damaged facility. The'scorpion' robot is designed to withstand up to 1,000 sieverts of radiation - but had its mission aborted after the probe ran into trouble, Tokyo Electric Power company said After a manually operated camera probed the deepest point yet within the reactor earlier this month, Tokyo Electric Power Co (TEPCO) estimate that radiation levels inside the plant's No. 2 reactor have hit 530 sieverts per hour. Radiation exposure at 530 sieverts per hour would effectively shut down TEPCO's planned robot camera probe in under two hours.

A renewed attempt to survey reactor 2 at the damaged Fukushima No. 1 nuclear power plant failed Thursday when the latest robot probe became obstructed. The robot was inserted into the primary containment vessel at around 7:50 a.m. to approach the metal grating directly underneath the pressure vessel, where a black mass has been found. Tokyo Electric Power Company Holdings Inc. had hoped to take a closer look at what could be melted nuclear fuel, but it was forced to abandon the operation shortly after 3 p.m. The robot didn't reach its objective, Tepco said, and the utility eventually severed its controller cable. Having detected an extraordinarily high radiation level --estimated at 650 sieverts per hour -- in a preparatory survey, Tepco had hoped to obtain more precise readings, images and data needed to remove fuel and other debris to decommission the plant.