With the advent of drones, robots and self-driving vehicles a recent report released by the White House contended that artificial intelligence could transform the economy. The report lists strategies that will increase the benefits and diminish the costs of AI, helping to create opportunities in cyberdefense and fraud detection. Although the report clearly states that the precise economic impact is difficult to estimate, it highlights five possible effects of an economy driven by AI, including an increased demand for higher technical skills and uneven distribution of the impact across sectors, wage levels, etc. A depiction of AI has often been seen on television shows. In 1962, I sing the Body Electric, an episode of The Twilight Zone, significantly captured the unique concept of AI by presenting a robotic grandmother adjusting smoothly in a human family.

It can read lips and create new food recipes. It can win at chess, Jeopardy and the game Go. Every major technology company appears to be integrating it into how they organize and operate their business. And it seems like just about every new app in existence claims its software uses some sort of machine learning to make life even better. Artificial intelligence is splashed across headlines like never before.

Early on an unusually blustery day in June, Kevin Esvelt climbed aboard a ferry at Woods Hole, bound for Nantucket Island. Esvelt, an assistant professor of biological engineering at the Massachusetts Institute of Technology, was on his way to present to local health officials a plan for ridding the island of one of its most persistent problems: Lyme disease. He had been up for much of the night working on his slides, and the fatigue showed. He had misaligned the buttons on his gray pin-striped shirt, and the rings around his deep-blue eyes made him look like a sandy-haired raccoon. Esvelt, who is thirty-four, directs the "sculpting evolution" group at M.I.T., where he and his colleagues are attempting to design molecular tools capable of fundamentally altering the natural world. If the residents of Nantucket agree, Esvelt intends to use those tools to rewrite the DNA of white-footed mice to make them immune to the bacteria that cause Lyme and other tick-borne diseases. He and his team would breed the mice in the laboratory and then, as an initial experiment, release them on an uninhabited island. If the number of infected ticks begins to plummet, he would seek permission to repeat the process on Nantucket and on nearby Martha's Vineyard. More than a quarter of Nantucket's residents have been infected with Lyme, which has become one of the most rapidly spreading diseases in the United States. The illness is often accompanied by a red bull's-eye rash, along with fever and chills. When the disease is caught early enough, it can be cured in most cases with a single course of antibiotics. For many people, though, pain and neurological symptoms can persist for years. In communities throughout the Northeast, the fear of ticks has changed the nature of summer itself--few parents these days would permit a child to run barefoot through the grass or wander blithely into the woods. "What if we could wave our hands and make this problem go away?" Esvelt asked the two dozen officials and members of the public who had assembled at the island's police station for his presentation. He explained that white-footed mice are the principal reservoir of Lyme disease, which they pass, through ticks, to humans.

One of the most important things that the U.S. can do to improve economic growth is to invest in artificial intelligence, or A.I., said the White House, in a new report. A.I.-driven, intelligent systems have the potential to displace millions, such as truck drivers, from their jobs. But potential negative impacts can be offset by investments in education as well as by ensuring there is a safety net to help affected people, the White House argued, in what will likely be the Obama administration's final report on technology policy. Some of the report's recommendations, which include expanded unemployment help and access to healthcare, may be anathema to a Republican-controlled Congress with a focus on tax reductions and spending cuts. But this report -- "Artificial Intelligence, Automation, and the Economy" (PDF) -- which was in the works well before election day, also describes broader, technological-driven changes that will impact jobs and may pose issues for President-elect Donald Trump.

Welcome to California Inc., the weekly newsletter of the L.A. Times Business Section. Many of us are off this week and hitting the road. Happily, the average price of self-serve regular gas in the Los Angeles-Long Beach area is at the lowest level in eight years. Pump prices in the region are down nearly $2 a gallon from the all-time highs reached in October 2012, when refinery outages and heightened fears of lower supplies in California sent prices soaring. Changes at the top: At least eight companies will be getting new chief executives this coming weekend.

After three years of almost single-handedly juicing up the slow-growing economy, Janet L. Yellen and the Federal Reserve should be looking at easier days ahead. Yellen, in what will probably be her last full year as Fed chair, may finally get help from somewhere else in Washington. Tax cuts and infrastructure spending planned by President-elect Donald Trump, if backed by the Republican-controlled Congress, would lighten the load for a Fed whose easy-money policies have been the primary economic support for the nation. She is already breathing easier on the Fed's employment mandate; the jobless rate has fallen to a nine-year low of 4.6%. Inflation, too, is under control and, by all accounts, creeping toward the central bank's optimal level of 2%.

NASA is set to launch the robotic portion of its Asteroid Redirect Mission (ARM) in 2021. This will be the first mission to visit and collect a multi-ton sample from a large near-Earth asteroid. The collected sample will be used in a demonstration of enhanced gravity tractor asteroid deflection. Recently at the Robotic Operation's Center of NASA's Goddard Space Flight Center in Greenbelt, Maryland, a robotic capture module system prototype used a mock asteroid boulder to test its capabilities. NASA, along with students from West Virginia University, created the mock asteroid boulder from rock, styrofoam, plywood and an interior aluminum frame.

Google wants to apply its machine learning technology to NHS patient data within the next five years, TechCrunch reports. The search giant's London-based artificial intelligence research lab, DeepMind, announced a partnership with the Royal Free NHS Trust in London in February but the full extent of the arrangement is only just becoming clear. A Memorandum of Understanding (MoU) between DeepMind and the Royal Free shows that the pair envisage a "broad ranging, mutually beneficial partnership, engaging in high levels of collaborative activity and maximizing the potential to work on genuinely innovative and transformational projects." The MoU -- obtained via a Freedom of Information (FoI) request from New Scientist -- states that DeepMind hopes to gain access to "data for machine learning research under appropriate regulatory and ethical approvals" within the next five years. Machine learning -- a subfield of computer science that gives computers the ability to learn without being explicitly programmed -- has the potential to speed up patient diagnosis and optimise their treatments.

As financial companies have begun employing automated advisors aimed at helping customers manage their money, and oncologists have started using the artificial intelligence system known as Watson to identify new treatments, the prominent role that sophisticated computer programs have begun to occupy in our lives has become undeniable. Government agencies are also harnessing the powers of automation. The U.S. Environmental Protection Agency and the U.S. Food and Drug Administration, for example, are starting to use complex computer models that can predict environmental exposure to chemicals and drug interactions across patient groups. As agencies begin to enter this brave new world of automation, questions have begun to emerge about how government officials should delegate important tasks to machines. For one, will automation negatively affect the level and quality of human deliberation and dialogue that are integral to democratic governance? Furthermore, when adjudicating individual determinations, like the awarding of disability benefits, will machines prove incapable of providing much needed empathy to claimants?

We adopted an approach based on an LSTM neural network to monitor and detect faults in industrial multivariate time series data. To validate the approach we created a Modelica model of part of a real gasoil plant. By introducing hacks into the logic of the Modelica model, we were able to generate both the roots and causes of fault behavior in the plant. Having a self-consistent data set with labeled faults, we used an LSTM architecture with a forecasting error threshold to obtain precision and recall quality metrics. The dependency of the quality metric on the threshold level is considered. An appropriate mechanism such as "one handle" was introduced for filtering faults that are outside of the plant operator field of interest.