With its army short of ammunition and troops to break the deadlock on the battlefield, Ukraine has increasingly taken the fight behind Russian lines, attacking warships, railways and airfields in an attempt to diminish Moscow's military operations. Most recently, that campaign has focused on oil infrastructure, hitting refineries deep in Russian territory and driving home the country's vulnerability to such attacks. On Tuesday and Wednesday, Ukrainian drones hit four Russian refineries, officials on both sides said, adding to a series of recent attacks that have set fire to depots, fuel tanks and other oil infrastructure across Russia. Since the beginning of the year, Ukraine has claimed responsibility for nearly a dozen such assaults, and local Russian authorities have reported five more.

Artificial intelligence is one of the most exciting technological improvements to encircle our society in living memory, however few individuals have a solid comprehension of AI as well as the plethora of ways that it is changing our planet. Nowhere is Artificial intelligence more significant and tumultuous than at the energy industry, where professionals from a broad assortment of backgrounds are discovering it immensely beneficial. Nonetheless, the use of AI from the petroleum and gas industry remains largely misunderstood, and lots of prospective entrants into the sector don't have any clue where to start cleaning up with this intricate topic. Here's a breakdown of how AI is disrupting oil and gas, and why intelligent machines will be imperative to the future of the energy sector. When there's a simple way to describe the part of AI from the gas and oil industry, it is that this technology has become an integral part of the way that energy businesses and professionals achieve their aims. Gas and oil companies have been enormous collectors of information; if nicely employees could not access tremendous treasure troves of information about the area they are working in, for example, they'd never have the ability to be successful in their tasks while ensuring workplace safety and cost-effectiveness.

The oil price crash of 2014 and the global'digitalization and disruption' drive coincided in a rather bizarre way to push the oil industry to seek cost cuts through innovation and new technologies. Big Tech was only too pleased to help Big Oil, seeing a new revenue stream in an industry long thought to be of the'dinosaur' type that was too slow to embrace new ways of doing things. Many oil and gas firms, especially the world's biggest, are already using data analytics, cloud computing, digital oil fields, digital twins, robotics, automation, predictive maintenance, machine learning, and even AI. The technology giants have seized the opportunity to sell such services to Big Oil, and top managers at Amazon Web Services, Microsoft Azure, and ABB Group, to name a few, flocked to this week's top energy industry event CERAWeek by IHS Markit in Houston to pitch their solutions to a wider audience. "A great wave of innovation and technology is transforming the industry and reshaping the energy future," said Daniel Yergin, conference chair and vice chairman of IHS Markit.

Last year's augmented reality investments roundup was impressive. And in 2018, the dollars flowing toward AR haven't decreased, as venture capitalists and strategic investors continue to aggressively fund AR startups at a rapid pace. And while the technology still has yet to produce the mainstream breakout hits that the financial analysts and media are looking for, as one expert explained recently, revolutionary technology is a long game. "When I first got my first computer decades ago, I got it at my office. I learned how to use a computer at the office; I didn't bring it home. It was years before I got one to come home with. These headsets, these glasses, augmented reality, it's going to start more on an enterprise business-to-business kind of standpoint," said Larry Jones, CEO of Blackthorn Media (and former TV Land head) in an interview with CNBC.

Crude oil prices hit record highs back in 2008, reaching upwards of $150 per barrel, boosting production and inspiring a gold rush amongst investors who banked on the trajectory of a perceivably promising industry. Yet, the reality plaguing global powerhouses like Exxon Mobil, Shell and BP proved the exact opposite.

There's a chart I came across earlier this year, and not only does it tell an extremely important story about automation, but it also tells a story about the state of the automation discussion itself. It even reveals how we can expect both automation and the discussion around automation to continue unfolding in the years ahead. The chart is a plot of oil rigs in the United States compared to the number of workers the oil industry employs, and it's an important part of a puzzle that needs to be pieced together before it's too late. What should be immediately apparent is that as the number of oil rigs declined due to falling oil prices, so did the number of workers the oil industry employed. But when the number of oil rigs began to rebound, the number of workers employed didn't. That observation itself should be extremely interesting to anyone debating whether technological unemployment exists or not, but there's even more to glean from this chart.

While the oil and gas industry has had its share of ups and downs over the past decade, many financial institutions are banking on a very slow growth of oil prices in 2017. Though some believe that the efficiency gains that the oil industry can capture are quickly coming to an end, this sentiment is only capturing hard technology specifically related to oil and gas. To help bring the O&G industry to the 21st century, technology from other industries needs to be incorporated, using many hard-earned years of expertise and different lines of thinking. Oilprice previously mentioned incorporating food industry technology to increase safety standards when fracking, but incorporating technology from the IT industry is something that the O&G industry as a whole can benefit from. Whether its neural networks, machine learning, fuzzy logic, case-based reasoning or expert systems, AI has the potential to transform the industry.

At that point, technological revolution was still in its deployment phase. In 1908 Henry Ford had introduced the idea of Fordism and the production line. It was a brand new concept. Sales of the Ford car accelerated pretty quickly, pretty exponentially for the time. There's the readjustment phase: Wall Street crashed in 1929, followed by the depression and then World War II.

Arithmetically, the problem is a combination of collapsing productivity and insufficient capital investment. On February 19, 2017, the New York Times ran a feature story on recent changes in the United States oil industry.2 The focus was on the recent "embrace" of technological innovation in the industry after the 2014 plunge in the global oil market. This was just one of a rash of such pieces in the popular press, relying, as is typical of such writing, on a smattering of skewed, decontextualized data, a healthy serving of the anecdotal, and a host of the worst tech journalism clichés ("a few icons on a computer screen," "a click of the mouse," video game marathons as job training, a compulsory reference to drones). Zeroing in on the effects of these changes on workers in west Texas, the article's upshot is unobjectionable enough: as oil prices recover, output rises, and production becomes more capital-intensive, many workers who lost jobs in the downturn will be replaced by machines. These workers, often Latino, are sure to be forced out of these semi-skilled, relatively well-paid jobs into other sectors of the labor market, where their skills and experience will serve little purpose. At first blush, the situation seems dire. We are told that some 30% of jobs in the industry were lost after the oil market crash of mid-2014, when employment in the industry was at its peak.

While the oil and gas industry has had its share of ups and downs over the past decade, many financial institutions are banking on a very slow growth of oil prices in 2017. Though some believe that the efficiency gains that the oil industry can capture are quickly coming to an end, this sentiment is only capturing hard technology specifically related to oil and gas. To help bring the O&G industry to the 21st century, technology from other industries needs to be incorporated, using many hard-earned years of expertise and different lines of thinking. Oilprice previously mentioned incorporating food industry technology to increase safety standards when fracking, but incorporating technology from the IT industry is something that the O&G industry as a whole can benefit from. Whether its neural networks, machine learning, fuzzy logic, case-based reasoning or expert systems, AI has the potential to transform the industry.