We've scoped out these real-world AI use cases so we could detail how artificial intelligence has been a game-changer for FinTech. Few verticals are such a perfect match for the improved capabilities brought by the AI revolution like the financial sector. Traditional financial services have always struggled with massive volumes of records that need to be handled with maximum accuracy. Join nearly 200,000 subscribers who receive actionable tech insights from Techopedia. However, before the advent of AI and the rise of Fintech companies, very few giants of this industry had the bandwidth to deal with the inherently quantitative nature of this world.

The military has its eye on artificial intelligence solutions to everything from data analysis to surveillance, maintenance and medical care, but before the Defense Department moves full steam ahead into an AI future, they're laying out some ethical principles to live by. "The United States, together with our allies and partners, must accelerate the adoption of AI and lead in its national security applications to maintain our strategic position, prevail on future battlefields, and safeguard the rules-based international order," said Esper wrote. "AI technology will change much about the battlefield of the future, but nothing will change America's steadfast commitment to responsible and lawful behavior." The list is the result of a 15-month study by the Defense Innovation Board, which is made up of academics and executives in tech and business, who presented their proposed principles in a public forum at Georgetown University in October. According to Esper's Monday memo, the Pentagon pledges that its AI efforts will be: 1) Responsible, 2) Equitable, 3) Traceable, 4) Reliable and 5) Governable.

Security professionals need a varied bag of tricks to keep up with savvy and sophisticated cybercriminals. Artificial intelligence is one valuable weapon in the arsenal as it can handle certain tasks faster and more efficiently than can human beings. That's why many security pros still want the human element to play a significant role in their security defense, according to a survey from WhiteHat Security. Based on a survey of 102 industry professionals conducted at the RSA Conference 2020, WhiteHat's "AI and Human Element Security Sentiment Study" found that more than half of the respondents are using AI or machine learning (ML) in their security efforts. More than 20% said that AI-based tools have made their cybersecurity teams more efficient by eliminating a huge number of more mundane tasks. Further, almost 40% of respondents said they feel their stress levels have dropped since adding AI tools to their security process.

Artificial intelligence, such as the Bank of England Bot, is set to take over an increasing number of central bank functions. Billionaire John Catsimatidis uses artificial intelligence to research daughter's date

In the 1960s, the Star Trek television series brought the vision of artificial intelligence into the living rooms of millions of people. AI was everywhere in the show, in the form of machines that had all the intelligence of humans -- and a lot more. Take, for example, the universal translator on the USS Enterprise. It could translate alien languages into English or any other language instantaneously. That, of course, was all science fiction back in the days when Lyndon B. Johnson was the U.S. president, as were a lot of the other AI applications in use on the starship.

'As a result of federal initiatives to "get tough on crime," such as the Reagan Administration's War on Drugs and the Clinton Administration's "Three Strikes" laws, the total number of incarcerated Americans more than quadrupled from roughly 500,000 inmates in 1980 to 2.2 million inmates in 2015. During these decades, black Americans were incarcerated at a rate five times higher than that of white Americans. Despite a new 2019 US Bureau of Justice Statistics (BJS) report, which suggests that the racial disparity between white and black incarceration rates is "narrowing," a Pew Research Center review of BJS stats reveals that this 2019 report "counts only inmates sentenced to more than a year."Moreover, Whites accounted for 64% of adults but 30% of prisoners. . . . In 2017, there were 1,549 black prisoners for every 100,000 black adults--nearly six times the imprisonment rate for whites (272 per 100,000)."

Extreme temperature can do strange things to metals. In severe heat, iron ceases to be magnetic. In devastating cold, lead becomes a superconductor. For the last 30 years, physicists have been stumped by what exactly happens to uranium ruthenium silicide (URu2Si2) at 17.5 kelvin (minus 256 degrees Celsius). By measuring heat capacity and other characteristics, they can tell it undergoes some type of phase transition, but that's as much as anyone can say with certainty. A team led by Brad Ramshaw used a combination of ultrasound and machine learning to narrow the possible explanations for what happens to this large sample of uranium ruthenium silicide when it enters its so-called "hidden order."

Air Force acquisition chief Will Roper said March 11 the Air Force is still working on promising research despite a largely stagnant science and technology budget request for fiscal 2021 that is worrying some lawmakers. As the U.S. looks to develop advanced military systems like improved hypersonic weapons and enabling technologies like artificial intelligence faster than Russia and China, Roper lamented that the service's research fund lost ground to more pressing priorities. Nuclear modernization, joint all-domain command and control, and the effort to stand up a Space Force pulled money and resources away from basic research in the 2021 request released last month. "Sometimes the innovation voices did not win at budget closeout," Roper said. "[There are] a lot of things on the Air Force's plate … and unfortunately when we had to make the budget balance, we had to look for areas to take risk."

The president's budget request for fiscal 2021 proposed $738 million to fund the National Institutes of Science and Technology, a dramatic reduction from the more than $1 billion in enacted funds allocated for the agency this fiscal year. The House Science, Space and Technology Committee's Research and Technology Subcommittee on Wednesday held a hearing to hone in on NIST's reauthorization--but instead of focusing on relevant budget considerations, lawmakers had other plans. "We're disappointed by the president's destructive budget request, which proposes over a 30% cut to NIST programs," Subcommittee Chairwoman Rep. Haley Stevens, D-Mich., said at the top of the hearing. "But today, I don't want to dwell on a proposal that we know Congress is going to reject ... today I would like this committee to focus on improving NIST and getting the agency the tools it needs to do better, to do its job." Per Stevens' suggestion, Under Secretary of Commerce for Standards and Technology and NIST Director Walter Copan reflected on some of the agency's dire needs and offered updates and his view on a range of its ongoing programs and efforts.

Change point detection is an important part of time series analysis, as the presence of a change point indicates an abrupt and significant change in the data generating process. While many algorithms for change point detection exist, little attention has been paid to evaluating their performance on real-world time series. Algorithms are typically evaluated on simulated data and a small number of commonly-used series with unreliable ground truth. Clearly this does not provide sufficient insight into the comparative performance of these algorithms. Therefore, instead of developing yet another change point detection method, we consider it vastly more important to properly evaluate existing algorithms on real-world data. To achieve this, we present the first data set specifically designed for the evaluation of change point detection algorithms, consisting of 37 time series from various domains. Each time series was annotated by five expert human annotators to provide ground truth on the presence and location of change points. We analyze the consistency of the human annotators, and describe evaluation metrics that can be used to measure algorithm performance in the presence of multiple ground truth annotations. Subsequently, we present a benchmark study where 13 existing algorithms are evaluated on each of the time series in the data set. This study shows that binary segmentation (Scott and Knott, 1974) and Bayesian online change point detection (Adams and MacKay, 2007) are among the best performing methods. Our aim is that this data set will serve as a proving ground in the development of novel change point detection algorithms.