Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and can be trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") to be a core part of their business model and future success. Find all the details on our methodology here. The honorees span categories like human resources, security, insurance, and finance, with healthcare, transportation, and infrastructure startups best represented on the list.

Imagine sending a text message to a friend. As your fingers tap the keypad, words and the occasional emoji appear on the screen. Perhaps you write, "I feel blessed to have such good friends:)" Every character conveys your intended meaning and emotion. But other information is hiding among your words, and companies eavesdropping on your conversations are eager to collect it. Every day, they use artificial intelligence to extract hidden meaning from your messages, such as whether you are depressed or diabetic.

The following editorial appeared in Sunday's Japan News-Yomiuri: Fake videos misusing artificial intelligence are spreading on the internet. Is the information coming from a credible source? It is important to be aware of them on a daily basis. A video of U.S. House of Representatives Speaker Nancy Pelosi looking drunk while giving a lecture was disseminated online in May. The video was deliberately slowed down, and it is not clear who posted it online.

Artificial intelligence, alongside proper training and education, can manage even the worst of security breaches into a positive outcome for airports and their users, says Kristina Dores, Chief, Aerodromes & Ground Aids at Namibia Civil Aviation Authority, and Brad Hayes, CTO at Circadence Corporation. However, the key question is when (not if) will organisations take the steps to prepare for the coming wave of digitisation? Highly-interconnected and increasingly-digitised systems are a necessary part of modern airport infrastructure. Furthermore, vulnerabilities at these interfaces – through personnel and digital systems alike – lead to an increased threat of intrusion and potentially catastrophic disruption. This problem is not one that we can simply train and hire our way out of as these systems and their attack surfaces do not scale linearly in complexity.

On the face of it, NASA's newest probe sounds incredible. Known as Dragonfly, it is a dual-rotor quadcopter (technically an octocopter, even more technically an X8 octocopter); it's roughly the size of a compact car; it's completely autonomous; it's nuclear powered; and it will hover above the surface of Saturn's moon Titan. But Elizabeth Turtle, the mission's principle investigator at the Johns Hopkins Applied Physics Laboratory, insists that this is actually a pretty tame space probe, as these things go. "There's not a lot of new technology," she says. Quadcopters (even X8 octocopters) are for sale on Amazon these days.

Stocks inched up Tuesday, with the benchmark Nikkei 225 average closing above 22,000 for the first time in about five months. The Nikkei rose 13.03 points, or 0.06 percent, to end at 22,001.32, The last time the Nikkei finished above 22,000 was April 26. On Friday, the key market gauge jumped 228.68 points. The market was closed Monday for a national holiday.

The US Food and Drug Administration (FDA) has cleared an artificial intelligence (AI) algorithm from GE Healthcare that analyzes chest x-rays for pneumothorax and helps flag suspected cases for radiologists to prioritize reading, the company announced today. The algorithm, part of a set of other quality-assurance algorithms named the Critical Care Suite, was developed to run on a GE Healthcare mobile x-ray device. The software is not yet for sale, and an outside expert expressed concern about its false positive rate. The idea for the application came from bedside clinician experience of waiting for radiologists to read chest x-rays, said Rachael Callcut, MD, MSPH, a surgeon and director of data science for the Center for Digital Health Innovation at the University of California, San Francisco. UCSF proposed developing the feature as part of a development partnership with GE Healthcare.

Businesses using innovative artificial intelligence (AI) solutions should turn their attention to Brussels as the next EU Commission promises to come forward with legislation on AI within 100 days of taking office on 1 November. European politicians have expressed concerns about some applications of AI and are convinced that immediate legislation is the answer. However, attempting to regulate a technology like AI, with its variety of applications, is a complex process and may produce unintended negative consequences. With a new parliament in place and a new Commission about to start its term, the EU is going through the process of setting its priorities for the next five years. Technology and digital policy remain key areas of interest for EU policy-makers, following on from the General Data Protection Regulation (GDPR) and Digital Single Market (DSM) Strategy.

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and can be trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed techniques like machine learning (where systems learn from data to improve upon tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") to be a core part of their business model and future success. Find all the details on our methodology here. The honorees span categories like human resources, security, insurance, and finance, with healthcare, transportation, and infrastructure startups best represented on the list.

Artificial intelligence technology used by police forces in the UK to predict future crimes replicates - and in some cases amplifies - human prejudices, according to a new report. While "predictive policing" tools have been used in the UK since at least 2004, advances in machine learning and AI have enabled the development of more sophisticated systems. These are now used for a wide range of functions including facial recognition and video analysis, mobile phone data extraction, social media intelligence analysis, predictive crime mapping and individual risk assessment. However, the report by the Royal United Services Institute (RUSI) warns that human biases are being built into these machine learning algorithms, resulting in people being unfairly discriminated against due to their race, sexuality and age. One police officer who was interviewed for the report commented that: "Young black men are more likely to be stop and searched than young white men, and that's purely down to human bias. "That human bias is then introduced into the datasets, and bias is then generated in the outcomes of the application of those datasets." In addition to these inherent biases, the report points out that individuals from disadvantaged sociodemographic backgrounds are likely to engage with public services more frequently. As a result, police often have access to more data relating to these individuals, which "may in turn lead to them being calculated as posing a greater risk". Matters could worsen over time, another officer said, when software is used to predict future crime hotspots. "We pile loads of resources into a certain area and it becomes a self-fulfilling prophecy, purely because there's more policing going into that area, not necessarily because of discrimination on the part of officers," the officer said. The report also warns that police forces could become over-reliant on the AI to predict future crimes, and discount other relevant information. "Officers often disagree with the algorithm.