An artificially intelligent computer program can now diagnose skin cancer more accurately than a board-certified dermatologist.1 Better yet, the program can do it faster and more efficiently, requiring a training data set rather than a decade of expensive and labor-intensive medical education. While it might appear that it is only a matter of time before physicians are rendered obsolete by this type of technology, a closer look at the role this technology can play in the delivery of health care is warranted to appreciate its current strengths, limitations, and ethical complexities. Artificial intelligence (AI), which includes the fields of machine learning, natural language processing, and robotics, can be applied to almost any field in medicine,2 and its potential contributions to biomedical research, medical education, and delivery of health care seem limitless. With its robust ability to integrate and learn from large sets of clinical data, AI can serve roles in diagnosis,3 clinical decision making,4 and personalized medicine.5 For example, AI-based diagnostic algorithms applied to mammograms are assisting in the detection of breast cancer, serving as a "second opinion" for radiologists.6

Japan's Hayabusa2 on Thursday released a robotic explorer bound for the surface of an asteroid in the probe's final task before returning to earth, the nation's space agency said. The Minerva-II2, a small rover attached to Hayabusa2, began its descent toward the surface of the Ryugu asteroid at around 1 a.m. Its primary task will be to research the asteroid's gravity. Previous plans for surface observations were scrapped due to glitches, according to the Japan Aerospace Exploration Agency (JAXA). Observing the explorer's descent to the surface will be the last mission for the probe before it leaves the asteroid in November or December, the Japan Aerospace Exploration Agency (JAXA) said.

In 2010, the small community of specialists who pay attention to US road safety statistics picked up the first signs of a troubling trend: more and more pedestrians were being killed on American roads. That year, 4,302 American pedestrians died, an increase of almost 5% from 2009. The tally has increased almost every year since, with particularly sharp spikes in 2015 and 2016. Last year, 41% more US pedestrians were killed than in 2008. During this same period, overall non-pedestrian road fatalities moved in the opposite direction, decreasing by more than 7%. For drivers, roads are as safe as they have ever been; for people on foot, roads keep getting deadlier. Through the 90s and 00s, the pedestrian death count had declined almost every year. No one would have confused the US for a walkers' paradise – at least part of the reason fewer pedestrians died in this period was that people were driving more and walking less, which meant that there were fewer opportunities to be struck. But at least the death toll was shrinking. The fact that, globally, pedestrian fatalities were much more common in poorer countries made it possible to view pedestrian death as part of an unfortunate, but temporary, stage of development: growing pains on the road to modernity, destined to decrease eventually as a matter of course. The US road death statistics of the last decade have blasted a hole in that theory.

A facial recognition service has been launched that enables governments and businesses to get real-time data on people's online habits, preferences and social presence. Entitled VR Office Place, the product is being touted for a range of applications, including identifying security risks, preventing accidents and providing additional information to sales people to improve the chances of making a deal. According to its creators, London, UK-based ETalc Technologies, the facial recognition service identifies people from video feeds, such as CCTV, and then provides analytics of the individuals identified. Using information that is publicly available online, this analytics can include name, occupation and interests, with granular details such as favourite movies being suggested by the company. Each organisation using VR Office Place is able to tailor the results to their needs, enabling it to be used by both businesses and government departments, with use cases such as border security and car sales suggested by the company.

As part of the continued strategy and growth of Decision Point AI it has today incorporated it's professional services consulting business Decision Point AI UK as Decision Point AI Limited in Edinburgh, Scotland. We have embarked upon a major strategic engagement in the UK, USA and the Europe, using Scotland as a launch pad. Today we formally launch Decision Point AI UK our UK Professional Services Consulting capability with the'problem solved' attitude to servicing clients issues. As with our UK consulting launches 3 month lead period, we also involved in soft launches in the USA from NYC and Europe from Dublin. The company continues to gain clients and markets based on the prior'BigFour' relationships from its leadership team and new clients from the thriving Scottish technology and innovation scene.

KPMG estimated the size of the automotive insurance is likely to shrink by 70 % because of the increase in need for the change and autonomous automobiles in liability subsequently being positioned on the automobile manufacturer. With the rise of AI in many sectors, it makes sense that AI would find the way of its into the motor vehicle insurance community. This particular article intends to offer business leaders of the automobile insurance room with a concept of what they are able to presently expect from Ai in the business of theirs. We wish this report allows business leaders in automobile insurance to garner insights they are able to confidently relay to the executive teams of theirs so they are able to make educated choices when thinking about AI adoption. At the minimum, this article intends to serve as a technique of decreasing the time industry leaders in automobile insurance invest researching AI businesses with whom they might (or might not) be keen on working.

What exactly is artificial intelligence (AI) and what business does it have in higher education? Simply put, AI is an attempt to emulate human knowledge by programming extensive rules into computers. Through machine learning and expert systems, machines can produce patterns within mass flows of data and pinpoint correlations that couldn't possibly be immediately intuitive to humans. The developmental capabilities and precision of AI ultimately depend on the gathering of data – Big Data. Where better to find a continuous stream of information than within the highly active and engaging community of students.

Last week Google released several thousand deepfake videos to help researchers build tools that use artificial intelligence to spot altered videos that could spawn political misinformation, corporate sabotage, or cyberbullying. Google's videos could be used to create technology that offers hope of catching deepfakes in much the way spam filters catch email spam. In reality, though, technology will only be part of the solution. That's because deepfakes will most likely improve faster than detection methods, and because human intelligence and expertise will be needed to identify deceptive videos for the foreseeable future. Deepfakes have captured the imagination of politicians, the media, and the public.

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 gets 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 to show that 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") are 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.