Dealers are likely looking at the flat or declining sales forecast for this year and figuring out how they will make up for that loss of new car sales profits. They should also be thinking longer term, because the entire nature of car ownership will have changed dramatically in just a bit over a decade, per KPMG. Personal ownership has peaked in the U.S., or will in the next few years, and be replaced by mobility services, KPMG principle Jono Anderson, tells Automotive Buy Sell Report. Mobility services include ride hailing services such as Uber and Lyft, but also, increasingly, will be based on fleets of autonomous vehicles. Mobility services represent about seven percent of all miles driven today, he says. That will increase to 20 percent by 2030.

It's scary enough making a doctor's appointment to see if a strange mole could be cancerous. Imagine, then, that you were in that situation while also living far away from the nearest doctor, unable to take time off work and unsure you had the money to cover the cost of the visit. In a scenario like this, an option to receive a diagnosis through your smartphone could be lifesaving. A dermatologist uses a dermatoscope, a type of handheld microscope, to look at skin. Computer scientists at Stanford have created an artificially intelligent diagnosis algorithm for skin cancer that matched the performance of board-certified dermatologists.

Artificial intelligence is well on the way to powering everyday functions and devices, and transforming how society lives. Now, a Boston-based start-up is trying to conquer the next frontier of machine learning -- by making a range of products even smarter and more autonomous. Neurala, which recently raised a whopping $14 million in funding, is a software company looking to bring the AI phenomenon to consumer devices and influence how they operate in real time. According to the company, Neurala's efforts are focused on four major markets: drones, smart cars, cameras and toys. Founded in 2006 by Heather Ames, Anatoly Gorshechnikov and CEO Massimiliano "Max" Versace, Neurala's flagship product is the Neurala Brain, which utilizes deep learning neural networks to allow objects like drones to recognize and identify things in their environment and take the appropriate action depending on what they see.

At Narrative Science, we love making predictions about innovation, technology and, in particular, the rise of artificial intelligence. We may be a bit too optimistic about the timing of certain technologies going mainstream, but we can't help it. We are wildly optimistic about the future and genuinely believe that we have entered a dramatically new era of artificial intelligence innovation. That said, this year, we tried to focus our predictions on the near-term. Here's our best guess as to what will happen in 2016.

When you arrive at the office at 8 a.m., there's a lot that stands between you and the work you need get done that day. Pull up yesterday's blog traffic. Check in on the monthly lead count. Build a list for your next email send. Report on the results of your latest content campaign … Some days, it's easy to feel like you don't actually spend that much time marketing.

"I can't wait to push some paper today!" The mind-numbing work to keep the wheels of commerce rolling--filling out invoices, deciphering hand-written memos, processing insurance claims--can be a real grind. It's been that way since the time when Ebenezer Scrooge refused to provide another lump of coal to help warm overworked clerk Bob Cratchit. Lacking frailty of mind and body, artificial intelligence for business process automation appears to be a no-brainer. In fact, a number of companies are employing AI techniques such as machine learning, computer vision and natural language processing to automate business processes.

Intel realizes there will be a post-Moore's Law era and is already investing in technologies to drive computing beyond today's PCs and servers. The chipmaker is "investing heavily" in quantum and neuromorphic computing, said Brian Krzanich, CEO of Intel, during a question-and-answer session at the company's investor day on Thursday. "We are investing in those edge type things that are way out there," Krzanich said. To give an idea of how far out these technologies are, Krzanich said his daughter would perhaps be running the company by then. Researching in these technologies, which are still in their infancy, is something Intel has to do to survive for many more decades.

The current language when talking about Artificial Intelligence, Robots and Automation – (what we can name the'AIRA' technologies), and their impact on jobs is often fearful or aggressive. The'robots will take your job and everything is ruined' mentality seems pervasive. The headlines are pitched to grab your attention while pulling at your fears. However, increasing anxiety over job security is understandable as we're seeing artificial intelligence, robots and automation, taking over in areas we previously thought were safe. Undeniably there is a huge change happening thanks to these technologies. Yes, many jobs are under threat – but that isn't the whole story by any stretch of the imagination.

To say that AI is the number one buzz word in legal at the moment is to say the least. But there is still a big uncertainty about what it actually is and what it can do. A general misconception seems to be that Artificial Intelligence is a single "thing". It can be clause identification, anomaly detection, general due diligence review tools, cognitive systems, machine learning etc. One of the AI-seminars at LegalTech focused on the use of machine-learning technology in due diligence reviews, where the tools help lawyers review large sets of material, looking for risks and pitfalls.

One of the biggest confusions about "Artificial Intelligence" is that it is a very vague term. That's because Artificial Intelligence or AI is a term that was coined way back in 1955 with extreme hubris: We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire. The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves. AI is over half a century old and carries with it too much baggage.