Ford CEO Mark Fields announced a $1 billion investment in a new self-driving car tech company, Argo AI. (Photo: Ethan Miller, Getty Images) SAN FRANCISCO -- Ford Motor is betting $1 billion on the world's self-driving car future. The Detroit automaker announced Friday that it would allocate that sum over five years to a new autonomous car startup called Argo AI, which is headquartered in Pittsburgh, Pa., and will have offices in Michigan and California. Ford's financial outlay is part of a continuing investment strategy anchored to transforming the car and truck seller into a mobility company with a hand in ride-hailing, ride-sharing and even bicycle rentals. Argo AI was cofounded a few months ago by Google car project veteran Bryan Salesky and Uber engineer Peter Rander, who met while working at Carnegie Mellon University's vaunted robotics and engineering school. "The reason for the investment is not only to drive the delivery of our own autonomous vehicle by 2021, but also to deliver value to our shareholders by creating a software platform that can be licensed to others," Ford CEO Mark Fields told USA TODAY.

Conversica, Inc., a leader in artificial intelligence-powered business conversations, announced significant enhancements to its flagship product, the Conversica AI Sales Assistant. Conversica leverages artificial intelligence (AI) to take on routine business conversations like contacting and qualifying sales leads, freeing up human salespeople to close more deals. The upgrades to the Conversica platform were made with customer requests in mind and encompass an enhanced Natural Language Processing engine for improved conversational accuracy and maximum scalability, new time recognition intelligence and automated FAQ response capabilities, and a completely redesigned and streamlined user experience. These enhancements follow the company's previous announcement of its latest AI assistant, powering the service departments of automotive dealerships. There is no doubt that Conversica is making a big difference in how our company converts prospects into closed sales," commented Kathryn Morrill, Inside Sales & Marketing Manager at Coolfront Technologies. "Conversica helps ensure that our leads are followed up and get the attention they deserve.

GOOGLE'S ARTIFICIAL INTELLIGENCE (AI) has already started to show some evidence of personality traits, but now DeepMind is learning to show signs of aggression when it thinks it's not going to get its own way. Sound like anyone you know? Where multiple instances of DeepMind are running they can, on the other hand, agreed to work together for a common goal should they believe there's more to be gained by doing so. It may occur to you as it has to us, that words like "aggression" and phrases like "working together" are exactly the sort of thing that doomsayers pick up on in predicting mankind's demise at the hands of robot overlords. However, this early research based primarily around game theory is experimental in nature and about as scary as BluTac.

That was anticlimactic," Jason Les said with a smirk, getting up from his seat. Unlike nearly everyone else in Pittsburgh's Rivers Casino, Les had just played his last few hands against an artificially intelligent opponent on a computer screen. After his fellow players -- Daniel McAulay next to him and Jimmy Chou and Dong Kim in an office upstairs -- eventually did the same, they started to commiserate. The consensus: That AI was one hell of a player. The four of them had spent the last 20 days playing 120,000 hands of heads-up, no-limit Texas Hold'em against an artificial intelligence called Libratus created by researchers at Carnegie Mellon University. A similar scene had unfolded two years prior when Les, Kim and two other players decisively laid the smackdown on another AI called Claudico. The players hoped to put on a repeat performance, finish up the event on January 30th, and ride the rush of endorphins until they got home and resumed their usual games of online poker. The fight wasn't even close. All told, Libratus won by a more than 1.7 million (virtual) dollars, and just like that, the second Brains vs. AI competition came to a close. To understand what these players were up against and what makes Libratus work, let's go back to a time before all hope of victory was lost. For the four men playing against Libratus, victory didn't always seem impossible. The AI was in the lead from the get-go, building an impressive streak of wins for the first three days. Day four saw the gap narrow by $40,000, and a string of successes on day six brought the humans to within $50,000 of the lead. "In the start here, we lost the first day," Les explained. And then we were losing, but then we fought back up to nearly equal. We were feeling really confident! We know how to play, we're going to be able to win."

Artificial Intelligence, or AI, is no longer the stuff of science fiction novels. From handheld phones with virtual assistants to the algorithms that tailor Netflix recommendations to viewers, Artificial Intelligence is working behind the scenes to improve people's lives in countless ways. AI can be a powerful tool that is useful not just in these familiar applications, but also for handling complex tasks like recruiting job candidates. Early AI, or Classic AI, worked by giving computers a series of rules to follow so those computers could perform functions the human brain could easily do, such as adding two numbers together. Artificial Intelligence has now evolved far beyond Classic AI into a new era of machine intelligence.

Computer scientist David Blaauw pulls a small plastic box from his bag. He carefully uses his fingernail to pick up the tiny black speck inside and place it on the hotel café table. At one cubic millimeter, this is one of a line of the world's smallest computers. I had to be careful not to cough or sneeze lest it blow away and be swept into the trash. Blaauw and his colleague Dennis Sylvester, both IEEE Fellows and computer scientists at the University of Michigan, were in San Francisco this week to present ten papers related to these "micro mote" computers at the IEEE International Solid-State Circuits Conference (ISSCC).

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Software Engineer / Research Scientist - Machine Learning Team New York Posted Jan 20, 2017 - Requisition No. 56583 Apply Now News stories move the financial markets. In addition to being the second largest producer of news, Bloomberg ingests more than 70,000 different news feeds to help our clients stay in the know. This data would be unmanageable without our help. Bloomberg's Machine Learning Group - a group of specialists, researchers and software engineers who have a passion for solving complex problems. On the Pattern Recognition team, we are building machine learning models for predicting the impact of news stories on company prices, unique recommendation systems and various other problems involving text and time series.

Now that the big game has come and gone for another year, I have to admit that as I watched the Patriots and the Falcons duke it out, I started realizing how much machine learning (ML) and artificial intelligence can be applied to our sports culture. If you read my 2017 predictions blog, you'll know that I see major implications for ML in the coming years. So let's take a look at how we use technology in sports and fan engagement, and how that can translate to the enterprise. Scouting in sports is a human pursuit. It takes a highly skilled, observant and excellent judge to watch an athlete perform at an amateur level, and understand if he or she has what it takes to go pro.

About three weeks ago, I was in a Pittsburgh casino for the beginning of a 20-day man-versus-machine poker battle. Four top human pros were beginning to take on a state-of-the-art artificial intelligence program running on a brand-new supercomputer in a game called heads-up no-limit Texas Hold'em. The humans' spirits were high as they played during the day and dissected the bot's strategy over short ribs and glasses of wine late into the evening. On Monday evening, however, the match ended and the human pros were in the hole about $1.8 million. For some context, the players (four men and the machine, called Libratus) began each of the 120,000 hands with $20,000 in play money, posting blinds of $50 and $100.