The Intel International Science and Engineering Fair has a winner: Ionut Budisteanu of Romania received the Gordon E. Moore Award. He gets to take home the $75,000 prize package as the first-place champ for creating a model of a low-cost, self-driving car that uses artificial intelligence.

Ionut used a low-res 3-D radar and mounted webcameras for an autonomously controlled car that uses AI to detect traffic lanes and curbs, along with the real-time position of the car. The cost? Just $4,000, according to Intel’s announcement of the winners. That’s tens of thousands of dollars less than Google, which reportedly relies on costly high-res 3-D radar, and luxury car companies can do it for.

But that’s not the only AI-related development in the vehicles space in recent days.

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John Roach of NBC News reports, “When all the humans went home for the day, a personal-assistant robot under development in a university lab recently built digital images of a pineapple and a bag of bagels that were inadvertently left on a table – and figured out how it could lift them. The researchers didn’t even know the objects were in the room. Instead of being frightened at their robot’s independent streak, the researchers point to the feat as a highlight in their quest to build machines that can fetch items and microwave meals for people who have limited mobility or are, ahem, too busy with other chores.” Read more

Daniela Hernandez of Wired reports, “There’s a theory that human intelligence stems from a single algorithm. The idea arises from experiments suggesting that the portion of your brain dedicated to processing sound from your ears could also handle sight for your eyes. This is possible only while your brain is in the earliest stages of development, but it implies that the brain is — at its core — a general-purpose machine that can be tuned to specific tasks. About seven years ago, Stanford computer science professor Andrew Ng stumbled across this theory, and it changed the course of his career, reigniting a passion for artificial intelligence, or AI. ‘For the first time in my life,’ Ng says, ‘it made me feel like it might be possible to make some progress on a small part of the AI dream within our lifetime’.” Read more

Alex Howard of O’Reilly Radar reports, “After years of steady growth, open data is now entering into public discourse, particularly in the public sector. If President Barack Obama decides to put the White House’s long-awaited new open data mandate before the nation this spring, it will finally enter the mainstream. As more governments, businesses, media organizations and institutions adopt open data initiatives, interest in the evidence behind  release and the outcomes from it is similarly increasing. High hopes abound in many sectors, from development to energy to health to safety to transportation. ‘Today, the digital revolution fueled by open data is starting to do for the modern world of agriculture what the industrial revolution did for agricultural productivity over the past century,’ said Secretary of Agriculture Tom Vilsack, speaking at the G-8 Open Data for Agriculture Conference.” Read more

Robert D. Hof of the MIT Technology Review recently discussed “deep learning” as one of the ten breakthrough technologies of 2013. He writes, “When Ray Kurzweil met with Google CEO Larry Page last July, he wasn’t looking for a job. A respected inventor who’s become a machine-intelligence futurist, Kurzweil wanted to discuss his upcoming book How to Create a Mind. He told Page, who had read an early draft, that he wanted to start a company to develop his ideas about how to build a truly intelligent computer: one that could understand language and then make inferences and decisions on its own. Read more

Tempo AI, maker of a new mobile calendar app powered by cutting-edge artificial intelligence research, is announcing the launch of Tempo Smart Calendar in Canada. In its first month, Tempo has “AI’ed” over 50M unique calendar events in the U.S., and seen many Tempo Smart Calendar users replacing their default iOS calendar with Tempo.

In order to apply all of the benefits of Tempo AI’s contextual learning engine and bring the smartest possible experience to Tempo users, the company has been allowing users into the system in batches. New improvements and more steady demand are now allowing the company to double the rate at which users are being accepted, and Tempo Smart Calendar will be available to all users soon. Read more

Conversational user interfaces and natural language processing could be put to much more use than they currently are.  At the GigaOM Structure Data event in New York City this week, IBM distinguished engineer Currie Boyle, who leads the vendor’s North American natural language services practice, including for deep question and answer Watson-type natural language and unstructured information processing systems, and Nuance Communications CTO Vlad Sejnoha, discussed the realized promises, but also the waiting opportunities.

At Nuance, Sejnoha noted, the focus is on the notion that we are entering a time when how we interact with systems and access information and content is undergoing a “dramatic transformation.” Contributors to that include high- level artificial intelligence reasoning and natural language understanding. “We are overwhelmed with lots of data including unstructured data and these technologies make a difference in how we take advantage of all that,” he said.

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James Hendler recently discussed what the arrival of Watson at RPI will mean  for the growing technology. He writes, “The Watson program is already a breakthrough technology in AI. For many years it had been largely assumed that for a computer to go beyond search and really be able to perform complex human language tasks it needed to do one of two things: either it would “understand” the texts using some kind of deep ‘knowledge representation,’ or it would have a complex statistical model based on millions of texts.” Read more

A new article out of Concept Searching reports that the company “has entered into a partnership agreement with Discovery Machine, Inc., developer of knowledge capture and deployment technologies for subject matter expertise automation. This arrangement brings together Concept Searching’s expertise in metadata generation, search, auto-classification, and taxonomy management, and combines it with Discovery Machine’s proven methodology for capturing subject matter expertise. Discovery Machine has leveraged its success with the Defense Advanced Research Projects Agency (DARPA), Office of Naval Research (ONR), Naval Air System Command (NAVAIR), and Boeing to develop a suite of Artificial Intelligence (AI) software solutions.” Read more

Charlie Neer of Co.Create recently shared his insights regarding the rise of predictive analytics and how humans stack up by comparison. He writes, “We all know the history behind the recent economic crisis. I wonder though, if most people know that trading algorithms predicted the fall from grace long before the actual traders? Check it out for yourself. When you consider this, it makes perfect sense. Given the amount of variables that abound and the speed at which they are changing, humans simply can’t keep up. In a more industry-specific example, look at the evolution of display ad serving optimization. As the number of variables increased, so did the speed of technology adoption. We went from spreadsheets to dynamic cost per thousand (dCPM) to RTB in less than five years.”

He goes on, “Let’s think beyond today. What happens when you break through the finite set of inferred third-party targeting attributes in display advertising to a point where one has the ability to adjust bids based on plethora of accurate first-party data curated by the end user? Read more