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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Google, in the midst of its I/O conference (see our story here), also has teamed up with NASA to form the Quantum Artificial Intelligence Lab at the agency’s Ames Research Center.

According to a post on Google’s Research Blog, the lab will house a D-Wave Systems quantum computer. The goal is to study how quantum computing can solve some of the most challenging computer science problems, with a focus on advancing machine learning. Machine learning, as Director of Engineering Hartmut Neven writes, “is all about building better models of the world to make more accurate predictions,” but it’s hard work to build a really good model. Real-world applications that he discusses include building a more useful search engine by better understanding spoken questions and what’s on the web to provide the best answer.

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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

MOOCs (massive open online courses) are gaining greater ground. Earlier this year we looked at some semantics-related MOOCs of study from outfits like Coursera, edX and Udacity. Since then, news has gone around about some other MOOC opportunities (albeit not necessarily with semantic course offerings), such as MOOC2Degree, Canvas Network, CourseSites, Udemy and Thinkful. The Hasso Plattner Institute also is involved with its openHPI courses, including coverage of semantic web technologies.

Now, word comes that Iversity, which offers its own MOOC platform, and the Foundation for German Science are sponsoring a competition to produce ten MOOCs, five courses for the winter term 2013/14 and five courses for the summer semester 2014. Winners will get  25,000 Euro grants each towards production. The MOOC Production Fellowship selection process is being managed by Iversity, as is the subsequent course production.

About 250 concepts for online courses have been submitted so far, and Internet users have up until May 23 to cast their votes for the ones they view as particularly interesting and groundbreaking. A list of submissions is here.

The categories range from linguistics and cultural studies to interdisciplinary work to natural and computer sciences. The entries include courses focused on semantic, social analytics and related technologies:

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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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Earlier this month Gartner named semantic technologies to its top ten trends list (see our story here). Recently, we caught up with Gartner vp and distinguished analyst Debra Logan, the lead author on the semantic technologies section of the Top 10 Technology Trends Impacting Information Infrastructure, 2013, to learn more about sem tech’s earning a place on the list.

One interesting point Logan made is that the top ten trends list actually is a reflection of inquiries Gartner sees from its end-user clients. So, semantic technologies’ spot on the list would seem to indicate a bubbling-up of real-world, enterprise interest. As Logan sees it, it’s very much about information overload, about minimizing the risk and maximizing the value of the data on their hands, and about the availability now from providers like Amazon and Google of infrastructures for analyzing Big Data sets.

“If we could get the same meaning from data, we might actually know what is going on, because we sure don’t now,” says Logan, of the quandary facing enterprise IT leaders. “They are struggling with definition issues and reconciliation because of the proliferation of different IT systems.”

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