Serdar Yegulalp of InfoWorld recently wrote, “Over the last year, as part of the new enterprise services that IBM has been pushing on its reinvention, Watson has become less of a “Jeopardy”-winning gimmick and more of a tool. It also remains IBM’s proprietary creation. What are the chances, then, of creating a natural-language machine learning system on the order of Watson, albeit with open source components? To some degree, this has already happened — in part because Watson itself was built in top of existing open source work, and others have been developing similar systems in parallel to Watson. Here’s a look at four such projects.” Read more
Posts Tagged ‘DARPA’
Liat Clark of Wired UK reports, “The US Defense Advanced Research Projects Agency has launched a programme aimed at developing the next generation of task-orientated search engines that will help index and organise ‘mission-critical publically available information’ on the web and deep web. The first domain it wants to target with this new technology, it says, is human trafficking. ‘We’re envisioning a new paradigm for search that would tailor indexed content, search results and interface tools to individual users and specific subject areas, and not the other way around,’ commented Darpa programme manager Chris White in a release. ‘By inventing better methods for interacting with and sharing information, we want to improve search for everybody and individualise access to information. Ease of use for non-programmers is essential.’ ” Read more
Amaani Lyle of Official Wire reports, “Defense Advanced Research Projects Agency scientists will build on language processing technologies with improved speed and accuracy –- offering an advantage to analysts in a variety of military and non-military scenarios, a program manager said today at the DARPA Congressional Tech Showcase here. Dr. Bonnie Dorr, DARPA Human Language Technologies, demonstrated Raytheon BBN Technologies’ ‘Byblos,’ one of several speech recognition systems that represent the state of the art in trainable, large-vocabulary, speaker-independent speech recognition. ‘What’s of interest here is gleaning information from the huge volumes that come through to us in foreign languages,’ Dorr said. ‘So it’s really [addressing] the big data problem.’ ” Read more
SRI International, which spearheaded the CALO (Cognitive Agent That Learns and Organizes) intelligent assistant for DARPA (Defense Advanced Research Projects Agency), has had more than one semantic project up its sleeve. One of them was Tempo.AI, which was spun off by SRI at the end of 2011. Earlier this year, the smart calendar app for the iPhone was formally launched, with Thierry Donneau-Golencer as co-founder and AI lead.
Donneau-Golencer, having also worked on CALO, clearly has a strong history of work related to dealing with information and how to make sense of it. “A lot of it had to do with semantic analysis, deriving meaning and useful information from content,” says Donneau-Golencer, with Tempo representing the next step in smart search across content by making the job more proactive.
At October’s Semantic Technology & Business Conference in NYC, Donneau-Golencer will share with attendees insights into the role semantic technology has in helping find and correlate information for users, with the least input possible required.
A report from Meghan Neal at Motherboard discusses the work underway at DARPA to develop a machine that can think on its feed, reasoning and problem-solving on the fly, without human intervention. This intelligent real-time computing machine will “focus on mimicking the cerebral neocortex—the part of the brain that’s crucial for things like memory, perception, awareness, and attention,” she writes.
Neal notes that DARPA recently put out a request for information for the research and development of this technology, which it’s calling a “Cortical Processor.” The goal, the article notes, “is to develop a machine that can understand and learn from a huge onslaught of data—including new information that’s streaming in in real-time—from complex environments, like, say, a battlefield. By processing and analyzing all this information in a smart way, the machine could theoretically “decide” an appropriate action to take.”
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
Big Data Startup Ayasdi Launches; Machine Learning Platform Combines Computer Science And Topological Data Analysis
This week a new Big Data startup company launched, Ayasdi, co-founded by Stanford mathematics professor Gunner Carlsson and based on his DARPA-funded research in the area of applied topology, with $10+million in Series A funding led by Khosla Ventures and Floodgate.
The technology, dubbed the Insight Discovery platform, is explained to be the “first machine learning platform that combines computer science and a branch of mathematics known as Topological Data Analysis (TDA) that visualizes the entire dataset.” Hundreds of machine learning algorithms, it says, go to work exploring datasets to in minutes automatically discover insights that can’t be determined through query-based or ad hoc approaches.
Konstantin Kakaes of the New America Foundation recently discussed the NLP challenges of language translation. Kakaes writes, “Recently, on the eighth floor of an office building in Arlington, Va., Rachel held her finger down on a Dell Streak touchscreen and asked Aziz whether he knew the village elder. The handheld tablet beeped as if imitating R2-D2 and then said what sounded like, ‘Aya tai ahili che dev kali musha.’ Aziz replied in Pashto, and the Streak said in a monotone: ‘Yes, I know.’ Rachel asked: ‘Would you introduce me to him?’ Aziz failed to understand the machine’s translation (though he does speak English), so she asked again: ‘Could you introduce me to the village elder?’ This time, there was success, after a fashion. Aziz, via the device, replied: ‘Yes, I can introduce myself to you.’ Aziz, who is at most middle-aged and was wearing a sweater vest, was not the village elder.” Read more
Michael Cooney reports that next month the Defense Advanced Research Projects Agency (DARPA) is set to detail “the union of advanced technologies from artificial intelligence, computational linguistics, machine learning, natural-language fields it hopes to bring together to build an automated system that will let analysts and others better grasp meanings from large volumes of text documents.”
DARPA stated, “Automated, deep natural-language understanding technology may hold a solution for more efficiently processing text information. Read more
A new article reports, “The Defense Advanced Research Projects Agency (DARPA), the DoD progenitors of revolutionary tech like passive radar and the Internet, is calling for research applications of social media to strategic communication. According to an agency announcement (PDF), DARPA is looking to shell out $42 million in funding for ‘innovative approaches that enable revolutionary advances in science, devices, or systems.’ The general goal of the Social Media in Strategic Communication (SMISC) program is to develop a new science of social networks built on an emerging technology base.” This push toward the innovative social technology is hardly new territory for DARPA – the agency has been at the forefront of the semantic web for years with initiatives like DAML, the US flagship R&D program in semantic web. Read more