Goto

Collaborating Authors

 SPE


AI Drives Startup to Map Deep Learning Computer EE Times

#artificialintelligence

Look no further than Google's Tensor Processing Unit (TPU), SoftBank's acquisition of ARM (SoftBank hopes to be a big player in AI), and now a venture-backed startup rolling out a family of "Deep Learning" computers. That startup is Wave Computing, based in Campbell, Calif. The six-year-old company came out of stealth mode Thursday (July 21), revealing its design of a massively parallel dataflow processing architecture called the Wave Dataflow Processing Unit (DPU) for deep learning. Derek Meyer, Wave Computing CEO, told EE Times, "In order to accelerate deep learning, the world needs a new computing architecture." Traditional computer architectures are designed for control flow-oriented applications.


Bringing Anzac Heroes to Life with AI Chatbots on Facebook

#artificialintelligence

Curious to know what an Australian soldier fighting in WWI had for brekkie? Now you can ask him yourself, along with anything else that comes to mind. The Wizeline bots team has partnered News Corp Australia to launch the AnzacLive chatbot, an innovative way to share history with a modern audience. The chatbot was created to commemorate Anzac Day, which recognizes the anniversary of the first major military action fought by the Australian and New Zealand Army Corps. in WWI -- namely the historic battles of Fromelles and Pozieres in July 1916. How did our bots team create a cross-century AMA? Journals from one of the soldiers, Archie Barwick, have been powered by technology.


CIOReview Names MedyMatch in 100 Most Promising Big Data Solutions 2016

#artificialintelligence

MedyMatch Technology Ltd., announced today that it has been ranked in the list of "100 Most Promising BigData Solution Providers" by CIOReview. "The companies selected for our 100 Most Promising BigData Solution Providers 2016 list are an elite group of companies whose products and solutions are changing their respective industries," said Jeevan George, Managing Editor of CIOReview. "We are proud to feature MedyMatch Technology in this edition for its effort in helping organizations to easily and quickly adopt BigData analytics as a core part of their business and accelerate conversion of data into valuable business insights." "It is an honor to be recognized by CIOReview for MedyMatch's achievements in cognitive analytics, artificial intelligence and medical imaging," said Robert Mehler, coFounder & COO. "It is a testament to the accomplishments and capability of our product development team in conjunction with our medical big data clinical partnerships," adds Mehler.


Inspur's Secrets Unveiled Behind Baidu's Driverless Car Technology RoboticsTomorrow

#artificialintelligence

As the pioneer in artificial intelligence field, Baidu chose the Inspur NF5568M4 heterogeneous supercomputing server in its unmanned auto road condition model training. Artificial intelligence has advanced through the years and voice recognition, intelligent hardware, and driverless cars are all technologies that influence our lives. Behind artificial intelligence technology is a neural network that is built from deep learning -- mimicking mechanisms of the human brain when interpreting data. In order to meet all the latest deep learning requirements, a high-performance CPU GPU co-processing acceleration server is growing to become the essential foundation for artificial intelligence hardware.


6 Founders Share Their Secret To Building A Successful AI App

#artificialintelligence

The artificial intelligence and voice recognition space has been growing rapidly. According to a Gartner report, by 2020, 85% of customer interactions will be managed without a human. This is pretty much likely, as we are already teaching our machines to interpret data into logical solutions. Apps running on artificial intelligence should make a user's life easy, but what goes into building such apps? In a #Bitesize interview with us, Xavier Amatriain, VP of engineering at Quora, explained the key to successful machine learning in developing products.


Bot influencers are the programmatic future of conversational advertising

#artificialintelligence

Vladimir Klimontovich is the CTO and founder of GetIntent. In the near future, ads will just be part of the conversation. Bots, and the AI technologies that drive them, are taking huge leaps forward in sophistication and reach. Facebook and Telegram recently added bot APIs to their platforms, and Apple Messages will soon allow third-parties to plug in, too. While bots had previously been limited to very specific requests, such as checking a balance or flight status, next-generation AI, like the recently unveiled Viv, will better understand context and integrate with a host of services -- including programmatic advertising.


Sci non-fi

#artificialintelligence

Written by our strategist and resident science fiction nerd Erik Magnuson, these monthly roundups won't cover every development in the ever accelerating world of technology, but they will hopefully provide a little insight into why things are happening, and what might happen next. I will start this roundup as I often do by talking about artificial intelligence. I am convinced that Eric Horvitz of Microsoft Research is correct when he says "the next if not last enduring battlefield between technology companies is artificial intelligence." That battle has so far been fought mostly between digital assistants from Amazon, Apple, Google, and Microsoft. But recently a new player entered the arena: Viv.


Artificial intelligence - Wikipedia, the free encyclopedia

#artificialintelligence

Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, an ideal "intelligent" machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal.[1] Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".[2] As machines become increasingly capable, facilities once thought to require intelligence are removed from the definition. For example, optical character recognition is no longer perceived as an exemplar of "artificial intelligence" having become a routine technology.[3] Capabilities still classified as AI include advanced Chess and Go systems and self-driving cars. AI research is divided into subfields[4] that focus on specific problems or on specific approaches or on the use of a particular tool or towards satisfying particular applications. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.[5] General intelligence is among the field's long-term goals.[6] Approaches include statistical methods, computational intelligence, soft computing (e.g. machine learning), and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience and artificial psychology. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."[7] This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence, issues which have been explored by myth, fiction and philosophy since antiquity.[8] Attempts to create artificial intelligence has experienced many setbacks, including the ALPAC report of 1966, the abandonment of perceptrons in 1970, the Lighthill Report of 1973 and the collapse of the Lisp machine market in 1987. In the twenty-first century AI techniques became an essential part of the technology industry, helping to solve many challenging problems in computer science.[9]


The current state of machine intelligence 2.0

#artificialintelligence

A year ago today, I published my original attempt at mapping the machine intelligence ecosystem. So much has happened since. I spent the last 12 months geeking out on every company and nibble of information I can find, chatting with hundreds of academics, entrepreneurs, and investors about machine intelligence. This year, given the explosion of activity, my focus is on highlighting areas of innovation, rather than on trying to be comprehensive. Despite the noisy hype, which sometimes distracts, machine intelligence is already being used in several valuable ways.


Megan Smith: Perspectives on artificial intelligence from the White House

#artificialintelligence

The government is using artificial intelligence in tasks ranging from planning space missions to forecasting job growth. Given the potential effects of these technologies on culture and economy, U.S. Chief Technology Officer Megan Smith says the government's larger challenge is to bring "humanity's greatest talent" to bear on the development and direction of AI. To hear more, watch her talk at the 2016 Global Entrepreneurship Summit partner event, "The Future of Artificial Intelligence."