Conf. on Information and Knowledge Management (CIKM) h5 49 International Conference on Artificial Intelligence and Statistics (AISTATS) h5 43 Data Mining and Knowledge Discovery Journal (DMKD) h5 35 Neural Computation h5 34 SIAM International Conference on Data Mining (SDM) h5 33 European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD) h5 30 European Conference on Information Retrieval (ECIR) h5 26 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) h5 23 CORE B ACM Conference on Recommender Systems (RecSys) h5 40 International Joint Conference on Neural Networks (IJCNN) h5 32 Neural Processing Letters h5 23 Information Retrieval h5 20 International Conference on Artificial Neural Networks (ICANN) h5 14 International Conference in Inductive Logic Programming (ILP) h5 - CORE Unranked Asian Conference on Machine Learning (ACML) h5 13 International Conference on Learning Representations (ICLR) h5 - Wahrnehmung und Sehen Die Fähigkeit zur Verarbeitung visueller Information ist eine Grundbedingung für künstliche Intelligenzen.

Shanghai-based artificial intelligence company Yitu Technology announced this month that is launching its first R&D center outside of China in Singapore. The move is part of a larger trend among Chinese tech companies hoping to achieve two goals: Access top foreign engineering and scientific talent by setting up R&D centers in key global knowledge hubs, and embed themselves deeper in local ecosystems to spur new long-term growth engines -- most notably in Southeast Asia. The ultimate goal for many of China's leading tech companies is to become true multinationals. Their strategy is to build a significant presence in their huge home market and then leverage that to branch out internationally. However, they face a steep learning curve: The free-for-all ethos and Darwinian natural selection that guide their modus operandi in China often prove to be counter-productive in smaller, more insulated markets.

"We are not talking about walking, talking terminator robots that are about to take over the world; what we are concerned about is much more imminent: conventional weapons systems with autonomy," Human Right's Watch advocacy director Mary Wareham told the BBC. Another big question that arises: who is responsible when a machine does decide to take a human life? Is it the person who made the machine? "The delegation of authority to kill to a machine is not justified and a violation of human rights because machines are not moral agents and so cannot be responsible for making decisions of life and death," associate professor from the New School in New York Peter Asaro told the BBC. But not everybody is on board to fully denounce the use of AI-controlled weapon systems.

I have worked on the problem of open-sourcing Machine Learning versus sensitivity for a long time, especially in disaster response contexts: when is it right/wrong to release data or a model publicly? This article is a list of frequently asked questions, the answers that are best practice today, and some examples of where I have encountered them. The criticism of OpenAI's decision included how it limits the research community's ability to replicate the results, and how the action in itself contributes to media fear of AI that is hyperbolic right now. It was this tweet that first caught my eye. Anima Anankumar has a lot of experience bridging the gap between research and practical applications of Machine Learning.

As a futurist, some patents really stand out. Here is one I'm really bullish on, as we enter a post-mobile world of Voice-AI controls and hand gestures. What if there was an invisible button between your thumb and index finger, what could it do? What AI-assistant or dashboard could it summon? Alphabet's Google unit won approval from U.S. regulators to deploy a radar-based motion sensing device known as Project Soli.

The U.S. military wants to expand its use of artificial intelligence in warfare, but says it will take care to deploy the technology in accordance with the nation's values. The Pentagon outlined its first AI strategy in a report released Tuesday. The plan calls for accelerating the use of AI systems throughout the military, from intelligence-gathering operations to predicting maintenance problems in planes or ships. It urges the U.S. to advance such technology swiftly before other countries chip away at its technological advantage. "Other nations, particularly China and Russia, are making significant investments in AI for military purposes, including in applications that raise questions regarding international norms and human rights," the report says.

Artificial Intelligence is way overhyped. I remember well how over-hyped AI was back in the early 1980s when I worked with Applied Expert Systems, a startup founded by some MIT professors that aspired to use expert systems to transform the world of personal financial planning. I helped bring the software to the company and participated in so-called knowledge engineering by interviewing a personal financial planning expert. The idea was to convert the expert's decision making rules into software and build a system that would replace personal financial planners. Sadly for those who invested time and money in this company, its product never found much of a market and it folded.

This week, President Donald Trump signed a new executive order on artificial intelligence and the Pentagon declassified part of its AI strategy. Neither was a first attempt at a national AI strategy. In 2016, the Obama administration published a comprehensive plan on the future of AI, which never had time to gain the momentum it needed in government. The Pentagon has been researching intelligent machines for the better part of 60 years, and only recently did it come to a consensus: Our future wars will be fought in code, using data and algorithms as powerful weapons. Using AI techniques, a military can "win" by destabilizing an economy rather than demolishing countrysides and city centers. From that perspective, and given China's unified march advancing artificial intelligence, China is dangerously far ahead of the West.

The US government averted another shutdown when Donald Trump instead opted to declare a national emergency to fund his border wall dreams--a wall which raises huge privacy and security concerns and will cause more problems than it solves. As the country digested the national emergency, cybersecurity workers were still scrambling to clean up the security nightmare wrought by the longest shutdown in history. Amid all the border wall news this week, you'd be forgiven for missing that the president also signed an executive order creating the American AI Initiative. In an op-ed for WIRED, White House deputy assistant to the president for technology policy Michale Kratsios explained why AI strategy is a security issue. Speaking of AI, to combat the growing threat of deep fakes, a new tool uses the blockchain to monitor video for tampering and manipulation.

Today I'm pleased to present to readers what's next up in our series featuring author Richard Abbott, whose space jaunts have so delighted me--and many others. Of course, I'd previously reviewed Abbott's debut sci-fi novel, Far from the Spaceports, followed up by another for its sequel, Timing. The audio excerpts below come from the second novel and, like our previous entry, utilize Amazon's Polly software, which is enabled for text-to-speech in multiple accents and intonations. This compares to Alexa, a single voice. Before moving forward, for those unfamiliar with the novels and their plots, I've linked the book covers to their respective Amazon blurbs.