Campaigners are renewing calls for a pre-emptive ban on so-called "killer robots" as representatives of more than 80 countries meet to discuss the autonomous weapons systems. The use of lethal autonomous weapons systems (LAWS) is "a step too far", said Mary Wareham, the global coordinator of the Campaign to Stop Killer Robots. "They cross a moral line, because we would see machines taking human lives on the battlefield or in law enforcement. "We want weapon systems and the use of force to remain under human control," Wareham said. Wareham spoke to Al Jazeera before Monday's meeting in Geneva, Switzerland on a possible ban on LAWS. This is the fifth international meeting to discuss so-called "killer robots" since 2014, but no formal decisions will be taken yet as countries are still working towards a common definition of LAWS, and have yet to agree on whether they should be outlawed in international law. This is going to be a crucial year. If we do not move swiftly, we could end up in a situation where it's too late and where fully autonomous weapons proliferate to the extent that every country has them," Wareham told Al Jazeera.

Chinese universities and U.S. technology companies such as International Business Machines Corp. and Microsoft Corp. are racing to develop quantum computers, a type of processing that is forecast to be so powerful it can transform how drug-makers, agriculture companies and auto manufacturers discover compounds and materials. Quantum computing uses the movement of subatomic particles to process data in amounts that modern computers cannot handle. Mostly theoretical now, the technology is expected to be able to perform calculations that make today's computers look akin to an abacus. While overall spending by China is unknown, its government is building a $10 billion National Laboratory for Quantum Information Sciences in Hefei, Anhui Province, which is slated to open in 2020. U.S.-funded research in quantum is about $200 million a year, according to a July 2016 government report, and some researchers and companies don't believe that is enough.

Google has launched a new product to the American market, the Google Clip, that uses AI and machine learning to automatically capture photos of what it deems to be "interesting moments". In Australia, the answers appear to be: there isn't and no one. Under Australian law, the author of an artistic work is "the person who took the photograph". The Clip is a machine, not a person, so is not the author (under Australian law). The owner of the Clip did not "take" the photograph, so is not the author.

WASHINGTON – The computer expert who alleges a trove of Facebook data was improperly used to help President Donald Trump's campaign in the 2016 election says he will cooperate with a Justice Department investigation. Christopher Wylie is a whistle-blower and former employee of the data mining firm Cambridge Analytica, which has come under criticism over reports that it swiped the data of about 50 million Facebook users to sway elections. Wylie tells NBC's "Meet the Press" that he plans to meet with "law enforcement and the Department of Justice." Special counsel Robert Mueller was appointed by the Justice Department to run the election probe and has been scrutinizing connections between Cambridge Analytica and Trump's Republican campaign. Democrats on a House Intelligence Panel have previously said they would interview Wylie.

The outcome of the explorative data analysis (EDA) phase is vital for successful data analysis. EDA is more effective when the user interacts with the system used to carry out the exploration. In the recently proposed paradigm of iterative data mining the user controls the exploration by inputting knowledge in the form of patterns observed during the process. The system then shows the user views of the data that are maximally informative given the user's current knowledge. Although this scheme is good at showing surprising views of the data to the user, there is a clear shortcoming: the user cannot steer the process. In many real cases we want to focus on investigating specific questions concerning the data. This paper presents the Human Guided Data Exploration framework, generalising previous research. This framework allows the user to incorporate existing knowledge into the exploration process, focus on exploring a subset of the data, and compare different complex hypotheses concerning relations in the data. The framework utilises a computationally efficient constrained randomisation scheme. To showcase the framework, we developed a free open-source tool, using which the empirical evaluation on real-world datasets was carried out. Our evaluation shows that the ability to focus on particular subsets and being able to compare hypotheses are important additions to the interactive iterative data mining process.

Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That is, adversarial examples, obtained by adding delicately crafted distortions onto original legal inputs, can mislead a DNN to classify them as any target labels. In a successful adversarial attack, the targeted mis-classification should be achieved with the minimal distortion added. In the literature, the added distortions are usually measured by L0, L1, L2, and L infinity norms, namely, L0, L1, L2, and L infinity attacks, respectively. However, there lacks a versatile framework for all types of adversarial attacks. This work for the first time unifies the methods of generating adversarial examples by leveraging ADMM (Alternating Direction Method of Multipliers), an operator splitting optimization approach, such that L0, L1, L2, and L infinity attacks can be effectively implemented by this general framework with little modifications. Comparing with the state-of-the-art attacks in each category, our ADMM-based attacks are so far the strongest, achieving both the 100% attack success rate and the minimal distortion.

We are very excited to be hosting the world renown Tamara McCleary, international technology futurist, emerging technology guru, sci-fi writer, marketing digital strategy consultant and Thulium CEO. Tamara is ranked in the Worlds Top 5 in Artificial Intelligence, Robotics and Internet of Things (IoT), the WorldsTop 15 Machine to Machine (M2M), the Worlds Top 50 Blockchain, Digital Transformation and Big Data. Tamara is rank in the Top 1% of Global Social Media Influencers (Klear) and listed as one of the Top 50 Social Influencers of 2015, 2016, 2017 (Onalytica). Tamara was named Number 1 Most Influential Woman in MarTech (B2B Marketing) and ranked the 2nd most mentioned person on Twitter by Chief Marketing Officers (LeadTail). Tamara is an IBM Futurist and creator of the trademarked RelationShift method.

In one season, it rains heavily, cities get flooded with water, and life comes to a halt. In another season, there is a scarcity of water and thousands of lives are affected every year with drought. Can I harvest the rain water and manage water scarcity? This is one student thinking differently, observing a problem, asking questions and challenging situations, developing a solution and creating an impact. As a society, we often discuss problems, share our views and opinions, but how many of us really contribute towards developing innovative solutions to address the problem?

The Facebook crisis involving Cambridge Analytica's data breach leads many to question how Facebook treats their users' data; Reaction on'Outnumbered.' The man who revealed the Cambridge Analytica data-harvesting scandal said Sunday he believed the political consulting firm snatched information from more than the previously reported 87 million Facebook users. "I think that there is, you know, a genuine -- a genuine risk that this data has been accessed by quite a few people. And that it could be stored in various parts of the world, including Russia, given the fact that, you know, the professor who was managing the data harvesting process was going back and forward between the U.K. and to Russia," Christopher Wylie said on NBC News' "Meet the Press." Wylie was referring to Aleksandr Kogan, whose company, Global Science Research, harvested Facebook's data using a personality app, according to officials.

Separately on Friday, consumer groups filed a complaint with the Federal Trade Commission, saying Facebook violates users' privacy rights through its facial-recognition software. In October, Facebook unveiled a similar authorization requirement for election-related ads. The latest move will cover "issue ads"--those that don't specifically mention a candidate but weigh in on a divisive issue, including during an election campaign. Such advertisers will be required to confirm their identities and locations with the company. The change marks the latest step in Facebook's efforts to secure its platform after Russian-backed groups used the social network to sow divisions before and after the 2016 U.S. presidential election, and elsewhere in the world.