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.

At least 24 teams from 11 countries, including Germany, Turkey, China, Singapore and South Korea, have competed with local teams for the 2018 robotics football cup in Tehran, Iran. The 13th RoboCup Iran Open included a number of robotic football leagues, as well as teams focused on rescue and de-mining simulations, home applications and unmanned aerial vehicle operation. A team from Leipzig University of Applied Sciences won in the football standard league championship, while a team from Iran's Qazvin Islamic Azad University won the overall trophy by winning in seven categories. RoboCup is an international research and education initiative that researches artificial intelligence and its utility for future applications while fostering interest among young students in robotics. At the opening of the event last week, Sourena Sattari, Iran's vice president for science and technology, called for an overhaul in policy to help young robotics experts find jobs and outlets for their work.

WHETHER to maintain patient records or help analyze sophisticated medical images like those from a CT scan or an MRI machine, computers have always played an important role in healthcare. The medical fraternity understands how computers help make their job better and easier. For them, the transition to AI-powered devices has been almost natural and is a journey most healthcare professionals look forward to. According to a new report published by Allied Market Research, the global AI in healthcare market was valued at US$1,441 million in 2016, and is estimated to reach at US$22.79 billion by 2023, registering a CAGR of 48.7 percent from 2017 to 2023. The study indicates that North America was the highest contributor in the AI in healthcare market in 2016.

Alibaba Group Holding Ltd. has led a US$600 million series C round in SenseTime, a Beijing-based Chinese artificial intelligence company specializing in facial and image recognition technology and its application. Temasek Holdings and Chinese retailer Suning Commerce Group Co., Ltd also participated in the round, according to SenseTime's announcement on its official WeChat account. SenseTime is valued at US$4.5 billion on China Money Network's China Unicorn Ranking. The firm did not disclose the valuation after the new round. With its AI technology, SenseTime has been favored by investors.

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.

The level in this article is for college students familiar with calculus, This material will be also of interest to college professors looking for new material to teach, or for original exam questions, as well as for business data scientists with some spare time, interested in refreshing their math skills. The problems cover real analysis, mathematical algorithms and numerical precision, correct visualizations, as well as geometry. The third problem is the most interesting one in my opinion, and could become a subject of active mathematical research with one new great, unsolved conjecture being proposed, of a probabilistic nature. The last problem has many applications in engineering science. Note the alternance of the signs.

SenseTime Group Ltd. has raised $600 million from Alibaba Group Holding Ltd. and other investors at a valuation of more than $3 billion, becoming the world's most valuable artificial intelligence startup. The company, which specializes in systems that analyze faces and images on an enormous scale, said it closed a Series C round in recent months in which Singaporean state investment firm Temasek Holdings Pte and retailer Suning.com SenseTime didn't outline individual investments, but Alibaba was said to have sought the biggest stake in the three-year-old startup. With the deal, SenseTime has doubled its valuation in a few months. Backed by Qualcomm Inc., it underscores its status as one of a crop of homegrown firms spearheading Beijing's ambition to become the leader in AI by 2030.

Visitors watch a robot dance at the World Robot Conference 2017 in Beijing, capital of China, Aug. 25, 2017. Over 300 artificial intelligent (AI) specialists and representatives of over 150 robot enterprises attended the conference. BEIJING, April 7 (Xinhua) -- A government program is training 500 university teachers and 5,000 students in artificial intelligence (AI). The program organized by the Ministry of Education, Peking University and Innovation Works (a Beijing incubator) will continue for five years. Last year, China's cabinet issued an AI development outline, stressing the need to train AI talent and attract the world's leading professionals to China.

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.

Information retrieval and binary classification can be considered equivalent problems in principle. Information retrieval means to mark documents in a set of candidate documents as relevant or non-relevant for some question, on the basis of the properties of the documents. For binary classification, the problem is to distinguish between the'positive' and'negative' instances from a dataset, based on the features of the instances. Hence, from an abstract point of view, information retrieval is a special case of binary classification, with the documents being instances, the document properties being features and'relevant' being translated as'positive'. In practice, however, the general concepts from binary classification are not always helpful for information retrieval applications. The fact that often the proportion of relevant documents in a set of documents subject to a search is small or even very small is only one of the reasons for information retrieval to be considered a field of research for its own. As a consequence, some performance measures for information retrieval methods differ from those in use for binary classifiers or are called by different names. Precision and recall are possibly the most popular performance measures(see Chapter 8 of Manning et al., 2008, for a list of performance measures) for information retrieval methods: - Precision is the proportion of documents (instances) that are truly relevant (positive) among those documents which have been predicted relevant (positive). The term precision is also commonly used (with the same meaning) in binary classification.