SINGAPORE--New U.S. export controls may compel artificial-intelligence giant Nvidia to cancel billions of dollars in next-year orders for its advanced chips to China, a move that could deprive Chinese tech companies of crucial AI resources. The Santa Clara, Calif.-based company had already finished delivering orders of its advanced AI chips to China for this year, according to people familiar with the matter, and was pushing to deliver some 2024 orders in advance before the new rules were scheduled to come into effect in mid-November.

SINGAPORE--American workers hold key positions throughout China's domestic chip industry, helping manufacturers develop new chips to catch up with foreign rivals. Now, those workers are in limbo under new U.S. export control rules that prohibit U.S. citizens from supporting China's advanced chip development. At least 43 senior executives working with 16 publicly listed Chinese semiconductor companies are American citizens, according to an examination of company filings and official websites by The Wall Street Journal. Many of them hold C-suite titles, from chief executive to vice president and chairman. Almost all of the executives moved to China's chip industry after spending years working in Silicon Valley for U.S. chip makers or semiconductor equipment firms, according to the companies' filings.

At least 42 law enforcement agencies in Minnesota reportedly used Clearview AI facial recognition software, according to a Buzzfeed investigation. Questions about the softwares reliability and legal standing remain in limbo, according to law enforcement, artificial intelligence, and privacy experts. Clearview AI is a web-based platform that allows users to submit pictures for possible matches in a database of more than 3 billion images pulled from open source websites, including news sites and social media, according to the company's web page. The company also boasted of a 100% accuracy rate at one point, according to a document obtained by a public records request from Buzzfeed. However, questions about the software's reliability and legal standing remain in limbo, according to law enforcement and artificial intelligence and privacy experts.

Police forces, hospitals and councils struggle to understand how to use artificial intelligence because of a lack of clear ethical guidance from the government, according to the country's only surveillance regulator. The surveillance camera commissioner, Tony Porter, said he received requests for guidance all the time from public bodies which do not know where the limits lie when it comes to the use of facial, biometric and lip-reading technology. "Facial recognition technology is now being sold as standard in CCTV systems, for example, so hospitals are having to work out if they should use it," Porter said. "Police are increasingly wearing body cameras. What are the appropriate limits for their use? "The problem is that there is insufficient guidance for public bodies to know what is appropriate and what is not, and the public have no idea what is going on because there is no real transparency." The watchdog's comments came as it emerged that Downing Street had commissioned a review led by the Committee on Standards in Public Life, whose chairman had called on public bodies to reveal when they use algorithms in decision making. Lord Evans, a former MI5 chief, told the Sunday Telegraph that "it was very difficult to find out where AI is being used in the public sector" and that "at the very minimum, it should be visible, and declared, where it has the potential for impacting on civil liberties and human rights and freedoms". AI is increasingly deployed across the public sector in surveillance and elsewhere. The high court ruled in September that the police use of automatic facial recognition technology to scan people in crowds was lawful. Its use by South Wales police was challenged by Ed Bridges, a former Lib Dem councillor, who noticed the cameras when he went out to buy a lunchtime sandwich, but the court held that the intrusion into privacy was proportionate. Durham police have spent three years evaluating an AI tool devised by Cambridge University to predict whether an arrested person is likely to reoffend and so should not be released on bail. Similar technologies used in the US, where they are also guide sentencing, have been accused of concluding that black people are more likely to be future criminals, but the results of the British trial are yet to be made public. The committee is due to report to Boris Johnson in February, but Porter said the task was urgent because of the rapid pace of technological change and an unclear system of regulation in which no single body had oversight. The information commissioner is responsible for the use of personal data but not surveillance, while Porter's office regulates the use of CCTV systems and all technologies attached to them, including facial recognition and lip-reading software. "We've been calling for a wider review for months," Porter said. "The SCC, for example, is the only surveillance regulator in England and Wales and we date back to when the iPhone 5 was new and exciting.

Environmental and financial crises loom and we feel we have no influence. If society has already reduced us to a childlike state of weakness, isolation and vulnerability, it is perhaps no surprise that modern pop culture and technology tend towards infantilisation, and that many video games function as childish wish fulfilment. By turning us into star footballers or super space marines, they reconstruct adolescent fantasies of proficiency and heroism. Yet some games have begun to depict a childhood experience more in tune with the current social context. These games make us play as children, and in doing so often accentuate feelings of powerlessness and fear.

Baidu (BIDU) stock sold off Friday as analysts pondered whether its push into artificial intelligence will stall in the wake of its chief operating officer stepping down. COO Qi Lu, a former Microsoft (MSFT) executive, headed Baidu's artificial intelligence research. Baidu is just one stock to watch for artificial intelligence developments. The China-based internet search leader fell 7.4% to 259 on the stock market today, tumbling out of a buy zone. Credit Suisse downgraded Baidu to neutral on the management shake-up, announced late Thursday.

FILE - In this April 6, 2016, file photo, Iranian students prepare their robots during the international robotics competition, RoboCup Iran Open 2016, in Tehran, Iran. Universities in the U.S. say President Donald Trump's revised travel ban would block hundreds of graduate students who play key roles in research. Twenty-five of America's largest universities told The Associated Press they've sent acceptance letters to more than 500 students from the six banned countries for next fall, mostly from Iran, who are known for their strength in engineering and sciences.

Memory researchers have shone light into a cognitive limbo. A new memory--the name of someone you've just met, for example--is held for seconds in so-called working memory, as your brain's neurons continue to fire. If the person is important to you, the name will over a few days enter your long-term memory, preserved by permanently altered neural connections. But where does it go during the in-between hours, when it has left your standard working memory and is not yet embedded in long-term memory? To figure this out, a research team resurrects memories from this limbo. Their observations point to a new form of working memory, which they dub prioritized long-term memory, that exists without elevated neural activity. Consistent with other recent work, the study suggests that information can somehow be held among the synapses that connect neurons, even after conventional working memory has faded. This new memory state could have a range of practical implications, from helping college students learn more efficiently to assisting people with memory-related neurological conditions such as amnesia, epilepsy, and schizophrenia.

Bayesian Optimization (BO) is designed for the most challenging ones: when the gradient is unknown, evaluating a solution is costly, and evaluations are noisy. This is, for instance, the case when we want to find optimal parameters for a machine learning algorithm [Snoek et al., 2012], because testing a set of parameters can take hours, and because of the stochastic nature of many machine learning algorithms. Besides parameter tuning, Bayesian optimization recently attracted a lot of interest for direct policy search in robot learning [Lizotte et al., 2007, Wilson et al., 2014, Calandra et al., 2016] and online adaptation; for example, it was recently used to allow a legged robot to learn a new gait after a mechanical damage in about 10-15 trials (2 minutes) [Cully et al., 2015]. At its core, Bayesian optimization builds a probabilistic model of the function to be optimized (the reward/performance/cost function) using the samples that have already been evaluated [Shahriari et al., 2016]; usually, this model is a Gaussian process [Williams and Rasmussen, 2006]. To select the next sample to be evaluated, Bayesian optimization optimizes an acquisition function which leverages the model to predict the most promising areas of the search space.