We'll be talking about everyone's favorite topic at the moment: facial recognition. First San Francisco, Somerville ... now Oakland: California's Oakland has become the third US city to ban its local government using facial recognition technology, after its council passed an ordinance this week. Council member Rebecca Kaplan submitted the ordinance for city officials to consider earlier this year in June. The document describes the shortcomings of the technology and why it should be banned. "The City of Oakland should reject the use of this flawed technology on the following basis: 1) systems rely on biased datasets with high levels of inaccuracy; 2) a lack of standards around the use and sharing of this technology; 3) the invasive nature of the technology; 4) and the potential abuses of data by our government that could lead to persecution of minority groups," according to the ordinance.

The public sector has a crucial role to play in India's growth story. It is through an effective and efficient public service delivery model that India can achieve inclusive and sustainable socio-economic development. In order to achieve this, the government has begun harnessing artificial intelligence (AI) in the delivery of public services such as education, health, social security and transport, among others. AI is set to offer a competitive advantage over existing models of delivery of public services. Traditionally, the delivery models were simple, standalone departmental projects.

Fernando "Corby" Corbató, an MIT professor emeritus whose work in the 1960s on time-sharing systems broke important ground in democratizing the use of computers, died on Friday, July 12, at his home in Newburyport, Massachusetts. Decades before the existence of concepts like cybersecurity and the cloud, Corbató led the development of one of the world's first operating systems. His "Compatible Time-Sharing System" (CTSS) allowed multiple people to use a computer at the same time, greatly increasing the speed at which programmers could work. It's also widely credited as the first computer system to use passwords. After CTSS Corbató led a time-sharing effort called Multics, which directly inspired operating systems like Linux and laid the foundation for many aspects of modern computing.

Matrix-variate distributions can intuitively model the dependence structure of matrix-valued observations that arise in applications with multivariate time series, spatio-temporal or repeated measures. This paper develops an Expectation-Maximization algorithm for discriminant analysis and classification with matrix-variate $t$-distributions. The methodology shows promise on simulated datasets or when applied to the forensic matching of fractured surfaces or the classification of functional Magnetic Resonance, satellite or hand gestures images.

Way out, beyond the heliosphere, an A.I. aboard NASA space probe Voyager 3 generates free jazz - broadcast via livestream 24/7 - until we lose contact. Its artificial neural network was trained on John Coltrane's INTERSTELLAR SPACE with modified SampleRNN. It listened to the album 16 times then continued to make music in the style. Voyager 1 and 2 launched in 1977 carrying a mixtape Carl Sagan made called THE SOUNDS OF EARTH. It featured Blind Willie Johnson, Chuck Berry, recordings of laughter, Beethoven, Bach, Stravinsky, along with diagrams of human reproductive organs. It was intended for an audience of intelligent extraterrestrial lifeforms.

AI, which is supposed to stand for "artificial intelligence," now spans applications from cameras to the military to medicine. One thing we can be sure about AI -- because we are told it so often and at so increasingly high a pitch -- is that whatever it actually is, the national interest demands more of it. And we need it now, or else China will beat us there, and we certainly wouldn't want that, would we? What does it look like, how would it work, and how would it change our society? The race is on, and if America doesn't start taking AI seriously, we're going to find ourselves the losers in an ever-widening Dystopia Gap.

SINGAPORE - The use of artificial intelligence (AI) will not make soldiers obsolete, but it might redefine their roles in the future, said expert panellists at a technology summit on Thursday (June 27). In fact, soldiers could become more proficient if they are technically skilled and are able to make use of AI systems to their advantage, they added. Speaking at the second Singapore Defence Technology Summit, Israeli computer scientist Yaniv Altshuler said it is "not so unlikely" to foresee a future where soldiers operate a swarm of armoured, autonomous, or semi-autonomous vehicles remotely. "Now, you see soldiers or pilots actually graduating from flying academies and they are flying drones. Do you call them pilots, or are pilots now redundant?... I think the same would be with soldiers," he said.

China has been often touted as the fastest emerging hub for AI development, even surpassing the superpowers such as the USA in the emerging tech. Chinese companies and government are taking the analytics and AI play quite seriously, bringing newer and favourable policies around its adoption. Numbers suggest that in 2018, 60 per cent of total global AI investments poured into China with investments from VCs, private equity and the Chinese government. Not just the companies but educational institutes are taking AI seriously as many schools are teaching AI courses to make its citizens AI-ready. There is no doubt that China has been serious about its AI strategy, but is its power and supremacy in artificial intelligence real or exaggerated?

Fast forward 50 years and the processing power of the Apollo Guidance Computer (AGC) that took those men to the surface of the moon is now in your pocket, multiple times over-- in fact, an iPhone 6 could be used to guide 120 million Apollo 11 spacecraft to the moon, all at the same time. This factoid doesn't really do justice to the brilliance of the AGC. Given Moore's law, you could pick anything computational and say that 50 years later, there will exist a machine that can run it 2²⁵ faster. It was people like Margaret Hamilton, the lead for the software team who coded the AGC, who chose not to see current hardware limitations as a barrier, but instead as a challenge. She used the resource available to her at the time to achieve the unthinkable.

The financial services industry has seen an explosive growth in Artificial Intelligence (AI) to supplement, and often supplant, existing processes both customer-facing and internal. Given the potential created by rapid advancements in AI sophistication and functionality, more and more financial services firms are leveraging the technology to deploy new use cases for improved decision-making processes – particularly in the areas of anti-money laundering, fraud prevention, risk management, and lending. While the first wave of AI was generally focused on automating manually-intensive and repetitive tasks, banks are now turning to machine learning systems (ML) to uncover more dynamic ways of interpreting their vast swaths of customer data. Whereas AI, at a fundamental level, permits a machine to imitate intelligent human behavior, ML is a specific application (or subset) of AI that enables systems automatically to learn and improve – e.g., reduce errors or maximize the likelihood that their predictions will be true – without being explicitly programmed to make such adjustments. This development has an exciting potential to expand the products available to underbanked communities and improve services and customer experience as a whole.