Machine learning started out as the idea of giving a machine human intelligence. The discipline was originally intertwined with artificial intelligence (AI), as scientists wove together the fields of computer science, mathematics, statistics, probability, expert systems and neural networks. The original benchmark for machine learning and artificial intelligence was the Turing Test, created by British mathematician and computer scientist Alan Turing. "A computer was said to be able to'thin' if a human interrogator could not tell it apart, through conversation, from a human being". Since then, machine learning has been reorganized as a separate field from AI, with the aim of finding solutions to solvable problems using methods based in statistics and probability theory.

Accenture's technology R&D head urges China to scale up smart machine trials at home and abroad, Chen Yingqun and Zhang Xia report. China should step up its efforts to adopt artificial intelligence in its industries to boost the country's economic transformation, according to French technology expert Marc Carrel-Billiard. The development of artificial intelligence is a hot topic in China, he said, especially since the central government unveiled the Made in China 2025 strategy, which largely aims to upgrade the manufacturing industry with high-technology over the next decade. AI refers to machines or systems that can understand, learn and act independently, allowing them to take on cognitive functions otherwise performed by a human, such as problem-solving. Carrel-Billiard said such technology is important due to the shift toward greater connectivity, either through cloud computing or smart networks.

The fact that Catherine - who's learned that her ex-husband Theodore has taken up with Samantha, a honey-voiced Operating System who screens his emails, entertains his fantasies and sends his writing off to publishers - comes off as judgmental is testament to Jonze's filmmaking skills. But it's also proof of how deeply we've internalised the notion that artificial intelligence is an extension of male desires and that, really, few things may be hotter than the hard-to-nail promise of female servitude. As Laurie Penny writes in an April 2016 article in The New Statesman, the issue of whether or not robots are slaves designed to serve their masters or sentient beings with inner lives and autonomous instincts has long paralleled the questions we ask of women in the world. READ MORE: * New Zealand could become first country to use Domino's pizza delivery robot * Drones, self-drive cars and'car butler' in our near future * Professor hopes robots will take over the rehabilitation world * Robots could threaten up to half New Zealand's jobs in next 20 years * Robots fooling humans they love something that can't love them back: AI expert * Self-learning robot escapes Russian facility, disrupts traffic * New robot from Google shows off human-like qualities Robots may take on domestic tasks and give working mothers more time. From Metropolis, the 1927 Fritz Lang classic in which Maria, a cyborg whose sultry ways plunge the city and its workers into chaos (she's later burned at a stake) to Austin Powers: International Man of Mystery, the hit 1997 spy film whose comely fembots are programmed to ensnare the bumbling Powers with his own libido, female robots are often cast as temptresses or destroyers, coincidentally enough, the same roles reserved for flesh-and-blood women.

Representations of probability measures in reproducing kernel Hilbert spaces provide a flexible framework for fully nonparametric hypothesis tests of independence, which can capture any type of departure from independence, including nonlinear associations and multivariate interactions. However, these approaches come with an at least quadratic computational cost in the number of observations, which can be prohibitive in many applications. Arguably, it is exactly in such large-scale datasets that capturing any type of dependence is of interest, so striking a favourable tradeoff between computational efficiency and test performance for kernel independence tests would have a direct impact on their applicability in practice. In this contribution, we provide an extensive study of the use of large-scale kernel approximations in the context of independence testing, contrasting block-based, Nystrom and random Fourier feature approaches. Through a variety of synthetic data experiments, it is demonstrated that our novel large scale methods give comparable performance with existing methods whilst using significantly less computation time and memory.

Artificial intelligence may be the new face of medical diagnostics. For the first time, a flavor of A.I. called deep learning is being implemented in new ultrasound imaging equipment to aid in breast exams and help patients avoid unnecessary biopsies. A new feature in Samsung Medison's ultrasound system uses a deep-learning algorithm to make recommendations about whether a breast abnormality is benign or cancerous. The "S-Detect for Breast" feature is now included in an upgrade to the company's RS80A ultrasound system and is commercially available in parts of Europe, the Middle East and Korea and is pending FDA approval in the U.S., according to PR manager Doug Kim. Deep learning relies on large amounts of data to inform complex decision-making algorithms, has aided in everything from speech and image recognition software to pharmaceutical research.

Optimization for machine learning is essential to ensure that data mining models can learn from training data in order to generalize to future test data. Data mining models can have millions of parameters that depend on the training data and, in general, have no analytic definition. In such cases, effective models with good generalization capabilities can only be found by using optimization strategies. Optimization algorithms come in all shapes and sizes, just like anything in life. Attempting to create a single optimization algorithm for all problems would be as foolhardy as seeking to create a single motor vehicle for all drivers --there is a reason we have semi-trucks, automobiles, motorcycles, etc.

It is not every day you see a runaway robot causing traffic chaos in a city centre - but in one Russian suburb is has happened twice in the last week. The robot, named Promobot, was being put through its paces at a research lab in the city of Perm in central Russia's Perm Krai region. In its first escape, the robot, designed to avoid obstacles and to turn around when it reached a boundary, had been left walking around an outside yard. This is the hilarious moment a runaway robot causes traffic chaos in a city centre. The robot - called Promobot - was being put through its paces at a research lab in the city of Perm in central Russia's Perm Krai region Promobot - short for Promotional Robot - is a unique robot created by Russian scientists and is designed to work in customer relations.

A robot in Russia caused an unusual traffic jam last week after it "escaped" from a research lab, and now, the artificially intelligent bot is making headlines again after it reportedly tried to flee a second time, according to news reports. Engineers at the Russian lab reprogrammed the intelligent machine, dubbed Promobot IR77, after last week's incident, but the robot recently made a second escape attempt, The Mirror reported. Last week, the robot made it approximately 160 feet to the street, before it lost power and "partially paralyzed" traffic. Promobot, the company that designed the robot, announced the escapade in a blog post the next day. The strange escape has drawn skepticism from some who think it was a promotional stunt, but regardless of whether the incident was planned, the designers seem to be capitalizing on all the attention.

Designers of a Russian robot which made a break for it it after researchers left a door open have received pleas not to terminate it. 'Promobot' escaped from a testing facility in the city of Perm in central Russia's Perm Krai region earlier this month, and its designers are considering recycling the robot. But the digital creators have received impassioned pleas from members of the public, begging them not to destroy the unique robot just because of its wanderlust. Promobot (pictured) is due to be decommissioned after repeated escapes from a Russian research lab. But the robot's designers have received pleas from the public asking them not to'kill' the robot Promobot - short for Promotional Robot - is a unique robot created by Russian scientists and is designed to work in customer relations.

Long ago I lived in Santa Cruz, California. Almost every morning I would throw on a wet suit, grab my surfboard out of the garage, and head to the rocky cliffs just a few blocks from my house. I would descend a well-worn path to the ocean below, paddle out to the break, and spend hours surrounded by kelp beds and barking sea lions, catching waves, feeling exhilarated, and floating on my board, a world away from the troubles on land. I have a family now and have lived for years in the generally wave-less realms of New York City. But a few months ago I suddenly felt that old hunger again. I wanted to race out to the garage and grab a board.