Arriving at Creator, a new restaurant located on the ground floor of an office building on downtown San Francisco's Folsom Street, feels like walking into a catalog. Sleek, wooden communal tables with high white stools line one end of the room, with a bookshelf full of hand-picked culinary books against the wall and modern light fixtures overhead. It's what you would have imagined a restaurant eventually looking like if you watched a lot of The Jetsons. Those machines, with large transparent glass casings and ingredients in cylindrical tubes, are Creator's burger-making robots. Each 14-foot device contains around 350 sensors and 20 microcomputers to produce the best, freshest, locally sourced cheeseburger that $6 can get you in America's most expensive city.

Executives from the Taiwanese contract electronics company Foxconn made high-profile visits to the United States during the last few weeks. They announced a new company in Silicon Valley that will focus on artificial intelligence (AI). And Foxconn's founder joined President Donald Trump for a ground-breaking ceremony at a new factory in Wisconsin. Foxconn, also known as Hon Hai Precision Industry, is the world's largest contract maker of electronics. It operates factories across China and is most well-known for making phones and other devices for Apple.

What is the relationship between machine learning and optimization? On the other hand, what happens when machine learning is used to solve optimization problems? Consider this: a UPS driver with 25 packages has 15 trillion possible routes to choose from. And if each driver drives just one more mile each day than necessary, the company would be losing $30 million a year. While UPS would have all the data for their trucks and routes, there is no way they can run 15 trillion computations per each driver with 25 packages.

When analyzing empirical data, we often find that global linear models overestimate the number of parameters required. In such cases, we may ask whether the data lies on or near a manifold or a set of manifolds (a so-called multi-manifold) of lower dimension than the ambient space. This question can be phrased as a (multi-) manifold hypothesis. The identification of such intrinsic multiscale features is a cornerstone of data analysis and representation and has given rise to a large body of work on manifold learning. In this work, we review key results on multi-scale data analysis and intrinsic dimension followed by the introduction of a heuristic, multiscale framework for testing the multi-manifold hypothesis. Our method implements a hypothesis test on a set of spline-interpolated manifolds constructed from variance-based intrinsic dimensions. The workflow is suitable for empirical data analysis as we demonstrate on two use cases.

Many if not most large enterprises run hybrid computing environments and are looking for management software flexible enough to run in and manage assets across private and public clouds. Against this backdrop, BMC has rebuilt its venerable IT service-management product suite to run on a range of cloud platforms while incorporating machine learning to enhance predictive-analysis capabilities. The BMC Helix Cognitive Service Management is a software-as-a-service (SaaS) offering that runs on Amazon Web Services as well as BMC's own cloud. It will be available for Azure in the fourth quarter and for Google Public Cloud at the end of the year or beginning of next year, BMC said. The software is designed to manage applications, IT services and the infrastructure underneath those services.

The nonprofit MathandCoding, a San Francisco Bay Area-based organization that teaches coding to kids, June 11 announced it has expanded its offering to include machine learning and engineering workshops to its lessons. The organization as a whole has grown since being founded by three high school students to hold lessons at more than 25 libraries and community centers throughout the area. The success has led to co-founder Anika Cheerla saying the organization has ventured into physics, engineering and machine learning. MathandCoding started machine learning and AI for Girls initiative about a year ago to encourage middle and high school girls to learn machine learning and artificial intelligence, which Cheerla said are the future technologies sweeping all facets of life. "It was received with a lot of enthusiasm," the Indian American said in an email to India-West of the workshop, where students learn to use open databases to create models and do predications.

Kroger and Nuro executives said delivering groceries without drivers--while still years away--would make such services cheaper and easier to introduce in less densely populated parts of the country. Nearly a third of 4,504 adults surveyed by Forrester Analytics earlier this year said they didn't do more grocery shopping online because of costs including delivery charges. "We are not trying to be a dollar cheaper than regular delivery. We are trying to be an order of magnitude cheaper," said Dave Ferguson, who helped lead Google parent Alphabet Inc.'s GOOGL 0.21% self-driving vehicle arm before co-founding Mountain View, Calif.-based Nuro in 2016. The Nuro partnership is the third deal Kroger has made in the past two months that aims to aid in how it sells to customers as competitors Amazon.com

On the windy afternoon of March 17, 2017, I opened my mailbox and saw a white envelope from the San Francisco Unified School District. The envelope contained a letter assigning my younger daughter to a middle school. This letter was a big deal; San Francisco's public schools range from excellent to among the worst in the state, and kids are assigned to them through a lottery. The last time we put her name into the lottery, for kindergarten, she was assigned to one of the lowest-performing schools in California. Then we got a break: A private school offered a big discount on tuition.

SYDNEY – Australia will invest 7 billion Australian dollars ($5.2 billion) to develop and buy high-tech U.S. drones for joint military operations and to monitor waters including the South China Sea, it said Tuesday. Canberra has been embarking on its largest peacetime naval investment through a massive shipbuilding strategy that includes new submarines, offshore patrol vessels and frigates to shore up its defense capabilities. As part of this, the government will spend AU$1.4 billion to buy the first of six MQ-4C Triton maritime surveillance drones, with the aircraft to enter service from mid-2023, complementing seven P-8A Poseidon planes currently in use. "Together these aircraft will significantly enhance our anti-submarine warfare and maritime strike capability, as well as our search and rescue capability," Prime Minister Malcolm Turnbull said in a statement. "This investment will protect our borders and make our region more secure."

Flocks of robotic birds are taking to the skies of China equipped with high-tech surveillance technology, according to a report. The so-called "spy bird" programme, first reported by the South China Morning Post, is already in operation in at least five provinces and provides another tendril in the country's already advanced surveillance network. The dove-like drones are being developed by researchers at Northwestern Polytechnical University in the Shaanxi province, who have previously worked on stealth fighter jets used by China's airforce. One of the researchers involved said the roll out of the technology was still in its early stages. "The scale is still small," said Yang Wenqing, an associate professor at the university's School of Aeronautics who worked on the programme.