On the other side of the world, there is a remote and mysterious land where countries and companies alike go to perform dangerous underground experiments. Between 1952 and 1958, the United Kingdom conducted multiple nuclear weapons trials there, using highly radioactive materials, the locals kept mostly unaware of the risks. China allegedly uses the place to test its influence campaigns, including “strategies for breaking up the global reach of the United States.” It has a relatively small, uninfluential economy, making it a great place to play around with money: Private equity firms have used it to test “so-called unitranche loans,” popular in the U.S. and Europe but untested in the region, while it’s also been called the “ideal testing ground for blockchain-based trading” due to the lack of fragmentation in its markets. Domino’s, meanwhile, tested pizza-delivering robots there.
The most far-reaching experiments, however, are conducted from afar. Managed from across the Pacific, in Silicon Valley, they take place on the inhabitants’ smartphones. Facebook, Spotify, Tinder—all have used the society as a test dummy for new features.
Regina Barzilay and James Collins have been named the faculty co-leads of the Abdul Latif Jameel Clinic for Machine Learning in Health, or J-Clinic, effective immediately, announced Anantha Chandrakasan, dean of the School of Engineering and chair of J-Clinic. Institute Professor Philip Sharp will also serve as the chair of J-Clinic’s advisory board.
Launched on Sept. 17, J-Clinic is the fourth major collaborative effort between MIT and Community Jameel, the social enterprise organization founded and chaired by Mohammed Abdul Latif Jameel ’78. A key part of the MIT Quest for Intelligence, J-Clinic will focus on developing machine learning technologies to revolutionize the prevention, detection, and treatment of disease. It will concentrate on creating and commercializing high-precision, affordable, and scalable machine learning technologies in areas of health care ranging from diagnostics to pharmaceuticals.
Travel-booking app Hopper is taking a big leap this morning, announcing a $100 million venture funding round.
The Series D financing was led by Omers Ventures. Other investors in the round included new backer Citi Ventures, as well as earlier Hopper investors Caisse de dépôt et placement du Québec (CDPQ), Accomplice, Brightspark Ventures, Investissement Québec, and BDC Capital IT Venture Fund.
Hopper says the new money will be used to speed up its international expansion and fund further development of artificial intelligence technologies that power its product. The company says it has raised $184 million in venture funding to date.
Rethink Robotics, the Boston, Mass.-based maker of collaborative robots Baxter and Sawyer, shut its doors today. Rethink was founded in 2008 and raised nearly $150 million to date, according to Crunchbase. Its last round of funding was an $18 million Series E in August 2017.
PR Newswire, University of Illinois Gies College of Business
from
Mao Ye, associate professor of finance at Gies College of Business, has been awarded a $422,288 grant over four years from the National Science Foundation to further research that could lay the groundwork for important public policy changes on Wall Street. Fellow Gies Business professors Alex Chinco and Adam Clark-Joseph are co-Principal Investigators on the project. The National Center for Supercomputing Applications on the University of Illinois campus will receive another $400,000 to help store and analyze relevant data.
Burger King’s newest TV ad campaign claims each spot was “created by artificial intelligence,” an explanation that precedes some truly bizarre voice-overs, such as, “Bed of lettuce for you to sleep on, bed of mayonnaise for extra sleep,” and, “Burger King logo’s chicken is the new potato.”
In a statement announcing the campaign—which will air during prime time on cable networks including MTV, History, TBS, Adult Swim and E!—the brand refers to as the creation of “a new deep learning algorithm that could give a glimpse into what the future of marketing and communications could look like.”
Is that true? No. It’s all one big joke at AI’s expense. But the laughs are real.
“This is when I start feeling my age,” says Anne Corcoran. She’s a scientist at the Babraham Institute, a human biology research centre in Cambridge, UK. Corcoran leads a group that looks at how our genomes – the DNA coiled in almost every cell in our bodies – relate to our immune systems, and specifically to the antibodies we make to defend against infection.
She is, in her own words, an “old-school biologist”, brought up on the skills of pipettes and Petri dishes and protective goggles, the science of experiments with glassware on benches – what’s known as “wet lab” work. “I knew what a gene looked like on a gel,” she says, thinking back to her early career.
These days that skill set is not enough. “When I started hiring PhD students 15 years ago, they were entirely wet lab,” Corcoran says. “Now when we recruit them, the first thing we look for is if they can cope with complex bioinformatic analysis.” To be a biologist, nowadays, you need to be a statistician, or even a programmer. You need to be able to work with algorithms.
Honda is investing $750 million in Cruise, the self-driving car startup whose majority shareholder is General Motors. The deal values Cruise at $14.6 billion. The deal is important for Honda because until now it has been a laggard in the race to build self-driving cars.
Honda also said on Wednesday that it plans to invest $2 billion over the next 12 years to develop and manufacture self-driving cars based on Cruise’s software.
There’s a mine, deep underground in Canada, that’s unlike any other. Just outside of Sudbury, Ontario, in a forest where curious bears frequently forage for raspberries in backyards, Creighton Mine workers in blue hard hats extract nickel from deep below the ground. But when they enter the half-open, jittery pitch-black lift to descend into the spacious cavern, they share the ride with a bunch of other hard-hatted folks. Their hats are orange though, and they are mining for something completely different: nothing.
That is, nothing so far. The fellow miners are actually physicists working at a massive, subterranean lab dubbed SNOLAB. It’s located at a depth of two kilometres – so deep you could easily stack four and a half Empire State buildings into this hole, one on top of the other. SNOLAB detectors scour the cosmos for the elusive stuff thought to make up the bulk of matter in our universe: dark matter. It’s an almighty, and thus far unfruitful, search.
So far, we have been able to detect only a measly five per cent of all matter in the universe; this atomic matter makes up all the galaxies and stars, planets, black holes, quasars, pulsars, neutrinos – as well as humans and all other life on Earth. The rest is unknown stuff, dark matter (25 per cent) and even the more enigmatic dark energy (70 per cent). We can observe dark matter’s gravitational effects on stars and galaxies but can’t seem to net its “dark” particles with any of our instruments. And boy have we tried.
University of Southern California, Viterbi School of Engineering
from
How to make scientific collaboration across colleagues and continents run smoothly? That’s what computer scientist, Ewa Deelman, a research director at USC ISI, does. As scientists work with myriad data points and pull in data from sensors all over the world, they need to work collaboratively utilize distributed resources to do complex scientific computations. Instead of reinventing the wheel for each project, Deelman creates computational tools for scientists to collaborate. One can say she creates the complex cyber ‘plumbing’ so that data can flow freely between, and be crunched easily by researchers to advance scientific knowledge.
Deelman’s systems have been leveraged by the Nobel Prize winning scientists who directly detected gravitational waves and by biologists and seismologists. Her lab at USC ISI will now lead an effort to conduct a pilot study for a potential Cyberinfrastructure Center of Excellence. Collaborating with computer scientists at the University of North Carolina’s Renaissance Computing Institute, the University of Utah, Indiana University and the University of Notre Dame she will work on developing a cyberinfrastructure blueprint that could support scientists working on various high-profile National Science Foundation (NSF) programs.
Data scientist is the hottest occupation in the country, and on October 1 BU President Robert A. Brown announced that the University plans to be a leader in educating the next generation in the field by building a dramatic 17-floor tower on Commonwealth Avenue to house the new BU Data Sciences Center.
“This is the science that’s going to change the way we behave, driving our behavior for the next 50 or 100 years,” Brown says.
With the proposed project, BU would build the first major teaching center on the Charles River Campus in a half century, and the tallest building on campus. By bringing the mathematics and statistics and computer science departments under one roof, BU will also further its efforts to become one of the leading urban interdisciplinary research institutions in the country.
MapD is a name that has served us amazingly well for the first 5 years of our journey. Originating from my research at MIT’s Computer Science and AI Laboratory, our platform is now being used by major businesses and government agencies around the world, and we’ve created a community of passionate adopters. Our company is growing fast, and our customers are transforming how they do big data analytics everyday.
“Submissions are solicited for the NIPS 2018 AI for Social Good workshop focusing on social problems for which artificial intelligence has the potential to offer meaningful solutions.” Deadline for submissions is October 15.
Facebook Marketplace was introduced in 2016 as a place for people to buy and sell items within their local communities. Today in the U.S., more than one in three people on Facebook use Marketplace, buying and selling products in categories ranging from cars to shoes to dining tables. Managing the posting and selling of that volume of products with speed and relevance is a daunting task, and the fastest, most scalable way to handle that is to incorporate custom AI solutions.
On Marketplace’s second anniversary, we are sharing how we use AI to power it. Whether someone is discovering an item to buy, listing a product to sell, or communicating with a buyer or seller, AI is behind the scenes making the experience better. In addition to the product index and content retrieval systems, which leverage our AI-based computer vision and natural language processing (NLP) platforms, we recently launched some new features that make the process simpler for both buyers and sellers.