Sumit Paul-Choudhury picks out trends that could shape music over the coming decades, including algoraves, Fortnite concerts and songs catered to smart speakers.
Microsoft is playing catch-up in Africa’s growing tech community. Last month Google opened an AI research centre in the Ghanaian capital Accra. The centre will draw on local machine learning researchers and engineers to drive AI development in the region. Huawei has announced plans for two data centres in Africa; and last year Amazon Web Services announced it would open its first African data centre in 2020.
Enter TikTok, whose parent company ByteDance is reported to be prepping a streaming service. TikTok has more than 30% penetration among 16-19s and is the heir apparent to Musically, which Byte Dance acquired before then shuttering. TikTok lets its users express themselves with music as the soundtrack and has the power to turn obscure tracks into viral megahits. Let’s work on the assumption that ByteDance leverages its TikTok assets and doesn’t get browbeaten by rightsholders into launching a Spotify clone (the fact it has focused so far on non-western labels like T-Series suggests it is looking to break the licensing mould). The combination of a fandom-focused streaming service that also looks like it will be targeted at emerging markets could spur the next stage of streaming growth. So far only Tencent has successfully monetised fandom at scale. Now ByteDance looks set to follow suit. Western streaming services can either watch from the side lines or start working with rightsholders to bring heart and soul back to music. The future is monetising fandom.
When Yale recently decided to relocate three-quarters of the books in its undergraduate library to create more study space, the students loudly protested. In a passionate op-ed in the Yale Daily News, one student accused the university librarian—who oversees 15 million books in Yale’s extensive library system—of failing to “understand the crucial relationship of books to education.” A sit-in, or rather a “browse-in,” was held in Bass Library to show the administration how college students still value the presence of books. Eventually the number of volumes that would remain was expanded, at the cost of reducing the number of proposed additional seats in a busy central location.
Little-noticed in this minor skirmish over the future of the library was a much bigger story about the changing relationship between college students and books. Buried in a slide deck about circulation statistics from Yale’s library was an unsettling fact: There has been a 64 percent decline in the number of books checked out by undergraduates from Bass Library over the past decade.
[Giorgia] Lupi describes her profession as “telling stories with data,” which sounds like an oxymoron, until you see her work. For the Milan Design Triennial, Lupi and her previous design studio, Accurat, created a so-called data tapestry, made up of horizontal bands crosshatched with vertical lines, that wraps around three sides of a gallery, titled “The Room of Change.” Each horizontal band represents a different data set, ranging from world population to animal extinctions, alcohol consumption, and technology access. Each vertical slice represents a moment in time. The wow factor comes when you step back and realize that all those numbers—all that data—look from afar like the sketch for a Bauhaus tapestry, done in colored pencil. The installation works as both visual art and a narrative of environmental decline.
Lupi calls what she does “data humanism,” a reaction against the computer-generated, harsh-toned bar graphs, pie charts, and rows of tiny humans that leapt from corporate reports into mainstream media in the nineties. In a manifesto of sorts that was published in Print magazine, Lupi writes how “ ‘cool’ infographics promised us the key to master this untamable complexity.” When that did not work out, “we were left with gigabytes of unreadable 3D pie charts and cheap translucent user interfaces full of widgets.” The ostensibly neutral visual language of these graphics suggested authority, but they could easily mislead or be misread. What was needed was a more honest, approachable, graspable way to present data.
“Performing for the USPS on this pilot in this particular commercial corridor gives us specific use cases to help us validate our system and expedite the technological development and commercialization progress,” said Xiaodi Hou, president and chief technology officer of TuSimple.
Donald Trump has long blamed Amazon for the woes of the United States Postal Service (USPS) and has called on the government agency to charge the ecommerce platform more for shipping to compensate for billions in annual losses he attributes to Amazon. In 2018 in particular, the USPS lost $3.9 billion and saw volume drop by 3.2 billion packages.
Once treated by the field with skepticism (if not outright derision), the artificial neural networks that 2018 ACM A.M. Turing Award recipients Geoffrey Hinton, Yann LeCun, and Yoshua Bengio spent their careers developing are today an integral component of everything from search to content filtering. So what of the now-red-hot field of deep learning and artificial intelligence (AI)? Here, the three researchers share what they find exciting, and which challenges remain.
Declaring that the scale of the opportunities and challenges facing the world “demands that we be bold,” President Marc Tessier-Lavigne unveiled “A Vision for Stanford,” a long-range plan designed to guide Stanford for the next decade and beyond, at Thursday’s annual Academic Council meeting. … Two years in the making and engaging thousands of Stanford community members in the process, the plan is structured under three overarching themes:
The National Oceanic and Atmospheric Administration is about to roll out the new version of its main weather forecasting model next month — but it won’t help the agency gain much ground against its international rivals for the title of having the world’s most accurate weather model.
Why it matters: Weather forecasting today relies on numerical prediction models that simulate the current and future state of the atmosphere. If the most commonly used computer model is off target during high-impact weather events, it can affect the larger economy and possibly even cost lives.
Donald Trump, the diplomatic pugilist, doesn’t agree particularly often with other countries, be they friends of foes. An exception is the topic of artificial intelligence.
His administration signed on last week to a set of A.I. principles advocated by the Organization for Economic Co-operation and Development, a group of generally rich nations that doesn’t include China. The principles are mostly fluffy stuff, not unlike Trump’s own executive order in February advocating for the U.S. having an A.I. policy in the first place. The OECD principles support A.I. being a force for “inclusive growth,” respectful of the rule of law, responsibly transparent, and so on. It all sounds a bit like an international bureaucrat’s version of motherhood and apple pie.
Still, if the choice is between the U.S. joining with other nations on important global policy frameworks or not joining with them, the former is undeniably better. The move speaks to the influence of Trump technology advisor Michael Kratsios, an outspoken advocate for A.I. policy.
The film world is full of intriguing what-ifs. Will Smith famously turned down the role of Neo in The Matrix. Nicolas Cage was cast as the lead in Tim Burton’s Superman Lives, but he only had time to try on the costume before the film was canned. Actors and directors are forever glancing off projects that never get made or that get made by someone else, and fans are left wondering what might have been.
For the people who make money from movies, that isn’t good enough.
If casting Alicia Vikander instead of Gal Gadot is the difference between a flop and smash hit, they want to know. If a movie that bombs in the US would have set box office records across Europe, they want to know. And now, artificial intelligence can tell them.
Apple says, “What happens on your iPhone stays on your iPhone.” Our privacy experiment showed 5,400 hidden app trackers guzzled our data — in a single week.
Arm, the company that designs the basic chip architecture for most of the world’s smartphones, today announced the launch of its next suite of designs for premium phones. It’ll be a while before you’ll see the first phones that use chips based on this design, but typically we see the first actual chips before the end of the year. With this launch, the company is announcing the Cortex-A77 CPU, the Mali-G77 GPU and a more energy efficient and powerful machine learning processor.
Given recent trends, it’s no surprise that the new Cortex-A77 doesn’t only focus on overall performance improvements, though the company’s promise of 20% IPC performance improvement over the last generation is nothing to sneer at. Thanks to a combination of hardware and software optimizations, the Cortex-A77 now promises significantly better machine learning performance, too.
A new analysis by two economists takes issue with those who argue that liberal arts education is not worth the investment.
Catharine B. Hill and Elizabeth Davidson, of the Andrew W. Mellon Foundation, looked at how much graduates with a liberal arts education can earn. They found that while liberal arts majors may not earn as much engineers, they do well, showing that critics are incorrect about the worth of the degree.
That brings us to the post below, written by Donald Lazere, professor emeritus of English at California Polytechnic State University at San Luis Obispo, who asks and answers the following question: If a liberal arts education isn’t worth the money, as critics contend, why do the United States’ wealthy families want their children to get one?
Facebook Research’s goal for this RFP “is to help the academic community to address problems in the area of safer online conversations. This includes problems around misinformation, as well as hate speech and inauthentic online behavior, to name a few. The grant aims to provide funding for projects that build research infrastructure such as datasets or evaluation platforms that can accelerate research in a broader way.” Deadline for submissions is June 20.
“If you’re training a model, calculating analytics, or just combining data from multiple sources and loading them into another system, you’ll need to build a data processing or ETL1 pipeline. … The problems we work on are challenging, so the solutions can be complex, but we don’t want to introduce complexity where’s it’s not needed. Because we must support our work in production, our small teams share the responsibility of being on-call and help support each other’s pipelines. This allows us to do important things, like take vacation. This summer, my wife and I are heading to Italy to take the honeymoon we meant to take years ago. The last thing I want to think about while I’m there is whether my teammates are struggling to support and understand the pipelines that I wrote.”