Explore Sway navigation

Specific topics in this chapter include the following:

  • Creating a Sway account
  • Finding your way around Sway
  • Creating a new Sway
  • Signing in and out of Sway

Getting started with Sway is easy—sign up using your Microsoft account and begin designing. You can create a Sway from scratch or convert a Word document, PowerPoint presentation, or PDF to Sway. If you’re not sure where to begin, view sample Sways to discover how they were designed and use these for inspiration or as a template for your own Sways.

 

Creating a Sway Account

Creating an account on Sway is a simple, straightforward process. All you need is a Microsoft account and access to the Internet through your computer or iOS mobile device.

Navigate to https://sway.com in your browser, and then click the Get Started button.

  1. Enter the email address of the Microsoft account you want to use with Sway.
  2. Click the Next button.
  3. Enter your password.
  4. If you want to remain signed in, select the Keep Me Signed In check box.

Popular compiler yields more efficient parallel programs

Compilers are programs that convert computer code written in high-level languages intelligible to humans into low-level instructions executable by machines.

But there’s more than one way to implement a given computation, and modern compilers extensively analyze the code they process, trying to deduce the implementations that will maximize the efficiency of the resulting software.

Code explicitly written to take advantage of parallel computing, however, usually loses the benefit of compilers’ optimization strategies. That’s because managing parallel execution requires a lot of extra code, and existing compilers add it before the optimizations occur. The optimizers aren’t sure how to interpret the new code, so they don’t try to improve its performance.

At the Association for Computing Machinery’s Symposium on Principles and Practice of Parallel Programming next week, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory will present a new variation on a popular open-source compiler that optimizes before adding the code necessary for parallel execution.

As a consequence, says Charles E. Leiserson, the Edwin Sibley Webster Professor in Electrical Engineering and Computer Science at MIT and a coauthor on the new paper, the compiler “now optimizes parallel code better than any commercial or open-source compiler, and it also compiles where some of these other compilers don’t.”

That improvement comes purely from optimization strategies that were already part of the compiler the researchers modified, which was designed to compile conventional, serial programs. The researchers’ approach should also make it much more straightforward to add optimizations specifically tailored to parallel programs. And that will be crucial as computer chips add more and more “cores,” or parallel processing units, in the years ahead.

The idea of optimizing before adding the extra code required by parallel processing has been around for decades. But “compiler developers were skeptical that this could be done,” Leiserson says.

“Everybody said it was going to be too hard, that you’d have to change the whole compiler. And these guys,” he says, referring to Tao B. Schardl, a postdoc in Leiserson’s group, and William S. Moses, an undergraduate double major in electrical engineering and computer science and physics, “basically showed that conventional wisdom to be flat-out wrong. The big surprise was that this didn’t require rewriting the 80-plus compiler passes that do either analysis or optimization. T.B. and Billy did it by modifying 6,000 lines of a 4-million-line code base.”

Skilled human planners improves automatic planners

Every other year, the International Conference on Automated Planning and Scheduling hosts a competition in which computer systems designed by conference participants try to find the best solution to a planning problem, such as scheduling flights or coordinating tasks for teams of autonomous satellites.

On all but the most straightforward problems, however, even the best planning algorithms still aren’t as effective as human beings with a particular aptitude for problem-solving — such as MIT students.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory are trying to improve automated planners by giving them the benefit of human intuition. By encoding the strategies of high-performing human planners in a machine-readable form, they were able to improve the performance of competition-winning planning algorithms by 10 to 15 percent on a challenging set of problems.

The researchers are presenting their results this week at the Association for the Advancement of Artificial Intelligence’s annual conference.

“In the lab, in other investigations, we’ve seen that for things like planning and scheduling and optimization, there’s usually a small set of people who are truly outstanding at it,” says Julie Shah, an assistant professor of aeronautics and astronautics at MIT. “Can we take the insights and the high-level strategies from the few people who are truly excellent at it and allow a machine to make use of that to be better at problem-solving than the vast majority of the population?”

The first author on the conference paper is Joseph Kim, a graduate student in aeronautics and astronautics. He’s joined by Shah and Christopher Banks, an undergraduate at Norfolk State University who was a research intern in Shah’s lab in the summer of 2016.

National Inventors Hall of Fame

Is the Internet old or new? According to MIT professor of mathematics Tom Leighton, co-founder of Akamai, the internet is just getting started. His opinion counts since his firm, launched in 1998 with pivotal help from Danny Lewin SM ’98, keeps the internet speedy by copying and channeling massive amounts of data into orderly and secure places that are quick to access. Now, the National Inventors Hall of Fame (NIHF) has recognized Leighton and Lewin’s work, naming them both as 2017 inductees.

“We think about the internet and the tremendous accomplishments that have been made and, the exciting thing is, it’s in its infancy,” Leighton says in an Akamai video. Online commerce, which has grown rapidly and is now denting mall sales, has huge potential, especially as dual screen use grows. Soon mobile devices will link to television, and then viewers can change channels on their mobile phones and click to buy the cool sunglasses Tom Cruise is wearing on the big screen. “We are going to see [that] things we never thought about existing will be core to our lives within 10 years, using the internet,” Leighton says.

Leighton’s former collaborator, Danny Lewin, was pivotal to the early development of Akamai’s technology. Tragically, Lewin died as a passenger on an American Airlines flight that was hijacked by terrorists and crashed into New York’s World Trade Center on Sept. 11, 2001. Lewin, a former Israeli Defense Forces officer, is credited with trying to stop the attack.

According to Akami, Leighton, Lewin, and their team “developed the mathematical algorithms necessary to intelligently route and replicate content over a large network of distributed servers,” which solved congestion that was then becoming known as the “World Wide Wait.” Today the company delivers nearly 3 trillion internet interactions each day.

The NIHF describes Leighton and Lewin’s contributions as pivotal to making the web fast, secure, and reliable. Their tools were applied mathematics and algorithms, and they focused on congested nodes identified by Tim Berners-Lee, inventor of the World Wide Web and an MIT professor with an office near Leighton. Leighton, an authority on parallel algorithms for network applications who earned his PhD at MIT, holds more than 40 U.S. patents involving content delivery, internet protocols, algorithms for networks, cryptography, and digital rights management. He served as Akamai’s chief scientist for 14 years before becoming chief executive officer in 2013.

Automation and mobility combines

Daniela Rus loves Singapore. As the MIT professor sits down in her Frank Gehry-designed office in Cambridge, Massachusetts, to talk about her research conducted in Singapore, her face starts to relax in a big smile.

Her story with Singapore started in the summer of 2010, when she made her first visit to one of the most futuristic and forward-looking cities in the world. “It was love at first sight,” says the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and the director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). That summer, she came to Singapore to join the Singapore-MIT Alliance for Research and Technology (SMART) as the first principal investigator in residence for the Future of Urban Mobility Research Program.

“In 2010, nobody was talking about autonomous driving. We were pioneers in developing and deploying the first mobility on demand for people with self-driving golf buggies,” says Rus. “And look where we stand today! Every single car maker is investing millions of dollars to advance autonomous driving. Singapore did not hesitate to provide us, at an early stage, with all the financial, logistical, and transportation resources to facilitate our work.”

Since her first visit, Rus has returned each year to follow up on the research, and has been involved in leading revolutionary projects for the future of urban mobility. “Our team worked tremendously hard on self-driving technologies, and we are now presenting a wide range of different devices that allow autonomous and secure mobility,” she says. “Our objective today is to make taking a driverless car for a spin as easy as programming a smartphone. A simple interaction between the human and machine will provide a transportation butler.”

The first mobility devices her team worked on were self-driving golf buggies. Two years ago, these buggies advanced to a point where the group decided to open them to the public in a trial that lasted one week at the Chinese Gardens, an idea facilitated by Singapore’s Land and Transportation Agency (LTA). Over the course of a week, more than 500 people booked rides from the comfort of their homes, and came to the Chinese Gardens at the designated time and spot to experience mobility-on-demand with robots.

The test was conducted around winding paths trafficked by pedestrians, bicyclists, and the occasional monitor lizard. The experiments also tested an online booking system that enabled visitors to schedule pickups and drop-offs around the garden, automatically routing and redeploying the vehicles to accommodate all the requests. The public’s response was joyful and positive, and this brought the team renewed enthusiasm to take the technology to the next level.