MIT: Carpooling services could replace most NYC cabs

Researchers have proved mathematically what you probably already knew: Carpooling services are more efficient, less polluting and less costly than traditional taxis. Using data from three million New York City taxi rides, a team from from MIT’s CSAIL computer science lab found that just 3,000 vehicles from services like UberPOOL and Lyft Line could replace NYC’s 14,000 strong cab fleet. What’s more, they’d reduce congestion by three times, barely impact travel times, and you’d only have to wait an average of 2.7 minutes for a ride.

The study is, of course, highly academic, especially the assumption that you could convince 15,000 gainfully employed drivers to just go ahead and do something else. Putting that aside, however, implementing the ideas could lead to a more efficient transportation infrastructure, a reduction in lost time, lower pollution and more manageable traffic, the researchers say.

The main key is the carpooling aspect. The researchers created an algorithm that’s more efficient than the ones used by companies like Uber or Lyft, which often require a trip to be fully booked before a route is create. Instead, it works in real time to reroute cars based on incoming requests and can send idle vehicles to high demand areas, speeding up service by 20 percent.

A graph showing how MIT/CSAIL researchers optimize carpool rides (CSAIL/MIT)

“A key challenge was to develop a real-time solution that considers the thousands of vehicles and requests at once,” says CSAIL Professor Daniela Rus. The system does that by creating a graph of all vehicles and requests, then calculating every possible trip combination to determine the best assignments. Any vehicles without trips are rebalanced and sent to high-demand areas.

The system could cover 98 percent of trips in the Big Apple with 3,000 four-passenger vehicles, and 95 percent of trips with 2,000 ten-passenger vans. What’s more, the algorithms would get better the more they’re used, leading to even greater efficiency. “A system like this could allow drivers to work shorter shifts, while also creating less traffic, cleaner air and shorter, less stressful commutes,” Rus says.

Unfortunately, the algorithms don’t take into account the fact that many, if not most passengers would rather ride by themselves if they can afford it. Nor, of course, that many cities are set against ride-sharing services that compete against taxis, for safety and other reasons, despite the many disadvantages of old-school cabs.

The point of the study, though, is to look toward a more efficient future. As much as Uber, Lyft and other services have changed urban transport in the last few years, autonomous and electric cars could shake things up even more. “It’s important that we as researchers do everything we can to explore ways to make these transportation systems as efficient and reliable as possible,” says Rus.

Inside Mercedes’ Silicon Valley research center

A metal typewriter sits on a pedestal churning out the next sentence of a collaborative story. For every line I typed onto paper, the AI computer controlling the hunk of metal replies with what it thinks would be a good follow up. The goal of the experiment is to see what happens when you feed an artificial intelligence only fairy tales. It’s the kind of seemingly idiosyncratic thing you’d expect from IBM, Google or Apple. But I actually found it inside Mercedes Benz’s R&D North American headquarters in Silicon Valley.

The German automaker is trying to see what happens when you let a computer learn how to write, space and spell on its own. The experiment could help researchers build an artificial brain for a car that could independently deduce and react to what’s happening on the road. It might seem like these things are unrelated, but a typewriter cranking out sentences and a car automatically braking to miss an object in the road are both utilizing the learn and react system of AI to get a job done. All that deep learning is one building blocks of autonomous systems.

Another import aspect of self-driving cars is that the computers needed to keep them on the road not only have to learn and react but also actually see what’s going on. Most automakers use Lidar to scan the surrounding world with lasers to create a vast pixel map. The amount of data created by all those pinpoints is staggering. Mercedes thinks it’s solved the problem of trying to crunch all that information by joining blocks of pixels to create single objects. So instead of an automobile trying to decipher 500,000 pixels, the car only has to figure out the location of 1,000 object-specific rectangles called “Stixels.” Each Stixel can be a person, car, or object and is assigned a color based on how close they are to the vehicle.

Experiments like this are part of the company’s new CASE (Connected, Autonomous Driving, Shared usage and Electric drive) strategy. Mercedes wants to build its own future instead of teaming up with a tech company. When you’re beholden to another entity, you’re stuck with whatever they decide to add to their platform. So it’s got its Silicon Valley facility working hard on a variety of initiatives.

During a recent tour of the R&D headquarters, I saw the shiniest result of those initiatives and latest CASE project, the EQ concept vehicle it unveiled at the Paris Auto show. The electric car has autonomous features, replaced the dash with a giant display and shed all of its mirrors in favor of tiny cameras. While the vehicle looks like it’s a prop from a reboot of TRON, it’s actually the launching pad of the EQ line of vehicles and home energy storage.

Sadly the concept vehicle on display will never appear in showrooms. Instead it’s a marketing tool for the launch of the upcoming EQ brand of vehicles and mobility initiatives that will start appearing in three years. It’s a new category within the company similar to Smart, it’s small-car subsidiary. But while the new business venture is a ways off, the automaker is already adding connected features to its current and upcoming lineup of Mercedes Benz vehicles.

The automaker already has an iOS and Apple Watch companion app for locking the doors. In the next year it’ll be adding Google home support. Drivers will be able to interact with the search-giant’s home assistant with the sound of their voice while driving. The integration will also learn a person’s habits and will offer to turn on or off devices based on the car’s location via AI. Don’t worry if you’re already part of the Alexa or HomeKit ecosystem, both of those platforms are being investigated.

But it’s not just the cars Mercedes sells to individuals that are being upgraded. The automaker is working on speeding up deliveries from services like UPS, FedEX and DHL. In a garage a few miles from the main building, a team of researchers are building a carpet-like covering for the shelves and floor of a delivery van that can weigh a package no matter where it is.

I was initially unsure why the weight of each box was important. That was until they explained that the system can pinpoint the location of any item in the truck based on its mass and can have nearby LEDs light up when the driver needs to find said package.

According to Mercedes, tests of the system with local delivery drivers have increased efficiency 35 percent. The drivers no longer have to hunt for a box that slid around the back of the truck during a sharp turn, the system just knows where everything is.

It’s research like this that could help the automaker maintain the pace needed to compete in the increasingly accelerating automotive tech landscape. It’s a legacy brand that’s seen the cars changing quicker in the past few years than in the previous 90. It’s done a good job keeping up, but pressure from Tesla, Google and established automakers means it has to be more nimble and think outside horsepower and tires. Even if it means experiments with mechanical typewriters and fairy tales.

Apple Announces Chinese New Year Event Featuring Free Beats Solo3 Headphones With Mac or iPhone Purchase

Apple today announced an upcoming one-day sale in celebration of Chinese New Year, where the company will provide free Beats Solo3 Wireless On-Ear Headphones in red to all customers who purchase a select Mac or iPhone in various countries around the world.

The sale will kick off on January 6 at 8:00 a.m. local time and will be available in China, Hong Kong, Singapore, and Taiwan. A Chinese New Year announcement is available in Malaysia, but the country is not included in the free headphone offer.

To get the free Beats headphones, customers in eligible countries will need to purchase an iMac, MacBook, MacBook Pro, MacBook Air, or Mac Pro, but the late 2016 MacBook Pro with a Touch Bar is excluded from the sale. Eligible iPhones include the iPhone 7, iPhone 7 Plus, iPhone 6s, and iPhone 6s Plus.

Apple’s sale announcement is accompanied by a New Year’s gift guide featuring a range of New Year’s-themed products in red and gold, including a lion dance LionBot kit, a limited edition DJI Phantom 4 drone, and a Chinese New Year iPhone 7 case from Tech21.

Last year, Apple celebrated Chinese New Year by introducing two exclusive Apple Watch Sport models featuring (PRODUCT)RED Sport Bands.
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How to Boost Your Mac with Movavi Mac Cleaner

After a few months of using your new Mac, you will realize that your computer is getting slower and slower. You are wondering why is this happening to your Mac computer and what you can do to speed up the performance. The solution is to get a Mac cleaner software like Movavi Mac Cleaner to clean up your Mac computers.

There is a high chance that the slowing down of your computer performance is due to insufficient free space left available on your Mac computer. The reason why your computer is having insufficient free space is due to the accumulation of junk files. Various types of junk files may be responsible for slowing down of your Mac computer such as caches, log files, duplicate files, and old files.

Movavi Mac Cleaner can help you to locate all thousands of junk files in just a few minutes. You don’t have to click any button to prompt it to perform a scan on the computer. It will automatically launch a scan and detect all kinds of junk files. It won’t automatically delete the junk files it detected. After it finished scanning, it will first let you know whether your computer needs cleaning. The cleaner for Mac software gives you the option to press the Start Cleaning button to delete all the unnecessary junk files.

It is not necessarily that all the files it detected are files that you don’t need so it is best to navigate each of the tab one of the one yourself to see which files you want to delete. In each tab, it will states how many MB or GB is in that category of junk files. If there is no junk file in the tab category, you won’t see any size figure. The first tab that you want to go should be the system cleanup tab where you can delete the cache and log files.

In the Trash cleanup tab, you can see whether there is any trash that you haven’t deleted. Moving files into the trash does not mean that it will stop taking up space on the hard disk. It is only after emptying the trash that you can claim back the space on the hard disk. Sometimes, you save the same files in different folders. This ends up wasting space as you only need to retain the copy of a single version of the file. In the Duplicate Files tab, you can check the unnecessary duplicate files and have them deleted with the click of a single button.

The Large and Old Files tab is where you can all sorts of large files that are occupying the majority of the space on the hard disk. If you haven’t already deleted the unused language packs, you can go to the Unused Languages tab and select all language packs except 2 – 3 language packs that you regularly use. System apps that are hard to uninstall on Mac can be uninstalled via the Uninstaller tool. You can select all the system apps under the OS X Apps tab except a few important system apps and press the Remove button to completely uninstall them.