With speech recognition getting better every day, it’s remarkable how well Siri, Alexa, and Cortana can parse human speech. But what about cheering crowds or crashing waves? Can our AI personal assistants tell the difference between those? Well, probably not. Sound recognition is actually very difficult for computers, particularly natural sounds.
From our smartphones to our most advanced supercomputers, recognizing images and speech is something they’re able to do fairly well across the board. While natural sounds have been an exception, that may be about to change. Scientists at the Massachusetts Institute of Technology might have found a solution.
According to Phys.Org, a group of researchers at MIT’s Computer Science and Artificial Intelligence Laboratory, or CSAIL, have pioneered a new way to teach computers to recognize sound – by cutting out the middle men.
Normally, vast databases of sounds need to be annotated by hand, by humans, to teach computers how to recognize and identify particular sounds. This new method, however, circumvents the human element by using video.
“Computer vision has gotten so good that we can transfer it to other domains. We’re capitalizing on the natural synchronization between vision and sound. We scale up with tons of unlabeled video to understand sound,” Carl Vondrick, an MIT graduate student in electrical engineering, told Phys.Org.
The new system essentially leverages a computer’s ability to recognize visual information and tie that recognition to its understanding of the sounds the videos produce. Think of it this way, the computers recognize objects in the video, and look for correlations between the appearance of those objects and the sound information they’re processing.
It’s a quicker, easier, and more accurate way to train computers to recognize sounds. According to a research paper, it’s between 13 and 15 percent more accurate than the previous method of hand-annotating massive libraries of sounds and feeding that information into a computer.
The CSAIL research team’s full conclusions will be presented at the Neural Information Processing Systems conference in early December.
The absolutely absurd idea of putting a touchscreen display on a mouse isn't exactly new. Turtle Beach already did it with its Command Series MC7, which features a 2.25-inch control screen. But apparently, even that wasn't ridiculous enough for Arctic Fox Technologies. Its new Super Mouse looks like someone took the chunky old Atari ST mouse, slapped a touchscreen and scroll wheel on it, and called it an upgrade.
The result is a rather unusual-looking mouse that is now on Kickstarter, starting at $199. And as ridiculous as it looks, some of its features are genuinely intriguing.
Apple is less than a day away from launching its highly anticipated OLED MacBook Pro with a touch-sensitive screen. But it appears that the upgrade is going to cost a pretty penny. According to a report by Bloomberg, Apple is reportedly eyeing a starting price of $2,899 for the 14-inch MacBook Pro, while the 16-inch version could start at $3,399 in the US.
"At $2,899, the 14-inch model would mark the highest starting price for a new MacBook Pro model, surpassing the $2,799 Apple charged for a 17-inch version introduced in 2006," says the report. The report claims that Apple is targeting a minimum price hike of $400 for its upcoming redesigned 14-inch and 16-inch MacBook Pro models.
I've spent a good amount of time digging into the spec sheet of the new M6 MacBook Pro (14-inch), and for all intents and purposes, this is a classic Apple "chip and connectivity" refresh. It's not a full redesign. The chassis, Liquid Retina XDR panel, speakers, ports, and battery, all of them carry over unchanged.
However, the M6 brings more cores, stronger on-device AI, higher memory bandwidth on the larger configs, and modern wireless. Here’s the practical rundown of what actually improved, and whether those gains are worth your money.