If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Toyota has unveiled a new humanoid robot that can mimic the actions of a human operator, allowing it to do everything from balancing on one foot to squeezing a balloon without popping it. The new system relies on a remote control'Master Maneuvering System', which uses an array of sensors to directly communicate physical movements to the robot. According to the creators, this could be used to assist people at home, hospitals, or one day, even in space. Toyota has unveiled its third-generation humanoid, dubbed T-HR3. The bot connects to a human operator using a Master Maneuvering System and a virtual reality headset.
Forbes calls its 2018 30 Under 30 lists an "encyclopedia of creative disruption featuring 600 young stars in 20 different industries." So it should come as no surprise that these lists are heavily populated by recent MIT graduates and other members of the Institute community. Similar to past years, at least 29 MIT faculty, research staff, and alumni are listed throughout Forbes' seventh annual edition of the world's best young innovators. Read about the MIT community members who made this year's list below: "Abudayyeh and Gootenberg pioneered two advances: a new enzyme for editing genes and a new technique for editing RNA." David Bierman SM '14, PhD '17 (energy), founder of Marigold Power, Inc. "At MIT he helped to develop a thermophotovoltaic converter that absorbs sunlight and converts it to a form of light."
The growth of the Web is a success story that has spurred much research in knowledge discovery and data mining. Data mining over Web domains that are unusual is an even harder problem. There are several factors that make a domain unusual. In particular, such domains have significant long tails and exhibit concept drift, and are characterized by high levels of heterogeneity. Notable examples of unusual Web domains include both illicit domains, such as human trafficking advertising, illegal weapons sales, counterfeit goods transactions, patent trolling and cyberattacks, and also non-illicit domains such as humanitarian and disaster relief.
Over the last decade, crowdsourcing has been used to harness the power of human computation to solve tasks that are notoriously difficult to solve with computers alone, such as determining whether or not an image contains a tree, rating the relevance of a website, or verifying the phone number of a business. The machine learning and natural language processing communities were early to embrace crowdsourcing as a tool for quickly and inexpensively obtaining the vast quantities of labeled data needed to train systems. Once this data is collected, it can be handed off to algorithms that learn to make autonomous predictions or actions. Usually this handoff is where interaction with the crowd ends. The crowd provides the data, but the ultimate goal is to eventually take humans out of the loop.
Deep learning has been widely successful in solving complex tasks such as image recognition (ImageNet), speech recognition, machine translation, etc. In the area of personalized recommender systems, deep learning has started showing promising advances in recent years. The key to success of deep learning in personalized recommender systems is its ability to learn distributed representations of users' and items' attributes in low dimensional dense vector space and combine these to recommend relevant items to users. To address scalability, the implementation of a recommendation system at web scale often leverages components from information retrieval systems, such as inverted indexes where a query is constructed from a user's attribute and context, learning to rank techniques. Additionally, it relies on machine learning models to predict the relevance of items, such as collaborative filtering.
It has now become inevitable for Amazon's Echo series to reign supreme in the smart speaker market this holiday season after Apple decided to reschedule the launch of its HomePod device to early next year. This will consequently benefit the manufacturers of the Echo speakers. On Tuesday, DigiTimes disclosed that the delayed release of Apple's HomePod would translate to the domination of the Amazon Echo series in the market during the year-end holidays of 2017. The outlet also learned from a Chinese language report that Amazon has already received its supply of Echo Spot and Echo Show speakers for the holiday season. Amazon's Echo speakers are being manufactured by Foxconn Electronics and Compal Electronics.
Motion sickness is a real problem in self-driving cars. As you're not in control of where the car is going, you might feel queasy when the vehicle moves in ways you weren't anticipating. Uber clearly needs to minimize that urge to hurl if it's going to create an autonomous fleet -- and accordingly, it's exploring technology that could make you feel at ease. It's applying for a patent on a raft of technologies that would counter motion sickness by stimulating your senses as the car moves, distracting your brain. Light bars and screens could signal the car's intentions, giving your mind a chance to prepare for that upcoming turn.
Have you wondered why it took Apple 3 years to come up with an answer to the Amazon Echo in the form of the HomePod? Apparently, it's because it wasn't really meant as an answer to the Echo. Bloomberg sources claim that work on the HomePod started in 2012 as a side project (common at Apple), and it was reportedly cancelled and resurrected "several times" as the company tried to figure out how a connected speaker would work in its lineup. It reportedly went through multiple dramatic redesigns, including a 3-foot-tall design chock-full of speakers. The company did study the Echo closely when it showed up in 2014, but dismissed its lackluster audio quality and set to working on something that sounded better.
Some people listen to rain sounds to relax, others watch rivers of red hot lava flowing from an active Hawaiian shield volcano. Like Erez Marom, who used a drone to capture mesmerising footage of lava streaming through the Puʻu ʻŌʻō crater of Kīlauea, Hawai'i. It's one of the world's most active volcanoes, and has been spewing lava in its latest eruption since September. Marom shot the footage during a two-week trip to Hawaii, in which he and a friend hiked to the edge of Hawai'i Volcanoes National Park. The lava melted the plastic inside the drone camera, but not before he'd nailed some impressive shots.
One of Google's most powerful new features is finally rolling out to Pixel phones. Google Lens, the company's intelligent camera software that can analyze the world around you, is now rolling out to Google Assistant on Pixel phones. Announced earlier this year, Lens is one of the company's most important new products as it offers an early look at what the future of search will look like for Google. SEE ALSO: Google Pixel Buds review: They're great... if you own a Pixel phone Though Google Lens has been available within Google Photos since the Pixel 2 launched, this update, which is rolling out "over the coming weeks," marks the first time the feature has been available outside of Google Photos. This means Pixel owners will be able to use Google Lens with their smartphone camera in real-time, rather than simply using the feature to analyze photos they've previously taken.