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) …
CAPE CANAVERAL, FLORIDA - A SpaceX shipment arrived at the International Space Station on Monday with a "cosmic catch" by a pair of Canadians. The Dragon capsule delivered 5,500 pounds (2,500 kg) of equipment and experiments. Canadian astronaut David Saint-Jacques used the station's big robot arm -- also made in Canada -- to capture the Dragon approximately 250 miles (400 kilometers) above the North Atlantic Ocean. An external cable that normally comes off during launch dangled from the capsule, but it did not interfere with the grappling. "Welcome on board, Dragon," Saint-Jacques radioed.
Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items. The matching stage retrieves candidate items relevant to user interests, while the ranking stage sorts candidate items by user interests. Thus, the most critical ability is to model and represent user interests for either stage. Most of the existing deep learning-based models represent one user as a single vector which is insufficient to capture the varying nature of user's interests. In this paper, we approach this problem from a different view, to represent one user with multiple vectors encoding the different aspects of the user's interests. We propose the Multi-Interest Network with Dynamic routing (MIND) for dealing with user's diverse interests in the matching stage. Specifically, we design a multi-interest extractor layer based on capsule routing mechanism, which is applicable for clustering historical behaviors and extracting diverse interests. Furthermore, we develop a technique named label-aware attention to help learn a user representation with multiple vectors. Through extensive experiments on several public benchmarks and one large-scale industrial dataset from Tmall, we demonstrate that MIND can achieve superior performance than state-of-the-art methods for recommendation. Currently, MIND has been deployed for handling major online traffic at the homepage on Mobile Tmall App.
Multi-head attention is appealing for its ability to jointly extract different types of information from multiple representation subspaces. Concerning the information aggregation, a common practice is to use a concatenation followed by a linear transformation, which may not fully exploit the expressiveness of multi-head attention. In this work, we propose to improve the information aggregation for multi-head attention with a more powerful routing-by-agreement algorithm. Specifically, the routing algorithm iteratively updates the proportion of how much a part (i.e. the distinct information learned from a specific subspace) should be assigned to a whole (i.e. the final output representation), based on the agreement between parts and wholes. Experimental results on linguistic probing tasks and machine translation tasks prove the superiority of the advanced information aggregation over the standard linear transformation.
Capsule network has shown various advantages over convolutional neural network (CNN). It keeps more precise spatial information than CNN and uses equivariance instead of invariance during inference and highly potential to be a new effective tool for visual tasks. However, the current capsule networks have incompatible performance with CNN when facing datasets with background and complex target objects and are lacking in universal and efficient regularization method. We analyze the main reason of the incompatible performance as the conflict between information sensitiveness of capsule network and unreasonably higher activation value distribution of capsules in primary capsule layer. Correspondingly, we propose sparsified capsule network by sparsifying and restraining the activation value of capsules in primary capsule layer to suppress non-informative capsules and highlight discriminative capsules. In the experiments, the sparsified capsule network has achieved better performances on various mainstream datasets. In addition, the proposed sparsifying methods can be seen as a suitable, simple and efficient regularization method that can be generally used in capsule network.
An average person with type 1 diabetes and no insulin pump sticks a needle into their abdomen between 700 and 1,000 times per year. A person with the hormone disorder acromegaly travels to a doctor's office to receive a painful injection into the muscles of the butt once a month. Someone with multiple sclerosis may inject the disease-slowing interferon beta drug three times per week, varying the injection site among the arms, legs and back. Medical inventor Mir Imran, holder of more than 400 patents, spent the last seven years working on an alternate way to deliver large drug molecules like these, and his solution--an unusual "robotic" pill--was recently tested in humans. The RaniPill capsule works like a miniature Rube Goldberg device: Once swallowed, the capsule travels to the intestines where the shell dissolves to mix two chemicals to inflate a balloon to push out a needle to pierce the intestinal wall to deliver a drug into the bloodstream.
SpaceX sent its Crew Dragon capsule skyward on Saturday for a crucial test of its ability to carry human passengers. Now, slightly more than 24 hours later, the next phase of the test has played out. The Crew Dragon capsule, designated Demo-1, was able to successfully dock with the International Space Station at roughly 3:00 a.m. Although there was no crew aboard this time, SpaceX's reusable capsule is designed to carry up to seven astronauts to and from Earth's orbit. SEE ALSO: SpaceX kicks off a'new era in spaceflight' with the Crew Dragon launch The company has been sending an earlier version of its capsule to the ISS for a number of years, but in those instances the space station's robotic arm has helped the smaller vehicle successfully dock.
SpaceX's Crew Dragon capsule arrives at the International Space Station for the first time on March 3, 2019 after launching from Kennedy Space Center. A SpaceX capsule that could be astronauts' next ride to orbit from the United States safely reached the International Space Station early Sunday, completing a flawless daylong voyage from Kennedy Space Center on its first test flight. The Crew Dragon eased into a docking port at 5:51 a.m., becoming the first privately designed and operated spacecraft capable of flying to people to visit the outpost. The station had not hosted a U.S. crew ship for nearly eight years, since Atlantis on NASA's final space shuttle mission in July 2011. Since then, only Russia's Soyuz has flown astronauts up and down.
SpaceX's new crew capsule arrived at the International Space Station on Sunday, acing its second milestone in just over a day. No one was aboard the Dragon capsule launched Saturday on its first test flight, only an instrumented dummy. But the three station astronauts had front-row seats as the sleek, white vessel neatly docked and became the first American-made, designed-for-crew spacecraft to pull up in eight years. TV cameras on Dragon as well as the space station provided stunning views of one another throughout the rendezvous. If the six-day demo goes well, SpaceX could launch two astronauts this summer under NASA's commercial crew program.
The demonstration flight of America's new astronaut capsule will see it attempt to dock with the International Space Station (ISS). The Dragon vehicle, launched by California's SpaceX company on Saturday, is designed to make the attachment autonomously. It is the latest in a series of tests the capsule must pass in order to get approval from Nasa to transport people. All this particular mission is carrying is a test dummy and 90kg of supplies. The docking should occur at about 11:00 GMT.
SpaceX launched its Crew Dragon capsule for the first time late Friday in a test flight without humans aboard, a milestone that moves the Elon Musk-led company closer to ferrying NASA astronauts to the International Space Station. The capsule, some 400 pounds of cargo and a mannequin passenger named Ripley, lifted off on a SpaceX Falcon 9 rocket at 11:49 p.m. Pacific time from the same Florida pad where Apollo and space shuttle programs once began their missions. The Crew Dragon deployed from the rocket's second-stage about 11 minutes after lift-off, sending it on a trajectory to the space station where it is scheduled to dock early Sunday morning. The Falcon 9 rocket landed on a floating sea platform in the Atlantic Ocean about 10 minutes after liftoff. Friday's launch was the first test flight for NASA's commercial crew program, a public-private partnership involving Hawthorne-based SpaceX and Boeing Co., which have contracts worth a combined total of $6.8 billion to build separate craft to transport astronauts to the space station.