Israeli research company AI21 Labs today published the paper SenseBERT: Driving Some Sense into BERT, which proposes a new model that significantly improves lexical disambiguation abilities and has obtained state-of-the-art results on the complex Word in Context (WiC) language task.
Since Google Research introduced its Bidirectional Transformer (BERT) in 2018 the model has gained unprecedented popularity among researchers. Now, a group of researchers from the National Cheng Kung University Tainan in Taiwan are challenging BERT’s efficacy.
Two years ago Elon Musk launched a company called Neuralink. Musk already leads high-profile companies including Tesla, SpaceX, and Hyperloop, but Neuralink may be the 48 year-old entrepreneur’s most ambitious plan yet: to surgically connect human brains with artificial intelligence through an ultra high bandwidth brain-machine interface.
Have you ever shot a perfect video only to have it spoiled by an unsightly pedestrian, truck or other moving object passing through the frame? Although most people know how to crop or photoshop their photos to remove unwanted stuff, doing so with video is another matter entirely.
Although there are many means for identifying and locating a missing person — police and amber alerts, photos and biometrics such as fingerprints and even facial recognition — few of these resources are available for finding a lost dog, and about 75 percent of dogs in the USA are not microchipped.