In 2015, Anh Nguyen published a paper in CVPR that identified a limit in computer vision, where you can fool a deep neural network (DNN) by changing an image in a way that’s imperceptible to humans, but can cause the DNN to label the image as something else entirely.
New autoencoder-like generative network, called Adversarial Generator-Encoder Networks (AGE Network), does not have any discriminators, which makes the entire architecture much simpler than some recently-proposed GANs, but with nearly the same-level performance
Word2vec is an open source tool developed by a group of Google researchers led by Tomas Mikolov in 2013. It describes several efficient ways to represent words as M-dimensional real vectors, also known as word embedding, which is of great importance in many natural language processing applications
In order to provide personalized ads, tech giants such as Google and Facebook are trying to abstract their users’ personality from their posts on social media. Hence, it is essential for social networking applications to predict personality from written text.
From May 14 to 18, the 30th International Joint Conference on Neural Networks (IJCNN 2017) was held in Anchorage, AK, USA. Continuing the long tradition, the conference is organized by the International Neural Network Society (INNS), in cooperation with the IEEE Computational Intelligence Society (IEEE-CIS).
At the 10th Google I/O, held May 17-19 at the Shoreline Amphitheatre in Mountain View, California, Google took a different approach from unveiling exciting new products, by putting its focus on the convergence of existing products, aimed at providing a better user experience.
Personal computers and mobile devices are in their heyday. Researchers are swarming standalone AI, focusing on how to automate self-learning intelligent systems. The interfaces for wearables meanwhile are evolving from smart screens to gesture commands, like those often seen in AR and VR commercials.