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.
In a joint effort with the Perimeter Institute for Theoretical Physics and Alphabet (Google) X, Google AI researchers recently announced a new open source library, TensorNetwork, which can greatly improve the efficiency of tensor calculations for tensor network algorithms.
By 2050 almost one-in-four humans will be aged 60 years and older, double today’s share. Moreover, the number of people aged 80 years and older will quadruple. This demographic shift is opening new vistas for AI technologies in elders’ daily healthcare management, and as a useful tool for healthcare professionals and institutions treating seniors.
The world’s biggest technical professional organization, the Institute of Electrical and Electronics Engineers (IEEE) issued a statement on May 22 that forbids its colleagues from Huawei and 68 of its affiliates from reviewing or accessing non-public papers submitted by other persons for publications.
Imagine the lips forming the Mona Lisa’s famous smile were to part, and she began “speaking” to you. This is not some sci-fi fantasy or a 3D face animation, it’s an effect achieved by researchers from Samsung AI lab and Skolkovo Institute of Science and Technology, who used adversarial learning to generate a photorealistic talking head model.
A group of AI experts from top US universities is organizing a sample-efficient reinforcement learning competition, MineRL, which will start on June 1, 2019. The organizers want to increase group participation in reinforcement learning and are encouraging people to “play to benefit science”.
Google’s deep learning TensorFlow platform has added Differentiable Graphics Layers with TensorFlow Graphics, a combination of computer graphics and computer vision. Google says TensorFlow Graphics can solve data labeling challenges for complex 3D vision tasks by leveraging a self-supervised training approach.
Automated machine learning (AutoML) is a hot topic in artificial intelligence. Researchers from German digital and software company USU Software AG and the University of Stuttgart recently published a review paper summarizing the latest academic and industrial developments in AutoML.
Google has achieved a milestone in machine learning research that will boost the company’s broader ambitions in healthcare. In a paper published today in Nature Medicine, Google researchers present an end-to-end deep learning model that can predict lung cancer comparably or better than human radiologists.
The annual meeting of the Association for Computational Linguistics (ACL) is world-leading conference in the field of natural language processing, Yesterday, conference organizers sent out author notifications on accepted papers for the 57th ACL gathering, which will take place in Florence, Italy from July 28 to August 2.
n the new paper Adversarial Examples Are Not Bugs, They Are Features, a group of MIT researchers propose that adversarial examples’ effectiveness can be attributed to non-robustness: “Adversarial vulnerability is a direct result of our models’ sensitivity to well-generalizing features in the data.”
Current state-of-the-art convolutional architectures for object detection tasks are human-designed. In a recent paper, Google Brain researchers leveraged the advantages of Neural Architecture Search (NAS) to propose NAS-FPN, a new automatic search method for feature pyramid architecture.