AI Technology & Industry Review
In a new paper, researchers from the New York University and Modl.ai, a company applying machine learning to game developing, suggest that simple spacial processing methods such as rotation, translation and cropping could help increase model generality.
The tool can significantly accelerate the prediction time of a virus’s RNA secondary structure, affording frontline researchers an opportunity to better understand the virus and develop targeting vaccines in a time of crisis.
Facebook’s new HiPlot is a lightweight interactive visualization tool that takes this further, using parallel plots to discover correlations and patterns in such high-dimensional data.
Now, DeepMind and University College London (UCL) have introduced a new deep network called MEMO which matches SOTA results on Facebook’s bAbI dataset for testing text understanding and reasoning, and is the first and only architecture capable of solving long sequence novel reasoning tasks.
A new study suggests human-to-human transmission of the 2019 Novel Coronavirus (2019-nCoV) may have started as early as mid December, 2019.
One of a new breed of open-domain chatbots designed to engage in conversations across any topic, Meena’s free and natural conversational abilities are closing the gap on human performance.
Facebook AI researchers have further developed the BART model with the introduction of mBART.
A team of researchers from the Natural Language Processing Lab at the University of British Columbia in Canada have proposed AraNet, a deep learning toolkit designed for Arabic social media processing.
Inspired by the performance of attention mechanisms in NLP, researchers have explored the possibility of applying them to vision tasks.
A new study suggests DeepMind’s amazing game-playing algorithm AlphaZero could help unlock the power and potential of quantum computing.
A recent paper published by Microsoft researchers proposes a new vision-language pretrained model for image-text joint embedding, ImageBERT, which which achieves SOTA performance on both the MSCOCO and Flickr30k datasets.
Researchers from Beijing’s National Laboratory of Pattern Recognition (NLPR), SenseTime Research, and Nanyang Technological University have taken the tech one step further with a new framework that enables totally arbitrary audio-video translation.
A group of researchers from The Katholieke Universiteit Leuven and The Technical University of Berlin recently introduced a Dutch RoBERTa-based language model, RobBERT.
A team from Google Research introduced FixMatch, an algorithm that combines two common SSL methods for deep networks: pseudo-labeling (aka self-training) and consistency regularization.
The Autonomous Learning Library is a deep reinforcement learning (DRL) library for PyTorch that streamlines the building and evaluation of novel reinforcement learning agents.
AI systems are already helping farmers with soil analysis, planting, animal husbandry, water conservation and more.
Google recently introduce Flax - a neural network library for JAX that is designed for flexibility.
To enable both content creators and end users to seriously restyle their apps’ interfaces while maintaining content detail clarity essential to their usability, researchers from Stanford have proposed ImagineNet, a novel and powerful new tool for interface customisation.
DeepMind researchers have uncovered parallels between how brains react to dopamine and the trending AI theory of distributional reinforcement learning.
A trio of AI detecting breast cancer papers from Google, NYU, and DeepHealth have triggered huge discussions. What are the breakthroughs? Is AI truly beating radiologists? Where exactly are we right now?
A research team from the Hong Kong University of Science and Technology and Harbin Engineering University has adopted facial recognition technology to analyze students’ emotions in the classroom through a visual analytics system called “EmotionCues.”
Fake images and videos are giving AI a black eye — but how can the machine learning community fight back?
The Fujitsu Laboratories and R&D Center behavioural analysis technology identifies suspicious activity by analysing complex combinations of human actions and movements — and does so with minimal training data.
AutoGluon is designed to be an easy-to-use and easy-to-extend AutoML toolkit, suitable for both machine learning beginners and experts.
Researchers trained a neural network, CGANet (Convolution module, bidirectional Gated Recurrent Unit module, Attention module), to automate the mating success prediction process for pandas based on their vocal sounds.
FAIR as now open-sourced PySlowFast, along with a pretrained model library and a pledge to continue adding cutting-edge resources to the project.
PracticalAI recently released “practicalAI 2.0,” a platform that includes illustrative machine learning lessons in TensorFlow 2.0 + Keras and has garnered over 23k stars on GitHub.
In an effort to sustain RL’s momentum, a team of researchers from Machine Zone, Google Brain, and California Institute of Technology have introduced a new software framework and benchmark for reproducible reinforcement learning research.
To help users design and tune machine learning models, neural network architectures or complex system parameters in an efficient and automatic way, in 2017 Microsoft Research began developing its Neural Network Intelligence (NNI) AutoML toolkit, open-sourcing v1.0 version in 2018.
A new study from Peking University and Microsoft Research Asia proposes a novel two-phase framework, FaceShifter, that aims for high-fidelity and occlusion-aware face exchange.
Researchers recently proposed a new machine learning method for worldbuilding based on content from LIGHT, a research environment open-sourced by Facebook comprising crowd-sourced game locations, characters, and objects, etc.
A recent paper accepted by ICLR 2020 proposes a new transformer model called “Reformer” which achieves impressive performance even when running on only a single GPU.
Results of the various experiments show GELU consistently has the best performance compared with ReLU and ELU, and can be considered a viable alternative to previous nonlinear approaches.
Google has now released a major V2 ALBERT update and open-sourced Chinese ALBERT models.
A team of researchers from Mila and Google Brain believe simple pencil sketches could help AI models generalize to a better understanding of unseen images.
Although “Sudoku“ grid-based number puzzles are no match for today’s artificial intelligence systems, a novel approach to the challenge is trending on GitHub due to its practical integration of computer vision technologies.