AI Technology & Industry Review
Technical review of the newest machine intelligence research.
In EMNLP 2020, a Montreal-based research team introduced a large medical text dataset designed to boost abbreviation disambiguation in the medical domain.
Researchers achieved world-class interface smoothness with a-axis YBa2Cu3O7-x/PrBa2Cu3O7-x/YBa2Cu3O7-x trilayers grown on (100) LaAlO3 substrates.
A new study by South China University of Technology and Tencent WeChat AI researchers is the latest fruitful attempt to utilize transformer architectures in object detection.
A new AI-powered image synthesis framework makes “learning” to moonwalk or drop Blackpink dance moves a snap.
Facebook AI is building an automatic differentiation system for the Kotlin programming language and developing a system for tensor typing.
The Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) kicked off on Monday as a virtual conference.
The CoRL 2020 Best System Paper Award was presented today to Huawei Noah’s Ark Lab, Shanghai Jiao Tong University and University College London for their paper SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving.
Stylized Neural Painter is a novel automatic image-to-painting translation method that generates vivid and realistic artworks in controllable styles
A new DeepMind scalable environment simulator takes a digital approach to the question, enabling the examination of environmental factors on AI agents.
CoRL 2020 kicked off yesterday and runs virtually through November 18. This year saw 475 papers submitted, a 20 percent rise over 2019.
New Spoken Language Understanding (SLU) research from MIT CSAIL and Amazon AI introduces step-skipping semi-supervised frameworks that take speech as input and achieve performance competitive to systems leveraging oracle text.
“Our research provides enriched AR user experiences by enabling a more fine-grained visual recognition feature in AR, which is desirable in a wide range of application scenarios including technical support,” IBM researchers say.
Google Research and DeepMind debut Long-Range Arena (LRA) benchmark for Transformer research on tasks with long sequence lengths.
Google Brain ICLR 2021 submission analyzes learned optimizers’ performance advantage over well-tuned baseline optimizers.
A new study proposes using human feedback and interaction logs to boost offline reinforcement learning (RL) in natural language processing (NLP).
Google AI yesterday released its Objectron dataset — a collection of short, object-centric video clips capturing a large set of common objects from different angles.
Researchers introduced a modular primitive that uses existing, highly optimized hardware graphics pipelines to deliver performance superior to previous differentiable rendering systems.
Amazon Alexa AI paper asks whether NLU problems could be mapped to question-answering (QA) problems using transfer learning.
MIT, UChicago, Harvard and Diffeo *Bayesian Delegation* multi-agent learning mechanism enables agents to coordinate behaviour on the fly
DeepMind and Universidade de Lisboa introduce graph-based toolkit for analyzing and comparing multiplayer games
Cornell and Facebook AI “Correct and Smooth” high-accuracy graph learning method is fast to train and outperforms big Graph Neural Network (GNN) models
In a new paper, researchers from Google, OpenAI, and DeepMind introduce “behaviour priors,” a framework designed to capture common movement and interaction patterns that are shared across a set of related tasks or contexts.
A team of researchers from Shanghai Jiao Tong University (SJTU) has built a lightweight benchmark suite designed to help make life-saving models of medical image analysis even stronger.
This new deep learning model, MHCAttnNet, uses Bi-LSTMs to predict the MHC-peptide binding more accurately than existing methods.
Facebook AI says DNNs can perform well without class specific neurons and overreliance on intuition-based methods for understanding DNNs can be misleading.
Probability trees may have been around for decades, but they have received little attention from the AI and ML community.
Amazon extracts an optimal subset of architectural parameters for BERT architecture by applying recent breakthroughs in algorithms for neural architecture search.
Now, just in time for costume season, another indie developer has taken facial image transfer tech to the opposite end of the cuteness spectrum, building a zombie generator.
Google recently introduced mT5, a multilingual variant of its “Text-to-Text Transfer Transformer” (T5), pretrained on a new Common Crawl-based dataset covering 101 languages.
Google Brain has improved the SOTA on the LibriSpeech automatic speech recognition task, with their score of 1.4 percent/ 2.6 percent word-error-rates.
Japanese AI startup Preferred Networks (PFN) is moving ChainerRL to the PyTorch ecosystem.
ICLR 2021 submission proposes LambdaNetworks, a transformer-specific method that reduces costs of modeling long-range interactions for CV and other applications.
Facebook AI open-sourced a multilingual machine translation (MMT) model that translates between any pair of 100 languages without relying on English data.
The UK researchers identify just how much AI research might benefit from the field of animal cognition.
Google AI recently launched the open-source browser-based toolset “rǝ,” which was created to enable the exploration of city transitions from 1800 to 2000 virtually in a three-dimensional view.
An international research team is suggesting AI might become even more efficient and reliable if it learns to think more like worms.
A new Facebook AI and CMU renewable energy storage project could enable labs to perform days of electrocatalyst screening and calculations in just seconds.
“The Computational Limits of Deep Learning” first author Neil Thompson of MIT says DL’s economic and environmental footprints are growing worrying fast
Pinkney and Adler NeurIPS 2020 workshop paper enables realistic image generation in domains such as animation and ukiyo-e with creative control on the output.
ICLR 2021 submitted paper proposes efficient VAEs that outperform PixelCNN-based autoregressive models in log-likelihood on natural image benchmarks.