AI Technology & Industry Review
Global machine intelligence updates.
In a bid to solve the temporal generalization problem of modern language models, a team of DeepMind researchers propose it’s time to develop adaptive language models that will remain up-to-date in our ever-changing world.
A new study by University Tübingen introduces the world’s largest unified eye dataset with over 20 million human eye images captured using head-mounted eye trackers.
To track progress in natural language generation (NLG) models, 55 researchers from more than 40 prestigious institutions have proposed GEM (Generation, Evaluation, and Metrics), a “living benchmark” NLG evaluation environment.
The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21) kicked off today as a virtual conference. The organizing committee announced the Best Paper Awards and Runners Up during this morning’s opening ceremony.
A bold Carnegie Mellon University (CMU) team recently explored the prospect of using AI to review AI papers.
Researchers from the University of Sheffield, Beihang University, and Open University’s Knowledge Media Institute have proposed a transfer learning approach that can automatically process historical texts at a semantic level to generate modern language summaries.
A new study by the Georgia Institute of Technology and Facebook AI introduces TT-Rec, a way to drastically compress the size of memory-intensive Deep Learning Recommendation Models (DLRM) and make them easier to deploy at scale.
A recent study by the Google Brain Team proposes a new way of programming automated machine learning (AutoML) based on symbolic programming.
UmlsBERT is a deep Transformer network architecture that incorporates clinical domain knowledge from a clinical Metathesaurus in order to build ‘semantically enriched’ contextual representations that will benefit from both the contextual learning and domain knowledge.
A new study by NVIDIA, University of Toronto, McGill University and the Vector Institute introduces an efficient neural representation that enables real-time rendering of high-fidelity neural SDFs for the first time while delivering SOTA geometry reconstruction quality.
Researchers from University of California, Merced and Microsoft have introduced ZeRO-Offload, a novel heterogeneous DL training technology that enables training of multi-billion parameter models on a single GPU without any model refactoring.
A new BibTeX-normalizing tool dubbed Rebiber is gaining popularity in the AI research community. The creation of a PhD student, Rebiber addresses incomplete or confusing paper citation information.
Researchers from Naver AI Lab says they’ve found a computationally efficient re-labelling strategy that fixes a significant flaw in popular image classification benchmark ImageNet.
On January 22, Beijing-based AI firm 4Paradigm announced USD 700 million series D investments from Boyu Capital, Primavera Capital and Hopu Investments.
Recent footage shows agricultural robot co-developed by National Research Institute Agricultural Research Organization, Ritsumeikan University, and automobile parts manufacturer Denso harvesting apples in Japan’s orchards.
Is it possible for machines to understand and integrate human emotions in visual arts? Meet ArtEmis, a new large-scale dataset of emotional reactions and explanations for visual artworks.
Analyzing papers and patent data collected from top AI journals and conferences, 44 in total from 2011 to 2020, Tsinghua University’s new AI development report revealed new statistical insights.
IBM has closed off its Beijing-based China Research Laboratory (CRL) after 25 years of operation.
This is the second in a special Synced series of introductory articles on traditionally theoretical fields of studies and their impact on modern-day machine learning.
This paper is the first to systematically study the security of Multi-Sensor Fusion (MSF) based localization in high-autonomy Autonomous Vehicles (AVs). Researchers design FusionRipper, a novel and general attack that opportunistically captures and exploits take-over vulnerabilities.
Researchers from Drexel University, Northeastern University and IT University Copenhagen explore how humans interact with AI in such contexts, with a focus on computer games.
In a new paper, Stanford University researchers dispel the assumption that boosting deep learning model performance on ImageNet translates to better performance on medical imaging tasks.
Synced invited Dr. Linchao Zhu, a lecturer at the ReLER lab, University of Technology Sydney whose works focus on video representation learning, to share his thoughts on the paper Text-to-Image Generation Grounded by Fine-Grained User Attention.
According to reports on January 20, South Korea’s Gwangju is adopting integrated AI technology to help with city governance.
On January 18, in efforts to understand and manage extreme weather events, McGill University announced a new interdisciplinary project to combine deep learning (DL) with social network analysis (SNA).
A Nepalese machine learning (ML) researcher has introduced a handy browser extension that lets users directly access videos related to research papers published on the popular preprint platform arXiv.
Kuzi is using satellite data, soil sensor data, ground meteorological observation and machine learning technology trained on predict the locusts’ breeding, appearance and migration routes.
Researchers from the City University of Hong Kong and SenseTime propose a lightweight matting objective decomposition network (MODNet) that can smoothly process real-time human matting from a single input image with diverse and dynamic backgrounds.
A new study proposes using human feedback and interaction logs to boost offline reinforcement learning (RL) in natural language processing (NLP).
Shenzhen launched the construction of the Automatic Testing Center for Metro Center which is scheduled to be put into operation in June 2021.
ABB announced an investment of RMB 1 billion to build a new robot super factory in Shanghai, which began construction in 2019.
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
A new AI Expert Roadmap developed by German software company AMAI is garnering keen interest from aspiring AI professionals around the world.
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.
NeurIPS 2020 Institute of Automation CAS and Microsoft Research Asia paper presents an attention-based decoder that integrates CV object representations
Facebook researchers introduced a new research platform for dynamic data collection and benchmarking called Dynabench, which will offer a more accurate and sustainable way for evaluating progress in AI.
On September 13th, NVIDIA announced the acquisition of UK-based semiconductor startup ARM for US$40 billion, unveiling the largest acquisition dealContinue Reading