AI Technology & Industry Review
A research team lead by Geoffrey Hinton has created an imaginary vision system called GLOM that enables neural networks with fixed architecture to parse an image into a part-whole hierarchy with different structures for each image.
A research team from Facebook AI has proposed a Unified Transformer (UniT) encoder-decoder model that jointly trains on multiple tasks across different modalities and achieves strong performance on seven tasks with a unified set of model parameters.
A team from Microsoft and Université de Montréal proposes a new mathematical framework that uses measure theory and integral operators to achieve the goal of quantifying the regularity of the attention operation.
A research team from UC Berkeley, University of Maryland and UC Irvine identifies pitfalls that cause instability in the GPT-3 language model and proposes a contextual calibration procedure that improves accuracy by up to 30 percent.
On February 3, Japanese automotive manufacturer Toyota has began to construct a high-tech city at the base of Mount Fuji.
South Korea’s Customs Service has partnered with the government-funded Institute for Basic Science (IBS) to conduct joint research on AI technology using customs trade data.
Dell Technologies has opened a new innovation facility in Singapore, to focus on R&D for edge computing, data analytics and augmented reality.
On February 18, Baidu released the 2020 full year and Q4 financial report, presenting revenue of RMB 107.1 Billion, and its net profit of RMB 22 billion.
On February 19, Beijing-based AI startup Unisound has decided halted its IPO application to the Shanghai Stalk Exchange.
A Microsoft team has introduced Error Analysis, a responsible AI toolkit designed to identify and diagnose errors in machine learning models.
University of Toronto researchers propose a BERT-inspired training approach as a self-supervised pretraining step to enable deep neural networks to leverage newly and publicly available massive EEG (electroencephalography) datasets for downstream brain-computer-interface (BCI) applications.
A research team from Google and Johns Hopkins University identifies variance-limited and resolution-limited scaling behaviours for dataset and model size in four scaling regimes.
British consulting firm L.E.K. has released a recent research report stating that as unmanned technology and network scale greatly reduce costs, by 2040, drones may account for as much as 30 percent of same-day parcel deliveries.
On February 16, Goldman Sachs announced that it is launching an automated wealth management platform to invest client funds in a portfolio of stocks and bonds.
According to statement on February 12, Chinese AI chip unicorn Horizon Robotics announces a third time series C financing.
As part of the long-term strategy to “expand AI capabilities”, Swiss flavours and fragrance giant Givaudan announced that it will acquire the French company Myrissi.
UC Berkeley, Facebook AI Research and New York University researchers’ Multiple Sequence Alignments (MSA) Transformer surpasses current state-of-the-art unsupervised structure learning methods by a wide margin.
DeepMind has designed a family of Normalizer-Free ResNets (NFNets) that can be trained in larger batch sizes and stronger data augmentations and have set new SOTA validation accuracies on ImageNet.
Stanford researchers’ DERL (Deep Evolutionary Reinforcement Learning) is a novel computational framework that enables AI agents to evolve morphologies and learn challenging locomotion and manipulation tasks in complex environments using only low level egocentric sensory information.
The research develop machine learning methods that enable virtual agents (such as avatars from a computer game) to communicate non-verbally.
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.
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.
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.
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.
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.
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.
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 University of Texas, Austin have proposed a novel framework called Training-Free Neural Architecture Search (TE-NAS) for “training-free” neural architecture search.
As part of our year-end series, Synced highlights 10 AI-powered art projects that inspired and entertained us in 2020.
Synced has selected 10 AI-related podcasts for readers to check out over the holiday season.
The Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) kicked off on Monday as a virtual conference.
DeepMind and Universidade de Lisboa introduce graph-based toolkit for analyzing and comparing multiplayer games
The 36th International Conference on Machine Learning (ICML) kicked off Monday in California. The ICML is one of the world’s two top conferences in ML and AI (the other being NeurIPS).
On Sunday, March 10, an Ethiopian Airlines Boeing 737 MAX 8 aircraft en route to Nairobi crashed shortly after takeoff from Addis Ababa, killing all 157 people on board. It was the second fatal crash in six months involving Boeing 737 MAX 8 airplanes.