AI Technology & Industry Review
Fujitsu has collaborated with Inria to develop a new technology that can automatically create AI models that detect anomalies by extracting the necessary information from time-series data.
Covid-Sanity, a web interface designed to navigate the flood of bioRxiv and medRxiv COVID-19 papers and make the research within more searchable and sortable.
As part of the Women in AI special project, Synced spoke with Chelsea Finn, an assistant professor in Computer Science and Electrical Engineering at Stanford University.
Many artificial intelligent education institutions are offering free online courses and accounts to students.
Their proposed framework outperforms state-of-the-art approaches for 3D reconstructions from 2D and 2.5D data, achieving 12 percent better performance on average in the ShapeNet benchmark dataset and up to 19 percent for certain classes of objects.
Researchers looks at current studies that are using AI to tackle the COVID-19 crisis and suggests some promising future research directions.
Researchers from the University of Chicago Oriental Institute (OI) and the Department of Computer Science have introduced an artificial intelligence tool called DeepScribe designed to read cuneiform tablets from 25 centuries ago.
Researchers have introduced a novel hybrid continual learning algorithm, Adversarial Continual Learning, which aims to enable the persistent explicit or implicit replay of experiences by storing original samples
A research team from MIT, Adobe Research, and Shanghai Jiao Tong University have introduced a novel method for reducing the cost and size of Conditional GAN generators.
Synced looked into smart solutions that could help keep kids engaged and entertained, and might even be educational.
Researchers from Google Brain Tokyo and Google Japan have proposed a novel approach that helps guide reinforcement learning (RL) agents to what’s important in vision-based tasks.
Researchers investigate how different ImageNet models affect transfer accuracy on domain adaptation problems.
In autonomous food and medicine delivery and beyond, the increasingly mature AI industry is actively engaged in countering the COVID-19 outbreak.
Google Brain announced this week that it is open-sourcing its object detector EfficientDet, which achieves SOTA performance while requiring significantly less compute.
The Association for Computing Machinery (ACM) this morning announced Patrick M. (Pat) Hanrahan and Edwin E. (Ed) Catmull as its 2019 Turing Award winners.
A research team has proposed non-contrast thoracic chest CT scans as an effective tool for detecting, quantifying, and tracking COVID-19.
Researchers have proposed a new image generative model that leverages the hierarchical space of deep features learned by pretrained classification networks and provides a unified and versatile framework for image generation and manipulation tasks.
The White House on Monday joined a number of research groups to announce the release of the COVID-19 Open Research Dataset (CORD-19) of scholarly literature about COVID-19, SARS-CoV-2, and the Coronavirus group.
“In epidemiology analysis, the relationship between people in space and time is very important,” explains Bao Jie, head of the JD Group city data management platform, “and human activity trajectories are a typical form of spatiotemporal data.”
A recent report suggests China has picked up speed, with Beijing emerging as a new self-driving vehicle hot spot.
Women currently make up 24.4% of the computer science workforce and receive median salaries that are only 66% of the salaries of their male counterparts.
Researchers from Bocconi University have prepared an online overview of the commonalities and differences between language-specific BERT models and mBERT.
A new study suggests that VSR models could perform even better if they used additional available visual information.
The earliest evidence of China’s recorded history is found in the Shang dynasty (~1600 to 1046 BC), and this hasContinue Reading
The model outperforms existing methods in image manipulation and offers researchers a possible solution to the scarcity of paired datasets.
Organizers announced today that the COVID-19 outbreak and associated travel restrictions have forced the cancellation of the “physical conference” ofContinue Reading
Researchers proposed a new training scheme that targets this bias by controlling and exposing textural information slowly through the training process.
Researchers from the Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley explored the effect of Transformer model size on training and inference efficiency.
Researchers proposed an automatic structured pruning framework, AutoCompress, which adopts the 2018 ADMM-based weight pruning algorithm and outperforms previous automatic model compression methods while maintaining high accuracy.
DeepMind released the structure predictions for six proteins associated with SARS-CoV-2, the virus that causes COVID-19, using the most up-to-date version of their AlphaFold system.
Pushed by the coronavirus outbreak, in early March 2020 China’s face mask production hit 110 percent capacity, with daily output exceeding 100 million masks according to state agency statistics.
A new study leverages an established AI-based drug discovery pipeline to produce molecular structures as part of the widening fight against the 2019-nCoV outbreak.
Researchers propose a flexible GNN benchmarking framework that can also accommodate the needs of researchers to add new datasets and models.
Shum will speak at China’s Tsinghua University in Beijing, where he will formally assume a Dual-Professorship position with the prestigious school’s Institute for Advanced Study.
UC Berkeley and Adobe Research have introduced a “universal” detector that can distinguish real images from generated images regardless of what architectures and/or datasets were used for training.
Proposed by researchers from the Rutgers University and Samsung AI Center in the UK, CookGAN uses an attention-based ingredients-image association model to condition a generative neural network tasked with synthesizing meal images.
The KaoKore dataset includes 5552 RGB image files drawn from the 2018 Collection of Facial Expressions dataset of cropped face images from Japanese artworks.
The paper acceptance rate fell to approximately 22 percent from 25 percent in 2019 and 29.6 percent in 2018.
Researchers propose a novel model compression approach to effectively compress BERT by progressive module replacing.
The crowdsourcing produced 111.25 hours of video from 54 non-expert demonstrators to build “one of the largest, richest, and most diverse robot manipulation datasets ever collected using human creativity and dexterity.”