Facebook AI RegNet Models Outperform EfficientNet Models, Run 5x Faster on GPUs
Researchers from Facebook AI introduce a novel low-dimensional design space, RegNet, which produces simple, fast and versatile networks.
Author: Synced
Machine Intelligence | Technology & Industry | Information & Analysis
DarwinAI Open-Sources COVID-Net as Medical Imaging in COVID-19 Diagnosis Debate Continues
Researchers recently developed and open-sourced COVID-Net, a convolutional neural network for detecting COVID-19 through chest radiography.
Fei-Fei Li Proposes AI-Assisted Elder Care Solution at Stanford-Hosted Virtual Conference on COVID‑19 and AI
Fei-Fei Li, Stanford computer science professor and co-director of Stanford’s Human-Centered AI Institute (HAI), shared her thoughts on possible AI technologies that could help care for the seniors during the coronavirus pandemic
Google DeepMind ‘Agent 57’ Beats Human Baselines Across Atari Games Suite
Agent57 is the first deep reinforcement learning (RL) agent to top human baseline scores on all games in the Atari57 test set.
Synced Machine Intelligence Awards Recognize Innovation: 50 Industry Leaders and 60 Solutions
The Synced Machine Intelligence Awards 2019 focus is on “the power of industry,” and the selection process keyed in on AI products, application cases and industry landings, with choices based on verifiable industry performance.
New Fujitsu & Inria Tech Automatically Builds Anomaly-Detecting AI Models
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 Interface Elegantly and Efficiently Organizes Web COVID-19 Papers
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.
Women in AI | Chelsea Finn: ‘I Certainly Feel Like a Minority’
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.
Westlake University Researchers Show How SARS-CoV-2 Binds to Human Cells
Respected journal Science Magazine has published COVID-19 research that identifies the viral entry attachment stage for the new coronavirus.
Physical Distancing Boosts AI-Powered Online Education in China
Many artificial intelligent education institutions are offering free online courses and accounts to students.
‘Front2Back’ AI Reconstructs 3D Shapes from 2D Images
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.
UN, WHO & Mila Map the AI vs COVID-19 Battlefield
Researchers looks at current studies that are using AI to tackle the COVID-19 crisis and suggests some promising future research directions.
AI Deciphers Persian Cuneiform Tablets from 25 Centuries Ago
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.
Novel Hybrid Continual Learning Algorithm Counters Agent Forgetfulness
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
New Compression Method Enables Conditional GANs on Edge Devices
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.
WFH Parents: Here’s an AI Toybox for Your Kids!
Synced looked into smart solutions that could help keep kids engaged and entertained, and might even be educational.
Google Introduces Neuroevolution for Self-Interpretable Agents
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.
Impact of ImageNet Model Selection on Domain Adaptation
Researchers investigate how different ImageNet models affect transfer accuracy on domain adaptation problems.
China’s Autonomous Delivery Vehicles Navigate the Coronavirus Outbreak
In autonomous food and medicine delivery and beyond, the increasingly mature AI industry is actively engaged in countering the COVID-19 outbreak.
Google Brain Open-Sources EfficientDet: SOTA Performance, 28x Fewer Flops
Google Brain announced this week that it is open-sourcing its object detector EfficientDet, which achieves SOTA performance while requiring significantly less compute.
Folding@Home: How Your PC Can Help in the Fight Against COVID-19
The new goal of the Folding@home project is modelling the structure of SARS-CoV-2 spike protein to identify sites that can be targeted by a therapeutic antibody.
2019 Turing Award Honours Computer Graphics Pioneers Hanrahan and Catmull
The Association for Computing Machinery (ACM) this morning announced Patrick M. (Pat) Hanrahan and Edwin E. (Ed) Catmull as its 2019 Turing Award winners.
AI CT Scan Analysis for COVID-19 Detection and Patient Monitoring
A research team has proposed non-contrast thoracic chest CT scans as an effective tool for detecting, quantifying, and tracking COVID-19.
‘Semantic Generation Pyramid’ for Image Generation and Manipulation
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.
White House & Partners Launch COVID-19 AI Open Research Dataset Challenge on Kaggle
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.
Learning From the 1854 Cholera Outbreak: Tracking and Containing COVID-19 Using AI Spatiotemporal Analysis
“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.”
Beijing Self-Driving Vehicle Road Tests Topped One Million Km in 2019
A recent report suggests China has picked up speed, with Beijing emerging as a new self-driving vehicle hot spot.
Exploring Gender Imbalance in AI: Numbers, Trends, and Discussions
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.
BERTLang Helps Researchers Choose Between BERT Models
Researchers from Bocconi University have prepared an online overview of the commonalities and differences between language-specific BERT models and mBERT.
Beyond Lipreading: Visual Speech Recognition Looks You in the Eye
A new study suggests that VSR models could perform even better if they used additional available visual information.
Chinese Researchers Use CNNs to Classify 3000-Year-Old Oracle Bone Scripts
The earliest evidence of China’s recorded history is found in the Shang dynasty (~1600 to 1046 BC), and this hasContinue Reading
Synthesized Paired Data Boosts Facial Manipulation
The model outperforms existing methods in image manipulation and offers researchers a possible solution to the scarcity of paired datasets.
ICLR 2020 Cancelled Over Coronavirus; Virtual Conference Arranged
Organizers announced today that the COVID-19 outbreak and associated travel restrictions have forced the cancellation of the “physical conference” ofContinue Reading
Augmented Training Scheme Fixes CNN Texture Bias
Researchers proposed a new training scheme that targets this bias by controlling and exposing textural information slowly through the training process.
‘Train Large, Then Compress’ – UC Berkeley BAIR Improves Large Transformer Model Training and Inference
Researchers from the Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley explored the effect of Transformer model size on training and inference efficiency.
AutoCompress: SOTA Automatic DNN Pruning for Ultra-High Compression Rates
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.
Google DeepMind Releases Structure Predictions for Coronavirus Linked Proteins
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.
100M Masks/Day: Automated Production Lines Work Overtime to Stop COVID-19 Spread
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.
AI-Based Drug Discovery Pipeline Generates Novel Drug Compounds against Coronavirus
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.
Yoshua Bengio and Team Introduce GNN Benchmarking Framework
Researchers propose a flexible GNN benchmarking framework that can also accommodate the needs of researchers to add new datasets and models.