2020 in Review With Johan A.K. Suykens
Synced has invited Prof. Johan A.K. Suykens to share his insights about the current development and future trends of artificial intelligence.
Category: Machine Learning & Data Science
Japanese Manga Translation Via Multimodal Context-Aware Framework
A new machine translation method enables global manga fans to enjoy immediate translations of their favourite Japanese comics.
Are RL Agents More Humanlike When Not Seeking Rewards? New Research from Vector Institute, University of Toronto & Google Brain
Researchers from Vector Institute, University of Toronto and Google Brain recently studied three common types of intrinsic motivation across seven agents, three Atari games, and the 3D game Minecraft.
2020 in Review With Viral B. Shah
Synced has invited Dr. Viral B. Shah to share his insights about the current development and future trends of artificial intelligence.
Tsinghua University Releases First AutoML Toolkit for Graph Datasets & Tasks
Researchers from Tsinghua University have developed an AutoML framework and toolkit specifically designed for graph datasets and tasks.
2020 in Review With Jürgen Schmidhuber
Synced has invited Prof. Jürgen Schmidhube to share his insights about the current development and future trends of artificial intelligence.
2020 in Review: 10 Nonfiction Books AI Experts Enjoyed Reading
Synced has compiled a list of nonfiction books that notable AI researchers and engineers have recommended on Twitter over the last 12 months.
‘The Debate of the Next Decade’ – AI Debate 2 Explores AGI and AI Ethics
The four-hour event included three panel discussions: Architecture and Challenges, Insights from Neuroscience and Psychology, and Towards AI We Can Trust.
2020 in Review: 10 AI-Powered Art Projects
As part of our year-end series, Synced highlights 10 AI-powered art projects that inspired and entertained us in 2020.
2020 in Review: 10 AI Podcasts You Need to Know
Synced has selected 10 AI-related podcasts for readers to check out over the holiday season.
Heidelberg University Researchers Combine CNNs and Transformers to Synthesize High-Resolution Images
Researchers combine the effectiveness of the inductive bias in CNNs with the expressivity of transformers to model and synthesize high resolution images.
URI Researchers Trained CNN Networks to ID mosquitos
Rapid and accurate identification of mosquitoes that transmit human pathogens such as malaria is an essential part of mosquito-borne disease surveillance.
‘We Can Do It’ – Geoffrey Hinton and UBC, UT, Google & UVic Team Propose Unsupervised Capsule Architecture for 3D Point Clouds
In the new paper Canonical Capsules: Unsupervised Capsules in Canonical Pose, Turing Award Honoree Dr. Geoffrey Hinton and a team of researchers propose an architecture for unsupervised learning with 3D point clouds based on capsules.
2020 in Review: 10 AI Papers That Made an Impact
As part of our year-end series, Synced highlights 10 artificial intelligence papers that garnered extraordinary attention and accolades in 2020.
WILDS: Benchmarking Distribution Shifts in 7 Societally-Important Datasets
WILDS is an ambitious benchmark of in-the-wild distribution shifts spanning diverse data modalities and applications.
Facebook AI & University of Notre Dame Propose Multi-Face Pose Estimation Without Face Detection
University of Notre Dame and Facebook AI research propose Img2pose, real-time 6DoF 3D face pose estimation without face detection or landmark localization.
NeurIPS 2020 | Teaching Transformers New Tricks
This year, 22 Transformer-related research papers were accepted by NeurIPS, the world’s most prestigious machine learning conference. Synced has selected ten of these works to showcase the latest Transformer trends.
Mila Proposes New Inductive Biases to Boost Deep Learning
Yoshua Bengio and Anirudh Goyal from Mila - Quebec AI Institute delve into human and non-human animal intelligence and how it can inform deep learning.
NeurIPS 2020 | Machine Learning Vs Climate Change
Organizers of NeurIPS 2020 (Conference on Neural Information Processing Systems) see machine learning as an invaluable tool in the fight against climate change.
SlimGANs: Real-Time Adjustable Model Sizes
SlimGANs can easily change model sizes during runtime to implement quality-efficiency trade-offs based on practical needs.
A Brief History of Deep Learning Frameworks
Looking back at the evolution of deep learning frameworks we can clearly see a tightly coupled relationship between deep learning frameworks and deep learning algorithms.
Depix AI Recovers Pixelized Passwords, Earns 10K GitHub Stars
“Depix” is a new AI-powered tool that can easily undo pixelization to enable recovery of the information therein.
AWS Announces Amazon DevOps Guru
New machine learning powered operations service provides tailored recommendations to improve application availability
NeurIPS 2020 | Conference Watch on Self-Supervised Learning
This year, NeurIPS is hosting two workshops dedicated to self-supervised learning: Self-Supervised Learning for Speech and Audio Processing on Friday, December 11; and Self-Supervised Learning — Theory and Practice on Saturday, December 12.
MIT CSAIL Uses Deep Generative Model StyleGAN2 to Deliver SOTA Image Reconstruction Results
CSAIL researchers propose a framework for image reconstruction tasks using the state-of-the-art generative model StyleGAN2.
This Pizza Does Not Exist: StyleGAN2-Based Model Generates Photo-Realistic Pizza Images
The new AI-powered Multi-Ingredient Pizza Generator (MPG) can deliver all these mouth-watering pies and many more.
NeurIPS 2020: NVIDIA Achieves AI Training Breakthrough Using Limited Datasets of 1,500 Images
NVIDIA blog introduced company’s latest NeurIPS presentation: applying a novel neural network training technique, adaptive discriminator augmentation, to the popular NVIDIA StyleGAN2 model.
Open AI’s GPT-3 Paper Shares NeurIPS 2020 Best Paper Award With Works from Politecnico di Milano, CMU and UC Berkeley
OpenAI’s groundbreaking GPT-3 language model paper, a no-regret learning dynamics study from Politecnico di Milano & Carnegie Mellon University, and a UC Berkeley work on data summarization have been named the NeurIPS 2020 Best Paper Award winners.
NeurIPS 2020 | Probabilistic Approaches for Algorithmic Recourse With Limited Causal Knowledge
Max Planck Institute, University of Cambridge and Saarland University initiate two probabilistic approaches designed to achieve algorithmic recourse in practice
AAAI 2021 Announces Paper Totals – ‘Amazingly High Technical Level’
AAAI 2021 received a record-high 9034 submissions and over 7911 papers went to review and a total of 1692 papers made it, for an acceptance rate of 21 percent
Can Autonomous Vehicles Self-Learn the Rules of the Road?
What if, instead of hard-coding road rules into self-driving algorithms, AI agents were free to come up with their own ways of safely and efficiently sharing the road?
NVIDIA Neural Talking-Head Synthesis Makes Video Conferencing 10x More Bandwidth Efficient
The approach dramatically reduces bandwidth requirements by sending only a keypoint representation [of faces] and reconstructing the source video on the receiver side with the help of generative adversarial networks (GANs) to synthesize the talking heads.
Airbus AI Introduces Natural Language QA System for Flight Crews
Airbus has developed a new Smart Librarian (SL) FCOM QA system comprising a dialogue engine, retriever (search engine), and QA module.
Princeton Student’s AI Model Generates Chinese Landscape Paintings That Fool Human Evaluators
A Princeton student designed a GAN framework for Chinese landscape painting generation that is so effective most humans can’t distinguish its works from the real thing.
‘Biology’s ImageNet Moment’ – DeepMind Says Its AlphaFold Has Cracked a 50-Year-Old Biology Challenge
Google’s UK-based lab and research company DeepMind says its AlphaFold AI system has solved the protein folding problem, a grand challenge that has vexed the biology research community for half a century.
Synced Tradition and Machine Learning Series | Part 1: Entropy
This is the first in a special Synced series of introductory articles on traditionally theoretical fields of studies and their impact on modern day machine learning.
Facebook Proposes Free-Viewpoint Rendering on Monocular Video
Facebook’s new model enables free-viewpoint rendering of dynamic scenes in a single video.
USC & Amazon ‘SLADE’ Self-Training Framework Uses Unlabelled Data to Improve Information Retrieval
The SeLf-trAining framework for Distance mEtric learning (SLADE) framework combines self-supervised learning and distance metric learning methods to improve information retrieval performance.
University of Alberta U^2-Net: Generating Realistic Pencil Portraits Using Salient Object Detection
University of Alberta recently proposed U^2-Net, a novel deep network architecture that achieves very competitive performance in salient object detection.
McGill University, Facebook & Mila Release 14M Article NLP Pretraining Dataset for Medical Abbreviation Disambiguation
In EMNLP 2020, a Montreal-based research team introduced a large medical text dataset designed to boost abbreviation disambiguation in the medical domain.