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.
AI Technology & Industry Review
Synced has invited Prof. Johan A.K. Suykens to share his insights about the current development and future trends of artificial intelligence.
A new machine translation method enables global manga fans to enjoy immediate translations of their favourite Japanese comics.
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.
Synced has invited Dr. Viral B. Shah to share his insights about the current development and future trends of artificial intelligence.
Researchers from Tsinghua University have developed an AutoML framework and toolkit specifically designed for graph datasets and tasks.
Synced has invited Prof. Jürgen Schmidhube to share his insights about the current development and future trends of artificial intelligence.
Synced has compiled a list of nonfiction books that notable AI researchers and engineers have recommended on Twitter over the last 12 months.
The four-hour event included three panel discussions: Architecture and Challenges, Insights from Neuroscience and Psychology, and Towards AI We Can Trust.
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.
Researchers combine the effectiveness of the inductive bias in CNNs with the expressivity of transformers to model and synthesize high resolution images.
Rapid and accurate identification of mosquitoes that transmit human pathogens such as malaria is an essential part of mosquito-borne disease surveillance.
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.
As part of our year-end series, Synced highlights 10 artificial intelligence papers that garnered extraordinary attention and accolades in 2020.
WILDS is an ambitious benchmark of in-the-wild distribution shifts spanning diverse data modalities and applications.
University of Notre Dame and Facebook AI research propose Img2pose, real-time 6DoF 3D face pose estimation without face detection or landmark localization.
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.
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.
Organizers of NeurIPS 2020 (Conference on Neural Information Processing Systems) see machine learning as an invaluable tool in the fight against climate change.
SlimGANs can easily change model sizes during runtime to implement quality-efficiency trade-offs based on practical needs.
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” is a new AI-powered tool that can easily undo pixelization to enable recovery of the information therein.
New machine learning powered operations service provides tailored recommendations to improve application availability
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.
CSAIL researchers propose a framework for image reconstruction tasks using the state-of-the-art generative model StyleGAN2.
The new AI-powered Multi-Ingredient Pizza Generator (MPG) can deliver all these mouth-watering pies and many more.
NVIDIA blog introduced company’s latest NeurIPS presentation: applying a novel neural network training technique, adaptive discriminator augmentation, to the popular NVIDIA StyleGAN2 model.
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.
Max Planck Institute, University of Cambridge and Saarland University initiate two probabilistic approaches designed to achieve algorithmic recourse in practice
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
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?
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 has developed a new Smart Librarian (SL) FCOM QA system comprising a dialogue engine, retriever (search engine), and QA module.
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.
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.
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’s new model enables free-viewpoint rendering of dynamic scenes in a single video.
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 recently proposed U^2-Net, a novel deep network architecture that achieves very competitive performance in salient object detection.
In EMNLP 2020, a Montreal-based research team introduced a large medical text dataset designed to boost abbreviation disambiguation in the medical domain.