Yearly Archives: 2021

MLCommons Releases Both A Multilingual Speech Dataset And A Large 30,000 Hour Diverse English Dataset To Drive Democratization of Machine Learning

The MLCommons Association, an open engineering community, dedicated to making machine learning more accessible to everyone, has released free datasets and technologies to help...

Microsoft Research Introduces ‘BugLab’: A Deep Learning Model to Detect and Fix Bugs Without Using Labelled Data

Finding and repairing problems in code is a time-consuming and frequently unpleasant element of software engineers' day-to-day work. Can deep learning solve this challenge...

Understanding AlphaZero Neural Network’s SuperHuman Chess Ability

As a common and (sometimes) proven belief, deep learning systems seem to learn uninterpretable representations and are far from human understanding. Recently, some studies...

OpenAI Releases A New Feature That Allows Developers To Customize GPT-3, Its Powerful Natural Language Processing (NLP) Model

GPT-3 is the advanced natural language processing model developed by OpenAI. It returns a natural language text completion in response to any text request,...

Researchers from MIT, Yonsei University, and University of Brasilia Introduce ‘Computer Progress’: A New Portal to Analyze the Computational Burden From Over 1,000 Deep...

Deep Learning is now being used to predict how proteins fold, translate between languages, Analyze medical scans, and play complex games like Go, to...

Google AI Proposes Temporal Fusion Transformer (TFT): An Attention-Based DNN (Deep Neural Network) Model For Multi-Horizon Forecasting

Deep learning technologies, such as automatic learning of temporal dependence and automated handling of temporal structures like trends and seasonality, hold a lot of...

‘HiClass’: A Python Package that Provides Implementations of Popular Machine Learning Models and Evaluation Metrics for Local Hierarchical Classification

Classification is the process of grouping items into categories. Classification problems can be naturally modeled hierarchically, typically in the tree or directed acyclic graph...

Google AI Introduces ‘GSPMD’: A Largely Automated Parallelization System For Machine Learning Computation Graphs

In many machine learning (ML) applications of the real world, such as language understanding, computer vision, and neural machine translation, scaling neural networks, whether...

Google AI’s ‘TokenLearner’ Can Improve Vision Transformer Efficiency And Accuracy

Transformer models consistently obtain state-of-the-art computer vision tasks, including object detection and video classification. In standard convolutional approaches, images are processed pixel-by-pixel. To obtain...

Researchers Propose ‘ProxyFL’: A Novel Decentralized Federated Learning Scheme For Multi-Institutional Collaborations Without Sacrificing Data Privacy

Tight rules generally govern data sharing in highly regulated industries like finance and healthcare. Federated learning is a distributed learning system that allows multi-institutional...

Researchers Develop i-Melt: A Deep Neural Network That Can Predict Glass Quality Based On Melt Composition

Glass can be found all around us. It's in our computer screens, next-generation batteries, medical implants, and even volcanoes. Glass is manufactured by melting something...

AI Researchers Propose ‘GANgealing’: A GAN-Supervised Algorithm That Learns Transformations of Input Images to Bring Them into Better Joint Alignment

The correspondence problem of visual alignment is one that computer vision algorithms must solve for many different applications.It's considered a critical element in Optical...

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