Yearly Archives: 2021

Developers Can Now Use ONNX Runtime (Machine Learning Inference Engine) To Build Machine Learning Applications Across Android And iOS Platforms Through Xamarin

Traditionally, AI models were run over powerful servers in the cloud. Implementing β€œon-device machine learning,” like using mobile phones, is rarely heard of. This...

Researchers Demonstrate Face Detection in Untrained Deep Neural Networks

Identifying and recognizing faces is a fundamental skill for social interaction. This ability is assumed to be derived from single or multi-neuronal neuronal tuning....

Meta AI Announces the Beta Release of ‘Bean Machine’: A PyTorch-Based Probabilistic Programming System Used to Understand the Uncertainty in the Machine Learning Models

Meta AI releases the beta version of Bean Machine, a probabilistic programming framework based on PyTorch that makes it simple to describe and learn about...

OpenAI Researchers Find Ways To More Accurately Answer Open-Ended Questions Using A Text-Based Web Browser

Long-form question-answering (LFQA), a paragraph-length answer created in response to an open-ended question, is a growing difficulty in NLP. LFQA systems hold the potential...

A New Google Research Introduces ALX For Large Scale Matrix Factorization on TPUs

One of the most important approaches in recommender systems and graph analysis is matrix factorization. Alternating least squares (ALS) is a basic approach for...

IBM Research Unveils ‘VTFET’: A Revolutionary New Chip Architecture Which is Two Times the Performance finFET

On a silicon sheet, the most modern processors resemble expansive suburbs, with transistors stacked like blocks of dwellings. IBM attempts to flatten the entire...

Purdue University Research Introduces Parsimonious Neural Networks (PNNs) That Learn Interpretable Physical Laws Using Machine Learning

Machine learning systems use neural networks that are frequently too vast and sophisticated to quickly find the most basic explanation for an event or...

Huawei Research Introduces ‘VMAgent’: A Platform for Exploiting Reinforcement Learning (RL) on Virtual Machine (VM) Scheduling Tasks

In games and robotics simulators, reinforcement learning has demonstrated competitive performance. Solving mathematical optimization issues with RL approaches has recently attracted a lot of...

MIT Researchers Propose Patch-Based Inference to Reduce the Memory Usage for Tiny Deep Learning

Machine learning provides researchers with excellent tools for identifying and predicting patterns and behavior. These tools are also capable of learning, optimizing, and performing...

UC Berkeley Research Explains How Self-Supervised Reinforcement Learning Combined With Offline Reinforcement Learning (RL) Could Enable Scalable Representation Learning

Machine learning (ML) systems have excelled in fields ranging from computer vision to speech recognition and natural language processing. Yet, these systems fall short...

Meta AI Introduces A New AI Technology Called ‘Few-Shot Learner (FSL)’ To Tackle Harmful Content

For the training of AI models, a massive number of labeled data points or examples are required. Typically, the number of samples needed is...

Microsoft Researchers Introduce ‘FS-MOL’, A Few-Shot Learning Molecular Dataset, To Bring Deep Learning in Early-Stage Drug Discovery

The discovery, design, and testing phases of the drug development process are iterative. Drugs were previously sourced from plants and found through trial-and-error methods....

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