New & Notable
Neural networks and deep learning News
November 20, 2020
These 3D chimera creatures are brought to you by Google's Chimera Painter, an AI-powered tool that turns 2D images into 3D creature models.
November 17, 2020
Amid the pandemic, Boston-based AI vendor DataRobot raised $270 million in a pre-IPO fundraising round. The company is likely to file for an IPO.
October 28, 2020
As the coronavirus pandemic has forced more businesses online, e-commerce fraud has spiked. AI fraud detection and prevention tools, however, can help merchants.
September 25, 2020
Disinformation could harm the 2020 presidential election, and technology simply isn't advanced enough to detect manipulated content, especially deepfakes.
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Learn how a design pattern based on convolutional neural networks can be adapted to create a visual graphics generator model for image recognition. Continue Reading
Machine learning is helping make motion analysis more usable for the average enterprise, creating new use cases and applications that can drive value. Continue Reading
GPT-3 is the latest natural language generation model, but its acquisition by Microsoft leaves developers wondering when, and how, they'll be able to use the model. Continue Reading
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Dive into Giuseppe Bonaccorso's recent book 'Mastering Machine Learning Algorithms' with a chapter excerpt on modeling neural networks. Continue Reading
Autoencoders are neural networks that serve machine learning models -- from denoising to dimensionality reduction. Seven use cases explore the practical application of autoencoder technology. Continue Reading
Enterprises are adopting machine learning technologies at rapid rates. In this machine learning guide, we break down what you need to know about this transformative technology. Continue Reading
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Overfitting remains a common model error, but data scientists can combat the problem through automated machine learning, improving AI literacy and creating test data sets. Continue Reading
Giant AI chips like the Cerebras WSE are dazzlingly fast and could transform AI models, but how soon is the question for CIOs. Experts mull the merits of small vs. big AI chips. Continue Reading
Deep learning model training requires not only the right amount of data, but the right type of data. Enterprises must be inventive and careful when training their models. Continue Reading
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Autoencoders' ability for automated feature extraction, data preparation, and denoising are complicated by their common problems and limitations in usage. Continue Reading
Bias in AI is a systematic issue that derails many projects. Dismantling the black box of deep learning algorithms is crucial to the advancement and deployment of the technology. Continue Reading
The personal mobility market is turning to emotional analysis and AI to negate fear and trepidation around emerging vehicle technology and the future of transportation. Continue Reading