Stable Diffusion: Generating Images Out of Thin Air

Stable Diffusion is a free, open-source neural network for generating photorealistic and artistic images based on text-to-image and image-to-image diffusion models. Read our tips to start generating your own masterpieces in minutes.

A Guide to One-Shot Learning

Find out how the one-shot learning algorithm works and the practical applications of this novel paradigm in neural networks.

NN Research Best Practices: Interview with Dr. Varun Ojha

What are the best strategies for training neural networks? How to avoid overfitting? Which open-source datasets to choose? Find the answers to these questions in our interview with Dr. Varun Ojha.

Deep Learning Applications for Computer Vision

Deep learning has been a game changer in the field of computer vision. It’s widely used to teach computers to “see” and analyze the environment similarly to the way humans do.

How Sber Built ruDALL-E: Interview with Sergei Markov

What does it take to build a model with 12 billion parameters? Why is open-source culture important in machine learning research? Find out the answers to these questions in our interview with Sergei Markov, the chief of the SberDevices experimental machine learning systems department.

Is Self-Supervised Learning the Future of AI?

Self-supervised learning is one of the most popular approaches to ML today. SSL algorithms don’t require manual target labeling and can obtain all the information they need from the data. Find out more about how they work in our new post.

Convolutional Neural Networks for Beginners

This beginner guide will help you understand how convolution neural networks (CNNs) work and what they are useful for.

A Guide to Deep Learning and Neural Networks

The difference between deep learning and neural networks is often confusing for beginners. What does it mean for an algorithm to be “deep”? What types of neural networks exist out there? You’ll learn all that and more in our guide.

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