Welcome to the Abacus.AI blog

Most of the machine learning applications are concerned with processing data such as images or databases – their key characteristic is that they can be “taken in” by a learning model all at once. They don’t have any temporal properties. Today we’ll be talking about a different case – models that deal with data that is sequential by nature, text, and voice being several examples.

Neural architecture search (NAS) is a popular area of machine learning, with the goal of automating the development of the best neural network for a given dataset. In this post, we summarize our recent paper, which suggests that existing NAS benchmarks may be too small to effectively evaluate NAS algorithms.

In this post, we give an introduction to bias in machine learning, and we discuss new techniques for debiasing pretrained neural networks (i.e., post-hoc debiasing).

When reading about Machine Learning, the majority of the material you’ve encountered is likely concerned with classification problems. What about the other way around when you want to create data with predefined features? Today we’ll be breaking down VAEs and understanding the intuition behind them.

Like many other Machine Learning concepts, meta-learning is an approach akin to what human beings are already used to doing. Meta-learning simply means “learning to learn.”

Pattern recognition is a crucial aspect of modern data analytics. These patterns can be studied to better understand the underlying structure of data and monitor behavior over time. However, there are often rare items or observations that seem to differ significantly from these patterns. These items are called anomalies (or outliers).

The painting “Edmond de Belamy” is an AI-generated portrait that was sold at an auction for $432,500 in 2018. That’s a lot of money for an artificial painting, but how exactly was it created? Generative Adversarial Networks.

Over just a few months, the new coronavirus disease (COVID-19) has grown from several cases in Wuhan province to a global health threat. News has been brimming with the term “flattening the curve”, which comes from what science currently understands about the spread of diseases like COVID-19.

In this post, we discuss the details behind our GAN demo at RealityEngines.AI. Generative adversarial networks (GANs) are viewed by many as the most exciting deep learning development of the last decade, with many applications...