Artificial Intelligence - Paperspace Blog

Fighting COVID-19 with Data and AI: A Review of Active Research Groups and Datasets

The economy has come to a halt; people are quarantined; work is stagnating; and governments fear the public health crisis this could turn into. The deadly coronavirus (SARS-CoV-2, or COVID-19

News

How AI And Deep Learning Are Shaping Education: An Interview With Terry Sejnowski

Among Terry Sejnowski’s many interests has been a focus on education, specifically how we can use what we know about learning in the brain to improve education. A little

News

Do Machines Dream? An Interview With Terry Sejnowski on Boltzmann Machines and The Brain

Terry Sejnowski is one of the pioneers of deep learning who, together with Geoffrey Hinton, created Boltzmann machines: a deep learning network that has remarkable similarities to learning in the

News

The Future of ML: Unsupervised Learning, Reinforcement Learning, or Something Else?

Yoshua and Samy Bengio, Yann Lecun, Rich Sutton and Sergey Levine talk about the future of machine learning and how unsupervised learning methods will likely get us to human-level intelligence in machines.

News

Climate Change, China and AI

Climate change and competition with China are the two things that top my list of the most important trends in machine learning. I had the opportunity to talk with key people in both of those realms in recent months for the Eye on AI podcast.

Computer Vision

Image Captioning With AI

One application that has really caught the attention of many folks in the space of artificial intelligence is image captioning. If you think about it, there is seemingly no way

Generative Models

A 2020 Guide to Synthetic Media

Synthetic media is an exciting new area of research that has seen great advancements in the past few years. This field has the potential to completely revolutionize the way we

Artificial Intelligence

Introducing The AI Wiki 🧠

We made the AI Wiki to keep the world of artificial intelligence a little less daunting. With easy-to-understand definitions and helpful graphics, the AI Wiki explains dozens of topics in AI, machine learning and deep learning, for beginners and practitioners alike.

Python

Cythonizing Genetic Algorithms: 18x Faster

In this tutorial we use Cython to reduce the execution time of the genetic algorithm implemented in Python. We've brought down our computational time from 1.46 seconds to a mere 0.08 seconds, so that 1 million generations run in less than 10 seconds with Cython, compared to 180 seconds in Python.

Generative Models

Implementing CycleGAN for Age Conversion

If you've been on any sort of social media this year, you've probably seen people uploading a recent picture of themselves right next to another picture of what they'll look

Advanced Technologies Group

Move Quickly, Think Deeply: How Research Is Done @ Paperspace ATG

The Advanced Technologies Group is an R&D-focused team here at Paperspace, comprising ML Engineers and Researchers. As a group, we're interested in exploring advanced topics in deep learning,

Deep Learning

Going beyond torchvision models

ResNets, DenseNets and Inception networks are undoubtedly some of the most powerful models out there for performing image classification and object recognition. These models have shown some promising results in

CI/CD

CI/CD for Machine Learning & AI

The ecosystem for developing modern web applications is incredibly rich. There are countless tools for delivering a modern web app to production, monitoring it's performance, and deploying in real-time. These

Gradient

What's new in Gradient?

We've been hard at work developing Gradient° into a robust and scalable deep-learning platform. Here's a roundup of some of the things we've added recently: Product release notes can be

Computer Vision

Facial Recognition Using Deep Learning

Convolutional Neural Networks (CNN) and Feature Extraction Convolutional Neural Networks allow us to extract a wide range of features from images. Turns out, we can use this idea of feature extraction for face recognition too! That’s what we are going to explore in