What is A/B Testing? Almost everyone hated learning statistics (well, maybe except some statisticians). With all those distributions and critical values that we needed to memorize, we just ended up with a headache. You might have swore not to ever touch the subject again; that is, until you had to analyze an A/B test. A/B testing is the “fun” name … [Read more...] about Why You Should Switch To Bayesian A/B Testing
Technical Guide
How Can You Tell If Your Recommender System Is Any Good?
It’s an exciting time to be working on recommender systems. Not only are they more relevant than ever before, with Facebook recently investing in a 12 trillion parameter model and Amazon estimating that 35% of their purchases come from recommendations, but there is a wealth of powerful, cutting edge techniques with code available for anyone to try. So the … [Read more...] about How Can You Tell If Your Recommender System Is Any Good?
How Does An AI Imagine The Universe?
What’s out there? In this vast, infinite and inconceivable universe… Stars, planets, nebulae and celestial bodies are colliding, orbiting, being born and dying since the dawn of time. Humans have always looked up to the sky with fascination, imagining fantastic worlds and unreachable galaxies, and this has prompted mankind to use science to better understand the … [Read more...] about How Does An AI Imagine The Universe?
Introduction To AI For Social Good
AI for Social Good — a relatively new research field at the intersection of AI and a number of other fields. Source “Whenever I hear people saying AI is going to hurt people in the future I think, yeah, technology can generally always be used for good and bad and you need to be careful about how you build it … if you’re arguing against AI then you’re arguing against … [Read more...] about Introduction To AI For Social Good
Self-Supervised Learning In Vision Transformers
Anyone who has ever approached the world of machine learning has certainly heard of supervised learning and unsupervised learning. These are in fact two important possible approaches to Machine Learning that have been widely used for years. Only recently, however, has there been an explosion of a new term, Self-Supervised Learning! But let’s get there step by step and look at … [Read more...] about Self-Supervised Learning In Vision Transformers
On The Gap Between Adoption And Understanding
This blog post describes our recent paper: Federico Bianchi and Dirk Hovy (2021). On the Gap between Adoption and Understanding in NLP. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. The main focus of this work is to describe issues that currently affect NLP research and hinder scientific development. NLP is driven by … [Read more...] about On The Gap Between Adoption And Understanding
How To Learn Deep Learning By Reading Papers
Deep learning is moving so fast, that the only way to keep up is by reading directly from the people who publish these new findings. If you’re a technical person and want to learn about deep learning in 2021, you need to read papers. Formal education will only get you so far. Unfortunately, universities, in general, are slow to incorporate new material into their … [Read more...] about How To Learn Deep Learning By Reading Papers
How To Automate 3D Point Cloud Segmentation And Clustering With Python
If you have worked with point clouds in the past (or, for this matter, with data), you know how important it is to find patterns between your observations 📈. Indeed, we often need to extract some higher-level knowledge that heavily relies on determining “objects” formed by data points that share a pattern. This is a task that is accomplished quite comfortably by our visual … [Read more...] about How To Automate 3D Point Cloud Segmentation And Clustering With Python
Topical Language Generation With Transformers
Full Paper Codes Large-scale transformer-based language models (LMs) demonstrate impressive capabilities in open text generation. However, controlling the generated text’s properties such as the topic, style, and sentiment is challenging and often requires significant changes to the model architecture or retraining and fine-tuning the model on new supervised data. We … [Read more...] about Topical Language Generation With Transformers
Vision Transformers or Convolutional Neural Networks? Both!
The field of Computer Vision has for years been dominated by Convolutional Neural Networks (CNNs). Through the use of filters, these networks are able to generate simplified versions of the input image by creating feature maps that highlight the most relevant parts. These features are then used by a multi-layer perceptron to perform the desired classification. But recently … [Read more...] about Vision Transformers or Convolutional Neural Networks? Both!