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
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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!
Should Machine Learning Experts Respond to Climate Change Call To Action?
Our planet's proper functioning and survival rely on a delicate balance of a vast heterogeneity of animal, plant, and microorganism species that contribute to the ecosystem established on Earth. Of all the organisms, there is one that has had a great impact on the planet, so great that it was capable of upsetting its balance, causing entire ecosystems to disappear and … [Read more...] about Should Machine Learning Experts Respond to Climate Change Call To Action?
How AI Can Help Us Recycle
Authors: Duncan Wang, Arnaud Guzman-Annès, Sophie Courtemanche-Martel & James Hogan The recycling problem Reduce, Reuse, and Recycle. Otherwise known as the three Rs of waste management, this aphorism has been largely popularized as the solution for solving the rising waste crisis. In North America, rising environmental awareness amongst the general public and the … [Read more...] about How AI Can Help Us Recycle
The Secret Guide To Human-Like Text Summarization
Summarization has become a very helpful way of tackling the issue of data overburden. In my earlier story, I shared how you can create your personal text summarizer using the extractive method — if you have tried that, you may have noticed that, because no new sentences were generated from the original content, at times you may have difficulties understanding the generated … [Read more...] about The Secret Guide To Human-Like Text Summarization
Is Attention What You Really Need In Transformers?
In recent years there has been an explosion of methods based on self-attention and in particular Transformers, first in the field of Natural Language Processing and recently also in the field of Computer Vision. If you don’t know what Transformers are, or if you want to know more about the mechanism of self-attention, I suggest you have a look at my first article on this … [Read more...] about Is Attention What You Really Need In Transformers?
On DINO, Self-Distillation With No Labels
It has been clear for some time that the Transformers had arrived in the field of computer vision to amaze, but hardly anyone could have imagined such astonishing results from a Vision Transformer in such a short time since their first application. In this article, we discuss one of the most interesting advances in the field of computer vision, DINO, announced a few days … [Read more...] about On DINO, Self-Distillation With No Labels