Authors: Duncan Wang, Arnaud Guzman-Annès, Sophie Courtemanche-Martel & James HoganThe recycling problemReduce, 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
Computer Vision
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
On Transformers, TimeSformers, And Attention
Transformers are a very powerful Deep Learning model that has been able to become a standard in many Natural Language Processing tasks and is poised to revolutionize the field of Computer Vision as well.It all began in 2017 when Google Brain published the paper destined to change everything, Attention Is All You Need [4]. Researchers apply this new architecture to … [Read more...] about On Transformers, TimeSformers, And Attention
New Ways To Leverage AI Image Synthesis For Marketing & Advertising Content
This research summary is part of our AI for Marketing series which covers the latest AI & machine learning approaches to 5 aspects of marketing automation:AttributionOptimizationPersonalizationAnalyticsContent Generation: ImagesContent Generation: VideosContent Generation: TextAfter Generative Adversarial Networks (GANs) were introduced by Ian Goodfellow in 2014, a … [Read more...] about New Ways To Leverage AI Image Synthesis For Marketing & Advertising Content
Novel AI Methods For Video Generation for Marketing & Advertising
This research summary is part of our AI for Marketing series which covers the latest AI & machine learning approaches to 5 aspects of marketing automation:AttributionOptimizationPersonalizationAnalyticsContent Generation: ImagesContent Generation: VideosContent Generation: TextAI algorithms can significantly increase the efficiency of the original content generation … [Read more...] about Novel AI Methods For Video Generation for Marketing & Advertising
Step-By-Step Implementation of GANs on Custom Image Data in PyTorch: Part 2
In Part 1 on GANs, we started to build intuition regarding what GANs are, why we need them, and how the entire point behind training GANs is to create a generator model that knows how to convert a random noise vector into a (beautiful) almost real image. Since we have already discussed the pseudocode in great depth in Part 1, be sure to check that out as … [Read more...] about Step-By-Step Implementation of GANs on Custom Image Data in PyTorch: Part 2
How I Would Explain GANs From Scratch to a 5-Year Old: Part 1
Note: Quite frankly, there are already a zillion articles out there explaining the intuition behind GANs. While I will briefly touch upon it, the rest of the article will be an absolute deep dive into the GAN architecture and mainly coding — but with a very very detailed explanation of the pseudocode (open-sourced as an example by PyTorch on Github).Why do I need … [Read more...] about How I Would Explain GANs From Scratch to a 5-Year Old: Part 1
Why Is Object Detection So Messy?
Those working with Neural Networks know how complicated Object Detection techniques can be. It is no wonder there is no straight forward resource for training them. You are always required to convert your data to a COCO-like JSON or some other unwanted format. It is never a plug and play experience. Moreover, no diagram thoroughly explains Faster R-CNN or YOLO as there is for … [Read more...] about Why Is Object Detection So Messy?
Transformers in Computer Vision
Transformer architecture has achieved state-of-the-art results in many NLP (Natural Language Processing) tasks. One of the main breakthroughs with the Transformer model could be the powerful GPT-3 released in the middle of the year, which has been awarded Best Paper at NeurIPS2020.In Computer Vision, CNNs have become the dominant models for vision tasks … [Read more...] about Transformers in Computer Vision