Today we’re excited to announce that Dessa is being acquired by Square! We’ll continue to operate under the Dessa brand, keep our headquarters in Toronto, and be open to collaborations with other organizations or companies. You can read more about it in a blog post from Square, and in a letter from our CEO Stephen Piron below. This is only the beginning — stay tuned for more news about our work together on applied machine learning.
Today we are announcing that Dessa is being acquired by Square. By joining forces, we will be able to build machine learning applications that allow people to do more with their money than ever before, and in general, stretch the limits of what’s possible with AI. …
Authors: Rayhane Mama & Sam Shi
Before we start: The codebase and data we present in this article can be found in our open source Github repository for anyone to replicate and build on. What appears below is an excerpt from a full article about our work on deepfake detection, which you can find on the Dessa website.
Link to full article: Dessa website
Download the source code and data: Github repository
Download the trained model and check out our experiments: Atlas Experiment…
ICYMI: Earlier this summer we broke new ground with RealTalk, a speech synthesis system created by Machine Learning Engineers at Dessa (Hashiam Kadhim, Rayhane Mama, Joseph Palermo). With their AI-powered text-to-speech system, the team managed to replicate the voice of Joe Rogan, a podcasting legend known for his irreverent takes on consciousness, sports and technology. On top of that, their recreation of Rogan’s voice is the most realistic AI voice that’s been released to date.
If you haven’t heard the voice yet, you should.
Here’s the video we shared on YouTube featuring a medley of their faux Rogan’s musings:
Our initial post focussed on the ethical implications of fake voices and AI’s growing capabilities in deceiving human senses. …
Today we’re excited to announce that three Machine Learning Engineers at Dessa (Hashiam Kadhim, Rayhane Mama, Joseph Palermo) have produced the most realistic AI simulation of a voice we’ve heard to date.
It’s the voice of someone you’ve probably heard of before: Joe Rogan. (For those who haven’t—Joe Rogan is the creator and host one of the world’s most popular podcasts, which to date has nearly 1300 episodes and counting.)
Obviously, something like this has to be heard to be believed. So without further ado, check it out for yourself:
Today we’re excited to announce a new course for graduate students at the University of Toronto, facilitated by Ragavan Thurairatnam, our Chief of Machine Learning, and Jodie Zhu, one of our Machine Learning Engineers.
Ragavan and Jodie were recently appointed as Adjunct Lecturers at the University’s Dalla Lana School of Public Health, where they will teach a course on Applied Deep Learning to graduate students studying at the school (as well as those from other faculties). In addition, the course will also feature a number of guest lecturers from our Machine Learning Engineering team throughout the semester.
We think this course will fill an important gap in the current academic offerings for students advancing their knowledge of machine learning. At UofT and other institutions today, the majority of courses focus almost exclusively on the theoretical underpinnings of the field. With this course, Ragavan and Jodie are setting out to change that. …
Pop into Dessa’s offices and you’ll soon find traces of the company’s fascination with outer space. A Lego replica of Saturn V, the rocket that made it to the moon, sits on our reception area coffee table. Venture a bit further, and you’ll discover that each of the meeting rooms are named after spaceports from around the world. For a few employees on Dessa’s software and machine learning engineering teams, this company-wide enthusiasm for space has evolved into a full-blown passion project.
Combining their interest in space with an exploration of deep learning’s potential applications for astronomy, 3 of Dessa’s engineers have collaborated on a project called space2vec since summer 2017. Recently, the team built a deep learning system that identifies supernovas from telescope images with record-breaking speed: cutting the time it would take astronomers to identify supernovas almost in half! …