The biggest AI news of 2020 was the success of OpenAI’s monstrous new language model, GPT-3. In this post I summarize why GPT-3 has caused such a splash, before highlighting some consequences for companies building things with AI. 
Organizing applied machine learning research
May 12, 2020Applied Machine Learning research is a bit different from standard software engineering. This post summarizes some of the things I’ve learned about leading applied ML teams. 
Lockdown projects: Corona Calculator, Glass of Wine, and Weather Window
May 10, 2020Lockdown in Montreal prompted a spree of building: The Corona Calculator, A Glass of Wine May Help, and Weather Window. 
The customer is the enemy
April 28, 2019It’s a bit of a cliché, but reading a tiny bit of military strategy can inform your thinking about startups. 
Predicting the performance of deep learning models
April 14, 2019It’s widely acknowledged that the recent successes of Deep Learning rest heavily upon the availability of huge amounts of data. Vision was the first domain in which the promise of DL was realised, probably because of the availability of large datasets such as ImageNet. The recent surge of simulators for RL further illustrates that as we \[…\] 
Abuse detection on Twitter: a collaboration with Amnesty International
January 27, 2019At the NeurIPS 2018 workshop on AI for Social Good we presented a piece of work we performed in collaboration with Amnesty International. We leveraged a mixture of crowdsourcing and deep learning to study the nature and quantity of abuse suffered by prominent women on twitter. At this point quite a lot has been written about the project: if \[…\]