The biggest AI news of 2020 so far is the success of OpenAI’s monstrous new language model, GPT-3. In … Keep reading
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Organizing applied machine learning research
Over the past three years, I’ve spent >50% of my time thinking about what the applied research teams I’ve been part of should be building, and how. This post is about some of the challenges we’ve faced organizing applied machine … Keep reading
Lockdown projects: Corona Calculator, Glass of Wine, and Weather Window
With the touring skis gathering dust and the camping gear slumbering in dry bags, I’ve been using the obligatory indoors time to work on some side projects with friends. Here’s a run down, with some notes on what I’ve learned … Keep reading
The customer is the enemy
“We must therefore be prepared to cope – even better, to thrive – in an environment of chaos, uncertainty, constant change, and friction”
Those who work in startups will recognize the tone from blogposts and books spewed by startup mecca, … Keep reading
Predicting the performance of deep learning models
It’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 … Keep reading
Abuse detection on Twitter: a collaboration with Amnesty International
At 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 … Keep reading