Abstract:

Machine learning has been cropping up more and more up news articles over the past few years. Most of the time in a click-baiting manner. This is catalyzed by high profile figures talking about machine learning philosophy, such as intelligence singularities, which creates more confusion for the media. Whilst this great for the publicity of the field, we are unfairly representing what is possible with this, still amazing technological advancement. This talk looks at how we can improve the way we communicate about machine learning in a more objective and representative way - and still maintain the hype.

Josh's bio:

I'm a developer working to deliver top quality engineering at startup speed with Theodo, a London/Paris startup. We are a lean tech team for hire among startups and large corporates alike - launching MVPs using the latest open source technology. We are tech stack agnostic, working with the highest quality tools for specific product needs, using lean and agile methodologies.

Personally, I'm interested in natural language processing and production machine learning systems. Aside from the AI, I have interests in formal verification, concurrent systems, and web development.