I ran my first design sprint last week. According [https://www.gv.com/sprint/] to the creators: > The sprint is a five-day process for answering critical business questions through design, prototyping, and testing ideas with customers. The starting point of a sprint could be a problem like “website visitors don’
“Founders at Work [https://www.goodreads.com/book/show/98233.Founders_at_Work]” is a unique book by Jessica Livingston, one of the founders of YCombinator. It contains un-narrated, almost unedited interviews with founders of successful startups like Paypal, Hotmail, Apple, and 27 others. I’m only through about 10%
A few years ago at Starship, I contributed to the Data is the Specification [http://dataisspec.github.io/] manifesto. The core idea is that it's better to solve problems directly against a collection of examples, as opposed to trying to generalise the problem first and then solving the general problem.
As the coronavirus pandemic escalated, I was travelling around the world. The timing was unfortunate, but the endless hours of flying also presented an opportunity for reflecting on the virus. Most people correctly focus on the immediate effects of the virus: survival is required for anything interesting in the future.
Pretty much every presentation I give about AI includes the following slide, in the context of automatically authenticating users using face recognition. The idea is that even automation-reliant businesses don’t need to go 100% automatic to start serving customers: you can start with a basic model that outputs a
It’s common to see job descriptions along the lines of the following. -------------------------------------------------------------------------------- Looking for a data scientist. Responsibilities: 1. Building big data databases, data warehouses, data lakes, and pipelines. 2. Training and deploying deep learning models and neural networks for prediction. 3. Creating dashboards, analyses, visualisationgs and reports.
As the popularity of machine learning grows, so does the amount of academic papers, blog posts and software released. As an industry practicioner I need to be up-to-date with useful ones without spending hours each week combing through new developments to find the few important updates. The obvious solution to
There’s a specific type of person I’ve noticed applying to jobs, participating in ML communities, or writing to me online: software engineers with an interest in machine learning. Their ML background typically consists of a course or two from Andrew Ng [https://www.coursera.org/courses?query=machine%