Originally published in Eugeneyan. Applying machine learning effectively is tricky. You need data. You need a robust pipeline to support your data flows. And most of all, you need high-quality labels. As a result, most of the time, my first iteration doesn’t involve machine learning at all. Wait—start without machine learning? I’m not alone in saying this.
Originally published in United AI, Sept 24, 2021. According to new research, one of the largest Natural Language Processing (NLP) datasets available has been extensively ‘filtered’ to remove black and Hispanic authors, as well as material related to gay...
Originally published in IEEE Spectrum, Oct 4, 2021. Imagine you’re a farmer in the northern United States. It’s early spring, and nighttime temperatures are just starting to rise above freezing. You need to fertilize your newly-planted crops,...
Originally published in Nature, Sept 22, 2021. Throughout the COVID-19 pandemic, countries relied on a variety of ad-hoc border control protocols to allow for non-essential travel while safeguarding public health: from quarantining all travellers to restricting entry...
Originally published in IEEE Spectrum, Sept 24, 2021. Deep Learning is now being used to translate between languages, predict how proteins fold, analyze medical scans, and play games as complex as Go, to name just a few applications of a technique...
Originally published in The Markup, Sept 30, 2021. A huge but little-known industry has cropped up around monetizing people’s movements. Companies that you likely have never heard of are hawking access to the location history on your...
Originally published in MIT Technology Review, Sept 28, 2021. Government use of face ID systems exploded during the pandemic—but tying it to critical services has left some people locked out at the moment they needed help the...
Webinar: The Data Model Strategy: Make Analytics Work for Your Business, Not the Other Way Around Speaker: Declan Owens, Digital Analytics Expert at Piano (more…)
