Our second R&D Report, Probabilistic Methods for Realtime Streams, has gone out! In this report, we explored probabilistic algorithms for machine learning on potentially large realtime streams of data with efficient CPU and memory usage.
Our prototype demonstrated these algorithms running on large amounts of social conversation data. More on that soon.
More from the Blog
Mar 31 2015
The Hoff stopped by Fast Forward Labs!
Apr 6 2015
by — It’s restyled blog day here at Fast Forward Labs! Having wrapped up our second report, I (Grant, Fast Forward Labs designer-dev) am now spending some time putting our web presence in order. The real big piece of that is a revamped Fast Forward website, which should be out next week, but as a warm-up today I worked on getting our blog into shape. I wanted to keep things clean ...
Jun 26 2018
by — Today’s machines can identify objects in photographs, predict loan repayments or defaults, write short summaries of long articles, or recommend movies you may like. Up until now, machines have achieved mastery through laser-like focus; most machine learning algorithms today train models to master one task, and one task only. We are excited to introduce multi-task learning in our upcoming webina...