The Hoff stopped by Fast Forward Labs!
More from the Blog
Dec 19 2014
We’re very pleased to announce our second research report topic will be realtime stream analysis, with a focus on probabilistic data structures. Using these techniques, we’re able to build systems that enable extremely fast and memory efficient computation over very large data sets. For example, imagine being able to do comparisons between two sets of billions of items in milliseco...
Apr 1 2015
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.
Jan 29 2019
by — UMAP explorer: an interactive visualization of the MNIST data set We’re in the middle of work on our next report, Learning with Limited Labeled Data, and the accompanying prototype. For the prototype’s front-end we wanted to be able visualize and explore the embedding of a large image data set. Once you get into the tens of thousands of points, this can be a challenge to do in the browser. T...