I’m very pleased to introduce Fast Forward Labs.
Fast Forward Labs is an independent data technology research lab. We focus on taking technologies that are just becoming possible, and making them useful.
We believe that the existing research structures are failing in 2014. We offer companies a new approach to applied research that helps them find those product and business opportunities that exist at the intersection of their existing business and new data and technology capabilities.
Our business model is simple: we make our clients as smart as we are about data and technology.
You can subscribe to our research, and every few months you’ll get a new paper that describes an emerging technology, how it works, the current landscape of the technology (commercial, academic, and open source), and our predictions for where it will go next along with a working prototype of the technology. If you like what you see, we’ll be happy to work with you.
Our first project is on natural language generation algorithms (representing structured data as stories!), and will be available in early August. Look forward to future projects on rich media classification, stream algorithms, context-aware computing and more.
Always moving forward,
Founder and CEO
More from the Blog
Aug 21 2014
At Fast Forward Labs we’re thoughtful about the kind of work space we want to spend our time in. We decided that we preferred a shared large table instead of individual desks, to make it easier to collaborate and offer the flexibility to spread out when necessary, and to allow space for other people to drop in and work with us. We also love to build things, and find an hour o...
Jul 22 2019
by — We discussed this research as part of our virtual event on Wednesday, July 24th; you can watch the replay here! Convolutional Neural Networks (CNNs or ConvNets) excel at learning meaningful representations of features and concepts within images. These capabilities make CNNs extremely valuable for solving problems in the image analysis domain. We can automatically identify defects in manufactur...