Post
Discussing NLG with Automated Insights
Jan 27 2016
On January 26, we co-hosted an online discussion with Robbie Allen, the founder and CEO of natural language generation software provider Automated Insights. You may know them as the company behind Yahoo! fantasy football reports and the Associated Press’s automated company earning statements. Their latest release of Wordsmith allows non-technical business to define template language with less overhead from IT and professional service teams.
The webinar covers how NLG works, how different industries verticals are applying the technology, how users engage with Wordsmith, and where we suspect NLG will go in the near future.
Check it out, and let us know if you have questions about our NLG resources!
</figure>
More from the Blog
-
Older ↓
interview
Jan 22 2016
Eli Pariser on the Ethics of Algorithmic Filtering
by with — Chiefly his reflection, of which the portrait / Is the reflection, of which the portrait / Is the reflection once removed. / The glass chose to reflect only what he saw / Which was enough for his purpose: his image / Glazed, embalmed, projected at a 180-degree angle. — Parmagiano and John Ashbery - Self-Portrait in a Convex Mirror Personalizing experiences and recommendations for consum...
…read more
by Kathryn with Eli Pariser
-
Newer ↓
Post
Feb 3 2016
What History Teaches Us About Data Science
by — The FFL team at the New York Historical Society’s Silicon City exhibit Study the past if you would define the future. — Confucius Until April 17, 2016, the New York Historical Society is featuring an exhibition called Silicon City: Computer History Made in New York. The Fast Forward Labs team took a field trip to the museum back in December to augment our perspective on our current mach...
…read more
by Kathryn
-
Newest ↓
Featured Post
Sep 17 2018
Deep learning made easier with transfer learning
Deep learning has provided extraordinary advances in problem spaces that are poorly solved by other approaches. This success is due to several key departures from traditional machine learning that allow it to excel when applied to unstructured data. Today, deep learning models can play games, detect cancer, talk to humans, and drive cars. But the differences that make deep learning power...
…read more