We recently had to migrate our multiple PostgreSQL databases between cloud providers. We wanted to keep downtime to an absolute minimum. This is what we did using Londiste.
Creating a similar content recommender for all the abstracts of this year’s EMNLP 2015 Conference in Lisbon using Lateral’s machine learning API.
Previously we’ve written about how machines can learn meaning. One of the exciting opportunities of this approach is that it also means they can learn new languages very quickly. We have recently started working on supporting new languages, and thought we would share some initial impressions here.
A while back we partnered up with Blockspring to enable anyone to use our API without needing to write any code. They’ve created an awesome solution that allows you to make use of a range of great APIs using only a spreadsheet. This enables you to bring data into your spreadsheet, run text-analysis and much more. […]
Today we are pleased to announce the release of our Article Extractor API! When recommending content it’s important to ensure you are only recommending for the relevant text of an article. We have often faced this challenge with online articles and blogs. We’d want to fetch a URL but just extract the main body of […]
For the last few months, we’ve been doing occasional work on an approximate nearest neighbours (ANN) vector search tool, written in Python. It’s still not finished and there are many rough edges, but it comes with a working DynamoDB adaptor and hence operates out-of-memory, one our main requirements. On the down side, it isn’t as fast […]
The arXiv is a repository of over 1 million preprints in physics, mathematics and computer science. It is truly open access, and the preprints are an excellent dataset for testing out all sorts of language modelling / machine learning prototypes.
Which public companies work with solar technology, or are similar to Tesla? Find out quickly, using the Lateral API, serving publicly accessible data from Bloomberg.
We recently wrote about what our NewsBot Chrome extension does today I’m going to add to that and explain how it works behind the scenes. When building this project we approached it as if we were a user of the Lateral API to see what we could build.