mohaps

Interviewer: What are your strengths? Me: Cache Invalidation and Naming Things.

We paused and looked at each other for a minute and then we burst out laughing.

the basic difference in approach was to switch the earlier approach of

if (conditionA && conditionB && !conditionC) cache_it()

to

hey look, an item with featureset X is cacheable while one with featureset Y is not.

This reflects in the API which is just two calls predict() and feedback()

this simplifies the integration code and is easily debuggable even in the face of changes.

To add to Vlad's comment above: The major win was in being able to create a simple API which inherently computes update -> cache invalidation probability taking into account the semantics of the item being cached and its relevance to the query. To be able to do this explicitly via heuristics leads to bespoke effort for each new and modified query.

With Spiral, we were able to approach this top down as a classification problem.

e.g.

If you have a cached query for "Friends that liked my post", the Spiral classifier quickly learns that "Post Last Viewed At" or "Post Last Modified At" is not relevant to this via the feedback from the caching code.

Pre-spiral, this was expressed via a curated blacklist/whitelist which had to be recreated if the query characteristics changed.

One of the authors here. Be happy to answer questions

Thanks! Working on the timeline feature. The temporal data and diet/size tags need some clean up - a tedious work via an offline tool with RegEx and some nltk elbow grease :)

I built PaleoCodex as an online interactive encyclopedia for Dinosaurs and other prehistoric animals for my six year old using wikipedia data.

He is a big dinosaur buff and wants to be a paleontologist when he grows up. His project brief was "Build a pokedex... but for dinosaurs"

Still kind of a WIP (Search is very basic and Text to speech / Listen feature may not work on iPhones, works on iPad/Nexus and Desktop using Chrome and Safari) and very much a weekend hack.

Built using python, tornado, wikipedia data and the skeleton html5 boilerplate. Uses ResponsiveSpeech for text to speech.

Enjoy! (and do send in your comments and suggestions)