Artificial intelligence and machine learning seem to be everywhere at the moment – every day there’s a new story about the latest smart assistant, self-driving car or the impending take over of the world by robots. With FixMyStreet having recently reached one million reports, I started wondering what kind of fun things could be done with that dataset.
Inspired by a recent post that generated UK place names using a neural network, I thought I’d dip my toes in the deep learning sea and apply the same technique to FixMyStreet reports. Predictably enough the results are a bit weird.
I took the titles from all the public reports on fixmystreet.com as the training data, and left the training process to run overnight. The number crunching was pretty slow and the calculations had barely reached 5% in the morning. I suspect the training set was a bit too large, at over 1M entries, but end result still gives enough to work with.
The training process produces checkpoints along the way, which you can use to see how the learning is progressing. After 1000 iterations the model was starting to be aware that it should use words, but didn’t really know how to spell them:
Mertricolbes Ice does thrown campryings Sunky riking proper, badger verwappefing cars off uping is! Finst Knmp Lyghimes Jn fence Moadle bridge is one descemjop
After 15000 iterations it’s starting to get the hang of real words, though still struggling to form coherent sentences.
Untaxed cacistance. Broken Surface in ARRUIGARDUR. Widdy movering Cracked already nail some house height avenue. Light not worky I large pot hole Dumped shood road nod at street. Grim Dog man Ongorently obstructing sofas. This birgs. Serious Dirches
After 68000 iterations there seems to be enough confusion in the training data that things start to go south again with the default parameters:
Urgely councille at jnc swept arobley men. They whention to public bend to street? For traffic light not working
Tweaking the ‘temperature’ of the sampling process produces increasingly sensible results:
Large crumbling on pavement Potholes all overgrown for deep pothole Very van causing the road Very deep potholes on pavement Weeds on the pavement Several potholes in the road Rubbish Dumped on the road markings Potholes on three away surface blocking my peride garden of the pavement Potholes and rubbish bags on pavement Poor road sign damaged Poor street lights not working Dog mess in can on road bollard on pavement A large potholes and street light post in middle of road
As well as plenty of variations on the most popular titles:
Pot hole Pot hole on pavement Pot holes and pavement around Pot holes needings to path Pothole Pothole dark Pothole in road Pothole/Damaged to to weeks Potholes Potholes all overgrown for deep pothole Potholes in Cavation Close Potholes in lamp post Out Potholes in right stop lines sign Potholes on Knothendabout Street Light Street Lighting Street light Street light fence the entranch to Parver close Street light not working Street light not working develter Street light out opposite 82/00 Tood Street lights Street lights not working in manham wall post Street lights on path Street lights out
It also seems to do quite well at making up road names that don’t exist in any of the original reports (or in reality):
Street Light Out - 605 Ridington Road Signs left on qualing Road, Leave SE2234 4 Phiphest Park Road Hasnyleys Rd Apton flytipping on Willour Lane The road U6!
Here are a few of my favourites for their sheer absurdity:
Huge pothole signs Lack of rubbish Wheelie car Keep Potholes Mattress left on cars Ant flat in the middle of road Flytipping goon! Pothole on the trees Abandoned rubbish in lane approaching badger toward Way ockgatton trees Overgrown bush Is broken - life of the road. Poo car Road missing Missing dog fouling - under traffic lights
Aside from perhaps generating realistic-looking reports for demo/development sites I don’t know if this has any practical application for FixMyStreet, but it was fun to see what kind of thing is possible with not much work.