Anyone who knows me knows I'm all about solving problems. That's my thing. There's a problem, here are the facts, here's the solution. It's almost always a technical solution.
So when I was presented with the problem of making it easier to make background music for YouTube videos, I built Harmonious Studio.
Technically, its a good solution – it lets you mix individual loopable instruments into a single track. Behind the scenes, it uses a the Web Audio API to manage the individual tracks in the browser and ffmpeg to prepare the final high-quality download.
The question is: what now?
The original plan was to allow others to upload their tracks and create a marketplace for music – basically positioning Harmonious Studio as "Shutterstock for Music". There are several options for this – monthly subscription for unlimited downloads, fee per premium track, fee per download.
There are a few problems with this, however.
1. Free is better
There is a huge amount of free music available online. Every week there's a post on /r/gamedev where a composer gives away thousands of tracks for free. The majority of responses I got from the feedback form I asked for on Harmonious fell into the segment "Yes, I use background music. No, I'd never pay for it".
2. Good enough is good enough
The idea was that content creators would be able to make music to fit their content exactly. However, getting something instantly for free that almost fits is preferable to making something custom that costs time and money. Kind of obvious when you think about it.
3. If it works, keep it
The other piece of feedback I got from YouTubers was that, once they've found a piece of music that works, they're more likely to copy-paste it into the next video than get a new one. Once they've got 3 or 4 'go-to' tracks, they've got everything they need for most kinds of videos.
So... what now?
It's a good technical solution to a problem without a good market. This is usually the point where the insightful entrepreneur pivots and relaunches using the tech in a completely new way. Anyone have any suggestions about how to do that?
You'll have noticed I haven't updated much recently. Even when I did, if was with distinctly non-tech stuff. The reason being I've been busy. Not "I've got a big to-do list" busy or "I've had a couple of browser tabs open for a few weeks that I'll get round to eventually" busy, either. I've got a text-file to-do list that's been open, unsaved in the background since January 2017 and there are a couple of background tabs I've been meaning to get round to reading since late 2014. Really.
A couple of years back, a few of us got interested in how IoT devices could work with location. What's the smallest, simplest device we can connect to the cloud and pin point on a map? Within a few weeks, we had a basic cloud and at CES in January this year, we launched a fully-fledged product. In that time, I've moved from 'prototyper who built version 0.1 on his laptop during the Christmas holidays' to something roughly equivalent to CTO of a medium-sized tech company. Not bad.
What's it do?
In essence, a small IoT device with some combination of GSM, WiFi and Bluetooth does a scan to find out what wireless networks, Bluetooth beacons and cell towers are visible and how strong they appear. They send their scan to HERE Tracking where it gets resolved into a latitude/longitude and then saved. The best bit is that it works indoors and outdoors.
Look, we've even got our own shiny video with cheesy voiceover!
And another that shows what it actually does!
There are a bunch of other features as well such as geofences, notifications, filtering, etc. but the main focus is this large-scale ingestion and storage of data.
At this point, our original Tracking team has grown to include HERE Positioning (the clever people who actually figure out where the devices are) and HERE Venues (we recently acquired Micello). By combining, the Tracking, Positioning and Venues bits together, we can follow one of these devices from one factory, across the country on a truck or train, overseas, into another country, into another factory, out into a shop... and so on.
Seeing as both Prolog and CSS are declarative languages, I found myself wondering if it would be possible to create a mapping from one to the other. It was an interesting thought experiment that quickly found itself being turned into code.
Way back when, Prolog was actually one of the first languages I learned to program in. It had been a while since I'd last used it for anything (a chess endgame solver in high school, I think) so I looked up an online tutorial. The following example is derived from section 1.1. of Learn Prolog Now
Simple rules
If you think of Prolog facts as denoting true/false attributes of elements, you can consider every known item in a KnowledgeBase (KB) as a DOM Element. For example:
mia.
Is equivalent to:
<div id="mia"></div>
While
woman(mia).
Equates to:
<div id="mia" class="woman"></div>
You can make multiple statements about an item in the KB:
The only real issue is that CSS values can’t be aggregated. If they could be, you could always use the same attribute (e.g. box-shadow) and combine them:
And here are the queries that could be answered by looking at the visual output:
?- woman(mia).
Yes (the element with id="mia" has a yellow background)
?- playsAirGuitar(jody).
Yes (the element with id="jody" has a solid black border)
?- playsAirGuitar(mia).
No (the element with id="mia" does not have a solid black border)
?- playsAirGuitar(vincent).
No (there is no element with id="vincent")
?- tattooed(jody).
No (there is no CSS style for a class '.tattooed')
?- party.
Yes (the element with id="party" exists)
?- rockConcert.
No (the element with id="rockConcert" does not exist)
Sure, it's all a bit silly but it was quite a fun little experiment. There are probably a few big aspects of Prolog that are unmappable but I like to think it might just be possible to create a chess endgame solver using nothing but a few thousand lines of CSS.
Thanks to some great work by Daniel Wabyick and his team, Hardy has had a bunch of improvements over the last few weeks.
The biggest change in this version is that, if you have GraphicsMagick installed on your machine, Hardy will use it for native image diffs but fall back to the built-in method if you don't. The current image diff technique involves creating an HTML page with a canvas, opening that with PhantomJS, loading the image into the canvas and using imagediff.js to calculate the diffs. It works everywhere PhantomJS works but it's slow. Daniel benchmarked the difference and it's a huge performance gain if you rely on image diff tests.
There's also some minor improvement around logging and the cucumber report format but I'll write about them later once I've had a chance to update the Hardy website.