Archive for category events
The Sydney Opera House hackathon is off to a bad start. The infamous institution is holding a hackathon next month. They are offering a prize of $4K AU (about $3, 750 US) along with ‘The glory of developing an app for Sydney Opera House which will be seen by millions of visitors every year’ for the best hack. The Register dove into the Terms & Conditions (warning, 2,000 words of legalize) and dug up all sorts of IP grabs. Bottom line, at the end of the hack the SOH can do just about anything it wants with what you built at the hackathon. To quote the Register:
“By entering this competition, every last line of code you cut becomes the property of the Sydney Opera House Trust.”
There’s also this little nugget in the T&C:
“By entering this Hackathon, you agree that use of information in our representatives’ unaided memories in the development or deployment of our products or services does not create liability for us”
One can just imagine how it this came about. Some biz guys (yeah, all evil comes from the biz guys) were sitting around thinking about how they could get their mobile app done for cheap. “Let’s do a hackathon! Toss a few bean bag chairs and power strips into a hotel conference room. Send in boxes of Pizza every 6 hours and out will pop dozens of apps to chose from. Even if none of the apps built are polished enough for release we will be able to mine all the best ideas from the most creative Australian techies and put them into our app when we finally hire that digital agency to build it.”
Unfortunately for the SOH, developers are too smart for that. They can do the math. To win a high profile hackathon with a goal of building a mobile app for millions of users, you probably need a team of four: the front-end programmer, the back-end programmer, the designer and the do-everything-else-including-the-presentation guy/gal (a.k.a The Face). At a modest $125 an hour per team member on the open market that team costs $500 per hour, so 24 hours of hacking is worth about $12,000. (That’s not even counting the pre-hack work that any team going to win will do – getting the code repository setup, the tools primed, the workflow established). The chance to win a $4K prize for $12K of work is just not worth it. And of course, the SOH IP grab crosses the line. Any developer who goes to the SOH understanding the T&C will leave their best ideas at home. No one wants to give away their good ideas for nothing.
The Sydney Opera House is not the first example of a hackathon abuse nor will it be the last – but it highlights the wrong thinking that many businesses seem to have about hackathons – that hackathons are a way to get stuff built quickly and cheaply. So here’s some unsolicited advice to businesses thinking about holding hackathons from someone who’s been to lots of them and has seen how they work.
Hackathons are not competitions - Hackers love to build stuff. We build apps, we build web sites, we build hardware gizmos, we build musical instruments. Hacking is all about being creative and building stuff. Nothing fosters creativity more than being in a room full of other like-minded folks. Folks that share your passion for building cool stuff. At a hackathon such as a Music Hack Day, the emphasis is not on prizes, the emphasis is on creativity. At a Music Hack Day hackers form teams spontaneously to build stuff. They share ideas with each other, they help each other – they revel in every cool demo. If you throw a big prize into the mix the dynamic changes dramatically. The hackathon becomes a competition. Hackers become developers that are thinking strategically about how to win the prize. They don’t share ideas with others, they don’t go for the creative but risky idea – they go for the conservative idea and spend their extra energy making nice colors and fonts in the PowerPoint presentation for the demo. In the early days of the Music Hack Day, we had one event where a big local sponsor brought a $10K cash prize. Not knowing any better, we went with it, but that was a mistake. Yes, there were lots of hackers and lots of completed projects, but the whole vibe of the hackathon was different. The hackathon was no longer a center of creative sharing, instead it was a cut-throat event. The goal was no longer about being creative, the goal was to win $10K . We learned our lesson and now we make sure that prizes offered at Music Hack Days are modest. Note that there are some really good hackathons like HackerOlympics that are designed to be competitions. These hackathons value teams that can think quickly and creatively across a wide range of skill sets. Winners get bragging rights and modest prizes.
Don’t use a hackathon as a way to develop your app - no one wants to go to a hackathon to do work for someone else. Hackers want to scratch their own creative itch , they don’t want to build your app for you. No amount of free pizza is going to change that. Now, if you’ve got a million dollars to spend, I’m sure you’ll get some good apps but that’s not the kind of hackathon I’d really want to go to.
Bottom line - if your hackathon has a T&C that requires developers to give up any rights to the stuff they’ve created at your hackathon you are doing it wrong. If you are going to give away big prizes, don’t expect to have a creative, sharing atmosphere – if you give away big prizes expect to see people spend more time working on a powerpoint and less time on that creative but risky hack. The currency at a hackathon should be creativity, not money or prizes and at the end of it all, the creators should own their own ideas. No amount of pizza should change that.
I’m writing this post from Espoo Finland which is home to three disruptive brands: Nokia, who revolutionized the mobile phone market in the 1990s with its GSM technology; Rovio, who brought casual gaming to the world with Angry Birds; and Children of Bodom perhaps one of the most well known melodic death metal bands. So it is not surprising that Espoo is a place where you will find a mix of high tech, playfulness and hard core music – which is exactly what I found this past weekend at the Helsinki Music Hack Day hosted at the Startup Sauna in Espoo Finland.
At the Helsinki Music Hack Day, dozens of developers gathered to combine their interest in tech and their passion for music in a 24 hour hacking session to build something that was music related. Representatives from tech companies such as SoundCloud, Spotify and The Echo Nest joined the hackers to provide information about their technologies and guidance in how to use their APIs.
After 24 hours, a dozen hacks were demoed in the hour-long demo session. There was a wide range of really interesting hacks. Some of my favorites are highlighted here:
Cacophony – A multi-user remote touch controlled beat data sequencer. This hack used the Echo Nest (via the nifty new SoundCloud/Echo Nest bridge that Erik and I built on the way to Espoo), to analyze music and then allow you to use the beats from the analyzed song to create a 16 step sequencer. The sequencer can be controlled remotely via a web interface that runs on an iPad. This was a really nice hack, the resulting sequences sounded great. The developer, Pekka Toiminen used music from his own band Different Toiminen which has just released their first album. You can see the band and Pekka in the video:
It was great getting to talk to Pekka, I hope he takes his hack further and makes an interactive album for his band.
Hackface & Hackscan - by hugovk - This is a pretty novel set of hacks. Hackface takes the the top 100 or 1000 artists from your listening history on Last.fm, finds photos of the artists (via the Echo Nest API), detects faces using a face detection algorithm, intelligently resizes them and composites them into a single image giving you an image of what your average music artist in your listening history looks like.
Hackscan - takes a video and summarizes it intelligently into a single image by extracting single columns of pixels from each frame. The result is a crazy looking image that captures the essence of the video.
Hugo was a neat guy with really creative ideas. I was happy to get to know him.
Stronger Harder Faster Jester – Tuomas Ahva and Valtteri Wikstrom built the first juggling music hack that I’ve seen in the many hundreds of hack demos I’ve witnessed over the years. Their hack used three bluetooth-enabled balls that when thrown triggered music samples.
The juggler juggles the balls in time with the music and the ball tossing triggers music samples that align with the music. The Echo Nest analysis is used to extract the salient pitch info for the aligment. It was a really original idea and great fun to watch and listen to. This hack won the Echo Nest prize.
µstify - This is the classic boy meets girl story. Young man at his first hackathon meets a young woman during the opening hours of the hackathon.
They decide to join forces and build a hack (It’s Instagram for Music!) and two days later they are winning the hackathon! Alexandra and Arian built a nifty hack that builds image filters (in the style of Instagram) based upon what the music sounds like. They use The Echo Nest to extract all sorts of music parameters and use these to select image filters. Check out their nifty presentation.
Gig Voter - this Spotify app provides a way for fans to get their favorite artists to come to their town. Fans from a town express an interest in an artist. Artists get a tool or helping them plan their tour based on information about where their most active fans actually are as well as helping them sell gigs to location owners by being able to prove that there is demand for them to perform at a certain location. Gig Voter uses Echo Nest data to help with the search and filtering.
Hit factory - Hit Factory is a generative music system that creates music based upon your SoundCloud tastes and adapts that music based upon your feedback . Unfortunately, no samples of the music are to be found online, but take my word, they were quite interesting – not your usual slightly structured noise.
Abelton Common Denominator – a minimal, mini-moog style interface to simplify the interaction with Abelton – by Spotify’s Rikard Jonsson.
Swap the Drop - this was my hack. You can read more about it here.
One unusual aspect of this Music Hack Day was that a couple of teams that encountered problems and were unable to finish their hacks still got up and talked about their failures. It was pretty neat to see hardcore developers get up in front of a room full of their peers and talk about why they couldn’t get Hadoop to work on their terrabyte dataset or get their party playlister based on Meteor to run inside Spotify.
I’ve enjoyed my time in Espoo and Helsinki. The Hack Day was really well run. It was held in a perfect hacking facility called the Startup Sauna.
There was plenty of comfortable hacking spots, great wifi, and a perfect A/V setup.
The organizers kept us fed with great food (Salmon for lunch!), great music, including a live performance by Anni.
There was plenty of Angry Birds Soda.
Many interesting folks to talk to …
Thanks to Lulit and the rest of the Aaltoes team for putting together such a great event.
I’ve been in Helsinki this weekend (which is not in Sweden btw) for the Helsinki Music Hack Day. I wanted to try my hand at a DJ app that will allow you to dynamically and interactively mix two songs. I started with Girl Talk in a Box, ripped out the innards and made a whole bunch of neat changes:
- You can load more than one song at a time. Each song will appear as its own block of music tiles.
- You can seamlessly play tiles from either song.
- You can setup branch points to let you jump from an point in one song to any point in another (or the same) song.
- And the killer feature – you can have two active play heads allowing you to dynamically interact with two separate audio streams. The two play heads are always beat matched (the first play head is the master that sets the tempo for everyone else). You can cross-fade between the two audio streams – letting you move different parts of the song into the foreground and the background.
All the regular features of Girl Talk in a Box are retained – bookmarks, arrow key control, w/a/s/d navigation and so on. See the help for more details on the controls.
You can try the app here: Swap the Drop
For my Boston Music Hack Day hack I built Yet Another Party Playlisting App (YAPPA), because the world needed another party playlister – but really, I built it because I needed another hack, because 15 hours into the 24 hour hackathon I realized that my first hack just wasn’t going to work (more on that in another post). And so, with 9 hours left in the hack day, I thought I would try my hand at the party playlisting app.
The YAPPA is a frequently built app. In some sense one can look at the act of building a YAPPA as a hacking exercise. Just as a still life painter will practice by painting a bowl of fruit, or a pianist will practice scales, a music hacker can build their hacking muscle by creating a YAPPA.
The essential features of a YAPPA are straightforward – create a listening experience for a party based upon the tastes of the guests. Allow guests to suggest music for the party, apply some rules to select music that satisfies all the guests, and keep the music flowing.
With those features in mind, I created my party playlisting app. The interface is dead simple – guests can add music to the party via the master web interface or text the artist and song from the mobile phones to the party phone number. Once the party has started, PAPPA will keep the music flowing.
The key technology of PAPPA is how it picks the music to play next. Most YAPPAs will try to schedule music based on fairness so that everyone’s music taste is considered. Some YAPPAs also use song attributes such as song hotttnesss, song energy and danceability to make sure that the music matches the vibe of the party. PAPPA takes a very different approach to scheduling music. That’s because PAPPA takes a very different approach to parties. PAPPA doesn’t like parties. PAPPA wants everyone to go home. So PAPPA takes all of these songs that have been carefully texted to the party phone number, along with all the artist and song suggestions submitted via the web and throws them away. It doesn’t care about the music taste of the guests at the party. In fact it despises their taste (and the guests as well). Instead, PAPPA selects and plays the absolute worst music it can find. It gives the listener an endless string of the most horrible (but popular) music. Here’s a sample (the first 3 songs are bait to lure in the unwitting party guests):
- Royals by Lorde
- Levels by Avicii
- Blurred Lines by Robin Thicke
- #Twerkit featuring Nicki Minaj by Busta Rhymes
- From The Bottom Of My Broken Heart by Britney Spears
- Amigas Cheetahs by The Cheetah Girls
- Do Ya Think I’m Sexy by Paris Hilton
- Incredible by Clique Girlz
- No Ordinary Love by Jennifer Love Hewitt
- Mexican Wrestler by Emma Roberts
- I Don’t Think About It by Emily Osment
- A La Nanita Nana by The Cheetah Girls
- Don”t Let Me Be The Last To Know by Britney Spears
- Wild featuring Big Sean by Jessie J
- Heartbeat (Album Version) by Paris Hilton
- Love The Way You Love Me by The Pussycat Dolls
- When You Told Me You Loved Me by Jessica Simpson
- Jericho by Hilary Duff
- Strip by Brooke Hogan
- Pero Me Acuerdo De Tí by Christina Aguilera
- Bang Bang by Joachim Garraud
- Right Now featuring David Guetta (Sick Individuals Dub) by Rihanna
- Wilde Piraten by The Cool Kids
- Friend Lover by Electrik Red
- Betcha Can’t Do It Like Me by D4L
- Who’s That Girl by Hilary Duff
- Get In There, Frank! by Fun
- Hold It Don”t Drop It by Jennifer Lopez
- Sweet Sixteen by Hilary Duff
- Live It Up featuring Pitbull by Jennifer Lopez
- Freckles by Natasha Bedingfield
- I Want You by Paris Hilton
- Hold It Close by Fun
- Magic by The Pussycat Dolls
- How To Lose A Girl by Mitchel Musso
- Fairy Tales by JoJo
- Slow It Down featuring Fabolous (Album Version (Explicit)) by The-Dream
- Mr. Hamudah by Charles Hamilton
- Promise by Vanessa Hudgens
- Metamorphosis by Hilary Duff
How does PAPPA find the worst music in the world? It looks through all the data that The Echo Nest is collecting about how people experience music online to find the songs that have been banned frequently. When a music listener says “ban this song” they are making a pretty strong statement about the song – essentially saying, “I do not ever want to hear that song again in my life”. PAPPA finds these songs that have the highest banned-to-play ratio (i.e. the songs that have been proportionally banned the most when play count is taken into consideration) and adds them to the playlist. The result being a playlist filled with the most reviled music – with songs by Paris Hilton, Jennifer Love Hewitt and the great Emma Roberts. The perfect playlist to send your guests home.
At this moment, lets pause and listen to the song Mexican Wrestler by Emma Roberts:
What happens to all those carefully crafted text messages of songs sent by the guests? No, there’s no Twilio app catching all those messages, parsing out songs and adding them to a play queue to be scheduled. They just go to my phone. That’s so if people are not leaving the party fast enough, I can use all the phone numbers of the guests to start to text them back and tell them they should go home.
By the way, if you look at the songs that were texted to me during my two minute demo you’d realize how fruitless a YAPPA really is. There’s no possible way to make a party playlist that is going to satisfy everyone in the room. Tastes are too varied, and there’s always that guy who thinks he is clever by adding some Rick Astly to the party queue. Here’s what was texted to me during my two minute demo:
- Gregory Porter – be good
- Rebecca Black – It’s Friday
- Weird Al Yankovic – Fat
- Lady Gaga – Applause
- Weird Al Yankovic – Amish Paradise (from a different phone number from the other weird Al fan)
- boss ass bitch
- Basement Jaxx raindrops
- John Mayer your body is a wonderland
- jay z holy grail
- Underworld spikee
- wake me up
- Britney Spears – Hit Me Baby One More Time
- Slayer War Ensemble
- Bieber baby
- Ra Ra riot
- Rick Astley
- Mikey Cyrus
- Hi paul
- Stevie wonder overjoyed
Imagine trying to build a party playlist based upon those 24 input songs. Admittedly, a hackathon demo session is not a real test case for a party playlister but I still think you’d end up with a terrible mix of songs that no smart algorithm, nor any smart human, could stitch together into a playlist that would be appropriate and pleasing for a party. My guess is that if you did an A/B test for two parties, where one party played music based upon suggestions texted to a YAPPA and the other party played the top hotttest songs, the YAPPA party would always lose. I’d run this test, but that would mean I’d have to go to two parties. I hate parties, so this test will never happen. Its one of the flaws in our scientific method.
Who are the worst artists?
Looking at the PAPPA playlists I see a number of recurring artists – Britney Spears and Paris Hilton seem to be well represented. I thought it would be interesting to create a histogram of the top recurring artists in the most banned songs list. Here’s the fascinating result:
One thing I find notable about this list is the predominance of female artists. Females outnumber males by a substantial amount. Here’s some pie:
80% of the most banned artists are female. A stunning result. There’s something going on here. Someone suggested that the act of banning a song is an aggressive act that may skew male, and many of these aggressively banning males don’t like to listen to female artists. More study is needed here. It may involve parties, so I’m out.
Wrapping it all up
I enjoyed creating my PAPPA YAPPA. Demoing it was really fun and the audience seemed to enjoy the twist ending. The patterns in the data underlying the app are pretty interesting too. Why are so many banned songs by female artists?
If you are having your own party and want to use PAPPA to help enhance the party you can go to:
Just replace the phone number in the URL with your own and you are good to go.
Music Hack Day NYC has just wrapped up, and what a great weekend it was!. Hosted at Spotify’s spiffy new headquarters in midtown, Music Hack Day NYC was the place to be if you are passionate music, technology and building stuff. During all night Friday and all day Saturday, hundreds of hackers used music APIs from companies like The Echo Nest, Soundcloud, Gracenote, Rdio and of course Spotify, to build next generation music apps.
It was a really fun event. The Spotify headquarters are perfect for hacking. Flawless and apparently limitless wifi/bandwidth, awesome A/V setup, and great sound for an unending social hacking playlist.
Over the course of about 20 hours of hacking, 36 hacks were built and demoed. There was quite a range of inventive hacks. Some of my favorites:
The crowd favorite was Oscar Celma’s extremely clever EERFY – He solved the Music Industry Problem in 24 hours by turning it upside down with EERFY:
Another favorite was Leo and Jason’s halfstep – a chrome extension that motivates you to move more. How? If you only moved 20% of your movement goal yesterday, then halfstep will also let you listen to first 20% of any songs today. Check out the screencast of their hack.
There were lots of great Echo Nest hacks including the Echo Nest prize winner partyOutlook by Matt Egan. PartyOutlook is a CocoaLibSpotify powered iPad jukebox that accepts tracks via the Twillio API and displays real-time information about the life of the party using Echo Nest song data. Allows an administrator to pause and play music, as well as skip tracks.
Another really neat Echo Nest hack was TuneTravelr created by Chris Evans and Joshua Boggs. Tune Travelr is a web app that takes cities and locales a well as a time period and returns a playlist of songs that were hot at the time. It uses the Echo Nest data to leverage some analytic querying, before pipping the results into Rdio’s web API for playback.
MoodVenue used The Echo Nest API to help find out what’s going on tonight based on your mood and location.
Artists fight to the death, using only the sheer repetitive force of their music! By Brian McFee. Brian used the Echo Nest analysis data to build a custom metric for repetition for any song and used that to score songs by the artist for the face-off.
A novel use of The Echo Nest API was Cheese Tray - A Spotify app that takes selects randomly from among your Spotify playlists and analyzes it. It then adds to that playlist a song that best represents the average attributes of the playlist, as given by The Echo Nest API. Then, via SMS through the Twilio service, it sends a command to your Android device that changes its background to the album artwork for that average song.
Uses wikipedia articles titled ‘List of songs about…” to generate Spotify/Rdio playlists about different subjects/places. Songs about used The Echo Nest’s Rosetta Stone to get the song IDs for playing in Spotify and Rdio.
Awesome Chart Explorer
This is my hack. A visualization that lets you explore and listen to 50 years of Billboard charts.
Upload a song, ccRex’ll fetch Creative Commons music to match using Echo Nest song attributes to determine the best match.
Other nifty Echo Nest hacks:
- opporTUNE – context dependent playlisting based upon weather, activity, location, time of day and your favorite genres
- crowdPlay – an SMS enabled party playlister
- BPM Reader – an app that updates a playlist in real-time based on user keyboard input correlated to BPM. Tap in your beat, and generate a playlist of songs with that rhythm.
- Moody calls - Get a phone call with a song that matches your mood
- Spotify V. Rdio -Pitting the two music platforms against each other using your listening history
- Perl client for the Echo Nest – Ajax built a library that provides support for nearly all of The Echo Nest API features.
All in all, it was a great event with lots of awesome, innovative hacks and lots of smart people. A good time was had by all. Thanks to Spotify and @mager for organizing the event. Well Done!
In a couple of weeks I’m heading out to Chicago to give a talk at the Chicago Music Summit about Music Hacking at Music Hack Days. I’ll have an hour to talk about hack days and show off lots of demos. Naturally, I’d like to highlight all the best hacks. However, given that there have been over 30 music hack days, remembering the best of the 2000+ hacks is going to be a challenge. I’m hoping you can help me remember the best hacks, either by adding a comment to this post or just tweeting with #bestmusichack. I prefer hacks that I can demo directly via the web or that have been captured on video. To get things started here are some of the most notable hacks that I can recall.
Music Exploration and Discovery Hacks
Of the many party playlisting hacks that have been created, which one is the best?
Hacks that have been turned into businesses
Music Remixing Hacks
No need to be shy about suggesting your own hacks. As you can see, I have no qualms about adding my own hacks (Bonhamizer, Infinite Jukebox and Boil The Frog) to the list.
I anticipate your recommendations. Thanks in advance for your help!
With 3 new Music Hack Days announced this week, it might be time for you to check out what goes on at a Music Hack Day. Here are some videos that give a taste of what it’s like:
Music Hack Day Paris 2013
Music Hack Day Sydney 2012**
Music Hack Day 2012 Barcelona
Music Hack Day NYC 2011
**It is strange how a non-hacker made it onto the thumbnail for the Sydney video. Dude, It’s Sydney Australia, not Sydney Lawrence ;).
Fall is traditional Music Hack Day season, and 2013 is shaping up to be the strongest yet. Three Music Hack Days have just been announced:
- Chicago – September 21st and 22nd – this will be the first ever Music Hack Day in Chicago.
- Bologna – October 5th and 6th – in collaboration with roBOt Festival 2013. The first Music Hack Day in Italy.
- New York - October 18th and 19th – being held in Spotify’s nifty new offices.
There will no doubt be more hack days before the end of the year including the traditional Boston and London events. You can check out the full schedule and sign up to be notified whenever at a new Music Hack Day is announced at MusicHackDay.org.
Music Hack Day is an international 24-hour event where programmers, designers and artists come together to conceptualize, build and demo the future of music. Software, hardware, mobile, web, instruments, art – anything goes as long as it’s music related.
SXSW 2014 PanelPicker has opened up. I took a tour through the SXSW Music panel proposals to highlight the ones that are of most interest to me … typically technical panels about music discovery and interaction. Here’s the best of the bunch. You’ll notice a number of Echo Nest oriented proposals. I’m really not shilling, I genuinely think these are really interesting talks (well, maybe I’m shilling for my talk).
I’ve previously highlighted the best the bunch for SXSW Interactive.
A Genre Map for Discovering the World of Music
All the music ever made (approximately) is a click or two away. Your favorite music in the world is probably something you’ve never even heard of yet. But which click leads to it?
Most music “discovery” tools are only designed to discover the most familiar thing you don’t already know. Do you like the Dave Matthews Band? You might like O.A.R.! Want to know what your friends are listening to? They’re listening to Daft Punk, because they don’t know any more than you. Want to know what’s hot? It’s yet another Imagine Dragons song that actually came out in 2012. What we NEED are tools for discovery through exploration, not dictation.
This talk will provide a manic music-discovery demonstration-expedition, showcasing how discovery through exploration (The Echo Nest Discovery list & the genre mapping experiment, Every Noise at Once) in the new streaming world is not an opportunity to pay different people to dictate your taste, but rather a journey, unearthing new music JUST FOR YOU.
The Predictive Power of Music
Music taste is extremely personal and an important part of defining and communicating who we are.
Musical Identity, understanding who you are as a music fan and what that says about you, has always been a powerful indicator of other things about you. Broadcast radio’s formats (Urban, Hot A/C, Pop, and so on) are based on the premise that a certain type of music attracts a certain type of person. However, the broadcast version of Musical Identity is a blunt instrument, grouping millions of people into about 12 audience segments. Now that music has become a two-way conversation online, Musical Identity can become considerably more precise, powerful, and predictive.
In this talk, we’ll look at why music is one of the strongest predictors and how music preference can be used to make predictions about your taste in other forms of entertainment (books, movies, games, etc).
Your Friends Have Bad Taste: Fixing Social Music
Music is the most social form of entertainment consumption, but online music has failed to deliver truly social & connected music experiences. Social media updates telling you your aunt listened to Hall and Oates doesn’t deliver on the promise of social music. As access-based, streaming music becomes more mainstream, the current failure & huge potential of social music is becoming clearer. A variety of app developers & online music services are working to create experiences that use music to connect friends & use friends to connect you with new music you’ll love. This talk will uncover how to make social music a reality.
Anyone Can Be a DJ: New Active Listening on Mobile
The mobile phone has become the de facto device for accessing music. According to a recent report, the average person uses their phone as a music player 13 times per day. With over 30 million songs available, any time, any place, listening is shifting from a passive to a personalized and interactive experience for a highly engaged audience.
New data-powered music players on sensor-packed devices are becoming smarter, and could enable listeners to feel more like creators (e.g. Instagram) by dynamically adapting music to its context (e.g. running, commuting, partying, playing). A truly personalized pocket DJ will bring music listening, discovery, and sharing to an entirely new level.
In this talk, we’ll look at how data-enhanced content and smarter mobile players will change the consumer experience into a more active, more connected, and more engaged listening experience.
Human vs. Machine: The Music Curation Formula
Recreating human recommendations in the digital sphere at scale is a problem we’re actively solving across verticals but no one quite has the perfect formula. The vertical where this issue is especially ubiquitous is music. Where we currently stand is solving the integration of human data with machine data and algorithms to generate personalized recommendations that mirrors the nuances of human curation. This formula is the holy grail.
Algorithmic, Curated & Social Music Discover
As the Internet has made millions of tracks available for instant listening, digital music and streaming companies have focused on music recommendations and discovery. Approaches have included using algorithms to present music tailored to listeners’ tastes, using the social graph to find music, and presenting curated & editorial content. This panel will discuss the methods, successes and drawbacks of each of these approaches. We will also discuss the possibility of combining all three approaches to present listeners with a better music discovery experience, with on-the-ground stories of the lessons from building a Discover experience at Spotify.
Beyond the Play Button – The Future of Listening (This is my talk)
35 years after the first Sony Walkman shipped, today’s music player still has essentially the same set of controls as that original portable music player. Even though today’s music player might have a million times more music than the cassette player, the interface to all of that music has changed very little.
In this talk we’ll explore new ways that a music listener can interact with their music. First we will explore the near future where your music player knows so much about you, your music taste and your current context that it plays the right music for you all the time. No UI is needed.
Next, we’ll explore a future where music listening is no longer a passive experience. Instead of just pressing the play button and passively listening you will be able to jump in and interact with the music. Make your favorite song last forever, add your favorite drummer to that Adele track or unleash your inner Skrillex and take total control of your favorite track.
5 Years of Music Hack Day
Started in 2009 by Dave Haynes and James Darling, Music Hack Day has become the gold standard of music technology events. Having grown to a worldwide, monthly event that has seen over 3500 music hacks created in over 20 cities the event is still going great guns. But, what impact has this event had on the music industry and it’s connection with technology? This talk looks back at the first 5 years of Music Hack Day, from it’s origins to becoming something more important and difficult to control than it’s ‘adhocracy’ beginnings. Have these events really impacted the industry in a positive way or have the last 5 years simply seen a maturing attitude towards technologies place in the music industry? We’ll look at the successes, the hacks that blew people’s minds and what influence so many events with such as passionate audience have had on changing the relationship between music and tech.
The SXSW organizers pay attention when they see a panel that gets lots of votes, so head on over and make your opinion be known.
SXSW 2014 PanelPicker has opened up. I took a tour through the SXSW Interactive talk proposals to highlight the ones that are of most interest to me … typically technical panels about music discover and interaction. Here’s the best of the bunch. Tomorrow, I’ll take a tour through the SXSW Music proposals.
Algorithmic Music Discovery at Spotify
Spotify crunches hundreds of billions of streams to analyze user’s music taste and provide music recommendations for its users. We will discuss how the algorithms work, how they fit in within the products, what the problems are and where we think music discovery is going. The talk will be quite technical with a focus on the concepts and methods, mainly how we use large scale machine learning, but we will also some aspects of music discovery from a user perspective that greatly influenced the design decisions.
Delivering Music Recommendations to Millions
At its heart, presenting personalized data and experiences for users is simple. But transferring, delivering and serving this data at high scale can become quite challenging.
In this session, we will speak about the scalability lessons we learned building Spotify’s Discover system. This system generates terabytes of music recommendations that need to be delivered to tens of millions of users every day. We will focus on the problems encountered when big data needs to be replicated across the globe to power interactive media applications, and share strategies for coping with data at this scale.
Are Machines the DJ’s of Digital Music?
When it comes to music curation, has our technology exceeded our humanity? Fancy algorithms have done wonders for online dating. Can they match you with your new favorite music? Hear music editors from Rhapsody, Google Music, Sony Music and Echonest debate their changing role in curation and music discovery for streaming music services. Whether tuning into the perfect summer dance playlist or easily browsing recommended artists, finding and listening to music is the result of very intentional decisions made by editorial teams and algorithms. Are we sophisticated enough to no longer need the human touch on our music services? Or is that all that separates us from the machines?
Your Friends Have Bad Taste: Fixing Social Music
Music is the most social form of entertainment consumption, but online music has failed to deliver truly social & connected music experiences. Social media updates telling you your aunt listened to Hall and Oates doesn’t deliver on the promise of social music. As access-based, streaming music becomes more mainstream, the current failure & huge potential of social music is becoming clearer. A variety of app developers & online music services are working to create experiences that use music to connect friends & use friends to connect you with new music you’ll love. This talk will uncover how to make social music a reality, including:
- Musical Identity (MI) – who we are as music fans and how understanding MI is unlocking social music apps
- If my friend uses Spotify & I use Rdio, can we still be friends? ID resolution & social sharing challenges
- Discovery issue: finding like-minded fans & relevant expert music curators
- A look at who’s actually building the future of social music
‘Man vs. Machine’ Is Dead, Long Live Man+Machine
A human on a bicycle is the most efficient land-traveller on planet Earth. Likewise, the most efficient advanced, accurate, helpful, and enjoyable music recommendation systems combine man and machine. This dual-pronged approach puts powerful, data-driven tools in the hands of thinking, feeling experts and end users. In other words, the debate over whether human experts or machines are better at recommending music is over. The answer is “both” — a hybrid between creative technology and creative curators. This panel will provide specific examples of this approach that are already taking place, while looking to the future to see where it’s all headed.
Are Recommendation Engines Killing Discovery?
Are recommendation engines – like Yelp, Google, and Spotify – ruining the way we experience life? “Absolutely,” says Ned Lampert. The average person looks at their phone 150 times a day, and the majority of content they’re looking at is filtered through a network of friends, likes, and assumptions. Life is becoming prescriptive, opinions are increasingly polarized, and curiosity is being stifled. Recommendation engines leave no room for the unexpected. Craig Key says, “absolutely not.” The Web now has infinitely more data points than we did pre-Google. Not only is there more content, but there’s more data about you and me: our social graph, Netflix history (if you’re brave), our Tweets, and yes, our Spotify activity. Data is the new currency in digital experiences. While content remains king, it will be companies that can use data to sort and display that content in a meaningful way that will win. This session will explore these dueling perspectives.
Genre-Bending: Rise of Digital Eclecticism
The explosion in popularity of streaming music services has started to change the way we listen. But even beyond those always-on devices with unlimited access to millions of songs that we listen to on our morning commutes, while wending our way through paperwork at our desks or on our evening jogs, there is an even a more fundamental change going on. Unlimited access has unhinged musical taste to the point where eclecticism and tastemaking trump identifying with a scene. Listeners are becoming more adventurous, experiencing many more types of music than ever before. And artists are right there with them, blending styles and genres in ways that would be unimaginable even a decade ago. In his role as VP Product-Content Jon Maples has a front row seat to how music-listening behavior has evolved. He’ll share findings from a recent ethnographic study that reveals intimate details on how people live their musical lives.
Put It In Your Mouth: Startups as Tastemakers
Your life has been changed, at least once, by a startup in the last year. Don’t argue; it’s true. Think about it – how do you listen to music? How do you choose what movie to watch? How do you shop, track your fitness or share memories? Whoever you are, whatever your preferences, emerging technology has crept into your life and changed the way you do things on a daily basis. This group of innovators and tastemakers will take a highly entertaining look at how the apps, devices and online services in our lives are enhancing and molding our culture in fundamental ways. Be warned – a dance party might break out and your movie queue might expand exponentially.
And here’s a bit of self promotion … my proposed panel is all about new interfaces for music.
Beyond the Play Button – The Future of Listening
35 years after the first Sony Walkman shipped, today’s music player still has essentially the same set of controls as that original portable music player. Even though today’s music player might have a million times more music than the cassette player, the interface to all of that music has changed very little. In this talk we’ll explore new ways that a music listener can interact with their music. First we will explore the near future where your music player knows so much about you, your music taste and your current context that it plays the right music for you all the time. No UI is needed. Next, we’ll explore a future where music listening is no longer a passive experience. Instead of just pressing the play button and passively listening you will be able to jump in and interact with the music. Make your favorite song last forever, add your favorite drummer to that Adele track or unleash your inner Skrillex and take total control of your favorite track.
The SXSW organizers pay attention when they see a panel that gets lots of votes, so head on over and make your opinion be known.