This document summarizes a presentation given at SXSW 2014 about moving beyond simply playing music to more interactive listening experiences. It discusses categorizing listeners into types like "savants" and "indifferents" and how their tastes, spending habits, and interactions differ. It also explores how attributes like gender, age, and location impact music preferences and describes building contextual playlists based on activities. Finally, it outlines approaches to music discovery through pathfinding within artist collaboration networks, cover songs, and other relationships to engage more active listeners.
How does having 30 million songs in our pocket affect how we listen to music? In this data-driven and demo-laden talk we’ll explore the behavior of today’s music listener. We’ll look at how today’s easy and ubiquitous access to nearly all of recorded music is changing how a listener organizes, discovers and experiences music. By exploring big music data being collected by organizations such as Spotify and The Echo Nest we can get a deeper and more nuanced view of how today’s listener really interacts with their music.
I've got 10 million songs in my pocket. Now what? Paul Lamere
The proverbial 'celestial jukebox' has become a reality. With today's online music services a music fan is never more than a few clicks away from being able to listen to nearly any song that has ever been recorded. Recommender systems can play a key role in this new music ecosystem, helping listeners explore, discover, organize and share music. However, in many ways music recommendation is very different than recommendation in other well-studied domains such as books and movies. In this talk we explore how recommender systems can be used in the music space, and the particular challenges that the music domain presents to the designers of recommender systems.
How does having 30 million songs in our pocket affect how we listen to music? In this data-driven and demo-laden talk we’ll explore the behavior of today’s music listener. We’ll look at how today’s easy and ubiquitous access to nearly all of recorded music is changing how a listener organizes, discovers and experiences music. By exploring big music data being collected by organizations such as Spotify and The Echo Nest we can get a deeper and more nuanced view of how today’s listener really interacts with their music.
I've got 10 million songs in my pocket. Now what? Paul Lamere
The proverbial 'celestial jukebox' has become a reality. With today's online music services a music fan is never more than a few clicks away from being able to listen to nearly any song that has ever been recorded. Recommender systems can play a key role in this new music ecosystem, helping listeners explore, discover, organize and share music. However, in many ways music recommendation is very different than recommendation in other well-studied domains such as books and movies. In this talk we explore how recommender systems can be used in the music space, and the particular challenges that the music domain presents to the designers of recommender systems.
An analysis of the responses I received form my survey into the R&B genre as part of my A2 Media Coursework, their artists and the consumption of music videos, broken down by gender.
An analysis of the responses I received form my survey into the R&B genre as part of my A2 Media Coursework, their artists and the consumption of music videos, broken down by gender.
The Future of Fashion Stores & Virtual Retail- ELSE Corp visionELSE CORP
ELSE Corp brings a new solution for retail stores. ELSE Corp presents and introduce "The Future of Fashion Stores and Virtual Retail"
A new solution for retail store. http://www.else-corp.com/
Luxury 3.0- a new Retail Scenario for Product Mass Customization and On Deman...ELSE CORP
ELSE Corp offers a new solution for luxury fashion retail: "Luxury Product Customization and Virtual Retail". Introduction to New Trends & New Principles, The Perfect Product and The Virtual Retail. Luxury 3.0 scenario
For more info: http://www.else-corp.com/
This was a speech that I gave at an Ignite event - where you have 20 slides that automatically move after 15 seconds!
I added some of what I was saying during the presentation for this to make sense!
Finding Music With Pictures: Using Visualization for DiscoveryPaul Lamere
Slides from my SXSW 2011 talk. Here's the abstract:
With so much music available, finding new music that you like can be like finding a needle in a haystack. We need new tools to help us to explore the world of music, tools that can help us separate the wheat from the chaff. In this panel we will look at how visualizations can be used to help people explore the music space and discover new, interesting music that they will like. We will look at a wide range of visualizations, from hand drawn artist maps, to highly interactive, immersive 3D environments. We'll explore a number of different visualization techniques including graphs, trees, maps, timelines and flow diagrams and we'll examine different types of music data that can contribute to a visualization. Using numerous examples drawn from commercial and research systems we'll show how visualizations are being used now to enhance music discovery and we'll demonstrate some new visualization techniques coming out of the labs that we'll find in tomorrow's music discovery applications.
The Echo Nest workshop for Boston Music Hack DayPaul Lamere
This is a slide deck for the Echo Nest API workshop presented at the Boston Music Hack Day on November 21, 2010. Note that the live presentation has music and video that is not present in this deck
Using Visualizations for Music DiscoveryPaul Lamere
As the world of online music grows, tools for helping people find new and interesting music in these extremely large collections become increasingly important. In this tutorial we look at one such tool that can be used to help people explore large music collections: information visualization. We survey the state-of-the-art in visualization for music discovery in commercial and research systems. Using numerous examples, we explore different algorithms and techniques that can be used to visualize large and complex music spaces, focusing on the advantages and the disadvantages of the various techniques. We investigate user factors that affect the usefulness of a visualization and we suggest possible areas of exploration for future research.
This is the slide set for the ISMIR 2009 tutorial by Justin Donaldson and Paul Lamere. Note that this presentation originally included a large number of audio and video samples which are not included in this slide deck due to space considerations.
Music recommendation is broken - automatic music recommenders make mistakes that no human would ever make. In this talk, we will explore why recommenders make such dumb mistakes and we will explore some of the new ideas coming from recommendation and music researchers to help make music recommendations better.
Slides from the SXSW 2009 Panel. Speakers: Paul Lamere from The Echo Nest, and Anthony Volodkin from The Hype Machine.
Social Tags and Music Information Retrieval (Part I)Paul Lamere
Part 1 of the Social Tags and Music Information Retrieval Tutorial. Abstract: Social Tags are free text labels that are applied to items such as artists, playlists and songs. These tags have the potential to have a positive impact on music information retrieval research. In this tutorial we describe the state of the art in commercial and research social tagging systems for music. We explore some of the motivations for tagging. We describe the factors that affect the quantity and quality of collected tags. We present a toolkit that MIR researchers can use to harvest and process tags. We look at how tags are collected and used in current commercial and research systems. We explore some of the issues and problems that are encountered when using tags. We present current MIR-related research centered on social tags and suggest possible areas of exploration for future resear
Social Tags and Music Information Retrieval (Part II)Paul Lamere
Part 2 of the slides for the Social Tags and Music Information Retrieval Tutorial - Abstract: Social Tags are free text labels that are applied to items such as artists, playlists and songs. These tags have the potential to have a positive impact on music information retrieval research. In this tutorial we describe the state of the art in commercial and research social tagging systems for music. We explore some of the motivations for tagging. We describe the factors that affect the quantity and quality of collected tags. We present a toolkit that MIR researchers can use to harvest and process tags. We look at how tags are collected and used in current commercial and research systems. We explore some of the issues and problems that are encountered when using tags. We present current MIR-related research centered on social tags and suggest possible areas of exploration for future resear
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
Beyond the Play Button - The future of listening
1. Beyond the Play Button - SXSW 2014 - #PlayButton
Beyond the Play Button
The future of listening
Paul Lamere
The Echo Nest
SXSW March 11, 2013
#sxsw #PlayButton
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The 1979 iPod
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The 1979 iPod
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The 1979 iPod
Vinyl Cassette
CD
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The 1979 iPod
Vinyl Cassette
CD
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Digital Music Milestones
2001 2003 2007 2008
1979 1995 1999
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All listeners are not created equal
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Four listener types
Savants
Enthusiasts
Casuals
Indifferents
Survey conducted in 2003 and again in 2006 by Emap
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0%
10%
20%
30%
40%
Savants Engaged Casuals Indifferents
Distribution of Listener Types
10%
20%
30%
40%
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0%
10%
20%
30%
40%
Savants Engaged Casuals Indifferents
Distribution of Listener Types
>$1,000
$100
$10
$1
Dollars spent per year by listener type
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0%
10%
20%
30%
40%
Savants Engaged Casuals Indifferents
Distribution of Listener Types
100+
10
1
0
Average Interactions per Listening Session
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0%
10%
20%
30%
40%
Savants Engaged Casuals Indifferents
Distribution of Listener Types
100+
10
1
0
Average Interactions per Listening Session
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Money to spend
Musical sophistication
Interaction
Savant Engaged Casual Indifferent
More Less
70% of listeners
Lean forward Lean back
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I like Adele
What should I pick?
Interfaces built
for engaged music
fans will challenge
the casual or
indifferent fan
One size doesn’t fit all
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Better than radio
The challenge: to engage casual and indifferent listeners
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Understanding the Listener
Demographics
Music Taste
Context
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Demographics
• Gender
• Age
• Location
How much does a
listener’s
demographic affect
their listening?
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Gender
How does a listener’s gender affect their taste in music?
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Gender Skewed Playlists
http://static.echonest.com/contextual/gender.html
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Top gender-skewed artists
• Iron Maiden
• Rage Against the Machine
• Van Halen
• N.W.A
• Jimi Hendrix
• Limp Bizkit
• Wu-Tang Clan
• Xzibit
• The Who
• Moby
• Danity Kane
• Cody Simpson
• Hannah Montana
• Emily Osment
• Playa Limbo
• Vanessa Hudgens
• Sandoval
• Miranda Lambert
• Sugarland
• Aly & AJ
Skews Male Skews Female
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Top genres by gender
• Pop
• Dance Pop
• Contemporary Hit Radio
• Urban Contemporary
• R&B
• Hot Adult Contemporary
• Latin Pop
• Teen Pop
• Neo soul
• Latin
• Pop rock
• Contemporary country
• Rock
• Hip Hop
• House
• Album Rock
• Rap
• Pop Rap
• Indie Rock
• Funk Rock
• Gangster Rap
• Electro house
• Classic rock
• Nu metal
Top female genres Top male genres
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Age
How does a listener’s age affect their taste in music?
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Distribution of listeners by age
Relativenumberoflisteners
Year of Birth
22 y/o
32
42
52
62
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Age specific listening preferences
• Skrillex
• Emblem3
• Sage The Gemini
• Selena Gomez & The Scene
• Barden Bellas
• Karmin
• Cher Lloyd
• Mac Miller
• The Treblemakers
• Little Mix
• Hannah Montana
• Ross Lynch
• Zedd
• Roy Orbison
• James Taylor
• Jackson Browne
• The Everly Brothers
• Neil Diamond
• Willie Nelson
• The Doors
• Tony Bennett
• Cat Stevens
• Bee Gees
• Rod Stewart
• Nat King Cole
• Joni Mitchell
13-year-old 64-year-old
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Age specific listening preferences
13-year-old 64-year-old
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Location
How does where a listener’s lives
affect their taste in music?
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Regional listening preferences
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Regional listening preferences
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Regional listening preferences
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Listener’s Music Taste
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Listener’s Music Taste
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Context
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Context
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Automatically building contextual playlists
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Automatically building contextual playlists
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Automatically building contextual playlists
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Automatically building contextual playlists
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Automatically
Inferring
Context
From Activity
Personalized
Implicit
Contextual
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The most boring data
Next gen devices
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Zero UI devices
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Zero UI devices
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The most boring data
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The most boring data
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Lean Forward Listener
Experience
Discovery
Interaction
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Money to spend
Musical sophistication
Interaction
Savant Engaged Casual Indifferent
More Less
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Money to spend
Musical sophistication
Interaction
Savant Engaged Casual Indifferent
More Less
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Enhancing the listening experience
http://www.stanford.edu/~dgleich/demos/worldofmusic/WorldOfMusic.html
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Tinie Tempah Rap Demonstration
Created by British agency We Make Awesome Sh.
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Tinie Tempah Rap Demonstration
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Attention Deficit Radio
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Music discovery for the
more active listener
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Music discovery as path finding
http://www.stanford.edu/~dgleich/demos/worldofmusic/WorldOfMusic.html
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Music discovery as path finding
http://www.stanford.edu/~dgleich/demos/worldofmusic/WorldOfMusic.html
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There must be five ways to get
from Miley Cyrus to Cannibal Corpse
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Six Degrees of Black Sabbath
Path finding through the artist
collaboration space
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Boil the Frog
Path finding through the artist
similarity space
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Going Under Cover
Path finding through the
cover song space
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Roadtrip Mixtape
Path finding through the
physical space
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90. Beyond the Play Button - SXSW 2014 - #PlayButton
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3D Music Maze
Path finding through a
virtual game space
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Visualizing the structure of pop music
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Tik Tok by Ke$ha
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Paparazzi by Lady Gaga
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Baby by Justin Bieber
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Fearless by Taylor Swift
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Stairway to Heaven by Led Zeppelin
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Raise your weapon by Deadmau5
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Take Five by Dave Brubeck
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Green Grass and High Tides by The Outlaws
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Roundabout byYes
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Cello Suite No.1,Yo-Yo Ma
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4’33 by John Cage (Live performance)
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Nyan Cat
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Girl Talk in a Box
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I’ve got 30 million songs in my pocket.
Now what?
The future of
music listening:
Engage the
indifferents
Empower the
the music fan
Tuesday, March 11, 14
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Beyond the Play Button
Paul Lamere
@plamere
The Echo Nest // Spotify
SXSW March 11, 2013
#sxsw #PlayButton
Links to slides, demos and supporting
data can be found at:
musicmachinery.com
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