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From a theoretical physicist who come up with experiments to find extra dimensions in the universe and searching genes using machine learning, I want to talk about two realistic and achievable ideas ...

From a theoretical physicist who come up with experiments to find extra dimensions in the universe and searching genes using machine learning, I want to talk about two realistic and achievable ideas that I like to build as a technologist. These two products revolve around speech recognition & next generation social networks. Presented for Barcamp Singapore 3.

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The Undercover Technologist The Undercover Technologist Presentation Transcript

  • THE UNDERCOVER TECHNOLOGIST Bernard Leong A Pragmatic Idealist (http://bleongcw.typepad.com) bleongcw (at) gmail.com Friday, February 27, 2009
  • My Life in a Space-Time Diagram Time Space Friday, February 27, 2009
  • My Life in a Space-Time Diagram Time Singapore Cambridge Space Friday, February 27, 2009
  • AS A THEORETICAL PHYSICIST, I ... Find an experimental signature to show the Universe has more • than 3 spatial dimensions. Applying Self Organized Criticality to look at the firings of football • managers in the Premiere League. Use Bayesian theory, Machine Learning and Independent • Component Analysis to learn interesting DNA motifs in the Human Genome Project from stem cell regulation to cancer. Friday, February 27, 2009
  • AS A THEORETICAL PHYSICIST, I ... Find an experimental signature to show the Universe has more • than 3 spatial dimensions. Applying Self Organized Criticality to look at the firings of football • managers in the Premiere League. Use Bayesian theory, Machine Learning and Independent • Component Analysis to learn interesting DNA motifs in the Human Genome Project from stem cell regulation to cancer. Friday, February 27, 2009
  • AS A THEORETICAL PHYSICIST, I ... Find an experimental signature to show the Universe has more • than 3 spatial dimensions. Applying Self Organized Criticality to look at the firings of football • managers in the Premiere League. Use Bayesian theory, Machine Learning and Independent • Component Analysis to learn interesting DNA motifs in the Human Genome Project from stem cell regulation to cancer. Friday, February 27, 2009
  • AS A THEORETICAL PHYSICIST, I ... Find an experimental signature to show the Universe has more • than 3 spatial dimensions. Applying Self Organized Criticality to look at the firings of football • managers in the Premiere League. Use Bayesian theory, Machine Learning and Independent • Component Analysis to learn interesting DNA motifs in the Human Genome Project from stem cell regulation to cancer. Friday, February 27, 2009
  • AS A THEORETICAL PHYSICIST, I ... Find an experimental signature to show the Universe has more • than 3 spatial dimensions. Applying Self Organized Criticality to look at the firings of football • managers in the Premiere League. Use Bayesian theory, Machine Learning and Independent • Component Analysis to learn interesting DNA motifs in the Human Genome Project from stem cell regulation to cancer. Friday, February 27, 2009
  • AS A THEORETICAL PHYSICIST, I ... Find an experimental signature to show the Universe has more • than 3 spatial dimensions. Applying Self Organized Criticality to look at the firings of football • managers in the Premiere League. Use Bayesian theory, Machine Learning and Independent • Component Analysis to learn interesting DNA motifs in the Human Genome Project from stem cell regulation to cancer. Friday, February 27, 2009
  • AS A THEORETICAL PHYSICIST, I ... Find an experimental signature to show the Universe has more • than 3 spatial dimensions. Applying Self Organized Criticality to look at the firings of football • managers in the Premiere League. Use Bayesian theory, Machine Learning and Independent • Component Analysis to learn interesting DNA motifs in the Human Genome Project from stem cell regulation to cancer. Friday, February 27, 2009
  • WHAT DOES THAT GOTTA DO WITH THE TALK TODAY? • Two Interesting Ideas about Technology that I am interested to think about/invest/develop if I ever have the free time. • Next Generation Social Networks based on Degrees of Association which measure Influence and Reputation. • Voice Recognition on Mobile Phones and Computers. • This talk is just a sketch of how each one of these products can be created and developed. • Remember: Ideas are cheap, Execution is key. Friday, February 27, 2009
  • PRODUCT 1 NEXT GENERATION WEIGHTED SOCIAL NETWORKS Friday, February 27, 2009
  • SOCIAL NETWORKS Social Networks are Cultural, Generational & Geographical. Source: Oxyweb, Nov 2008 Friday, February 27, 2009
  • From Friendster to Facebook Static Profile Dynamic Profile: News Feed, Groups, Events Friday, February 27, 2009
  • Linkedin connects people professionally but does not distinguish the influencers or the connectors Friday, February 27, 2009
  • THE PROPERTIES OF A SOCIAL GRAPH Six Degrees of Self-Organizing Nature • • Seperation: Everyone is of Networks: scale free connected to each other and the ability of identify within six degrees of generic hubs and experiment. connectors in a network. Friday, February 27, 2009
  • THE PROPERTIES OF A SOCIAL GRAPH Six Degrees of Self-Organizing Nature • • Seperation: Everyone is of Networks: scale free connected to each other and the ability of identify within six degrees of generic hubs and experiment. connectors in a network. Friday, February 27, 2009
  • THE PROPERTIES OF A SOCIAL GRAPH Six Degrees of Self-Organizing Nature • • Seperation: Everyone is of Networks: scale free connected to each other and the ability of identify within six degrees of generic hubs and experiment. connectors in a network. Friday, February 27, 2009
  • THE PROPERTIES OF A SOCIAL GRAPH Six Degrees of Self-Organizing Nature • • Seperation: Everyone is of Networks: scale free connected to each other and the ability of identify within six degrees of generic hubs and experiment. connectors in a network. Friday, February 27, 2009
  • A SOCIAL GRAPH THOUGHT EXPERIMENT Friday, February 27, 2009
  • In the online world, each connection is characterized by a 1(Connected) or 0 (Not Connected) Friday, February 27, 2009
  • The Current Social Network is unable to measure Degrees of Association, i.e. how well you know that person. Friday, February 27, 2009
  • TRY THIS NEW IDEA 9 9 Rule 1: Each user assigns a degree of association 7 5 value (1-10) on how well you know the other 7 person. Do it for multiple 8 users. Score this based on the average of each pair scores. Friday, February 27, 2009
  • 10 5 10 9 10 • Rule 2: Fit a statistical 2 distribution on all your associations. • Rule 3: Calibrate the weights between each pair of 7.5 users based on the social 9.5 6 Friday, February 27, 2009
  • A WEIGHTED SOCIAL NETWORK Friday, February 27, 2009
  • With a weighted social network, you can search for best path to connect to someone within a network and also find the influencers and hubs. Friday, February 27, 2009
  • PRODUCT 2 AN OPEN SOURCE VOICE RECOGNITION PROJECT Friday, February 27, 2009
  • PROBLEM • Can you build a voice recognition app which shows the name of the person and his/her number when you say his/her name? • Current Developments: iPhone - Google App (1.5 mins), Nokia (2-3 mins), Blackberry (2-3 mins). • The challenge is to reduce the time to recall the name and number within 30s. Friday, February 27, 2009
  • WHY IS IT SO DIFFICULT TO SAY “COMPUTER, ...”? • Getting the Universal Voice Training Set is extremely difficult: • Different Accents • Different Languages • Different Intonation • Different Pitch Friday, February 27, 2009
  • HERE’S A SKETCH: Fundamental Assumption: What if we confine voice recognition of a gadget • such as a mobile phone to the user alone and specifically target the apps adjusted to him? An Open Source Voice Recognition Project (GPL) that consists of: • Repository to store training sets of users for research purposes. • An API built on three core layers: Training Data API, Recognition API and • Application API. Build a few apps and get the developers/users community to join the fray • Training Data API Recognition API Application API Friday, February 27, 2009
  • Training Data API Friday, February 27, 2009
  • Training Data API Friday, February 27, 2009
  • Training Data API Friday, February 27, 2009
  • Training Data API Friday, February 27, 2009
  • Training Data API Friday, February 27, 2009
  • Training Data API Friday, February 27, 2009
  • Training Data API Hidden Markov Model Friday, February 27, 2009
  • Training Data API Hidden Markov Model Friday, February 27, 2009
  • Training Data API Hidden Markov Model Friday, February 27, 2009
  • Training Data API Hidden Markov Model Friday, February 27, 2009
  • Training Data API Hidden Markov Model Friday, February 27, 2009
  • Friday, February 27, 2009
  • Friday, February 27, 2009
  • Friday, February 27, 2009
  • Friday, February 27, 2009
  • Friday, February 27, 2009
  • WHAT TYPE OF APPLICATION • Suggestions for Basic Voice Recognition Apps: • Voice Recognition Lock • Voice Recognition Shutdown • Voice Recognition Search (1-3 words) to locate where you are. • Slowly evolve the complexity and let your imagination run wild. Friday, February 27, 2009
  • IS IT A PIPE DREAM? “You see things; and you say ‘Why?’ But I dream things that never were; and I say ‘Why not?’” - George Bernard Shaw Friday, February 27, 2009