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Michael Tetelman
Works at Stealth Mode Startup
Attended Нижегородский Государственный Университет им. Н.И. Лобачевского (ННГУ)
Lives in San Francisco Bay Area
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Michael Tetelman
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Finally we can use a linear solution as a baseline.
 
This is the first paper, which I kind of "supervised" :-P

Good work by +David Krueger et al
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Nice tool and (almost) free API.
 
I gave a keynote talk at GCP NEXT a couple of months ago, and as part of that, I demoed this nice visual explorer that folks at Google built to demonstrate the Cloud Vision API. You get to fly through a point cloud of tens of thousands of images, annotated and clustered automatically by Google's Cloud Vision API. As of today, this demo is now released to the public, so you too can play with it (requires a relatively recent version of Chrome).

You can learn more about the Cloud Vision API, which is now in GA ("General Availability") at https://cloud.google.com/vision/

Have fun!
CV Explorer shows you how to combine Cloud Vision API w/dimensionality reduction & cluster analysis so you can build a 3D catalog of an image repository
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Michael Tetelman

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Short version of Variational Stochastic Gradient Descent is available on openreview: http://beta.openreview.net/pdf?id=0YrnoNZ7PTGJ7gK5tNYY
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Michael Tetelman

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"We are ‘almost definitely’ living in a Matrix-style simulation, claims Elon Musk" - I would add: if it so, watch for glitches where physical laws are strangely broken
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"Almost definitely", eh?  I guess you need to have the courage of your convictions to start a company that sells electric cars.
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Tensor Processing Units (TPUs)
I'm very excited that we can finally discuss this in public. Today at Google I/O +Sundar Pichai revealed the TPU (Tensor Processing Unit), a custom ASIC that Google has designed and built specifically for machine learning applications. We've had TPUs deployed in Google datacenters for more than a year, and they are an order of magnitude faster and more power efficient per operation than other computational solutions for the kinds of models we are deploying to improve our products. This computational speed allows us to use larger, more powerful machine learned models, expressed and seemlessly deployed using TensorFlow (tensorflow.org) into our products, and to deliver the excellent results from those models in less time.

TPUs are used on every Google Search to power RankBrain (https://en.wikipedia.org/wiki/RankBrain), they were a key secret ingredient in the recent AlphaGo match against Lee Sedol, they are used for speech and image recognition, and they are powering a growing list of other smart products and features.

+Norm Jouppi and the rest of the team that developed this ASIC did a fabulous job, and it's great to see it discussed in public!

Blog post:
https://cloudplatform.googleblog.com/2016/05/Google-supercharges-machine-learning-tasks-with-custom-chip.html

Link to the part of the keynote where Sundar discusses TPUs:
https://www.youtube.com/watch?v=862r3XS2YB0&feature=youtu.be&t=7300

WSJ article:
http://www.wsj.com/articles/google-isnt-playing-games-with-new-chip-1463597820

Edit: Added a link and some text.
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These just released videos are from a symposium to honor David MacKay who left us this past week: http://divf.eng.cam.ac.uk/djcms2016/
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Sorry to hear of his passing!! I met him at a maxEnt conference, and bought his book as a result of meeting him and that conference. 
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Have him in circles
516 people
S M Abdullah Al Mamun's profile photo
Nick Sergievskiy's profile photo
Uwe Schmitt's profile photo
Gonzalo Garateguy's profile photo
Yun Chi's profile photo
Yury Talapila's profile photo
Hitata nob's profile photo
Praveen Kulkarni's profile photo
Liang Guo's profile photo
Work
Occupation
I am a scientist. I am working on Technology of Prediction, which basically means understanding what you already know in a way to make a good guess about what you do not know yet.
Skills
Developing and implementing algorithms based on Deep Learning with Neural Networks and Variational Bayes
Employment
  • Stealth Mode Startup
    Founder, 2016 - present
    Deep Learning, Computer Vision and Robotics
  • Invensense, Inc
    Principal Speech Processing ASR Engineer, 2015 - 2016
    Developing Artificial Intelligence in Any Sense by Farming and Schooling Neural Nets: creating a NN framework that allows to learn from sensory data and produce an optimized runnable code for any chip without a human touch.
Places
Map of the places this user has livedMap of the places this user has livedMap of the places this user has lived
Currently
San Francisco Bay Area
Previously
I grew up far far away ( but not in Kansas)
Links
Story
Tagline
Life is a chain of accidents, but it is a most probable chain of accidents
Introduction
"Thoughts are invariants of spoken representations" - you realize that when you try to apply Group Theory to Artificial Intelligence.
I am working on advanced Machine Learning methods called Deep Learning with Infinite Feature Algebras and Continuous Learning - that is a continuous improvement of predictive models which has an interesting link to SVMs as a special limit of "perfect" models. This seems to be an universal approach to learn  structures and to model sources of any kind of data, continuously and without limits. 
Bragging rights
Developing Artificial Intelligence in Any Sense by Farming and Schooling Neural Nets: creating a NN framework that allows to learn from sensory data and produce an optimized runnable code for any chip without a human touch.
Education
  • Нижегородский Государственный Университет им. Н.И. Лобачевского (ННГУ)
    PhD, Theoretical and Mathematical Physics, Nizhniy Novgorod State University, Russia, 1992
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Male