Zeiler received his Ph.D. in machine learning and image recognition, and his research produced the top 5 results in the 2013 ImageNet classification competition.
In a recent interview with BigData-MadeSimple.com he highlights that GPUs are fueling the deep learning renaissance in recent years.
“For computation, graphics processors have become the “goto” computation device, performing about 30x faster than traditional computer CPUs. This was first used around 5 years ago and enabled much more complex models to process much more data, ultimately providing markedly better performance. Graphics processors also happen to be small, relatively cheap, and easy to operate without a massive data center.”
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Interview with the Founder of Advanced Image Recognition Startup, Clarifai
Sep 28, 2015
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AI-Generated Summary
- Matthew Zeiler, founder and CEO of Clarifai, attributes the recent deep learning advancements to the use of GPUs, which have become the preferred computation device due to their speed and efficiency.
- GPUs perform computations about 30 times faster than traditional computer CPUs, enabling the processing of more complex models and larger data sets.
- The adoption of GPUs for computation began around 5 years prior to the interview, marking a significant shift in the field of machine learning and image recognition.
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Matthew Zeiler is the founder and CEO of Clarifai, which uses machine learning and deep neural networks to develop the world’s advanced image recognition system.