Wall-following for mobile robots

Wall-following is a relatively simple and useful method for an autonomous mobile robot to explore its environment. However, wall-following can be tricky for a number of reasons: Incomplete sensor coverage Limiting behaviors of range-finding infrared (IR) sensors Variety and complexity

Wall-following for mobile robots

Wall-following is a relatively simple and useful method for an autonomous mobile robot to explore its environment. However, wall-following can be tricky for a number of reasons: Incomplete sensor coverage Limiting behaviors of range-finding infrared (IR) sensors Variety and complexity

Teaching People to Teach Machines with Mechanical Turk

Mechanical Turk has proven to be a powerful tool for machine learning.  In particular, it makes it very easy to generate large amounts of training data for machine learning tasks.  For example, one can have Mechanical Turk workers transcribe recorded

Teaching People to Teach Machines with Mechanical Turk

Mechanical Turk has proven to be a powerful tool for machine learning.  In particular, it makes it very easy to generate large amounts of training data for machine learning tasks.  For example, one can have Mechanical Turk workers transcribe recorded

Principal Component Analysis and Extensions

Last summer, while working at Numenta, I spent some time reading about sensory coding and how it relates to pattern recognition.  I read a lot about sparse coding, principal component analysis, independent component analysis, nonnegative matrix factorization and other methods.  It

Principal Component Analysis and Extensions

Last summer, while working at Numenta, I spent some time reading about sensory coding and how it relates to pattern recognition.  I read a lot about sparse coding, principal component analysis, independent component analysis, nonnegative matrix factorization and other methods.  It

On the perceptual accessibility of abstract physical laws

There’s a quote widely attributed to Feynman that goes like this: “If you think you understand quantum mechanics, you don’t understand quantum mechanics.” Yet quantum mechanics, as weird as it is, is considered to be the most experimentally accurate theory

On the perceptual accessibility of abstract physical laws

There’s a quote widely attributed to Feynman that goes like this: “If you think you understand quantum mechanics, you don’t understand quantum mechanics.” Yet quantum mechanics, as weird as it is, is considered to be the most experimentally accurate theory

The Principal Components of Handwritten ‘2’s

Another example of principal components of shape datasets, this time images of ‘2’s from the MNIST handwritten digit database.  The images below are the first 50 principal components.

The Principal Components of Handwritten ‘2’s

Another example of principal components of shape datasets, this time images of ‘2’s from the MNIST handwritten digit database.  The images below are the first 50 principal components.

The Principal Components of Butterflies

The first 50 principal components of a dataset of signed distance functions computed from 100 binary images (“silhouettes”) of butterflies.

The Principal Components of Butterflies

The first 50 principal components of a dataset of signed distance functions computed from 100 binary images (“silhouettes”) of butterflies.