Thursday, December 18, 2014

Weaver: a new dynamic graph framework

My friend Yaron Weinsberg sent me a link to Weaver, a new dynamic graph framework from Cornell.

Wednesday, December 17, 2014

Minerva: open source deep learning on GPU software from MS

I got this from my colleague Chris DeBois - Minerva is an open source deep learning software.  They claim to be able to support multiple GPUs on the same machine.

Here is the paper which describes Minerva.

Tuesday, December 16, 2014

Bitcoin conference: Jan 27, SF

My friend and colleague Ben Lorica, chief scientist of O'Reilly Media never rests.. Now how organize an interesting BitCoin related one day conference on Jan 27 in SF.

Readers of this blogs are welcome to use discount code USGR20.

Intel Xeon-Phi is trying to catch up on NVIDIA

I got this article from my colleague Matt from Walmart:
http://hips.seas.harvard.edu/content/micmat-python-scientific-computing-intel-xeon-phi
it seems that Intel is trying to catch up on NVIDIA by creating tools for GPU processing.

NVIDIA has some opinion on Intel's effort which is listed here.


Friday, December 12, 2014

Hardcore data science

My friend and colleague Ben Lorica, just sent me a link to the hardcore data science track is his organizing at Strata San Jose. Super interesting topics - in addition, you are welcome to use discount code GRAPHLAB20 when registering.

Tuesday, December 9, 2014

GraphLab's deep learning - the power of graph applied to images

A couple of months ago we have released a deep learning toolkit for GraphLab Create. I just got today a code contribution from Marian Moldovan & Enrique Otero, from Beeva.com.

They created a super awesome application. Imagine you have a repository of images and you would like to understand the relation between the images. The images are of buildings in Barcelona, as this work was created at the hacknight of papis.io.

Here is the first building:


And here is the second building:


What is the architecture transition that can explain this path? Using GraphLab Create it is easy to compute!

Here is a graph of all the similar buildings:

And here is a path between two interesting buildings (number 16 and 23)
Using GraphLab Create, it is very simple to extract features from those images, create a nearest neighbor graph, and then find shortest path on this graph.

Email me if you like to get the ipython notebook with this example!