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A gigantic shift in computing is about to dawn upon us, one that is as significant as only two other moments in computing history. First came the “desktop era” of computing, powered by central processing units (CPUs), followed by the “mobile era” of computing, powered by more power-efficient mobile processors. Now, there is a new computing stack that is moving all of software with it, fueled by artificial intelligence (AI) and chips specifically designed to accommodate its grueling computations.

Matroid has raised $10 million Series A co-led by Intel and NEA, bringing funding to $13.5M, following a $3.5M seed round from NEA. We are excited to work with Intel and NEA to continue bringing Computer Vision to everyone. Join us! We are hiring at matroid.com/careers

Today the Internet Archive announced "Face-o-matic", to identify prominent public figures in TV channels aired across the world.

Matroid has been covered by The Wall Street Journal, Bloomberg, MIT Technology Review, TechCrunch, BBC, Seattle Times, Register, CNBC, and many others.

Matroid was presented at the Fermilab special colloquium on May 9th. Slides and a video of the talk are available on the Fermilab lab colloquium page.

First Two Chapters of "TensorFlow for Deep Learning" Released, head over to the O'Reilly website to download your copy. A PDF of the first two chapters is also available exlusively via Matroid here.

Matroid launched at Scaled ML 2017, and was covered by The Wall Street Journal, Bloomberg, TechCruch.

The Scaled Machine Learning 2017 Conference Slides.

Come see what we've been up to, learn about leading deep learning cloud providers, and meet leading researchers in the area! More details at http://scaledml.org

In this post, I explore the “hardness” in optimizing neural networks and see what the theory has to say. In a nutshell: the deeper the network becomes, the harder the optimization problem becomes.

As Intel moves aggressively into Machine Learning, they have published an interview with Matroid.

The FusionNet architecture will be presented at the NIPS 2016 workshop for 3D Deep Learning.

Organized by Amazon and Matroid, the DEEM workshop will be held in conjunction with SIGMOD/PODS 2017 in Raleigh, North Carolina. DEEM aims to bring together researchers and practitioners at the intersection of applied machine learning, data management and systems research, with the goal to discuss the arising data management issues in ML application scenarios.

Leading a group of industry and academic contributors, Matroid receives the KDD 2016 Best Paper Award runner-up in the applied data science track.

Our new Neural Network architecture named FusionNet is leading in the Princeton ModelNet challenge.

"That openness, and continual Google updates, have lured developers like computer-vision startup Matroid, which re-wrote its software to work with TensorFlow, after building on another free AI tool called Caffe."

Slides from the Matroid Scaled Machine Learning Conference held on Stanford campus.

We are excited for the upcoming Scaled Machine Learning Conference on Stanford Campus. See the lineup at http://scaledml.org. At Matroid we have been using TensorFlow extensively, and to help the Open Source community learn more about this tool, we are running two sessions devoted to it at our company conference.

Announcing the Scaled Machine Learning Conference on Stanford University Campus, Matroid's company conference.

Several weeks ago, Innovation Endeavors partnered with Bloomberg BETA to host an exclusive deep learning event for top experts – academics, entrepreneurs, and engineers – and investors to take a closer look at the space. The event centered around a panel discussion with Ilya Sutskever, Research Director at OpenAI; Reza Zadeh, CEO at Matroid and Professor at Stanford University; and Richard Socher, CEO of MetaMind. The conversation was moderated by Jack Clack of Bloomberg.

Today O'Reilly released a report on the Future of Machine Intelligence. The concluding chapter is an interview with Matroid.

Join us at Strata 2016 in San Jose, on Thursday March 31st, in room 210 A/E. Reza from Matroid will be hosting the Spark session. See here for a full schedule.

Matroid recently moved into a new office! Visit us at 3239 El Camino Real, Palo Alto 94306.

Located next to Caltrain and the restaurants of California Avenue. 

How we chose the name "Matroid", a concept from Computer Science Theory and Mathematics.

We were at the Strata + Hadoop world conference this past week and presented in the "Hard Core Data Science" track.