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Recent press coverage

Financial Times

AI is (also) starting to feed a very different paradigm of computing. This is one that pushes more data-crunching out to the network " edge"… from internet-connected cameras ands smart watches to autonomous cars.

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The New York Times

Ali Farhadi holds a puny $5 computer, called a Raspberry Pi, comfortably in his palm and exults that his team of researchers has managed to squeeze into it a powerful program that can recognize thousands of objects…

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"AI for Everyone, Everywhere” may sound like a science fiction slogan, but it’s actually the name given to software from Xnor.ai that’s already making devices smarter in the real world…

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Seattle Business

Ali Farhadi and, Mohammed Rastegari, devised a way to shrink the resource requirements of AI by changing how algorithms are processed.

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The speed, memory and power savings (of Xnor’s algorithms) are huge, enabling devices with bargain-bin CPUs to perform serious tasks like real-time object recognition

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Imagine what is possible if that style of computing could be done on the device in your hand, on your wrist, or in your car

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Why Xnor.ai

The company is named after the xnor logic gate. Xnor replaces the expensive and slow high-precision arithmetic operations used in traditional neural networks with simple and fast xnor and xor operations to create its binary neural networks, with no compromise of accuracy.


Xnor logic gate

Xnor logic gate


Xnor.ai logo



Xnor.ai secondary



Xnor.ai mark only

Mark only



Technical Papers

Xnor-Net: ImageNet Classification Using
Binary Convolutional Neural Networks

You Only Look Once: Unified, Real-Time
Object Detection

Founder bios

Ali Farhadi

An image of Ali Farhadi, Co-Founder of XNor
Ali Farhadi is a founder of Xnor.ai. He is focused on efficient and embedded deep learning with the goal of providing ubiquitous AI. Ali is an Associate Professor in the Dept of Comp Sci & Eng at the University of Washington. Previously to this, he was a postdoctoral fellow at the Robotics Institute at Carnegie Mellon University. He received his PhD from University of Illinois at Urbana-Champaign under the supervision of David Forsyth. Ali has been awarded the Allen Distinguished Investigator Award, the inaugural Google fellowship in computer vision and image interpretation, the University of Illinois CS/AI 2009 award, and CVPR2011 Best Student Paper Award, NSF 2017 CAREER award, and Sloan Fellowship in 2017. Ali also leads project Plato at the Allen Institute for Artificial Intelligence where his team is mainly focused on fundamental problems at the intersection of AI and computer vision.

Mohammad Rastegari

An image of Mohammad Rastegari, Co-Founder of XNor
Mohammad Rastegari is the CTO and a founder of Xnor.ai. His main area of research and expertise is efficient methods for machine learning and computer vision. He is known for his XNOR-NET work that trains neural networks using binary operations. In addition, he has been working as a research scientist at the Allen Institute for Artificial Intelligent. Prior to AI2, Mohammad was a Facebook fellow in the artificial intelligent team (FAIR) and a research scholar at UC Berkeley. He received his PhD from University of Maryland. Mohammad’s background spans leading research organizations including Facebook, Microsoft, Adobe and Disney.

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