Matroid, Inc.
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Company type | Private |
---|---|
Industry | computer vision |
Founded | 2016 |
Founder | Reza Zadeh |
Headquarters | |
Website | matroid.com |
Matroid, Inc. is a computer vision company that offers a platform for creating computer vision models, called detectors, to search visual media for objects, persons, events, emotions, and actions. Matroid provides real-time notifications once the object of interest has been detected, as well as the ability to search past events.[1][2][3][4][5][6][7][8]
History
[edit]Matroid was founded in 2016 by Reza Zadeh, a Stanford professor. Matroid raised $20M in a Series B round led by Energize Ventures to expand into manufacturing and industrial IOT. Previous investors New Enterprise Associates and Intel Capital joined Energize in the round. The new financing brought total funding to $33.5 million.[9][10][11][12] [13]
Product
[edit]Once a detector has been trained using the Matroid GUI, it automatically finds the objects of interest in real-time video and archived footage.[2][3][5][6] Users can explore detection information via reports, notifications, or a calendar interface to view events and identify trends. Matroid’s functionality is also exposed via a developer API.
Supported hardware platforms:
- On-cloud: www.matroid.com, allows for scaling based on workload
- On-prem: contains the same functionality of www.matroid.com in a secure, offline environment for applications where data privacy and security are key concerns
- On-device: runs on embedded devices such as cameras, sensors, etc.
![](http://upload.wikimedia.org/wikipedia/commons/thumb/9/94/ScaledML_2020_Conference.jpg/220px-ScaledML_2020_Conference.jpg)
Scaled Machine Learning Conference
[edit]Matroid annually holds a conference, Scaled Machine Learning, where technical speakers lead discussions about running and scaling machine learning algorithms, artificial intelligence, and computing platforms, such as GPUs, CPUs, TPUs, & the nascent AI chip industry.[14][15]
Past speakers include Turing Award Winners, creators of Keras, TensorFlow, PyTorch, Caffe, OpenAI, Kubernetes, Horovod, Allen Institute for AI, Apache Spark, Apache Arrow, MLPerf,[16] Matroid, and others.
Announcements
[edit]- 2020 - Matroid raised $20M in a Series B round led by Energize Ventures. Previous investors NEA and Intel Capital joined in the round. The new financing brings total funding to $33.5M.[17]
- 2020 - Eagle Eye Networks and Matroid announce partnership to provide AI to Eagle Eye Cloud VMS customers.[18]
- 2018 - Matroid announced a partnership with HP for their on-prem platform. Matroid certified a selection of HP Z computers as Computer-Vision-Ready (CV-Ready) for monitoring video streams.[citation needed]
- 2018 - Oracle announced their software integration with Matroid to provide real-time and analytics based on people monitoring.[19][20][21]
Awards
[edit]- 2019 - Matroid was selected by Gartner, Inc. as a “Cool Vendor” for Cool Vendors in AI Core Technologies.[22]
- 2016 - Matroid was awarded a Best Paper Award at KDD 2016.[23]
Notable publications
[edit]Diagnosing Glaucoma using 3D CNN
[edit]Together with Stanford Hospital and hospitals in Hong Kong, India, and Nepal, Matroid used computer vision in the field of Ophthalmology.[24] The company created a model that learns to predict glaucoma from areas of the eye previously ignored during diagnosis, specifically the Lamina Cribrosa, as no established automated metrics existed for this region yet. Matroid is able to detect glaucoma on OCT scans of the eye, with an F1 score of 96% and similar AUC and accuracy.
FusionNet 3D Object Classification
[edit]FusionNet was released as a leading neural networks architecture at the Princeton ModelNet competition.[25] It is a fusion of three convolutional neural networks, one trained on pixel representation and two networks trained on voxelized objects. It exploits the strength of each component network in order to improve the classification performance. Each component network of FusionNet considers multiple views or orientations of each object before classifying it. While it is intuitive that one can get more information from multiple views of the object than a single view, it is not trivial to put the information together in order to enhance the accuracy. Matroid used information from 20 views for pixel representation and 60 CAD object orientations for voxel representation before predicting the object class. FusionNet outperformed the current leading submission on the Princeton ModelNet leaderboard in both the 10 class and the 40 class datasets.
TensorFlow for Deep Learning
[edit]Matroid released a book with co-author Bharath Ramsundar, TensorFlow for Deep Learning.[26] It introduces the fundamentals of machine learning through TensorFlow and explains how to use TensorFlow to build systems capable of detecting objects in images, understanding human text, and predicting the properties of potential medicines.
References
[edit]- ^ Sandell, Scott (3 December 2016). "If You Can't Impose Self-Discipline, You Can't Be Better Off As A Private Co". Outlook Business.
- ^ a b Mannes, John (25 March 2017). "Matroid can watch videos and detect anything within them". TechCrunch.
- ^ a b Bass, Dina (25 March 2017). "This AI Company Can Tell You What and Who Appears in Your Videos". Bloomberg.
- ^ Pasternack, Alex (30 March 2017). "The Vast, Secretive Face Database That Could Instantly ID You In A Crowd". Fast Company.
- ^ a b Matsakis, Louise (5 December 2018). "Tumblr's Porn-Detecting AI Has One Job—and It's Bad at It". Wired.
- ^ a b Peng, Tony (17 August 2018). "Building DIY Human Action Detectors With Matroid". Synced.
- ^ Feldman, Michael (8 April 2018). "GPUs Setting the Pace for the Machine Learning Age". The Next Platform.
- ^ Mark Bergen, Lucas Shaw (11 April 2019). "To Answer Critics, YouTube Tries a New Metric: Responsibility". Bloomberg.
- ^ Martin, Scott (27 March 2017). "A Life's Ambition, Matroid Launches". The Wall Street Journal.
- ^ Mannes, John (18 September 2017). "Matroid Picks up $10M Series A to Automate Video Stream Monitoring". TechCrunch.
- ^ "Matroid Computer Vision Funding Intel". Scott Amyx. 25 Oct 2017.
- ^ Razzaq, Asif (9 February 2020). "Top Artificial Intelligence Influencers to Follow in 2020". Marketechpost.
- ^ "Matroid Completes $20 Million Series B Financing to Expand into Manufacturing and Industrial IOT". Bloomberg.com. 2020-10-13. Retrieved 2020-10-26.
- ^ "Scaled Machine Learning Conference". ScaledML. Retrieved 23 March 2020.
- ^ Bauvin, Renaud (30 April 2019). "Highlights of ScaledML 2019". Criteo AI Lab.
- ^ Reddi, Vijay Janapa; Cheng, Christine; Kanter, David; Mattson, Peter; Schmuelling, Guenther; Wu, Carole-Jean; Anderson, Brian; Breughe, Maximilien; Charlebois, Mark; Chou, William; Chukka, Ramesh (2019-11-06). "MLPerf Inference Benchmark". arXiv:1911.02549v1 [cs.LG].
- ^ "Matroid Completes $20 Million Series B Financing to Expand into Manufacturing and Industrial IOT". finance.yahoo.com. Retrieved 2020-10-26.
- ^ "Eagle Eye Networks and Matroid Announce Partnership to Provide Matroid's Advanced AI On Eagle Eye Cloud VMS". www.een.com. 2020-05-05. Retrieved 2020-06-14.
- ^ Supreet, Oberoj (7 January 2019). "Part I: The Need For Computer Vision in Industrial IOT". Oracle.
- ^ Supreet, Oberoj (7 January 2019). "Part II: Surveying Computer Vision Techniques for Industrial IOT". Oracle.
- ^ Supreet, Oberoj (7 January 2019). "Part III: Integrating Computer Vision with Oracle IOT Applications". Oracle.
- ^ "Cool Vendors in AI Core Technologies". Gartner. Retrieved 2020-03-24.
- ^ "SIGKDD Awards". SIGKDD. 23 March 2020.
- ^ Erfan Noury, Suria S. Manni, Robert T. Chang, An Ran Ran, Carol Y. Cheung, Suman S. Thapa, Harsha L. Rao, Srilakshmi Dasari, Mohammed Riyazuddin, Sriharsha Nagaraj, Reza Zadeh (14 October 2019). "Detecting Glaucoma Using 3D Convolutional Neural Network of Raw SD-OCT Optic Nerve Scans". arXiv:1910.06302 [eess.IV].
{{cite arXiv}}
: CS1 maint: multiple names: authors list (link) - ^ Hegde, Vishakh; Zadeh, Reza (2016-07-19). "FusionNet: 3D Object Classification Using Multiple Data Representations". arXiv:1607.05695v4 [cs.CV].
- ^ Ramsundar, Bharath and Zadeh, Reza Bosagh (2018). TensorFlow for Deep Learning. Sebastopol, CA: O'Reilly. ISBN 9781491980446.
{{cite book}}
: CS1 maint: multiple names: authors list (link)