computer science

Matroid, Inc.

Matroid, Inc. is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Matroid, Inc. rather than just read about it. In short: 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.

Key takeaways

Matroid, Inc. belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Matroid, Inc. to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Matroid, Inc. from memory before moving on to harder problems.

Reference excerpt

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.

History 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.

Product Once a detector has been trained using the Matroid GUI, it automatically finds the objects of interest in real-time video and archived footage. 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.

Scaled Machine Learning Conference 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. Past speakers include Turing Award Winners, creators of Keras, TensorFlow, PyTorch, Caffe, OpenAI, Kubernetes, Horovod, Allen Institute for AI, Apache Spark, Apache Arrow, MLPerf, Matroid, and others.

Announcements 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. 2020 - Eagle Eye Networks and Matroid announce partnership to provide AI to Eagle Eye Cloud VMS customers. 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. 2018 - Oracle announced their software integration with Matroid to provide real-time and analytics based on people monitoring.

Awards 2019 - Matroid was selected by Gartner, Inc. as a “Cool Vendor” for Cool Vendors in AI Core Technologies. 2016 - Matroid was awarded a Best Paper Award at KDD 2016.

Notable publications

Diagnosing Glaucoma using 3D CNN Together with Stanford Hospital and hospitals in Hong Kong, India, and Nepal, Matroid used computer vision in the field of Ophthalmology. 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 FusionNet was released as a leading neural networks architecture at the Princeton ModelNet competition. 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 Matroid released a book with co-author Bharath Ramsundar, TensorFlow for Deep Learning. 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

Illustrations

Worked examples

Example 1 — a first encounter with Matroid, Inc.

Start with the simplest possible case. Write down what Matroid, Inc. claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Matroid, Inc. before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Matroid, Inc. ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Matroid, Inc.

In research: Matroid, Inc. appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Matroid, Inc. in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Matroid, Inc. is common in secondary-school and first-year university syllabi. It links to neighbouring topics Computer vision software, Software companies based in California, Software companies of the United States, so understanding it makes those chapters shorter.
In everyday life: Look for Matroid, Inc. outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Matroid, Inc. in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Matroid, Inc. means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Matroid, Inc. out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Matroid, Inc. in simple terms?

Why does Matroid, Inc. matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Matroid, Inc.?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Matroid, Inc..