NanoEdge AI StudioWe cracked the code for:
Simple, fast and affordable Edge AI
160 billion machines just want to do a better job!
The current approach of AI is not relevant to objects. Lack of qualified data to train models, difficulties to find and attract data scientists, dependence on cloud architectures, significant budgets: That’s why most projects in this space never go further than a Proof of Concept.
Get NanoEdge AI Studio today and give your embedded developers what they need to quickly turns your products into smart objects.
What is
NanoEdge AI Studio ?
NanoEdge™ AI Studio is a software solution running on Windows 10 or Linux Ubuntu, developed by Cartesiam.
If you want to learn, infer, and predict at the Edge, directly inside the microcontroller, you are at the right place.
NanoEdge™ AI Studio will easily let you create a machine learning static library to embed in your main program running on any ARM© Cortex© M microcontroller.
When embedded in microcontrollers, it gives them the ability to locally “learn” and “understand” sensor patterns, by themselves, without the need for the user to have additional skills in Mathematics, Machine Learning, Data science, or creation of pre-trained neural network. In 4 steps, NanoEdge™ AI Studio will let you generate a static library that contains an AI model designed to gather knowledge incrementally during a learning phase to able to detect potential anomalous machine behaviors and predict them.
To help you test your machine learning library, NanoEdge™ AI Studio comes fully loaded with NanoEdge AI Emulator (Windows and Linux)
You will be able to emulate the behavior of your NanoEdge AI Library and start testing it as if it was running in your embedded application. No need to flash your code in your microcontroller, simply test your library on your PC either from the command line, or the interface provided through NEAI Studio.
The NanoEdge AI Emulator comes with each library created by NanoEdge™ AI Studio.
The emulator is compiled using the same algorithm. This means that for one library, there is one emulator.
Using this tool, you can learn and detect as you would do in your embedded application.
Learn using the nominal signals used in the Studio, or any other dataset you consider as “nominal.”
Detect using the abnormal signals used in the Studio, or any other dataset you consider as “abnormal.”
It is as simple as that.
AI at the Edge
Why Cartesiam ?
Think out of the box
Unlike the traditional approach consisting in creating a static knowledge model on the server-side using labeled data and an AI Framework such as TensorFlow or others, Cartesiam’s approach is to allow the knowledge creation through dynamic learning, directly on the equipment.
The NanoEdge AI Library generated with NanoEdge AI Studio will be in charge of creating this knowledge model directly in the microcontroller and will be customized for each device.
This allows us to answer the two main challenges that slow down the deployment of AI projects in the industry, namely: The lack of qualified data to train your model and the lack of data scientists to create the knowledge models using AI frameworks.
Data scientists new best friend
We all know how painful it is to capture and label data in preparation of model creation.
Server-side Machine Learning projects heavily depend on a large volume of high quality labeled data. Without sufficient data, it is impossible for an “AI” to learn, and if the situation encountered does not match learned data, it simply won’t work. Gathering data is a challenge but nothing compared to classifying and labeling them, to reflect a realistic vision of the phenomenon you want to learn. It takes a lot of time, cost and requires heavily skilled data scientists. Another important feature in Cartesiam’s approach is to help Datascientist capture only relevant data using NanoEdge AI Library to sort through the data and log only the relevant one to create a static knowledge.
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NanoEdge™ AI studio
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