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tinyML a huge potential 

SynkaMicroCenter TinyML the AI alternative that exclusively uses extremely low-profile devices to process machine learning algorithms.

tiny machine learning (TinyML) has recently emerged as a promising field of AI. It pushes the intelligence to the edge and makes use of tiny devices such as microcontrollers to execute AI algorithms.

In the privacy aspect there is a growing interest from the AI community in leveraging a plethora of cryptographic techniques to secure data both in the training phase and the testing phase. However, by deploying TinyML where the source of data is created and since this data does not leave the device, privacy concerns are largely addressed

Why  tinyML+IoT

When there is a collective network between the collaborative ecosystems of AI and IoT, a very strong technology is created that has the ability to sense, interpret, control, activate, communicate and solve important challenges.

All of these sensors have one thing in common: they generate a large amount of data at the point where they are placed and this data is used in machine learning applications.

tinyML and IoT synergy 

Data collected by IoT devices needs to be analyzed to extract meaningful insights and create intelligent applications with ML models, but due to the extension of ML models, this can only be done on IoT units powered by tinyML.


A TinyML Framework’s goal is to provide a comprehensive solution for constructing and deploying machine learning models on low-power devices, making it easier for developers to create edge computing applications.

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