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SensiML Unveils Data Studio – Next-Generation Sensor Data Management for AI / ML

SensiML

SensiML™ Corporation, a leader in AI software for IoT and a subsidiary of QuickLogic, announced the launch of Data Studio, a ground-breaking platform designed to redefine the landscape of sensor data management. With a focus on practicality and efficiency, Data Studio empowers engineers and data scientists by offering an integrated solution that addresses the most time-consuming tasks in AI engineering projects – creating high-quality datasets for evaluating and developing ML models.

According to Cognilytica, a well-respected AI / ML consulting firm, approximately 80% of the total time for machine learning (ML) projects is allocated to data preparation.  These tasks include data identification, aggregation, cleansing, labeling, and augmentation – all of which are supported in SensiML’s collaborative development environment.

SensiML Data Studio significantly improves productivity and simplifies dataset management for anyone working on sensor data ML projects. With real-time connectivity, intuitive visualization tools, sensor data video synchronization, and robust support for large-scale collaborative projects, it offers a seamless experience for developers on edge devices, gateways, PCs, and cloud platforms.

Also Read: Rescale Announces Metadata Management for Seamless Data Collaboration and AI-assisted Product Development

A comprehensive overview of all the features of Data Studio can be found on the SensiML website. The primary features are highlighted below:

“SensiML Data Studio makes sensor data management and analysis more accessible and efficient, empowering developers to build better, more impactful applications using sensor data across a wide range of industries,” said Chris Knorowski, CTO of SensiML.

SensiML Data Studio is poised to transform sensor data analysis, offering a valuable resource for researchers, engineers, and data scientists across diverse sectors from agriculture and consumer wearables to medical devices, smart buildings, and factory maintenance.

SOURCE: PRNewswire

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