We are proud to announce the successful completion of our ambitious AI + IoT Research and Development project at Scramjet. This project marks a major milestone in our journey, showcasing the capabilities of the Scramjet Transform Hub and Scramjet Cloud Platform, and showing new capabilities of cloud and edge computing.
Our platform now simplifies the collection and transformation of data from IoT devices. This feature means you can gather critical information effortlessly, making your IoT ecosystem smarter and more responsive.
Scramjet Cloud Platform brings you the convenience of managing all your IoT devices from a single point. Whether they’re scattered across various locations or nested in one, control and oversight have never been this streamlined.
You no longer have to do manual, location-bound deployments. With our technology, you can deploy programs automatically to any device, from the smallest microcontroller to powerful servers equipped with GPUs. This flexibility is a game-changer in the realm of program deployment and execution. We mean it, you can fire up Scramjet without issues on something as small as Raspberry Pico.
Our platform enables uninterrupted data streaming between your programs, irrespective of their physical location. This feature ensures a consistent flow of information, vital for real-time decision-making and process automation.
One of the most important aspects of our project is the ability to train Machine Learning models continuously with streamed data. This eliminates the complicated process of downloading datasets. We’re hoping to streamline the pathway to smarter, AI-driven solutions.
Experience a new level of interaction with your deployed ML models. Reduced latency in data streaming, for both program input and output API endpoints, ensures faster, more efficient model interactions.
For a deeper dive into what we’ve accomplished, please visit our ML and Pico development repositories on GitHub. There, you’ll find practical examples that demonstrate deploying programs on microcontrollers, leveraging data streaming for ML model training and inference, and orchestrating devices in varied environments to create a comprehensive AI + IoT ecosystem.
Our examples include training a Speech-to-Intent model using data streaming and collecting audio data from a microcontroller with a microphone. You'll see how to send this data seamlessly to an AI model and receive classification results on the microcontroller to trigger actions, such as switching on or off a light sensor.
Stay tuned for our upcoming tutorials on AI + IoT. We are on a mission to make these advanced technologies accessible and user-friendly, and we can't wait to share more about our journey with you!
At Scramjet, we’re not just building platforms; we’re eagerly building the future of AI + IoT integration. Join us on this exciting journey!
Register now for your free trial HERE.