Originally published at: Announcing Golioth for AI - Golioth
Today, we are thrilled to announce the launch of Golioth for AI, a comprehensive set of features designed to simplify and enhance the integration of AI into IoT products. At Golioth, we envision a future where AI and IoT converge to create smarter, more efficient systems that can learn, adapt, and improve over time. The fusion of AI and IoT has the potential to unlock unprecedented levels of innovation and automation across various industries. However, integrating AI into IoT devices can be complex and challenging, requiring robust solutions for managing models, training data, and performing inference. Today, at Golioth, we are addressing these challenges head-on. Our new set of features focuses on three core pillars: training data, model management, and inference. By streamlining these processes, we aim to empower developers and businesses to quickly add AI to their IoT projects, where it was not readily possible to do so before. Training Data: Unlocking the Potential of IoT Data At Golioth, we recognize that IoT devices generate rich, valuable data that can be used to train innovative AI models. However, this data is often inaccessible, in the wrong format, or difficult to stream to the cloud. We’re committed to helping teams extract this data and route it to the right destinations for training AI models that solve important physical world problems. We’ve been building up to this with our launch of Pipelines, and new destinations and transformers have been added every week since. Learn more about Pipelines in our earlier announcement. In v0.14.0 of our Firmware SDK, we added support for block-wise uploads. This new capability allows for streaming larger payloads, such as high-resolution images and audio, to the cloud. This…
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