AI with MATLAB: from Embedded to LLMs

Large Language Models (LLMs) like ChatGPT have dominated technology conversations in recent years. With their exceptionally large footprint, they are a great example of cloud-deployed AI, which may be a part of a larger system. At the other end of the spectrum, AI models are increasingly entering devices around us through their small footprint embedded implementations. Speech interfaces in voice-enabled devices are a good example of systems spanning the whole embedded-to-cloud implementation spectrum, from audio pre-processing and wake-up phrase detection to spoken language understanding.

When it comes to AI-powered engineered systems, MATLAB can be used from creating the training data down to the final deployment. It is also adopted for building early prototypes that may include external hardware, embedded code, other programming languages like Python, cloud services, and custom App interfaces.

In this session, you’ll learn how to create a real-time prototype of a voice interface, complete with embeddable AI models built in MATLAB, deep networks developed with PyTorch, and the use of ChatGPT for language understanding. The session will also discuss other engineering workflows involving the use of LLMs with MATLAB.