In the latest issue of HackSpace magazine, out now, Ben Everard puts the new Raspberry Pi AI Kit through its paces.
In case you’ve missed the news, AI is poised to be the next big thing in tech. Actually, scratch that, it’s already the current big thing in tech. The only slight problem is that no one can quite agree what it is.While the latest headlines are being grabbed by large language models, including ChatGPT, which have a habit of lying to users and writing uncompilable code, AI models have been quietly working away in the background. They generate captions for our videos, help us take better photographs, help scientists identify things in photographs, improve quality control in factories, and generally help make our lives progress a little smoother. The neural networks underpinning these are running everywhere, from server rooms to the phones in our pockets.Neural networks have two stages – first, they must be trained. This is where you define the structure of the network, and run training data through it (typically large amounts of training data). While a lot depends on the particulars of the model you’re training, this usually takes a huge amount of computing power and is only done rarely. In fact, the majority of people using AI don’t train their own models. Instead, they use pretrained models that are available from a variety of sources (there’s a wide range of models for the Hailo-8L – the accelerator at the heart of the AI Kit – available here).Once you have a model, you can then run it – this is where you use it to analyse real-world data. Running a model takes a much more modest amount of computing power, and it’s this that the Raspberry Pi AI Kit is designed to do.