BrainChip has collaborated with Edge Impulse to address the growing demand for large-scale edge AI deployment. The agenda behind this collaboration is to strengthen the training of AI workloads and inference deployment of computer vision and natural language processing models on the edge network.
Now, customers will be able to make integrated hardware and software solutions, which will help accelerate the adoption of ML at the edge.
The collaboration aims to deliver platforms to customers looking to develop products that utilize the companies’ ML capabilities, partners said in a statement.
This announcement will help enterprise edge-computing deployment at scale gain traction in a wide range of industries, including health care, automotive, and military and aerospace. Resource-constrained edge devices introduce increased complexity in data processing at the edge network, which will be an important challenge to address. BrainChip and Edge Impulse will help developers and engineers achieve broader adoption in potential edge-computing use cases.
More and more companies are understanding the benefits of deploying ML and AI technologies at the edge, i.e., closer to the physical location where sensor data is collected. This has led to a rise in demand for products that enable such computing, and more and more companies harness Moore’s Law to develop processors that are small enough to be located at the edge, in conjunction with sensors. A technology with great implications in edge computing is neuromorphic chips, i.e., chips that contain circuits that mimic the brain.