Vrajesh Bhavsar writes:
From smartphones and smart homes to drones and autonomous cars, AI and machine learning already play a crucial role in our daily lives … and much of this activity is running on Arm technology. As we continue to push the limits of the possible – and security, latency and cost become ever-more important – AI will increasingly happen on the devices around us. Our new developer site provides a one-stop repository, hosting resources, detailed product information and a shared knowledge base to help you to tackle ML at the edge, and find creative solutions to your challenges.
As we grow this space, we’d love your feedback on what you’d like to see here and how we can help you take computing further!
Resources from Arm and our ecosystem
Over the years, Arm has provided many software tools and libraries to support ML applications. These products work in sync with our hardware architecture to enhance the developer experience, from increasing performance to debugging issues. We’re continually updating these resources, to help developers leverage the breadth of our solutions and experience to tackle their challenges, and you’ll find the most relevant tools here on the developer site.
Whether it’s Linux solutions for servers or software modules for mobile solutions, we also work closely with our ecosystem to support the software stack and SDKs running on Arm devices. We’ve been working with ML frameworks to make sure they’re optimized and ready to address the breadth of our hardware products, so look out for some really useful resources here, too.
We’d like to invite new developers and partners to join our ecosystem and share their knowledge and ideas – and if you’re an existing partner and we’ve missed your solution here, we’d like to make sure that it’s highlighted, too. Please get in touch!
Tutorials and techniques
Sometimes, a new technology such as ML can seem daunting – especially if you’ve heard it’s only possible on huge, specialized platforms – but we’ll debunk the myths and show you how to get started with something as small as Raspberry Pi!
We’ll also look at the fundamentals of the computing problems around realizing ML applications on common devices, and consider ways of approaching them differently. We look forward to sharing ideas on innovative solutions for neural network models for low power systems, and new ways to think about topics such as privacy and security.
Looking ahead
This is just the beginning of an exciting new year for machine learning on Arm. We’re really looking forward to engaging with the community and giving you what you need most; we’re working on more developer platforms and a host of tutorials, as well as some interesting use cases that can solve the challenges you’re facing with your products today.
We’d really like to hear how this space can work best for you. Please join the community by signing up for our ecosystem partnership and leave us your comments and feedback.