We announced a range of IP to protect silicon from physical attacks, extending our portfolio of Arm security IP to bring physical security within reach of any IoT product.
This blog will focus on some of the key technologies needed to protect network access, availability and data, with a brief overview of Arm’s underlying platform that is providing the foundation for trust…
Service providers or anyone involved in building out next-generation networks are faced with complex challenges today as they seek to evolve, future-proof, and secure their networks to meet the ever-increasing…
Neural Network accelerators as an essential part of bringing ML to life on your device – and whilst it’s true that they have a significant role to play, they’re just one part of the story.
The sources of interest in the VORAGO Technologies HT-DAB-1 high temperature data acquisition evaluation and reference design kit has surprised me a bit.
Functional safety is a foundational pillar for Arm in designing our purpose-built IP for automotive, which requires us to take an end-to-end approach and design with the entire vehicle in mind.
We are launching Project Trillium to kickstart a new wave of invention in the world of artificial intelligence (AI), of which machine learning is a key part.
Securing embedded systems has become a critical task for developers. It is nearly impossible to turn on the news and not hear about yet another major security breach.
Synopsys is proud to have collaborated with Arm on the development of this new AMBA 5 AXI5 and ACE5 specification and also deliver the first source code test suite and Verification IP (VIP) for these new…
What would you do with a Cortex-M4, a neural network, some Lego and cable ties? Sebastian Förster built a small, four-legged robot and taught it to walk.
Nordic announces the nRF9160 System-in-Package (SiP) - the very first chip to implement the Arm Cortex-M33 processor (with TrustZone) and Arm CryptoCell-310.
We have invested in our online training platform, further developed online content and invested in a ‘Classroom training in the digital age’ training programme. Find out more in this blog
Artificial Intelligence is still in the early stages of adoption, but it is clear that Machine Learning will move to the edge of the network to enable new use cases and drive innovation.
CMSIS-NN is a library of neural network kernels that maximizes the performance & efficiency of DNNs on Cortex-M-based platforms for smart IoT edge devices.
It is possible to optimize neural network architectures to fit within the memory and compute constraints of microcontrollers without sacrificing accuracy.
The engineering wizardry that spawned the smart phone revolution—putting astonishing compute power, long battery life and wireless connectivity in the palms of our hands—is now transforming the PC market…