ARTIFICIAL INTELLIGENCE AND AUTONOMOUS SYSTEMSLEGAL UPDATE (2Q19)

whitePaper | November 1, 2021

Robotics, automation, Internet of Things (IoT), and data are not new in manufacturing. Manufacturing is one of the most data-rich and first industries piloting artificial intelligence at the edge. It’s been estimated, however, that about 95% of all industrial data goes unused. The reason? Legacy equipment and operational systems that tend to be proprietary and siloed are incapable of communicating with each other.

whitePaper | November 1, 2019

Artificial Intelligence is becoming an ever more important part of our lives. Many of us are already familiar with its everyday applications, such as decluttering our inboxes with spam filters or receiving personalised shopping recommendations. Yet, whether it is powering a new generation of self-driving cars, guarding us against fraud or helping doctors better diagnose health conditions, AI’s transformational abilities are being felt in increasingly ubiquitous and innovative ways.

whitePaper | August 1, 2020

The majority of enterprise companies have hundreds of apps deployed in the cloud, and that trend is expected to continue, according to a new survey by IDG. That said, 52% of companies find that securing those apps continues to be challenging. But that doesn’t mean that the remaining 48% are fully confident in their cloud app security or are fully aware of all of the facets of cloud security they should be considering. “Cloud security is a broad issue,” says Jim Fulton, Director, Cloud & Edge Protection Solutions for Forcepoint. “From what I’ve seen, about 10% of companies really understand all of the facets.

whitePaper | January 20, 2022

Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there is an increasing interest in developing neural network (NN) solutions to deploy them on low-power edge devices such as the Arm Cortex-M microcontroller systems. To enable that, we present CMSIS-NN, an open-source library of optimized software kernels that maximize the NN performance on Cortex-M cores with minimal memory footprint overhead. We further present methods for NN architecture exploration, using image classification on CIFAR-10 dataset as an example, to develop models that fit on such constrained devices.

whitePaper | September 22, 2021

The value of conversational AI is clear—meaning it’s time to take the next step and begin setting specific goals if you want to see real returns on your investment. Access this beginner’s guide to conversational AI to learn important industry terms and explore the questions you need to be asking as you explore different solutions.

whitePaper | April 16, 2020

The Iron Triangle or, as it is more commonly known, the project management triangle has influenced project teams for years. Summed up as “fast, good, or cheap.pick two,” the concept asserts that there are firm boundaries on what is possible to produce. The triangle metaphor implies there is no way to provide goods or services that are simultaneously on budget, on time, and of high quality because of the competing nature of these priorities.