AI is changing the game. Whether you're working on systems that act intelligently in a specific domain (narrow AI), or in general (strong AI). Designing those systems is no easy task. Explore our resources to stay up to date in the world of AI trends, technology, and technical expertise.
With the growing demand for personalised healthcare, remote monitoring, and advanced diagnostic tools, innovative electronics are paving the way for safer, smarter, and more efficient medical devices.
This article looks at how these modules have evolved from development tools, for teaching and prototyping, to enterprise-quality components that can simplify your product development while meeting industrial standards.
Machine vision is enabling many existing and emerging markets. Security, manufacturing and industrial automation all use machine vision. Adding artificial intelligence (AI) inferencing at the sensor provides many benefits. Industrial automation combines ...
Artificial intelligence has the potential to influence every part of any company. As a trusted partner and leader in technology, Avnet has a responsibility to its customers and suppliers to consider the impact of AI from all angles.
Intelligence comes in many forms. More of us are interacting with devices that appear to understand us. What and how they understand depends on the technology inside. How are embedded engineers implementing intelligence?
Artificial neural networks are complex, multi-layered and multi-dimensional arrays of interconnected numerical values. Executing the math behind those connections is at the heart of AI. This math is unlike any other in the digital domain.
Continuous passive motion (CPM) is now a critical part of patient rehabilitation. New technologies, including artificial intelligence, are helping medical OEMs take the next step to optimize patient therapy.
AI is impacting the performance, security and maintenance of 5G networks. Network operators are racing to reap the benefits. AI promises to deliver returns on network investment and improve the end-customer experience along the way.
With the number of connected nodes that make up the Internet of Things (IoT) growing on a daily basis, it is universally accepted that the way in which machine learning (ML) inferencing is executed has to change.
Smart homes and factories, smart clothing (socalled “wearables”), autonomous cars, trucks and drones and other stuff from the world of science fiction.
Artificial Intelligence (AI) will become so commonplace it will be taken for granted. We can say this with some confidence, because so many semiconductor manufacturers already have embedded processors that are designed for AI.
Rapidly growing interest in the use of artificial intelligence (AI) in space exploration and commercialisation is being fuelled by the promise that it can improve the robustness and cut the cost of missions.
Putting more real-time intelligence at the heart of industrial automation is creating a new breed of control technology. Connectivity and control must go hand in hand in the Industrial IoT, but it requires the best of both worlds.
AI may be the headline act, but a greater impact on manufacturing will come from the trends enabled by AI. OEMs can expect to feel the impact in three areas.
Machine vision (MV) and artificial intelligence (AI) provide valuable inspection and analysis capabilities to a wide range of leading-edge applications. As with all advanced technologies, there are pitfalls to avoid.
Field programmable gate arrays (FPGAs) deliver many advantages to artificial intelligence (AI) applications. How do graphics processing units (GPUs) and traditional central processing units (CPUs) compare?