OEMs undergoing digital transformation require legacy device support, robust security, tools for managing diverse systems, and the ability to scale. They need an edge-to-cloud Industrial IoT platform.
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Computer vision and AI are the foundations for groundbreaking applications. Healthcare providers, educators, retailers, cities, and more are using these technologies to aid response and recovery.
Wondering why you should attend Google Cloud Next? With nine weeks of (online) speakers, panels, and demos, there’s a ton to see and learn about the tech that powers Google's innovations. Read more.
IoT projects are complicated, so why not try a no-code approach? Find out how you can focus on data flows instead of programming.
What’s the best way to train AI models that accurately represent real-world conditions? You need to get out of the lab and an agile approach to identify and adjust to unexpected data sets. Read how.
The path to the Smart Factory requires suppliers to be more agile. Digital transformation is more than just building hardware. The good news is software development is becoming easier. Read how.
Manufacturers on the path to a smart factory need more than new technology. They need a partner with deep process knowledge, where digitalization can help, and the services to get there. Read more.
When creating an innovative, high-performance computer vision app, it’s hard to know your performance needs. Read how one HW platform lets you start big and go even bigger—no redesign required.
As IoT devices become interconnected, they are at big risk of cyberattacks. Read how embedded designers can use virtual platforms to catch security vulnerabilities and quickly fix the problems.
Computer vision can solve quality audit (QA) problems for complex, varied products. See how electronics can make it part of their industry 4.0 transformation.
Cisco Live is one of the best places to learn about the latest in IoT. And now it’s virtual so you can attend from anywhere in the world.
Can a recipe-like approach make it easier to develop industrial AI-enabled applications? When it comes to smart factory visual quality inspection applications, the answer is “definitely.” Read how.
Are you testing your proof of concept with realistic network conditions? If not, your IoT project is at risk. See how smarter simulators save the day.
What can manufacturers learn from race cars? How to use AI for machine monitoring. Join us for a wild ride that covers everything from edge inferencing to sensor fusion.
What if there were a shortcut to the smart factory? Read how a new approach helps industrial organizations develop, deploy, and test applications on preconfigured solutions.
Defect detection requires multiple types of computer vision with different compute requirements. That’s why a platform with flexible combinations of CPUs, GPUs, and AI accelerators is so valuable.
How can manufacturers upgrade to the latest industrial PCs with the least impact on daily operations? Three software options lead the way. Read on to find out how.
What’s holding back the smart factory? A lack of AI-ready infrastructure. Here’s how an enterprise AI platform solves the problem by uniting everything from machine sensors to ERP systems.
How can manufactures achieve their vision of lights-out manufacturing? To start, capabilities must be defined by software rather than hardware. Read how one company is making this a possibility.