Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making
Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
Explore the rise of intelligent EV hardware and how real-time processing, ML acceleration, and hardware virtualization are enabling safer, smarter, software-defined electric vehicles.
Training AI models is costly, forcing a trade-off between compressing large models or accepting weaker performance from smaller ones trained from scratch.
Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
In this episode, we talk about how Toyota and Stanford are collaborating to utilize AI for drifting controls and the efforts behind a team at TUM which has resulted in an autonomous race car performing at the capacity of an amateur F1 driver.
Article #5 Altair Startup Series. How startups can accelerate growth and effectively use artificial intelligence for quality assurance, data analytics, and other critical engineering tasks.
Deep-learning algorithms are enabling powerful video analytics. A practical use in manufacturing is monitoring human actions in manual operations. Some assemblies require specific torquing sequences, which can't always be tracked with traditional methods. AI-based Computer Vision advances quality management.
Artificial intelligence (AI) is showing significant promise in medical imaging. To translate this promise to reality requires rigorous evaluation of these algorithms.
Developing a tool that evaluates button and switch devices from both hardware (through physical input) and software perspectives is the next logical step in the evolution of device testing automation.
For now, at least, machines need humans as much as humans need machines. At this intersection, machine learning (ML) offers intriguing possibilities for managing the billions of end devices that comprise the IoT. ML is a practical, mathematical field.
UTEP 2022 ends with 12 submissions in the final month. The recent articles covered different areas of technology like smart farming, AI, 3D printing, wind energy, structural engineering, biotechnology, and more. As we eagerly wait for the results, here is an article summarizing the new submissions.
In a highly competitive environment, retailers are leveraging cutting-edge technologies to boost efficiency and run their businesses more effectively. AI-powered robots are transforming the retail sector by optimizing pricing strategies, inventory management, and more.
Before the pandemic, research suggested that adoption of AI (artificial intelligence) and ML (machine learning) in business was increasing at a rate of about 25% per year.