AI: Driving the Industry Towards Greater Success

Angelika Teglasy
Ai robotics working on a car

Artificial intelligence (AI) is seen as a promising technology that can help leading OEMs to maintain their position as market leaders. In this post, read about how AI is changing the manufacturing sector, as well as its potential advantages and potential drawbacks.

  • 763

Artificial Intelligence (AI) has become an omnipresent force in the ever-evolving landscape of technology. From chatbots to self-driving cars, AI is rapidly changing the way we interact with the world. But it’s not just about convenience or automation; AI has the power to transform entire industries, drive innovation, and create new opportunities.

But why is there an urgency to embrace AI now more than ever? The answer is simple – the world is changing at an unprecedented speed, and leading OEMs need to constantly innovate in order to maintain their position as market leaders. The manufacturing sector is benefitting from AI-powered solutions to streamline operations, improve product performance, and find new revenue streams. But with so many AI technologies and platforms available, it may be hard to know where to start.

That’s where this article, published in Connected Technology Solutions, comes in. The author explores the benefits of AI, barriers to AI adoption, and how AI and robotics are transforming manufacturing.

Read the full article 

Featured products

All products mentioned in this blog post are developed by MathWorks.

Learn more

Recommended Events

Recommended Posts

MATLAB and Simulink for Automotive

MATLAB and Simulink for Automotive

Discover how MATLAB and Simulink drive automotive innovation. Learn how these tools expedite vehicle development and help OEMs meet evolving market demands.

Machine Learning with MATLAB

Explore how MATLAB transforms the world of machine learning. Discover 5 areas where MATLAB can help solve diverse learning problems. From interactive apps to Simulink integration, we’ve got you covered.

Excitation Signals for Identification of Dynamic Systems

Excitation Signals for Identification of Dynamic Systems

Learn about optimizing multisine signals for precise frequency-domain system identification. Discover the importance of low Crest Factor (CF) in excitation signals and explore techniques to enhance signal-to-noise ratios (SNR) for improved measurement accuracy.