Welcome to the Association for Advancing Automation’s AI Update newsletter. Edited byRobert Huschka, A3’s vice president of education strategies, this newsletter will provide you and your business with the latest news, trends, stats and use cases on artificial intelligence in automation. We hope you enjoy it. If not, you can alwaysunsubscribe. Tell your colleagues to subscribehere.
When it comes to machine learning (ML) projects, it’s easy to get caught up in algorithms and model building. After all, the whole point of an ML project is to develop a model that can operate on new data to answer questions, uncover insights, increase safety, and reduce human error. A model is only as good as the datasets it uses, however. In fact, data preparation is arguably the most important step in the process. This particularly holds for supervised ML, which depends on labeled datasets to train a model to make decisions autonomously (or semi-autonomously).
As AI becomes more powerful, robots and other machines can quickly learn what they need to do to perform given tasks without expensive and difficult-to-find AI experts. Read more to learn what Max Versace, CEO at Neurala, has to say on how AI is benefitting the manufacturing industry.
The manufacturing labor shortage has paved the way for widespread deployment of some very exciting innovations in Artificial Intelligence for manufacturing. So potent are these developments that McKinskey predicts they will create some $3.7 trillion in value by 2025.
Largest grant ever awarded to a Georgia Tech-led coalition of partners to drive Build Back Better initiatives. The grant will increase job and wage opportunities in distressed and rural communities, as well as among historically underrepresented and underserved groups.
Given the complexity of manufacturing operations, one of the biggest challenges is enabling a free flow of information throughout the operational process while simultaneously protecting rights to valuable data and AI-related intellectual property (IP).
As companies increase the use of automation technologies in their factories, warehouses, and other locations, they recognize the need for artificial intelligence technologies (such as machine vision to inspect for defects) that can guide decisions in real time.
Employees hired to keep quality control processes in check can make mistakes; thus, such factories also rely on software to evaluate their experiences, change parameters if needed, and ensure that the [product] reaches the end-of-line as high quality as possible.
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The International Robot Safety Conference (IRSC) will offer conference sessions and workshops that examine key issues in robot safety and provide an in-depth overview of current industry standards and best-practices.
This packed, one-day AI & Smart Automation Conference will help start your journey to unlock the power of AI by featuring discussions on data strategy, advances in AI robotics and machine vision, and AI-powered optimization and prediction.
Join us for Autonomous Mobile Robots & Logistics Week, where you’ll learn about the exciting advances in AMR technology, plus new developments in logistics automation.