Unlocking Value from Artificial Intelligence in Manufacturing

whitePaper | July 29, 2022

China is following a national strategy to lead the world in artificial intelligence by 2030, including by pursuing “general AI” that can act autonomously in novel circumstances. Open-source research identifies 30 Chinese institutions engaged in one or more of this project‘s aspects, including machine learning, brain-inspired AI, and brain-computer interfaces. This report previews a CSET pilot program that will track China’s progress and provide timely alerts.

whitePaper | April 16, 2020

In construction, we are often designing and constructing made-to-order assets, so there is immediately less certainty. We may be dealing with multiple projects for different people, with different schedules, and run by different project managers. Each will be in a different location, with different site footprints, different ground conditions, different access routes, etc. And, partly influenced by their locations, we are often dealing with different suppliers we might select local designers, subcontractors, plant, materials, and product suppliers based on their proximity to the site.

whitePaper | August 6, 2020

The purpose of any data acquisition system is to gather useful measurement data for characterization, monitoring, or control. The specific parameters of your application will dictate the resolution, accuracy, channel count, and speed requirements of a data acquisition system. A wide assortment of data acquisition components and solutions is available on the market, including low-cost USB modules, benchtop data loggers, and large channel systems. Before you start your search for a data acquisition solution, carefully analyze your application requirements to understand how much capability and performance you need to purchase.

whitePaper | December 26, 2022

IBM embraces five foundational pillars of trustworthy AI: Explainability, Fairness, Robustness, Transparency, and Privacy. These pillars underpin the development, deployment and use of AI systems. This document and IBM’s trustworthy AI pillars are meant to help you align on both process and outcomes.

whitePaper | September 15, 2022

The concept of Artificial Intelligence (AI) and Machine Learning (ML) dates back to the 1950s with researchers trying to use machines to simulate human intelligence in machines. However, their use in the financial sector has been limited. With enhanced customer service and mounting cost pressures, financial institutions (FIs) have now started to look at AI as a possible solution for improving cost and operational efficiencies.

whitePaper | December 23, 2022

The transformative potential of artificial intelligence (AI) is a kind of truism. Seeking to capture the benefits of the “Fourth Industrial Revolution” or “third wave of the digital revolution,” countries are prioritizing efforts to reorganize their public and private sectors, fund research and development (R&D), and establish structures and policies that unleash AI innovation.