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AI Risks Include Data Poisoning and Model Corruption

Logistics Viewpoints

These are big data platforms that monitor news sources and assorted databases from governments, financial institutions, ESG NGOs, and other sources to detect when an adverse event has occurred or may be about to occur. Most argue that when the UI is trained with the companys own data, the risk of hallucination is small.

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Supplier Onboarding is Core to a Digital Supply Chain Transformation

Logistics Viewpoints

When you talk to companies that have implemented enterprise or supply chain applications, executives will usually admit that they have under-invested in training and preparing users to use the new technology. They sell to the automotive, data communications, medical, industrial, consumer electronics, and other industries.

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How AI and BI Empower Lawn, Pest, Cleaning and Security Industries to Harness Their Data for Success

WorkWave

For these companies, maintaining profitability while protecting their margins hinges on operational efficiency and the strategic use of data. Data is critical to managing every dimension of the business. Lets explore how AI and BI empower these industries, using specific examples to illustrate their transformative potential.

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The AI Wars: Battlefronts, Breakthroughs, and the New Era of the Industrial AI (R)Evolution

Logistics Viewpoints

Datacenter Hardware: The demand for powerful computing to train ever larger and more accurate AI models is insatiable. AWS has custom AI chips Trainium and Inferentia , for training and running large AI models. The battle here is to develop hardware that can handle this massive computational load efficiently and cost-effectively.

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Building AI to Unlearn Bias in Recruiting

Research shows that the hiring process is biased and unfair. While we have made progress to solve this, it’s potentially at risk due to advancements in AI technology. This eBook covers these issues & shows you how AI can ensure workplace diversity.

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Rise of the Industrial Data Scientist

Logistics Viewpoints

Enter the industrial data scientist, a new breed of data analyst with access to more industrial data than ever before and the advanced technology to translate that information into actionable intelligence. However, leveraging AI requires data science capability, which adds additional complexity to an already complex environment.

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From Warehouse to Delivery – How Digital Twins Drive Real-World Efficiency

Logistics Viewpoints

These are not static dashboards or simple visualizationstheyre living, data-rich models of real-world operations. Warehouse Optimization: Testing Without Touching The Carhartt Example: Carhartt adopted a digital twin strategy in partnership with IBM Turbonomic to model application performance and warehouse workflows.