Model poisoning, where training data is manipulated to introduce vulnerabilities or biases, is a significant threat. Here are some strategies to mitigate it. By following these best practices and ...
Supply chains, once governed by fixed rules and human planning, are becoming AI-driven systems that learn, adapt, and ...
In recent years, the words “supply chain issues” have emerged as a familiar explanation for the inability of families and businesses in the United States and elsewhere to access certain goods, from ...
LLM and AI are buzzwords, but over the last several months we’ve seen examples of LLM-powered chatbots really go off the rails. So, executives are becoming cautious about the future of AI. I argue ...
The global supply chain is undergoing a fundamental shift, driven by the urgent need for resilience and responsiveness. Traditional models are no longer enough in the face of frequent disruptions, ...
As 2025 comes to an end, where do we stand with AI in the supply chain? What is real? What is hype? Machine learning has been a part of advanced demand forecasting for over 20 years. But these ...
For decades, global commodity supply chains have operated in a largely analog way. Metals are extracted from the ground, sold through layers of intermediaries, shipped across continents, and ...
Supply chains have typically been quiet enablers, optimized for cost, consistency, and scale. But in today’s volatile world, supply chains must no longer be designed solely for efficiency; they must ...
Supply chain leaders increasingly rely on data science to navigate disruptions, optimize operations and drive decisions. Yet data, like crude oil, holds no value unless refined into usable insights.
Your biggest risk may be a vendor you trust. How can SMBs map their third-party blind spots and build operational resilience?
Air route diversions and constrained regional access are eroding schedule certainty for temperature-controlled air freight, while fuel-price shocks and carrier capacity limits inflate end-to-end ...