Stagnant productivity, a tightening workforce, and rising global competition are reprioritizing manufacturing in the U.S. What’s needed: new production models.
Organizations see success by starting with smaller AI transformations. Aiming for incremental value builds a foundation for sustainable results.
Experts in artificial intelligence from MIT Sloan are keeping an eye on the human-LLM accuracy gap, AI guardrails, and other trends.
AI systems built or run with limited resources could soon perform on par with leading larger models while costing much less, according to new research.
Supply chain guru Yossi Sheffi identifies post-COVID-19 trends, including blockchain, robotic process automation, IoT, dark stores, and “China plus one.”
During a visit to MIT, Jon Moeller talked about sustainability, technology and marketing trends, and how P&G reduced its product portfolio in order to grow.
Experts detail how ripple effects are impeding the flow of goods, creating catastrophic food shortages, and fueling dramatic cost increases and product shortages.
Indirect emissions that occur along a company’s value chain account for 75% of the organization’s overall emissions, on average. They remain difficult to track.
When stakeholders become more involved in generative AI design and implementation, it’s more likely that such tools will augment work rather than displace workers.
To succeed with generative artificial intelligence and extended reality, companies should also harness human creativity, curiosity, and compassion.
