The clock is ticking. Our planet is heating up, and with every passing day the stakes rise. Wildfires, floods, and storms are no longer distant headlines; they’re unfolding right on our doorstep. Humanity stands at a crucial turning point.

Time: We all have a sense of it, an innate feel for it. We see it and use it every day.

Large language models can do impressive things, like write poetry or generate viable computer programs, even though these models are trained to predict words that come next in a piece of text.

In the process of aerosol filling, precision and safety are crucial, given the complex nature of handling pressurized products and ensuring quality control at every stage. Traditionally, robots have been employed to automate several parts of production.

In today’s market, it seems like all 3D scanners have similar specifications, as if manufacturers look at their competitors’ data and use the same numbers.

In the highly regulated world of life sciences, data integrity isn’t optional; it’s essential.

As dairies scramble to meet sustainability targets ahead of the first year of responding to the European Union Corporate Sustainability Reporting Directive, the significant losses in push-out processes have been identified as low-hanging fruit by many companies.

In the 1960s cartoon series The Jetsons, Rosie the robotic maid seamlessly switches from vacuuming the house to cooking dinner to taking out the trash. But in real life, training a general-purpose robot remains a major challenge.

Despite their impressive capabilities, large language models (LLMs) are far from perfect. These artificial intelligence models sometimes “hallucinate” by generating incorrect or unsupported information in response to a query.

For an organization to develop a sustainable, continuous improvement culture, it must, as we say at Greater Boston Manufacturing Partnership, involve everybody, every day—i.e., process improvement mus