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As the holidays approach, and I walk through our historic mill in Faribault, Minnesota, Im reminded of how much work mattersnot just for what it produces, but for what it represents. At Faribault Mill, we make artisanal wool and cotton blankets the old-fashioned way: spinning, weaving, and finishing under one roof, much as we have since the companys founding in 1865. We also design, market, sell, and ship those same products directly to consumers across the country. In a world where most companies outsource one step or another, we do it all. That makes us one of the few fully vertically integrated manufacturers left in America, and it gives us a unique perspective on the value of work, across every discipline and title. In our company, blue collar and white collar arent separate worlds; theyre on the same team. The loom operator depends on the marketing manager. The salesperson depends on the sewers to make what we promise. And the shipping team depends on both to ensure every order arrives on time. We succeed only when every link in that chain works together. Thats not just true in our millits true across America. Yet too often, our society talks about work in ways that divide instead of connect. We frame debates as worker versus employer, white collar versus blue, corporate versus labor, us versus them. But those are false choices. To be pro-worker you must also be pro-employer, and to be pro-business you must also be pro-employee. THE DIGNITY OF ALL WORK I spend a lot of time on our mill floor, and what I see there is something deeply American: people showing up, solving problems, learning trades, and taking pride in making something real. But I also see the same pride in our officesin the designers who obsess over every product detail, the digital marketers who bring our brand to life online, and the customer service team who answers the phone when someone calls to say theyre gifting a Faribault blanket to their new grandchild. All of it is work, all of it is valuable, and all of it deserves respect. A FULLY INTEGRATED AMERICAN BUSINESS At Faribault Mill, we dont just make products, we build relationships from start to finish. We source the fiber, spin it into yarn, weave it into fabric, finish it into blankets, and then sell it directly to customers in stores, online, and through retail partners. We photograph every product, write every description, and ship every order ourselvesoften from the same building where it was made. That level of integration means everyone at our company has a stake in the outcome. The weaver on the floor sees the final product featured in our marketing mailers. The marketing team understands the work that goes into running a loom. The warehouse team sees firsthand how a surge in holiday demand affects production. This connectedness creates a sense of shared purposethe belief that what we do matters not just to the business, but to one another. Its not always easy. There are late nights, tight deadlines, and tough decisions, but its real and its honest, and its exactly what American work should be. THE HOLIDAYS AND THE SPIRIT OF WORK During the holidays, our mill runs at full tilt. Orders spike, machines run longer, and the warehouse buzzes with activity. But for our team, this season isnt just about sales. Its about the satisfaction of knowing that tens of thousands of families will open a box on Christmas morning and find something made by hand, by people who care. Thats the magic of work when its done with purpose. Its also a reminder that behind every productwhether its a wool blanket, a meal in a restaurant, or a car rolling off the linethere are people who make it possible. Workers and managers; designers and operators; the seen and the unseen. THE PARTNERSHIP THAT POWERS PROGRESS Work in America has never been a solo act. The great advances in our history, from the Industrial Revolution to the digital age, have all come from teamwork and partnership. It is between inventors and operators, owners and workers, management and labor. The most sustainable companies arent those that treat workers as costs or management as adversaries. Theyre the ones who understand shared success. At Faribault Mill, we compete every day with global brands that make things cheaper overseas. We cant win on price alone, but we can win on quality, authenticity, and the strength of our team. That requires trust between every person in the company, from the spinning floor to the boardroom. We dont get everything right, but we try to model whats possible when a business honors both sides of the work equation. A CALL FOR RESPECT AND RENEWAL This holiday season, as we reflect on what unites us, I hope we can start to see work itself as sacred, not just a means to an end, but as the connective tissue of a healthy society. That means valuing people who make things just as much as those who market them. It means celebrating both the weaver and the web developer, the craftsman and the creative, the shop-floor supervisor and the CEO. The future of American enterprise depends on both. Ross Widmoyer is president and CEO of Faribault Mill.
Category:
E-Commerce
In the race to deploy large language models and generative AI across global markets, many companies assume that English model translate it is sufficient. But if youre an American executive preparing for expansion into Asia, Europe, the Middle East, or Africa, that assumption could be your biggest blind spot. In those regions, language isnt just a packaging detail: its culture, norms, values, and business logic all wrapped into one. If your AI doesnt code-switch, it wont just underperform; it may misinterpret, misalign, or mis-serve your new market. The multilingual and cultural gap in LLMs Most of the major models are still trained predominantly on English-language corpora, and that creates a double disadvantage when deployed in other languages. For example, a study found that non-English and morphologically complex languages often incur 35X more tokens (and hence cost and compute) per unit of text compared to English. Another research paper places around 1.5 billion people speaking low-resource languages at higher cost and worse performance when using mainstream English-centric models. The result: a model that works well for American users may stumble in India, the Gulf, or Southeast Asia, not because the business problem is harder, but because the system lacks the cultural-linguistic infrastructure to handle it. A regional example worth noting Take Mistral Saba, launched by French company Mistral AI as a 24B-parameter model tailored for Arabic and South Asian languages (Tamil, Malayalam, etc.) Mistral touts that Saba provides more accurate and relevant responses than models five times its size when used in those regions. But it also underperforms in English benchmarks. Thats the point: context matters more than volume. A model may be smaller but far smarter for its locale. For a U.S. company entering the MENA region (Middle East & North Africa) or the South-Asia market, that means your global AI strategy isnt global unless it respects local languages, idioms, regulation, and context. Token costs, language bias, and global ROI From a business perspective, the technical detail of tokenization matters. A recent article points out that inference costs for Chinese may be 2X English, while for languages like Shan or Burmese, token inflation can be 15X. That means if your model uses English-based encoding and you deploy in non-English markets, your usage cost skyrockets, or your quality drops because you cut back tokens. And because your training corpus was heavily English-centric, your underlying model may lack semantic depth in other languages. Add culture and normative differences into the mix: tone, references, business practices, cultural assumptions, etc., and you arrive at a very different competitive set: not were we accurate but were we relevant. Why it matters for executives expanding abroad If youre leading a U.S. corporation or scaling startup into international markets, here are three implications: Model selection isnt one-size-fits-all: you may need a regional model or a specialized fine-tuning layer, not just the largest English model you can license. Cost structure will vary by language and region: token inflation and encoding inefficiencies mean your unit cost in non-English markets will likely be higher, unless you plan for it. Brand risk and user experience are cultural: A chatbot that misunderstands basic local context (e.g., religious calendar, locale idioms, regulatory norms) will erode trust faster than a slower response. How to build a culturally aware multilingual AI strategy For executives ready to sell, serve, and operate in global markets, here are practical steps: Map languages and markets as first-class features. Before you pick your largest model, list your markets, languages, local norms, and business priorities. If Arabic, Hindi, Malay, or Thai matter, treat them not as translations but as first-class us-cases. Consider regional models or joint-deployment. A model like Mistral Saba may handle Arabic content more cheaply, more accurately, and more natively than a generic English model fine-tuned. Plan for token-cost inflation. Use pricing comparison tools. A model may have a U.S. cost of $X per 1 M tokens, but if your deployment is Turkish or Thai, the effective cost may be 2X or more. Fine-tune not just for language, but for culture and business logic. Local datasets shouldnt just include language, they should capture regional context: regulations, business customs, idioms, risk frameworks. Design for active switching and evaluation. Dont assume your global model will behave locally. Deploy pilot tests, evaluate on local benchmarks, test user-acceptance, and include local governance in your rollout. The bigger ethical and strategic lens When AI models privilege English and Anglophone norms, we risk reinforcing cultural hegemony. The technical inefficiencies (token cost, performance gap) are symptoms of a deeper bias: which voices, languages, economies are considered core versus edge. As executives, its tempting to think well translate later. But translation alone fails to address token inflation, semantic mismatch, cultural irrelevance. The real challenge is making AI locally grounded and globally scaled. If youre betting on generative AI to power your expansion into new markets, dont treat language as a footnote. Language is infrastructure. Cultural fluency is a competitive advantage. Token costs and performance disparities are not just technical: they are strategic. In the AI world, English was the path of least resistance. But your next growth frontier? It might require language, culture, and cost structures that act more like differentiators than obstacles. Choose your model, languages, rollout strategy not on the size of the parameter count, but on how well it understands your market. If you dont, you wont just fall behind in performance: youll fall behind in credibility and relevance.
Category:
E-Commerce
The city of San Francisco filed a lawsuit against some of the nation’s top food manufacturers on Tuesday, arguing that ultraprocessed food from the likes of Coca-Cola and Nestle are responsible for a public health crisis.City Attorney David Chiu named 10 companies in the lawsuit, including the makers of such popular foods as Oreo cookies, Sour Patch Kids, Kit Kat, Cheerios and Lunchables. The lawsuit argues that ultraprocessed foods are linked to diseases such as Type 2 diabetes, fatty liver disease and cancer.“They took food and made it unrecognizable and harmful to the human body,” Chiu said in a news release. “These companies engineered a public health crisis, they profited handsomely, and now they need to take responsibility for the harm they have caused.”Ultraprocessed foods include candy, chips, processed meats, sodas, energy drinks, breakfast cereals and other foods that are designed to “stimulate cravings and encourage overconsumption,” Chiu’s office said in the release. Such foods are “formulations of often chemically manipulated cheap ingredients with little if any whole food added,” Chiu wrote in the lawsuit.The other companies named in the lawsuit are PepsiCo; Kraft Heinz Company; Post Holdings; Mondelez International; General Mills; Kellogg; Mars Incorporated; and ConAgra Brands.None of the companies named in the suit immediately responded to emailed requests for comment.U.S. Health Secretary Robert F. Kennedy Jr. has been vocal about the negative impact of ultraprocessed foods and their links to chronic disease and has targeted them in his Make America Healthy Again campaign. Kennedy has pushed to ban such foods from the Supplemental Nutrition Assistance Program for low-income families.An August report by the U.S. Centers for Disease Control and Prevention found that most Americans get more than half their calories from ultraprocessed foods.In October, California Gov. Gavin Newsom signed a first-in-the-nation law to phase out certain ultraprocessed foods from school meals over the next decade.San Francisco’s lawsuit cites several scientific studies on the negative impact of ultraprocessed foods on human health.“Mounting research now links these products to serious diseasesincluding Type 2 diabetes, fatty liver disease, heart disease, colorectal cancer, and even depression at younger ages,” University of California, San Francisco, professor Kim Newell-Green said in the news release.The lawsuit argues that by producing and promoting ultraprocessed foods, the companies violate California’s Unfair Competition Law and public nuisance statute. It seeks a court order preventing the companies from “deceptive marketing” and requiring them to take actions such as consumer education on the health risks of ultraprocessed foods and limiting advertising and marketing of ultraprocessed foods to children.It also asks for financial penalties to help local governments with health care costs caused by the consumption of ultraprocessed foods. Jaimie Ding, Associated Press
Category:
E-Commerce
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