I Had a Choice the Other Day in Shanghai: Which Tomorrowland to Visit?

A Fascinating and Impressive but Ultimately Disturbing Experience

I had a recent opportunity to visit Huawei’s massive new research center in Shanghai, which is roughly the size of 225 football fields and is home to 104 individually designed buildings, with manicured lawns, connected by a Disney-like monorail, housing labs for up to 35,000 scientists, engineers, and other workers, offering 100 cafes, plus fitness centers and other perks designed to attract the best Chinese and foreign technologists.

Huawei’s Response to the U.S. Attempt to Choke It to Death

The Lianqiu Lake R. & D. campus is Huawei’s response to the U.S. attempt to choke it to death beginning in 2019 by restricting the export of U.S. technology, including semiconductors, to Huawei amid national security concerns. The ban inflicted massive losses on Huawei, but with the Chinese government’s help, the company sought to innovate its way around the ban.

A.I. Technology and Electric Vehicles

Huawei also went into the business of creating A.I. technology for everything from electric vehicles, self-driving cars, and even autonomous mining equipment that can replace human miners. Huawei officials said in 2024 alone it installed 100,000 fast chargers across China for its electric vehicles; by contrast, in 2021 the U.S. Congress allocated $7.5 billion toward a network of charging stations, but as of November this network had only 214 operational chargers across 12 states.

It’s Downright Scary to Watch this Close Up

President Trump is focused on what teams American transgender athletes can race on, and China is focused on transforming its factories with A.I. so it can outpace all our factories. Trump’s "Liberation Day" strategy is to double down on tariffs while gutting our national scientific institutions and workforce that spur U.S. innovation. China’s liberation strategy is to open more research campuses and double down on A.I.-driven innovation to be permanently liberated from Trump’s tariffs.

Beijing’s Message to America: We’re Not Afraid of You

Beijing’s message to America: We’re not afraid of you. You aren’t who you think you are — and we aren’t who you think we are.

A Strategy for the Future: Made in America by American Workers in Partnership with Chinese Capital and Technology

I prefer to express my patriotism by being brutally honest about our weaknesses and strengths, China’s weaknesses and strengths, and why I believe the best future for both of us — on the eve of the A.I. revolution — is a strategy called: Made in America by American workers in partnership with Chinese capital and technology.

Trump’s Magical Thinking

I agreed with Trump regarding his tariffs on China in his first term. China was keeping out certain U.S. products and services, and we needed to treat Beijing’s tariffs reciprocally. For instance, China dragged its feet for years on letting U.S. credit cards be used in China, waiting until its own payment platforms completely dominated the market and made it a cashless society, where virtually everyone pays for everything with mobile payment apps on their phones.

A Better Strategy for the Future

My problem is with Trump’s magical thinking that you just put up walls of protection around an industry (or our whole economy) and — presto! — in short order, U.S. factories will blossom and make those products in America at the same cost with no burden for U.S. consumers.

Conclusion

In conclusion, the article discusses the recent visit of the author to Huawei’s massive new research center in Shanghai, which is a testament to China’s rapid technological advancements and its ability to innovate its way around U.S. restrictions. The article also highlights the need for a new strategy for the future, one that combines the strengths of both the U.S. and China, and is based on mutual cooperation and benefit.

Frequently Asked Questions (FAQs)

Q: What is the purpose of Huawei’s massive new research center in Shanghai?
A: The purpose of Huawei’s massive new research center in Shanghai is to house up to 35,000 scientists, engineers, and other workers, offering 100 cafes, plus fitness centers and other perks designed to attract the best Chinese and foreign technologists.

Q: Why did Huawei build this research center?
A: Huawei built this research center as a response to the U.S. attempt to choke it to death beginning in 2019 by restricting the export of U.S. technology, including semiconductors, to Huawei amid national security concerns.

Q: What is the significance of Huawei’s A.I. technology?
A: Huawei’s A.I. technology is significant because it allows the company to transform its factories with A.I. so it can outpace all U.S. factories.

Q: What is the strategy for the future?
A: The strategy for the future is to combine the strengths of both the U.S. and China, and is based on mutual cooperation and benefit.

Q: Why is it important to have a new strategy for the future?
A: It is important to have a new strategy for the future because the current strategy is not working, and a new approach is needed to ensure the continued prosperity of both the U.S. and China.

Q: What is the author’s conclusion?
A: The author’s conclusion is that the best future for both the U.S. and China is a strategy called: Made in America by American workers in partnership with Chinese capital and technology.

Cimcorp, a provider of robotic handling solutions, has been selected by Grupo MAS, a family-owned food distribution business in Spain, to optimize fresh fruit distribution through automation.

Cimcorp will implement an advanced order-picking system at the Grupo MAS distribution center in Guillena, Sevilla, to ensure faster deliveries, improved employee support, and a more sustainable supply chain.

This strategic move reinforces Grupo MAS’ commitment to innovation, operational excellence and providing the freshest products to its customers.

With more than 50 years of experience in the food distribution sector, Grupo MAS operates a growing network of supermarkets, convenience markets, and cafes across Andalusia and Extremadura.

Facing challenges such as limited space, rising logistics costs, and increasing demand for efficiency, Grupo MAS sought a solution to optimize its logistics operations without compromising employee wellbeing.

Cimcorp’s proven automation technology stood out as the perfect fit, able to not only boost productivity but also support employees in their daily work.

Jose Manuel Martín Alba, director, logistics and transport, at Grupo MAS, says: “With Cimcorp’s solution, we can prepare goods in 24 hours, giving us the flexibility and agility to deliver to our more than 200 stores.

“The system will reduce manual handling, streamline operations and improve stock control, enabling our team to focus on higher-value tasks while enjoying a safer and more structured work environment.”

Notably, Cimcorp’s automation will support Grupo MAS’ commitment to sustainability, a key pillar of the company’s business strategy.

Grupo MAS runs a dedicated “Zero Waste” program that drives the implementation of sustainable solutions across all operations to reduce environmental impact.

Cimcorp’s robotic technology and intelligent software will ensure perishable goods move swiftly through the distribution process to significantly reduce food waste, minimize shrinkage, and deliver the freshest fruit to customers.

Martín Alba says: “This project aligns perfectly with our long-term goal of becoming a regional leader in distribution while upholding our commitment to sustainability.

“With Cimcorp’s technology, we can reduce our environmental impact by optimizing logistics, minimizing waste and supporting local farmers who supply fresh, seasonal produce to our stores.”

Beyond operational benefits, Grupo MAS’ automation initiative will directly enhance the customer experience. With a more efficient logistics network, Grupo MAS can ensure that fresh fruit is always available in stores before they open, with full product availability across all SKUs.

Martín Alba says: “Customers expect fresh products at all times, and this solution ensures we meet those expectations. By accelerating order fulfillment and improving accuracy, we can deliver the right products at the right time—every time.”

As Grupo MAS prepares for its ambitious growth agenda for 2026-2028 and beyond, investing in automation is a crucial step toward scalability. Cimcorp’s solution will enable the logistics team to adapt seamlessly to increasing sales volumes and evolving market demands.

Hannu Kailasvuo, director, business development at Cimcorp Group, says: “We are proud to support Grupo MAS in this transformation. Our automation technology is designed to simplify complexity, reduce costs and enhance operational efficiency.

“Innovation is in Cimcorp’s DNA, and this project is a testament to how forward-thinking companies like Grupo MAS are leveraging automation to drive long-term success. Together, we are shaping the future of fresh food distribution.”

New Study Raises Questions About OpenAI’s Data Use

AI Disclosures Project Investigates Large Language Model Training Data

A new study from the AI Disclosures Project has raised questions about the data OpenAI uses to train its large language models (LLMs). The research indicates that the GPT-4o model from OpenAI demonstrates a "strong recognition" of paywalled and copyrighted data from O’Reilly Media books.

The AI Disclosures Project

The AI Disclosures Project, led by technologist Tim O’Reilly and economist Ilan Strauss, aims to address the potentially harmful societal impacts of AI’s commercialization by advocating for improved corporate and technological transparency. The project’s working paper highlights the lack of disclosure in AI, drawing parallels with financial disclosure standards and their role in fostering robust securities markets.

Methodology and Key Findings

The study used a legally-obtained dataset of 34 copyrighted O’Reilly Media books to investigate whether LLMs from OpenAI were trained on copyrighted data without consent. The researchers applied the DE-COP membership inference attack method to determine if the models could differentiate between human-authored O’Reilly texts and paraphrased LLM versions.

The key findings from the report include:

• GPT-4o shows "strong recognition" of paywalled O’Reilly book content, with an AUROC score of 82%. In contrast, OpenAI’s earlier model, GPT-3.5 Turbo, does not show the same level of recognition (AUROC score just above 50%).
• GPT-4o exhibits stronger recognition of non-public O’Reilly book content compared to publicly accessible samples (82% vs 64% AUROC scores respectively).
• GPT-3.5 Turbo shows greater relative recognition of publicly accessible O’Reilly book samples than non-public ones (64% vs 54% AUROC scores).
• GPT-4o Mini, a smaller model, showed no knowledge of public or non-public O’Reilly Media content when tested (AUROC approximately 50%).

Implications and Conclusion

The researchers suggest that access violations may have occurred via the LibGen database, as all of the O’Reilly books tested were found there. They also acknowledge that newer LLMs have an improved ability to distinguish between human-authored and machine-generated language, which does not reduce the method’s ability to classify data.

The study highlights the potential for "temporal bias" in the results, due to language changes over time. To account for this, the researchers tested two models (GPT-4o and GPT-4o Mini) trained on data from the same period.

The report concludes that using 34 proprietary O’Reilly Media books, the study provides empirical evidence that OpenAI likely trained GPT-4o on non-public, copyrighted data.

FAQs

Q: What is the AI Disclosures Project?
A: The AI Disclosures Project is a initiative led by technologist Tim O’Reilly and economist Ilan Strauss that aims to address the potentially harmful societal impacts of AI’s commercialization by advocating for improved corporate and technological transparency.

Q: What is the purpose of the study?
A: The study aims to investigate whether LLMs from OpenAI were trained on copyrighted data without consent, and to provide empirical evidence on the use of non-public, copyrighted data in AI model training.

Q: What are the implications of the study’s findings?
A: The study’s findings suggest that access violations may have occurred via the LibGen database, and that newer LLMs have an improved ability to distinguish between human-authored and machine-generated language, which does not reduce the method’s ability to classify data. The study also highlights the potential for "temporal bias" in the results, due to language changes over time.