One scorching day this past September, I made the dangerous decision to try to circumnavigate some data centers. The ones I chose sit between a regional airport and some farm fields in Goodyear, Arizona, half an hour's drive west of downtown Phoenix. When my Uber pulled up beside the unmarked buildings, the temperature was 97 degrees Fahrenheit. The air crackled with a latent energy, and some kind of pulsating sound was emanating from the electric wires above my head, or maybe from the buildings themselves. With no shelter from the blinding sunlight, I began to lose my sense of what was real. Microsoft announced its plans for this location, and two others not so far away, back in 2019--a week after the company revealed its initial 1 billion investment in OpenAI, the buzzy start-up that would later release ChatGPT.

Through decades of support, Microsoft was an instrumental force helping China become the AI powerhouse it is today. Now, as the very thought of a U.S. company partnering in tech projects in China draws scrutiny from lawmakers, national security hawks, and human rights advocates, Microsoft could be forced to grapple with tough decisions surrounding the thriving AI ecosystem it fostered there. Microsoft established its research lab in Beijing in 1998, when it was a pioneer paving the way for AI research and business collaborations between the U.S. and China. It was three years before China joined the World Trade Organization, a time when President Bill Clinton actively pushed for closer trade ties with the country, and when AI was mostly the stuff of sci-fi pipe dreams. Since then, Microsoft Research Asia, or MSRA, has been known as one of the most influential hubs of AI research in the world, advancing speech recognition, natural language and image processing, and other deep-learning work, spreading its discoveries far and wide. Elements of research conducted at MSR China have been used to build Microsoft's advertising, chatbots, Bing search, Windows, Xbox, Azure Cloud, and other products used everywhere.

Every sibling relationship has its clichés. In the Microsoft family of social-learning chatbots, the contrasts between Tay, the infamous, sex-crazed neo-Nazi, and her younger sister Zo, your teenage BFF with #friendgoals, are downright Shakespearean. When Microsoft released Tay on Twitter in 2016, an organized trolling effort took advantage of her social-learning abilities and immediately flooded the bot with alt-right slurs and slogans. Tay copied their messages and spewed them back out, forcing Microsoft to take her offline after only 16 hours and apologize. A few months after Tay's disastrous debut, Microsoft quietly released Zo, a second English-language chatbot available on Messenger, Kik, Skype, Twitter, and Groupme.

What finally broke me was the recipes. On July 1, I abandoned Google search and committed myself instead to Bing. I made it the default search mode in Chrome. Since then, for the most part, any time I've asked the internet a question, Bing has answered. But also an earnest attempt to figure out how the other half--or the other 6 percent overall, or 24 percent on desktop, or 33 percent in the US, depending on whose numbers you believe--finds their information online. The second-largest search engine by market share in the US, and one of the 50 most visited sites on the internet, according to Alexa rankings. I wanted to know how those people experienced the web, how much of a difference it makes when a different set of algorithms decides what knowledge you should see.

Microsoft today announced it has acquired Lobe, creator of a platform for building custom deep learning models using a visual interface that requires no code or technical understanding of AI. Lobe, a platform that can understand hand gestures, read handwriting, and hear music, will continue to develop as a standalone service, according to the company's website. Financial terms of the deal were not disclosed. People have only started to utilize the full potential of AI, Microsoft CTO Kevin Scott said today in a blog post announcing the acquisition. "This in large part is because AI development and building deep learning models are slow and complex processes even for experienced data scientists and developers. To date, many people have been at a disadvantage when it comes to accessing AI, and we're committed to changing that," he said.