The Pew survey results suggest that ChatGPT, at least for now, has not become the disruptive phenomenon in schools that proponents and critics forecast. Among the subset of teens who said they had heard about the chatbot, the vast majority -- 81 percent -- said they had not used it to help with their schoolwork. "Most teens do have some level of awareness of ChatGPT," said Jeffrey Gottfried, an associate director of research at Pew. "But this is not a majority of teens who are incorporating it into their schoolwork quite yet." Cheating has long been rampant in schools. In surveys of more than 70,000 high school students between 2002 and 2015, 64 percent said they had cheated on a test.

Microsoft on Tuesday reported strong sales in its latest quarter, showing that its corporate customers have been shaking off jitters about spending heavily in the uncertain economy. The results also showed early signs that the company's investments in generative artificial intelligence were beginning to bolster sales, most notably reversing what had been slowing growth of the company's important cloud computing product. The company had $56.5 billion in sales in the three months that ended in September, up 13 percent from a year earlier. Profit hit $22.3 billion, up 27 percent. The results beat analyst expectations and Microsoft's own estimates.

The widely used chatbot ChatGPT was designed to generate digital text, everything from poetry to term papers to computer programs. But when a team of artificial intelligence researchers at the computer chip company Nvidia got their hands on the chatbot's underlying technology, they realized it could do a lot more. Within weeks, they taught it to play Minecraft, one of the world's most popular video games. Inside Minecraft's digital universe, it learned to swim, gather plants, hunt pigs, mine gold and build houses. "It can go into the Minecraft world and explore by itself and collect materials by itself and get better and better at all kinds of skills," said a Nvidia senior research scientist, Linxi Fan, who is known as Jim.

Artificial intelligence is transforming many aspects of the practice of medicine, and some medical professionals are using these tools to help them with diagnosis. Doctors at Beth Israel Deaconess, a teaching hospital affiliated with Harvard Medical School, decided to explore how chatbots could be used -- and misused -- in training future doctors. Instructors like Dr. Rodman hope that medical students can turn to GPT-4 and other chatbots for something similar to what doctors call a curbside consult -- when they pull a colleague aside and ask for an opinion about a difficult case. The idea is to use a chatbot in the same way that doctors turn to each other for suggestions and insights. For more than a century, doctors have been portrayed like detectives who gather clues and use them to find the culprit.

For decades, Silicon Valley anticipated the moment when a new technology would come along and change everything. It would unite human and machine, probably for the better but possibly for the worse, and split history into before and after. It could happen in several ways. One possibility is that people would add a computer's processing power to their own innate intelligence, becoming supercharged versions of themselves. Or maybe computers would grow so complex that they could truly think, creating a global brain.

Let's start at the beginning. The term "artificial intelligence" gets tossed around a lot to describe robots, self-driving cars, facial recognition technology and almost anything else that seems vaguely futuristic. A group of academics coined the term in the late 1950s as they set out to build a machine that could do anything the human brain could do -- skills like reasoning, problem-solving, learning new tasks and communicating using natural language. Progress was relatively slow until around 2012, when a single idea shifted the entire field. It was called a neural network.

The Bing chatbot is powered by a kind of artificial intelligence called a neural network. That may sound like a computerized brain, but the term is misleading. A neural network is just a mathematical system that learns skills by analyzing vast amounts of digital data. As a neural network examines thousands of cat photos, for instance, it can learn to recognize a cat. Most people use neural networks every day. It's the technology that identifies people, pets and other objects in images posted to internet services like Google Photos.

As Tesla faces a federal investigation and lawsuits over fatal accidents involving its Autopilot system, shaking public confidence in robotic cars, could a pared-down approach like the one described -- variously called "partial autonomy" or "driver assistance" systems -- be the more realistic future of hands-free driving? This type of system, more like a no-nonsense chaperone than one you would find in a fully robotic car, is a necessary component for top scores from the Insurance Institute for Highway Safety's forthcoming ratings of partial-autonomous tech; high ratings from the independent nonprofit are prized. And though General Motors is taking the lead with their Super Cruise system, they not alone; Ford, BMW and Mercedes-Benz are making similar attempts. Super Cruise combines minutely detailed, 3-D laser-scanned roadway maps with cameras, radar and onboard GPS. By the end of this year, the company intends to expand the system's network to two-way highways for the first time and double its total operational domain to 400,000 miles.

Though police have been using facial recognition technology for the last two decades to try to identify unknown people in their investigations, the practice of putting the majority of Americans into a perpetual photo lineup has gotten surprisingly little attention from lawmakers and regulators. Lawmakers, civil liberties advocates and police chiefs have debated whether and how to use the technology because of concerns about both privacy and accuracy. But figuring out how to regulate it is tricky. So far, that has meant an all-or-nothing approach. City Councils in Oakland, Portland, San Francisco, Minneapolis and elsewhere have banned police use of the technology, largely because of bias in how it works.

On a recent afternoon, Mr. Luckey, dressed as if ready for the beach in a Hawaiian-like shirt, shorts and flip-flops, joined other Anduril employees at the company's testing site near Camp Pendleton, a Marine training facility. As the drone took off and swooped between the hills, Mr. Luckey said it could track an object and capture detailed images from seven football fields away. Using many of the artificial intelligence technologies that underpin self-driving cars, Anduril's drones can identify and track vehicles, people and other objects largely on their own. The drones are not armed, but could be useful for guarding bases or reconnaissance. The same sensor technologies that allow the drones to fly on their own could also be used to identify targets on a battlefield.