Mayra Leiva of Reseda, California, knew her eight-year-old son was a little interested in history. But she was surprised when all at once he became a walking encyclopedia, spouting dates and pretending every tire swing was a time machine. "It happened after he saw Night at the Museum," she says. I've had to do a lot of Googling to keep up!" Not many children will tell you that their favorite school subject is history. Memorizing dates and learning long-ago facts that don't seem relevant isn't exactly high on their fun list. Perhaps that's why pop culture--movies, music, television, and even video games and comic books--can be such useful teaching tools. "Teaching through pop culture helps students relate history to their own background and experiences," says Gail Hudson, a fifth-grade teacher and 2020 Nevada Teacher of the Year. "It's tying into something that's already caught their interest." Take the movie version of the Broadway show Hamilton, which releases on Disney July 3.

Best listening experience is on Chrome, Firefox or Safari. The irony of artificial intelligence is how much human brainpower is required to build it. For three years, our next guest had been on loan from the University of Massachusetts, to the Defense Advanced Research Projects Agency. There's she headed up several DARPA artificial intelligence projects. Now she's been awarded a high honor, the Meritorious Public Service Medal.

Black Lives Matter is reverberating around the world, triggering a fresh reckoning with the racist global history of colonialism and slavery. While Confederate statues began to tumble across the American South, in Bristol, England, a diverse group felled a statue of a slave trader that has long provoked offense. Statues of colonial conquerors of Africa and South Asia have followed, along with a robust discussion of the ways in which such actions make history rather than erase it. These movements abroad are not merely echoes of BLM; BLM itself is global. The shared impetus is a common opposition to racism, of which anti-Black racism has been the most lethal and traumatic.

The coronavirus pandemic has led to enhanced health-care collaboration, innovation, and increased use of digital technologies. Telehealth enables doctors to safely connect with patients virtually and monitor them remotely, whether in different cities or down the hall. And smarter and smaller medical devices are producing better outcomes for patients--a disruption is sensed, like low blood sugar or a too-rapidly beating heart, and a therapy is applied, in real time. This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review's editorial staff. All of this is aided by improved processing capabilities and data--lots of data, and that means artificial intelligence. The guest in this episode of Business Lab is Laura Mauri, vice president of global clinical research and analytics at Medtronic. And she knows all about how data can help drive better patient outcomes, improve the patient experience, and provide valuable information for doctors and medical device creators. Dr. Mauri is an interventional cardiologist and one of the world's leading experts on clinical trials, but, as she says, the success of a clinical trial really does come down to the patient experience, and how it's improved. Mauri also has great hope for health care and technology. And although she cautions that this work is not simple, you can literally see progress happening--which is the outcome we all want. Business Lab is hosted by Laurel Ruma, director of Insights, the custom publishing division of MIT Technology Review.

Considering various factors such as the research areas, research focus, courses offered, duration of the program, location of the university, honors, awards, and job prospects, we came up with the best universities to help you in your choosing process. This article is most suited for individuals who'd like to pursue a Ph.D. with a focus on machine learning and need some guidance on their decision making. Feel free to jump to the end if you are looking for only the names of the Universities. Note: The universities mentioned below are in no particular order. To summarize, we have listed the top universities for a Ph.D. with a focus area in machine learning below:

Editor's note: A leading figure in the Chinese tech scene and in artificial-intelligence development globally, Kai-Fu Lee earned a PhD in computer science from Carnegie Mellon University in 1988 before serving in executive roles at Apple, SGI, Microsoft, and Google, where he was president of Google China. Now chairman and CEO of Sinovation Ventures in Beijing, he is the author of AI Superpowers: China, Silicon Valley, and the New World Order. Here, he discusses with Project Syndicate the global AI race, the current state of the field, and what may – and should – come next. Question: As someone who long worked for U.S. companies and now oversees a tech venture capital firm, you're deeply familiar with the world's two main settings for AI development and research. What are the trade-offs of each R&D environment?

The images are everywhere: People crowded face-to-face in swimming pools, shoulder-to-shoulder in indoor bars, cheering without masks at a rally held by President Trump, who often downplays the global pandemic. Now, as many public health experts predicted, waves of new COVID-19 infections and deaths are rolling across the South and West. Many, still practicing social distancing, look at their fellow Americans and ask, "What are they thinking?" We turned to Steven Pinker for help with an answer. The professor of psychology at Harvard, author of widely discussed books, including How the Mind Works and most recently, Enlightenment Now, sees the deep-seated mindset, tribalism, at work in people's defiance of health recommendations.

When we're first learning to make music, most of us don't worry about an A.I. stealing our flow. They say imitation is the sincerest form of flattery. But when Jay-Z heard himself on the internet spitting iambic pentameter -- Hamlet's "To Be, or Not to Be" soliloquy, to be exact -- "flattered" is hardly the word for how he responded. It was produced by a well-trained computer speech synthesis program using artificial intelligence. An anonymous YouTube artist named Vocal Synthesis has created a library of popular voices mismatched with unexpected famous texts, including George Bush reading "In Da Club" by 50 Cent, Barack Obama reading "Juicy" by Notorious B.I.G, and, yes, Jay-Z reading Hamlet (and Billy Joel's "We Didn't Start the Fire").

When neuroscientists David Hubel and Torsten Wiesel wanted to figure out how the brain parses its visual environment, they went as simple as they could go. In a Harvard lab crammed with electrical equipment, they positioned cats in front of a screen and showed them extremely basic images: dots in particular locations, lines at various angles. At the same time, they used implanted electrodes to, quite literally, "listen" to neurons in the areas of the brain devoted to vision. By observing which neurons fired in response to which shapes, they were able to unlock a part of the brain's "visual code," the way in which it represents visual information about its environment. For their achievement, Hubel and Wiesel won the Nobel Prize in 1981, and their discoveries kick-started the rich, diverse field of visual neuroscience.

Many critics of police facial recognition use warn of the potential for racial bias that leads to false arrests, and unfortunately that appears to have happened. The ACLU has filed a complaint against Detroit police for the wrongful arrest of Robert Williams when a DataWorks Plus facial recognition system incorrectly matched security footage against Williams' driver's license, marking him as a suspect. Officers showed the match to an offsite security consultant who identified Williams as the culprit, but this person never saw the perpetrator first-hand. The ACLU argued that the DataWorks system "can't tell Black people apart" and that the whole system was "tainted" by officers' assumptions that the facial recognition system produced the right suspect. In a Washington Post opinion piece, Williams added that he was concerned about the tech even if it was completely accurate -- he didn't want his daughters' faces to go into a database and prompt future police questioning when they're spotted at a "protest the government didn't like."