For all the hype around folding phones, there's plenty of anxiety concerning how well those bendable screens survive long term. Depending on who you ask, they're either weaker than spider silk or hardy enough to make your average lumberjack weep with envy. That's why Sam Rutherford took matters into his own hands, spending the last year running his own durability test. He's been using his Z Fold 4 without a case, leaving its factory-installed screen protector as the only defense. At the dawn of the Z Fold 5, Rutherford is now ready to reveal how well he got on with its predecessor.

Last Monday an eminent, elderly British scientist lobbed a grenade into the febrile anthill of researchers and corporations currently obsessed with artificial intelligence or AI (aka, for the most part, a technology called machine learning). The scientist was Geoffrey Hinton, and the bombshell was the news that he was leaving Google, where he had been doing great work on machine learning for the last 10 years, because he wanted to be free to express his fears about where the technology he had played a seminal role in founding was heading. To say that this was big news would be an epic understatement. The tech industry is a huge, excitable beast that is occasionally prone to outbreaks of "irrational exuberance", ie madness. One recent bout of it involved cryptocurrencies and a vision of the future of the internet called "Web3", which an astute young blogger and critic, Molly White, memorably describes as "an enormous grift that's pouring lighter fluid on our already smoldering planet".

We often have blind spots for the reasons that cause problems in our lives. We try to fix our issues based on assumptions, false analysis, and mistaken deductions. These create misunderstanding, anxiety, and frustration in our personal and work relationships. Resist jumping to conclusions prematurely. Evaluate information correctly and consistently to make better decisions.

The joy, anxiety, and anticipation of getting a COVID vaccine in America culminates, quite anticlimactically, with a piece of white cardstock. Some have already lost their vaccine cards or never got them to begin with. Others have their names misspelled and crossed out on it. Many are having trouble reconciling how something so simple--and easily forged--can carry such import and weight. The White House has recently clarified that there will be no federal vaccine passport.

I've grown accustomed to conflicting views when it comes to the pandemic. We can gather in the library, but our kids can't go to school. I can finally get my hair done, but a facial is not allowed. You shouldn't wear a mask, you have to wear a mask, you really should be wearing two masks. This virus is so new that all of us -- from CDC scientists to supermarket cashiers -- are still trying to navigate a steep learning curve. And I like to think that nothing surprises me anymore.

The U.S. Food and Drug Administration on Thursday convened a public meeting of its Patient Engagement Advisory Committee to discuss issues regarding artificial intelligence and machine learning in medical devices. "Devices using AI and ML technology will transform healthcare delivery by increasing efficiency in key processes in the treatment of patients," said Dr. Paul Conway, PEAC chair and chair of policy and global affairs of the American Association of Kidney Patients. As Conway and others noted during the panel, AI and ML systems may have algorithmic biases and lack transparency – potentially leading, in turn, to an undermining of patient trust in devices. Medical device innovation has already ramped up in response to the COVID-19 crisis, with Center for Devices and Radiological Health Director Dr. Jeff Shuren noting that 562 medical devices have already been granted emergency use authorization by the FDA. It's imperative, said Shuren, that patients' needs be considered as part of the creation process.

Back in 2016, Juan Pablo Torres-Padilla, who has been the CEO of an artificial intelligence (AI) company in France and has held other key positions in the telecommunications and financial investment world, decided to take the opportunity to buy the historic Napa Valley 26 acre Sullivan Rutherford Estate from the Sullivan family, the custodians of that piece of land for over 40 years. It would prove to be a good partnership in terms of handing over the estate to someone who not only wanted to bring this winery more to the forefront of the Napa fine wine world but that the history and legacy would be appreciated and built upon. The estate lies on land that has a deep and rich history which goes back almost two centuries to 1821 when Mexico took over ownership of Napa Valley from Spain. Mexico divided the Napa Valley into two parts: Rancho Carne Humana in the North and Rancho Caymus in the South. Sullivan Rutherford Estate director of winemaking, Jeff Cole, said that they are "essentially in the middle of the heart of Napa Valley vineyards" since the back of the border of their estate is along the Rancho Caymus line as it is right in the middle of where the property lines of Rancho Caymus and Rancho Carne Humana meet.

One of the most pressing questions public health officials are trying to answer about the coronavirus is how many people actually have been infected by it. Have a relatively significant portion of Californians been infected with the virus but survived without much problem? Or has the virus touched only a tiny sliver of California, suggesting the chances of serious illness are greater if you're infected? In April, controversial studies out of Stanford University and USC suggested the coronavirus has circulated much more widely than previously thought in Silicon Valley and Los Angeles County. Almost immediately, there have been questions from other epidemiologists around the country about whether those estimates were too high.

At the heart of the discipline of artificial intelligence is the idea that one day we'll be able to build a machine that's as smart as a human. Such a system is often referred to as an artificial general intelligence, or AGI, which is a name that distinguishes the concept from the broader field of study. It also makes it clear that true AI possesses intelligence that is both broad and adaptable. To date, we've built countless systems that are superhuman at specific tasks, but none that can match a rat when it comes to general brain power. But despite the centrality of this idea to the field of AI, there's little agreement among researchers as to when this feat might actually be achievable.

At the heart of the discipline of artificial intelligence is the idea that one day we'll be able to build a machine that's as smart as a human. Such a system is often referred to as an artificial general intelligence, or AGI, which is a name that distinguishes the concept from the broader field of study. It also makes it clear that true AI possesses intelligence that is both broad and adaptable. To date, we've built countless systems that are superhuman at specific tasks, but none that can match a rat when it comes to general brain power. But despite the centrality of this idea to the field of AI, there's little agreement among researchers as to when this feat might actually be achievable.