The technology sector has been hit hard as of late, as the impending economic reopening has gotten more attention, and rising long-term bond rates have hit growth stocks particularly hard. As rates go up, future earnings are discounted more, harming valuations for growth stocks and increasing attention on value stocks that make profits today. And yet, technology will still play an ever-increasing role in society even post-pandemic. AI helps businesses make sense of their vast troves of data, glean insights, and react quickly in an automated fashion. As AI helps grow revenue and cut costs at the same time, it will be a mission-critical capability for any large company, even post-pandemic. But are there really any AI stocks that still trade at reasonable valuations, and which can handle the market's current value rotation?

Recently, I was at a party in San Francisco when a man approached me and introduced himself as the founder of a small artificial intelligence (AI) start-up. As soon as the founder figured out that I was a technology writer for The New York Times, he launched into a pitch for his company, which he said was trying to revolutionise the manufacturing sector using a new AI technique called "deep reinforcement learning". The founder explained that his company's AI could run millions of virtual simulations for any given factory, eventually arriving at the exact sequence of processes that would allow it to produce goods most efficiently. This AI, he said, would allow factories to replace entire teams of human production planners, along with most of the outdated software those people relied on. "We call it the Boomer Remover," he said.

Harm wrought by AI tends to fall most heavily on marginalized communities. In the United States, algorithmic harm may lead to the false arrest of Black men, disproportionately reject female job candidates, or target people who identify as queer. In India, those impacts can further impact marginalized populations like Muslim minority groups or people oppressed by the caste system. And algorithmic fairness frameworks developed in the West may not transfer directly to people in India or other countries in the Global South, where algorithmic fairness requires understanding of local social structures and power dynamics and a legacy of colonialism. That's the argument behind "De-centering Algorithmic Power: Towards Algorithmic Fairness in India," a paper accepted for publication at the Fairness, Accountability, and Transparency (FAccT) conference, which begins this week. Other works that seek to move beyond a Western-centric focus include Shinto or Buddhism-based frameworks for AI design and an approach to AI governance based on the African philosophy of Ubuntu.

In 2018, volunteers with an interest in microdosing--regularly taking tiny amounts of psychedelic drugs such as LSD--began taking part in an unusual experiment. For four weeks, researchers at Imperial College London asked them to swap some of their drugs with empty capsules--placebos--so that when they took them, they didn't know if they were microdosing or not. They then completed online surveys and cognitive tasks at regular intervals, aimed at gauging their mental well-being and cognitive abilities. The idea: to explore if microdosing produces the benefits to mood and brain function that some people claim. This story originally appeared on WIRED UK.

Despite major disruptions from the ongoing COVID-19 pandemic, global investment in AI technologies grew by 40 percent in 2020 to $67.9 billion, up from $48.8 billion in 2019, as AI research and use continues to boom across broad segments of bioscience, healthcare, manufacturing and more. The figures, compiled as part of Stanford University's Artificlal Intelligence Index Report 2021 on the state of AI research, development, implementation and use around the world, help illustrate the continually changing scope of the still-maturing technology. The 222-page AI Index 2021 report, touted as the school's fourth annual study of AI impact and progress, was released March 3 by Stanford's Institute for Human-Centered Artificial Intelligence. The report provides a detailed portrait of the AI waterfront last year, including increasing AI investments and use in medicine and healthcare, China's growth in AI research, huge gains in AI capabilities across industries, concerns about diversity among AI researchers, ongoing debates about AI ethics and more. "The impact of AI this past year was both societal and economic, driven by the increasingly rapid progress of the technology itself," AI Index co-chair Jack Clark said in a statement.

New York, March 7 (IANS) Researchers have developed a method based on Artificial Intelligence (AI) that rapidly identifies currently available medications that may treat Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing FDA-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment -- but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," said researcher Artem Sokolov from Harvard Medical School. "We therefore built a framework for prioritising drugs, helping clinical studies to focus on the most promising ones," Sokolov added.

IMAGE: A computer created facial images that appealed to individual preferences. Researchers have succeeded in making an AI understand our subjective notions of what makes faces attractive. The device demonstrated this knowledge by its ability to create new portraits on its own that were tailored to be found personally attractive to individuals. The results can be utilised, for example, in modelling preferences and decision-making as well as potentially identifying unconscious attitudes. Researchers at the University of Helsinki and University of Copenhagen investigated whether a computer would be able to identify the facial features we consider attractive and, based on this, create new images matching our criteria.

I wake up in the middle of the night. "Hey, Google, what's the temperature in Zone 2," I say into the darkness. A disembodied voice responds: "The temperature in Zone 2 is 52 degrees." "Set the heat to 68," I say, and then I ask the gods of artificial intelligence to turn on the light. Many of us already live with A.I., an array of unseen algorithms that control our Internet-connected devices, from smartphones to security cameras and cars that heat the seats before you've even stepped out of the house on a frigid morning.

The Big Mac might be McDonald's most famous item, but a lot of people don't know much about it. Check out the history of the fast-food chain's beloved burger. The COVID-19 pandemic brought a lot of changes to restaurants. Since many casual restaurants had to close their doors and switch to take-out only, people were ordering fast food even more than usual. And because the "grab-and-go" factor is already a perk of fast-food restaurants, it was basically a no-brainer for those who hoped grab a meal and maintain social distancing.

Even with technology, sometimes we believe in fairy tales. A fairy tale is a story with a "fantastic and magical setting or magical influences within a story." I hadn't thought much about fairy tales recently, until I began reviewing the number of online case studies about artificial intelligence (AI) in companies. In most of these case studies, the bottom line was that an AI solution had been successfully implemented. However, when I reviewed the stories for business outcomes or results, the results weren't there.