We drank adaptogen drinks for weeks, and taste-tested with a trained sommelier. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. The best adaptogen drinks promise not just to wake you up in the morning, but offer focus and clarity and maybe even a warm wash of well-being. A different drink might tuck you gently in at night, or sub in for alcohol as a mindful party drink. I've spent months trying some of the most popular functional drinks on the market, bedding down with kava or tryptophan-laced xicha morada, and waking up with caffeine and L-theanine. Many of the new school of nootropic and functional drinks are like kissing cousins of mushroom coffee, except in refreshing soda form. Functional sodas might be chockablock with mushroom adaptogens such as reishi and cordyceps, alongside traditional home anxiety remedies such as ashwagandha or L-theanine. I both logged the effects of each soda, and held a large taste test with Portland, Oregon, sommelier Sami Gaston, owner of an excellent wine bar and shop called Bar Diane and Negociant, respectively--to determine how happy you'd be to drink them even if they didn't help you focus better on endless spreadsheets or the hunt for a job. Also check out WIRED's guide to mushroom gummies, or take your wellness in powdered form with the best greens powders and the best protein powders .

Oraichain is the world's first intelligent and secure solution for emerging Web3, scalable Dapps, and decentralized AI. The proposed Oraichain could be a bridge to bring AI to smart contracts. The Oraichain mechanism seems similar to Band Protocol and Chainlink, but it focuses more on AI APIs and the quality of the provided AI models. In each user request, test cases are attached, and the providers' API must pass a certain number of test cases to receive payment. The validators manage the features of test cases and AI model quality, and that makes Oraichain unique and different.

Google revealed today that it has given control of cooling several of its leviathan data centers to an AI algorithm. Over the past couple of years, Google has been testing an algorithm that learns how best to adjust cooling systems--fans, ventilation, and other equipment--in order to lower power consumption. This system previously made recommendations to data center managers, who would decide whether or not to implement them, leading to energy savings of around 40 percent in those cooling systems. Now, Google says, it has effectively handed control to the algorithm, which is managing cooling at several of its data centers all by itself. "It's the first time that an autonomous industrial control system will be deployed at this scale, to the best of our knowledge," says Mustafa Suleyman, head of applied AI at DeepMind, the London-based artificial-intelligence company Google acquired in 2014. The project demonstrates the potential for artificial intelligence to manage infrastructure--and shows how advanced AI systems can work in collaboration with humans.

At Google, artificial intelligence isn't just a means of building cars that drive on their own, smartphone services that respond to the spoken word, and online search engines that instantly recognize digital images. It's also a way of improving the efficiency of the massive data centers that underpin the company's entire online empire. According to Joe Kava, the man who oversees the design and operation of Google's worldwide network of data centers, the web giant is now using artificial neural networks to analyze how these enormous computing centers behave, and then hone their operation accordingly. These neural networks are essentially computer algorithms that can recognize patterns and then make decisions based on those patterns. They can't exactly duplicate the intelligence of the human brain, but in some cases, they can work much faster–and more comprehensively–than the brain. And that's why Google is applying these algorithms to its data center operations.

Google made headlines when it revealed that it is using machine learning to optimize its data center performance. In fact, Google's effort is only the latest in a series of initiatives to create an electronic "data center brain" that can analyze IT infrastructure. Automation has always been a priority for data center managers, and has become more important as facilities have become more complex. The DevOps movement seeks to "automate all the things" in a data center, while the push for greater efficiency has driven the development of smarter cooling systems. Where is this all headed? The data center won't be a portal to Skynet anytime soon.