The company behind a robot fast food cook has a new mission: Help humans cook burgers that won't get customers sick. Miso Robotics, the firm behind Flippy, the robot-on-rails fry cook solution that's been garnering big backing and has debuted at restaurants including Pasadena's CaliBurger chain, has a new software-based offering for fast food restaurants that aren't ready to go full robot just yet. Packaged as a standalone software as a service (SaaS) offering, the company's new CookRight is billed as the world's first artificial intelligence (AI) powered cooking platform meant to keep human fry cooks from torching burgers--or worse, undercooking them, which can be a serious health hazard. That last is a particularly strong selling point in the wake of a global pandemic that's left consumers more conscious than ever of safe handling practices. According to the Centers for Disease Prevention and Control (CDC), every year, an estimated 1-in-6 Americans (or 48 million people) get sick, 128,000 are hospitalized, and 3,000 die of foodborne diseases.
As the coronavirus pandemic continues to rage, those fortunate enough to be fully vaccinated and live in countries with declining case counts are now beginning to imagine a future without COVID-19. Whether or not that future will include the disinfecting robots purchased by hotel chains, universities, and stadiums is anyone's guess. The machines, some of which cost north of $100,000 dollars a piece, initially appeared an ideal solution to a virus believed to be transmitted primarily by physical contact. Manufacturers of robotic devices that blast ultraviolet light, or disinfecting spray, touted their products as vital technological tools in the battle against COVID-19. And a justifiably concerned public was receptive to the pitch.
The world's first fully autonomous ship is set to make its maiden voyage across the Atlantic next month. Inspired by the ship that brought the Pilgrims to North America, 'Mayflower 400' will be guided by artificial intelligence rather than a human crew. If all goes well, it will depart from Plymouth, England on May 15 and arrive at Plymouth, Massachusetts, about 3,000 miles and two weeks later. The original Mayflower, which transported 102 Pilgrims and other passengers, took 10 weeks to reach its destination in 1620. Mayflower 400 was set to embark on its transatlantic cruise last September for the Mayflower's 400th anniversary, but was delayed because of the coronavirus pandemic.
The phrase'digital transformation' has been bouncing off the walls of boardrooms around the world for more than a decade. You might have expected Covid-19 to put the brakes on some of this activity, but it's been full steam ahead. In fact, Gartner reports that digital innovation and the application of emerging technologies has actually accelerated during the pandemic. Amit Gupta is Executive Vice President and Global Head – DRYiCETM Software, HCL Technologies. The phrase emerging technologies used to apply to AI, which was something of an optional add-on when the concept of digital transformation first hit the mainstream.
As the world grapples with the devastation of the coronavirus, one thing is clear: The United States simply wasn't prepared. Despite repeated warnings from infectious disease experts over the years, we lacked essential beds, equipment, and medication; public health advice was confusing; and our leadership offered no clear direction while sidelining credible health professionals and institutions. Infectious disease experts agree that it's only a matter of time before the next pandemic hits, and that one could be even more deadly. So how do we fix what COVID-19 has shown was broken? In this Mother Jones series, we're asking experts from a wide range of disciplines one question: What are the most important steps we can take to make sure we're better prepared next time around? On a hazy day in early March, a drone packaged in protective red casing and carrying precious cargo descended upon a crowd gathered in the Ashanti region of Ghana.
Two years ago I spoke at the Women of Silicon Roundabout Conference about machine learning (ML) startups and why they were a trend to watch. It occurred to me recently that I never got to share with the wider world the interesting cases we discussed, and, alas, I am not allowed to share the full recording of the talk. It also sounds like I've been remembered more for the yellow platforms I stomped around the stage with (evidence here), rather than the actual content. So I've decided to revisit the topic, re-examining some of the original cases alongside newer startups that have since come out of the woodwork. I also work at an ML startup, meaning that we sell predictions from ML models (specifically, predictions about which customers are committing fraud).
The data which shows that robot-assisted procedures accounted for 15.1% of all general surgeries in 2018, up from 1.8% in 2012,1 is an indication of two things: In the long term, integrating robotics into surgical procedures will result in a more enhanced healthcare system: we would be able to perform more complex surgical procedures, and as a result, save more lives. But this change would also require a pivot in the educational system. In order to sustain a high standard of performance using the existing solutions on the market, doctors would need to understand the basics of robotics; otherwise a more intuitive navigation system will be required. In addition to the rise in surgical robots, there has a rapid increase in the overall implementation of robotics applications in healthcare. The COVID-19 pandemic has shifted the way robots are perceived – now they can be involved in patient screening, surface disinfection, positioning of medical devices and distribution of medicines, while keeping nurses and doctors safe from infection.
As I look out over the Port of Los Angeles with its shipping cranes and waterways, I think about the 800,000 gallons of water similar in quality to drinking water lying in tanks under my feet. Less than 24 hours earlier, it had been raw sewage entering the Terminal Island Water Reclamation plant, where environmental engineer Lance Thibodeaux is showing me around so I can see high-tech filtration in action. What made the water's transformation possible? Advanced purification systems, constantly and automatically run by a centralized computer program housed in a small office a few hundred yards away. Between heat, fluid dynamics, bacteria, and gravity, nature has its own tools for safely reabsorbing human waste back into the environment.
Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Girl Scouts in Virginia are going high tech when it comes to delivering their seasonal cookies. According to Google's drone delivery company Wing, a local troop in the town of Christiansburg has been using its service to test cookie dispatch. Girl Scouts Alice Goerlich (right) and Gracie Walker (left) pose with a Wing delivery drone in Christiansburg, Va. on April 14, 2021.
The Covid-19 pandemic was devastating for many industries, but it only accelerated the use of artificial intelligence across the U.S. economy. Amid the crisis, companies scrambled to create new services for remote workers and students, beef up online shopping and dining options, make customer call centers more efficient and speed development of important new drugs. Even as applications of machine learning and perception platforms become commonplace, a thick layer of hype and fuzzy jargon clings to AI-enabled software.That makes it tough to identify the most compelling companies in the space--especially those finding new ways to use AI that create value by making humans more efficient, not redundant. With this in mind, Forbes has partnered with venture firms Sequoia Capital and Meritech Capital to create our third annual AI 50, a list of private, promising North American companies that are using artificial intelligence in ways that are fundamental to their operations. To be considered, businesses must be privately-held and utilizing machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language) or computer vision (which relates to how machines "see"). AI companies incubated at, largely funded through or acquired by large tech, manufacturing or industrial firms aren't eligible for consideration. Our list was compiled through a submission process open to any AI company in the U.S. and Canada. The application asked companies to provide details on their technology, business model, customers and financials like funding, valuation and revenue history (companies had the option to submit information confidentially, to encourage greater transparency). Forbes received several hundred entries, of which nearly 400 qualified for consideration. From there, our data partners applied an algorithm to identify 100 companies with the highest quantitative scores--and that also made diversity a priority. Next, a panel of expert AI judges evaluated the finalists to find the 50 most compelling companies (they were precluded from judging companies in which they have a vested interest). Among trends this year are what Sequoia Capital's Konstantine Buhler calls AI workbench companies--building of platforms tailored to different enterprises, including Dataiku, DataRobot Domino Data and Databricks.