California will be the epicenter of non working human zombies soon!
Burger robot can grill a perfect patty, but it doesn’t provide service with a smile.
The next time you place an order at a fast food joint, you could see a robot behind the counter. Flippy is an AI-driven kitchen assistant that can flip burgers and place them on buns, and it debuted today at a CaliBurger restaurant in Pasadena, California.
Flippy was developed by Miso Robotics and CaliBurger’s owner, Cali Group. It uses cameras, sensors and deep learning software to locate ingredients in a kitchen without needing to reconfigure existing equipment. Not only does it position and flip the patties, it tracks their temperature and cooking time too. When the burgers are done, it alerts a human cook, who applies the cheese and other toppings.
“Much like self-driving vehicles, our system continuously learns from its experiences to improve over time,” said David Zito, CEO of Miso Robotics, in a statement. Eventually, Zito said Flippy can be trained to help with other kitchen tasks, like frying chicken, cutting vegetables or plating.
Self-ordering kiosks are already replacing workers at fast food chains like McDonald’s and Wendys. But, Miso Robotics said Flippy is designed to work alongside human staff. Once its “probation” ends in Pasadena, it will roll out to more than 50 CaliBurger locations over the next two years. When that happens, some people could be reassigned to the dining room to engage more with customers, while others will be trained to operate their new assistant.
“Tasting food and creating recipes will always be the purview of a chef,” Zito recently told TechCrunch. “And restaurants are gathering places where we go to interact with each other. Humans will always play a very critical role in the hospitality side of the business given the social aspects of food. We just don’t know what the new roles will be yet in the industry.”
Taser has started its own in-house AI unit, laying the groundwork for police body cameras that record fully-searchable video evidence
The police body camera industry is the latest to jump on the artificial intelligence bandwagon, bringing new powers and privacy concerns to a controversial technology bolstered by the need to hold police accountable after numerous high-profile killings of unarmed black citizens. Now, that tech is about to get smarter.
Last week, Taser, the stun gun company that has recently become an industry leader in body-mounted cameras, announced the creation of its own in-house artificial intelligence division. The new unit will utilize the company’s acquisition of two AI-focused firms: Dextro, a New York-based computer vision startup, and Misfit, another computer vision company previously owned by the watch manufacturer Fossil. Taser says the newly formed division will develop AI-powered tech specifically aimed at law enforcement, using automation and machine learning algorithms to let cops search for people and objects in video footage captured by on-body camera systems.
Moreover, the move suggests that body-worn cameras, which are already being used by police departments in many major cities, could soon become powerful surveillance tools capable of identifying different objects, events, and people encountered by officers on the street — both retroactively and in real time.
The idea is to use machine learning algorithms to streamline the process of combing through and redacting hours of video footage captured by police body cameras. Dextro has trained algorithms to scan video footage for different types of objects, like guns or toilets, as well as recognize events, like a foot chase or traffic stop. The result of all this tagging and classifying is that police will be able use keywords to search through video footage just like they’d search for news articles on Google, allowing them to quickly redact footage and zoom in on the relevant elements. Taser predicts that in a year’s time, their automation technology will reduce the total amount of time needed to redact faces from one hour of video footage from eight to 1.5 hours.