Collaborating Authors


A smarter, more capable Flippy robot knows how to fry 19 things


The restaurant industry has never been for the faint of heart, what with the razor-thin profit margins and continuous churn of employees. Combine that with the economic devastation wrought by the COVID-19 pandemic and, well, it's no surprise that tens of thousands of eateries across the country have shuttered permanently over the last seven months alone. However, Miso Robotics (makers of Flippy, the burger-flipping robot chef) argue that the path back to financial stability for America's restaurants will require an autonomous revolution. Buck Jordan, founder and CEO of Miso Robotics, points out to Engadget that the switch from full-service dining to exclusively take out and delivery has many restaurants "operating a loss and just trying to hang on," especially when delivery apps like UberEats and DoorDash take upwards of a 30 percent cut out of each order. "You can see why closing up shop is really the only option for many once your revenue is coming from delivery orders," he continued.

Online dating grows with corona-era search for love

Boston Herald

If there's one thing the pandemic hasn't canceled, it's the search for love. Throughout the health emergency, daters have taken to apps, websites and matchmaking services in search of connection, with more meeting in person as the crisis drags on at a time when every touch is calculated and fraught. They're feeling resilient, and they're not willing to put a year of their love life on hold because of the global pandemic," said Logan Ury, chief researcher for the popular dating app Hinge. In March, Hinge experienced a 30% increase over January and February in messages sent among users. In June, compared to the same month last year, there was a 13% increase in the number of dates -- virtual and in person -- in the U.S. and U.K., Ury said. Some daters insist on safety precautions before leaping into offline meetups. Others take no precautions, relying on mutual trust. A lucky few are on the ultimate step, marriage. Look no further than Jordan and Brittany Tyler in Allegan, Mich., as evidence of that. Jordan, an adjunct professor of communications at Western Michigan University, and Brittany, who supervises a program for autistic youth, had both been divorced about a year when the pandemic hit. Neither had dated online before they signed up for "When the lockdown happened an alert went off on my phone and it sounded liked'The Purge' or something," Brittany laughed. "I thought, 'I'm going to die alone.'" Both had dated their exes for several years before marrying. The two started texting March 18. They were wed by July after spending much of quarantine together after a romantic date March 24 at Jordan's place. He made gluten-free pasta from scratch and threw steaks on the grill. They watched the movie "P.S.

Introduction To Image Denoising


Image enhancement is an important research topic in image processing and computer vision. It is mainly used as image pre-processing or post-processing to make the processed image clearer for subsequent image analysis and understanding. There are many sources of noise in images, and these noises come from various aspects such as image acquisition, transmission, and compression. The types of noise are also different, such as salt and pepper noise, Gaussian noise, etc. There are different processing algorithms for different noises.

The AI Revolution Is Here. It's Just Different Than We Expected.


Two years ago, Berkeley computer science professor and AI expert Michael I. Jordan wrote an article warning against overinflating the claims of AI. He declared the AI revolution something we could only hope to reach in the future. I'd argue the revolution is now here. It just doesn't look the way sci-fi always portrayed it. As Jordan rightly points out in his article, the term "artificial intelligence" or "AI" is applied so widely to so many technologies that it has become practically meaningless.

Connecting actuarial judgment to probabilistic learning techniques with graph theory Artificial Intelligence

The aim of improvements in data driven exercises in insurance has led to the desire to gather additional data than traditionally available. In addition to underwriting characteristics such as age, gender and address, technology now allows the collection of many more variables. Examples include dynamic data from sensors for driving behaviour in vehicles, appliance and electrical usage in homes and static data from external databases on traffic violations, crime scores or credit scores. High dimensional models arise if modelling sensor data at multiple time points and the individual variables that comprise summary scores. Reasoning with a large number of variables can become unnecessarily complex without any actuarial judgment. For example, it may not be necessary to include hundreds of rating factors as predictors if many of them are known to be related or unnecessary. This discussion proposes the use of graph theory as a means of translating intuitive reasoning to mathematical properties. This is done via graphical models, which involve the use of graph theory to formulate probabilistic models (Lauritzen, 1996). The approach has been used in applications such as medical expert systems (Franklin et al., 1989), natural language processing (Blei et al., 2003), image processing, bioinformatics and others (Wainwright and Jordan, 2008).

Meet White Castle's new robot chef, Flippy


Move over human grill cooks, White Castle is teaming up with Miso Robotics to test an automated sous-chef. The aptly named Flippy--an AI-enabled kitchen assistant--is set to join the staff at a Chicago-area burger joint for a trial run that could usher in a new era of robot hash slingers. Since its unveiling in 2018, Flippy has cooked more than 40,000 pounds of fried food--including 9,000 sandwiches at LA's Dodger Stadium, the Arizona Diamondbacks' Chase Field, and two CaliBurger locations, where it works alongside humans to increase productivity and consistency. "I think automation is here to stay and this is the first example of a really large credible player starting down that journey," Miso Robotics CEO Buck Jordan told TechCrunch of the White Castle collab. Engineers are working to install the latest version of Flippy at an undisclosed location in Chicago, where the mechanical fry cook will be integrated into the restaurant's point-of-sale system, allowing it to get to work as soon as an order is placed.

Your next White Castle slider could be cooked by a robot


While robotic short-order cooks have been in development for a few years, their use in actual customer-facing businesses has been largely restricted to either independent or gimmick restaurants. But that changes today as Miso Robotics, maker of Flippy, and White Castle, maker of sliders, announce an Indiana-based pilot program that could one day see burger-flipping robots slinging patties and dunking fries all across the country. "The industry is facing some real, fundamental challenges," Buck Jordan, Miso Robotics CEO and Co-founder, told Engadget. "There's labor challenges due to self-sufficiency in kitchens, there's been a massive increase of delivery and now, of course, shifting consumer preferences towards low-touch establishments. These are all challenges that can be solved through automation."

Convolutional Neural Networks for Medical Images Diagnosis


This course was designed and prepared to be a practical CNN-based medical diagnosis application. It focuses on understanding by examples how CNN layers are working, how to train and evaluate CNN, how to improve CNN performances, how to visualize CNN layers, and how to deploy the final trained CNN model. All the development tools and materials required for this course are FREE. Besides that, all implemented Python codes are attached with this course.Who this course is for: Dr. Hussein received his B.Eng. degree in Computer Engineering (2006 Yarmouk University, Jordan), M.Eng.

Trump aims to sidestep another arms pact to sell more U.S. drones

The Japan Times

Washington – The Trump administration plans to reinterpret a Cold War-era arms agreement between 34 nations with the goal of allowing U.S. defense contractors to sell more American-made drones to a wide array of nations, three defense industry executives and a U.S. official told Reuters. The policy change, which has not been previously reported, could open up sales of armed U.S. drones to less stable governments such as Jordan and the United Arab Emirates that in the past have been forbidden from buying them under the 33-year-old Missile Technology Control Regime (MTCR), said the U.S. official, a former U.S. official and one of the executives. It could also undermine longstanding MTCR compliance from countries such as Russia, said the U.S. official, who has direct knowledge of the policy shift. Reinterpreting the MTCR is part of a broader Trump administration effort to sell more weapons overseas. It has overhauled a broad range of arms export regulations and removed the U.S. from international arms treaties including the Intermediate-Range Nuclear Forces Treaty and the Open Skies Treaty.