Title of the article is very oxymoronic: having an optimization and inefficiencies in the same context. But it is very true looking at the trend and current practices in the logistics industries. In this article, we are going to discuss how current practice of optimization is contributing significant inefficiencies for the organizations. And, how big firms (Like Amazon, Shopify, Uber) are taking an advantage of advancements in the field of combinatorial/mathematical optimization to identify the new opportunities, and winning the competition over thin margin, by creating a little wiggle room for the profit. Few months ago, I was discussing with my friend about an idea of mathematical formulation for a kitchen which can be efficient enough to make 1500 entirely different recipes (not just a vegetables, sauces and cheese on bread or bun), with less than 100 ingredients in inventory, with the use of minimal kitchen appliances.
OAKLAND, California, Dec. 14, 2020 /Press Release/ -- Silicon Valley Robotics, the world's largest cluster of innovation in robotics, announces the inaugural'Good Robot' Industry Awards, celebrating the robotics, automation and Artificial Intelligence (AI) that will help us solve global challenges. These 52 companies and individuals have all contributed to innovation that will improve the quality of our lives, whether it's weed-free pesticide-free farming, like FarmWise or Iron Ox; supporting health workers and the elderly manage health care treatment regimes, like Catalia Health or Multiply Labs; or reimagining the logistics industry so that the transfer of physical goods becomes as efficient as the transfer of information, like Cruise, Embark, Matternet and Zipline. The categories Innovation, Vision and Commercialization represent the stages robotics companies go through, firstly with an innovative technology or product, then with a vision to change the world (and occasionally the investment to match), and finally with real evidence of customer traction. The criteria for our Commercialization Award is achieving $1 million in revenue, which is a huge milestone for a startup building a new invention. Tessa Lau, Founder and CEO of Dusty Robotics, an Innovation Awardee said "We're almost there. Dusty Robotics' FieldPrinter automates the painstaking, time-consuming process of marking building plans in the field, replacing a traditional process using measuring tape and chalk lines that hasn't changed in 5000 years. The company's vision of creating robot-powered tools for the modern construction workforce resonates strongly with commercial construction companies. Dusty's robot fleet is now in production, producing highly accurate layouts in record time on every floor of two multi-family residential towers going up in San Francisco. The SVR'Good Robot' Industry Awards also highlight diverse robotics companies. In our Visionary Category, Zoox is the first billion dollar company led by an African-American woman, Aicha Evans, and Robust AI shows diversity at every level of the organization. Diversity of thought will be critical as Robust AI tackles the challenge of building a cognitive engine for robotics that incorporates common sense reasoning. "Robotics and AI will shape the next century in the same way the Industrial revolution shaped the 20th century.
In 2019, Walmart started working with a company called Gatik to test autonomous delivery trucks on a two-mile route between a fulfillment center and a store in Bentonville, Arkansas. After those vehicles logged more than 70,000 miles with a human driver there to make sure nothing went wrong, Walmart and Gatik say they're ready for a new challenge. Next year, there won't be any human drivers in the trucks. That milestone will make Gatik one of the first companies in the space to operate a fully autonomous route in this way. As the startup itself is quick to point, it has its simplified approach to thank for the achievement.
Researchers are aiming to "teach" a computer to recognize the sounds of resident killer whales in order to develop a warning system for preventing ships from fatally striking endangered orcas off British Columbia's coast. Steven Bergner, a computing science research associate at Simon Fraser University's Big Data Hub, said he is collecting and managing a database of sounds picked up 24 hours a day by a network of hydrophones in the Salish Sea. Marine biologists will identify the sounds of different species of whales, including humpbacks and transients, and differentiate the acoustics from other noise such as waves and boats, he said. Machine learning or artificial intelligence would help detect the presence of orcas through patterns in the data. "That (information) goes through another system that then decides whether there should be a warning that ultimately reaches the vessel pilots," Bergner said.
TOKYO--For a year that started out with a share crash, a record loss and a global pandemic, 2020 is turning out to be very good for SoftBank Group Corp. The Japanese technology investor, best known for its $100 billion Vision Fund and its mercurial chief executive, Masayoshi Son, this week scored an estimated $11 billion paper gain when U.S. food-delivery company DoorDash Inc. went public. It was the latest in a series of wins as soaring tech stocks pushed up the value of many of SoftBank's holdings. Cashing in on another investment, SoftBank said Friday that it agreed to sell an 80% stake in Boston Dynamics, a company known for dog-like robots that can maneuver through rooms, to Hyundai Motor Group . The deal valued the robotics company at $1.1 billion.
Neptune Lines PCTCs feature METIS Ship Connect – the automated data acquisition solution whose accuracy is approved by Lloyds Register. The METIS platform uses a network of Wireless Intelligent Collectors to harvest machinery, navigation and operational data regardless of equipment supplier. Its ship performance analysis also integrates AIS data, data fetched from vessels' daily / arrival / departure regular reporting and weather forecasts to provide services such as automated noon reporting, analysis of technical and operational domains and weather-related reporting. Outputs include live dashboards showing the condition of main engines, diesel generators, ballast water treatment systems and other machinery as well as power and fuel consumption. However, the METIS platform also allows Neptune Lines management to visualize KPIs such as power vs speed under the full ship speed range and in all weathers using machine learning models and run'what if' routing scenarios to weigh up consequences for fuel and arrival times.
You arrive at your fancy hotel and are greeted by a robot that promptly takes your luggage off your hands and carries it to your room for you, all while reciting cool things to do and places to eat in the city nearby. It sounds like something out of a sci-fi movie, but the reality is that this is not so far-fetched after all. It is already happening in places like South Korea, where it was recently announced by the Novotel Ambassador Seoul Dongdaemun Hotels and Residences that they're going to be using a robot helper to deliver luggage and room service to guests' rooms, using 3D mapping, 5G and artificial intelligence. It's becoming more and more common to see robots being used in place of humans – in warehouse production lines, at airports and train stations, and even cleaning homes. So how is robotics going to change the service industry?
Yesterday at AWS re:Invent 2020, we announced AWS Panorama, a new machine learning (ML) Appliance and SDK, which allows organizations to bring computer vision (CV) to their on-premises cameras to make automated predictions with high accuracy and low latency. In this post, you learn how customers across a range of industries are using AWS Panorama to improve their operations by automating monitoring and visual inspection tasks. For many organizations, deriving actionable insights from onsite camera video feeds to improve operations remains a challenge, whether it be increasing manufacturing quality, ensuring safety or operating compliance of their facilities, or analyzing customer traffic in retail locations. To derive these insights, customers must monitor live video of facilities or equipment, or review recorded footage after an incident has occurred, which is manual, error-prone, and difficult to scale. Customers have begun to take advantage of CV models running in the cloud to automate these visual inspection tasks, but there are circumstances when relying exclusively on the cloud isn't optimal due to latency requirements or intermittent connectivity.
A fleet of 30 Starship autonomous delivery robots has been deployed at the University of Houston, home to over 53,000 students, faculty and staff. In partnership with Chartwells Higher Education, UH is the first institution of higher education in the state of Texas to offer robotic food deliveries on campus. The recipient can even track the delivery -- made to a building's nearest outdoor entrance -- in real time. "This revolutionary delivery method will make it more convenient for the campus community to take advantage of our diverse dining program from anywhere on campus while expanding the hours of operation," said Emily Messa, UH associate vice president for administration. "By opening our campus to this innovative service, which is paid for by the customers, the university didn't have to spend any money purchasing the technology, yet we're enhancing our food delivery capabilities."
Full truckload transportation (FTL) in the form of freight containers represents one of the most important transportation modes in international trade. Due to large volume and scale, in FTL, delivery time is often less critical but cost and service quality are crucial. Therefore, efficiently solving large scale multiple shift FTL problems is becoming more and more important and requires further research. In one of our earlier studies, a set covering model and a three-stage solution method were developed for a multi-shift FTL problem. This paper extends the previous work and presents a significantly more efficient approach by hybridising pricing and cutting strategies with metaheuristics (a variable neighbourhood search and a genetic algorithm). The metaheuristics were adopted to find promising columns (vehicle routes) guided by pricing and cuts are dynamically generated to eliminate infeasible flow assignments caused by incompatible commodities. Computational experiments on real-life and artificial benchmark FTL problems showed superior performance both in terms of computational time and solution quality, when compared with previous MIP based three-stage methods and two existing metaheuristics. The proposed cutting and heuristic pricing approach can efficiently solve large scale real-life FTL problems.