MLOps is a relatively new concept in the AI (Artificial Intelligence) world and stands for "machine learning operations." Its about how to best manage data scientists and operations people to allow for the effective development, deployment and monitoring of models. "MLOps is the natural progression of DevOps in the context of AI," said Samir Tout, who is a Professor of Cybersecurity at the Eastern Michigan University's School of Information Security & Applied Computing (SISAC). "While it leverages DevOps' focus on security, compliance, and management of IT resources, MLOps' real emphasis is on the consistent and smooth development of models and their scalability." The origins of MLOps goes back to 2015 from a paper entitled "Hidden Technical Debt in Machine Learning Systems."
Its about how to best manage data scientists and operations people to allow for the effective development, deployment and monitoring of models. "MLOps is the natural progression of DevOps in the context of AI," said Samir Tout, who is a Professor of Cybersecurity at the Eastern Michigan University's School of Information Security & Applied Computing (SISAC) .
From Michigan to Tokyo, the coronavirus pandemic has led to a surge in demand for contactless delivery robots. In Ann Arbor, Michigan, lunch orders for Refraction AI's last-mile REV-1 autonomous delivery robot have jumped by up to four-fold since the health crisis began. The company, which started operations in July 2019, created the robot for local deliveries between stores and customers. Residents in Ann Arbor, where the pilot program is now underway, can register for REV-1's lunch delivery that offers cuisine from a variety of restaurants including Asian and Mexican. Able to operate in the bike lane and on public roads, REV-1's can travel at up to 15mph but will slow to a fast walking pace in residential areas.
The American car company Ford has introduced two new employees to the team – four-legged robot dogs named Fluffy and Spot. The firm announced the addition of Boston Dynamics' machines at its Michigan manufacturing plant to assist human employees with a number of tasks. The duo will be used to scan the plant with lasers and high-definition cameras to collect data on how to retool Ford's facilities. A complete documentation of one plant can take up to two weeks, but using the bots will cut the time by half and at a fraction of the cost, according to Ford. Boston Dynamics' Spot officially went on sale for commercial and industrial use last month with a price tag of $74,500 and it appears Ford quickly jumped at the offer.
A Ford plant in Michigan has enlisted two Boston Dynamics robots to aid in laser scanning the plant as it's prepped for updates, Ford announced yesterday. The robots, nicknamed Fluffy and Spot, will roam the Van Dyke Transmission Plant in Dearborn, MI on four legs, much like a dog would. However, unlike their furry counterparts, these robots are equipped with five cameras, can perform 360-degree scans and are able to climb stairs for hours. Ford is leasing the Boston Dynamics Spot robots (although you can buy them for $75,000) and deploying them in early August. Fluffy and Spot will scan the plant so engineers have an updated model of what the floor looks like, as changes have been made over the years that may not have been documented, said Mark Goderis, Ford's digital engineering manager.
Ford's new robot dogs, Fluffy and Spot, can technically sit and shake, but they're too busy working for any of that. Ford is leasing the two Boston Dynamics "dogs" to scan and create 3D imagery of its Van Dyke Transmission Plant in Michigan as part of a pilot. Ford uses the scans to redesign the floor layout and prepare for new production projects. It's usually tedious work for a human with a camera (and costs what Ford says is about $300,000), but this is what the quadruped robodogs were made to do. The $75,000 bots can crouch, walk on uneven terrain, and climb stairs.
> Science's COVID-19 coverage is supported by the Pulitzer Center. In a normal summer, Appledore Island, a 39-hectare outcrop 12 kilometers off the coast of Maine and New Hampshire, becomes a classroom. Students from high school to graduate level live in close quarters, eat in a communal dining hall, and work shoulder to shoulder to explore the biology of the shore and waters in 18 courses organized by the Shoals Marine Laboratory. But this summer, with the pandemic surging, students have stayed home. Instead, a skeleton staff on Appledore is streaming field trips and dissections of fish and invertebrates and setting up cameras to gather data for students. Rather than leading students around the island, coastal restoration ecologist Gregg Moore from the University of New Hampshire (UNH), Durham, hauls a backpack full of equipment: “a dual modem with two different cellular carriers, a signal-boosting directional antenna, and a large DC power source,” he says. The equipment allows him to teach 12 remote students—twice the course's usual enrollment—basic techniques of coastal ecology. Moore's is just one of hundreds of lab and field courses forced online by COVID-19—“a seismic shift for those who were not already involved in distance or online education,” says Martin Storksdieck, a science education researcher at Oregon State University, Corvallis. Some researchers worry students will miss out on certain practical and problem-solving skills and won't be able to judge whether the hands-on work of a scientist is a good fit for them. But instructors are developing high-tech ways to simulate the field and lab experiences. “I would say [these courses] are not virtual,” says Jennifer Seavey, director of the Shoals lab. “They are real.” And some advantages are emerging. By lowering geographical and financial barriers, Seavey says, “Virtual field courses are democratizing fieldwork.” The shift has taken ingenuity. “Professors must get creative and use a combination of what is available,” including online videos and free or commercially available online labs, says Mildred Pointer, a physiologist at Howard University who is working on a fall course in general biology. No single tool meets all their needs, Pointer says. As the pandemic gained momentum, emails flew among the leaders of the National Association of Geoscience Teachers. Many U.S. geology majors must take a “capstone” field course to graduate. The cancellation of more than three-quarters of these courses jeopardized graduation for many majors. So the association invited instructors to develop learning objectives that did not depend on students doing fieldwork. It also compiled online exercises to help the 29 field courses that have moved online this summer. Lessons range from “Orienteering in Minecraft” to “Geology of Yosemite Valley,” which includes a 43-stop Google Earth tour with photos and embedded text. Like Moore, geoscientist Jim Handschy wanted to give remote students “as close to the real experience as possible.” He runs Indiana University's Judson Mead Geologic Field Station in Montana, which had enrolled 60 students before classes were canceled in March. He and a few instructors visited each outcrop in their course plan, filmed the rocks and landscape, and captured magnified views of samples. Each week, the class delves deeper into the rock layers and their history. For their final project, students digitally map a 3100-hectare landscape. Shannon Dulin, a geologist at the University of Oklahoma, Norman, who just finished teaching a field course, sees the value of learning how to survey a landscape without setting foot on it. On their class evaluations, her students said they gained unexpected skills. “And these are skills they are going to need on the job,” she adds, as geologists are increasingly being asked to evaluate sites they don't visit. In other fields, hands-on learning takes place in labs. Typically, students work in pairs and share equipment, “so there are a lot of issues about virus transmission,” says Heather Lewandowski, a physicist at the University of Colorado (CU), Boulder. At her university this fall, lab exercises as diverse as building an electrical circuit or analyzing solar flare data will most likely be completely remote. Luckily, physics already had a foot in the virtual lab world—especially at CU. There, back in 2002, Nobel laureate Carl Wieman developed the Physics Education Technology (PhET) Interactive Simulations project to provide “games” that teach students basic physics concepts. The PhET web portal now has 106 physics-based simulations and another 50 or so for other disciplines. It became a go-to place this spring for faculty shifting to online teaching; traffic increased fivefold, says Director Katherine Perkins. In addition, several universities have adopted a handheld device called the iOLab that rents for $50 a semester. With it, students can measure magnetism, light intensity, acceleration, temperature, gravity, and atmospheric pressure, and do basic physics experiments at home. “They like that we trust them and are not just giving them instructions,” says iOLab inventor and physicist Mats Selen at the University of Illinois, Urbana-Champaign. Lewandowski and her colleagues surveyed physics instructors and students about their experiences and posted their findings on arXiv, the physics preprint server, on 2 July. Respondents said online labs work best when projects are open-ended, and online class meetings are kept small. They complained about technical difficulties, students having unequal access to the internet and materials, and longer prep times for both students and instructors. But they reported they could meet most key learning objectives, Lewandowski says, even though “there are lots of things we can't replicate in remote experiments,” such as such as building vacuum chambers or troubleshooting equipment. Some institutions decided this spring that virtual just wouldn't do. The Marine Biological Laboratory (MBL) in Woods Hole, Massachusetts, simply canceled its summer courses. “MBL courses are world-renowned for the intensity of the hands-on nature of the lab work,” says Director Nipam Patel. Students spend long hours with famous faculty and do their own projects using organisms collected locally. “We felt that it would be exceedingly difficult to replicate these experiences as a virtual lab course.” Other institutions will try for a mix of in-person and virtual labs. Suely Black, chemistry chair at Norfolk State University, expects only half of his students will be in lab each week this fall, while the other half will be in online classes analyzing data and writing reports. “The crisis has caused us to more critically evaluate what activities students must experience in the lab setting,” he says. Similarly, this fall, organic chemistry students at the University of Michigan (UM), Ann Arbor, will rotate into the lab in small groups, giving each a taste of the hands-on experience. Personal protection equipment is standard for this course and all the work is done in hoods with excellent air exchange, so “they are really fully protected,” says UM biochemist Kathleen Nolta. Storksdieck, an advocate of online learning, questions the value of smelling fumes or using a pipette. “We have to ask whether all the hands-on taught so far was all that great,” he says. Dominique Durand, a biomedical engineer at Case Western Reserve University, says after he put a master's program in biomedical engineering completely online 5 years ago, he concluded that solving problems was more important than hands-on experience. And University of California, Santa Cruz, ecologist Erika Zavaleta thinks virtual courses will open fieldwork to far more students. “There are things you can do online that you can't do in person,” she adds, such as visiting more places than possible by driving. Even so, Handschy laments that his geology students will not have the 12-hour-a-day immersive interactions with each other and faculty that past classes have had. Natalie White, a rising junior at UNH who took Moore's course on Appledore last year, agrees: “You don't have all the time in between when you walk around the island and can ask impromptu questions.” Appledore Island is the source of some her fondest memories. “I think they are missing out on the community.”
Robots can learn how to find things faster by learning how different objects around the house are related, according to work from the University of Michigan. A new model provides robots with a visual search strategy that can teach them to look for a coffee pot nearby if they're already in sight of a refrigerator, in one of the paper's examples. The work, led by Prof. Chad Jenkins and CSE Ph.D. student Zhen Zeng, was recognized at the 2020 International Conference on Robotics and Automation with a Best Paper Award in Cognitive Robotics. A common aim of roboticists is to give machines the ability to navigate in realistic settings--for example, the disordered, imperfect households we spend our days in. These settings can be chaotic, with no two exactly the same, and robots in search of specific objects they've never seen before will need to pick them out of the noise.
I just heard from those clever chaps and chapesses at Algolux, who tell me they are using an evolutionary algorithm approach in their Atlas Camera Optimization Suite, which -- they say -- is the industry's first set of machine-learning tools and workflows that can automatically optimize camera architectures intended for computer vision applications. As we will see, this is exciting on many levels, not the least that it prompted me to start cogitating, ruminating, and musing on the possibilities that might ensue from combining evolutionary algorithms (EAs) and genetic algorithms (GAs) with artificial intelligence (AI). But before we plunge headfirst into the fray with gusto and abandon (and aplomb, of course), let's remind ourselves that not everyone may be as familiar with things like genetic algorithms as you and yours truly, so let's take a slight diversion to bring everyone up to speed. Personally, I find the entire concept of genetic algorithms to be tremendously exciting. John Henry Holland (1929 – 2015) was an American scientist and Professor of psychology and Professor of electrical engineering and computer science at the University of Michigan, Ann Arbor.
By Rajiv Saxena Police in Detroit, while investigating, were trying to figure out who stole five watches from a Shinola retail store. Authorities mentioned that the thief took off with an estimated $3,800 worth of merchandise. Investigators pulled a security video that had recorded the incident from cameras installed in the store and neighbourhood, which is very common in the US. Detectives zoomed in on the grainy footage and ran the person who appeared to be primary through'facial recognition software'. A hit came back: Robert Julian - Borchak Williams, 42, of Farmington Hills, Michigan, about 25 miles northwest of Detroit. In January, police pulled up to Williams' home and arrested him while he stood on his front lawn in front of his wife and two daughters, ages 2 and 5, who cried as they watched their father being taken away in the patrol car.