To better understand the behavior of image classifiers, it is useful to visualize the contribution of individual pixels to the model prediction. In this study, we propose a method, MoXI~($\textbf{Mo}$del e$\textbf{X}$planation by $\textbf{I}$nteractions), that efficiently and accurately identifies a group of pixels with high prediction confidence. The proposed method employs game-theoretic concepts, Shapley values and interactions, taking into account the effects of individual pixels and the cooperative influence of pixels on model confidence. Theoretical analysis and experiments demonstrate that our method better identifies the pixels that are highly contributing to the model outputs than widely-used visualization methods using Grad-CAM, Attention rollout, and Shapley value. While prior studies have suffered from the exponential computational cost in the computation of Shapley value and interactions, we show that this can be reduced to linear cost for our task.

ChristianaCare this week announced some new help to augment its workforce: robotic assistants that can help nurses and other hospital staff spend more time with patients by automatic certain time-intensive tasks. WHY IT MATTERS The technology, called Moxi, is a collaborative robot that can work alongside nurses and interact with them directly, performing nonclinical tasks such as deliveries and pickups to enable them to focus on care delivery. ChristianaCare purchased five of these 300-pound "cobots" – which can work 22-hour shifts, be fully charged in two hours and carry up to 70 pounds – with a $1.5 million grant from the American Nurses Foundation. The Moxi cobots will soon be integrated with ChristianaCare's Cerner electronic health record platform, officials say. Connected to the EHR data, the cobots can anticipate the needs of both clinicians and patients – and perform tasks without human involvement.

Venture capital firms are eager to allocate money into robotics firms in a wide range of industries from shipping to healthcare as more automation became a focus during the global pandemic. In 2021, funding globally for robotics and drone companies rose to $14.9 billion, according to PitchBook. The amount of funding raised for robotics in 2022 has been steady. By January, VCs allocated $560 million of funding into robotics startups, excluding the round for Wandelbots, a German industrial robotics company that raised $84 million for its Series C round in January. The funding for the company's no-code platform came from U.S. investor Insight Partners, which led the round and was also supported by its existing backers - Microsoft (MSFT) - Get Microsoft Corporation Report, 83North, Next47, Paua, Atlantic Labs and EQT.

Since February, the nurses at Mary Washington Hospital in Fredericksburg, Virginia have had an extra assistant on their shifts: Moxi, a nearly six-foot tall robot that ferries medication, supplies, lab samples, and personal items through the halls, from floor to floor. After two years of battling Covid-19 and related burnout, it's been a welcome relief. "There's two levels of burnout: There's'we're short this weekend' burnout, and then there's pandemic burnout, which our care teams are experiencing right now," says Abigail Hamilton, a former ICU and emergency room nurse that manages nursing staff support programs at the hospital. Moxi is one of several specialized delivery robots that has been developed in recent years to ease the strain on health care workers. Even before the pandemic, nearly half of US nurses felt that their workplace lacked adequate work-life balance.

People often ask me about the real-life potential for inhumane, merciless systems like Hal 9000 or the Terminator to destroy our society. Growing up in Belgium and away from Hollywood, my initial impressions of robots were not so violent. In retrospect, my early positive affiliations with robots likely fueled my drive to build machines to make our everyday lives more enjoyable. Robots working alongside humans to manage day-to-day mundane tasks was a world I wanted to help create. Now, many years later, after emigrating to the United States, finishing my PhD under Andrew Ng, starting the Berkeley Robot Learning Lab, and co-founding Covariant, I'm convinced that robots are becoming sophisticated enough to be the allies and helpful teammates that I hoped for as a child.

The concept of robotics is as wide as the landmass of the planet. Robotics is a combination of applied science, engineering, and computer science. Perhaps the healthcare industry, one of the most profitable industries, across the world seeks robot applications to progress. Subsequently, medical robotics companies have earned a great deal of trust across the world and are booming remarkably. Technologies used for medical robotics include mechanisms such as AI-powered machinery, software, and applications, physical as well as virtual.

We give robots some pretty scary and stressful jobs: cleaning up nuclear sites, inspecting pipelines from the inside, exploring the frozen wastes of Mars. The arrival of the coronavirus has transformed more familiar settings, like grocery stores and hospitals, into potentially hazardous environments as well. Erika Hayasaki, a writer and journalism professor in California, learned that the pandemic is leading some organizations to speed up their automation plans in order to aid front-line workers. Her feature article appears in the July issue of MIT Technology Review. In this episode of Deep Tech, she describes her reporting on companies in California and Texas that are rushing to meet the demand, and asks whether the new wave of safety-driven automation could ultimately force more human workers into retraining programs. Amazon's Investment in Robots is Eliminating Human Jobs, December 5, 2017 Wade Roush: The day when robots show up in your workplace may be closer than you think. BBC Business News: The robots are coming.

Inside a Schnucks grocery store in St. Louis, Missouri, the toilet paper and baking ingredients are mostly cleared out. A rolling robot turns a corner and heads down an aisle stocked with salsa and taco shells. It comes up against a masked customer wearing shorts and sneakers; he's pushing a shopping cart carrying bread. The robot looks something like a tower speaker on top of an autonomous home vacuum cleaner--tall and thin, with orb-like screen eyes halfway up that shift left and right. A red sign on its long head makes the introductions. Tally freezes, sensing the human, and the customer pauses, seeming unsure of what to do next. Should he maneuver around the robot? Or wait for it to move along on its own?

Diligent Robotics, maker of an autonomous robot assistant for hospitals, has raised $3 million in seed funding. The raise was headed by True Ventures and Ubiquity Ventures, as well as Next Coast Ventures, Capital Factory, Pathbreaker Ventures, Boom Capital, Grit Ventures and other unnamed angel investors. This adds to another $2.1 million round announced back in the beginning of 2018, as well as a $725,000 National Science Foundation grant. This week's funding news was complemented with an announcement that the startup's hospital robot, called Moxi, is exiting beta testing and has entered market with its first official rollout in a Texas Hospital. While Diligent Robotics' broad aim is to develop robotic assistants for a range of chores or activities, the company has so far focused on healthcare use cases for its technology with Moxi.

Diligent Robotics's Moxi is a robot created by Andrea Thomaz (a former robotics professor at UT Austin and Georgia Tech's Socially Intelligent Machines Lab) and Vivian Chu (one of Thomaz's former grad students); they funded by a National Science Foundation grant to create a robotic nursing aide that is designed to do routine, non-human-interaction chores for nurses with a minimum of effort from nurses. For example, when a patient is discharged, a Moxi can fetch and deliver an "admission bucket" (a standard package of supplies for a new patient) automatically; some nurses in a limited trial say they never saw Moxi undertake this chore, but rather simply found that every recently vacated room had an admission bucket waiting at the appropriate time. The design is meant to relieve nurses of mechanical, robotic tasks (errands) and free them up to concentrate on care and humans. After four one-month beta trials, the company says Moxi robots do that very well, but they were surprised by the affection that both nurses and patients expressed for the robots, which was so intense that the technicians began to schedule an hour-long "social lap," in which the robot wanders around and makes heart-emoji eyes at patients. The physical design of Moxi reflects Thomaz's "Socially Intelligent Machines" research; they are designed to be cute and nonthreatening, and to give social cues that humans intuitively grasp, like looking in the direction they're moving.