Research and innovation in artificial intelligence (AI) in the mining industry operations and technologies sector has declined in the last year.

Prototype drones capable of navigating dangerous and unpredictable environments without crashing could prove useful for search-and-rescue teams. Paolo De Petris at the Norwegian University of Science and Technology and his colleagues have developed a flying drone that aims to avoid crashes altogether. The robot, called RMF-Owl, made its debut while winning a competition hosted by the US Defense Advanced Research Projects Agency, in which it had to navigate an underground mine and perform rescue-related tasks.

BAN MAI, Thailand – As a child, Manit Boonkhiew watched his grandparents plow their rice farm near Bangkok with water buffaloes, and harvest by hand. His parents switched to tractors and threshers, while he now uses a zippy drone to spray pesticide on his field. Manit, who grows rice, orchids and fruit trees on about 40 acres (16 hectares) of land in Ban Mai, is part of a community enterprise that recently acquired a drone under a Thai government program to digitize agriculture. Drones to plant seeds, and spray pesticide and fertilizers are growing in popularity in the Southeast Asian country as it grapples with a labor shortage that worsened during the coronavirus pandemic, with restrictions on movement of workers. "Labor is the biggest challenge for us -- it's hard to get, and it's expensive," said Manit, 56, a leader of the Ban Mai Community Rice Center farm that comprises 57 members with nearly 400 acres of land.

AMP Robotics has extended its partnership with Evergreen, a producer of food-grade recycled polyethylene terephthalate (rPET). Evergreen now has 15 of AMP's robotic sorting systems installed or planned across three facilities. In addition to six robots in Clyde, Evergreen has added six in Riverside, California, and will soon add three in Albany, New York. AMP's technology identifies and sorts green and clear PET from post-consumer bales of plastic soft drink bottles at speeds up to three times faster and at a higher accuracy than manual sorters can achieve. Evergreen then recycles the material into reusable flakes or pellets, which it sells to end markets as feedstock for new containers and packaging.

Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 minutes) with little drift. Prediction errors are on the order of the soft deflection sensor's accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application.

In its early days, robotic process automation emerged from rudimentary screen scraping, macros and workflow automation software. Once a script-heavy and limited tool that was almost exclusively used to perform mundane tasks for individual users, RPA has evolved into an enterprisewide megatrend that puts automation at the center of digital business initiatives. In this Breaking Analysis, we present our quarterly update of the trends in RPA and share the latest survey data from Enterprise Technology Research. The new momentum in RPA is around enterprisewide automation initiatives. Once exclusively focused on back office automation in areas such as finance, RPA has now become an enterprise transformation catalyst for many larger organizations. Initially focused on cost savings in the finance department and other back-office functions, RPA has moved beyond the purview of the chief financial officer.

The latest research study released by HTF MI evaluating the market risk side analysis, highlighting opportunities and leveraged with strategic and tactical decision-making support. The market Study is segmented by key a region that is accelerating the marketization. The oil and gas (O&G) industry faces many severe challenges. The shortage of easily accessible hydrocarbon reserves forces companies to use remote reserves that are hard to discover, costly, and risky. Moreover, sustainability concerns are shifting demand away from O&G toward cleaner sources, and COVID-19 has further suppressed the demand.

AI is no longer exclusively for digital native companies like Amazon, Netflix, or Uber. Dow Chemical Company recently used machine learning to accelerate its R&D process for Polyurethane formulations by 200,000x -- from 2–3 months to just 30 seconds. A recent index from Deloitte shows how companies across sectors are operationalizing AI to drive business value. Unsurprisingly, Gartner predicts that more than 75% of organizations will shift from piloting AI technologies to operationalizing them by the end of 2024 -- which is where the real challenges begin. AI is most valuable when it is operationalized at scale. For business leaders who wish to maximize business value using AI, scale refers to how deeply and widely AI is integrated into an organization's core product or service and business processes.

What if there's a quick way to screen molecules and predict their reactivity and other properties? Certainly this will make drug and material design much faster because chemists could then focus more on the most promising compounds instead of trying them all. This is what the Merck Molecular Activity Challenge somehow illustrates. Here, the goal is to predict biological activities of different molecules, both on- and off-target, given numerical descriptors generated from their chemical structures. In other words, we have to predict whether a certain molecule will become highly active towards the intended target and "inert" to others (thereby minimal or zero side effects).

An expert on the future of food responds to JoeAnn Hart's "Good Job, Robin." The first time I seriously considered crickets as the food of the future was in late 2015 during a presentation by undergraduates. Their policy proposal outlining how the adoption of insect protein in the Los Angeles Area could help insulate the region from some of the impacts of climate-change included a tasting of a recent-to-market, paleo-friendly, cricket-based protein bar. As I sunk my teeth into the slightly gummy, peanut-buttery bite being passed around the classroom, my mind flashed between the grim food futures presented in science fiction novels and the much smaller collection of hopeful fiction portrayals of delicious future feasts. What is it about our contemporary anxieties that makes it so easy to imagine such dystopic food futures?