The pandemic caused many changes and hiccups within the U.S. economy, including several supply chain issues. While things are slowly getting back to normal, there are still some supply chain problems that companies across the country are trying to overcome. If there was one "positive" to the pandemic, however, it pointed out flaws and vulnerabilities in the chain. It's up to shipping and freight professionals to learn how to fill in those gaps by utilizing technology, so these major issues don't happen again. AI (Artificial Intelligence) is a promising technology that can make supply chains more resilient.

The pandemic ushered us all into this experience together, and now that we have "graduated" into a post-pandemic world, we can reflect on the lessons it has taught us. The lessons include living and working together to create a world and organisation unified by a purpose. It also helped shake the mindset of the global economy as we strived to make the impossible possible. Instead of employees following a fixed schedule, it has transitioned to employees being on-demand as per their choice of time and place. As a result, employees are now free from the office walls - it is limitless, and they can meet the needs of their companies and consumers.

During crises, we are confronted with an opportunity to think differently and create rapid change that can have long-lasting impact. The COVID-19 crisis is no exception. According to research by McKinsey & Company, COVID-19 has dramatically accelerated the adoption of new technologies, and many of these are here to stay. Organizations were forced to adopt new technologies overnight to survive, or risk becoming irrelevant. As a result, almost every sector has altered the way they interact and do business with their customers over the past two years.

As we navigate the post-pandemic world (and grapple with Covid's continual resurgence), voice technology supported by AI will be healthcare's next big tool. Artificial intelligence rocketed up the hype cycle during the pandemic, but no ascension is more fascinating than voice technology. With use cases in multiple industries, including the one on everyone's mind--healthcare, voice tech investments, and deployment will only increase as we navigate a post-Covid world. Voice tech has multiple use case potentials even outside the common customer service applications. Researchers at Carnegie Mellon, for example, pioneered voice tech to identify potential Covid infections from the sound of someone's voice and breathing patterns.

NEW YORK (Reuters) - Thomson Reuters Corp will streamline technology, close offices and rely more on machines to prepare for a post-pandemic world, the news and information group said on Tuesday, as it reported higher sales and operating profit. The Toronto-headquartered company will spend $500 million to $600 million over two years to burnish its technology credentials, investing in AI and machine learning to get data faster to professional customers increasingly working from home during the coronavirus crisis. Thomson Reuters' New York- and Toronto-listed shares each gained more than 8%. It aims to cut annual operating expenses by $600 million through eliminating duplicate functions, modernizing and consolidating technology, as well as through attrition and shrinking its real estate footprint. Layoffs are not a focus of the cost cuts and there are no current plans to divest assets as part of this plan, the company said.

The vision of Robots and Humans working together has been popularized by numerous Hollywood movies, comic books and the media for many decades now. Success stories about the application of automation in the manufacturing industry date back to the early 1980’s, when welding robots demonstrated efficiency and resilience to deliver on time and increased the overall supply. And ever since, robots have been used for a variety of applications such as painting, assembly, disassembly, pick and place for printed circuit boards, material handling, product inspection, and testing, all accomplished with high speed and precision. In the past few years, however, the world is seeing a significant shift towards AI-enabled robots that are changing the game by bringing various levels of autonomy into the picture. If we consider the example of the labor-intensive task of warehouse piece picking,  AI-enabled robots are learning to handle millions of objects with minimum help from humans. What once required individual item registration and programming of robots, can now be accomplished with self-directing or autonomous robots using deep learning algorithms. This in turn, is helping industries cut costs and improve profits in the long run. Further, with the dawn of COVID-19, the way we patronize restaurants and shops and see our doctors has changed drastically. From collaborative robots (co-robots) to robots with high levels of autonomy, the trend continues towards the application of Autonomous Mobile Robots (AMR) in every industry and retail setting; more so as societies are restructuring places of work and pleasure to minimize human contact. The accelerated adoption of AMRs is being seen in many frontline roles from spraying disinfectants to delivering & serving food to customers, in outdoor and indoor urban hotspots. A key advantage of using AMRs is that they are able to reliably do these repetitive physical tasks when many workers aren’t safely able to or willing to set foot in these areas. As AMRs are becoming more and more competent, a few popular ones that are gaining traction during this pandemic are discussed below.   TELEPRESENCE ROBOT Telepresence Robots or Virtual Assistance Robots, now more than ever, are revolutionizing the way we work or learn remotely. They enable telecommuters, doctors, remote workers, and students to feel more connected to their colleagues by giving them a physical presence where they can’t be in person.   Image Credit: Using robots to enable patients to be inspected remotely In recent times, Telepresence robots are being put to use to enable interactions with COVID-19 patients in isolation wards. These semi-autonomous robots could be teleoperated over the Wi-Fi, to visit the patients and provide a live video link to their loved ones or to deliver their food and medication.   DISINFECTANT ROBOT  In the post pandemic world, disinfecting shared public places has been a tricky problem to solve. A non-intrusive solution widely adopted in recent times is UV-C light, but due to its adverse effects on human skin, trolleying it would look somewhat like the image below.   Image credit: UV-C based disinfection trolley by rapid cleaning of hospital environment, helping in the fight against COVID-19 Enter AMR, mounted with a UV-C lamp as a payload, which would traverse autonomously in a designated area.                                                                                     Image Credit: Weston Robot   This is accomplished by using the mobile app where the user creates a map of the area and chooses the waypoints for the robot to traverse. The robot then follows the waypoints and stops at each waypoint, till the disinfection job is done. Also, it returns to the charging station once the battery is below a threshold eliminating the need for human intervention. A swarm of these robots could be used in and around the areas where the most interactions occur such as hospitals, railway stations, airports, etc. An intrusive solution would be to air-blast disinfectant liquids similar to the ones used in agricultural spraying, to increase the chlorine content in the air and reduce the possibility of aerosol transmission.   Image Credit: Robots deployed to disinfect open spaces This fully autonomous solution is basically an AMR, mounted with a sprayer mechanism, which can navigate to the decontamination area using pre-built maps giving  the technical staff less exposure to these highly concentrated chemicals while working in an entirely safe and risk-free environment. The range of its spray devices can reach up-to 30 feet.   LAST-MILE DELIVERY ROBOTS As door delivery businesses saw a huge increase in demand during the pandemic, Last-Mile delivery robots found application as a reliable and safe contactless delivery system. These robots are an alternative to human food delivery drivers from companies like Uber Eats and DoorDash, which perform tasks that a person cannot do safely. These companies have created and deployed cool new robots with the intelligence to navigate city streets to deliver orders from selected restaurants to the customer location using a mobile app, while avoiding dynamic obstacles like pedestrians.   Image Credit: Autonomous delivery robot   The robot’s body is equipped with a storage bin with a locking compartment where the restaurant stores the delivery package and the bin only unlocks upon authentication by the customer at her location during delivery. Typically, these robots are equipped with cameras and computer vision driven by machine learning. They can detect and classify what they see, and tell the difference between a car, a person, or a wall. While these robots are definitely cool tech; procuring, running and maintaining fleets of robots can be prohibitively expensive. To circumvent this, the solution that small restaurant owners are turning to is the clever ‘Robot-as-a-Service’(RaaS) business model for food delivery, which is becoming more crucial as Covid-19 reshapes the gig economy.   ROBOT AS A SERVICE Many are now familiar with the concept of Software as a Service (SaaS) or Big Data as a Service (BDaaS) or Platform as a Service (PaaS) where the intent is to democratize technology while lowering the barrier to entry for businesses, large and small alike. One of the new areas, this philosophy is becoming more prevalent, is “Robot as a Service” (RaaS), a cloud-based “robotic rental” solution used for both B2B or B2C businesses. RaaS takes the capabilities of robotics and removes the upfront cost of robot installation with large amounts of computing power, utilities, and knowledge.  And so, small- and medium-sized businesses are increasingly experimenting with RaaS because of its flexibility, scalability, and lower cost of entry compared to traditional robotics programs. For example, finding sufficient  numbers of workers in a warehouse, for online retailers during seasonal surges is quite the challenge. With the RaaS model, these seasonal labor shortcomings can be mitigated without investing in equipment that won’t be used in slower periods while still being able to quickly scale up to meet the high demand. RaaS might be the answer for businesses, trying to figure out how to improve productivity or reduce risk, but always thought, robots were out of their price range.   ROBOTICS AT IGNITARIUM Robotics and in particular Autonomous Mobile Robots is an area where Ignitarium has been developing technology solutions for the warehouse use cases. Robotics as a theme started as a R&D thread to leverage the existing skills in computer vision and AI/ML. In the past year, we have demonstrated various use cases on sensor fusion, integration of Lidars & Radars, visual odometry using RGB-D Cameras, path planning, obstacle avoidance, integrating with deep learning modules for object Classification / Detection / Tracking. Our vision is to create a software package which is hardware agnostic, for use  across hardware platforms with minimal customization.     CONCLUSION The COVID-19 pandemic has accelerated the adoption of Autonomous Mobile Robots (AMRs) such as Telepresence, Disinfectant, Last-mile delivery robots. Roboticists are also seeing adaptation of AMRs to new niches and are exploring new avenues. Although the robotics wave is changing the way services and products are sold, there are still challenges to overcome like the amount of customization required, both in hardware and software for the robots to adapt to customer specific needs. Regardless of the hurdles, RaaS will be the inevitable solution many organizations seek either with hardware & software or software-only flavors.

The promise of artificial intelligence finally came good in 2018 and 2019, with a wider adoption of AI - from its use in detecting and combating fraud in financial institutions, through to sophisticated analytics tools in contact center. There are a host of use cases showing the value of a future-facing AI strategy, leveraging accurate and collectable data to save time, improve efficiencies, and reduce operational costs. In fact, a recent KPMG report states that five of the most AI-mature companies are spending $75m annually on AI talent, indicating the increasing importance of using AI by business leaders. The same report also finds that analysis of voice data is a high priority AI initiative, but there are some critical foundational elements that are maybe not being given the consideration they should. Organizations interested in adopting this new technology - and those that already are - must remember that AI and analytics tools are fueled by data, and the output is directly correlated to the quality of the input.

Although the world is still battling the coronavirus, one Italian designer is looking toward a post-pandemic world to help commuters travel safely and securely to their destination. Andrea Ponti released a gallery of concept designs for a private jet-like drone that carries up to four passengers while they sit in single seats with soft fabric and leather cushions. Called'Kite,' the craft would use a propulsion system of four double-helix rotors and features a pair of LED headlights to help with landing and low-altitude flying. Ponti chose the name as a reference to the black kite, a well-known bird in Hong Kong, as he aims to use the air taxis in China's Greater Bay Area. This area consists of nine cities and two special administrative regions – locations that are suffering economically due to travel restrictions amid the coronavirus.

With its unique ability to identify and'learn' from data patterns and to develop predictive mappings between variables – machine and deep learning – artificial intelligence (AI) has proved to be an indispensable tool in the fight against the coronavirus pandemic. AI has enabled the deployment of predictive models of potential disease contagion and containment, and has been used for screening and tracking patients. AI has been deployed across the globe to improve understanding of the potential consequences of the viral infection for different economy sectors. Companies have increasingly relied on machine-learning-enabled systems to reengineer production delivery in the face of a massive disruption in supply chains. Policy-makers have also turned to AI technologies due to their great promise in strengthening the quality of remote education delivery, at times where schools and education systems struggle to remain accessible to learners.

Whether you turn to news outlets, tech magazines, or academic sources for insight, you're likely to hear that the COVID-19 pandemic is going to drive massive growth in automation, especially via robots.1 The arguments in favor of this view seem reasonable: Main Street might look dead, but companies that provide shippable goods have been facing double, triple, or even 10 times their previous demand. Robots, the thinking goes, should be able to reliably do that repetitive physical work when many workers aren't safely able or willing to set foot in the building. What's more, access to the technology is getting less expensive, with "robots as a service" models allowing companies to pay per touch rather than dipping into precious capital reserves. And robots are becoming more capable. In just the past few years, for example, we've seen a small number of companies building and selling AI-enabled robots to pick things out of bins, handle parts, tend machines, and test the latest electronics.