At the Techonomy 23 conference, Rebecca Yeung, the corporate vice president for operations science and advanced technology at FedEx, delves into the cutting-edge technologies being developed and utilized by her company, particularly in the realms of robotics and artificial intelligence. Her focus is on how these technologies are revolutionizing the company’s operations, enhancing efficiency, safety, and productivity.

Yeung emphasizes the significance of robotics and unmanned, autonomous technologies in shaping FedEx’s future. She notes that FedEx’s approach to robotics is not to start with the technology itself but to first identify the problem that needs solving. This approach is crucial in a complex environment like FedEx’s, where they handle a diverse array of packages differing in size, shape, and weight, requiring advanced robotics and AI-driven solutions.

A key aspect of FedEx’s technological advancement is the development of sophisticated AI algorithms, advanced computer vision, and high-speed processing capabilities, driven by GPU advancements. These technologies enable robots to make smarter decisions, particularly in handling the diverse and unpredictable nature of package sorting and transportation. Yeung points out that the convergence of these technologies has made robots much more capable and intelligent, moving beyond simple, repetitive tasks to more complex and varied functions.

Working Like, and Safely with, Humans

Safety is a top priority in FedEx’s operations, and Yeung underscores the importance of integrating safety into the design of robotics systems. She highlights the involvement of frontline team members in the design process, ensuring that the technology is not only efficient but also safe and intuitive for human interaction. FedEx’s approach is to develop robots that can safely navigate their environment and interact seamlessly with human workers.

Yeung also discusses the challenges of automating tasks like truck loading, where robots need to replicate human-like decision-making and tactile sensations. These robots must efficiently and safely stack packages, considering factors like weight and spatial optimization, akin to playing Tetris. The robots utilize advanced force control mechanisms and rapid generative world-building algorithms to achieve this.

FedEx is exploring various areas of automation, such as palletization, depalletization, and trailer unloading. The focus is on easing strenuous tasks for human workers and improving overall productivity. Yeung also touches upon FedEx’s experiments with autonomous vehicles, emphasizing the need for safety and redundancy in vehicle systems.

Finally, Yeung expresses excitement about the future of AI, seeing it as a powerful tool to transform operations and improve safety, efficiency, and productivity. Her vision is that we are only at the beginning of realizing AI’s full potential and its ability to revolutionize industries like logistics and transportation.

(This summary was prepared using generative artificial intelligence.)

Climate change, a growing population, and shifts in the labor market all jeopardize our ability to feed ourselves in the coming decades. Currently the gap between the expected gains in agricultural productivity and the necessary gains to sustain humanity is projected to widen considerably.

Artificial intelligence and robotics offer some tools to address this shortfall. In this discussion, two professors of the University of Florida–Carlos “Charlie” Messina and Changying “Charlie” Li describe their work on berries, corn, and other crops.

Sensing and Analyzing

Although they don’t currently work together, the types of work the two Charlies do is complimentary. Messina uses AI to map key aspects of plants (phenotype), such as their productivity, to different genetic variations (genotype) that correspond to those attributes. With this data, and powerful algorithms, he is able to virtually breed scores of different plant varieties in an effort to identify with the most productive and resilient strains. Messina used these methods to improve the drought tolerance of corn (maize) while working for DuPont. He’s now applying the technology to breed more productive strawberries, among other projects.

Charlie Li collects the kinds of phenotype data that can inform Messina’s work. He’s developed a modular, data gathering robot, called MARS, that can move through fields to collect visual information about the health and productivity of plants, as well as use depth sensors to understand their physical attributes. Li combines this information with other sensing technologies, such as LIDAR and hyperspectral sensors (working in near-infrared) to study attributes of plants and individual fruits.

Breeding Better Blueberries

Li’s research has primarily been on blueberries, but it is transferable to other crop types. In addition to helping improve yields, Li is also studying ways to improve robotic harvesting, which he sees as critical as fewer workers show interest in the low wages, hard labor, and erratic schedules of harvesting jobs. Li is studying the best shape of plants to facilitate mechanical harvesting, as well as ways to minimize bruising of fruit that can spoil parts of the harvest. For the latter, he has developed a blueberry-shaped sensor to measure pressure and stress of harvesting machines. In other words, a robotic blueberry is assessing the work of a robotic farm hand. You can read more about Charlie Li’s research in the Fall issue of Worth magazine.

At the Techonomy 23 conference, Mutale Nkonde, AI policy analyst and CEO of AI for the People, discusses the role for regulations in AI, including the U.S. Algorithmic Accountability Act, which she helped develop. She also describes the financial opportunities for companies that make responsible AI a selling point.

AI is fostering a Renaissance in the philosophy of human consciousness–including promoting existential dread–says Nicholas Dirks of the New York Academy of Sciences, in conversation with X. Eyeé of Malo Santo and Dan Costa of Worth and Techonomy–at Techonomy 23: The Promise and Peril of AI.

Every digital interaction you have is powered by artificial intelligence (AI). Our online presence, our actions, our clicks, and our views create and power the machine-learning for AI that companies, governments, and organizations use in their daily business.

This is no surprise, and intelligent, or AI-powered, customer service is something we’ve come to expect. Real-time chat functionality that has answers at our fingertips and advertising that is served up based on our activities and preferences are the norm. AI has been used in marketing and customer service since the early aughts when data collection and analysis became possible through the internet.

Today, we can use the same fundamentals to power the modern age of workers.

The consumerization of technology can be seen in everything we do at work today. From the Bring Your Own Device trend that started in the early 2000s to the post-pandemic practice of availability and ability to work from anywhere, the on-demand, real-time, always available, application-driven world is how we are conditioned to work.

And now there is a new and exciting work world that is taking shape. All built on the effect of AI in the enterprise. The employee experience is being transformed, and employee productivity is at an all-time high because of AI.

Let me be clear though, employees are not being replaced by AI. In fact, the cases of the greatest value are realized when AI augments the human experience. AI-enabled does not mean human-less.

In talking with BMC customers, there are a few areas where AI has had the most effect.

First, Generative AI has taken the world by storm. In a survey from McKinsey, 40% of their respondents shared that that their organizations will increase their AI investments because of advances in gen AI. It has drastically improved employee productivity and efficiency to automate tasks and provide employees with the insights and access to knowledge that help them operate with fewer errors and much more quickly.

One example I’ve heard BMC chief product officer, Ali Siddiqui, talk about is supporting code and application release. For application owners, the test and deploy process can be quite time consuming and ultimately have impact beyond the release manager’s purview. Gen AI can now be used in the DevOps process to predict and rectify any release impact, enhancing the human judgment and expanding visibility into the impact.

Another area that is quickly taking shape in the IT world is AIOps—or artificial intelligence for IT operations. With IT organizations wrangling a complex world of tools, technologies, and multi mode infrastructures in a world moving as fast as we do, they are tasked with nearly the impossible: real-time, personalized, digital business. A world-renowned and respected ratings agency shared with me that they’ve started their AIOps journey simply by deploying observability across the organization so they can assure their clientele of always-on, always-accurate, and up-to-date market information. Sounds simple enough, right?

Their IT operations are dependent on global market data, publicly listed companies’ earnings, global geo-political impacts, the political climates, and a global workforce that needs the most modern and user-friendly tools to serve their clientele. The scope of systems spread, data sources, and business applications that are in play around the clock and around the world puts incredible demand on the organization’s central IT group. And now, using AIOps, they are able to observe, monitor, and respond (more often than not, autonomously) to the changing needs of the business with always-on reliability.

One last area that I want to call out—near and dear to my own heart—is in the area of sustainability. We have the great fortune as a global technology company to drink our own champagne to support our impact on the environment. The BMC Global Command Center (our name for our network operations) has been using AI in our own IT operations for four years to optimize the use of precious resources and manage our carbon footprint. We operate as a global organization with our own data centers and hosted facilities to serve our customers, with an eye on how we can best use our own solutions to monitor, manage, and autonomously adjust our own energy consumption and carbon outputs for less impact.

We can all do our part as employees and be proud of the organization we work for, knowing that we’re operating in a way that supports environmental efforts.

AI is now on every C-Suite agenda and is often the topic that dominates every conversation from the Board to the individual contributor. Along with the technological advances that AI, and the fast-growing use of generative AI, can bring to our businesses, there is an incredible impact to be realized in the employee experience.