Blog: The Inevitable March Toward AI Robotics Continues
Blog: The Inevitable March Toward AI Robotics Continues
Amid pressure to “get the work done” and need for affordable, creative solutions, organizations are increasing embracing robots and AI in nearly every industry from reclamation to manufacturing.
The phrase “necessity is the mother of invention” may best encapsulate the growing embrace of robots and AI in every industry from reclamation, warehousing, manufacturing, food production, and more. As organizations face pressure to “get the work done” they are driven, by design, to search for affordable, creative solutions.
The story of Glacier, a San Francisco startup whose product combines robotics and AI to work in the recycling process, is a perfect example. The organization’s solution is a direct response to the need by the industry that faces a turnover rate of workers of 22 percent and an injury rate that runs around 4.7 per 100 workers (among the highest in the country per profession).
The world calls on mechanical engineers to work on the big tasks. And this is no more evident than in the warehousing and ecommerce industry. The second-largest employer in America, Amazon employs around 1.5 million workers and is planning to move away from its reliance on human employees. According to internal Amazon documents reviewed by The New York Times, some departments within the company plan to replace employees with robots to avoid hiring more than 160,000 people needed to staff its U.S. warehouses by 2027.
Said Tye Brady, chief technologist for Amazon Robotics, “The goal is to make technology the most practical, the most powerful tool it can be—so that work becomes safer, smarter, and more rewarding.” Blue Jay and Project Eluna build on recent advances like Vulcan and DeepFleet, extending Amazon’s approach to physical AI—technology that learns from contact, coordinates at scale, and supports people in the real world.
The most recent Federal shutdown just may hasten robots and AI assisted help when it comes to the work carried out by the Transportation Security Administration (TSA) and air traffic control under the Federal Aviation Administration that manages U.S. airspace. In fact, in a July press release, the TSA issued a Request for Information for “solutions” that will help make airport screening “faster, more secure, and easier on the traveling public.”
TSA is looking for solutions that will, in part, reduce workforce requirements and incorporate AI-driven passenger and baggage screening. And most in the industry understand that the current air traffic system needs updating with AI and Machine Learning (ML) technologies as part of the solution.
The European Union is already studying this as part of the Single European Sky Air Traffic Management Research project that identified projects that directly applied AI/ML models and techniques. And despite the complexity and magnitude of airspace operations, data-driven AI solutions are being looked at to provide actionable information for complex decision-making processes that controllers face and assist them in improving the efficiency and safety of operations.
In 2025, it may be difficult to find an industry not affected by robots and AI. Technology is replacing workers where we shop, in fact helping U.S. food stores save more than $20 billion on running costs in 2023. And its push goes straight to where food is produced in field and farm. Drones and other robots continue to replace some field workers and AI such as H-GNNLM-CropField, is used for crop health prediction and autonomous agricultural management.
However, most looking at the situations understand that robots, AI, and human workers will eventually be collaborating to get the work done safely and efficiently. No industry is this more apparent than in manufacturing where key technologies include collaborative robots (cobots). And industry 5.0 builds on advances, but with a strong emphasis on collaboration between humans and machines. This is especially important when looking at worker safety.
One very real challenge to automation is the availability of low-cost labor. Modern India, with its large population is also marred by low productivity and low-tech automation. In fact, relying too heavily on a low-wage workforce approach has resulted in stunted competitiveness as India is disincentivized from investing in productive production techniques like other developing nations.
And despite all the buzz, “many business leaders still feel unclear about what LLMs actually are, how they work, or what’s really possible with them,” wrote Justice Erolin, chief technology officer at BairesDev, in a recent blog post. Forbes agreed that the movement is not black-and-white, AI robots can displace workers in repetitive roles such as warehouse pickers, and assembly line operators, "but they also spark demand for new skills. MIT research shows companies adopting robots often grow, hiring more workers overall, while those that don’t automate lose ground and cut jobs.”
Cathy Cecere is membership content program manager.
The story of Glacier, a San Francisco startup whose product combines robotics and AI to work in the recycling process, is a perfect example. The organization’s solution is a direct response to the need by the industry that faces a turnover rate of workers of 22 percent and an injury rate that runs around 4.7 per 100 workers (among the highest in the country per profession).
The world calls on mechanical engineers to work on the big tasks. And this is no more evident than in the warehousing and ecommerce industry. The second-largest employer in America, Amazon employs around 1.5 million workers and is planning to move away from its reliance on human employees. According to internal Amazon documents reviewed by The New York Times, some departments within the company plan to replace employees with robots to avoid hiring more than 160,000 people needed to staff its U.S. warehouses by 2027.
Said Tye Brady, chief technologist for Amazon Robotics, “The goal is to make technology the most practical, the most powerful tool it can be—so that work becomes safer, smarter, and more rewarding.” Blue Jay and Project Eluna build on recent advances like Vulcan and DeepFleet, extending Amazon’s approach to physical AI—technology that learns from contact, coordinates at scale, and supports people in the real world.
The most recent Federal shutdown just may hasten robots and AI assisted help when it comes to the work carried out by the Transportation Security Administration (TSA) and air traffic control under the Federal Aviation Administration that manages U.S. airspace. In fact, in a July press release, the TSA issued a Request for Information for “solutions” that will help make airport screening “faster, more secure, and easier on the traveling public.”
TSA is looking for solutions that will, in part, reduce workforce requirements and incorporate AI-driven passenger and baggage screening. And most in the industry understand that the current air traffic system needs updating with AI and Machine Learning (ML) technologies as part of the solution.
The European Union is already studying this as part of the Single European Sky Air Traffic Management Research project that identified projects that directly applied AI/ML models and techniques. And despite the complexity and magnitude of airspace operations, data-driven AI solutions are being looked at to provide actionable information for complex decision-making processes that controllers face and assist them in improving the efficiency and safety of operations.
Blog: Engineers Integral to a Successful Circular Economy
Mechanical engineers are on the frontlines of sustainability—from reduce, reuse, and recycle, to the importance of delivering success in the circular economy.
However, most looking at the situations understand that robots, AI, and human workers will eventually be collaborating to get the work done safely and efficiently. No industry is this more apparent than in manufacturing where key technologies include collaborative robots (cobots). And industry 5.0 builds on advances, but with a strong emphasis on collaboration between humans and machines. This is especially important when looking at worker safety.
One very real challenge to automation is the availability of low-cost labor. Modern India, with its large population is also marred by low productivity and low-tech automation. In fact, relying too heavily on a low-wage workforce approach has resulted in stunted competitiveness as India is disincentivized from investing in productive production techniques like other developing nations.
And despite all the buzz, “many business leaders still feel unclear about what LLMs actually are, how they work, or what’s really possible with them,” wrote Justice Erolin, chief technology officer at BairesDev, in a recent blog post. Forbes agreed that the movement is not black-and-white, AI robots can displace workers in repetitive roles such as warehouse pickers, and assembly line operators, "but they also spark demand for new skills. MIT research shows companies adopting robots often grow, hiring more workers overall, while those that don’t automate lose ground and cut jobs.”
Cathy Cecere is membership content program manager.
The use of robotics in industrial settings continues to accelerate at a rapid pace. Explore this collection to learn more about automation, cobots, AI-enabled robots, customized robots, and drones.