by Gary Mintchell | Oct 22, 2025 | Robots, Technology
Crazy Stupid Tech, Interview of Rodney Brooks with Om Malik.
iRobot Founder: Don’t Believe The (AI & Robotics) Hype!
This is a must read interview for all of us interested in the current technology trajectories. Veteran technology journalist Om Malik interviewed iRobot Founder Rodney Brooks about robots, AI, and technology trajectories.
We are in the middle of another massive technological wave, thanks to generative artificial intelligence and its offshoot, robotics. A tanker load of money is being poured into these two areas, and it has come with increasingly breathless promotional activity. It warrants a reality check. For that, I turned to Rodney Brooks, who has spent decades in both arenas. The Australian-born Brooks was a Professor of Robotics at MIT and former director of the MIT Computer Science and Artificial Intelligence Laboratory. He has founded three companies: iRobot (maker of the Roomba), Rethink Robotics, and now Robust.AI, which now builds warehouse automation robots. He is an academic who entered the startup arena and hasn’t left it since.
Rodney: At MIT, I taught big classes with lots of students, so maybe that helped. I came here in an Uber this morning and asked the guy what street we were on. He had no clue. He said, “I just follow it.” (‘It’ being the GPS—Ed.) And that’s the issue—there’s human intervention, but people can’t figure out how to help when things go wrong.
Rodney: My companies have always been about letting the person still have control. The previous one, Rethink Robotics, involved people showing the robot what to do. The Roomba had a handle; if it got stuck, you could pick it up and move it. If a human grabs the Carta cart, they’re now in charge. If you grab its magic handlebar, you are like Superman—you move your hand a little, and it amplifies what you’re doing. We make the floor worker take control and put it in the right place without much physical effort.
There’s a tendency to go for the flashy demo, but the flashy demo doesn’t deal with the real environment. It’s going to have to operate in the messy reality. That’s why it takes so long for these technologies.
Rodney: I think we need multiple education approaches and not put everything in the same bucket. I see this in Australia—”What’s your bachelor’s degree?” “I’m doing a bachelor’s degree in tourism management.” That’s not an intellectual pursuit, that’s job training, and we should make that distinction. The German system has had this for a long time—job training being a very big part of their education, but it’s not the same as their elite universities.
[ Brooks is right in pointing out that we are busy propping up an education system that creates work for an industrial and industrial-version of digital economies. Germans (and many other parts of the world) have this idea of diplomas in specialized trade skills, which is exactly how we are going to be thinking about in the future, because the idea of work, augmented by digitized automation, both robotic and software, will need to evolve. As such, we need to really rethink the entire map of employment and fine-tune “collegial output” in terms of jobs needed to be done in tandem with the emergence of rapid computerized automation. The United States is still trying to use the same template of education that it has for decades. –OM ]
When Elon Musk decided he wanted to put stuff into orbit, he didn’t say, “I’ll write a Python script, and that will get stuff into orbit.” He had to figure out how to burn fuel efficiently, worry about mass, liquid flows, high temperatures, because you can write as big a program as you want, it’s not going to get stuff into orbit. Computation is not the stuff you need to physically move things.
I started manufacturing in China in the late ’90s. Just last week, my company put out a press release that Foxconn is going to build our robots at scale. They’re based in Taiwan, but it’s undeniable—if you want to do something at scale, that’s how you have to do it.
But let’s look ahead to this century. Fifty years from now, all the innovation is going to be happening in Nigeria. They’re going to be such a big part of the world population, and they’re going to have so many problems they have to deal with, and they will deal with them. Nigeria is going to be the center of the technological universe by the end of this century. (Just as China and its large population, and its need to solve its problems made it into an economic powerhouse, Brooks believes the sheer size of Nigeria is going to make it an economic and technological epicenter.–Ed)
Rodney: I was at a Brown University commencement giving a talk. And we were bemoaning the loss of US manufacturing. I asked the parents of the about to be Brown graduates—do who wants your kids to work in a factory? Oh no, not us! The poor people need the jobs, not my child. Who aspires that their kid is going to work at the sewage company? This bemoaning of manufacturing being lost is a little duplicitous—it’s not for us, it’s for the poor people.
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by Gary Mintchell | Oct 20, 2025 | Commentary, News, Robots
News reports back in the early 1980s continuously propagated the idea that Japan was far ahead of the US installing robots in manufacturing. Digging below the headlines, we could discover some pertinent technology facts.
We had two principle ways to pick parts, say off a conveyor, and place them into an assembly or on a pallet. One was a simple X-Y axis “pick-and-place”. The other was a 3-axis (or more) SCARA robot or a 5-axis robot (á la Fanuc or Asea). Japan considered all of the above as robots, whereas only the latter were considered robots in the US.
I really like News Items by John Ellis. He recently posted this news items sourcing The New York Times (hardly a bastion of authentic manufacturing information).
China is making and installing factory robots at a far greater pace than any other country, with the United States a distant third, further strengthening China’s already dominant global role in manufacturing. There were more than two million robots working in Chinese factories last year, according to a report released Thursday by the International Federation of Robotics, a nonprofit trade group for makers of industrial robots. Factories in China installed nearly 300,000 new robots last year, more than the rest of the world combined, the report found. American factories installed 34,000. While Chinese factories have been using more robots, they have also gotten better at making them. (Source: nytimes.com)
Perhaps China needs to install more robots because it is still catching up to US manufacturing? Not sure, but worth asking. Sometimes gross numbers from an industry group can be misleading. It’s like using percentages in places where percentage gain or loss is essentially meaningless.
I think another angle is to consider that the robot market in the US became mature. Even the collaborative robot market is saturating. Adding AI technologies and new form factors looks promising for expanding the market. I’d like to see much more depth—both from the IFR and the NYT.
More troubling was another item from the NYT on News Items.
New national test results for 12th graders, released this month, showed significant declines in students’ math and reading abilities since 2019, results that are now being felt in college and the labor market. On the national test, students’ reading scores were the worst in three decades, and math scores were the lowest since 2005. The scores are at least partially explained by the pandemic and school closures.
The numbers have not been good for quite some time. They offer an explanation that perhaps partially explains the drop. My neighbor, for example, taught 8th-grade math during the pandemic. She was frustrated trying to teach math over Zoom. But this is not a new phenomenon.
Anther contributor to the comparison numbers lies in the population. We test everyone in the US. Other countries do not test the entire population of students or may not have every child enrolled in that type of school.
So, the NYT falls into a trope:
But they also reflect broader societal changes, including an increase in time spent in front of screens for both young people and adults.
But they also point to something I’ve seen through the eyes of my wife—a long-time elementary school teacher.
The decline was primarily driven by lower-scoring students, who have been losing ground for a decade.
She was frustrated at both ends of the spectrum. Some parents didn’t care or were not supportive of their child. On the other hand, other parents pressed for special treatment, exemption from work, automatic better grades, and the like (helicopter or snow-plow parents).
They are correct in trying to come up with consequences:
The results have vast consequences for a generation of students, the U.S. economy and the country, which already ranks 28th in the world for math, behind Japan, Canada, the United Kingdom, Germany and nearly every other major industrialized democracy. The world’s highest-performing countries not only produce students who outscore the brightest American students at the top. They also manage to lift far more students up to a base level of skill — something some experts believe is only going to become more important in a world of artificial intelligence.
What can you do to help? Offer to tutor? Find ways to encourage kids? Sponsor a First Robotics team?
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by Gary Mintchell | Oct 10, 2025 | Generative AI, Robots, Technology
I’ve been trying to guide AI discussion toward useful applications rather than overly hyped general visions. Let the people dealing in billions of dollars promote themselves. For those who have real work to do, look into the details of AI news to discern real benefits. Perhaps this news from ABB fits that model. This news also follows the trend of larger companies investing in specialist companies in order to drive additional benefits for their products and solutions.
In this case, ABB (robotics) has invested in LandingAI in order to improve the company’s robotic applications for customers. Oh, and we get a new TLA (three-letter acronym). Note the specific examples.
In brief:
- Strategic investment secures ABB’s use of LandingAI’s vision AI capabilities, such as LandingLens, for robot AI vision applications
- Pre-trained models, smart data workflows and no-code tools reduce training time by 80% and accelerate deployment in fast-moving sectors including logistics, healthcare, and food & beverage
- First of its kind collaboration marks a major step towards ABB Robotics’ vision for Autonomous Versatile Robotics – AVR
This first of its kind collaboration will integrate LandingAI’s vision AI capabilities, like LandingLens, into ABB Robotics’ own software suite, marking another milestone in ABB’s journey towards truly autonomous and versatile robots.
“This announcement is the latest in our decade-long journey to innovate and commercialize AI, benefitting our customers by enhancing robot versatility and autonomy to expand the use of robots beyond traditional manufacturing,” said Sami Atiya, President of ABB Robotics & Discrete Automation. “The demand for AI in robotics is driven by the need for greater flexibility, faster commissioning cycles and a shortage of the specialist skills needed to program and operate robots. Our collaboration with LandingAI will mean installation and deployment time is done in hours instead of weeks, allowing more businesses to automate smarter, faster and more efficiently.”
As part of the collaboration ABB has made a venture capital investment through ABB Robotics Ventures, the strategic venture capital unit of ABB Robotics, driving collaboration and investment in innovative early-stage companies that are shaping the future of robotics and automation. Financial details of the investment were not disclosed.
LandingAI’s LandingLens is a vision AI platform that enables the rapid training of vision AI systems to recognize and respond to objects, patterns or defects with no complex programming or AI expertise required.
Through this collaboration, ABB Robotics will reduce robot vision AI training & deployment time by up to 80 percent. Once deployed, system integrators and end users can retrain the AI for new scenarios on their own, unlocking a new level of versatility. This is a critical step in scaling robot adoption in dynamic environments, beyond traditional manufacturing, especially in fast-moving sectors such as logistics, healthcare and food and beverage. ABB is already piloting LandingAI’s technology and actively working to integrate it into existing vision AI applications, including item-picking, sorting, depalletizing and quality inspection.
More information about RobotStudio with generative AI assistant:
- RobotStudio Al Assistant provides real-time, step-by-step guidance for robot programming
- More intelligent and easy-to-use generative Al interface creates faster, easier commissioning and boosts productivity
- Another step in enhancing robot accessibility and versatility beyond traditional manufacturing
Powered by a Large Language Model (LLM) that understands and interprets human language, RobotStudio AI Assistant draws from ABB’s comprehensive library of manuals and documentation to deliver high-quality, context-rich responses to questions, enabling users to set up faster and find rapid answers to questions and technical challenges.
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by Gary Mintchell | Oct 3, 2025 | Automation, Robots
Many complications have interfered with my keeping up with news. I could not make it to FABTECH this year held in early September. Collaborative Robot (cobot) developer Universal Robots (UR) introduced an extended reach cobot.
UR8 Long’s extended reach combined with coordinated multi-axis motion allows for complex weldments at consistent quality. Motion performance optimization also delivers smoother movements at maximum speed to significantly enhance fast-paced bin picking.
UR8 Long has the same 1750 mm (68.9 in) reach as the UR20 and a significantly slimmer profile, UR8 Long combines reach, stability and precision featuring an 8 kg (17.6 lbs) payload.
UR8 Long runs with both PolyScope 5 and PolyScope X, UR’s software platform, and can be extended with MotionPlus – UR’s new advanced motion control technology that allows for ease of integration with linear axis, rotary positioners and rotary turntables for precise control, smoother trajectories, and consistent accuracy.
Combined with UR’s upgraded freedrive capabilities, users can manually guide the arm with precision and ease – making lead-to-teach programming more intuitive and enabling quick, ergonomic setup even on complex parts, all without the need for layered interfaces or external tools. UR8 Long’s lighter mass – 30% less than the UR20 – and compact wrist design also makes it perfect for mounting on gantries, rails, or overhead systems, where external axes can operate more efficiently.
They showcased applications in welding and bin picking among others.
by Gary Mintchell | Jul 31, 2025 | Robots
In further AMR news, this from ABB. Notably, much news in this market emanates from a geographical axis of Sweden, Denmark, Germany, Switzerland.
As ABB explains:
- ABB extends leadership in AI-powered autonomous mobile robots with ultra-compact, high payload Flexley Mover P603 platform AMR
- AI-driven Visual SLAM and integrated load sensing enable stable and autonomous navigation, including in challenging conditions
- AMR Studio 4.0 version simplifies deployment with no-code programming and real-time fleet management
My previous blog post was about Siemens who also claimed the “most compact” AMR to handle 1500 kg.
ABB launched Flexley Mover P603 platform AMR, the most compact model in its class to handle payloads of up to 1500 kg. Designed to boost intralogistics efficiency, the P603 combines compact design with AI-driven Visual SLAM navigation and the latest version of AMR Studio software that maximizes flexibility by enabling different modules to be integrated into the AMR.
Features and benefits
The AMR P603 is part of ABB’s new era of Autonomous Versatile Robotics, where robots can seamlessly switch between tasks, in real time and with minimal effort. With its AI-driven Visual SLAM navigation, the AMR P603 is smarter, faster and safer (meeting ISO 3691-4 and ANSI 56.5 standards) while delivering industry-leading agility and positioning accuracy of ±5 mm, with no need for reflectors or change in infrastructure. Its differential bidirectional drive system enables smooth movement in tight production and warehouse layouts, while its integrated load detection capabilities optimize stability and safety during transport.
The P603’s agility and compact design makes it ideal for intralogistics applications, including end of line, goods to robot, line supply, inter-process connection, and kitting. It supports a wide range of load types and dimensions, including open and closed pallets, containers, racks, and trolleys, all handled with a single AMR and flexible top model configuration.
Designed with modularity in mind, the AMR P603 can be easily adapted with various ‘top modules’ to handle different load types. Combined with the AMR Studio upgrade, it enables rapid setup and seamless customization, with system integrators and end users able to build and modify applications using drag-and-drop tools. With this and other features such as intuitive no-code mission programming, AMR Studio reduces commissioning time by up to 20 percent. ABB’s Fleet Manager software is also integrated, allowing users to coordinate multiple AMRs in real time across large and dynamic production environments.
Future vision
ABB will continue to focus on fusing its precision hardware with artificial intelligence and software, towards further autonomy and versatility.
by Gary Mintchell | Jul 31, 2025 | Robots
This post and the next are Autonomous Guided Vehicle news items from June’s automatica show in Germany. First up, Siemens.
The news in brief:
- Operations Copilot to interact with physical AI agents
- Vision: Multi-agent systems with physical and virtual AI agents for autonomous transport systems and mobile robots
- New software-based safety solution Safe Velocity
Robots and autonomous vehicles come in a wide variety of form factors and use cases. Companies continue to reveal new innovations. This news from Siemens.
Siemens is announcing plans to integrate its Operations Copilot into driverless transport systems and mobile robots. The Operations Copilot is an industrial copilot for machine operation and maintenance. As mobile transport robots increasingly operate as autonomous physical agents powered by artificial intelligence (AI), the Operations Copilot will serve as a user interface for humans. Through this agent-based interface, users will be able to configure autonomous mobile robots (AMRs) and automated guided vehicles (AGVs), assigning them tasks like transporting materials and goods across the shop floor. This is yet another building block for automating automation in a factory with the help of generative AI.
Future Plans
Siemens plans to expand the capabilities of the Operations Copilot by introducing AI agents specifically developed for use with AMRs and AGVs. These agents support both the commissioning and operation of individual vehicles and entire fleets. Commissioning in particular is a complex and time-intensive process: AGVs need to be integrated into the factory’s existing IT and OT infrastructure and configured for specific conditions like routes and transfer stations. To streamline this task, engineers can rely on the Operations Copilot: It leverages AGV sensors and cameras to generate a detailed understanding of their environment. The Operations Copilot can access all relevant technical documentation of the installed components and retrieve real-time system data through its agent interface. This enables commissioning engineers and operators to work more efficiently, resolve issues faster, and ensure rapid deployment.
Safe Velocity
AGVs are equipped with navigation and sensor technologies, that allow them to move safely and reliably through production and intralogistics environments – with no direct human intervention. When people or objects appear in their path, AGVs automatically slow down, stop, or navigate around these obstacles. Siemens’ new software solution, Safe Velocity, enables the fail-safe monitoring of vehicle speed, which permits the protective fields of safety laser scanners to be dynamically adjusted in real time. The TÜV-certified software is compatible with the hardware and software from a variety of AGV manufacturers and enhances existing safety systems to meet stringent industrial safety standards. Safe Velocity reduces the need for additional safety hardware. This simplifies system architecture, saves valuable vehicle space, lowers engineering complexity, and minimizes cabling requirements – without compromising functional safety.
In the future, the Operations Copilot will interact with AI agents such as Safe Velocity to analyze targeted data from safety laser scanners and monitor the speed of AGVs. The virtual Safe Velocity agent supervises autonomous vehicles and can cooperate with other agents designed for AGV and AMR applications. This way, Siemens is building a multi-agent system where the Operations Copilot orchestrates both physical and virtual AI agents, enabling seamless interactions and deeper integration between the real and the digital worlds.
