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Our mission is to ensure that AGI (Artificial General Intelligence) benefits all of humanity. Systems that start to point to AGI* are coming into view, and so we think it’s important to understand the moment we are in. AGI is a weakly defined term, but generally speaking we mean it to be a system that can tackle increasingly complex problems, at human level, in many fields. People are tool-builders with an inherent drive to understand and create, which leads to the world getting better for all of us. Each new generation builds upon the discoveries of the generations before to create even more capable tools—electricity, the transistor, the computer, the internet, and soon AGI. Over time, in fits and starts, the steady march of human innovation has brought previously unimaginable levels of prosperity and improvements to almost every aspect of people’s lives. In some sense, AGI is just another tool in this ever-taller scaffolding of human progress we are building together. In another sense, it is the beginning of something for which it’s hard not to say “this time it’s different”; the economic growth in front of us looks astonishing, and we can now imagine a world where we cure all diseases, have much more time to enjoy with our families, and can fully realize our creative potential. In a decade, perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today. We continue to see rapid progress with AI development. Here are three observations about the economics of AI: 1. The intelligence of an AI model roughly equals the log of the resources used to train and run it. These resources are chiefly training compute, data, and inference compute. It appears that you can spend arbitrary amounts of money and get continuous and predictable gains; the scaling laws that predict this are accurate over many orders of magnitude. 2. The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use. You can see this in the token cost from GPT-4 in early 2023 to GPT-4o in mid-2024, where the price per token dropped about 150x in that time period. Moore’s law changed the world at 2x every 18 months; this is unbelievably stronger. 3. The socioeconomic value of linearly increasing intelligence is super-exponential in nature. A consequence of this is that we see no reason for exponentially increasing investment to stop in the near future. If these three observations continue to hold true, the impacts on society will be significant. We are now starting to roll out AI agents, which will eventually feel like virtual co-workers. Let’s imagine the case of a software engineering agent, which is an agent that we expect to be particularly important. Imagine that this agent will eventually be capable of doing most things a software engineer at a top company with a few years of experience could do, for tasks up to a couple of days long. It will not have the biggest new ideas, it will require lots of human supervision and direction, and it will be great at some things but surprisingly bad at others. Still, imagine it as a real-but-relatively-junior virtual coworker. Now imagine 1,000 of them. Or 1 million of them. Now imagine such agents in every field of knowledge work. In some ways, AI may turn out to be like the transistor economically—a big scientific discovery that scales well and that seeps into almost every corner of the economy. We don’t think much about transistors, or transistor companies, and the gains are very widely distributed. But we do expect our computers, TVs, cars, toys, and more to perform miracles. The world will not change all at once; it never does. Life will go on mostly the same in the short run, and people in 2025 will mostly spend their time in the same way they did in 2024. We will still fall in love, create families, get in fights online, hike in nature, etc. But the future will be coming at us in a way that is impossible to ignore, and the long-term changes to our society and economy will be huge. We will find new things to do, new ways to be useful to each other, and new ways to compete, but they may not look very much like the jobs of today. Agency, willfulness, and determination will likely be extremely valuable. Correctly deciding what to do and figuring out how to navigate an ever-changing world will have huge value; resilience and adaptability will be helpful skills to cultivate. AGI will be the biggest lever ever on human willfulness, and enable individual people to have more impact than ever before, not less. We expect the impact of AGI to be uneven. Although some industries will change very little, scientific progress will likely be much faster than it is today; this impact of AGI may surpass everything else. The price of many goods will eventually fall dramatically (right now, the cost of intelligence and the cost of energy constrain a lot of things), and the price of luxury goods and a few inherently limited resources like land may rise even more dramatically. Technically speaking, the road in front of us looks fairly clear. But public policy and collective opinion on how we should integrate AGI into society matter a lot; one of our reasons for launching products early and often is to give society and the technology time to co-evolve. AI will seep into all areas of the economy and society; we will expect everything to be smart. Many of us expect to need to give people more control over the technology than we have historically, including open-sourcing more, and accept that there is a balance between safety and individual empowerment that will require trade-offs. While we never want to be reckless and there will likely be some major decisions and limitations related to AGI safety that will be unpopular, directionally, as we get closer to achieving AGI, we believe that trending more towards individual empowerment is important; the other likely path we can see is AI being used by authoritarian governments to control their population through mass surveillance and loss of autonomy. Ensuring that the benefits of AGI are broadly distributed is critical. The historical impact of technological progress suggests that most of the metrics we care about (health outcomes, economic prosperity, etc.) get better on average and over the long-term, but increasing equality does not seem technologically determined and getting this right may require new ideas. In particular, it does seem like the balance of power between capital and labor could easily get messed up, and this may require early intervention. We are open to strange-sounding ideas like giving some “compute budget” to enable everyone on Earth to use a lot of AI, but we can also see a lot of ways where just relentlessly driving the cost of intelligence as low as possible has the desired effect. Anyone in 2035 should be able to marshall the intellectual capacity equivalent to everyone in 2025; everyone should have access to unlimited genius to direct however they can imagine. There is a great deal of talent right now without the resources to fully express itself, and if we change that, the resulting creative output of the world will lead to tremendous benefits for us all. Thanks especially to Josh Achiam, Boaz Barak and Aleksander Madry for reviewing drafts of this. *By using the term AGI here, we aim to communicate clearly, and we do not intend to alter or interpret the definitions and processes that define our relationship with Microsoft. We fully expect to be partnered with Microsoft for the long term. This footnote seems silly, but on the other hand we know some journalists will try to get clicks by writing something silly so here we are pre-empting the silliness…
The second birthday of ChatGPT was only a little over a month ago, and now we have transitioned into the next paradigm of models that can do complex reasoning. New years get people in a reflective mood, and I wanted to share some personal thoughts about how it has gone so far, and some of the things I’ve learned along the way. As we get closer to AGI, it feels like an important time to look at the progress of our company. There is still so much to understand, still so much we don’t know, and it’s still so early. But we know a lot more than we did when we started. We started OpenAI almost nine years ago because we believed that AGI was possible, and that it could be the most impactful technology in human history. We wanted to figure out how to build it and make it broadly beneficial; we were excited to try to make our mark on history. Our ambitions were extraordinarily high and so was our belief that the work might benefit society in an equally extraordinary way. At the time, very few people cared, and if they did, it was mostly because they thought we had no chance of success. In 2022, OpenAI was a quiet research lab working on something temporarily called “Chat With GPT-3.5”. (We are much better at research than we are at naming things.) We had been watching people use the playground feature of our API and knew that developers were really enjoying talking to the model. We thought building a demo around that experience would show people something important about the future and help us make our models better and safer. We ended up mercifully calling it ChatGPT instead, and launched it on November 30th of 2022. We always knew, abstractly, that at some point we would hit a tipping point and the AI revolution would get kicked off. But we didn’t know what the moment would be. To our surprise, it turned out to be this. The launch of ChatGPT kicked off a growth curve like nothing we have ever seen—in our company, our industry, and the world broadly. We are finally seeing some of the massive upside we have always hoped for from AI, and we can see how much more will come soon. It hasn’t been easy. The road hasn’t been smooth and the right choices haven’t been obvious. In the last two years, we had to build an entire company, almost from scratch, around this new technology. There is no way to train people for this except by doing it, and when the technology category is completely new, there is no one at all who can tell you exactly how it should be done. Building up a company at such high velocity with so little training is a messy process. It’s often two steps forward, one step back (and sometimes, one step forward and two steps back). Mistakes get corrected as you go along, but there aren’t really any handbooks or guideposts when you’re doing original work. Moving at speed in uncharted waters is an incredible experience, but it is also immensely stressful for all the players. Conflicts and misunderstanding abound. These years have been the most rewarding, fun, best, interesting, exhausting, stressful, and—particularly for the last two—unpleasant years of my life so far. The overwhelming feeling is gratitude; I know that someday I’ll be retired at our ranch watching the plants grow, a little bored, and will think back at how cool it was that I got to do the work I dreamed of since I was a little kid. I try to remember that on any given Friday, when seven things go badly wrong by 1 pm. A little over a year ago, on one particular Friday, the main thing that had gone wrong that day was that I got fired by surprise on a video call, and then right after we hung up the board published a blog post about it. I was in a hotel room in Las Vegas. It felt, to a degree that is almost impossible to explain, like a dream gone wrong. Getting fired in public with no warning kicked off a really crazy few hours, and a pretty crazy few days. The “fog of war” was the strangest part. None of us were able to get satisfactory answers about what had happened, or why. The whole event was, in my opinion, a big failure of governance by well-meaning people, myself included. Looking back, I certainly wish I had done things differently, and I’d like to believe I’m a better, more thoughtful leader today than I was a year ago. I also learned the importance of a board with diverse viewpoints and broad experience in managing a complex set of challenges. Good governance requires a lot of trust and credibility. I appreciate the way so many people worked together to build a stronger system of governance for OpenAI that enables us to pursue our mission of ensuring that AGI benefits all of humanity. My biggest takeaway is how much I have to be thankful for and how many people I owe gratitude towards: to everyone who works at OpenAI and has chosen to spend their time and effort going after this dream, to friends who helped us get through the crisis moments, to our partners and customers who supported us and entrusted us to enable their success, and to the people in my life who showed me how much they cared. [1] We all got back to the work in a more cohesive and positive way and I’m very proud of our focus since then. We have done what is easily some of our best research ever. We grew from about 100 million weekly active users to more than 300 million. Most of all, we have continued to put technology out into the world that people genuinely seem to love and that solves real problems. Nine years ago, we really had no idea what we were eventually going to become; even now, we only sort of know. AI development has taken many twists and turns and we expect more in the future. Some of the twists have been joyful; some have been hard. It’s been fun watching a steady stream of research miracles occur, and a lot of naysayers have become true believers. We’ve also seen some colleagues split off and become competitors. Teams tend to turn over as they scale, and OpenAI scales really fast. I think some of this is unavoidable—startups usually see a lot of turnover at each new major level of scale, and at OpenAI numbers go up by orders of magnitude every few months. The last two years have been like a decade at a normal company. When any company grows and evolves so fast, interests naturally diverge. And when any company in an important industry is in the lead, lots of people attack it for all sorts of reasons, especially when they are trying to compete with it. Our vision won’t change; our tactics will continue to evolve. For example, when we started we had no idea we would have to build a product company; we thought we were just going to do great research. We also had no idea we would need such a crazy amount of capital. There are new things we have to go build now that we didn’t understand a few years ago, and there will be new things in the future we can barely imagine now. We are proud of our track-record on research and deployment so far, and are committed to continuing to advance our thinking on safety and benefits sharing. We continue to believe that the best way to make an AI system safe is by iteratively and gradually releasing it into the world, giving society time to adapt and co-evolve with the technology, learning from experience, and continuing to make the technology safer. We believe in the importance of being world leaders on safety and alignment research, and in guiding that research with feedback from real world applications. We are now confident we know how to build AGI as we have traditionally understood it. We believe that, in 2025, we may see the first AI agents “join the workforce” and materially change the output of companies. We continue to believe that iteratively putting great tools in the hands of people leads to great, broadly-distributed outcomes. We are beginning to turn our aim beyond that, to superintelligence in the true sense of the word. We love our current products, but we are here for the glorious future. With superintelligence, we can do anything else. Superintelligent tools could massively accelerate scientific discovery and innovation well beyond what we are capable of doing on our own, and in turn massively increase abundance and prosperity. This sounds like science fiction right now, and somewhat crazy to even talk about it. That’s alright—we’ve been there before and we’re OK with being there again. We’re pretty confident that in the next few years, everyone will see what we see, and that the need to act with great care, while still maximizing broad benefit and empowerment, is so important. Given the possibilities of our work, OpenAI cannot be a normal company. How lucky and humbling it is to be able to play a role in this work. (Thanks to Josh Tyrangiel for sort of prompting this. I wish we had had a lot more time.) [1] There were a lot of people who did incredible and gigantic amounts of work to help OpenAI, and me personally, during those few days, but two people stood out from all others. Ron Conway and Brian Chesky went so far above and beyond the call of duty that I’m not even sure how to describe it. I’ve of course heard stories about Ron’s ability and tenaciousness for years and I’ve spent a lot of time with Brian over the past couple of years getting a huge amount of help and advice. But there’s nothing quite like being in the foxhole with people to see what they can really do. I am reasonably confident OpenAI would have fallen apart without their help; they worked around the clock for days until things were done. Although they worked unbelievably hard, they stayed calm and had clear strategic thought and great advice throughout. They stopped me from making several mistakes and made none themselves. They used their vast networks for everything needed and were able to navigate many complex situations. And I’m sure they did a lot of things I don’t know about. What I will remember most, though, is their care, compassion, and support. I thought I knew what it looked like to support a founder and a company, and in some small sense I did. But I have never before seen, or even heard of, anything like what these guys did, and now I get more fully why they have the legendary status they do. They are different and both fully deserve their genuinely unique reputations, but they are similar in their remarkable ability to move mountains and help, and in their unwavering commitment in times of need. The tech industry is far better off for having both of them in it. There are others like them; it is an amazingly special thing about our industry and does much more to make it all work than people realize. I look forward to paying it forward. On a more personal note, thanks especially to Ollie for his support that weekend and always; he is incredible in every way and no one could ask for a better partner.
There are two things from our announcement today I wanted to highlight. First, a key part of our mission is to put very capable AI tools in the hands of people for free (or at a great price). I am very proud that we’ve made the best model in the world available for free in ChatGPT, without ads or anything like that. Our initial conception when we started OpenAI was that we’d create AI and use it to create all sorts of benefits for the world. Instead, it now looks like we’ll create AI and then other people will use it to create all sorts of amazing things that we all benefit from. We are a business and will find plenty of things to charge for, and that will help us provide free, outstanding AI service to (hopefully) billions of people. Second, the new voice (and video) mode is the best computer interface I’ve ever used. It feels like AI from the movies; and it’s still a bit surprising to me that it’s real. Getting to human-level response times and expressiveness turns out to be a big change. The original ChatGPT showed a hint of what was possible with language interfaces; this new thing feels viscerally different. It is fast, smart, fun, natural, and helpful. Talking to a computer has never felt really natural for me; now it does. As we add (optional) personalization, access to your information, the ability to take actions on your behalf, and more, I can really see an exciting future where we are able to use computers to do much more than ever before. Finally, huge thanks to the team that poured so much work into making this happen!
Optimism, obsession, self-belief, raw horsepower and personal connections are how things get started. Cohesive teams, the right combination of calmness and urgency, and unreasonable commitment are how things get finished. Long-term orientation is in short supply; try not to worry about what people think in the short term, which will get easier over time. It is easier for a team to do a hard thing that really matters than to do an easy thing that doesn’t really matter; audacious ideas motivate people. Incentives are superpowers; set them carefully. Concentrate your resources on a small number of high-conviction bets; this is easy to say but evidently hard to do. You can delete more stuff than you think. Communicate clearly and concisely. Fight bullshit and bureaucracy every time you see it and get other people to fight it too. Do not let the org chart get in the way of people working productively together. Outcomes are what count; don’t let good process excuse bad results. Spend more time recruiting. Take risks on high-potential people with a fast rate of improvement. Look for evidence of getting stuff done in addition to intelligence. Superstars are even more valuable than they seem, but you have to evaluate people on their net impact on the performance of the organization. Fast iteration can make up for a lot; it’s usually ok to be wrong if you iterate quickly. Plans should be measured in decades, execution should be measured in weeks. Don’t fight the business equivalent of the laws of physics. Inspiration is perishable and life goes by fast. Inaction is a particularly insidious type of risk. Scale often has surprising emergent properties. Compounding exponentials are magic. In particular, you really want to build a business that gets a compounding advantage with scale. Get back up and keep going. Working with great people is one of the best parts of life.
Helion has been progressing even faster than I expected and is on pace in 2024 to 1) demonstrate Q > 1 fusion and 2) resolve all questions needed to design a mass-producible fusion generator. The goals of the company are quite ambitious—clean, continuous energy for 1 cent per kilowatt-hour, and the ability to manufacture enough power plants to satisfy the current electrical demand of earth in a ten year period. If both things happen, it will transform the world. Abundant, clean, and radically inexpensive energy will elevate the quality of life for all of us—think about how much the cost of energy factors into what we do and use. Also, electricity at this price will allow us to do things like efficiently capture carbon (so although we’ll still rely on gasoline for awhile, it’ll be ok). Although Helion’s scientific progress of the past 8 years is phenomenal and necessary, it is not sufficient to rapidly get to this new energy economy. Helion now needs to figure out how to engineer machines that don’t break, how to build a factory and supply chain capable of manufacturing a machine every day, how to work with power grids and governments around the world, and more. The biggest input to the degree and speed of success at the company is now the talent of the people who join the team. Here are a few of the most critical jobs, but please don’t let the lack of a perfect fit deter you from applying. Electrical Engineer, Low Voltage: https://boards.greenhouse.io/helionenergy/jobs/4044506005 Electrical Engineer, Pulsed Power: https://boards.greenhouse.io/helionenergy/jobs/4044510005 Mechanical Engineer, Generator Systems: https://boards.greenhouse.io/helionenergy/jobs/4044522005 Manager of Mechanical Engineering: https://boards.greenhouse.io/helionenergy/jobs/4044521005 (All current jobs: https://www.helionenergy.com/careers/)
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Don’t panic
This dairy barn is full of cows, as you might expect. Cows are being milked, cows are being fed, cows are being cleaned up after, and a few very happy cows are even getting vigorously scratched behind the ears. “I wonder where the farmer is,” remarks my guide, Jan Jacobs. Jacobs doesn’t seem especially worried, though—the several hundred cows in this barn are being well cared for by a small fleet of fully autonomous robots, and the farmer might not be back for hours. The robots will let him know if anything goes wrong. more frequently than the twice a day at a traditional dairy farm. Not only is getting milked more often more comfortable for the cows, cows also produce about 10 percent more milk when the milking schedule is completely up to them. Jan Jacobs is the human-robot interaction design lead for Lely, a maker of agricultural machinery. Founded in 1948 in Maassluis, Netherlands, Lely deployed its first Astronaut milking robot in the early 1990s. The company has since developed other robotic systems that assist with cleaning, feeding, and cow comfort, and the Astronaut milking robot is on its fifth generation. Lely is now focused entirely on robots for dairy farms, with around 135,000 of them deployed around the world. Essential Jobs on Dairy Farms The weather outside the barn is miserable. It’s late fall in the Netherlands, and a cold rain is gusting in from the sea, which is probably why the cows have quite sensibly decided to stay indoors and why the farmer is still nowhere to be found. Lely requires that dairy farmers who adopt its robots commit to letting their cows move freely between milking, feeding, and resting, as well as inside and outside the barn, at their own pace. “We believe that free cow traffic is a core part of the future of farming,” Jacobs says as we watch one cow stroll away from the milking robot while another takes its place. This is possible only when the farm operates on the cows’ schedule rather than a human’s. “We were spending 6 hours a day milking,” explains dairy farmer Josie Rozum, whose 120-cow herd at Takes Dairy Farm uses a pair of Astronaut A5 milking robots. “Now that the robots are handling all of that, we can focus more on animal care and comfort.”Lely in just 20 to 30 seconds. The actual milking takes only a few minutes, but with the average small dairy farm in North America providing a home for several hundred cows, milking typically represents a time commitment of 4 to 6 hours per day. Cows are happier with continuous access to food, which means feeding them several times a day. The feed is a mix of roughage (hay), silage (grass), and grain. The cows will eat all of this, but they prefer the grain, and so it’s common to see cows sorting their food by grabbing a mouthful and throwing it up into the air. The lighter roughage and silage flies farther than the grain does, leaving the cow with a pile of the tastier stuff as the rest gets tossed out of reach. This makes “feed pushing” necessary to shove the rest of the feed back within reach of the cow. 68 kilograms of manure a day. All that manure has to be collected and the barn floors regularly cleaned. Dairy Industry 4.0 The amount of labor needed to operate a dairy meant that until the early 1900s, most family farms could support only about eight cows. The introduction of the first milking machines, called bucket milkers, helped farmers milk 10 cows per hour instead of 4 by the mid-1920s. Rural electrification furthered dairy automation starting in the 1950s, and since then, both farm size and milk production have increased steadily. In the 1930s, a good dairy cow produced 3,600 kilograms of milk per year. Today, it’s almost 11,000 kilograms, and Lely believes that robots are what will enable small dairy farms to continue to scale sustainably. Lely But dairy robots are expensive. A milking robot can cost several hundred thousand dollars, plus an additional US $5,000 to $10,000 per year in operating costs. The Astronaut A5, Lely’s latest milking robot, uses a laser-guided robot arm to clean the cow’s udder before attaching teat cups one at a time. While the cow munches on treats, the Astronaut monitors her milk output, collecting data on 32 parameters, including indicators of the quality of the milk and the health of the cow. When milking is complete, the robot cleans the udder again, and the cow is free to leave as the robot steam cleans itself in preparation for the next cow. Lely argues that although the initial cost is higher than that of a traditional milking parlor, the robots pay for themselves over time through higher milk production (due primarily to increased milking frequency) and lower labor costs. Lely’s other robots can also save on labor. The Vector mobile robot handles continuous feeding and feed pushing, and the Discovery Collector is a robotic manure vacuum that keeps the floors clean. At Takes Dairy Farm, Rozum and her family used to spend several hours per day managing food for the cows. “The feeding robot is another amazing piece of the puzzle for our farm that allows us to focus on other things.”Takes Family Farm Marcia Endres, a professor in the department of animal science at the University of Minnesota. Endres specializes in dairy-cattle management, behavior, and welfare, and studies dairy robot adoption. “When we first started doing research on this about 12 years ago, most of the farms that were installing robots were smaller farms that did not want to hire employees,” Endres says. “They wanted to do the work just with family labor, but they also wanted to have more flexibility with their time. They wanted a better lifestyle.” added Lely robots to their dairy farm in Ely, Iowa, four years ago. “When we had our old milking parlor, everything that we did as a family was always scheduled around milking,” says Josie Rozum, who manages the farm and a creamery along with her parents—Dan and Debbie Takes—and three brothers. “With the robots, we can prioritize our personal life a little bit more—we can spend time together on Christmas morning and know that the cows are still getting milked.” Takes Family Dairy Farm’s 120-cow herd is milked by a pair of Astronaut A5 robots, with a Vector and three Discovery Collectors for feeding and cleaning. “They’ve become a crucial part of the team,” explains Rozum. “It would be challenging for us to find outside help, and the robots keep things running smoothly.” The robots also add sustainability to small dairy farms, and not just in the short term. “Growing up on the farm, we experienced the hard work, and we saw what that commitment did to our parents,” Rozum explains. “It’s a very tough lifestyle. Having the robots take over a little bit of that has made dairy farming more appealing to our generation.” Takes Dairy Farm about a third of the adoption rate in Europe, where farms tend to be smaller, so the cost of implementing the robots is lower. Endres says that over the last five years, she’s seen a shift toward robot adoption at larger farms with over 500 cows, due primarily to labor shortages. “These larger dairies are having difficulty finding employees who want to milk cows—it’s a very tedious job. And the robot is always consistent. The farmers tell me, ‘My robot never calls in sick, and never shows up drunk.’ ” The Lely Luna cow brush helps to keep cows’ skin healthy. It’s also relaxing and enjoyable, so cows will brush themselves several times a day.Lely much more relaxed and friendly toward people they meet. Rozum agrees. “We’ve noticed a tremendous change in our cows’ demeanor. They’re more calm and relaxed, just doing their thing in the barn. They’re much more comfortable when they can choose what to do.” Cows Versus Robots Cows are curious and clever animals, and have the same instinct that humans have when confronted with a new robot: They want to play with it. Because of this, Lely has had to cow-proof its robots, modifying their design and programming so that the machines can function autonomously around cows. Like many mobile robots, Lely’s dairy robots include contact-sensing bumpers that will pause the robot’s motion if it runs into something. On the Vector feeding robot, Lely product engineer René Beltman tells me, they had to add a software option to disable the bumper. “The cows learned that, ‘oh, if I just push the bumper, then the robot will stop and put down more feed in my area for me to eat.’ It was a free buffet. So you don’t want the cows to end up controlling the robot.” Emergency stop buttons had to be relocated so that they couldn’t be pressed by questing cow tongues. One of the dirtiest jobs on a dairy farm is handled by the Discovery Collector, an autonomous manure vacuum. The robot relies on wheel odometry and ultrasonic sensors for navigation because it’s usually covered in manure.Evan Ackerman Besides maintaining their dominance at the top of the herd, the current generation of Lely robots doesn’t interact much with the cows, but that’s changing, Jacobs tells me. Right now, when a robot is driving through the barn, it makes a beeping sound to let the cows know it’s coming. Lely is looking into how to make these sounds more enjoyable for the cows. “This was a recent revelation for me,” Jacobs says. ”We’re not just designing interactions for humans. The cows are our users, too.” Human-Robot Interaction Last year, Jacobs and researchers from Delft University of Technology, in the Netherlands, presented a paper at the IEEE Human-Robot Interaction (HRI) Conference exploring this concept of robot behavior development on working dairy farms. The researchers visited robotic dairies, interviewed dairy farmers, and held workshops within Lely to establish a robot code of conduct—a guide that Lely’s designers and engineers use when considering how their robots should look, sound, and act, for the benefit of both humans and cows. On the engineering side, this includes practical things like colors and patterns for lights and different types of sounds so that information is communicated consistently across platforms. Jacobs doesn’t want his robots to try to be anyone’s friend—not the cow’s, and not the farmer’s. “The robot is an employee, and it should have a professional relationship,” he says. “So the robot might say ‘Hi,’ but it wouldn’t say, ‘How are you feeling today?’ ” What’s more important is that the robots are trustworthy. For Jacobs, instilling trust is simple: “You cannot gain trust by doing tricks. If your robot is reliable and predictable, people will trust it.” The electrically driven, pneumatically balanced robotic arm that the Lely Astronaut uses to milk cows is designed to withstand accidental (or intentional) kicks.Lely From Dairy Farmers to Robot Managers With the additional time and flexibility that the robots enable, some dairy farmers have been able to diversify. On our way back to Lely’s headquarters, we stop at Farm Het Lansingerland, owned by a Lely customer who has added a small restaurant and farm shop to his dairy. Large windows look into the barn so that restaurant patrons can watch the robots at work, caring for the cows that produce the cheese that’s on the menu. A self-guided tour takes you right up next to an Astronaut A5 milking robot, while signs on the floor warn of Vector feeding robots on the move. “This farmer couldn’t expand—this was as many cows as he’s allowed to have here,” Jacobs explains to me over cheese sandwiches. “So, he needs to have additional income streams. That’s why he started these other things. And the robots were essential for that.” Besides managing the robots, the farmer must also learn to manage the massive amount of data that the robots generate about the cows. “The amount of data we get from the robots is a game changer,” says Rozum. “We can track milk production, health, and cow habits in real time. But it’s overwhelming. You could spend all day just sitting at the computer, looking at data and not get anything else done. It took us probably a year to really learn how to use it.” A Robotic Dairy A: One Astronaut A5 robot can milk up to 60 cows. After the Astronaut cleans the teats, a laser sensor guides a robotic arm to attach the teat cups. Milking takes just a few minutes. C: The Vector robot dispenses freshly mixed food in small batches throughout the day. A laser measures the height of leftover food to make sure that the cows are getting the right amounts. E: As it milks, the Astronaut is collecting a huge amount of data—32 different parameters per teat. If it detects an issue, the farmer is notified, helping to catch health problems early. F: Automated gates control meadow access and will keep a cow inside if she’s due to be milked soon. Cows are identified using RFID collars, which also track their behavior and health. A Sensible Future for Dairy Robots After lunch, we stop by Lely headquarters, where bright red life-size cow statues guard the entrance and all of the conference rooms are dairy themed. We get comfortable in Butter, and I ask Jacobs and Beltman what the future holds for their dairy robots. feed-pushing robot is equipped with lidar and stereo cameras, which allow it to autonomously navigate around large farms without needing to follow a metal strip bolted to the ground. A new overhead camera system will leverage AI to recognize individual cows and track their behavior, while also providing farmers with an enormous new dataset that could allow Lely’s systems to help farmers make more nuanced decisions about cow welfare. The potential of AI is what Jacobs seems most excited about, although he’s cautious as well. “With AI, we’re suddenly going to take away an entirely different level of work. So, we’re thinking about doing research into the meaningfulness of work, to make sure that the things that we do with AI are the things that farmers want us to do with AI.” Lely is aware of this and knows that its robots have to find the right balance between being helpful, and taking over. “We want to make sure not to take away the kinds of interactions that give dairy farmers joy in their work,” says Beltman. “Like feeding calves—every farmer likes to feed the calves.” Lely does sell an automated calf feeder that many dairy farmers buy, which illustrates the point: What’s the best way of designing robots to give humans the flexibility to do the work that they enjoy? Dairy farms are different. Perhaps that’s because the person buying the robot is the person who most directly benefits from it. But I wonder if the concern over automation of jobs would be mitigated if more companies chose to emphasize the sustainability and joy of work equally with profit. Automation doesn’t have to be zero-sum—if implemented thoughtfully, perhaps robots can make work easier, more efficient, and more fun, too. Jacobs certainly thinks so. “That’s my utopia,” he says. “And we’re working in the right direction.”
The book of March 2025 was Abundance. Ezra Klein and Derek Thompson are making a noble attempt to highlight the importance of solving America’s housing crisis the only way it can be solved: Building houses in places people want to live, via repealing the rules that make this impossible. They also talk about green energy abundance, and other places besides. There may be a review coming.
This is a sponsored article brought to you by Freudenberg Sealing Technologies. The increasing deployment of collaborative robots (cobots) in outdoor environments presents significant engineering challenges, requiring highly advanced sealing solutions to ensure reliability and durability. Unlike industrial robots that operate in controlled indoor environments, outdoor cobots are exposed to extreme weather conditions that can compromise their mechanical integrity. Maintenance robots used in servicing wind turbines, for example, must endure intense temperature fluctuations, high humidity, prolonged UV radiation exposure, and powerful wind loads. Similarly, agricultural robots operate in harsh conditions where they are continuously exposed to abrasive dust, chemically aggressive fertilizers and pesticides, and mechanical stresses from rough terrains. To ensure these robotic systems maintain long-term functionality, sealing solutions must offer effective protection against environmental ingress, mechanical wear, corrosion, and chemical degradation. Outdoor robots must perform flawlessly in temperature ranges spanning from scorching heat to freezing cold while withstanding constant exposure to moisture, lubricants, solvents, and other contaminants. In addition, sealing systems must be resilient to continuous vibrations and mechanical shocks, which are inherent to robotic motion and can accelerate material fatigue over time. Comprehensive Technical Requirements for Robotic Sealing Solutions The development of sealing solutions for outdoor robotics demands an intricate balance of durability, flexibility, and resistance to wear. Robotic joints, particularly those in high-mobility systems, experience multidirectional movements within confined installation spaces, making the selection of appropriate sealing materials and geometries crucial. Traditional elastomeric O-rings, widely used in industrial applications, often fail under such extreme conditions. Exposure to high temperatures can cause thermal degradation, while continuous mechanical stress accelerates fatigue, leading to early seal failure. Chemical incompatibility with lubricants, fuels, and cleaning agents further contributes to material degradation, shortening operational lifespans. Friction-related wear is another critical concern, especially in robotic joints that operate at high speeds. Excessive friction not only generates heat but can also affect movement precision. In collaborative robotics, where robots work alongside humans, such inefficiencies pose safety risks by delaying response times and reducing motion accuracy. Additionally, prolonged exposure to UV radiation can cause conventional sealing materials to become brittle and crack, further compromising their performance. Advanced IPSR Technology: Tailored for Cobots To address these demanding conditions, Freudenberg Sealing Technologies has developed a specialized sealing solution: Ingress Protection Seals for Robots (IPSR). Unlike conventional seals that rely on metallic springs for mechanical support, the IPSR design features an innovative Z-shaped geometry that dynamically adapts to the axial and radial movements typical in robotic joints. Numerous seals are required in cobots and these are exposed to high speeds and forces.Freudenberg Sealing Technologies This unique structural design distributes mechanical loads more efficiently, significantly reducing friction and wear over time. While traditional spring-supported seals tend to degrade due to mechanical fatigue, the IPSR configuration eliminates this limitation, ensuring long-lasting performance. Additionally, the optimized contact pressure reduces frictional forces in robotic joints, thereby minimizing heat generation and extending component lifespans. This results in lower maintenance requirements, a crucial factor in applications where downtime can lead to significant operational disruptions. Optimized Through Advanced Simulation Techniques The development of IPSR technology relied extensively on Finite Element Analysis (FEA) simulations to optimize seal geometries, material selection, and surface textures before physical prototyping. These advanced computational techniques allowed engineers to predict and enhance seal behavior under real-world operational conditions. FEA simulations focused on key performance factors such as frictional forces, contact pressure distribution, deformation under load, and long-term fatigue resistance. By iteratively refining the design based on simulation data, Freudenberg engineers were able to develop a sealing solution that balances minimal friction with maximum durability. Furthermore, these simulations provided insights into how IPSR seals would perform under extreme conditions, including exposure to humidity, rapid temperature changes, and prolonged mechanical stress. This predictive approach enabled early detection of potential failure points, allowing for targeted improvements before mass production. By reducing the need for extensive physical testing, Freudenberg was able to accelerate the development cycle while ensuring high-performance reliability. Material Innovations: Superior Resistance and Longevity The effectiveness of a sealing solution is largely determined by its material composition. Freudenberg utilizes advanced elastomeric compounds, including Fluoroprene XP and EPDM, both selected for their exceptional chemical resistance, mechanical strength, and thermal stability. Fluoroprene XP, in particular, offers superior resistance to aggressive chemicals, including solvents, lubricants, fuels, and industrial cleaning agents. Additionally, its resilience against ozone and UV radiation makes it an ideal choice for outdoor applications where continuous exposure to sunlight could otherwise lead to material degradation. EPDM, on the other hand, provides outstanding flexibility at low temperatures and excellent aging resistance, making it suitable for applications that require long-term durability under fluctuating environmental conditions. To further enhance performance, Freudenberg applies specialized solid-film lubricant coatings to IPSR seals. These coatings significantly reduce friction and eliminate stick-slip effects, ensuring smooth robotic motion and precise movement control. This friction management not only improves energy efficiency but also enhances the overall responsiveness of robotic systems, an essential factor in high-precision automation. Extensive Validation Through Real-World Testing While advanced simulations provide critical insights into seal behavior, empirical testing remains essential for validating real-world performance. Freudenberg subjected IPSR seals to rigorous durability tests, including prolonged exposure to moisture, dust, temperature cycling, chemical immersion, and mechanical vibration. Throughout these tests, IPSR seals consistently achieved IP65 certification, demonstrating their ability to effectively prevent environmental contaminants from compromising robotic components. Real-world deployment in maintenance robotics for wind turbines and agricultural automation further confirmed their reliability, with extensive wear analysis showing significantly extended operational lifetimes compared to traditional sealing technologies. Safety Through Advanced Friction Management In collaborative robotics, sealing performance plays a direct role in operational safety. Excessive friction in robotic joints can delay emergency-stop responses and reduce motion precision, posing potential hazards in human-robot interaction. By incorporating low-friction coatings and optimized sealing geometries, Freudenberg ensures that robotic systems respond rapidly and accurately, enhancing workplace safety and efficiency. Tailored Sealing Solutions for Various Robotic Systems Freudenberg Sealing Technologies provides customized sealing solutions across a wide range of robotic applications, ensuring optimal performance in diverse environments. Automated Guided Vehicles (AGVs) operate in industrial settings where they are exposed to abrasive contaminants, mechanical vibrations, and chemical exposure. Freudenberg employs reinforced PTFE composites to enhance durability and protect internal components. Delta robots can perform complex movements at high speed. This requires seals that meet the high dynamic and acceleration requirements.Freudenberg Sealing Technologies Delta robots, commonly used in food processing, pharmaceuticals, and precision electronics, require FDA-compliant materials that withstand rigorous cleaning procedures such as Cleaning-In-Place (CIP) and Sterilization-In-Place (SIP). Freudenberg utilizes advanced fluoropolymers that maintain structural integrity under aggressive sanitation processes. Seals for Scara robots must have high chemical resistance, compressive strength and thermal resistance to function reliably in a variety of industrial environments.Freudenberg Sealing Technologies SCARA robots benefit from Freudenberg’s Modular Plastic Sealing Concept (MPSC), which integrates sealing, bearing support, and vibration damping within a compact, lightweight design. This innovation optimizes robot weight distribution and extends component service life. Six-axis robots used in automotive, aerospace, and electronics manufacturing require sealing solutions capable of withstanding high-speed operations, mechanical stress, and chemical exposure. Freudenberg’s Premium Sine Seal (PSS), featuring reinforced PTFE liners and specialized elastomer compounds, ensures maximum durability and minimal friction losses. Continuous Innovation for Future Robotic Applications Freudenberg Sealing Technologies remains at the forefront of innovation, continuously developing new materials, sealing designs, and validation methods to address evolving challenges in robotics. Through strategic customer collaborations, cutting-edge material science, and state-of-the-art simulation technologies, Freudenberg ensures that its sealing solutions provide unparalleled reliability, efficiency, and safety across all robotic platforms.
What they are and what you need to understand to avoid them
