Robotics In Everyday Work

I’ll admit it......I expected AI to make offices emptier. The data says the opposite. A recent global survey of 16,000+ workers found that those who use AI most heavily actually spend less time working alone. Instead, they report stronger team relationships, higher trust, and deeper workplace friendships than those who rarely use AI. Why? Because when AI takes care of the routine, people reinvest that time in each other. That flips a common narrative on its head. The office isn’t becoming obsolete—it’s evolving into something more valuable: a hub for learning, collaboration, and connection. For leaders, the implication is clear: Designing great physical environments isn’t just a “nice to have.” It’s part of your AI strategy. So the real question is: 👉 How are you rethinking your team’s physical space in an AI-enabled world? Check out the report: https://lnkd.in/eUatD7Yv #FutureOfWork #AIatWork #WorkplaceDesign #Leadership

Breaking Space News 🚨 India’s First Space robotic arm in Action aboard POEM4. India says hi to them domain of Space robotics today. On wards and Upwards! Relocatable Robotic Manipulator-TD (RRM-TD) is Developed by ISRO-IISU RRM-TD aka Walking Robotic Arm is a technology demonstrator for the type of robotic arms that will be used on the Bharatiya Antariksh Station to help with its construction and maintenance. The specialty of this type of robotic arm is that it has the ability to relocate itself along the body of its parent spacecraft by "walking" end-over-end, similar to how an inchworm or leech moves, and grabbing onto fixed grappling points and re-routing power & data connections

MIT researchers paired 2,310 people into human-human and human-AI teams to create real ads in a collaborative workspace with some fascinating outcomes—tracking 183K messages, 2m copy edits, and over 5m ad impressions. The paper "Collaborating with AI Agents: Field Experiments on Teamwork, Productivity, and Performance" examined many facets of the dynamics of human-AI collaboration on what was most effective. Some of the valuable insights: 🤖 AI changes how teams talk and work together. Human-AI teams sent 45% more messages than human-only teams, with a focus on task execution—suggestions, instructions, and planning—while human teams sent more social and emotional messages. Despite this shift, both team types rated teamwork quality similarly, showing that collaboration can remain strong even when social interaction drops. 🧍➕🤖 One person plus AI can match or beat human teams. Individuals in human-AI teams produced 60% to 73% more ads than individuals in human-human teams, closing the productivity gap that usually favors groups. Despite having only one human per team, human-AI groups created just as many ads overall as two-human teams. 🧠 Human-AI success depends on psychological compatibility. When a conscientious person worked with a conscientious AI, message volume increased by 62%, signaling better engagement. But mismatches had negative effects—for example, extraverted humans working with conscientious AIs saw drops in text, image, and click quality across the board. 📊 AI lets people shift from doing to directing. Participants in human-AI teams made 60% fewer direct text edits compared to those in human-only teams. Instead of rewriting content themselves, they communicated what needed to be done—refocusing effort from manual changes to guiding and refining AI-generated output. 🔄 AI redistributes cognitive workload and changes who does what. With AI handling routine and complex text generation, humans shifted attention from editing to strategic input and idea generation. This redesigns roles within teams, suggesting new ways to organize work where humans steer, and AI constructs. Humans + AI is the future. This research provides more valuable foundations for understanding how to do this well.

A new study of 1,488 full-time U.S. workers reveals a striking paradox at the heart of the AI productivity promise: the same tools designed to make work easier may be making it cognitively harder. Researchers have identified a phenomenon they call "AI brain fry" — acute mental fatigue arising from the intensive oversight and management of AI systems — and found it carries measurable costs for decision quality, error rates, and employee retention. The study draws a critical distinction between two separate stress pathways. When AI absorbs repetitive, low-value tasks, workers experience lower burnout and greater engagement. But when AI demands constant human supervision — particularly across multiple simultaneous agents — it can push workers past their cognitive limits, producing a qualitatively different strain that existing burnout surveys rarely capture. These findings arrive at a pivotal moment, as companies increasingly measure performance through AI activity metrics and task employees with overseeing complex, multi-agent workflows. The research offers both a diagnosis and a roadmap for leaders who want the productivity gains of AI without the cognitive casualties. This study offers one of the most rigorous examinations to date of what intensive AI use actually does to the workers deploying it. Its core insight is deceptively simple: AI is not a monolith. The same category of technology can simultaneously reduce burnout and produce acute cognitive exhaustion, depending entirely on how it is deployed. The organizations most likely to benefit from AI are not those that push adoption hardest, but those that deploy it most thoughtfully — protecting the cognitive capacity that makes high-quality human judgment possible in the first place. The tools are powerful. So are the brains that still need to guide them. Ref: HBR

I watched our humanoid make coffee in the office kitchen. The milk was not where it was yesterday. A mug was half blocked by plates. Nothing was scripted. The robot adapted and kept going. That is the point. Kitchens are messy. Objects move. Layouts change. Interruptions happen. If a robot can operate there without freezing or breaking things, it can handle the edge cases that matter in logistics and industry. Most robotics demos avoid this. Fixed objects. Clean setups. Repeatable motions. That is not the real world. At Sereact we build for live, unscripted environments. The coffee is irrelevant. Learning to generalise is everything. If it works in our kitchen, it works in your warehouse.

China just turned its “Super Bowl moment” into a humanoid robotics showcase. At the Spring Festival Gala, in front of ~800M viewers, robots performed martial arts, synchronized choreography, and full physical routines. Is it entertainment? Yes. 𝐈𝐬 𝐢𝐭 𝐣𝐮𝐬𝐭 𝐞𝐧𝐭𝐞𝐫𝐭𝐚𝐢𝐧𝐦𝐞𝐧𝐭? 𝐍𝐨. 💡 𝐇𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐫𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐚𝐥. 𝐈𝐭’𝐬 𝐚𝐧 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐲. When a technology gets prime-time exposure at the most-watched event in the country, backed by national cloud and AI players, that’s not a demo. 👉 That’s positioning. Today it’s dance and kung fu. Tomorrow it’s: • Advanced warehouse automation. • Flexible manufacturing lines. • Hazardous environment operations. • 24/7 physical execution without labor friction. Once that scales, the impact isn’t technical. It’s economic. ✅ Cost-per-unit models shift. ✅ Industrial CAPEX gets redefined. ✅ Productivity curves steepen. ✅ Global competitiveness rebalances. The question isn’t whether this reaches the industry. The question is: 𝐰𝐡𝐨 𝐜𝐚𝐩𝐭𝐮𝐫𝐞𝐬 𝐭𝐡𝐞 𝐚𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞 𝐚𝐬 𝐢𝐭 𝐬𝐜𝐚𝐥𝐞𝐬? What’s most impressive isn’t the choreography. 𝐈𝐭’𝐬 𝐭𝐡𝐞 𝐬𝐩𝐞𝐞𝐝. 🚀 From viral folk dance to high-precision physical coordination in 12 months. Five years in combined hardware + AI cycles is not five “normal” years. It’s a different time scale. 🤯 Video below 👇 #AI #Robotics #Automation #DigitalTransformation #Unitree https://lnkd.in/e4J6DM_x

𝐓𝐡𝐞 𝐦𝐨𝐦𝐞𝐧𝐭 𝐦𝐚𝐜𝐡𝐢𝐧𝐞𝐬 𝐥𝐞𝐚𝐫𝐧 𝐭𝐨 𝐦𝐨𝐯𝐞 – 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐭𝐨 𝐭𝐡𝐢𝐧𝐤 – 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐬𝐡𝐢𝐟𝐭𝐬. In a recent client workshop, we analysed China’s rise of 𝐝𝐚𝐫𝐤 𝐟𝐚𝐜𝐭𝐨𝐫𝐢𝐞𝐬 – fully autonomous plants running with almost 𝐧𝐨 𝐡𝐮𝐦𝐚𝐧 𝐩𝐫𝐞𝐬𝐞𝐧𝐜𝐞. What struck everyone in the room was not the robotics itself, but the 𝐬𝐩𝐞𝐞𝐝. Some sites run 24/7 with 𝟕𝟎–𝟖𝟎 𝐩𝐞𝐫𝐜𝐞𝐧𝐭 𝐟𝐞𝐰𝐞𝐫 𝐰𝐨𝐫𝐤𝐞𝐫𝐬, guided by fleets of autonomous mobile robots and vision-driven quality systems. And then we looked west. ✔️ Amazon already operates more than 𝟕𝟓𝟎,𝟎𝟎𝟎 𝐫𝐨𝐛𝐨𝐭𝐬 across its fulfilment network. ✔️ Manufacturing costs for humanoid robots dropped 𝟒𝟎 𝐩𝐞𝐫𝐜𝐞𝐧𝐭 𝐢𝐧 𝐨𝐧𝐞 𝐲𝐞𝐚𝐫. ✔️ The global robotics market is projected to hit 𝐔𝐒𝐃 𝟑𝟗𝟐 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 by 2033. The message is simple: 𝐭𝐡𝐢𝐬 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 “𝐟𝐮𝐭𝐮𝐫𝐞 𝐰𝐨𝐫𝐤”. 𝐈𝐭 𝐢𝐬 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐢𝐯𝐞 𝐫𝐞𝐚𝐥𝐢𝐭𝐲. But the deeper shift is something else entirely. For the first time, intelligence isn’t staying behind screens. It is entering the physical world – perceiving, reasoning, deciding and acting 𝐢𝐧 𝐫𝐞𝐚𝐥 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭𝐬. What #Deloitte calls 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞. And with it, leadership must change at its core. In our latest work, Deloitte introduced the 𝟔𝐏𝐬 for leaders navigating this shift: 𝐏𝐫𝐞𝐩𝐚𝐫𝐞, 𝐏𝐞𝐫𝐜𝐞𝐢𝐯𝐞, 𝐏𝐫𝐨𝐜𝐞𝐬𝐬, 𝐏𝐞𝐫𝐟𝐨𝐫𝐦, 𝐏𝐫𝐨𝐜𝐞𝐞𝐝, 𝐏𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 – a roadmap stretching from data foundations to workforce design and long-term societal impact. Every executive said the same thing afterwards: “𝐈 𝐝𝐢𝐝𝐧’𝐭 𝐫𝐞𝐚𝐥𝐢𝐬𝐞 𝐡𝐨𝐰 𝐛𝐢𝐠 𝐭𝐡𝐞 𝐨𝐫𝐠𝐚𝐧𝐢𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐬𝐡𝐢𝐟𝐭 𝐦𝐮𝐬𝐭 𝐛𝐞.” Because this isn’t just automation. It is 𝐦𝐚𝐜𝐡𝐢𝐧𝐞𝐬 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐦𝐚𝐤𝐞𝐫𝐬. And that forces new questions: ❓𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐫𝐮𝐬𝐭 𝐦𝐞𝐚𝐧 𝐰𝐡𝐞𝐧 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐲 𝐡𝐚𝐬 𝐚 𝐛𝐨𝐝𝐲? ❓𝐇𝐨𝐰 𝐝𝐨 𝐰𝐞 𝐛𝐮𝐢𝐥𝐝 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 𝐰𝐡𝐞𝐫𝐞 𝐡𝐮𝐦𝐚𝐧𝐬 𝐚𝐧𝐝 𝐦𝐚𝐜𝐡𝐢𝐧𝐞𝐬 𝐜𝐨-𝐨𝐰𝐧 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬? ❓𝐖𝐡𝐞𝐫𝐞 𝐝𝐨 𝐰𝐞 𝐫𝐞𝐝𝐫𝐚𝐰 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲? The next decade won’t reward the fastest adopters. It will reward the 𝐛𝐫𝐚𝐯𝐞𝐬𝐭 𝐫𝐞𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐫𝐬. Curious where you stand: 𝐈𝐟 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐜𝐚𝐧 𝐧𝐨𝐰 𝐰𝐚𝐥𝐤 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐫𝐨𝐨𝐦 𝐰𝐢𝐭𝐡 𝐮𝐬 – 𝐡𝐨𝐰 𝐝𝐨 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐲𝐨𝐮𝐫 𝐨𝐫𝐠𝐚𝐧𝐢𝐬𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐞𝐯𝐨𝐥𝐯𝐞? #PhysicalIntelligence #FutureOfWork #LeadershipTransformation #RoboticsReimagined #HumanAndMachine

How did an iconic hotel in Singapore, Marina Bay Sands, cut labor dependency with AI and robots by 30% while simultaneously generating 162,000 manhours of greater value with its staff? The secret lies in treating AI and robotics as a partner for your people, not a replacement. Marina Bay Sands (known as MBS here) in Singapore, a large-scale integrated hotel + casino + mall, is demonstrating that AI and robotics are now fully viable for complex, large-scale hospitality operations. MBS became the first in Singapore’s hospitality industry to deploy a fleet of 12 Autonomous Mobile Robots (AMRs) for back-of-house deliveries across its hotel and convention center. Facing a 35 percent surge in delivery volumes between 2019 and 2023, the resort turned to automation to manage growing demands. The deployment of AMRs, which handle manpower-heavy tasks, carrying up to 300kg and moving at 84 meters per minute, resulted in a 30 percent drop in labor dependency. However, the crucial insight for long-term value and staff adoption is the strategic focus on the workforce, repurposing Talent for Sustainable Value. MBS's comprehensive automation efforts, which include over 200 automated work processes across various functions (like 'The Wardrobe' system managing over 200,000 uniforms via ultra-high-frequency chips and automated stocktaking, or the automated upcycling of 100% of food waste by end of 2025), have resulted in the repurposing of over 162,000 manhours annually towards greater value-added tasks. For example, instead of job elimination, members of the procurement and supply chain teams who previously handled manual deliveries are now trained in new, higher-value roles such as inventory management and robot dispatching. By investing in innovation and fostering a culture of productivity, MBS leadership proves that successful integration requires to be people-driven just as much as you are AI-driven. Repurposing staff generates motivation, long-term value, and ensures technology adoption, making automation a key driver of human capital enhancement. full article here: https://lnkd.in/g_M3bpPs #HospitalityInnovation #AIinHospitality #Robotics #WorkforceDevelopment #FutureofWork #MarinaBaySands #GenAI #Leadership #Singapore #TheWayForward

It is a mistake to view the current evolution of work as a simple matter of adopting new software or learning to write better prompts for a machine. We have spent decades tying our professional value to output, measured by how quickly we can process information or move through a list of technical tasks. This focus on speed and volume turned many into operators of digital assembly lines, where the primary goal was always to produce more in less time. The arrival of advanced technology changes that calculation, as it handles the repetitive and analytical parts of our roles with an efficiency no person can match. Ryan Roslansky, the CEO of LinkedIn and EVP of Microsoft Office & Copilot, and Aneesh Raman, LinkedIn’s Chief Economic Opportunity Officer, address this fundamental change in their book, Open to Work. They suggest that every job is essentially a collection of different tasks, many of which are now better suited for automation. The ideas they have shared point toward a necessary transition in how we view our careers. They argue that as the burden of production moves to machines, professionals must reclaim the human capabilities that have been sidelined by the pursuit of efficiency. This shift requires us to move away from the mindset of being a technical processor and instead focus on curiosity and communication. Our future at work depends on our ability to ask better questions and connect with others in ways that technology cannot replicate. By allowing tools to handle high-volume work, we can devote our energy to judgment and creativity. The challenge is deciding how to spend our time once the most demanding parts of our work are handled for us.

A new Harvard Business School study involving 700+ professionals at Procter & Gamble reveals AI is reshaping how teams work—moving to what researchers call a “cybernetic teammate.” Teams using AI (specifically ChatGPT-4 and 4o) consistently outperformed others, producing better solutions faster, while also fostering more cross-functional collaboration. AI broke down traditional silos, allowing people to contribute outside their usual expertise and enabling individuals to handle tasks that previously required entire teams. Interestingly, while AI users felt less confident, they did significantly better work and reported more positive emotions—hinting at a future where AI not only accelerates output but also improves the work experience. Key takeaway: Organizations that treat AI as just another tool are underestimating its impact. This study suggests we’re only seeing the floor of AI’s potential. As adoption and skills mature, the performance gap will widen—fast. The divide is no longer between teams—it's between those who embrace AI and those who don't. #ai