Forbes Business
중도 성향
IT/기술
Could Americans Build Wealth Through AI? Why Trump May Be Considering Equity-Sharing Scheme
The policy has attracted support from both sides of the aisle on how to respond to AI, but economists still have concerns.
IT/기술 · "SIDES" · 총 16건
필터 보기현재 지수
50.3
0 = 부정 우세
50 = 중립
100 = 긍정 우세
최근 7일 기준 80,589건을 분석한 결과, 뉴스 심리지수는 50.2(균형)입니다. 긍정 3,922건(4.9%)·중립 74,780건(92.8%)·부정 1,887건(2.3%)이며, 중립 비중이 뚜렷하게 높습니다. 성향 지수는 종합 14.5(중도 균형)입니다.
The policy has attracted support from both sides of the aisle on how to respond to AI, but economists still have concerns.
Chronologically, Control Resonant is a sequel to 2019's Control. But in most other ways, the games aren't directly connected. To developer Remedy, they're more like two sides of the same coin. When Resonant was first revealed last year, creative director Mikael Kasurinen said you can play the games in any order. The world of Control […]
“Why wouldn’t you want to be in both Pepsi and Coke?” says one venture capitalist. “It’s the same here.”
Chief Executive John Lee announced a series of innovation and technology agreements with Uzbekistan, following a visit to the Central Asian nation’s flagship IT hub on Friday. Writing on his social media, Lee detailed the delegation’s visit to Uzbekistan IT Park, a national special economic zone in Tashkent, where they met with Ayubkhon Sultanov, Uzbekistan’s First Deputy Minister of Digital Technologies. He said the IT Park serves as a core engine for Uzbekistan’s digital economic transformation, offering tax incentives and rental concessions and facilitating visa arrangements to attract tech enterprises and talent. The park, he said, is central to implementing the “Digital Uzbekistan 2030 Strategy” and the country’s national AI Strategy. The CE noted that while Uzbekistan is accelerating its economic transformation and I&T development, Hong Kong — as an international financial centre — is actively building itself into a global innovation hub. “Leveraging its world-class financing platform, professional services and unique bridging role connecting the mainland and international markets, Hong Kong is highly complementary to Uzbekistan’s development,” the CE wrote. Both places, he added, are important partners within the Belt and Road Initiative and can strengthen exchanges of development experience. Lee said senior executives from the Hong Kong Science and Technology Parks Corporation (HKSTP), Cyberport and the Hong Kong-Shenzhen Innovation and Technology Park (HSITP) signed memoranda of understanding (MoUs) with IT Park during the visit. The agreements aim to establish platforms for startup incubation, acceleration programmes and cross-border market access. Under the deals, Uzbekistan’s I&T companies would gain a strategic gateway into the Guangdong-Hong Kong-Macao Greater Bay Area and global markets, while Hong Kong enterprises would be able to tap into Uzbekistan’s young IT talent pool for software development and innovative collaborations. “Going forward, we can further synergise the innovation and technology ecosystems of both sides, explore collaborative projects and achieve complementary advantages and win-win partnerships,” the CE said. Lee concludes his Central Asia trip on Friday. Edited by Tony Sabine
Opera makers have always engaged with the latest inventions while also preserving historic crafts. I believe it’s possible to look both forwards and backwards in this fast-evolving landscape The disquiet and distrust surrounding artificial intelligence among artists and creatives remain real and consequential, and the language used by leading arts commentators is often apocalyptic: AI will decimate the arts, it is evil, it is the devil. Like many emerging technologies, AI has been driven by the corporations at the forefront of its creation. Introduced to the public at a rapid rate and continuously evolving, machine learning has become closely entwined with fear, antipathy and foreboding. At the same time, its powers and possibilities are expanding exponentially, becoming embedded in almost every aspect of human activity. The upcoming RBO/SHIFT festival at the Royal Opera House aims to interrogate all sides of this fast-evolving landscape to enable artists, performers, creatives and audiences to think deeply and widely about where we are now, and where we may be tomorrow. Machine learning represents a seismic shift, both in society and in the arts, and we need storytellers, artists, teachers and thinkers in this space to help determine the direction of that shift and help us navigate this unfamiliar territory. Continue reading...
Citi finds AI use jumped to 22% from 13% in a year, even as principals warn data privacy is “non-negotiable” and fear back-door exposure via SaaS tools.
NC AI said Sunday it signed a strategic business agreement with Posco DX on the joint development of a robot foundation model and for broader technical cooperation. The signing ceremony was attended by Kim Min-jae, chief technology officer at NC AI, and Yoon Suk-june, head of the robot automation center of Posco DX, along with senior officials from both companies. The two sides discussed long-term cooperation plans to enhance competitiveness in robot intelligence technologies and industrial AI.
Snowflake and Okta both saw record stock pops this week as investors found favor in their AI software strategies.
Shanghai: China's electronics giant Huawei is using a new principle for its chip designing framework that focuses more on cutting transmission time than shrinking transistors. The company plans to use innovative technologies like LogicFolding based on this principle to continuously compress signal propagation delay and improve transistor density.The current chip design framework rests on Moore's law which dates back decades when Intel co-founder Gordon Moore posited in 1965 that the number of transistors on a microchip will double every two years.The Tau Scaling principle could be a revolutionary step in the future of chip designing as it shifts focus from geometric scaling to time scaling. The principle that governs modern advanced chips is to shrink the size of transistors to fit onto a microchip. But this mechanism may have a handicap. It may not be easy to shrink them beyond a point. This is where time scaling becomes useful as it makes cutting signal transmission time the underlying principle of future chip designs.Also Read: PLI 2.0: India bets big on making more of the smartphone at homeThe innovative core technologies like LogicFolding, which Huawei will use for its Kirin chips scheduled to launch in Fall 2026, will work on the Tau Scaling principle in order to drive up performance, energy efficiency, and transistor density."With the t Scaling Law, we look forward to working closely with scientists, engineers, and industry partners around the world to drive the sustainable development of the semiconductor and electronics industries," Huawei's semiconductor chief He Tingbo noted.Huawei's new chip design breakthrough will help the chip maker to sidestep the US sanctions that restrict access to advanced lithography machines from ASML.Also Read: Indian semicon firm Netrasemi plans mass production of its first chip this yearBy 2031, Huawei is aiming for high-end chips based on the t Scaling Law that are expected to feature a transistor density that is equivalent to 14 A (1.4 nm) processes."This is a breakthrough for Huawei, but it's not a threat for TSMC," Reuters quoted Nvidia CEO Jensen Huang, who was in Taipei on Thursday."TSMC has been using die stacking and 3D packaging for how long now? Almost 10 years. And so TSMC's technology is very advanced," he added.A Reuters report mentioned Bernstein analysts cautioning in a note that while stacking multiple chip layers boosts transistor density, there's risk of increasing power density and overheating chips.
A self-described Boomer explores the generational war with Gen Z over housing costs, student debt and AI fears, arguing both sides have valid points.
Huawei Technologies has engineered a workaround to one of China’s most crippling chipmaking bottlenecks, but analysts warn that the nation’s path to semiconductor independence is still constrained by manufacturing challenges. The US-sanctioned tech giant on Monday introduced a new scaling law and a chip architecture designed to deliver products equivalent to an advanced 1.4-nanometre processing node by 2031. If true, the innovation marks a significant milestone for Huawei, which has been cut off...
Google's senior vice president of technology and society regrets that the group's innovations are not being rolled out in France, a country he considers too resistant to change. He hopes to reassure the public about the risks artificial intelligence poses to jobs.
ISLAMABAD: Pakistan and the Asian Infrastructure Investment Bank (AIIB) on Tuesday signed a $320 million loan agreement for the reconstruction and improvement of critical sections of the N-5 highway — the country’s longest national highway from Karachi to Torkham near the Afghan border. The loan agreement was signed for “Reconstruction of National Highway N-5 under Pakistan’s Resilient Recovery, Rehabilitation and Reconstruction Framework Project,” amounting to $320.16 million. The project will cover critical sections of the N-5, which traverses Sindh, Punjab, and Khyber Pakhtunkhwa, serving as a backbone of Pakistan’s transport network. The loan agreement was signed by Muhammad Humair Karim Kidwai, Secretary, Economic Affairs Division, on behalf of the Government of Pakistan, and Mr Konstantin Limitovskiy, Chief Investment Officer, Public Sector & Project and Corporate Finance (Global) Clients of the Beijing-based AIIB. Federal Minister for Economic Affairs Ahad Khan Cheema also attended the signing ceremony. A separate project agreement was also signed between the AIIB and the National Highway Authority (NHA). Pakistan has appreciated its longstanding partnership with the AIIB, which has consistently supported the country’s development sector, the economic affairs minister said. The minister said the N-5 project would not only strengthen the country’s resilient infrastructure but would also play a significant role in enhancing regional connectivity, trade activities and economic growth. The EAD secretary emphasised that the N-5 project will further deepen this partnership and strengthen mutual trust and cooperation, while advancing Pakistan’s sustainable infrastructure network. The N-5 corridor holds immense importance as it connects key regions of Pakistan, enhancing regional connectivity, strengthening sustainable infrastructure, and supporting economic growth across the country, he said. The chief investment officer of the Asian Infrastructure Investment Bank (AIIB) highlighted the strong development collaboration with the Government of Pakistan and stressed the strategic importance of the N-5 project, noting that it forms part of an international transport corridor. He said the N-5 reconstruction would be undertaken using modern, green, and climate-resilient design standards with state-of-the-art infrastructure, ensuring efficiency, sustainability, and long-term durability. The signing marks an important milestone in Pakistan-AIIB cooperation and reflects the shared commitment of both sides toward building resilient infrastructure, enhancing regional connectivity and promoting sustainable economic development, the EAD said in a statement. The agreement follows a number of AIIB investments in Pakistan. Most recently — supported by the AIIB and Asian Development Bank — Pakistan issued its inaugural Panda bond in China’s onshore capital market, raising $250 million. In 2019, the AIIB said it would invest over $1 billion in the country.
Editor’s note: If you’d like to pinpoint the instant when the world entered the nuclear age, 5:29:45 a.m. Mountain War Time on 16 July 1945, is an excellent choice. That was the moment when human beings first unleashed the power of the nucleus in an immense, blinding ball of fire above a gloomy stretch of desert in the Jornada del Muerto basin in New Mexico. Emily Seyl’s Trinity: An Illustrated History of the World’s First Atomic Test (The University of Chicago Press) offers hundreds of startlingly vivid photographs of the Manhattan Project that emerged from a 20-year restoration effort. This excerpt and the accompanying photos record the massive effort to capture the awesome detonation of “the Gadget.” aspect_ratioReprinted with permission from Trinity: An Illustrated History of the World’s First Atomic Test by Emily Seyl with contributions by Alan B. Carr, published by The University of Chicago Press. © 2026 by The University of Chicago. All rights reserved. In the North 10,000 photography bunker, Berlyn Brixner was listening to the countdown on a loudspeaker, his head inside a turret loaded with cameras and film. He was one of the only people instructed to look toward the blast—through his welder’s glasses—ready to follow the path of the fireball as it launched into the sky. The two Mitchell movie cameras at his station would deliver the best footage to come of the Trinity test, used by Los Alamos scientists to make some of the first measurements of the effects of a nuclear explosion. Related: New Trinity Book Uncovers Images of the First Atomic Test When the detonators fired, the cameras captured what Brixner could not have seen—the very first light of a violent, silent sea of energy unfurling into the basin. As 32 blocks of high explosives erupted all together, their incredible force surged inward toward the sleeping plutonium core, compressing the dense sphere of metal instantaneously from all sides and bringing its atoms impossibly close together. A carefully timed burst of neutrons sowed momentary, uncontrolled chaos, and then, as quickly as it began, the fission chain reaction ended. Footage from a high-speed Fastax camera in Brixner’s bunker, shot through a thick glass porthole, shows a translucent orb bursting through the darkness less than a hundredth of a second after detonation, as a rush of heat, light, and matter blew apart the Gadget. When the brightness faded enough for witnesses to make out ground zero, they saw a wall of dust rise up around a brilliant, shape-shifting, multicolored ball of flames—forming a fiery cloud that shot into the sky atop a twisting stream of debris. The camera footage tells a story no less dramatic but hundreds of times more intricate, preserving the moment for scientists to return to again and again to measure and describe the behavior of the fireball and other visible effects with exacting detail. On balance, the photography effort was a huge success, despite only 11 of the 52 cameras producing satisfactory images. By arranging those cameras at intentionally staggered distances, complementary angles, and with a broad spectrum of frame rates and focal lengths, the Spectrographic and Photographic Measurements Group was able to piece together a remarkably complete picture of their subject. On 12 July 1945, Herbert Lehr, a U.S. Army sergeant and electrical engineer assigned to Los Alamos, delivered the plutonium core to the McDonald ranch house, where the bomb was assembled. Los Alamos National Laboratory According to the group’s leader, Julian Mack, the more than 100,000 frames that were captured still “give no idea of the brightness, or of time and space scales.” Mack attributed fortune, as much as foresight, to the photographic record that was made, especially during the earliest phase of the blast. Indeed, the explosion was several times more powerful than predicted, and the intensity of its effects overwhelmed many of the cameras and diagnostic instruments. The human observers were similarly overcome. “The shot was truly awe-inspiring,” said Norris Bradbury, the physicist who would succeed Robert Oppenheimer as director of Los Alamos. “Most experiences in life can be comprehended by prior experiences, but the atom bomb did not fit into any preconception possessed by anybody. The most startling feature was the intense light.” Norris Bradbury, the physicist responsible for the final assembly of the Gadget, stands next to the partially assembled bomb at the top of the shot tower. The cables on the outside of the bomb would transmit the signals to trigger the synchronized detonations of conventional explosives, which would then create the inward-directed shock wave that would compress the bomb’s plutonium core. Bradbury would go on to succeed Robert Oppenheimer as director of Los Alamos on 17 October 1945.Los Alamos National Laboratory It is a common sentiment that words and even pictures pale in comparison to the experience of the explosion. Even so, soldiers, scientists, and many other witnesses have added their firsthand accounts—often absorbing and poetic—to complement the trove of hard data collected during the test shot. They describe an intense and blinding brightness that filled the basin with daytime; an ominous, darkening cloud rearing its head in eerie silence; the wait for the invisible wave rushing out from the heart of the Gadget; and the mighty roar that arrived at last, in a thunder, and seemed never to leave. Physicist Isidor Isaac Rabi, watching from 20 miles away, remembered, “It blasted; it pounced; it bored its way right through you.” James Chadwick, head of the British contingent of scientists who joined the Manhattan Project, later said, “Although I had lived through this moment in my imagination many times during the past few years and everything happened almost as I had pictured it, the reality was shattering.” The blast, captured with an assortment of high-speed and motion-picture cameras, shows the fireball expanding between 25 milliseconds and 60 seconds, by which time the mushroom cloud is over 3 kilometers high.Los Alamos National Laboratory And physicist George Kistiakowsky found himself certain that “at the end of the world—in the last millisecond of the Earth’s existence—the last human will see what we saw.”
This article is brought to you by DAIMON Robotics. This April, Hong Kong-based DAIMON Robotics has released Daimon-Infinity, which it describes as the largest omni-modal robotic dataset for physical AI, featuring high resolution tactile sensing and spanning a wide range of tasks from folding laundry at home to manufacturing on factory assembly lines. The project is supported by collaborative efforts of partners across China and the globe, including Google DeepMind, Northwestern University, and the National University of Singapore. The move signals a key strategic initiative for DAIMON, a two-and-a-half-year-old company known for its advanced tactile sensor hardware, most notably a monochromatic, vision-based tactile sensor that packs over 110,000 effective sensing units into a fingertip-sized module. Drawing on its high-resolution tactile sensing technology and a distributed out-of-lab collection network capable of generating millions of hours of data annually, DAIMON is building large-scale robot manipulation datasets that include vast amounts of tactile sensing data. To accelerate the real-world deployment of embodied AI, the company has also open-sourced 10,000 hours of its data. Prof. Michael Yu Wang, co-founder and chief scientist at DAIMON Robotics, has pioneered Vision-Tactile-Language-Action (VTLA) architecture, elevating the tactile to a modality on par with vision.DAIMON Robotics Behind the strategy is Prof. Michael Yu Wang, DAIMON’s co-founder and chief scientist. Prof. Wang earned his PhD at Carnegie Mellon — studying manipulation under Matt Mason — and went on to found the Robotics Institute at the Hong Kong University of Science and Technology. An IEEE Fellow and former Editor-in-Chief of IEEE Transactions on Automation Science and Engineering, he has spent roughly four decades in the field. His objective is to address the missing “insensitivity” of robot manipulation, which practically relies on the dominant Vision-Language-Action (VLA) model. He and his team have pioneered Vision-Tactile-Language-Action (VTLA) architecture, elevating the tactile to a modality on par with vision. We spoke with Prof. Wang about how tactile feedback aims to change dexterous manipulation, how the dataset initiative is foreseen to improve our understanding of robotic hands in natural environments, and where — from hotels to convenience stores in China — he sees touch-enabled robots making their first real-world inroads. Daimon-Infinity is the world’s largest omni-modal dataset for Physical AI, featuring million-hour scale multimodal data, ultra-high-res tactile feedback, data from 80+ real scenarios and 2,000+ human skills, and more.DAIMON Robotics The Dataset Initiative This month, DAIMON Robotics released the largest and most comprehensive robotic manipulation dataset with multiple leading academic institutions and enterprises. Why releasing the dataset now, rather than continuing to focus on product development? What impact will this have on the embodied intelligence industry? DAIMON Robotics has been around for almost two and a half years. We have been committed to developing high-resolution, multimodal tactile sensing devices to perceive the interaction between a robot’s hand (particularly its fingertips) and objects. Our devices have become quite robust. They are now accepted and used by a large segment of users, including academic and research institutes as well as leading humanoid robotics companies. As embodied AI continues to advance, the critical role of data has been clearer. Data scarcity remains a primary bottleneck in robot learning, particularly the lack of physical interaction data, which is essential for robots to operate effectively in the real world. Consequently, data quality, reliability, and cost have become major concerns in both research and commercial development. This is exactly where DAIMON excels. Our vision-based tactile technology captures high-quality, multimodal tactile data. Beyond basic contact forces, it records deformation, slip and friction, material properties and surface textures — enabling a comprehensive reconstruction of physical interactions. Building on our expertise in multimodal fusion, we have developed a robust data processing pipeline that seamlessly integrates tactile feedback with vision, motion trajectories, and natural language, transforming raw inputs into training-ready dataset for machine learning models. Recognizing the industry-wide data gap, we view large-scale data collection not only as our unique competitive advantage, but as a responsibility to the broader community. By building and open-sourcing the dataset, we aim to provide the high-quality “fuel” needed to power embodied AI, ultimately accelerating the real-world deployment of general-purpose robotic foundation models. The robotics industry is highly competitive, and many teams have chosen to focus on data. DAIMON is releasing a large and highly comprehensive cross-embodiment, vision-based tactile multimodal robotic manipulation dataset. How were you able to achieve this? We have a dedicated in-house team focused on expanding our capabilities, including building hardware devices and developing our own large-scale model. Although we are a relatively small company, our core tactile sensing technology and innovative data collection paradigm enable us to build large-scale dataset. Our approach is to broaden our offering. We have built the world’s largest distributed out-of-lab data collection network. Rather than relying on centralized data factories, this lightweight and scalable system allows data to be gathered across diverse real-world environments, enabling us to generate millions of hours of data per year. “To drive the advancement of the entire embodied AI field, we have open-sourced 10,000 hours of the dataset for the broader community.” —Prof. Michael Yu Wang, DAIMON Robotics This dataset is being jointly developed with several institutions worldwide. What roles did they play in its development, and how will the dataset benefit their research and products? Besides China based teams, our partners include leading research groups from universities, such as Northwestern University and the National University of Singapore, as well as top global enterprises like Google DeepMind and China Mobile. Their decision to partner with DAIMON is a strong testament to the value of our tactile-rich dataset. Among the companies involved there are some that have already built their own models but are now incorporating tactile information. By deploying our data collection devices across research, manufacturing and other real-world scenarios, they help us to gather highly practical, application-driven data. In turn, our partners leverage the data to train models tailored to their specific use cases. Furthermore, to drive the advancement of the entire embodied AI field, we have open-sourced 10,000 hours of the dataset for the broader community. Equipped with Daimon’s visuotactile sensor, the gripper delicately senses contact and precisely controls force to pick up a fragile eggshell.Daimon Robotics From VLA to VTLA: Why Tactile Sensing Changes the Equation The mainstream paradigm in robotics is currently the Vision-Language-Action (VLA) model, but your team has proposed a Vision-Tactile-Language-Action (VTLA) model. Why is it necessary to incorporate tactile sensing? What does it enable robots to achieve, and which tasks are likely to fail without tactile feedback? Over these years of working to make generalist robots capable of performing manipulation tasks, especially dexterous manipulation — not just power grasping or holding an object, but manipulating objects and using tools to impart forces and motion onto parts — we see these robots being used in household as well as industrial assembly settings. It is well established that tactile information is essential for providing feedback about contact states so that robots can guide their hands and fingers to perform reliable manipulation. Without tactile sensing, robots are severely limited. They struggle to locate objects in dark environments, and without slip detection, they can easily drop fragile items like glass. Furthermore, the inability to precisely control force often leads to failed manipulation tasks or, in severe cases, physical damage. Naturally, the VLA approach needs to be enhanced to incorporate tactile information. We expanded the VLA framework to incorporate tactile data, creating the VTLA model. An additional benefit of our tactile sensor is that it is vision-based: We capture visual images of the deformation on the fingertip surface. We capture multiple images in a time sequence that encodes contact information, from which we can infer forces and other contact states. This aligns well with the visual framework that VLA is based upon. Having tactile information in a visual image format makes it naturally suitable for integration into the VLA framework, transforming it into a VTLA system. That is the key advantage: Vision-based tactile sensors provide very high resolution at the pixel level, and this data can be incorporated into the framework, whether it is an end-to-end model or another type of architecture. DAIMON has been known for its vision-based tactile sensors that can pack over 110,000 effective sensing units.DAIMON Robotics The Technology: Monochromatic Vision-based Tactile Sensing You and your team have spent many years deeply engaged in vision-based tactile sensing and have developed the world’s first monochromatic vision-based tactile sensing technology. Why did you choose this technical path? Once we started investigating tactile sensors, we understood our needs. We wanted sensors that closely mimic what we have under our fingertip skin. Physiological studies have well documented the capabilities humans have at their fingertips — knowing what we touch, what kind of material it is, how forces are distributed, and whether it is moving into the right position as our brain controls our hands. We knew that replicating these capabilities on a robot hand’s fingertips would help considerably. When we surveyed existing technologies, we found many types, including vision-based tactile sensors with tri-color optics and other simpler designs. We decided to integrate the best of these into an engineering-robust solution that works well without being overly complicated, keeping cost, reliability, and sensitivity within a satisfactory range, thus ultimately developing a monochromatic vision-based tactile sensing technique. This is fundamentally an engineering approach rather than a purely scientific one, since a great deal of foundational research already existed. With the growing realization of the necessity of tactile data, all of this will advance hand in hand. DAIMON vision-based tactile sensor captures high-quality, multimodal tactile data.DAIMON Robotics Last year, DAIMON launched a multi-dimensional, high-resolution, high-frequency vision-based tactile sensor. Compared with traditional tactile sensors, where does its core advantage lie? Which industries could it potentially transform? The key features of our sensors are the density of distributed force measurement and the deformation we can capture over the area of a fingertip. I believe we have the highest density in terms of sensing units. That is one very important metric. The other is dynamics: the frequency and bandwidth — how quickly we can detect force changes, transmit signals, and process them in real time. Other important aspects are largely engineering-related, such as reliability, drift, durability of the soft surface, and resistance to interference from magnetic, optical, or environmental factors. A growing number of researchers and companies are recognizing the importance of tactile sensing and adopting our technology. I believe the advances in tactile sensing will elevate the entire community and industry to a higher level. One of our potential customers is deploying humanoid robots in a small convenience store, with densely packed shelves where shelf space is at a premium. The robot needs to reach into very tight spaces — tighter than books on a shelf — to pick out an object. Current two-jaw parallel grippers cannot fit into most of these spaces. Observing how humans pick up objects, you clearly need at least three slim fingers to touch and roll the object toward you and secure it. Thus, we are starting to see very specific needs where tactile sensing capabilities are essential. From Academia to Startup After 40 years in academia — founding the HKUST Robotics Institute, earning prestigious honors including IEEE Fellow, and serving as Editor-in-Chief of IEEE TASE — what motivated you to found DAIMON Robotics? I have come a long way. I started learning robotics during my PhD at Carnegie Mellon, where there were truly remarkable groups working on locomotion under Marc Raibert, who founded Boston Dynamics, and on manipulation under my advisor, Matt Mason, a leader in the field. We have been working on dexterous manipulation, not only at Carnegie Mellon, but globally for many years. However, progress has been limited for a long time, especially in building dexterous hands and making them work. Only recently have locomotion robots truly taken off, and only in the last few years have we begun to see major advancements in robot hands. There is clearly room for advancing manipulation capabilities, which would enable robots to do work like humans. While at Hong Kong University of Science and Technology, I saw increasingly greater people entering this area in the form of students and postdoctoral researchers. We wanted to jumpstart our effort by leveraging the available capital and talent resources. Fortunately, one of my postdocs, Dr. Duan Jianghua, has a strong sense for commercial opportunities. Recognizing the rapid growth of robotics market and the unique value that our vision-based tactile sensing technology could bring, together we started DAIMON Robotics, and it has progressed well. The community has grown tremendously in China, Japan, Korea, the U.S., and Europe. Robots equipped with DAIMON technology have been deployed in factory settings. The company aims to enable robots to achieve “embodied intelligence” and close the gap between what they can see and what they can feel.DAIMON Robotics Business Model and Commercial Strategy What is DAIMON’s current business model and strategic focus? What role does the dataset release play in your commercial strategy? We started as a device company focused on making highly capable tactile sensors, especially for robot hands. But as technology and business developed, everyone realized it is not just about one component, rather the entire technology chain: devices, data of adequate quality and quantity, and finally the right framework to build, train, and deploy models on robots in real application environments. Our business strategy is best described as “3D”: Devices, Data, and Deployment. We build devices for data collection, our own ecosystem, and for deploying them in our partners’ potential application domains. This enables the collection of real-world tactile-rich data and complete closed-loop validation. This will become an integral part of the 3D business model. Most startups in this space are following a similar path until eventually some may become more specialized or more tightly integrated with other companies. For now, it is mostly vertical integration. Embodied Skills and the Convergence Moment You’ve introduced the concept of “embodied skills” as essential for humanoid robots to move beyond having just an advanced AI “brain.” What prompted this insight? What new capabilities could embodied skills enable? After the rapid evolution of models and hardware over the past two years, has your definition or roadmap for embodied skills evolved? We have come a long way now see a convergence point where electrical, electronic, and mechatronic hardware technologies have advanced tremendously in last two decades. Robots are now fully electric, do not require hydraulics, because hardware has evolved rapidly. Modern electronics provide tremendous bandwidth with high torques. If we can build intelligence into these systems, we can create truly humanoid robots with the ability to operate in unstructured environments, make decisions, and take actions autonomously. “Our vision is for robots to achieve robust manipulation capabilities and evolve into reliable partners for humans.” —Prof. Michael Yu Wang, DAIMON Robotics AI has arrived at exactly the right time. Enormous resources have been invested in AI development, especially large language models, which are now being generalized into world models that enable physical AI capabilities. We would like to see these manifested in real-world systems. While both AI and core hardware technologies continue to evolve, the focus is much clearer now. For example, human-sized robots are preferred in a home environment. This is an exciting domain with a promise of great societal benefit if we can eventually achieve safe, reliable, and cost-effective robots. The Road to Real-World Deployment Today, many robots can deliver impressive demos, yet there remains a gap before they truly enter real-world applications. What could be a potential trigger for real-world deployment? Which scenarios are most likely to achieve large-scale deployment first? I think the road toward large-scale deployment of generalist robots is still long, but we are starting to see signs of feasibility within specific domains. It is very similar to autonomous vehicles, where we are yet to see full deployment of robo-taxis, while we have already started to find mobile robots and smaller vehicles widely deployed in the hospitality industry. Virtually every major hotel in China now has a delivery robot — no arms, just a vehicle that picks up items from the hotel lobby (e.g., food deliveries). The delivery person just loads the food and selects the room number. It is up to the robot thereafter to navigate and reach the guest’s room, which includes using the elevator, to deliver the food. This is already nearly 100 percent deployed in major Chinese hotels. Hotel and restaurant robots are viewed as a model for deploying humanoid robots in specific domains like overnight drugstores and convenience stores. I expect complete deployment in such settings within a short timeframe, followed by other applications. Overall, we can expect autonomous robots, including humanoids, to progressively penetrate specific sectors, delivering value in each and expanding into others. Ultimately, our vision is for robots to achieve robust manipulation capabilities and evolve into reliable partners for humans. By seamlessly integrating into our homes and daily lives, they will genuinely benefit and serve humanity. This interview has been edited for length and clarity.