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🇺🇸 미국 · IT/기술 · "UNLOCK" · 총 18건
필터 보기현재 지수
50.0
0 = 부정 우세
50 = 중립
100 = 긍정 우세
최근 7일 기준 11,815건을 분석한 결과, 뉴스 심리지수는 50.0(균형)입니다. 긍정 1건(0.0%)·중립 11,813건(100.0%)·부정 1건(0.0%)이며, 중립 비중이 뚜렷하게 높습니다. 성향 지수는 종합 18.8(중도 균형)입니다.
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Electrons are great. We use them to move vehicles, illuminate cities, and, of course, compute. But computation is not confined to the world of electronics. And shifting to alternative nonelectronic realms can unlock unique advantages: Photonic chips, for instance, process information with light while generating little heat. Another compelling alternative is fluidics, which uses pressurized gases or liquids to build logic circuits. Pioneered in the 1960s but sidelined by microchips, the field reemerged in the 1990s as “microfluidics.” This approach aims to shrink laboratories onto a single chip by creating microscopic fluid channels with integrated micropneumatic control systems. Today, there is a second fluidic revival, this time in the domain of soft robotics. Scaling microfluidic designs up to the millimeter-scale range (millifluidics) enables the higher flow rates necessary to drive robotic actuators. These robots exploit the nonlinear behaviors of soft materials to create lifelike motion and safer interactions, often utilizing pressurized air. By building systems that “think” with the same air that powers them, we can drastically reduce the need for bulky electronic-to-pneumatic interfaces. This is the focus of my Soiboi Studio robotics lab. With millifluidic logic, I have steadily scaled the complexity of my designs. What began with a simple oscillator has most recently evolved into a clock featuring a soft, four-digit, seven-segment display. What Is Millifluidics? Building on microfluidics research from the early 2000s and recent developments from the Grover Lab at the University of California, Riverside, I’ve developed millifluidic devices using standard 3D printing and silicone casting. The basic architecture is simple: A flexible membrane is sandwiched between rigid layers embedded with networks of air channels. Just as electronics rely on differing voltage potentials, these fluidic circuits operate on the pressure difference between atmospheric pressure (logical 0) and a near-vacuum at around −60 kilopascals of relative pressure (logical 1). Using negative pressure means the membrane is pulled into openings. This creates robust seals that allow me to replicate electronic building blocks. A cast silicone membrane forms the face of the clock [top], while behind it sits 3D-printed millifluidic blocks [middle rows]. An Arduino Uno controls driver boards that operate solenoids, which are connected to valves that are attached to a vacuum pump [bottom row].James Provost While fluidic resistors are easily realized by adjusting the channel geometry, the heart of the system is a valve that mimics a metal-oxide-semiconductor field-effect transistor, or MOSFET. This vacuum “transistor” features a flow layer with two chambers (the source and drain) divided by a central valve seat and a control layer containing a cavity (the gate). A membrane runs between the control and flow layers and normally prevents airflow between the source and drain chambers. To switch the transistor on, a vacuum is applied to the gate chamber, sucking the membrane into the cavity and lifting it off the seat. This opens a path for airflow, equivalent to closing an electric circuit. By adding a small aperture to the membrane, I created a check valve—the fluidic equivalent of a diode. By combining transistors and resistive “pull-down” channels, I can build a full suite of logic gates. The original microfluidic designs that inspired me were fabricated from etched glass and milled acrylic. Adapting them for a standard 3D printer required reengineering the logic elements and mastering two critical fabrication techniques. First, I need airtight prints, yet printed plastic is notoriously porous. By printing at elevated temperatures, slow speeds, and slight overextrusion, I was able to fill microscopic gaps. When you’re using transparent filament, there’s a handy visual indicator: The more transparent the plastic appears, the lower its porosity. Second, I used glass for my print bed. By printing the upper and lower chambers directly against this bed, I got the interface surface to become mirror smooth. This finish is essential for creating reliable, airtight seals. A 0.3-millimeter silicone membrane is placed between the layers and secured with screws. How Does the Soft Clock Work? The clockface is a cast silicone membrane. Each digit segment is formed by a small underlying cavity. When air is evacuated from this cavity, the membrane is sucked inward to create a concave hollow; when atmospheric pressure is restored, the silicone pops back flush with the surface. The result is a mesmerizing, organic motion. The “brain” of the clock is an Arduino Uno, while the fluidics significantly reduce the hardware footprint. A four-digit, seven-segment display with two separator dots would require 29 solenoid valves to control directly. My clock needs just 11 valves. A pneumatic transistor is off when its upper control chamber is at atmospheric pressure [top]. When air is removed from the control chamber, it lifts a membrane, which allows air to flow between lower flow chambers and turns the transistor on [bottom]. James Provost To understand how it works, consider a standard electronic four-digit, seven-segment LED display. This also uses 11 pins to drive its digits. (In clockface displays, an additional pin is required to drive the separator dots.) Every digit is connected to a shared data bus with seven lines, one per segment. The four control lines select individual digits. Only one digit is illuminated at time, and strobing the digits at least 50 times per second creates the illusion that all four are simultaneously illuminated. Such high-speed switching is not possible with air. Instead, I rely on memory. Each segment acts like a capacitor: By evacuating its cavity (logic 1), you “charge” the segment; by restoring atmospheric pressure (logic 0), you discharge it. Hence, each digit acts as an independent 7-bit memory. If the system is sufficiently airtight, the segments maintain their state for several seconds. Like the electronic display, the system utilizes a seven-line data bus. Each line connects to a solenoid valve that provides either vacuum or atmospheric pressure. To selectively address the individual digits, I placed a fluidic transistor between each segment and its data line. All the transistors’ control inputs for a given digit are combined into one “write enable” line connected to its own solenoid valve. Activating this valve allows me to write data into the corresponding digit’s memory. The clock updates one digit per second, meaning a full cycle across the face takes 4 seconds. This cycle also drives the separator dots: A set of fluidic diodes connects the enable lines to the dots’ cavities. Consequently, as each digit is addressed, the dots pulse automatically. This display is more than a clock; it is a soft robot that happens to tell time. By offloading computation to the same air that powers movement, the clock approaches a new class of machines that are simpler, lighter, and more integrated. I’m now developing a guide for getting started with vacuum-powered logic and may release a refined version of this clock in the future. Watching the silicone skin morph serves as a fascinating reminder that not all logic needs silicon; sometimes, all you need is flexible silicone and a flow of air. This article appears in the June 2026 print issue as “The Soft Clock.”
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Over the next few decades, billions of autonomous, AI-powered robots will work alongside people in factories, perform tedious tasks in warehouses, care for the elderly, assist in unsafe disaster areas, deliver packages and food to our doorsteps, and eventually help out in our homes. Some will look like us, and many won’t. What is certain is that regardless of form factor, robots will all rely heavily on AI in order to deliver real-world value. In 2025, total investments in robotics companies reached a record US $40.7 billion, accounting for 9 percent of all venture funding. The multibillion dollar question therefore is this: What will it take for AI-powered robots to begin to have a serious economic impact? Many of today’s robotics and AI companies are making bold claims, such as that humanoid robots will soon be coming into our homes, but there’s still a big gap between promise and reality. The promise of robots that live and work alongside us has been the stuff of science fiction for a very long time. And while many programmers have tried to make that promise a reality, the physical world is just too complicated for traditional computer programs to handle the endless complexity it presents. Thanks to AI, robots are no longer being programmed—instead, they learn to operate in the real world. With enough practice, they can learn to perceive and understand the world around them, reason about that world, and use that reason and understanding to perform tasks that are useful, reliable, and safe. The two of us have worked at the forefront of AI and robotics for the last decade, as a Professor in Robotics at Oregon State University and Co-Founder of Agility Robotics, and as former CEO of the Everyday Robots moonshot at Google X. Our experience deploying AI-powered robots in real-world settings has given us a perspective on where AI can be used to great benefit in complex robotic systems in the near term and where we are still on the frontier of science fiction. We believe AI will enable an inflection point in robotics advances, but that it will be through the well-engineered application of coordinated systems of different AI tools rather than a single ChatGPT-style breakthrough. As the excitement around AI is matched only by the uncertainty of what will be possible, here are five hard truths that will define AI in robotics. 1. The YouTube-to-Reality Gap Is Real For years, we have been seeing videos on YouTube with humanoid robots performing amazing moves on everything from a dance floor to an obstacle course. The inside knowledge in robotics is to “never trust a YouTube robot video.” The gap between real robots that can perform real work in unstructured human environments and carefully scripted and edited robot performances remains significant. The latest performance to get a lot of attention was a martial arts show featuring Unitree humanoid robots performing with children at the Chinese 2026 Spring Festival Gala. While impressive, this falls into a long lineage of tightly scripted robotic performances, where everything has been carefully choreographed and planned in advance. The low-level controls, synchronization, and choreography were stunning, yet the Spring Gala robot performance showed a level of autonomy and intelligence much closer to industrial robots building cars in a factory than something that will show up in your living room any time soon. Seeing these kinds of demos nevertheless raises questions about where robotics really is. If robots can perform kung fu moves and do backflips and dance, why aren’t they also showing up on factory floors yet? And why can’t they do the dishes in my home after dinner? The simple answer is this: Making AI-powered robots capable of performing general tasks in varied human environments is still really hard. While impressive technological feats like those at the Spring Festival may make it look like we could be very close, the use of AI in these demos is only for low-level motor control (to keep the robots from falling over) and therefore is only a small part of the solution for robots to be general purpose in the real, unstructured spaces where we humans live and work. 2. Data Is An Unsolved Challenge Large Language Models (LLMs) like OpenAI’s ChatGPT and Anthropic’s Claude were initially trained on an internet-scale database of text. The world woke up one day in late 2022 to ChatGPT demonstrating that AI computers could suddenly “speak” to us in prose or verse and about seemingly any topic. LLMs have turned out to generalize well and are now able to take multimodal input (text, images, video) and produce multimodal output. Importantly, the corpus of training data was both enormous and human-generated, which are characteristics that form the gold standard for AI training. The fastest path to robots as part of everyday life may emerge through a range of robot forms performing increasingly sophisticated applications and employing a range of AI tools.Agility Robotics Giving AI a body (in the form of a robot), so that it can engage with people in the physical world, continues to be a very difficult and broadly unsolved problem. AI models for general-purpose robotics must simultaneously satisfy multiple, often conflicting, physical, geometric, and temporal limitations while operating in unstructured, dynamic environments. In order to generalize, robot models need to be trained on data gathered in a high-dimensional configuration space, where “dimensions” represent text, lighting conditions, degrees of freedom, joint limits, velocities, force, and safety boundaries, just to mention a few. Importantly, this must be good data—it must contain many examples from what amounts to an infinite number of possible configurations in the physical world. Since there are very few existing sources of data like this, approaches like teleoperation, video analysis, motion capture of humans, and self-exploration in simulation and in the real world are all seen as important ways to collect data. It’s a herculean task. For example, at Everyday Robots at Google X, we ran 240 million robot instances in our simulator over the course of 2022 to collect training data, mostly to train a trash-sorting model. Similar amounts of data will be needed for every skill to get to a similar level of capability, which is not yet human level. 3. There Will Be No Single Robot AI We are far away from a moment where a single AI model might allow general-purpose robots to live and work alongside us. General-purpose robots can have wheels or legs. They can have one, two, three, or more arms. Some have propellers and can fly, while others may be designed to operate under water. Some will drive on busy roads. The physical world is infinitely varied and complex. And then there are all the people and other animals that will be surrounding the robots. How do you train a model to operate a robot safely and reliably in all of these settings? The simple answer is: You don’t. At least not for quite some time. We believe the winning AI architecture leading to the next big breakthroughs in general-purpose robotics will be “agentic AI” for robots, which are high-level coordinating models that can reason, plan, use tools, and learn from outcomes to execute complex tasks with limited supervision. Agentic, high-level models running on robots will invoke a system of specialized ones for different types of tasks. We will likely soon see multiple robots collaborating and coordinating with each other through their onboard agentic AI models. AI tools are unlocking new and powerful capabilities in robotics, which in turn will enable new solutions and new markets. It’s encouraging to see these new models being made broadly available, some even as open-source solutions. This availability is akin to what happened with the internet: Real progress occurred when it became ubiquitous. We anticipate an inevitable democratization of complex behaviors in robotics with wide access to these AI tools and technologies. 4. Hardware Is Still Very Hard Robots are complex systems with many parts that all need to work together with great precision. For a robot to be useful and safe, every part of it must be coordinated, from its perception systems to the computer controlling it, all the way down to its individual actuators. Actuators—that is, the motors and gears—are a good example of an important part of the robot where what got us here won’t get us there. The actuators used at scale by most industrial robots will not work for robots that will operate in human environments. If these robots accidentally collide with an obstacle, the resulting impacts are harsh, forces are high, and things break. Humans don’t move in this way. We are far more compliant in how we interact with the world, and we’re constantly making contact with our environment and using that contact to help us accomplish things. Consider the challenge of inserting a key in a lock: Humans typically don’t do this by aligning the key perfectly with the keyhole. Instead, we just feel for the edge of the keyhole and jiggle the key in. Robots need to be able to operate in novel ways to achieve comparable capabilities by using a new class of actuators that are sensitive to force and able to have a compliant interaction with the environment. While these kinds of actuators do exist, they are not yet generally available at scale for robot systems designed to operate around people. 5. Real Value Comes From “Easy” Tasks There’s a big difference between tasks that look impressive and real-world tasks that provide value. Robotics is a perfect example of Moravec’s paradox, which states that tasks that are hard for humans are easy for computers (like multiplying two big numbers), and tasks easy for humans (like a toddler’s movements) are extremely difficult for computers and robots. Serving customers is an unforgiving reality check, because customers only care about solving the real problems they have. If we are to deploy AI-based robot solutions, they must outperform the way things are currently done while demonstrating reliable performance metrics and safety. Agility Robotics’ early work to deploy our humanoid robot Digit in customer locations led to the realization that our first obstacle was safety: Robots that balance and manipulate objects in human spaces bring new types of risk to the workplace. In the first humanoid deployments, physical barriers were necessary, and Agility kicked off a multi-year engineering effort to solve the safety challenge, touching nearly every aspect of robot design and relying heavily on new AI-based approaches to human detection and behavior control. Everyday Robots at Google deployed robots in 2019 that worked autonomously in office buildings doing chores like cleaning cafe tables and sorting trash. We quickly learned how “messy” and difficult the real world is for a robot. This experience informed the architecture and deployment of our AI systems while also gathering real-world data that could be combined with simulation data for training and improving models. This focus on creating a product to meet specific customer needs and deploying robots in real-world settings is the only way to inform the structure of the AI tools and infrastructure for near-term utility on a path towards long-term broader capability and generality. There will be no “aha” moment, no silver bullet algorithm, and no volume of data sufficient to produce a general-purpose robot without extensive real-world experience. AI Robots Are Coming, One Step at a Time As we look to the future, there is no doubt that the world is bringing AI into the physical world through robots. We are at the beginning of a “Cambrian explosion“ of useful, intelligent machines. We believe AI is not one tool, but a huge frontier of technical approaches that is unlocking new capabilities so powerful, they will define our economy moving forward. This will happen not in one single definitive moment, but as an ongoing set of small and large breakthroughs, where AI-driven robots begin to provide real value in a few tasks, and then a few more, with impacts unfolding across numerous $100 billion-plus markets that will dramatically improve the quality of our lives.
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More than 30 years ago, in the mountain village of Mbem in northwest Cameroon, the moon and stars in the night sky were the only light young Jude Numfor knew after the sunset. Electricity had not yet reached his rural community. “There was one person in the village with a petrol generator and a small television,” Numfor says. “When he turned it on, all the children would run to his house and peep through the window.” That memory became the spark for Numfor’s mission: to bring electricity to rural communities like his hometown. To accomplish his goal, in 2006 he cofounded Wireless Light and Power, since renamed Renewable Energy Innovators Cameroon, and he serves as its CEO. REI Cameroon designs, installs, and maintains solar minigrids for rural electrification. The minigrids use photovoltaic technology and battery-energy storage systems to generate electricity at 50 hertz. The electricity is distributed through smart meters. In 2017 the company received a grant from IEEE Smart Village to fund the expansion of REI’s minigrid operations and refine its business model. Smart Village supports projects and organizations bringing electricity and educational and employment opportunities to remote communities worldwide. The program is supported by IEEE societies and donations to the IEEE Foundation. The partnership has led to a collaboration developing open source metering, a free, community-driven way of tracking energy usage. Unlike proprietary utility meters, the system allows users, researchers, and utilities to view, customize, and verify how data is collected, ensuring transparency in billing, consumption tracking, and grid management. Smart Village’s support has been pivotal, Numfor says: “It’s not just about money. We share ideas, we get advice, and we have made friends. Entrepreneurship is lonely, but with the [Smart Village] community, it is different.” From teenage tinkerer to entrepreneur Numfor’s first experience of life with electricity was in 2001, after moving in with a missionary family in the small village of Allat. They used solar panels to power their whole home—an unimaginable luxury in Mbem. “I could watch TV, eat ice cream, and turn on lights,” he says. “It made me wish my brothers in Mbem had the same opportunity.” Numfor’s curiosity about electricity was ignited when a motion-sensor solar light in the family’s home stopped working. He tinkered with the device to find out why. “My missionary family told me to play with it like a toy,” he says, laughingly. “I replaced the dead battery with a motorcycle battery and was able to bring the power back for the night.” Jude Numfor [right] testing a rechargeable solar lantern, which aimed to replace hazardous kerosene lamps—known locally as “bush lamps.”REI Cameroon His missionary parents encouraged Numfor to study technology and engineering on his own, as none of the country’s universities offered solar energy educational programs at the time. They built him a library and stocked it with books on engineering, management, and entrepreneurship. In 2006, armed with his new knowledge, Numfor launched Wireless Light and Power with a friend, Ludwig Teichgraber. The nonprofit aimed to replace hazardous kerosene lamps—known locally as “bush lamps”—with rechargeable solar lanterns. These solar lanterns—called “light packs”—were built locally by Numfor and a team of 11 young Cameroonians using PVC pipes, nickel-metal hydride batteries, and LED bulbs. Families rented the lamps for a small fee, swapping discharged lamps for fully charged ones at solar-powered charging kiosks when they ran out of power. The kiosks then recharged the depleted lamps, making them available for the next swap. “The solar lantern was safer and cleaner, plus it gave children a chance to read at night,” Numfor explains. “People loved them.” Between 2006 and 2010, his team replicated the model across several villages. But when the global financial crisis hit in 2008, donor support dwindled, forcing the organization to evolve. “We pivoted from being an NGO to a commercial venture,” he says. “That’s how REI was born.” Building solar minigrids to serve community needs The new company’s goal was to move away from the lanterns and toward full electrification of communities. Villagers’ aspirations changed, Numfor says, as they now wanted to power their TVs, music systems, and mobile phones. In response, in 2010, REI developed one of the first solar minigrids in West Africa. Using locally procured components, the prototype supplied steady power to six households. The minigrid system used 12 123-watt solar photovoltaic panels manufactured by Sharp, 16 12-volt 100 ampere-hour automatic gain control lead acid batteries, and a Xantrex charge controller and inverter. Locally sourced wooden light poles were erected to distribute electricity throughout the village. REI charged each household a fee for the electricity. “It was a product-market-fit moment,” Numfor says. “People immediately asked, ‘When can we get this, too?’” The word-of-mouth, grassroots growth caught the attention of global partners. Numfor connected with Smart Village and in 2017, REI Cameroon received its first seed grant from the program. With that funding, Numfor was able to grow organically and attract additional grants, including one from the U.S. Trade Development Agency (USTDA), in partnership with the U.S. Department of Energy’s National Renewable Energy Laboratory. REI has since expanded to six villages, providing power to more than 1,000 households and businesses. With a dedicated team of 16 people, the company operates in multiple regions of the country, each with unique terrain, languages, and cultural dynamics. “It wasn’t easy,” he acknowledges. “I’m not an academic person—I had to learn everything by doing. [Smart Village] helped me structure the project and grow as an entrepreneur.” Today, Numfor pays it forward by sharing his Smart Village experience and mentoring new entrepreneurs. Launching a coalition for smart metering Minigrids can’t operate efficiently without clarifying operating rules to ensure quality service requirements and consumer protection, while also enabling reliable and effective monitoring of the system, Numfor says. “We need to know how power is being used, detect problems early, and manage the minigrid from a distance,” he explains. Existing commercial smart-meter providers offer limited and proprietary solutions. One major provider left the market, making their technology infrastructure obsolete. “It’s risky for an entire sector to depend on a few companies for such a critical technology,” Numfor says. In 2025, with the help of the Smart Village technical community, Numfor convened a consortium of open-source power advocates, including the Africa Mini-Grid Developers Association, EnAccess, Energy IOT, and NESL. The goal was to develop an open smart metering system that is accessible, transparent, and sustainable for all energy providers. “These organizations are collaborating as Open Advanced Metering Infrastructure [OpenAMI], which is about giving control back to the people who deliver the energy,” he says. Scaling for impact Numfor’s passion has grown from bringing light to local rural communities to bringing light to his entire country. Just 54 percent of Cameroon’s citizens have access to electricity, according to the International Energy Agency. For Numfor, the challenge is not just technological—it’s social and economic as well. “Electricity is the most important enabler of education and economic growth today,” he says. “When you have power, you unlock everything else.” “Electricity changed my life. Now I want to make sure every child can grow up with that same light.” —Jude Numfor Across the villages where REI has installed sustainable electricity solutions, small businesses are flourishing. Barbershops hum with community chatter, food vendors can preserve perishables, and entrepreneurs run companies such as phone-charging stations and small mills. “Some villages even have laundromats now,” Numfor says proudly. “Electricity creates jobs and changes mindsets.” Still, it has been a bumpy journey. It wasn’t until 2025 that REI obtained its official authorization (license) from Cameroon’s government to produce and distribute electricity in off-grid areas using solar minigrids. This was a major milestone because REI is one of the first private enterprises in the country to receive such authorization. “We were stuck between pilot projects and growth,” he explains. “Our projects were successful, and there was community demand for more, but to grow, we needed investors who require legal guarantees before committing funds. Now we can scale up and attract investors.” REI plans to expand its reach dramatically, beginning with 134 new villages identified through a feasibility study supported by the USTDA. Their long-term goal is to electrify 760 villages across Cameroon by 2031. While authorization opens doors, financing remains one of REI’s biggest challenges. “The minigrid space doesn’t attract venture capitalists easily,” Numfor notes. “Our return on investment is under 15 percent, so it’s not a typical tech startup model. The real return here is the impact” on the community. He hopes to attract investors who understand that access to electricity drives education, health care, and entrepreneurship. “There are people out there who want to make meaningful change,” he says. “We just need to connect with them. When you electrify a village, you never know who the next innovator will be. Maybe it’s another kid like me, looking through a window, dreaming.” Finding skilled staff is another challenge, Numfor says. To address this, REI developed an intensive recruitment and training process. “It used to take years to find the right people,” he says. “Now, we can identify who fits our company culture within six months.” Numfor’s wife, Angela Taliklong, who joined the venture in 2010, now oversees administration and human resources. A brighter Cameroon and beyond Numfor offers simple words of advice to other impact-driven entrepreneurs: Keep moving. “One of my mistakes early on was trying to be perfect,” he says. “I was spending time improving prototypes instead of increasing the number of our project installations and scaling how many communities we could electrify. You must keep momentum. Don’t wait until everything is perfect before you move forward.” That mindset, rooted in resilience and experimentation, has defined his journey. Rajan Kapur, president of Smart Village, says Numfor is a “shining example” of the program’s vision: “scalable and enduring impact through local entrepreneurs, local procurement, and community engagement based on the use of IEEE technology in underserved communities.” With the ongoing Smart Village partnership, Numfor is determined to bring light and opportunity to every corner of Cameroon, and beyond. He already has launched REI Nigeria. “Electricity changed my life,” he says. “Now I want to make sure every child can grow up with that same light.”