Today on The Robot Beat, we're tracking a harsh reality check in the humanoid market. We've been following China's massive factory scale-up and recent wave of robotics IPOs, but a new survey reveals actual buyer satisfaction is sitting at just 23%. We're also tracking a major milestone from Google I/O, where the on-device AI teases we've been watching finally paid off with cloud-free, edge-running robots.
Two Taiwanese firms have unveiled new 'intelligent' humanoid robots, integrating advanced AI and NVIDIA hardware. TM Technology revealed a humanoid featuring an AI-powered 'brain' for reasoning and planning, utilizing 3D vision and LiDAR for real-time interaction. Separately, at Nvidia GTC 2026, Techman Robot showcased its TM Xplore I, which combines a humanoid upper body with a wheeled base. This robot is powered by NVIDIA's Jetson Thor compute platform and leverages NVIDIA's Vision-Language-Action (VLA) technology for industrial applications.
Why it matters
These launches demonstrate the rapid convergence of sophisticated AI models with capable hardware, marking a shift from pre-programmed industrial arms to more adaptive and intelligent systems. For the robotics ecosystem, this highlights the critical role of powerful, off-the-shelf AI hardware like NVIDIA's Jetson Thor in enabling smaller firms to compete and innovate in the advanced robotics space. The combination of a humanoid torso with a wheeled base also represents a pragmatic compromise, optimizing for mobility and cost in industrial settings while still providing human-like manipulation capabilities.
Interesting Engineering notes that these developments signal a move beyond traditional industrial automation. The focus on real-world operation in manufacturing, and potentially healthcare, suggests a growing market for versatile robotic solutions. The reliance on NVIDIA's ecosystem (Jetson Thor, VLA models) reinforces the chipmaker's central position in providing the 'brains' and nervous system for the next wave of robots, turning hardware manufacturers into key partners and customers.
Korean robotics firm ROBOTIS has demonstrated its AI Sapiens humanoid robot learning a complex K-Pop dance routine by watching a smartphone video. The process leverages an open-source AI framework that combines video-based motion capture, motion retargeting for the robot's specific body, reinforcement learning in simulation, and sim-to-real transfer. This method aims to dramatically simplify the process of teaching humanoid robots new physical skills.
Why it matters
This is a significant step towards democratizing humanoid robot programming. By replacing expensive, specialized motion-capture studios with a simple smartphone video, ROBOTIS is drastically lowering the barrier to entry for training robots. For entrepreneurs and developers, this open-source approach could catalyze a wave of innovation, enabling a broader community to experiment with and deploy humanoids for a wide variety of tasks without needing a massive R&D budget. It shifts the focus from 'how to program the robot' to 'what to teach the robot'.
The demonstration highlights the power of combining several existing AI techniques into a practical workflow. While sim-to-real transfer and learning-from-video are not new concepts, packaging them into an accessible, open-source framework is a key development. This approach could accelerate progress in physical AI by enabling rapid, low-cost iteration on a global scale, much as open-source software has done for other fields of computing.
Delivering on the pre-I/O teases we tracked surrounding Gemini Robotics ER-1.6, Google showcased two palm-sized Open Duck Mini v2 robots performing complex tasks using its Gemma 4 E2B AI model running entirely on-device. Built on a Raspberry Pi 5 and NVIDIA Jetson Orin Nano, the robots engaged in real-time speech and vision without a cloud connection.
Why it matters
By proving a sophisticated multimodal AI model can run on inexpensive edge hardware, Google has effectively delivered on its promise to solve the cloud dependency bottleneck for autonomous decision-making. For entrepreneurs and hobbyists, this opens the door to creating truly autonomous, intelligent robots without needing the backing of a large corporation.
ExplainX.ai, which reported on the demo, emphasized the accessibility of advanced AI on low-cost hardware as the key takeaway. The project successfully combines open-source hardware and AI, demonstrating a path for the robotics community to build more capable systems independently. This stands in contrast to the proprietary, vertically integrated ecosystems being built by larger corporations.
Tencent Robotics X, in partnership with Futian Lab and the Hunyuan team, has released HyVLA-0.5, an open-source Vision-Language-Action (VLA) model for robot manipulation. The model achieves over 90% success on real-world tasks by leveraging a massive dataset of over 10,000 hours of high-precision demonstration data and a novel reinforcement learning pipeline called FlowPRO. The framework is designed for cross-embodiment transfer, allowing it to be deployed on different types of robot arms.
Why it matters
The release of another high-performing, open-source VLA model from a major tech player like Tencent further accelerates the commoditization of robotic intelligence. By providing both the model and the high-fidelity training data, they are lowering the barrier for other developers and manufacturers to build capable robots. This move pushes the competitive landscape away from proprietary models and towards who can best integrate these 'brains' with hardware and solve real-world application problems. The emphasis on cross-embodiment transfer is particularly key, as it promises a future where a single AI can power a diverse fleet of robots.
Besthub.dev highlights the model's ability to reduce reliance on costly and time-consuming tele-operation for data collection. A separate technical paper indicates the system uses a 4B parameter model and a unique memory encoder to enable practical, real-robot deployment. This suggests a focus on creating a system that is not just powerful in simulation but genuinely workable in the physical world.
According to a new analysis, the compute power available for robotics applications has increased by a factor of 1,000 over the past eight years. This exponential growth, fueled by advancements in AI chips, sophisticated simulation environments, and the falling cost of computing, is a primary driver behind the current shift of autonomous robots from experimental prototypes to essential industrial infrastructure.
Why it matters
This 1,000x improvement in eight years quantifies the tectonic shift underpinning the entire robotics industry. It's the Moore's Law equivalent for physical AI, and it explains why tasks that were impossible a decade ago are now becoming commercially viable. For an entrepreneur, this trend is the fundamental tailwind. It means that more complex AI models, more sophisticated sensor fusion, and more autonomous decision-making can be packed into smaller, more energy-efficient, and cheaper robots, dramatically expanding the addressable market for automation.
Hypernova News, which compiled the analysis, cites data from the World Economic Forum and the International Federation of Robotics. The report suggests this compute explosion is democratizing robotics, making advanced capabilities accessible beyond just large, well-funded research labs. It positions the current moment as a key inflection point where technology maturity and economic viability are finally aligning for mass deployment.
A new project by developer Naveen Kumar demonstrates building a soccer-playing humanoid robot that runs all its AI processing on the edge, without cloud dependency. The system combines a HiWonder AiNex bipedal robot with a Particle Tachyon board, which features a Qualcomm Dragonwing QCM6490 SoC. Using the Edge Impulse platform, a YOLO-Pro model was trained to detect a soccer ball, enabling the robot to identify and interact with it in real-time.
Why it matters
This project is a powerful example of the democratization of advanced robotics. It shows how an individual developer, using commercially available hardware and user-friendly machine learning platforms, can build an embodied AI system that would have required a research lab and a team of specialists just a few years ago. It highlights the maturity of the tools and hardware in the edge AI ecosystem and provides a practical blueprint for hobbyists and entrepreneurs looking to build their own intelligent, autonomous robots.
The project write-up on Edge Impulse serves as a tutorial, breaking down the steps from hardware selection to model training and deployment. This open-source ethos and sharing of knowledge is critical for growing the robotics community and fostering innovation from the ground up. It's a tangible demonstration of how powerful SoCs from companies like Qualcomm are enabling a new wave of accessible, high-performance robotics projects.
Building on the Morgan Stanley projections we tracked earlier this month, a new Q2 2026 analysis confirms the humanoid market is bifurcating. Chinese manufacturers like Unitree have achieved mass production (shipping ~5,500 units in 2025), while Western automotive giants remain stuck in pilot phases. A notable exception: Tesla is reportedly preparing to start production of its Optimus Gen 3 in late July or August 2026, which could accelerate Western manufacturing efforts.
Why it matters
The distinction between China's volume-driven strategy and the West's application-specific pilot programs is critical, reinforcing the 'demand lags production capacity' dynamic we noted last week. Tesla's impending Optimus production start will serve as the primary catalyst testing whether Western deployments can rapidly scale to match Chinese volumes.
The report from Cornford & Cross contrasts the narrative of a single global race with a more nuanced picture of two distinct, parallel tracks for humanoid development and deployment. This is echoed by other analyses pointing to a potential glut in Chinese production capacity relative to current, demonstrable demand for functionally competent robots. The key question is whether China's scale will drive down costs and force a rapid learning curve, or if the West's focus on perfecting specific, high-value tasks will yield more economically viable robots in the near term.
While Chinese humanoid firms like Unitree and EngineAI ride the wave of IPOs we've been tracking, a new buyer survey reveals a stark reality check: only 23% of customers are satisfied with their purchased robots. The report highlights a massive gap between the physical hardware being produced at scale and the embodied AI's functional competence, noting a continued heavy reliance on foreign components like NVIDIA's Jetson modules and GR00T foundation model.
Why it matters
This reinforces the demand-side lag we saw in Morgan Stanley's recent projections. Simply scaling production—as dictated by China's MIIT mandates—isn't solving the core challenge of reliable embodied AI. The low satisfaction rate indicates current products are failing to meet customer expectations, leaving the door open for a company that can crack the code on intelligence and usability.
Markman Capital Insight's analysis frames the situation as a 'manufacturing boom vs. buyer satisfaction' dilemma. It questions the sustainability of high valuations if the robots themselves can't perform as advertised. This aligns with broader market commentary suggesting that while China is winning the race to produce the physical 'body' of the robot, the global race to build the 'brain' is still wide open.
Following the news that Hyundai has pre-sold Boston Dynamics' entire 2026 Atlas production run and committed to a massive 25,000-unit deployment, Yuanta Securities Korea has raised its target price for Hyundai Mobis, identifying the automotive parts manufacturer as a key supplier of core components for Atlas. The analyst report positions Mobis as a 'first-tier hardware platform supplier' that could eventually supply competing robotics firms.
Why it matters
This financial analysis is significant because it marks the moment the broader investment community begins to map and value the humanoid robot supply chain. It's no longer just about the flashy demos of the final robot; it's about the bill of materials. The recognition of Hyundai Mobis highlights how the established automotive supply chain is pivoting to provide the motors, actuators, and other critical hardware for robotics. For an entrepreneur, this signals a maturing market where reliable, scaled-up component suppliers are becoming crucial and represent a distinct investment and partnership opportunity.
Biz Chosun, reporting on the analyst note, emphasizes that Hyundai Mobis's role could extend beyond simply supplying its affiliate, Boston Dynamics. This suggests a potential future where Mobis becomes a quasi-merchant supplier of high-performance robotics components, leveraging its manufacturing scale from the automotive industry to drive down costs and establish a dominant position in the robotics hardware market.
Hot on the heels of India's National AI Mission targeting a $10,000 humanoid, Chennai-based startup Agni Robotics has unveiled its Agni-2 prototype for ~$18,000 (₹15 lakh). Targeting repetitive tasks in India's MSME manufacturing sector, the company says it has already secured pre-orders from major automotive component manufacturers, joining regional peers like Agnimanu Robotics in the push for affordable domestic automation.
Why it matters
Following the recent announcement of India's national mission to build a sub-$10,000 humanoid, the Agni-2 is a concrete step toward that goal. Its affordable price point could be a game-changer for democratizing automation in India's vast manufacturing landscape, which has traditionally been priced out of high-end robotics. This development, along with others like the Astra-1, signals the emergence of a vibrant domestic robotics industry in India focused on creating cost-effective solutions for local and global markets.
RobotWale News, which broke the story, notes that the focus on MSMEs is a key differentiator. By targeting this underserved segment, Agni Robotics is not competing directly with high-end models from Boston Dynamics or Tesla but is instead carving out a new market. The early pre-orders from the automotive sector suggest a clear demand for such a solution.
At a recent elder-care expo in Shanghai, Chinese tech company Yueban launched 'Xiaoban,' a self-driving robotic toilet aimed at assisting the elderly and individuals with mobility challenges. The device can be summoned by voice or remote control, navigate to a user's bedside, and assist with toileting. It also features self-cleaning and automatic docking for charging. The Xiaoban is priced at around $4,000.
Why it matters
This product is a highly practical application of assistive robotics that addresses a critical and often overlooked need in elder care: safe and dignified toileting. By automating this process, Xiaoban can significantly enhance independence for users and reduce the physical strain on caregivers. It's a prime example of how robotics is moving into specialized, high-impact niches within the home, tackling difficult problems beyond just cleaning or entertainment.
NewsBytes reports on the launch, positioning it as an innovative solution for China's rapidly aging population. The $4,000 price point, while not insignificant, may be seen as a worthwhile investment compared to the costs of full-time care or home modifications. The product signifies a growing trend in consumer robotics to develop devices that solve specific, challenging problems in daily life.
TetherIA, the company behind the USDT stablecoin, has launched the Aero Hand Open, a fully 3D-printed, open-source robotic hand priced at just $314. The hand features 7 degrees of freedom and 16 joints, is driven by tendons, and comes with full ROS2 support. The project's hardware and software are available on GitHub, with the stated goal of democratizing research in dexterous manipulation and embodied AI.
Why it matters
This is a significant contribution to the open-source robotics community. The high cost of dexterous robotic hands has long been a major barrier for independent researchers, startups, and universities. By releasing a capable, sub-$400 design with full open-source support, TetherIA is dramatically lowering the barrier to entry for physical research in embodied AI. This could spur a wave of innovation in manipulation by enabling many more people to conduct real-world experiments.
Crypto Briefing and ValueTheMarkets both highlight the hand's low cost and open-source nature as its key features. The modular design, allowing for easy 3D printing and repairs, is also seen as a major advantage for a research setting. The move by Tether, a crypto company, into open-source robotics hardware is unusual but reflects a growing interest from diverse corners of the tech world in the foundational problems of physical AI.
Chinese tech giant Alibaba has launched its first suite of AI models designed specifically for robots, including 'RynnBrain' for perception and a new version of its large language model, 'Qwen3.7-Max', for agentic tasks. This move signals a strategic pivot within the tech industry, moving beyond simple chatbots to creating sophisticated AI 'agents' capable of understanding commands and executing complex physical actions.
Why it matters
When a company of Alibaba's scale enters the robot AI market, it acts as a massive accelerant. This move underscores the industry's shift towards embodied AI as the next major frontier. For entrepreneurs in the robotics space, this means the tools and platforms for building intelligent robots are becoming more powerful and accessible. It also signals intensifying competition, as the race is no longer just about building the robot but about creating the most capable 'agent' software to run on it.
Reuters reports this as a broader industry trend away from chatbots. The Next Web frames it as a strategic emphasis on vertical integration and physical AI, which could speed up the deployment of intelligent robots in logistics and home environments. This development places Alibaba in more direct competition with other companies developing robot foundation models.
A new paradigm is gaining traction in robot foundation models: the World-Action Model (WAM). This approach uses a pre-trained world model, often built from vast amounts of video data, to understand and predict physical dynamics. This 'imagined' future is then used to inform the robot's actions. WAMs are emerging as a compelling alternative to Vision-Language Models (VLMs) that attempt to directly map language commands to robot actions, a process that often struggles with physical grounding and nuance.
Why it matters
This represents a significant architectural shift in the quest for generalist robot AI. Instead of teaching a robot what to do linguistically, WAMs aim to give the robot an intuitive 'physics engine' in its brain. For developers, this could mean more robust and generalizable robots that can better handle novelty and uncertainty because they have a foundational understanding of how the world works. Successfully implementing WAMs could be the key to overcoming the brittleness that plagues many current robotic systems.
NVIDIA's developer blog highlights this trend, suggesting that pre-training on video gives WAMs a significant head start in understanding scene dynamics. The approach aims to solve the 'language-to-action grounding wall' where language models struggle to translate abstract concepts into precise physical movements. The success of this approach could depend heavily on the quality and diversity of the video data used for pre-training and the efficiency of the world model itself.
Prometheus, an AI company co-founded by Jeff Bezos, has raised a massive $12 billion funding round at an approximate $41 billion valuation. The company is focused on building what it calls 'physical AI' or an 'artificial general engineer'—an AI system designed to understand the physical laws governing engineering and manufacturing systems, moving beyond simple pattern matching of historical data. The funding round saw participation from major investors including JPMorgan Chase.
Why it matters
This colossal funding round is a major signal that sophisticated investors believe the next frontier for AI is in the physical world, not just the digital one. The explicit framing of 'physical AI' and an 'artificial general engineer' suggests a new category of technology is being defined, focused on solving complex, real-world problems in industrial design and manufacturing. For the robotics and automation sector, this is a massive validation, likely to trigger a cascade of investment and talent into startups tackling hard engineering challenges with AI.
DevCuration frames this as a clear shift in investor interest away from purely digital or consumer AI. StartupHub.ai notes that Prometheus is one of several high-profile companies, including PhysicsX and Mistral AI, now using the term 'physics AI,' suggesting the emergence of a new industry category. Hacklogic positions the deal alongside NEURA Robotics' recent $1.4B raise as part of a broader trend of 'mega-rounds' for physical AI.
An analysis of robotics funding in China for the first half of 2026 reveals a highly concentrated market where state and industrial capital are the dominant forces. Chinese embodied intelligence companies raised over 46 billion yuan (approx. $6.3B USD) across 288 deals, but the distribution was extremely uneven. One company, Qianxun Intelligence, secured 4.5 billion yuan (~$620M) alone, illustrating a 'Matthew effect' where a few top-tier startups absorb a disproportionate share of investment, often from strategic industrial players and state-backed funds.
Why it matters
This trend reveals a fundamental difference in the capital structure for robotics between China and the West. In China, industrial giants and state funds are not just investors; they are strategic partners seeking to lock in supply chains, create ecosystems, and ensure local deployment. This makes it incredibly difficult for grassroots startups without elite pedigrees or early state backing to compete. For global entrepreneurs, it means that partnering with a major Chinese industrial player may be the only viable path to enter or scale within that market, as traditional VC funding plays a secondary role.
NextFin News, which published the analysis, notes that traditional financial VCs are increasingly being relegated to co-investor status in major robotics rounds. The primary drivers are large corporations and government funds looking for supply chain leverage and strategic control rather than purely financial returns, a dynamic that profoundly shapes which startups succeed.
The World Economic Forum has named Hello Robot as one of its 2026 Technology Pioneers. The company is recognized for its work in developing assistive robotic systems, most notably its flagship product, Stretch. The Stretch robot is a mobile manipulator designed to assist with tasks like retrieval and object manipulation, with a focus on supporting individuals with mobility limitations as well as serving as a platform for robotics research.
Why it matters
This recognition from a major global institution like the WEF is a significant validation for the field of assistive robotics. It highlights the growing importance of robots designed not for industrial automation, but for direct human assistance and improving quality of life. For an entrepreneur, this signals that there is a recognized and valued market for robotics in healthcare and home assistance, and it positions Hello Robot as a leader in this space, likely opening doors to new partnerships and policy discussions.
Rocking Robots notes that this honor places Hello Robot among a select group of companies poised to have a significant impact on business and society. The award acknowledges the company's innovative approach to creating robots that can operate in human environments to provide practical help, a key challenge in the consumer and assistive robotics sectors.
Rainbow Robotics, a South Korean firm in which Samsung is a major stakeholder, has begun testing its RB-Y1 mobile manipulator in a Coupang e-commerce fulfillment center. The robot, which features a dual-arm upper body on a high-speed wheeled base, is designed for sorting, transporting, and handling goods. This marks the robot's first reported trial in a commercial warehouse environment, aiming to evaluate its performance and reliability on real-world logistics tasks.
Why it matters
This pilot is a significant step toward commercializing advanced mobile manipulators in the demanding logistics sector. The RB-Y1's design—combining fast locomotion with dexterous, dual-arm manipulation—represents a hardware platform capable of tackling tasks that are difficult for simpler AMRs or fixed robotic arms. For the industry, a successful trial could validate this form factor as a viable solution for warehouse automation and accelerate Samsung's strategic push into the robotics market.
Interesting Engineering reports that this trial follows Samsung's increased investment in Rainbow Robotics, signaling a clear strategic intent. TechTimes notes the pilot aims to assess reliability and efficiency for tasks like sorting and moving goods. Miraitalk frames this as part of Samsung's broader ambition to revolutionize warehouse automation by integrating humanoid-like robots that can work in existing human-centric environments.
ABB Robotics has initiated a collaboration with PSYONIC, a company that makes advanced bionic hands for amputees. The partnership aims to improve the dexterity of industrial robots by training them on real-world data collected from users of PSYONIC's Ability Hand. By analyzing the tactile feedback and manipulation strategies used by humans controlling these prosthetics, ABB hopes to teach its GoFa cobots to handle complex and delicate objects with more human-like skill.
Why it matters
This is a novel and highly practical approach to solving one of robotics' hardest problems: dexterous manipulation. Instead of relying solely on simulation or painstakingly programmed routines, this collaboration taps into a unique source of real-world, high-stakes manipulation data. If successful, it could create a powerful new methodology for training robots, bridging the gap between human intuition and machine execution and significantly expanding the range of tasks that collaborative robots can perform in industrial and service settings.
The Robot Report highlights that the goal is to replicate human dexterity by understanding touch feedback. This initiative seeks to move beyond simple grasping to more nuanced manipulation, which is critical for tasks in assembly, quality inspection, and logistics. This interdisciplinary approach, combining prosthetics with industrial robotics, represents a creative path forward for developing more capable end effectors and control systems.
Following its recent FDA clearance in the United States, Penumbra, Inc. has now received the CE Mark in Europe for its THUNDERBOLT system. This computer-assisted vacuum thrombectomy (CAVT) technology is used for removing blood clots in acute ischemic stroke patients. The European approval paves the way for a global launch of the device, which uses modulated aspiration to more intelligently detect and remove clots.
Why it matters
Securing both FDA and CE Mark approval in quick succession is a major commercial milestone for Penumbra and a significant development for stroke care. It validates the technology on a global regulatory stage and dramatically expands the addressable market for this advanced medical robotic system. For the healthcare robotics sector, it demonstrates a successful pathway from clinical trials to international market access for devices that tackle critical medical needs, which is essential given the rising global incidence of stroke.
Cardiac Vascular News reports the CE Mark as a key step for the company's global launch plans. This builds on the FDA clearance covered by Med-Tech Insights and Medtech Insight, which highlighted the device's innovative use of computer-assisted technology. The Lancet had previously published data indicating that stroke mortality is projected to increase, underscoring the medical need for such advanced intervention tools.
In a recent interview, Qualcomm CEO Cristiano Amon announced that the company is actively developing over 40 new device designs that support an 'agent-first' computing paradigm. This initiative moves beyond smartphones to include smart glasses, AI-enabled jewelry, and camera-equipped earbuds. The strategy emphasizes a chip-to-cloud platform for context-aware AI agents that operate primarily on-device, reducing reliance on the cloud.
Why it matters
Qualcomm's strategic pivot to 'agent-first' computing is a clear indicator of where the next wave of AI hardware is headed. By focusing on low-power, on-device processing for a wide array of form factors, the company is building the foundational silicon for a future of pervasive, ambient AI. For the robotics industry, this is critical. The chips, platforms, and software being developed for these consumer devices will directly enable more intelligent, power-efficient, and smaller robotic systems, from companion bots to sophisticated end effectors.
Letsdatascience.com and Benzinga both covered the announcement, highlighting the shift away from a purely app-based model of interaction. Blockchain.news connected this to a push for smart glasses, a form factor that requires highly efficient, on-device AI. This initiative solidifies Qualcomm's role as a key enabler for the edge AI ecosystem, competing directly with NVIDIA and others to power the next generation of intelligent devices.
Humanoid Reality Check Multiple analyses highlight a growing gap between China's massive humanoid production capacity and lagging buyer satisfaction and functional competence. While companies are shipping thousands of units, a survey reveals only 23% satisfaction, pointing to the unsolved challenge of embodied AI. This is contrasted with Western firms' more measured, pilot-driven approach (c_9, c_3, c_6).
The 'Physical AI' Investment Tsunami A wave of mega-funding rounds for startups like Prometheus ($12B), Neura Robotics ($1.4B), and Theker ($85M) signals a major investor pivot towards 'physical AI'—applying AI to real-world engineering, manufacturing, and robotics, rather than purely digital applications (c_57, c_60, c_54, c_59).
The Robot Brain Race Heats Up Tech giants and startups are releasing powerful, open-source AI models and frameworks specifically for robotics. Alibaba's new models, ACE Robotics' Kairos, and Tencent's HyVLA-0.5 are all aimed at creating a general-purpose 'brain' for robots, shifting competition from just hardware to the intelligence layer (c_33, c_38, c_96).
India's Emerging Robotics Ecosystem India is rapidly developing its domestic robotics industry with a focus on affordability. The launch of the Agni-2 and Astra-1 humanoids, both priced around $18,000 for local manufacturing, alongside new high-end consumer robot launches from Dreame, signals a multi-tiered market strategy (c_10, c_28, c_21).
Component and Material Innovation as the Foundation Breakthroughs in underlying components are enabling more advanced robots. This includes new flexible sensors inspired by nature, advanced cooling for AI chips, and the democratization of research hardware like TetherIA's $314 open-source robotic hand (c_95, c_94, c_30, c_103, c_109).
What to Expect
2026-06-22—Automate 2026 begins, featuring a dedicated Humanoid Robot Pavilion and production-ready Physical AI applications from companies like Teradyne.
2026-10-25—IEEE SENSORS 2026 conference kicks off in Rotterdam, The Netherlands.
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