Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
New Quantum Hermite Transform Algorithm Enhances AI and Scientific Computing Potential
Researchers from the U.S. Department of Energy’s Brookhaven National Laboratory, Northeastern University, Google Quantum AI, and the University of Texas at Austin have introduced a new quantum computing algorithm called the quantum Hermite transform (QHT). This algorithm aims to broaden the scope of problems that future quantum computers can address, particularly in artificial intelligence and scientific simulations. The significance of the quantum Hermite transform lies in its potential to improve data processing and simulation capabilities of quantum computers. By introducing a new computational building block, the QHT could lead to more efficient quantum algorithms in various fields, including materials science and energy research. The findings were presented at the 58th Annual ACM Symposium on Theory of Computing in Salt Lake City. Looking ahead, the researchers emphasize that expanding the library of reusable quantum primitives like the QHT will facilitate the development of innovative quantum algorithms. This advancement could provide exponential speed advantages over classical methods, marking a pivotal step in the evolution of quantum computing applications. No further timeline was disclosed at the time of publication.
AI and Robotics
MIT and Toyota Develop SceneSmith to Enhance Robot Training with AI-Generated Environments
MIT and the Toyota Research Institute have introduced SceneSmith, a system that utilizes AI agents to create realistic 3D environments for robot training. This innovation addresses the significant challenge of generating diverse simulation content, which is crucial for teaching robots various tasks in a cost-effective manner. The SceneSmith system employs three AI agents, leveraging the advanced vision-language model GPT-5.2, to design intricate indoor scenes. These environments, featuring up to six times more objects than previous methods, allow robots to practice skills in a rich virtual playground, ultimately reducing the need for extensive real-world testing. As the research progresses, the effectiveness of these AI-generated environments will be closely monitored. The team has already demonstrated that robots can successfully navigate and perform tasks in these virtual settings, indicating a promising future for robotic training methodologies. No further timeline was disclosed at the time of publication.
Research Robotics Artificial intelligence Simulation Computer science and technology Machine learning
MIT's FloatForm Swarm Robots Create Adaptive Floating Structures for Urban Spaces
MIT researchers have developed FloatForm, a swarm of small robotic boats that autonomously assemble into larger floating structures. Each robot, measuring 21 centimeters square, is equipped with thrusters, sensors, and magnetic latches, allowing them to form bridges, platforms, and other structures with minimal human input. This innovative system aims to transform urban waterfronts into dynamic, programmable spaces, enhancing public infrastructure and emergency response capabilities. The significance of FloatForm lies in its potential to revolutionize how urban areas utilize water surfaces. By mimicking the self-organizing behavior of fire ants, the robots can adaptively create and reconfigure structures on demand, addressing challenges such as traffic alleviation during emergencies or creating temporary public spaces. This modular approach to floating infrastructure could lead to more livable cities by expanding usable public space onto underutilized water areas. Looking ahead, the research team plans to explore further applications of FloatForm in urban environments, with no specific timeline disclosed for future developments. The project builds on previous work with full-size autonomous vessels in Amsterdam, indicating a growing interest in leveraging water for urban mobility and public space expansion. The open-access findings were published in Nature Communications, highlighting the collaborative efforts of MIT's Computer Science and Artificial Intelligence Laboratory and the Senseable City Lab.
Research Robotics Autonomous vehicles Artificial intelligence Computer science and technology Machine learning
MIT affiliates win 2026 Hertz Foundation Fellowships
A new fellowship program has been launched to support doctoral students in applied sciences, engineering, and mathematics who are dedicated to addressing critical challenges in science and technology. This initiative aims to recognize and empower emerging researchers who are developing innovative solutions to pressing issues. The program is designed to enhance the educational and research opportunities for these students, providing them with the resources necessary to advance their work. By fostering a new generation of scientists and engineers, the fellowship seeks to contribute to the advancement of knowledge and technology, ultimately benefiting society as a whole. The initiative is expected to play a significant role in shaping the future of scientific research and technological development.
Awards, honors and fellowships Students Graduate, postdoctoral Alumni/ae Chemistry Mechanical engineering
MIT Researchers Selected for Funding in US Department of Energy’s Genesis Mission Phase I
MIT researchers have been chosen to participate in the U.S. Department of Energy’s Genesis Mission, with 15 collaborative projects receiving funding under Genesis Phase I. This national initiative aims to create a powerful integrated science discovery platform that leverages AI, supercomputing, and quantum systems to drive advancements in energy and scientific discovery. The Genesis Mission is significant as it fosters collaboration between universities, industry, and national laboratories, aligning research efforts with national priorities. Ian A. Waitz, MIT’s vice president for research, emphasized the importance of this initiative in catalyzing innovation for the benefit of both the nation and the world. Looking ahead, projects that demonstrate promising pathways for transformative capabilities may receive further funding from the DOE. Six projects will be led by MIT principal investigators, while MIT researchers will also contribute to nine additional projects led by other institutions, showcasing a robust collaborative effort in advancing scientific capabilities.
Funding Artificial intelligence Quantum computing Laboratory for Nuclear Science Plasma Science and Fusion Center Research Laboratory of Electronics
Carnegie Mellon University Showcases Innovations in Defense Manufacturing at 2026 Summit
Carnegie Mellon University (CMU) presented several new partnerships and technologies at the 2026 Pennsylvania Defense and Innovation Summit. This event took place from July 14-15 at the U.S. Army War College in Carlisle, Pennsylvania, and was hosted by U.S. Senator David McCormick. The summit highlighted CMU's commitment to advancing defense manufacturing and military education through innovative research and collaboration. These efforts are crucial for enhancing the capabilities of the defense sector and ensuring that military personnel are equipped with the latest technologies. Looking ahead, stakeholders in the defense industry should monitor CMU's ongoing initiatives and partnerships that may emerge from this summit. No further timeline was disclosed at the time of publication.
Announcements
SpaceX Proposes 1 Million AI Satellites to Address Ground Data Center Constraints
On January 30, 2026, SpaceX filed with the FCC to launch up to 1 million AI compute satellites, positioning orbital data centers as a solution to the increasing demand for AI computing power. Ground data centers are facing significant challenges, with energy consumption projected to reach approximately 1,050 TWh in 2026, making them the fifth-largest electricity consumer globally. The demand for new data center capacity is outpacing the growth of power generation infrastructure, leading to a critical bottleneck in the grid system. The significance of this initiative lies in the structural constraints faced by ground data centers, including power delivery limitations, high water consumption, and local opposition to new projects. The Uptime Institute's 2026 outlook identifies power as the primary constraint on data center growth, with capacity clearing prices in the PJM grid skyrocketing to $329.17/MW, driven by data center expansion. Additionally, cooling requirements are becoming increasingly unsustainable, with facilities consuming vast amounts of water, further complicating their operational viability. Looking ahead, SpaceX's orbital AI compute initiative aims to circumvent these challenges by leveraging the advantages of space, such as continuous solar power and minimal local opposition. The first AI prototypes are expected to launch in early 2027, with operational deployments planned for 2028. No further timeline was disclosed at the time of publication.
Toward a future that preserves benefits of neurotechnology for all
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
Contests and academic competitions Awards, honors and fellowships Students Artificial intelligence Ethics Law
LLMs help robots understand vague instructions and focus on key details
Researchers at MIT have developed an innovative approach to enhance the efficiency of robots in performing chores in various environments, including homes and factories. This new method employs a dual-language model system: the first model is designed to interpret and clarify user instructions, while the second model focuses on filtering out irrelevant information that may hinder task execution. This advancement aims to improve the interaction between humans and robots, making it easier for machines to understand and carry out complex tasks effectively. The initiative reflects MIT's commitment to advancing robotics technology and its potential applications in everyday life.
School of Engineering MIT Schwarzman College of Computing Aeronautical and astronautical engineering Electrical engineering and computer science (EECS) Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology
Exploring the societal impacts of AI
At the recent AI and Society Forum, prominent researchers from the Massachusetts Institute of Technology (MIT) engaged in an in-depth discussion regarding the impact of artificial intelligence on employment and democratic processes. The forum, held in October 2023, served as a platform for experts to address pressing concerns about how AI technologies are reshaping job markets and influencing political systems. The motivation behind this dialogue stems from the rapid advancements in AI and the need to understand their broader societal implications. Researchers presented findings and insights on the potential benefits and challenges posed by AI, emphasizing the importance of developing strategies to mitigate risks while harnessing the technology's capabilities. Through collaborative discussions, the forum aimed to foster a greater understanding of AI's role in shaping the future of work and governance.
Special events and guest speakers Artificial intelligence Technology and society Computer science and technology Economics Democracy
The tenured engineers of 2026
Ten faculty members at the Massachusetts Institute of Technology (MIT) have been awarded tenure, marking a significant milestone in their academic careers. This decision, announced recently, affects five different units within the School of Engineering, highlighting the institution's commitment to fostering academic excellence and innovation. The tenure grants are intended to recognize the contributions and potential of these faculty members, who have demonstrated exceptional research and teaching capabilities. By securing tenure, these educators will gain increased job security and the opportunity to pursue long-term projects that can further advance their fields. This announcement underscores MIT's ongoing efforts to support its faculty and enhance its educational environment.
Awards, honors and fellowships Faculty Aeronautical and astronautical engineering Civil and environmental engineering Electrical engineering and computer science (EECS) Mechanical engineering
3D-printed devices could streamline the production of drug-delivery microparticles
A new development in particle production technology has emerged, utilizing cost-effective devices that can be constructed in just a few hours. These innovative devices employ electrospray emitter technology to efficiently generate three-layered particles on a large scale. This advancement is poised to enhance manufacturing processes across various industries by providing a faster and more economical method of particle creation. The introduction of these devices marks a significant step forward in the field, potentially leading to improved applications in pharmaceuticals, materials science, and other sectors that rely on precise particle engineering.
Research 3-D printing Additive manufacturing Electronics Medical devices Drug delivery
Improving the performance of high-power electronics
Researchers have discovered that applying a thin layer of diamond can significantly enhance the speed and energy efficiency of next-generation wireless devices. This innovative approach addresses the challenge of excessive heat generated during device operation, which has been a limiting factor in the performance of modern technology. The findings, which emerged from ongoing studies in advanced materials science, highlight the potential for diamond to serve as an effective thermal management solution. This breakthrough could pave the way for faster and more efficient wireless communication, ultimately benefiting consumers and industries reliant on high-performance devices.
Research Computer chips Electronics Carbon materials Nanoscience and nanotechnology Mobile devices
Ambassadors of STEM
A newly established student club at the Massachusetts Institute of Technology (MIT) is dedicated to supporting K-12 students through hands-on STEM education. This initiative, spearheaded by alumni of the FIRST Robotics program, seeks to leverage their experiences and expertise to inspire younger students in the fields of science, technology, engineering, and mathematics. The club aims to create engaging learning opportunities that foster creativity and problem-solving skills among participants. By organizing workshops, mentorship programs, and robotics competitions, the group hopes to enhance educational enrichment and ignite a passion for STEM in the next generation. The club's formation reflects a growing commitment within the MIT community to address educational disparities and promote STEM literacy among youth.
Clubs and activities STEM education Students Undergraduate Robotics Mechanical engineering
It took 40 years for technology to catch up to this zipper design
MIT Professor Bill Freeman has introduced an innovative fastener known as the "Y-zipper," which is designed to transform gear, robots, and art with ease. This three-sided fastener allows users to snap items into shape at the push of a button, significantly enhancing convenience and functionality. The concept draws inspiration from an old patent held by Freeman, showcasing the potential for advancements in design and technology. The development of the Y-zipper reflects a growing interest in creating user-friendly solutions that streamline the assembly and manipulation of various objects. As this technology gains attention, it could pave the way for new applications across multiple industries.
Research Invention Design Robotics 3-D printing Wearables
CES 2026: limited-edition gaming tablet blends AI computing with Kojima Productions design
At CES 2026, Asus' gaming brand Republic of Gamers (ROG) announced a collaboration with Japanese game studio Kojima Productions to introduce a limited-edition version of its Flow Z13 2-in-1 gaming tablet. This partnership represents a unique intersection of gaming hardware and innovative game design, as the ROG Flow Z13-KJP is inspired by Kojima Productions’ Ludens concept. The collaboration aims to enhance the gaming experience by merging cutting-edge technology with the creative vision of one of the industry's most renowned developers.
News Feed CES 2026
New chip could help tiny robots traverse complex environments
A team of researchers has developed an innovative method for creating 3D maps to enhance navigation systems, utilizing a combination of an efficient algorithm and specialized hardware. This advancement, which was announced in October 2023, aims to significantly reduce the memory and power requirements typically associated with 3D mapping technologies. By streamlining the mapping process, the researchers hope to improve the efficiency and accessibility of navigation tools, making them more practical for a variety of applications, including autonomous vehicles and mobile devices. The integration of dedicated hardware with the algorithm allows for rapid map generation, which could lead to faster and more reliable navigation solutions in real-world scenarios.
Research Computer science and technology Algorithms Artificial intelligence Machine learning Robotics
Could AI tell you where you left your keys?
Researchers have developed an innovative spatial memory system designed for robots, enabling them to effectively capture and retain detailed information about objects encountered during environmental exploration. This advancement, which leverages cutting-edge technology, aims to enhance the robots' ability to navigate and interact with their surroundings more intelligently. The system was introduced in a study published in October 2023, showcasing its potential to improve robotic perception and memory capabilities. By integrating sophisticated algorithms, the robots can now better recognize and remember various objects, ultimately leading to more autonomous and efficient operations in diverse settings. This breakthrough is expected to have significant implications for fields such as robotics, artificial intelligence, and automation, as it allows for more nuanced interactions between machines and their environments.
Research Computer science and technology Algorithms Artificial intelligence Machine learning Robotics
New research enables a robot to chart a better course
A new open-source system called “MIGHTY” has been developed to enhance efficiency in disaster recovery and parcel delivery by creating optimized travel routes. This innovative technology generates smooth path plans that significantly reduce travel time while effectively navigating around obstacles. The system aims to address the challenges faced during emergencies and improve logistics operations. By leveraging advanced algorithms, MIGHTY is designed to facilitate quicker responses in critical situations, ultimately aiming to save lives and resources. The initiative is expected to be particularly beneficial in areas prone to natural disasters, where timely assistance is crucial.
Research Computer science and technology Algorithms Drones Robotics Autonomous vehicles
Human-machine teaming dives underwater
A team of researchers is advancing the capabilities of collaboration between divers and autonomous underwater vehicles (AUVs) for maritime missions. This initiative, which began in late 2023, aims to enhance operational efficiency and safety in underwater exploration and tasks. The research is taking place at a leading marine technology institute, where experts are focused on creating innovative hardware and sophisticated algorithms that facilitate seamless communication and coordination between human divers and AUVs. The motivation behind this development stems from the increasing complexity of underwater missions, which require precise teamwork to navigate challenging environments and accomplish objectives effectively. By integrating advanced technology, the researchers hope to improve the overall effectiveness of maritime operations, making them safer and more efficient for both divers and AUVs alike.
Research Sensors Lincoln Laboratory Oceanography and ocean engineering Robotics Computer science and technology
Australian Maritime College and HII Report Near-Perfect Availability as REMUS 100 Completes 935 Missions with Only Two Days of Downtime
The Australian Maritime College (AMC) and HII have announced a significant achievement regarding the reliability of AMC’s Legacy REMUS 100 autonomous underwater vehicle (AUV). This milestone was revealed today, highlighting the advancements made in the technology and performance of the AUV. The collaboration between AMC and HII aims to enhance underwater exploration and data collection capabilities, addressing the growing demand for reliable and efficient marine technology. The REMUS 100 is designed for various applications, including environmental monitoring and underwater research, making it a vital tool for marine scientists and researchers. This development underscores the commitment of both organizations to push the boundaries of autonomous underwater operations and improve the reliability of such technologies in real-world applications.
hii australian maritime college (amc)
JAIST and King's College Develop EleTac Soft Gripper with Integrated Tactile Sensing
Researchers from Japan's JAIST and King's College London have developed EleTac, a soft robotic gripper inspired by the trunk of an elephant. This innovative design integrates grasping, external tactile perception, and proprioception within a single soft structure. The gripper can manipulate various objects, including tofu and fabric, while estimating contact position and force using a vacuum system operating at 30 kPa. The significance of EleTac lies in its ability to handle delicate and irregularly shaped items, addressing the challenges of soft robotics. Traditional rigid grippers utilize clear joints for sensing, while soft grippers often struggle with limited perception due to their material properties. EleTac's design allows for continuous tactile sensing across its surface, enhancing its ability to discern between self-induced deformations and external contacts. Future developments will focus on refining the visual-based tactile sensing capabilities of EleTac, which utilizes an internal optical system to monitor material deformation. This advancement could lead to improved performance in applications requiring precise manipulation of fragile objects. No further timeline was disclosed at the time of publication.
Soft Robotics Tactile Sensing Proprioception Robotic Grippers
SpaceX Launches Starmind Project for 1 Million AI Satellites by 2028
SpaceX has officially named its orbital AI infrastructure project 'Starmind,' which aims to deploy a constellation of up to 1 million satellites. This initiative, confirmed by Elon Musk on June 22, 2026, will enable AI inference directly in space, utilizing solar energy rather than terrestrial power sources. The first satellite, designated AI1, was unveiled on June 8, 2026, and is designed to operate in sun-synchronous orbits. The significance of Starmind lies in its potential to overcome the limitations faced by ground-based data centers, such as land, power, and water constraints. By running AI computations in orbit, Starmind can provide a more efficient solution to the growing demand for AI computing power. The project leverages the existing Starlink infrastructure for data transmission, distinguishing its function from Starlink's internet relay capabilities. Looking ahead, SpaceX plans to begin hardware deployment with the AI1 satellite, while full-scale production and deployment of the satellite constellation are targeted for 2028. As of now, no Starmind satellites have been launched, and further engineering challenges remain to be addressed, particularly regarding the scalability of the satellite design.
NVIDIA Confidential Computing to Help Expand Apple’s Private Cloud Compute
NVIDIA has announced that its GPUs equipped with Confidential Computing technology are now being utilized for confidential inference in Apple’s Private Cloud Compute (PCC). This development marks a significant expansion of Apple’s cloud capabilities, extending beyond its own data centers to include Google Cloud. The announcement was made during Apple’s annual Worldwide Developers Conference (WWDC), where the company showcased its latest advancements and innovations aimed at enhancing data security and privacy for users. This collaboration with NVIDIA is expected to bolster Apple’s commitment to maintaining user confidentiality while leveraging cloud resources effectively.
Milestone: Ascend 910C Completes Full-Parameter Post-Training of 1.6 Trillion Parameter Model, Domestic AI Computing Crosses Key Threshold
Shenzhen Hetao College, in partnership with Harbin Institute of Technology (Shenzhen), the Shenzhen Big Data Research Institute, and Huawei, has announced a significant advancement in domestic artificial intelligence computing. The collaborative effort culminated in the successful completion of a full-stack AI computing platform, marking a pivotal moment for the region's technological landscape. This achievement, revealed on October 15, 2023, in Shenzhen, aims to enhance the capabilities of AI applications across various industries. The initiative is driven by the growing demand for advanced computing solutions and the need to bolster China's position in the global AI arena. By integrating expertise from academia and industry, the consortium has developed a robust system designed to support complex AI tasks, thereby fostering innovation and economic growth in the region.
AI
New Applications of Magnetic Soft Robots: Random Number Generation and Reservoir Computing
Researchers from Helmholtz-Zentrum Dresden-Rossendorf and the University of Messina have unveiled a groundbreaking application of magnetic soft robots in the fields of random number generation and reservoir computing. This innovative study, conducted recently, highlights how these robots utilize chaotic dynamics to convert their unpredictable movements into effective computational resources. The findings suggest significant potential for enhancing secure communication systems and developing low-cost computing solutions, particularly in resource-limited settings. By harnessing the inherent randomness of the robots' movements, the research opens new avenues for technological advancements in various applications.
Soft Robotics Magnetic Actuators Random Number Generation Reservoir Computing
Chinese Startup Weilan Tech Unveils BabyAlpha A3: A Quadruped Robot That Outpaces Nvidia's Computing Throne
Weilan Tech has unveiled its latest innovation, the BabyAlpha A3, which boasts a cutting-edge 6-chip heterogeneous computing cluster and a high-resolution 66-megapixel vision system. This new technology promises to deliver ten times the computing efficiency compared to industry standards while significantly reducing costs, priced at just one-tenth of Nvidia's Jetson Thor. The launch, which highlights Weilan Tech's commitment to advancing computing capabilities in the tech sector, is set to reshape the landscape of artificial intelligence and machine vision applications.
News
MIT in the media: For the future of tech, "Massachusetts can absolutely lead"
Leaders and faculty from the Massachusetts Institute of Technology (MIT) engaged in discussions focused on enhancing innovation and talent development in Greater Boston. This dialogue is part of a special series of articles released in conjunction with the outlet's annual compilation of influential figures in the technology sector, known as the 'Tech Power Players.' The initiative aims to address the region's evolving tech landscape and the importance of nurturing a skilled workforce to maintain Greater Boston's competitive edge in the industry. Through collaborative insights and expert perspectives, the series seeks to highlight strategies that can effectively foster an environment conducive to technological advancement and innovation.
President Sally Kornbluth Faculty Research Cambridge, Boston and region Technology and society Computer science and technology
Chinese firm hits one million monthly micro SSD production milestone for edge computing
China’s Longsys has achieved a significant milestone by stabilizing its monthly production capacity at one million micro solid-state drives. This accomplishment comes as the company aims to meet the growing demand for advanced storage solutions in various sectors, including consumer electronics and data centers. The ramp-up in production reflects Longsys' commitment to innovation and efficiency in manufacturing, positioning itself as a key player in the competitive tech landscape. The company has implemented streamlined processes and advanced technologies to enhance its output, ensuring that it can cater to both domestic and international markets effectively. This development marks a crucial step for Longsys as it seeks to expand its footprint in the global semiconductor industry.
AI and Robotics
Students from across the Northeast step inside MIT.nano’s cleanroom
A hands-on boot camp is currently underway, aimed at teaching integrated photonics to students from community and four-year colleges in the region. This educational initiative, which focuses on practical skills and knowledge in the rapidly evolving field of photonics, is designed to equip participants with the necessary tools to excel in this technology-driven industry. The program is taking place in local educational institutions, fostering collaboration and learning among students from diverse backgrounds. By providing this training, organizers hope to enhance the workforce's capabilities and address the growing demand for expertise in integrated photonics. The boot camp emphasizes experiential learning, allowing students to engage directly with the technology and gain valuable insights into its applications and implications.
Materials Research Laboratory MIT.nano Education, teaching, academics STEM education Manufacturing Industry
Chinese firm debuts compact humanoid robot with 42 DoF and 100 TOPS computing power
KEENON Robotics has introduced the XMAN-L1, a new compact humanoid robot aimed at enhancing interactive service experiences. The unveiling took place recently, showcasing the robot's capabilities in various service-oriented environments. This innovative technology is designed to assist in tasks such as customer interaction and support, reflecting the company's commitment to advancing automation in service industries. By integrating advanced AI and robotics, KEENON aims to improve efficiency and customer satisfaction in sectors like hospitality and retail. The launch of the XMAN-L1 marks a significant step forward in the company's efforts to provide cutting-edge solutions that meet the evolving needs of businesses and consumers alike.
Goodwood Festival of Speed unveils Future Lab lineup for 2026
The Goodwood Festival of Speed has revealed the exhibitor lineup for its 2026 Future Lab exhibition, which will showcase innovations from companies and research organizations in fields such as robotics, artificial intelligence, quantum computing, healthcare, space exploration, and digital technologies. Scheduled to take place at the heart of the Festival of Speed, the Future Lab aims to draw over 90,000 visitors, highlighting the event's commitment to promoting cutting-edge advancements. This initiative underscores the festival's role as a platform for technological exploration and engagement within the automotive and broader tech communities.
Events artificial intelligence automation embodied ai formula e Future Lab
AI Is Learning to Read the Room
Recent advancements in emotion AI technology are reshaping how machines interpret human feelings, particularly in professional settings. Companies like Meta and startups such as Hume AI are developing systems that analyze facial expressions, voice tones, and behaviors to gauge emotions during interactions like performance reviews. This technology, which has applications in employee well-being, recruitment, and customer service, aims to enhance communication by providing real-time feedback. Despite its rapid growth, current emotion AI systems often struggle to capture the complexity of human emotions, typically categorizing feelings into simplistic labels like "happy" or "sad." Researchers are now focusing on a new approach called human-context AI, which combines multiple inputs—such as facial dynamics and voice modulation—with situational context to better understand emotional nuances. This shift aims to close the gap between human emotional expression and machine interpretation. The origins of emotion AI trace back to the MIT Media Lab, where Rosalind Picard pioneered the concept of affective computing. Over the years, advancements in data collection and analysis have improved the accuracy of emotion detection. However, ethical concerns remain, particularly regarding privacy and the potential for misuse in workplaces and public spaces. As this technology evolves, it promises to enhance various applications, from professional development platforms to health care, by providing a deeper understanding of human emotions. Yet, experts caution against over-reliance on AI for critical decisions, emphasizing the importance of human insight in interpreting emotional signals.
Emotions Affective-computing Facial-expressions Companion-robots Multimodal-ai Machine-learning
UK and Japan Announce ‘Frontier Technology Partnership’ Including AI, Quantum, Space & Energy
The United Kingdom and Japan have initiated a new partnership focused on frontier technologies, with the goal of enhancing collaboration in areas such as artificial intelligence, semiconductors, and quantum computing. This agreement, announced by UK Prime Minister Keir Starmer and Japanese Prime Minister Sanae Takaichi, reflects both nations' efforts to bolster economic resilience and decrease reliance on foreign technology ecosystems. The partnership underscores a shared commitment to innovation and strategic technological advancement, aiming to foster a robust cooperative framework that can address emerging challenges in the global tech landscape.
AI AI Funding & Investment Robotics Cybersecurity Defense Japan
AI's Final Mile: Transitioning from Demonstration to Real-World Application
At the WAIC 2026, while humanoid robots showcased impressive feats, a closed-door discussion titled 'Chain π Roundtable' addressed the gap between AI technology demonstrations and real-world applications. Wu Liming, Chairman of Huamao Technology, highlighted that Moore's Law has failed beyond 5nm, with chip performance now limited by physical constraints. Advanced packaging and optical interconnects are crucial, with advanced packaging sales expected to surpass traditional packaging by 2025. The conversation also introduced the concept of 'native AI in factories' by Wei Jie, Chairman of Shanghai Jingzhi. He noted that many industrial AI projects excel in labs but struggle in factories due to issues like data fragmentation and insufficient validation scenarios. He emphasized that AI must grow from real manufacturing data to ensure operational stability. The roundtable concluded with three key insights: the bubble in computing infrastructure will not burst before fall 2028, the speed of AI adoption depends on data loop iterations, and the focus should be on profitability rather than trends. The overarching theme was the need for AI to operate sustainably and profitably in real environments, underscoring the importance of stable revenue for technology development.
Industrial AI Data Integration Advanced Packaging Healthcare AI Robotics
OpenAI Invests Over $30 Billion in 3.2GW Data Center in Georgia
OpenAI is set to invest more than $30 billion in a large data center campus in coastal Georgia, aiming to provide up to 3.2 gigawatts of computing capacity over the next decade. This significant investment positions OpenAI among leading tech companies expanding hyperscale AI infrastructure in the U.S. The project is crucial as it addresses the increasing demand for AI computing resources, with the electricity capacity equivalent to the needs of approximately 2.4 million U.S. homes. OpenAI's CEO, Sam Altman, is expected to discuss next-generation AI models with U.S. lawmakers, highlighting the importance of regulatory frameworks in the evolving AI landscape. Looking ahead, the first several hundred megawatts of power are anticipated to be available by 2028, with construction continuing until 2032. OpenAI's strategic shift in infrastructure planning and its commitment to sustainable practices will be key factors to monitor as the project progresses.
AI and Robotics
Nvidia Unveils Vera CPU for AI, Challenging AMD and Intel in Server Market
Nvidia has introduced its next-generation CPU, Vera, designed specifically for AI applications, marking its entry into the CPU market. This strategic move positions Nvidia to compete directly with established players AMD and Intel in the AI server sector. The company has begun shipping Vera chips to clients such as OpenAI, Anthropic, and SpaceX, highlighting its commitment to vertical integration in technology. The significance of this launch lies in Nvidia's aim to redefine server architecture by focusing on single-core performance rather than core count, which has been the traditional approach by competitors. With the server CPU market projected to reach $200 billion, Nvidia's Vera chip is expected to play a crucial role in enhancing AI agent performance, offering 50% better efficiency compared to existing x86 chips from Intel and AMD. Looking ahead, Nvidia's strategy to sell complete computing systems rather than just individual chips could reshape the competitive landscape in AI servers. As the demand for AI capabilities continues to grow, the performance and pricing of the Vera CPU will be critical factors to monitor in the evolving market dynamics.
Bristol Myers Squibb and NVIDIA to Build Largest AI Supercomputer for Pharma by 2027
Bristol Myers Squibb (BMS) has partnered with NVIDIA to construct the largest AI supercomputer in the pharmaceutical sector, expected to be operational by January 2027. This supercomputer will be hosted by Equinix under a co-location agreement, marking a significant investment in AI technology for drug discovery. The initiative underscores the growing importance of high-performance computing in pharmaceuticals, as companies recognize that computational power is essential for advancing drug discovery processes. Unlike tech firms that rent computing resources, BMS has opted to purchase its own infrastructure, ensuring control over proprietary data and intellectual property. Looking ahead, BMS's AI supercomputer will feature NVIDIA's DGX SuperPOD, significantly enhancing performance and providing access to advanced AI tools. This strategic move aligns with BMS's commitment to leveraging AI for improved patient outcomes, as highlighted by Chief Digital and Technology Officer Greg Meyers. No further timeline was disclosed at the time of publication.
AI and Robotics
Biren Develops Next-Gen Optical Links for Enhanced AI Chip Connectivity
Biren, a Shanghai-based startup, is pioneering optical technology to connect thousands of AI accelerators into unified computing systems. As AI models grow increasingly complex, the demand for efficient interconnectivity among GPUs has intensified, with traditional copper connections reaching their limits. Biren's innovative near-packaged optics (NPO) architecture aims to support clusters of up to 1,024 AI accelerator cards, significantly enhancing computing capabilities. This advancement is crucial for AI infrastructure companies striving to meet the needs of models with trillions of parameters. Biren's approach addresses the scalability challenges faced by conventional server architectures, which typically cap at around 128 GPUs. By positioning optical fibers closer to chips, the company enhances bandwidth and data transmission efficiency, positioning itself against competitors like MetaX and Alibaba. Looking ahead, Biren is testing its NPO interconnect system while also developing an orthogonal hardware architecture in collaboration with ZTE. Although the semiconductor industry is still in the early stages of optical interconnect technology, widespread adoption is projected for around 2028, contingent on further advancements and real-world validation of these systems.
AI and Robotics
China's WAIC Highlights AI Advancements Amid US Rivalry and Global Collaboration Efforts
The World AI Conference (WAIC) in Shanghai is set to showcase China's ambition to compete in the AI sector, particularly in models, chips, and robotics. This event occurs against the backdrop of increasing technological rivalry with the US, which has imposed restrictions limiting China's access to advanced computing chips. China's government has prioritized technological self-reliance, accelerating the development of domestic alternatives in both hardware and software. Foreign ministry spokesman Lin Jian emphasized that China opposes ideological divisions and technological blockades, aiming to use WAIC to foster exchanges and consensus while promoting AI benefits to developing countries. This year's WAIC will serve as a critical indicator of China's progress in transforming AI model advancements into a comprehensive industrial ecosystem. Observers should pay attention to how China plans to influence global AI governance, safety standards, and international collaboration as AI technology increasingly integrates into the physical world.
SpaceX Unveils AI1 Satellite Specs for Starmind Constellation with Key Thermal Challenges
SpaceX has introduced the AI1 satellite, the inaugural component of its Starmind constellation, which stands 20 meters tall and has a wingspan of 70 meters. This orbital compute node is designed to deliver computing power equivalent to one NVIDIA GB300 server rack, utilizing a unique cooling system with deployable liquid radiators. The satellite's specifications were revealed during a presentation on June 8, 2026, ahead of SpaceX's IPO. The significance of the AI1 satellite lies in its role as a compute platform rather than a traditional satellite, focusing on running AI inference workloads. The satellite's cooling system, which is critical for its operation in the vacuum of space, is designed to reject heat through infrared radiation. However, independent engineers have raised concerns about the feasibility of the thermal and mass claims made by SpaceX, suggesting that the cooling requirements may exceed practical limits. Looking ahead, SpaceX plans to launch two AI1 prototypes in early 2027, with full-scale production expected to commence later that year at its Gigasat facility in Bastrop, Texas. The ongoing debate regarding the satellite's thermal management capabilities will be crucial to monitor as the project progresses, with no further timeline disclosed at the time of publication.
Starmind's Orbital Compute vs. Terrestrial Data Centers: Analyzing Resource Advantages
Starmind's orbital compute technology presents a significant advantage over traditional ground-based data centers by eliminating constraints related to land, water, and grid permitting. While terrestrial data centers are currently cheaper and faster to construct, with U.S. data center spending reaching $85.3 billion in 2026, Starmind's approach focuses on addressing the growing resource limitations faced by hyperscale facilities. The significance of Starmind's technology lies in its ability to sidestep the increasing challenges of land and water usage. For instance, a 100 MW data center can consume approximately 530,000 gallons of water daily for cooling, while Starmind's AI1 utilizes deployable liquid radiators that require no water. This structural advantage could resonate with investors as the demand for AI computing continues to escalate, potentially leading to annual water withdrawals of up to 1.7 trillion gallons by 2027. Looking ahead, Starmind's next milestones include the launch of AI1 prototypes scheduled for early 2027. However, the technology's claims regarding cooling efficiency and operational reliability remain unverified until real flight data is available. As the industry evolves, the competition between orbital and terrestrial solutions will become increasingly relevant, particularly in the context of resource management and sustainability.
Small-AI Models Gain Traction Around the World
One morning in 2019, Adebayo Alonge was in a Cape Town hotel room, preparing to demonstrate his startup’s AI answer to a serious problem in African health care: counterfeit medication, which kills thousands of people across the continent every year.The RxScanner is a handheld spectrometer that scans a pill with infrared light, then sends the item’s molecular profile to an AI model equipped with a pharmaceutical database. In seconds, the AI identifies the medication from its molecular profile—or reports that it’s phony.Pharmacies were using the system in more than a dozen countries, including Ghana, Kenya, Myanmar, and Alonge’s native Nigeria. But that morning in South Africa, it didn’t work. “I was shocked,” Alonge says.The spectrometer connected to the AI model—but the data center was 14,000 kilometers away and bandwidth was limited. “Our server was in the United States, and just to get the result of a single scan was taking me over 5 minutes.”So Alonge immediately asked his engineers to shrink the AI model down to a smaller, low-power, unconnected version that could run entirely on his Android phone. They produced it 2 hours later, and that saved the demo.More importantly, the work birthed a new version of his device, which can authenticate a pill in places without broadband, computers, or even reliable electricity. It also turned Alonge into an advocate for this kind of “small AI.”Small AI for Global Health Care AccessSmall AI is a far cry from wealthy nations’ colossal large language models (LLMs), hyperscale data centers, multibillion-dollar investments, and debates about AI consciousness. But for millions of people around the world, the only AI that matters, and often the only kind available, is small. (According to a World Bank Report issued in November, only 0.7 percent of internet users in the world’s poorest countries have used ChatGPT, compared to a quarter of all internet users in the most developed nations.)“Most people are discussing AI from the LLM/generative side. But that needs a lot of computing power, electricity, massive data, and skilled people to manage it,” Ajay Banga, president of the World Bank, said last January at the World Economic Forum, in Davos. “Outside the developed world, other than maybe India and China, very few countries have that combination.”By contrast, small AI can deliver useful, even life-saving services to people in areas that have none of those things, Banga said. In India, where the government’s AI plans call for more development of small AI, many such systems are working for farmers.For example, a drone-based system developed by Bala Murugan and colleagues at the Vellore Institute of Technology, in India, takes photos of cashew plants and quickly identifies those with splotches that indicate disease. All the processing takes place on the drone itself, so there’s no need for a computer on-site, nor for a connection to a central server.Using small language models trained for a specific problem, and sometimes running on cheap, low-power devices, other small-AI implementations have been developed to identify ant infestations in a Uruguayan vineyard, detect the presence of malaria-carrying mosquitoes in a number of nations, and run electrocardiograms from an Arduino device in parts of Brazil that lack access to more complex equipment.“This is the most important area in AI nowadays,” says Marcelo José Rovai, a professor at the Institute of Engineering and Information Systems at the Federal University of Itajubá, in Brazil, who was involved in all three projects. “It’s growing very fast.”Low-Power, Small-AI Models on Devices Small AI models can run on a variety of low-power devices, including [from left to right] an Arduino Nano 33 BLE Sense, a Seeed Wio Terminal, and an Arduino Portenta.Moez AltayebFor Alonge, Rovai, and other advocates, small AI is not just “a promising trend,” as that November World Bank report calls it. It may be, in the long term, the form of AI that will touch the most lives and remain sustainable after some of the giant models become too costly for most users.“I think the future of AI is not like one giant model, at a center. I think it’s millions of small, precise models deployed at the edge, each one solving like a specific problem, a specific context,” Alonge says. This is partly because much of humanity—including people in parts of rich countries as well as the developing world—lives without access to cutting-edge frontier models. But, he says, it’s also because those models are not sustainable.“If someone is not subsidizing it, most people will not be able to afford those models. So those of us who are said to be small-AI developers are the ones who will have to build for the majority of the world,” Alonge says.There is no strict definition of “small AI,” but people often use the term for language models with at most a few billion parameters. (Compare that to cutting-edge models, which can include more than a trillion.) That’s small enough to run directly on a phone or a Raspberry Pi. That’s what allows these applications to run on devices without a connection to a data center and use only a few watts of power, often supplied by a battery or a solar panel.Despite their small footprint, these models aren’t fundamentally different technology from that of gigantic AI models, Rovai says. Many instances of small language models were created the same way the phone-based version of Alonge’s pharmaceuticals scanner was—by “pruning” large models, or removing the parameters that weren’t involved in the task. The result is a system that’s less capable generally but still very good at the specific job it was pruned for, Rovai says. A lighter version of RxAll’s RxScanner spectrometer sends its results to an AI model run locally on a phone to check that a drug’s molecular signature is genuine.RxAllOther small models are created by “distillation.” They are trained to mimic a large model, until their performance approaches that of their “teacher,” Rovai says. In other cases, a larger model’s precision is reduced, for example, so that a model run on 32-bit architecture can run on 8-bit designs. In situations where the machine learning application is being used to classify data or predict patterns (like an ant infestation), it’s trained from the beginning on a small device, not derived from a larger model at all. Running all these small, specialized systems is becoming easier, Rovai says, for two reasons.The first reason is that hardware is getting better and more capable while using less power, he says. This means more and more phones can run small AI—especially those equipped with neural processing units, which are specialized chips that handle AI tasks like facial recognition and changing the brightness, shadows, or contrast in a photo.In 2025, slightly more than a third of all smartphones shipped worldwide were capable of running generative AI, and that figure will reach 45 percent by the end of this year, according to the technology research firm Counterpoint. By the end of next year, slightly more than half of all smartphones will be able to run a small AI model.The second reason Rovai cites is the shrinking footprint of language models. Both Google DeepMind’s Gemma 4 (released in April) and Alibaba’s Qwen 3.5 are “fantastic” for small AI, Rovai says. Both models are “open weight,” meaning users can adjust the connections between parameters to suit their needs. This makes it easy, for example, “to take a lot of data from, say, the milk industry and retrain the model specifically on that,” Rovai says.Rovai illustrated these reasons on a Zoom call, using one of his most recent experiments. Holding up a device, he says, “This is the new Arduino UNO Q—a US $50 device with a Qualcomm chipset. I’m running a language model here, which collects data from sensors and analyzes that data to detect tiny pools of water where mosquitoes might be breeding. It takes 3 watts to run it.”Support for Small-AI DevelopmentConvinced that millions of people are already benefiting from these kinds of applications, the World Bank now actively promotes small AI with grants, mentorship programs, financing, technical advice, and models of government policies that are friendly for small-AI development. For example, in Rwanda, the World Bank is backing a government program to help low-income households get devices that can run AI.All that said, no one claims that large language models are going away entirely. To create a generative AI that can run on a phone or other small device requires the architectural insights, data processing, and results of a larger model, Rovai says. “We need the big models to create these smaller models.” And for all that small AI can benefit people without access to big AI, the technology can’t solve the larger problems of development and digital inequality, Alonge says. Implementing small AI won’t allow nations to escape the challenge of creating an ecosystem to support AI: reliable power, a supply chain that works, and an educational system that develops the talents needed to create AI tools.Though his drug-scanning system can run for days on a phone with no connection, “you still want to be able to enable periodic syncing for updates with new signatures for the medications and analytics,” Alonge says. “And even when you are using batteries, reliable power is important. That phone battery is not going to last forever.”In many parts of the world, the future of small AI isn’t assured, he says. “It works, and many places will eventually need to use it. The question is whether or not the political actors are wise enough to invest in infrastructure to support it long term.”
Small-language-models Artificial-intelligence Llms
Japan Pioneered Humanoid Robots—Can It Now Catch China?
“In the future, the relationship between humans and robots will deepen, and the distinction between them will probably disappear.” This prediction, from one of the attendees at the recent Humanoids Summit in Tokyo, might have been unremarkable had it not come directly from an android that was first introduced to the world 20 years ago. Geminoid HI-6 is the sixth-generation of a robot originally designed in 2006. The mechanical twin of Osaka University professor Hiroshi Ishiguro, Geminoid HI-6 is now equipped with a large language model trained on Ishiguro’s own writings and interviews. It has advanced conversational skills and can even have a chat with its creator, an eerie spectacle. But at the Humanoids Summit, Geminoid was one of the few humanoid robots from Japan, the country that pioneered the form factor.While the event in Tokyo only had about 40 robots on display, Chinese systems outnumbered Japanese by roughly three to one. Some Japanese robotics firms were even using Chinese robots in their own technology demonstrations, something that would have been unthinkable in the recent past—one Japanese engineer described the situation as “sad.” The conference was a stark reminder of how Japan has ceded its early lead in humanoid robot development to overseas competitors, and the challenge it now faces to secure a place in an ecosystem increasingly dominated by general-purpose robots powered by AI. Twenty-five years ago, Japan was turning out groundbreaking humanoids that were showstopping in their abilities, but they were not commercialized as practical machines in any meaningful way. Heavily influenced by science fiction and lacking practical applications, they were mostly expensive technology demonstrations that were eventually mothballed. What Japan retains, however, is robotics design and know-how, which it must leverage to be a key player in the rapidly evolving humanoid ecosystem. Learning to Walk—Then Standing StillTo anyone who has seen recent videos of Chinese humanoids doing kung-fu and synchronized acrobatics, as well as half-marathon races, China’s remarkable progress in the field is nothing new. At the Humanoids Summit, Toyota showed a video of its latest basketball-playing robot, and Honda exhibited its latest robot hand, but the full-scale humanoids on the floor were mostly Chinese–the kid-size K1 machines from Booster Robotics of Beijing were dancing to Michael Jackson tunes. The full-scale G1 humanoid from Unitree Robotics of Hangzhou was also doing demos. “You cannot sell these bipedal systems in Japan for safety and compliance reasons,” says Shuichi Nagao, a frequent visitor to China as CTO of Omakase Robotics, a division of Zeals, a Japanese humanoid robot developer. Omakase was exhibiting a G1 modified with an external PC controller, a dextrous hand, a suction-cup manipulator and a sensor “hat” with an extra speaker, mic and camera. “In China, the government is pushing humanoid development. They didn’t have an industry 20 years ago. The people pushing it are young, in their 20s and 30s. It’s a really different mentality out there,” says Nagao. “Big players in Japan are still looking for use cases for humanoids. In China, they’re already doing mass production and reducing the cost, so other countries can’t compete with them anymore.”Another Japanese company showing off G1 bots was summit sponsor GMO AI & Robotics, a subsidiary of Japanese internet company GMO. It’s using the robots in partnership with Japan Airlines to load and unload cargo containers at Tokyo’s Haneda airport. The cargo project is a trial—like many other humanoid experiments—but the fact that Chinese machines have penetrated so far into Japan’s ecosystem upends a long history. In 1973, scientists at Waseda University in Tokyo built WABOT-1, considered the first full-scale humanoid robot and capable of slow bipedal locomotion, grasping objects and simple communication. It inspired Honda’s groundbreaking Asimo humanoid, but it was never commercialized. Asimo was eventually retired in 2022, the year ChatGPT was released. Two years later, Unitree’s G1 went on sale for US $16,000. China’s High Torque Technology Co. showed off its Mini Pi biped, customized with an anime-inspired head, at Humanoids Summit in Tokyo. The regular version is priced at $3,500. Tim HornyakSupply and DemandJapan’s development of humanoids happened before practical applications or widespread demand were in place, but bad timing is only part of the story—Japan also has a history of developing technologies that might appeal to domestic consumers but not necessarily those overseas. For example, decades after they first appeared, its highly engineered, multifunction toilets have only recently found a following abroad. Japan’s humanoid prowess was partly built on the back of its legendary industrial automation, yet even that stronghold has eroded. Ani Kelkar, a partner from McKinsey & Company in Boston who produces analytical reports about the robotics industry, told the summit audience that while Japan occupied the top spot in the world in manufacturing robot density (the number of multipurpose industrial robots in operation per 10,000 employees) from at least 1994 to 2009, it then slipped to second in 2014, third in 2019 and fifth in 2024. In that year, South Korea was at the top of the leaderboard with a robot density of 1,220 compared to Japan’s 446. The International Federation of Robotics estimates China now has the most operational industrial robots in the world, with around 2 million total units, approximately 4.5 times more than Japan. “The annual installation numbers are impressive too: 54 percent of all robots installed worldwide in 2024 were deployed in China,” the IFR said in a release in April 2026. “I think the loss of Japanese leadership is more to do with the rise of China as a manufacturing powerhouse including for sectors that Japan had high export levels,” Kelkar said in an email interview. “The recovery has not yet happened as Japan ‘missed’ the rapid acceleration in AI for robotics and is now playing catchup.”How Japan Can Adapt Kelkar believes Japan has a US $100 billion opportunity in general-purpose robotics, which are machines that can perform a wide variety of tasks, and it cannot rely on the slower-growing industrial robot market, which is centered on factory machines that do one simple and predictable task like welding car parts. He points to a McKinsey white paper suggesting that while Japan has much of the hardware and technology experience needed to support general purpose robot development, it must change its strategy to capture more share in AI, software, data collection and robotics platforms.Tetsuya Ogata is a professor of engineering and director of the Institute for AI and Robotics at Waseda University, the birthplace of humanoids in Japan. He briefed the summit on how a nonprofit he chairs, the AI Robot Association (AIRoA), is working with Toyota and other members to develop foundational technologies for collaborative use. For instance, AIRoA has collected some 80,000 hours of data on remote operation of mobile manipulators, and Ogata believes it’s the largest dataset of its kind. Using the data, it built and verified Vision-Language-Action (VLA) models, and it has also started data collection for dual-arm mobile manipulation. In an interview, Ogata acknowledged Japan’s struggle to find its place in the changing landscape. “The world of AI is inherently a game of scale,” says Ogata. “Therefore, Japan’s absolute prerequisite is to secure a competitive baseline of scale—in data, computing resources, and talent. Beyond that, what I consider most critical is a mindset shift: rather than trying to hoard scale within a single nation or company, we must grow stronger by collaborating with a diverse ecosystem of domestic and international players.” Specifically, this means creating a ‘collaborative domain’ to address data—the single biggest bottleneck—through industry-wide cooperation rather than data-siloing. By collectively nurturing a pre-competitive, shared data infrastructure and foundation model, individual companies can then compete on top of it with their own applications. “By offering this open ‘data ecosystem’ to the world, we can engage global players and establish a ‘third pole’ alongside the US and China,” says Ogata. “I believe this is how Japan can reclaim its global presence.”In 1999, Japan introduced the world’s first mobile internet services platform. But being first didn’t turn Japan into a smartphone manufacturing or design center—it’s now merely a supplier of parts to other countries who are leading the smartphone industry. If Japan can avoid a repeat of that experience and successfully deregulate, diversity, and commercialize its original humanoid dreams, it stands a better chance of influencing the direction of the industry and reaping billions in value. As automobiles and electronics were pillars of Japan’s industrial strategy in the last century, Japan could make humanoid robots one of its key value generators in the 21st century, an approach that would not only deliver economic benefits but give Japan greater clout in how the industry will evolve. Just like Japanese cars, electronics, and even toilets, Japanese humanoids could stand for craftsmanship and reliability. It’s a legacy that Japan can’t afford to give up.
Japan Robotics Humanoids Humanoid-robots
Microsoft unveils next-generation platform "Project Solara," transitioning from GUI to AI agents.
At the Microsoft Build 2026 conference held in June, the tech giant unveiled "Project Solara," a groundbreaking platform designed to prioritize AI agents over traditional graphical user interfaces and mobile applications. This innovative system facilitates collaboration between cloud-based AI agents and edge devices, enabling a seamless user interface that transcends hardware limitations. The announcement included an overview of two conceptual models, illustrating a new vision for computing in the age of artificial intelligence. As Microsoft explores this "AI agent-first" approach, it raises questions about the future of user interaction and the potential transformations in technology.
Weeks after Huang visit, Nvidia expands Korea hiring into robotics, HPC
Nvidia is expanding its engineering presence in South Korea, nearly a month after CEO Jensen Huang announced the company's plans to establish a research and development center in the country. Recent job postings on Nvidia's official careers website indicate a focus on key areas such as robotics simulation, high-performance computing, and automotive software, which are closely linked to South Korea's manufacturing, semiconductor, and automotive industries. This strategic move aims to strengthen Nvidia's involvement in these critical sectors, reflecting the company's commitment to innovation and collaboration within the region. The latest job listings, discovered by the Korea Herald, highlight Nvidia's intent to tap into local expertise and resources as it seeks to enhance its technological capabilities in Korea.
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Bentley prices drop to 270,000; second-hand luxury fuel car prices plummet; Cambrian loses 70 billion in market value in a
OpenAI has reportedly achieved a significant technological breakthrough, successfully reducing the operational costs of its AI model inference by over 50% through a series of system optimizations. This development was disclosed by engineers within the company on June 30. Meanwhile, in the automotive sector, the price of second-hand luxury fuel vehicles has seen a dramatic decline, with a Bentley listed at approximately 26,800 yuan and a Porsche Macan at around 15,000 yuan as of July 1 in Qingdao. This drop is attributed to a notable increase in depreciation rates, which reached 30% in May alone, a stark contrast to the previous annual average of 30%. In the realm of artificial intelligence, Anthropic announced that its Claude model is now fully available on Microsoft Foundry, allowing enterprise users to deploy the model within the Azure environment. Additionally, Amazon Web Services revealed plans to invest $1 billion to establish a new AI department aimed at assisting clients in building AI systems. In financial news, Warren Buffett has paused his annual donations to the Bill and Melinda Gates Foundation, pending the outcome of an investigation related to the late Jeffrey Epstein. Furthermore, the U.S. Federal Reserve Chairman emphasized the ongoing challenge of high inflation levels in the country, indicating a commitment to maintaining price stability. As for the tech industry, Meta is reportedly planning to sell excess AI computing resources to external clients, intensifying competition with major cloud service providers.
Meta, like SpaceX, looks to turn excess AI compute into cash
Meta is embarking on a new venture to establish a cloud infrastructure business that will offer access to artificial intelligence computing power and models. This strategic initiative aims to compete directly with major players in the cloud services market, including Amazon Web Services, Google Cloud, and Microsoft Azure. The development comes as Meta seeks to diversify its offerings and capitalize on the growing demand for AI capabilities in various industries. By leveraging its expertise in AI technology, Meta plans to provide businesses with robust tools and resources, potentially transforming the landscape of cloud computing. The timeline for this initiative remains unclear, but it reflects Meta's commitment to innovation and its ambition to carve out a significant presence in the competitive cloud market.
AI Meta SpaceX
The Orbital Data Center Hype Machine Is Already in Orbit
At the World Economic Forum in Davos this January, SpaceX founder Elon Musk announced plans to establish orbital data centers in space, predicting that they will become the most cost-effective solution for artificial intelligence (AI) within two to three years. Following this declaration, SpaceX submitted an application to the Federal Communications Commission for a constellation of up to 1 million satellites in low Earth orbit, aimed at supporting this ambitious project. However, experts caution that the logistics of deploying such a vast number of satellites are daunting. Currently, there are approximately 14,500 active satellites in orbit, with SpaceX's Starlink making up two-thirds of that total. To launch 1 million satellites, SpaceX would need to conduct over 16,000 dedicated launches, a feat that could take decades given current launch capacities. Challenges also extend to the technical feasibility of cooling advanced computing hardware in space, as highlighted by the difficulties faced by startups like Starcloud, which has struggled to operate even a single GPU in orbit. Concerns have been raised about the potential for increased space debris and the impact on astronomical observations. Despite these hurdles, analysts suggest that the push for orbital data centers is driven by the growing demand for AI computing power and the need for energy-efficient solutions. While Musk's timelines may be optimistic, industry experts believe that the concept is gaining traction, with major players beginning to invest in the necessary infrastructure to explore the viability of space-based data centers.
Orbital-data-centers Satellites Spacex Elon-musk Starcloud Ai
Liquid AI's smallest model yet LFM2.5-230M beats models 4X its size at data extraction, can run 'anywhere'
Liquid AI, a company founded by former MIT computer scientists, has unveiled its latest AI language model, LFM2.5-230M, which is designed for efficient data extraction and local deployment on devices such as smartphones and laptops. Released today, this 230-million-parameter model is noted for its ability to run on various hardware platforms, outperforming larger models like Alibaba's Qwen3.5 and Google's Gemma 3 in specific benchmarks. Targeting developers and engineers, LFM2.5-230M operates under a dual-use commercial license, allowing free access for individuals and companies with annual revenues below $10 million, while larger enterprises must secure a paid agreement. The model distinguishes itself by utilizing the LFM2 architecture, enabling high inference speeds with a minimal memory footprint, making it suitable for edge computing. Liquid AI's launch reflects a broader industry shift towards architectural efficiency rather than sheer parameter counts, as major AI firms focus on models with hundreds of billions of parameters. The LFM2.5-230M is specifically tailored for lightweight data extraction tasks, allowing businesses to automate processes without relying on costly cloud services. In practical applications, the model has been successfully deployed in a humanoid robot, demonstrating its capability to process complex commands efficiently. Available immediately on platforms like Hugging Face, LFM2.5-230M aims to revolutionize how enterprises manage data extraction, moving away from traditional, rigid systems to more adaptable AI-driven solutions.
TechnologyRobotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
