Gene Therapy and Special Goggles Restore Limited Vision in Blind Patients

Scientists have developed an experimental treatment combining gene therapy with specialised goggles to restore limited vision in people affected by retinitis pigmentosa, a genetic disease that progressively destroys the retina’s light-sensitive cells. The treatment uses optogenetics, a technique that introduces a light-sensitive protein called ChrimsonR into retinal ganglion cells, enabling them to respond to light. Special goggles capture visual information and convert it into pulses of amber light that stimulate these modified cells, allowing visual signals to reach the brain. In a study, seven of ten participants experienced improved light sensitivity, demonstrating the potential of this approach to partially restore sight.

The results represent a promising advance in treating inherited blindness. Four of eight participants who completed behavioural testing could perform basic visual tasks, such as locating doorways or following lines, while wearing the goggles. However, the restored vision remains limited, with participants unable to recognise faces or read text. The treatment also requires an intact optic nerve to transmit visual information to the brain, restricting its suitability for certain forms of blindness. Despite these limitations, researchers consider the findings an important proof of concept and hope that further improvements will enable more sophisticated visual abilities.

More information:

https://www.sciencenews.org/article/cells-detect-light-blind-vision

Brain Implants Offer New Hope for Restoring Speech

Scientists are developing brain implants that help people who have lost their ability to speak due to conditions such as ALS, Parkinson’s disease, strokes and brain injuries. BCIs, detect electrical signals from the brain and use artificial intelligence to translate them into words or speech. One remarkable example is an ALS patient who received brain implants in 2023. Technology has allowed him to communicate nearly two million words, reconnect with his family and participate in everyday conversations. Researchers are also developing systems that can produce speech almost instantly, bringing them closer to restoring natural communication.

Despite these breakthroughs, technology remains experimental and faces challenges, including high costs, invasive surgery, limited portability and occasional inaccuracies in translating brain signals. Scientists are working on smaller wireless implants and more advanced AI systems that could reproduce natural speech patterns, emotions and gestures. Although widespread availability is not guaranteed, researchers believe these innovations could dramatically improve the quality of life for people with severe speech impairments, restoring not only their ability to communicate but also their independence and personal connections.

More information:

https://www.sciencenews.org/article/brain-implants-restore-voices-injuries

XREAL 1 Pro+

REAL has officially launched its new flagship augmented reality glasses, the XREAL 1 Pro+, priced at $599, introducing several improvements over the original One Pro released in 2025. The updated glasses feature significantly brighter Sony micro-OLED displays, increasing peak brightness from 700 to 1,200 nits, alongside AI-powered High Dynamic Range technology for enhanced image quality. The device retains its 1920 × 1080 resolution per eye, 57-degree field of view, 120Hz refresh rate, and proprietary X1 spatial computing chip. Additional enhancements include a redesigned ergonomic nose pad system for improved comfort and stability, while maintaining Bose-powered audio and 3DOF spatial tracking.

A notable advancement is the improved real-time 2D-to-3D content conversion, which now operates at 60 frames per second instead of 30, enabling smoother immersive viewing experiences. Although the XREAL 1 Pro+ resembles standalone smart glasses, it still requires a USB-C connection to compatible smartphones, laptops, or gaming devices. The glasses also support optional six degrees of freedom (6DOF) tracking through an external accessory. Available from October 15, 2026, the XREAL 1 Pro+ represents an incremental but meaningful upgrade, focusing on visual quality, spatial viewing, and user comfort rather than introducing an entirely new hardware platform.

More information:

https://roadtovr.com/xreal-1-pro-plus-release-date-price/

The Walking Robotic Hand

Researchers at ETH Zurich have developed an innovative autonomous robotic hand capable of walking on its fingers while simultaneously performing manipulation tasks. Unlike conventional robotic systems that require separate mechanisms for mobility and object interaction, this approach transforms a commercially available five-fingered robotic hand into a self-contained mobile robot. Using AI and reinforcement learning, the researchers trained the hand in simulation to navigate different surfaces, maintain balance, recover from falls, press keyboard keys, and push objects. Equipped with a compact onboard computer, battery, and motion sensors, the robotic hand successfully traversed 14 different surfaces, achieved an average walking speed of 9 centimetres per second, and demonstrated autonomous object manipulation. Its learning framework addresses the challenges posed by the hand's asymmetrical structure, enabling coordinated finger movements for both locomotion and manipulation.

The research introduces a promising direction for autonomous modular robotics, where individual robotic components can dynamically switch between different functions rather than remaining permanently assigned to specific tasks. Potential applications include industrial maintenance, inspection of confined environments, search-and-rescue operations, and advanced robotic manipulation in spaces inaccessible to conventional robotic arms. By combining mobility, dexterity, and intelligent control within a single compact platform, the technology could contribute to a new generation of adaptable, multifunctional robotic systems. Nevertheless, challenges remain regarding autonomous perception, navigation, mechanical durability, and reliability in complex environments. The broader vision is to develop robotic architectures in which individual components can operate independently or collaboratively, improving flexibility and adaptability across real-world applications.

More information:

https://spectrum.ieee.org/walking-robotic-hand

ViWAS Presentation - Future of Virtual Worlds

I participated in the 7^thmeeting of the European Commission’s Virtual Worlds Steering Group, held on 8 October 2026, delivering a presentation entitled “Future of Virtual Worlds: ViWAS – Virtual Worlds Skills Academy.” The presentation explored the rapidly evolving landscape of virtual worlds, highlighting advances in Extended Reality (XR), Artificial Intelligence (AI), immersive displays, spatial computing, digital humans, and intelligent virtual environments. Particular emphasis was placed on their transformative potential across education, cultural heritage, healthcare, industry, and digital collaboration, alongside critical challenges related to interoperability, accessibility, technological limitations, privacy, and sustainability. Prof. Liarokapis also introduced the ViWAS (Virtual Worlds Skills Academy) project, which aims to address Europe's emerging digital skills gap through innovative learning pathways, a pan-European competence and qualification framework, interoperable learning infrastructure, and inclusive educational opportunities for learners, educators, and professionals.

The presentation highlighted the initial research activities of ViWAS, including its Baseline Data Research Phase 1, focusing on identifying skills requirements and engaging stakeholders from industry, higher education, and vocational education and training. A key scientific contribution was the Extended Six-Dimensional Framework for Intelligent XR Learning Environments (6D-XR Framework), which integrates learner characteristics, pedagogical design, immersive representation, contextual environments, adaptive intelligence, and ethical and sustainability considerations. The presentation also introduced the project's emerging XR learning ecosystem and demonstration platform, illustrating how AI-supported personalisation, open educational resources, and interoperable technologies can facilitate accessible and future-ready immersive education. Through its participation in this European-level dialogue, CYENS reinforces its commitment to advancing responsible virtual worlds technologies, strengthening European digital competences, and fostering collaboration between research, education, industry, and policymakers.

More information:

https://ec.europa.eu/transparency/expert-groups-register/screen/meetings/consult?lang=en&meetingId=76421

Wearable Human Body

Engineers at Georgia Tech’s College of Engineering have developed a wireless system that allows wearable devices and tiny medical implants to communicate directly through the body’s tissues. Called SWANS (Smart Wireless Autonomous Networking System), the technology takes inspiration from the nervous system and uses the body’s natural ionic conductivity to transmit small electrical signals. Unlike conventional Bluetooth or NFC connections, which struggle to penetrate tissue and require relatively large antennas and substantial power, SWANS enables sensors and therapeutic devices located in different parts of the body to coordinate without being physically connected or positioned close together.

The researchers demonstrated the approach by creating a network of sensors and neural interfaces that coordinated limb movement in an animal model. Because the system requires very little power, implants can be made smaller than 3 millimeters, potentially allowing them to be inserted using a syringe rather than surgery. Sensors could eventually detect biological changes and automatically instruct another device to deliver medication, stimulate a nerve, or perform another therapeutic action at the appropriate location. Researchers vision SWANS as a step toward personalized bioelectronic medicine in which distributed sensors, wearables, and implants work together to monitor health and deliver treatments when needed.

More information:

https://coe.gatech.edu/news/2026/09/engineers-connect-health-wearables-and-implants-using-body-network

Smart Contact Lens Measures Stress Through Tears

Researchers have developed a lab on a contact lens capable of detecting serotonin in tears, potentially enabling continuous, noninvasive monitoring of stress and other physiological changes. The soft, reusable hydrogel lens incorporates flexible graphene and silver electrodes, with ferrocene helping it selectively detect extremely low serotonin concentrations. Laboratory tests showed sensitivity well below typical serotonin levels found in human tears, while experiments involving 10 volunteers found that tear serotonin decreased after stressful public-speaking and mathematics tasks. Testing on an anesthetized pig also demonstrated serotonin detection without signs of short-term irritation or infection.

The technology could eventually shift wearable health monitoring beyond physical measurements such as heart rate and temperature toward continuous biochemical sensing. Researchers have already produced a proof-of-concept wireless version using NFC for battery-free sensing and smartphone data transmission. However, substantial validation and safety testing remain necessary, particularly to understand how tear serotonin varies among individuals and relates to blood biomarkers and clinical assessments. Future versions could simultaneously measure serotonin, cortisol, and other molecules, potentially turning contact lenses into wearable platforms that provide a richer picture of stress and physiological health throughout everyday life.

More information:

https://spectrum.ieee.org/serotonin-stress-smart-contact-lens

Brain Waves May Underpin Cognition and Consciousness

A new theory from MIT proposes that cognition and consciousness emerge partly through analog computations performed by traveling electrical brain waves, rather than solely through fixed neural circuits and synaptic connections. While synapses provide the underlying infrastructure for storing memories, goals, and knowledge, researchers argue that they are too slow to explain the brain’s ability to rapidly reorganize information. Instead, rhythmic waves coordinate large populations of neurons in real time. Slower alpha and beta waves may regulate faster gamma activity associated with sensory information, dynamically determining which neural ensembles become active at places and moments. The interaction and interference of these waves could therefore enable parallel, analog forms of spatiotemporal computing.

The researchers extend this framework to consciousness, proposing that conscious experience emerges when brain-wave patterns organize activity across the cortex into a coherent, globally integrated state. Evidence from anesthesia studies supports this possibility: different anesthetic drugs can produce unconsciousness while disrupting large-scale wave dynamics despite acting through different molecular mechanisms. However, the authors emphasize that this remains a theory, and direct experimental evidence that brain waves perform the proposed analog computations is still needed. If confirmed, the framework could reshape models of cognition and potentially inspire treatments that target brain-wave dynamics, which can sometimes be influenced non-invasively.

More information:

https://www.technology.org/2026/09/19/cognition-and-consciousness-arise-from-analog-computations-says-new-theory/

AI Takes Root in Farming

Farmers are adopting artificial intelligence more readily than many other emerging technologies. Agriculture is particularly suited to AI because farms generate large amounts of data from machinery, sensors, satellites, weather services and field observations. AI can turn this information into practical recommendations, helping farmers predict yields, identify pests and diseases, optimise irrigation and fertiliser use, and make better operational decisions. Generative AI is also emerging as a kind of virtual agronomist, allowing farmers to obtain advice through natural-language queries and potentially making sophisticated agricultural knowledge easier to access.

Targeted applications of AI could generate around $100 billion in additional on-farm value globally. The appeal is largely driven by measurable benefits, higher productivity, reduced input and labour costs, improved resource efficiency and greater resilience to increasingly unpredictable environmental conditions. However, adoption is not uniform. Connectivity, data quality, affordability and concerns over control of farm data remain significant obstacles, particularly for smaller farms and farmers in regions with limited digital infrastructure. The broader message is that AI is gaining traction in agriculture because it can address concrete, everyday farming problems.

More information:

https://finance.yahoo.com/technology/ai/articles/farmers-embracing-ai-more-other-110000541.html

Brain Implant Enables Speech and Gestures Through an Avatar

Researchers at the University of California developed a BCI that allows people with severe paralysis to communicate using both speech and upper-body gestures through a digital avatar. The system uses one implant containing 253 electrodes positioned on the surface of the sensorimotor cortex to capture neural activity associated with attempted speech and movements. Machine-learning algorithms decode these signals in real time, enabling an animated avatar to speak while simultaneously performing gestures such as waving or nodding. The study involved two participants with severe paralysis and demonstrated that neural signals for speech and movement can be extracted from the same cortical region and translated into coordinated communication.

The research represents a step toward BCIs that reproduce the richness of natural human communication rather than simply generating text, speech, or cursor movements. Because conversation relies heavily on non-verbal cues, combining vocal expression with gestures could make interactions more intuitive and socially expressive for people affected by conditions such as ALS or brainstem stroke. Importantly, the findings suggest that a single neural interface can support multiple functions simultaneously, potentially reducing the need for separate implants dedicated to different tasks. The researchers ultimately envision multifunctional systems capable of restoring a broader range of communication and interaction abilities for people with severe paralysis.

More information:

https://www.science.org/content/article/single-brain-implant-lets-paralyzed-people-both-talk-and-gesture-avatar

Beijing’s Robot Kindergarten

A new robot kindergarten has opened in Beijing’s Shijingshan district to explore a different approach to training robots: allowing them to learn continuously through physical interaction, touch, trial and error, rather than relying primarily on human demonstrations. The facility was jointly established by tactile-sensing company Tashan Technology and a team led by Turing Award winner and reinforcement-learning pioneer Richard Sutton. Robots repeatedly attempt movements, receive feedback from their environment and modify their behaviour based on the results, for example, learning to avoid an obstacle after colliding with it. Sutton described the facility as a controlled environment where robots can learn about their own bodies and the physical world, making mistakes an essential source of training data.

The initiative reflects a broader effort to develop robots capable of continuous, autonomous learning after deployment, rather than having their behaviour largely fixed by pre-training, simulation or teleoperation. Researchers argue that robots could eventually generate their own experience-based datasets and potentially share what individual machines learn across common models, helping them adapt to situations not covered during initial training. Significant challenges remain, particularly hardware durability and the complexity of learning sophisticated humanoid behaviours. For now, autonomous experiential learning is expected to complement rather than replace imitation learning and simulation, while potentially becoming increasingly important as robots enter factories, services and homes.

More information:

https://www.globaltimes.cn/page/202609/1369570.shtml

Brain Implant Controlled Across Continents

Researchers from KAIST and Yonsei University have demonstrated a wireless brain implant that can be controlled across continents. Their system, called RAPIDO, received commands sent from Chicago to a laboratory in Daejeon, South Korea with an average response time of about 109 milliseconds. Designed for experiments with freely moving animals, the implant combines two capabilities: precisely delivering drugs into specific brain regions and providing targeted light stimulation for optogenetic experiments. Its refillable cartridge and internet-based control could enable longer-term studies while reducing the need for researchers to physically approach or repeatedly handle experimental animals.

In experiments with rats, RAPIDO successfully delivered controlled doses of cocaine into the nucleus accumbens over several weeks, producing measurable dose-dependent behavioral effects. In a separate experiment, researchers used the implant's light stimulation to activate the RhoA signaling pathway, preventing rats from developing the same learned preference for a cocaine-associated environment. The researchers stress that this does not constitute a treatment for addiction; rather, the work demonstrates a platform for remotely manipulating specific neural processes and studying their effects on behavior. Significant challenges must be addressed before such technology could be considered for human clinical applications.

More information:

https://www.sciencealert.com/a-brain-implant-in-korea-was-just-controlled-from-the-us

LLM-Personalised Autonomous Driving

Researchers at Delft University of Technology have developed an approach that allows passengers to personalise how an autonomous vehicle drives using natural-language commands. Instead of allowing a large language model (LLM) to control the vehicle directly, the system uses the LLM to interpret requests or indications that the passenger feels dizzy. These preferences are translated into adjustments to parameters used by a conventional, safety-aware motion planner, affecting characteristics such as speed, acceleration, steering smoothness and collision avoidance. The system also keeps the passenger in the loop by explaining the proposed changes in everyday language and asking for confirmation before applying them. Tests using the nuPlan autonomous-driving simulator showed that the system could successfully adapt driving behaviour to eight different passenger prompts, producing smoother driving when comfort was prioritised and higher speeds when urgency was expressed.

The approach is significant because it combines the flexibility and natural-language understanding of LLMs with the predictability of traditional autonomous-driving controllers. Rather than relying on an LLM for real-time driving decisions—which can suffer from latency, hallucinations and a lack of performance guarantees—the researchers use GPT-4o-mini only to translate subjective passenger preferences into changes within predefined safe limits. This separation means the underlying motion planner remains responsible for vehicle control, reducing the potential consequences of incorrect LLM outputs. However, researchers note that maintaining safe operating constraints still requires substantial engineering, and the Delft approach does not yet provide mathematically provable safety. Other work is therefore exploring additional verification layers that mathematically check AI-generated driving decisions against traffic rules and predicted road-user behaviour before they are executed.

More information:

https://spectrum.ieee.org/autonomous-vehicles-motion-planner-llm

Flexible Brain Circuits Enable Cognitive Switching

MIT neuroscientists discovered that the brain could reuse the same neural circuits for different cognitive tasks, helping explain how a finite number of neurons supports such a wide range of behaviors. In experiments with mice, researchers examined activity in the prefrontal and parietal cortices while the animals compared auditory tones and remembered information needed to decide. They found that while neurons in the parietal cortex mainly retained sensory information, a group of neurons in the prefrontal cortex could flexibly switch roles, first maintain a sensory memory of a tone and later store the action the animal planned to perform.

The findings support the concept of modular or compositional cognition, in which neural circuits function like reusable building blocks rather than dedicated systems for individual tasks. By applying the same computational mechanisms to different kinds of information (such as sensory inputs or motor plans) the brain can efficiently combine and repurpose neural resources to produce flexible behavior and learn new tasks without constructing entirely new circuits. The researchers plan to test this mechanism further by selectively inhibiting these modules during different stages of tasks to determine their causal role in cognitive flexibility.

More information:

https://news.mit.edu/2026/flexible-brain-circuits-can-switch-between-different-tasks-0817

AI-Designed Viruses Raise Safety Concerns

Scientists at Stanford University have created what are described as the first functional viruses whose genomes were designed by artificial intelligence. Researchers used genome language models called Evo1 and Evo2, trained on genetic information from about 2 million bacteriophages, viruses that infect bacteria, to generate thousands of candidate viral genomes. Nearly 300 were synthesised in the laboratory, producing 16 viable bacteriophages. A mixture of these AI-designed viruses successfully attacked strains of E. coli that had developed resistance to naturally occurring phages, demonstrating potential for developing more adaptable phage therapies against antibiotic-resistant bacterial infections.

The breakthrough also raises significant biosafety and biosecurity concerns because it demonstrates that generative AI can design complete, biologically functional viral genomes. The researchers deliberately excluded genetic data from viruses that infect humans, animals and plants, but experts warn that similar approaches applied to pathogenic organisms could create novel biological threats. Biosecurity specialists therefore argue that governance needs to develop alongside the technology, combining controls on AI-model development and access with responsible research oversight, DNA-synthesis screening, laboratory biosafety and restrictions on potentially dangerous genome production.

More information:

https://www.theguardian.com/science/2026/aug/06/safety-fears-as-scientists-make-first-viruses-designed-by-ai

Teaching Drones to Play Tag with AI

Researchers at Sandia National Laboratories are using reinforcement learning (RL) to teach autonomous drones how to cooperate and make rapid decisions in a strategic version of tag. In the experiment, two evader drones attempt to reach a protected base while two pursuer drones try to intercept them. The evaders learn through simulated rewards and penalties to coordinate their movements, including strategies that can cause the pursuers to interfere or collide with one another. Unlike the RL-trained evaders, the pursuers use a conventional proportional-navigation algorithm. The research demonstrates how multi-agent reinforcement learning can produce flexible cooperative behaviours without engineers having to explicitly program every possible manoeuvre.

The project is overcoming the simulation-to-reality gap: strategies that perform well in simulation can fail on physical drones because of factors such as battery depletion, aerodynamic interactions, communication delays and other unmodelled dynamics. Sandia therefore tests the algorithms on small, inexpensive quadrotors in its CAMINO facility, using high-precision motion capture to evaluate and refine their behaviour before moving toward more costly systems. Beyond the game itself, the work could contribute to autonomous systems capable of pursuit, evasion and coordinated swarm behaviour in rapidly changing environments, including potential applications for protecting critical infrastructure against hostile drones and other national-security scenarios.

More information:

https://www.sandia.gov/labnews/2026/08/13/teaching-drones-to-play-tag/