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/

Humanoid Robots Take on Real-World Firefighting

At the 2^nd World Humanoid Robot Games (WHRG) in Beijing, 23 teams competed in a realistic simulated firefighting challenge aimed at testing whether humanoid robots can progress from impressive demonstrations to practical work in hazardous environments. Held at an actual fire brigade, the competition required robots to complete three tasks within 30 minutes: identify hazardous materials, locate and close open valves, and find and operate a fire extinguisher. The event exposed significant challenges associated with real-world deployment, including rain, changing lighting, object recognition, manipulation accuracy and movement speed. Of the 12 teams competing on Sunday, only three completed the full challenge, highlighting the gap between laboratory performance and reliable operation in unpredictable environments.

Despite these limitations, organisers and participating teams viewed failures as valuable opportunities for improving humanoid robotics. Data from unsuccessful object recognition, manipulation and motion-planning attempts can be used to refine algorithms and train AI models. The competition also demonstrated emerging approaches such as VR-based teleoperation, multi-jointed robotic hands and specialised actuators combining precision with strength. The event reflects China's broader effort to move humanoid robots and embodied AI into practical applications, particularly dangerous tasks such as emergency response. Ultimately, the objective is not necessarily to replace firefighters, but to develop robots capable of working alongside humans and undertaking operations where human exposure would be risky.

More information:

https://www.globaltimes.cn/page/202608/1368322.shtml

AI Assistant for Art Provenance

Researchers are exploring how AI can help solve one of the art world’s most difficult problems: establishing an artwork’s provenance, or documented history of ownership and attribution. The NPR report describes efforts to develop an AI-based provenance assistant capable of searching and connecting information scattered across archives, auction catalogues, museum records, historical documents and other sources. Rather than replacing provenance researchers, the technology is intended to accelerate the labor-intensive process of identifying names, dates, transactions and relationships that may reveal where an artwork has been and who owned it. This could be particularly valuable for works whose histories contain significant gaps or whose ownership changed during periods such as war, displacement or political upheaval.

At the same time, the approach highlights the limitations of using AI for sensitive art-historical research. Provenance evidence can be incomplete, contradictory or ambiguous, meaning that an AI-generated connection cannot automatically be treated as historical fact. Human scholars still need to examine original records, assess the reliability of sources and determine whether proposed connections are credible. The broader promise, therefore, lies in using AI as a research assistant rather than an authority: a tool capable of navigating enormous collections of digitised information and suggesting leads that experts can subsequently verify. Such systems could ultimately make provenance investigations faster and more systematic while helping museums, collectors and researchers address questions of authenticity, ownership and potentially contested cultural property.

More information:

https://www.npr.org/2026/08/06/nx-s1-5922729/ai-art-provenance-assistant

Robots That Make Recycling Smarter

Researchers at the Karlsruhe Institute of Technology (KIT) have developed a robotic system designed to automatically dismantle broken products while preserving valuable components for reuse. Unlike conventional robotic assembly, disassembly is difficult because damaged devices can behave unpredictably. The system combines robotic manipulators with predictive algorithms, CAD models, and mathematical models of possible damage. It tests how individual components move, compares their behaviour with expectations, and updates its disassembly plan in real time. For example, if a screw is stuck, the robot can recognize that its original strategy has failed and switch to another technique, such as milling away surrounding material.

Users can also specify which components are particularly valuable, allowing the system to prioritize keeping them intact. The researchers see technology as an important step toward an automated circular economy, in which machines and electronic products are repaired, refurbished, and reused rather than discarded. The long-term vision is a factory containing many specialized robotic arms equipped with different tools, capable of dismantling a wide range of products, extracting defective components, replacing them, and potentially rebuilding the devices automatically. If scaled successfully, automated disassembly could make repairing products cheaper than manufacturing replacements, reducing electronic waste and the demand for new raw materials.

More information:

https://spectrum.ieee.org/recycling-robot

AI Creates More Realistic Multi-Person Images

Researchers at Cornell have developed a new AI approach for generating more realistic images involving multiple people interacting with one another. While existing image-generation models can create convincing individual people, they often struggle to represent complex interactions accurately. The Cornell method addresses this through iterative pose-image generation, progressively constructing a scene one person at a time. Each predicted pose helps guide the generation of subsequent people, allowing the system to better capture spatial relationships and interactions without requiring users to manually specify poses. The approach uses the FLUX image-generation model as its foundation and combines pose detection with a multimodal large language model to organise descriptions, poses and spatial regions for each person.

The researchers also introduced DrawWaldoWorlds, a benchmark designed to evaluate whether image-generation systems correctly represent not only multiple individuals but also their roles and relationships, essentially testing whether the model understands who does what to whom. Experiments showed that the new approach produced more faithful multi-person scenes than existing methods. In a user study involving 20 participants, images generated using the Cornell method were preferred roughly two-to-one over images produced by two versions of FLUX. The researchers argue that automatically incorporating pose information could make generative AI considerably better at depicting complex social activities, sports, group scenes and other situations where realistic human interaction is essential.

More information:

https://news.cornell.edu/stories/2026/07/strike-pose-creating-more-realistic-multi-person-images

Zoox Wins U.S. Approval for Driverless Robotaxis

Amazon-owned Zoox has become the first company in the United States to receive federal approval for the commercial deployment of purpose-built robotaxis that have no steering wheel, pedals or other human driving controls. The exemption from the National Highway Traffic Safety Administration (NHTSA) allows Zoox to deploy up to 2,500 vehicles annually for the next two years and begin charging passengers, initially in Las Vegas before expanding to other markets subject to state and local approvals. The electric, carriage-style vehicles feature inward-facing seats and are designed entirely around autonomous operation rather than modified versions of conventional cars.

The approval represents an important regulatory milestone for autonomous transportation, but it comes with enhanced safety oversight. NHTSA will require Zoox to provide additional reporting on crashes, inappropriate road stops and other operational problems, and the agency can withdraw the exemption if significant safety concerns emerge. Regulators are particularly focused on how autonomous vehicles interact with emergency services, construction zones, school buses and unusual road conditions following several incidents across the industry. The decision also signals a broader shift in U.S. regulation toward developing safety standards specifically designed for fully autonomous vehicles.

More information:

https://www.reuters.com/world/amazons-zoox-wins-first-us-approval-paid-robotaxis-with-no-human-controls-2026-07-30/

Digital Innovation Is Transforming the Museum Experience

Museums around the world are embracing digital technologies to create richer, more engaging experiences for visitors. By using data to better understand how people move through galleries, which exhibits attract the most attention, and how visitors interact with collections, museums can design exhibitions that are more intuitive, accessible, and enjoyable. These insights help institutions improve storytelling, enhance visitor engagement, and create experiences that appeal to audiences of all ages.

Technologies such as artificial intelligence, interactive displays, and digital guides are transforming museums into more immersive cultural spaces. Rather than replacing the traditional museum experience, these innovations complement it by making art, history, and heritage more accessible and interactive. The challenge lies in using technology responsibly, respecting visitors’ privacy while ensuring that digital tools enrich, rather than overshadow, the cultural and educational value of their collections.

More information:

https://arstechnica.com/culture/2026/07/with-help-from-data-art-museums-are-reframing-the-visitor-experience/

Snake Robots Aid Earthquake Rescue Efforts

Following the devastating earthquakes that struck northern Venezuela in June 2026, researchers from Carnegie Mellon University's Robotics Institute deployed advanced snake robots to assist international search-and-rescue teams in the heavily affected city of La Guaira. Designed to slither through narrow gaps in collapsed buildings, the robots are equipped with front-mounted cameras that allow rescuers to inspect areas inaccessible or too dangerous for humans. Working alongside the Venezuelan and Colombian Red Cross, Mexico's Topos rescue team, and volunteers from around the world, the CMU team aimed to improve the speed and safety of survivor searches.

Although the robots did not locate any survivors during the three-day mission, they played an important role by confirming that certain collapsed structures contained no trapped victims, allowing rescue teams to focus their efforts elsewhere and providing closure to waiting families. The deployment also highlighted both the promise and the practical challenges of using robotics in disaster response, including difficult terrain, equipment repairs, logistics, and communication barriers. The experience reinforced the potential of bio-inspired robotic systems as valuable tools that complement, rather than replace, human first responders during large-scale humanitarian emergencies.

More information:

https://www.cmu.edu/news/stories/archives/2026/july/snake-robots-support-earthquake-search-and-rescue-in-venezuela

Brain Implant Helps Paralysed Man Regain Independence

Researchers have developed a groundbreaking double neural bypass brain–computer interface that enabled a patient, who was paralysed from the chest down after a 2020 diving accident, to regain the ability to feed himself, drink from a cup, and perform everyday tasks independently. The system uses implanted brain electrodes to detect his intention to move, transmitting those signals directly to his arm and hand muscles while simultaneously sending sensory information back to the brain, allowing him to feel touch again. After 35 weeks of therapy, his arm strength improved dramatically, and he was able to handle delicate objects such as eggshells with remarkable precision.

Beyond restoring movement, the researchers found evidence that the technology may promote long-term healing of the nervous system rather than simply bypassing the spinal injury. By combining brain stimulation with sensory feedback and a technique called cortical mirroring, the patient regained sensation in areas that had been numb since his accident, with improvements persisting for more than two years after treatment. Although the results currently come from a single patient and larger clinical trials are still needed, the study represents a major advance in neuroprosthetics and offers new hope for millions of people living with paralysis.

More information:

https://www.theguardian.com/science/2026/jul/16/neural-bypass-brain-implant-paralysed-man-feed-himself-drink-from-cup

Cyprus Leads Europe's Virtual Worlds Skills Academy

Cyprus has taken on a leading role in advancing Europe's digital future through the Virtual Worlds Academy of Skills (ViWAS), a major European initiative coordinated by Prof. Fotis Liarokapis, Research Director at the CYENS CoE. Bringing together universities, research organisations, businesses, vocational education providers, and public-sector partners from across Europe, the academy aims to equip learners with the practical knowledge and skills required for emerging technologies such as extended reality (XR), artificial intelligence, digital twins, immersive design, cybersecurity, and digital creativity.

The initiative seeks to establish common European standards for virtual worlds education, making qualifications more interoperable while promoting flexible learning through practical training, short courses, and micro-credentials. Designed for a broad audience (including educators, healthcare professionals, engineers, artists, entrepreneurs, public servants, and lifelong learners) ViWAS emphasises inclusivity and accessibility, helping Europe address the growing demand for digital talent as immersive technologies become increasingly integrated into everyday life and professional practice.

More information:

https://en.politis.com.cy/life/1020289/cyprus-coordinates-europes-new-virtual-worlds-academy-for-digital-skills

Bird-Inspired Robot Swims and Flies

Researchers from MIT and EPFL have developed a lightweight flapping-wing robot inspired by diving birds such as puffins, petrels, and kingfishers that can both swim underwater and transition directly into flight. By studying the biomechanics of these birds, the team designed a robot with flexible wings, a steerable tail, and a waterproof body that can efficiently move through two vastly different environments. Experiments in water tanks and Lake Geneva showed that the robot could reliably swim, leap out of the water, and continue flying without requiring propellers, folding mechanisms, or paddling feet.

The breakthrough could enable a new generation of aerial-aquatic robots for environmental monitoring and ocean exploration. Unlike conventional drones or underwater vehicles, the robot could rapidly fly to remote locations, dive underwater to collect measurements or samples, and return with the data at a fraction of the cost of traditional methods. The researchers are now working to improve the robot's maneuverability and its ability to operate in rough water and windy conditions, with future applications including marine ecosystem monitoring, coastal surveillance, and climate research.

More information:

https://techxplore.com/news/2026-07-birdlike-robot-underwater-flight.html

Tiny Robot Boats Assemble Floating Structures

MIT researchers have developed FloatForm, a swarm of small autonomous robotic boats that can self-organise into floating structures such as bridges, platforms, or temporary workspaces. Inspired by the way fire ants link together to form rafts, each boat communicates only with its nearby neighbours rather than relying on a central controller. This decentralised approach allows the swarm to dynamically assemble, reconfigure, or repair structures even if individual robots fail or environmental conditions change. In laboratory demonstrations, groups of up to eight boats successfully formed a range of stable geometric configurations with a high success rate.

The researchers envision FloatForm as a flexible infrastructure solution for waterfront cities and disaster-response scenarios, where temporary floating structures can be deployed quickly without permanent construction. Potential applications include emergency bridges, floating markets, event stages, environmental monitoring platforms, and mobile sensor networks. By combining swarm intelligence with modular robotics, the system demonstrates how large-scale, adaptive infrastructure can emerge from the coordinated actions of many simple robots, opening new possibilities for resilient and responsive urban environments.

More information:

https://news.mit.edu/2026/tiny-robot-boats-build-floating-structures-0709

Cyborg Cockroach Swarms Go Underwater

Researchers from Nanyang Technological University in Singapore and Waseda University have developed remote-controlled cyborg cockroaches that can now operate underwater by wearing miniature 3D-printed diving suits. The lightweight system generates oxygen through a chemical reaction and delivers it directly to the insects' breathing openings, allowing them to survive and move underwater for up to three hours without impairing their natural mobility. The technology builds on previous work that enabled researchers to steer swarms of cockroaches remotely using tiny electronic implants.

The amphibious cyborg insects are designed to support search-and-rescue missions in environments inaccessible to conventional robots, such as flooded buildings, collapsed tunnels, drains, and other confined spaces. Because the insects rely on their own muscles for movement, they require far less energy than similarly sized robots while remaining highly agile. The research team also envisions future applications in infrastructure inspection and, eventually, exploration of extreme environments, including planetary missions where lightweight, energy-efficient biohybrid systems could offer significant advantages.

More information:

https://www.newscientist.com/article/2531894-remote-controlled-cockroach-swarm-can-now-breathe-underwater/

PaperTok Fights AI Slop

Researchers at the University of Washington have developed PaperTok, an AI-powered tool that helps scientists turn academic papers into engaging 45-second videos for platforms such as TikTok, YouTube Shorts, and Instagram Reels. Designed to combat misleading AI-generated science content ("AI slop"), the system keeps researchers in control by allowing them to review and refine AI-generated scripts before publication.

The developers argue that if scientists do not actively communicate their findings on popular social media platforms, inaccurate AI-generated summaries are likely to fill the gap. Early evaluations suggest that PaperTok can make research more accessible to non-specialist audiences while preserving scientific accuracy through researcher oversight. The team hopes it will encourage wider public engagement with credible scientific research.

More information:

https://www.geekwire.com/2026/short-form-science-university-of-washington-researchers-launch-papertok-to-combat-ai-slop/

Wearable Robotic Glove Restores Hand Function

Researchers from the Medical University of Vienna, working with collaborators from ETH Zurich, the Technical University of Munich, and the University of Belgrade, have developed a wearable neurorobotic system designed to restore hand function in people with severe neurological impairments. The system combines a lightweight robotic hand exoskeleton with functional electrical stimulation (FES), which activates weakened muscles through carefully timed electrical impulses. By synchronizing robotic assistance with the user's own muscle activity, the device enables more natural and coordinated grasping and finger movements than conventional rehabilitation approaches.

The researchers evaluated the system in individuals with spinal cord injuries and stroke-related hand paralysis, demonstrating significant improvements in performing everyday tasks such as grasping and manipulating objects. Unlike existing rehabilitation devices that often rely solely on robotics or electrical stimulation, the hybrid approach leverages the strengths of both technologies, promoting functional recovery while encouraging active patient participation. The team believes the wearable system could support both clinical rehabilitation and home-based therapy, offering a practical solution for improving independence and quality of life for people with impaired hand function.

More information:

https://www.news-medical.net/news/20260619/Scientists-develop-wearable-robotic-system-to-restore-hand-function.aspx

New Tool Detects AI Vision Hallucinations

Researchers at Los Alamos National Laboratory have developed a new tool called the Prelim Attention Score (PAS) to detect hallucinations in vision-language AI models, systems that combine image analysis with large language models. These models can sometimes generate descriptions of objects or details that are not actually present in an image. PAS works by monitoring how much the AI relies on the visual input versus its own previously generated text while producing a response, helping identify when the model is beginning to make things up.

The method operates in real time and can be integrated into existing vision-language models. By analyzing internal attention patterns, PAS provides a score indicating the likelihood of hallucination, allowing developers and users to assess the reliability of AI-generated outputs. The approach achieves state-of-the-art accuracy in detecting hallucinations and could improve the safety and trustworthiness of AI systems used in applications such as autonomous vehicles, healthcare imaging, robotics, and security monitoring.

More information:

https://interestingengineering.com/ai-robotics/us-tool-hallucinations-machine-vision-model