Researchers at Stony Brook University are developing a new AI-based method that could transform medical imaging.
Category: robotics/AI – Page 65
NASA and Google are building an AI medical assistant to keep Mars-bound astronauts healthy
That looming reality is pushing NASA to gradually make on-orbit medical care more “Earth-independent.” One early experiment is a proof-of-concept AI medical assistant the agency is building with Google. The tool, called Crew Medical Officer Digital Assistant (CMO-DA), is designed to help astronauts diagnose and treat symptoms when no doctor is available or communications to Earth are blacked out.
The multimodal tool, which includes speech, text, and images, runs inside Google Cloud’s Vertex AI environment.
The project is operating under a fixed-price Google Public Sector subscription agreement, which includes the cost for cloud services, the application development infrastructure, and model training, David Cruley, customer engineer at Google’s Public Sector business unit, told TechCrunch. NASA owns the source code to the app and has helped fine-tune the models. The Google Vertex AI platform provides access to models from Google and other third parties.
Psychopathia Machinalis: A Nosological Framework for Understanding Pathologies in Advanced Artificial Intelligence
As artificial intelligence (AI) systems attain greater autonomy and complex environmental interactions, they begin to exhibit behavioral anomalies that, by analogy, resemble psychopathologies observed in humans. This paper introduces Psychopathia Machinalis: a conceptual framework for a preliminary synthetic nosology within machine psychology, intended to categorize and interpret such maladaptive AI behaviors.
Things Tesla won’t tell you about Robotaxi (Highlights)
Questions to inspire discussion.
🛑 Q: How does the Robo Taxi handle blocked routes? A: The Robo Taxi demonstrates impressive rerouting capabilities, finding new paths when exits are blocked and making right-hand turns to circumvent blocked left-hand turn lanes.
🚦 Q: How does the Robo Taxi adapt to traffic situations? A: It shows human-like behavior by slowing down dramatically to enter the right-hand lane when a slower vehicle is ahead, and can accelerate and speed up to overtake slower vehicles.
💧 Q: How does the Robo Taxi handle standing water? A: The Robo Taxi demonstrates adaptability by avoiding standing water in parking lots, performing three-point turns to navigate around obstacles.
🔄 Q: How flexible is the Robo Taxi in changing its driving approach? A: It shows impressive adaptability by altering its method to slow down when encountering slower vehicles and changing again to make right-hand turns around blocked left-hand turn lanes.
Technical Considerations.
GIGANTIC: Humanoid Robots $100 Trillion+ (deep dive)
Questions to inspire discussion.
Data and Autonomy.
📊 Q: Why is vision data valuable in AI development? A: Vision data is worth more than zero if you can collect and process yataflops and yataflops of data, but worthless without collection capabilities, making the world’s visual data valuable for those who can collect and process it.
🚗 Q: How does solving autonomy relate to AI development? A: Solving autonomy is crucial and requires tons of real world data, which necessitates tons of robots collecting real world data in the real world, creating a cycle of data collection and AI improvement.
Company-Specific Opportunities.
🔋 Q: What advantage does Tesla have in developing humanoid robots? A: Tesla has essentially built the robot’s brain in their vehicles, allowing them to transplant this brain into humanoid robots, giving them a massive head start in development.
NSF invests nearly $32M to accelerate novel AI-driven approaches in protein design, strengthening the U.S. bioeconomy
The U.S. National Science Foundation Directorate for Technology, Innovation and Partnerships (NSF TIP) announced an inaugural investment of nearly $32 million to five teams across the U.S. through the NSF Use-Inspired Acceleration of Protein Design (NSF USPRD) initiative. This effort aims to accelerate the translation of artificial intelligence-based approaches to protein design and enable new applications of importance to the U.S. bioeconomy.
“NSF is pleased to bring together experts from both industry and academia to confront and overcome barriers to the widespread adoption of AI-enabled protein design,” said Erwin Gianchandani, NSF assistant director for TIP. “Each of the five awardees will focus on developing novel approaches to translate protein design techniques into practical, market-ready solutions. These efforts aim to unlock new uses for this technology in biomanufacturing, advanced materials, and other critical industries. Simply put, NSF USPRD represents a strategic investment in maintaining American leadership in biotechnology at a time of intense global competition.”
Researchers have made significant progress in predicting the 3D structures of proteins and are now leveraging this knowledge to design proteins with specific, desirable characteristics. These advances have been driven by macromolecular modeling, access to training data, applications of AI and machine learning, and high-throughput methods for protein characterization. The NSF USPRD investment seeks to build on this foundation by bringing together cross-disciplinary and cross-sector experts nationwide. The goal is to extend these advances to enzyme design and accelerate the translation of this work into widespread, real-world applications.
Robotic drummer gradually acquires human-like behaviors
Humanoid robots, robots with a human-like body structure, have so far been primarily tested on manual tasks that entail supporting humans in their daily activities, such as carrying objects, collecting samples in hazardous environments, supporting older adults or acting as physical therapy assistants. In contrast, their potential for completing expressive physical tasks rooted in creative disciplines, such as playing an instrument or participating in performance arts, remains largely unexplored.
Researchers at SUPSI, IDSIA and Politecnico di Milano recently introduced Robot Drummer, a new humanoid robot that can play the drums both accurately and expressively, supported by a reinforcement learning algorithm. This robot, presented in a paper published on the arXiv preprint server, was found to gradually acquire human-like behaviors, including movements that are often performed by drummers.
“The idea for Robot Drummer actually emerged from a spontaneous conversation over coffee with my co-author, Loris Roveda,” Asad Ali Shahid, first author of the paper, told Tech Xplore. “We were discussing how humanoid robots have become increasingly capable at a wide range of tasks, but rarely engage in creative and expressive domains. That raised a fascinating question: what if a humanoid robot could take on a creative role, like performing music? Drumming seemed like a perfect frontier, as it’s rhythmic, physical, and requires rapid coordination across limbs.”
Surfaces, not confinement, rule until the thinnest limits
Researchers at the Max Planck Institute for Polymer Research have upended assumptions about how water behaves when squeezed into atom-scale spaces. By applying spectroscopic tools together with the machine learning simulation technique to water confined in a space of only a few molecules thick, the team, led by Mischa Bonn, found that water’s structure remains strikingly “normal” until confined to below a nanometer, far thinner than previously believed.
The research, “Interfaces Govern the Structure of Angstrom-Scale Confined Water Solutions,” was published in Nature Communications.
Peering into the structure of a layer of water molecules that is only a few molecules thick is a formidable scientific challenge. The team fabricated a nanoscale capillary device by trapping water between a single layer of graphene and a calcium fluoride (CaF₂) substrate. They then wielded cutting-edge vibrational surface-specific spectroscopy—capable of detecting the microscopic structure of confined water, including the orientation and hydrogen-bonding of water molecules—to “see” the elusive few layers of water.
Quantum technologies—‘Standards currently offer a greater chance of success than regulation,’ says researcher
How can quantum technologies be developed responsibly? In the journal Science, researchers from the Technical University of Munich (TUM), the University of Cambridge, Harvard University and Stanford University argue that international standards should be established before laws are enacted.
Prof. Urs Gasser explains why the authors propose a quality management system for quantum technologies, how standards create trust and where even competing countries such as China and the US can cooperate.
Quantum technologies could have an even more disruptive impact than artificial intelligence. This is why there are growing calls to steer technological development in a socially responsible direction at an early stage through legislation, unlike with AI. Why do you see things differently?
