The healthcare industry faces a significant shift towards digital health technology, with a growing demand for real-time and continuous health monitoring and disease diagnostics [1, 2, 3]. The rising prevalence of chronic diseases, such as diabetes, heart disease, and cancer, coupled with an aging population, has increased the need for remote and continuous health monitoring [4, 5, 6, 7]. This has led to the emergence of artificial intelligence (AI)-based wearable sensors that can collect, analyze, and transmit real-time health data to healthcare providers so that they can make efficient decisions based on patient data. Therefore, wearable sensors have become increasingly popular due to their ability to provide a non-invasive and convenient means of monitoring patient health. These wearable sensors can track various health parameters, such as heart rate, blood pressure, oxygen saturation, skin temperature, physical activity levels, sleep patterns, and biochemical markers, such as glucose, cortisol, lactates, electrolytes, and pH and environmental parameters [1, 8, 9, 10]. Wearable health technology includes first-generation wearable technologies, such as fitness trackers, smartwatches, and current wearable sensors, and is a powerful tool in addressing healthcare challenges [2].
The data collected by wearable sensors can be analyzed using machine learning (ML) and AI algorithms to provide insights into an individual’s health status, enabling early detection of health issues and the provision of personalized healthcare [6,11]. One of the most significant advantages of AI-based wearable health technology is to promote preventive healthcare. This enables individuals and healthcare providers to proactively address symptomatic conditions before they become more severe [12,13,14,15]. Wearable devices can also encourage healthy behavior by providing incentives, reminders, and feedback to individuals, such as staying active, hydrating, eating healthily, and maintaining a healthy lifestyle by measuring hydration biomarkers and nutrients.
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In Huang’s vision of AI’s future, these models require more computing power from chips, not less.
Scientists are developing ever-more powerful magnets to enable clean energy sources like fusion. But China’s dominance of the supply chain for rare-earth magnets threatens their global availability.
Bloomberg Primer cuts through the complex jargon to reveal the business behind technologies poised to transform global markets. This six-part, planet-spanning series offers a comprehensive look at the \.
Which of these technologies excites you the most? CHAPTERS:00:00 20 Space Megastructures That Will Transform Our Future01:15:51 15 Robotics TechnologiesThat…
NVIDIA has just unveiled the Isaac GR00T N1, a foundation model that is revolutionizing humanoid robotics. This AI-driven system can learn tasks, make decisions, and adapt like never before!
At GTC 2025, NVIDIA CEO Jensen Huang revealed the Isaac GR00T N1, a next-generation AI model designed to train humanoid robots with unprecedented efficiency. It uses a dual-system approach—one for instant reactions and another for strategic thinking. NVIDIA also introduced Newton, a physics engine developed in collaboration with Google DeepMind and Disney, aiming to enhance robotic motion.
Additionally, NVIDIA’s Isaac GR00T Blueprint enables large-scale training with synthetic data. In just 11 hours, the system generated over 780,000 training examples, drastically improving robot accuracy. These advancements could reshape industries by making humanoid robots more intelligent and useful in real-world applications.
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This video takes a look at how future technology could change the Fermi Paradox. Asking if humanity is looking for life in the Universe in the wrong ways, or are we looking for the wrong things. Like trying to find smoke signals, in the age of fiber optics.
While the Drake Equation estimates how many civilizations could exist in the Universe, but what is the likelihood that humanity is even capable of detecting them.
Does there need to be another calculation, say the Detection Probability Equation. Showing what’s the likelihood that humanity is able to detect alien life at a given time, and solving the Fermi Paradox.
And does this create a new paradox. Because if future technology advancements increase the number of possible cosmic civilizations, could it also decrease humanity’s ability in detecting them — leading to the detection paradox.
Other topics covered in this sci-fi documentary video include: space telescopes, dyson spheres, the movie Contact by Carl Sagan, Interstellar movie and the time dilation effects, the great silence, the great filter, and solutions and theories for the Fermi Paradox.
PATREON
Could gravitational waves—the ripples in space-time—also be quantum in nature? Scientists believe they might! A new study suggests gravitational waves could induce quantum entanglement, revolutionizing physics and reshaping our understanding of gravity. But detecting these effects requires cutting-edge technology. Will future observatories like LIGO-India unlock the quantum secrets of space-time? Dive into this fascinating discovery and explore the possibilities of a quantum universe! Watch now and join the discussion!
Paper link: https://www.sciencedirect.com/science… 00:00 Introduction 00:29 The Quantum Nature of Gravitational Waves – A Theoretical Breakthrough 02:21 The Research Behind the Discovery 04:13 Implications and the Future of Quantum Gravitational Wave Research 07:30 Outro 07:43 Enjoy MUSIC TITLE : Starlight Harmonies MUSIC LINK : https://pixabay.com/music/pulses-star… Visit our website for up-to-the-minute updates: www.nasaspacenews.com Follow us Facebook: / nasaspacenews Twitter:
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For decades, scientists assumed that the expansion of the universe was powered by a new entity, known as the inflaton, but new research suggests that it may have been possible without it.