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Category: robotics/AI – Page 179

The Role of AI in medical learning: How chatbots and digital assistants are reshaping education

Artificial Intelligence (AI) is revolutionizing industries globally, and medical education is no exception. For a nation like India, where the healthcare system faces immense pressure, AI integration in medical learning is more than a convenience, it’s a necessity. AI-powered tools offer medical students transformative benefits: personalized learning pathways that adapt to individual knowledge gaps, advanced clinical simulation platforms for risk-free practice, intelligent tutoring systems that provide immediate feedback, and sophisticated diagnostic training algorithms that enhance clinical reasoning skills. From offering personalized guidance to transforming clinical training, chatbots and digital assistants are redefining how future healthcare professionals prepare for their complex and demanding roles, enabling more efficient, interactive, and comprehensive medical education.

Personalized learning One of AI’s greatest contributions to medical education is its ability to create and extend personalized learning experiences. Conventional methods, on the other hand, often utilize a one-size-fits-all approach, leaving students to fend for themselves when they struggle. AI has the power to change this by analyzing a student’s performance and crafting study plans tailored to their strengths and weaknesses. This means students can focus on areas where they need the most help, saving time and effort.

Mouse model unveils dynamics through which SYNGAP1 gene supports cognitive function

The SYNGAP1 gene, which supports the production of a protein called SynGAP (Synaptic Ras GTPase-Activating Protein), is known to play a key role in supporting the development of synapses and neural circuits (i.e., connections between neurons). Mutations in this gene have been linked to various learning disabilities, including intellectual disabilities, speech and language delays, autism spectrum disorder (ASD), and epilepsy.

Researchers at the Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology recently carried out a study aimed at better understanding the via which the SYNGAP1 gene contributes to healthy cognitive function. Their findings, published in Nature Communications, suggest that the autonomous expression of this gene in the cortical excitatory neurons of mice promotes the animals’ cognitive abilities via the assembly of long-range integrating sensory and motor information.

“Our paper builds on our ongoing research into how major risk genes for mental health disorders, including autism, regulate brain organization and function,” Gavin Rumbaugh, senior author of the paper, told Medical Xpress. “The field knows the major risk genes that directly contribute to cognitive and behavioral impairments that lead to diagnosable forms of autism and related neuropsychiatric disorders in humans.

What’s Best, According to the Italian Mathematician Alessio Figalli

The words “optimal” and “optimize” derive from the Latin “optimus,” or “best,” as in “make the best of things.” Alessio Figalli, a mathematician at the university ETH Zurich, studies optimal transport: the most efficient allocation of starting points to end points. The scope of investigation is wide, including clouds, crystals, bubbles and chatbots.

Dr. Figalli, who was awarded the Fields Medal in math that is motivated by concrete problems found in nature. He also likes the discipline’s “sense of eternity,” he said in a recent interview. “It is something that will be here forever.” (Nothing is forever, he conceded, but math will be around for “long enough.”) “I like the fact that if you prove a theorem, you prove it,” he said. “There’s no ambiguity, it’s true or false. In a hundred years, you can rely on it, no matter what.”

The study of optimal transport was introduced almost 250 years ago by Gaspard Monge, a French mathematician and politician who was motivated by problems in military engineering. His ideas found broader application solving logistical problems during the Napoleonic Era — for instance, identifying the most efficient way to build fortifications, in order to minimize the costs of transporting materials across Europe.

AI model generates antimicrobial peptide structures for screening against treatment-resistant microbes

A team of microbiologists, chemists and pharmaceutical specialists at Shandong University, Guangzhou Medical University, Second Military Medical University and Qingdao University, all in China, has developed an AI model that generates antimicrobial peptide structures for screening against treatment-resistant microbes.

In their study published in the journal Science Advances, the group developed a compression method to reduce the number of elements needed in training data for an AI system, which helped to reduce diversification issues with current AI models.

Prior research has suggested that drug-resistant microbes are one of the most pressing problems in medical science. Researchers around the world have been looking for new ways to treat people infected with such microbes—one approach involves developing , which work by targeting bacterial membranes.

Brewing The Perfect Cup Of Coffee With AI | Tech It Out | WION

A cafe in Finland has created an AI-coffee blend. From bean selection to packaging design, watch this report to see how the future of coffee is brewing.

#techitout #technology #tech.

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We are Almost at the End of History | Technological Singularity

Curious about the societal shifts that AGI will bring, like Universal Basic Income or new forms of coexistence between humans and machines?

Want insights that help you make sense of this rapidly approaching future?
Join us for a journey through the challenges and opportunities of living alongside AGI.

With each video, we aim to inform, inspire, and ignite a conversation to ensure we’re all ready for the world that’s unfolding.

Videos used:

The Future of Electronic Warfare: AI, Swarms, and Cyber Integration

In this video, we delve into The Future of Electronic Warfare, exploring how advancements in AI, drone swarms, and cyber integration are reshaping military strategies. Historically, electronic warfare (EW) began with basic communication interception in World War I and evolved through World War II with techniques like radar jamming. Today, we stand at the brink of a new era where technology significantly enhances operational capabilities.

The Evolution of Drone Swarms.

Recent developments have seen the emergence of AI-powered drone swarms, which offer unprecedented adaptability and efficiency on the battlefield. For instance, Thales’s COHESION demonstrator showcases how these swarms can operate autonomously, reducing the cognitive load on human operators while maintaining control during critical mission phases. Unlike traditional systems that require one operator per drone, these advanced systems leverage AI to allow multiple drones to work collaboratively, enhancing surveillance and attack capabilities across vast terrains.

Key features of ai-powered drone swarms.

Wide-Area Surveillance: Swarms can cover extensive areas, providing comprehensive monitoring and real-time situational awareness, ensuring no part of the terrain goes unmonitored.

Decentralized Coordination: Each drone operates autonomously while contributing to a collective intelligence network, allowing for effective mission execution even if individual drones are lost.

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Helios Presents Cognitive Software Algorithms Techniques for Electronic Warfare at NAVSEA FST

Breyt Coakley, Principal Investigator at Helios Remote Sensing Systems, Inc. discusses Cognitive Software Algorithms Techniques for Electronic Warfare. Helios is developing machine learning algorithms to detect agile emitters, not yet in Signal Intelligence (SIGINT) databases, without fragmentation. Traditional deinterleaving fragments these emitters into multiple unknown emitters, or even worse misidentifies them as matching multiple incorrect SIGINT database entries.