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Categories: Computer Science: Artificial Intelligence (AI), Mathematics: Modeling

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A new study finds that clinicians were fooled by biased AI models, even with provided explanations for how the model generated its diagnosis.

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An interdisciplinary team consisting of researchers has revealed a striking similarity between the memory processing of artificial intelligence (AI) models and the hippocampus of the human brain. This new finding provides a novel perspective on memory consolidation, which is a process that transforms short-term memories into long-term ones, in AI systems.

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Artificial intelligence can analyze registry data on people's residence, education, income, health and working conditions and, with high accuracy, predict life events.

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Researchers developed a way to quickly calculate the transition state structure of a chemical reaction, using machine-learning models.

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In the largest study yet of deep neural networks trained to perform auditory tasks, researchers found most of these models generate internal representations that share properties of representations seen in the human brain when people are listening to the same sounds.

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Artificial intelligence (AI) systems are often depicted as sentient agents poised to overshadow the human mind. But AI lacks the crucial human ability of innovation, researchers have found.

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Physician-investigators compared a chatbot's probabilistic reasoning to that of human clinicians. The findings suggest that artificial intelligence could serve as useful clinical decision support tools for physicians.

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ChatGPT may do an impressive job at correctly answering complex questions, but a new study suggests it may be absurdly easy to convince the AI chatbot that it's in the wrong.

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A joint research team in computer science, economics, and geography has developed an artificial intelligence (AI) technology to measure grid-level economic development within six-square-kilometer regions. This AI technology is applicable in regions with limited statistical data (e.g., North Korea), supporting international efforts to propose policies for economic growth and poverty reduction in underdeveloped countries. The research team plans to make this technology freely available for use to contribute to the United Nations' Sustainable Development Goals (SDGs).

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Seeing robots made with soft, flexible parts in action appears to lower people's anxiety about working with them or even being replaced by them. A study found that watching videos of a soft robot working with a person at picking and placing tasks lowered the viewers' safety concerns and feelings of job insecurity. This was true even when the soft robot was shown working in close proximity to the person. This finding shows soft robots hold a potential psychological advantage over rigid robots made of metal or other hard materials.

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Artificial intelligence tools hold promise for applications ranging from autonomous vehicles to the interpretation of medical images. However, a new study finds these AI tools are more vulnerable than previously thought to targeted attacks that effectively force AI systems to make bad decisions.

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Mathematics, histopathology and genomics converge to confirm that the most aggressive clear cell renal cell carcinomas display low levels of intratumour heterogeneity, i.e. they contain fewer distinct cell types. The study supports the hypothesis that it would be advisable to apply therapeutic strategies to maintain high levels of cellular heterogeneity within the tumour in order to slow down the evolution of the cancer and improve human survival.  

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In a step toward more autonomous soft robots and wearable technologies, researchers have created a device that uses color to simultaneously sense multiple mechanical and temperature stimuli.

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Electronic nanomaterials experts have imagined how recent advances in artificial intelligence (AI) and machine learning (ML) could aid scientific brainstorming and ideation. To accomplish this, they have developed a chatbot with knowledge in the kinds of science he's been engaged in.

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Researchers have demonstrated the use of AI-selected natural images and AI-generated synthetic images as neuroscientific tools for probing the visual processing areas of the brain. The goal is to apply a data-driven approach to understand how vision is organized while potentially removing biases that may arise when looking at responses to a more limited set of researcher-selected images.

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Researchers demonstrated monolithic 3D integration of layered 2D material into novel processing hardware for artificial intelligence computing. The new approach provides a material-level solution for fully integrating many functions into a single, small electronic chip -- and paves the way for advanced AI computing. 

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Engineers have come up with a new way to teach robots to know when they don't know. The technique involves quantifying the fuzziness of human language and using that measurement to tell robots when to ask for further directions. Telling a robot to pick up a bowl from a table with only one bowl is fairly clear. But telling a robot to pick up a bowl when there are five bowls on the table generates a much higher degree of uncertainty -- and triggers the robot to ask for clarification.

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Researchers report that they have developed a new composite material designed to change behaviors depending on temperature in order to perform specific tasks. These materials are poised to be part of the next generation of autonomous robotics that will interact with the environment.

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Computer scientists have developed AntiFake, a tool to protect voice recordings from unauthorized speech synthesis.

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A new technique enables an AI agent to be guided by data crowdsourced asynchronously from nonexpert human users as it learns to complete a task through reinforcement learning. The method trains the robot faster and better than other approaches.