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Categories: Computer Science: General, Mathematics: General

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Have you ever wished you could understand what your dog is trying to say to you? Researchers are exploring the possibilities of AI, developing tools that can identify whether a dog's bark conveys playfulness or aggression.

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Researchers have developed a model that enables computers to interpret and understand human emotions, utilizing principles of mathematical psychology. In the future, the model can help the computer to adapt its own behavior and guide an irritated or anxious user in different ways. The implications of such technology are profound, offering a glimpse into a future where computers are not merely tools, but empathetic partners in user interaction.

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Researchers have developed a platform for the interactive evaluation of AI-powered chatbots such as ChatGPT. A team of computer scientists, engineers, mathematicians and cognitive scientists developed an open-source evaluation platform called CheckMate, which allows human users to interact with and evaluate the performance of large language models (LLMs).

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A team used experiments and simulations to quantify and predict how knit fabric response can be programmed. By establishing a mathematical theory of knitted materials, the researchers hope that knitting -- and textiles in general -- can be incorporated into more engineering and manufacturing applications.

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Biological processes depend on puzzle pieces coming together and interacting. Under specific conditions, these interactions can create something new without external input. This is called self-organization, as seen in a school of fish or a flock of birds. Interestingly, the mammalian embryo develops similarly. Scientists now introduce a mathematical framework that analyzes self-organization from a single cell to a multicellular organism.

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An international research team has sparked interest in the scientific community with results in quantum physics. In their current study, the researchers reinterpret the Higgs mechanism, which gives elementary particles mass and triggers phase transitions, using the concept of 'magnetic quivers.'

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A novel, human-inspired approach to training artificial intelligence (AI) systems to identify objects and navigate their surroundings could set the stage for the development of more advanced AI systems to explore extreme environments or distant worlds, according to new research.

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MRI scans are commonly used to diagnose a variety of conditions, anything from liver disease to brain tumors. But, as anyone who has been through one knows, patients must remain completely still to avoid blurring the images and requiring a new scan. A prototype device could change that. The self-powered sensor detects movement and shuts down an MRI scan in real time, improving the process for patients and technicians.

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As more and more people drive electric cars, congestion and queues can occur when many people need to charge at the same time. A new study shows how AI-controlled charging stations, through smart algorithms, can offer electric vehicle users personalized prices, and thus minimize both price and waiting time for customers. But the researchers point to the importance of taking the ethical issues seriously, as there is a risk that the artificial intelligence exploits information from motorists.

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A team of researchers have developed a new machine-learning method that detects hate speech on social media platforms with 88 per cent accuracy, saving employees from hundreds of hours of emotionally damaging work.

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Image privacy could be protected with the use of generative artificial intelligence. Researchers created a system which replaces parts of images that might threaten confidentiality with visually similar but AI-generated alternatives. Named 'generative content replacement,' in tests, 60% of viewers couldn't tell which images had been altered. The researchers intend for this system to provide a more visually cohesive option for image censoring, which helps to preserve the narrative of the image while protecting privacy.

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Researchers recently published findings that could lay the groundwork for applying quantum computing methods to protein structure prediction.

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Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials science and more.

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Researchers demonstrated a scalable, modular hardware platform that integrates thousands of interconnected qubits onto a customized integrated circuit. This 'quantum-system-on-chip' (QSoC) architecture enables them to precisely tune and control a dense array of qubits.

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Artificial intelligence (AI) combined with a novel bio-inspired camera achieves 100 times faster detection of pedestrians and obstacles than current automotive cameras. This important step for computer vision and AI and can greatly improve the safety of automotive systems and self-driving cars.

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Researchers have developed an assistive machine learning model that greatly improves the ability of medical professionals to read the electroencephalography (EEG) charts of intensive care patients. Because EEG readings are the only method for knowing when unconscious patients are in danger of suffering a seizure or are having seizure-like events, the computational tool could help save thousands of lives each year.

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Researchers developed a computer vision framework for posture estimation and identity tracking which they can use in indoor environments as well as in the wild. They have thus taken an important step towards markerless tracking of animals in the wild using computer vision and machine learning.

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Engineers have developed an artificial intelligence system that lets someone wearing headphones look at a person speaking for three to five seconds to 'enroll' them. The system then plays just the enrolled speaker's voice in real time, even as the pair move around in noisy environments.

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Scientists describe a new method to make very thin crystals of the element bismuth -- a process that may aid the manufacturing of cheap flexible electronics an everyday reality.

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Researchers have unveiled a novel method to prepare quantum operations on a given quantum computer, using a machine learning generative model to find the appropriate sequence of quantum gates to execute a quantum operation. The study marks a significant step forward in unleashing the full extent of quantum computing.