Imagine you are in the middle of an unknown town. Even if your surroundings are initially unfamiliar, you can explore around and eventually create a mental map of your environment—where the buildings, streets, signs, and so on are in relation to one another. This ability to construct spatial maps in the brain is the basis of even more advanced types of cognition in humans: For example, it is theorized that language is encoded in a map-like structure in the brain.Imagine you are in the middle of an unknown town. Even if your surroundings are initially unfamiliar, you can explore around and eventually create a mental map of your environment—where the buildings, streets, signs, and so on are in relation to one another. This ability to construct spatial maps in the brain is the basis of even more advanced types of cognition in humans: For example, it is theorized that language is encoded in a map-like structure in the brain.[#item_full_content]

A study published in the journal PNAS Nexus reveals how social media algorithms favor politically sponsored content from certain parties given the same investment budget.A study published in the journal PNAS Nexus reveals how social media algorithms favor politically sponsored content from certain parties given the same investment budget.[#item_full_content]

How can a chatbot support students in lectures and with assigned exercises? Researchers at the Technical University of Munich (TUM) have developed the chatbot Iris, which offers informatics students personalized assistance with programming assignments.How can a chatbot support students in lectures and with assigned exercises? Researchers at the Technical University of Munich (TUM) have developed the chatbot Iris, which offers informatics students personalized assistance with programming assignments.[#item_full_content]

Dynamical systems describe the evolution of natural phenomena over time and space through mathematical frameworks, often using differential equations. Accurate predictions in these systems are crucial for various applications, yet traditional methods face challenges due to rigidity and complex dynamic behaviors.Dynamical systems describe the evolution of natural phenomena over time and space through mathematical frameworks, often using differential equations. Accurate predictions in these systems are crucial for various applications, yet traditional methods face challenges due to rigidity and complex dynamic behaviors.[#item_full_content]

Software is omnipresent in science, and yet it is overlooked everywhere. At a time when scientists (and many others) are talking about code, algorithms or artificial intelligence, software appears in the discourse as just another semantic subtlety. Many facets of software, such as questions about user licenses or file formats, are not part of the definition of code or algorithm.Software is omnipresent in science, and yet it is overlooked everywhere. At a time when scientists (and many others) are talking about code, algorithms or artificial intelligence, software appears in the discourse as just another semantic subtlety. Many facets of software, such as questions about user licenses or file formats, are not part of the definition of code or algorithm.[#item_full_content]

Humans can guess how someone on the other end of a phone call is feeling based on how they speak as well as what they say. Speech emotion recognition is the artificial intelligence version of this ability. Seeking to address the issue of channel alignment in downstream speech emotion recognition applications, a research group at East China Normal University in Shanghai developed a temporal shift module that outperforms state-of-the-art methods in fine-tuning and feature-extraction scenarios.Humans can guess how someone on the other end of a phone call is feeling based on how they speak as well as what they say. Speech emotion recognition is the artificial intelligence version of this ability. Seeking to address the issue of channel alignment in downstream speech emotion recognition applications, a research group at East China Normal University in Shanghai developed a temporal shift module that outperforms state-of-the-art methods in fine-tuning and feature-extraction scenarios.[#item_full_content]

A new camera could prevent companies from collecting embarrassing and identifiable photos and videos from devices like smart home cameras and robotic vacuums. It’s called PrivacyLens and was made by University of Michigan engineers.A new camera could prevent companies from collecting embarrassing and identifiable photos and videos from devices like smart home cameras and robotic vacuums. It’s called PrivacyLens and was made by University of Michigan engineers.[#item_full_content]

The emergence of so-called deepfake technology, which commonly involves the generation of fake images, video, and sound that seem so authentic as to confuse even expert viewers and listeners, is at the point where it can influence important aspects of our lives, such as politics, finance, and beyond.The emergence of so-called deepfake technology, which commonly involves the generation of fake images, video, and sound that seem so authentic as to confuse even expert viewers and listeners, is at the point where it can influence important aspects of our lives, such as politics, finance, and beyond.[#item_full_content]

A trio of computer scientists at Auburn University, in the U.S., working with a colleague from the University of Alberta, in Canada, has found that claims of visual skills by large language models (LLMs) with vision capabilities (VLMs) may be overstating abilities.A trio of computer scientists at Auburn University, in the U.S., working with a colleague from the University of Alberta, in Canada, has found that claims of visual skills by large language models (LLMs) with vision capabilities (VLMs) may be overstating abilities.[#item_full_content]

When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of large language models (LLMs) stems from their vast size, complex training methods, hard-to-predict behaviors, and elusive interpretability.When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of large language models (LLMs) stems from their vast size, complex training methods, hard-to-predict behaviors, and elusive interpretability.[#item_full_content]