All posts by Artificial Intelligence News -- ScienceDaily

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New computer vision system can guide specialty crops monitoring

Soilless growing systems inside greenhouses, known as controlled environment agriculture, promise to advance the year-round production of high-quality specialty crops, according to an interdisciplinary research team. But to be competitive and sustainable, this advanced farming method will require the development and implementation of precision agriculture techniques. To meet that demand, the team developed an automated crop-monitoring system capable of providing continuous and frequent data about plant growth and needs, allowing for informed crop management.

Researchers unveil neuromorphic exposure control system to improve machine vision in extreme lighting environments

A research team has recently developed a groundbreaking neuromorphic exposure control (NEC) system that revolutionizes machine vision under extreme lighting variations. This biologically inspired system mimics human peripheral vision to achieve unprecedented speed and robustness in dynamic perception environments.

Researchers create the world’s smallest shooting video game using nanoscale technology

A research team demonstrated the 'world's smallest shooting game,' a unique nanoscale game inspired by classic arcade games. This achievement was made possible by real-time control of the force fields between nanoparticles using focused electron beams. This research has practical applications, as the manipulation of nanoscale objects could revolutionize biomedical engineering and nanotechnology.

AI generates playful, human-like games

A team of scientists has now created a computer model that can represent and generate human-like goals by learning from how people create games. The work could lead to AI systems that better understand human intentions and more faithfully model and align with our goals. It may also lead to AI systems that can help us design more human-like games.

AI unlocks the emotional language of animals

Groundbreaking study shows machine learning can decode emotions in seven ungulate species. A game-changer for animal welfare? Can artificial intelligence help us understand what animals feel? A pioneering study suggests the answer is yes. Researchers have successfully trained a machine-learning model to distinguish between positive and negative emotions in seven different ungulate species, including cows, pigs, and wild boars. By analyzing the acoustic patterns of their vocalizations, the model achieved an impressive accuracy of 89.49%, marking the first cross-species study to detect emotional valence using AI.

Like human brains, large language models reason about diverse data in a general way

Researchers find large language models process diverse types of data, like different languages, audio inputs, images, etc., similarly to how humans reason about complex problems. Like humans, LLMs integrate data inputs across modalities in a central hub that processes data in an input-type-agnostic fashion.

Groundbreaking study reveals how topology drives complexity in brain, climate, and AI

Researchers have unveiled a transformative framework for understanding complex systems. This pioneering study establishes the new field of higher-order topological dynamics, revealing how the hidden geometry of networks shapes everything from brain activity to the climate and artificial intelligence (AI).
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