Deep learning models, such as those used in medical imaging to help detect disease or abnormalities, must be trained with a lot of data. However, often there isn’t enough data available to train these models, or the data is too diverse.Deep learning models, such as those used in medical imaging to help detect disease or abnormalities, must be trained with a lot of data. However, often there isn’t enough data available to train these models, or the data is too diverse.Machine learning & AI[#item_full_content]

Engineering researchers at the University of Minnesota Twin Cities have demonstrated a state-of-the-art hardware device that could reduce energy consumption for artificial intelligent (AI) computing applications by a factor of at least 1,000.Engineering researchers at the University of Minnesota Twin Cities have demonstrated a state-of-the-art hardware device that could reduce energy consumption for artificial intelligent (AI) computing applications by a factor of at least 1,000.Hardware[#item_full_content]

A team of computer scientists and roboticists with members from Texas A&M University in the U.S., and the Mohamed Bin Zayed University of Artificial Intelligence in Abu Dhabi, working with a colleague from Boston Dynamics, has configured a robot made by Boston Dynamics to seek out and stun weeds using a small blowtorch. The team has posted a paper describing their efforts to the arXiv preprint server.A team of computer scientists and roboticists with members from Texas A&M University in the U.S., and the Mohamed Bin Zayed University of Artificial Intelligence in Abu Dhabi, working with a colleague from Boston Dynamics, has configured a robot made by Boston Dynamics to seek out and stun weeds using a small blowtorch. The team has posted a paper describing their efforts to the arXiv preprint server.Robotics[#item_full_content]

Designing the spatial arrangement of underground powerhouses involves numerous complex parameters and boundaries, requiring frequent reference to various cases and specifications. Traditional methods struggle to efficiently retrieve this information, leading to suboptimal designs and extended project timelines. Due to these challenges, there is a pressing need for a more intelligent and efficient approach to streamline the design process, enhance accuracy, and improve project management in hydropower engineering.Designing the spatial arrangement of underground powerhouses involves numerous complex parameters and boundaries, requiring frequent reference to various cases and specifications. Traditional methods struggle to efficiently retrieve this information, leading to suboptimal designs and extended project timelines. Due to these challenges, there is a pressing need for a more intelligent and efficient approach to streamline the design process, enhance accuracy, and improve project management in hydropower engineering.Engineering[#item_full_content]

Using AI-generated datasets to train future generations of machine learning models may pollute their output, a concept known as model collapse, according to a new paper published in Nature. The research shows that within a few generations, original content is replaced by unrelated nonsense, demonstrating the importance of using reliable data to train AI models.Using AI-generated datasets to train future generations of machine learning models may pollute their output, a concept known as model collapse, according to a new paper published in Nature. The research shows that within a few generations, original content is replaced by unrelated nonsense, demonstrating the importance of using reliable data to train AI models.Machine learning & AI[#item_full_content]

Self-driving cars occasionally crash because their visual systems can’t always process static or slow-moving objects in 3D space. In that regard, they’re like the monocular vision of many insects, whose compound eyes provide great motion-tracking and a wide field of view but poor depth perception.Self-driving cars occasionally crash because their visual systems can’t always process static or slow-moving objects in 3D space. In that regard, they’re like the monocular vision of many insects, whose compound eyes provide great motion-tracking and a wide field of view but poor depth perception.Robotics[#item_full_content]

Many decisions that were previously made by humans will be left to machines in the future. But can we really rely on the decisions made by artificial intelligence? In sensitive areas, people would like a guarantee that the decision is actually sensible, or at least that certain serious errors have been ruled out.Many decisions that were previously made by humans will be left to machines in the future. But can we really rely on the decisions made by artificial intelligence? In sensitive areas, people would like a guarantee that the decision is actually sensible, or at least that certain serious errors have been ruled out.Machine learning & AI[#item_full_content]

Humans are interacting more than ever with artificial intelligence (AI)—from the development of the first “social robots” (a robot with a physical body programmed to interact and engage with humans) like Kismet in the 1990s to smart speakers such as Amazon’s Alexa.Humans are interacting more than ever with artificial intelligence (AI)—from the development of the first “social robots” (a robot with a physical body programmed to interact and engage with humans) like Kismet in the 1990s to smart speakers such as Amazon’s Alexa.Robotics[#item_full_content]

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