OpenAI on Thursday said it was putting its artificial intelligence engine to work in a challenge to Google’s market-dominating search engine.OpenAI on Thursday said it was putting its artificial intelligence engine to work in a challenge to Google’s market-dominating search engine.Internet[#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]
The internet, a vast and indispensable resource for modern society, has a darker side where malicious activities thrive.The internet, a vast and indispensable resource for modern society, has a darker side where malicious activities thrive.Security[#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]
Organizations are increasingly utilizing machine-learning models to allocate scarce resources or opportunities. For instance, such models can help companies screen resumes to choose job interview candidates or aid hospitals in ranking kidney transplant patients based on their likelihood of survival.Organizations are increasingly utilizing machine-learning models to allocate scarce resources or opportunities. For instance, such models can help companies screen resumes to choose job interview candidates or aid hospitals in ranking kidney transplant patients based on their likelihood of survival.Computer Sciences[#item_full_content]
Most robotic systems developed to date can either tackle a specific task with high precision or complete a range of simpler tasks with low precision. For instance, some industrial robots can complete specific manufacturing tasks very well but cannot easily adapt to new tasks. On the other hand, flexible robots designed to handle a variety of objects often lack the accuracy necessary to be deployed in practical settings.Most robotic systems developed to date can either tackle a specific task with high precision or complete a range of simpler tasks with low precision. For instance, some industrial robots can complete specific manufacturing tasks very well but cannot easily adapt to new tasks. On the other hand, flexible robots designed to handle a variety of objects often lack the accuracy necessary to be deployed in practical settings.Robotics[#item_full_content]
Los Alamos National Laboratory scientists are developing powerful machine learning models—an application of artificial intelligence—to simulate underground hydrogen storage operations under various cushion gas scenarios. This will play a vital role in the low-carbon economy of the future.Los Alamos National Laboratory scientists are developing powerful machine learning models—an application of artificial intelligence—to simulate underground hydrogen storage operations under various cushion gas scenarios. This will play a vital role in the low-carbon economy of the future.Energy & Green Tech[#item_full_content]
