Imagine you read a book. You commit details of the book to memory and ruminate on the ideas contained in it.Imagine you read a book. You commit details of the book to memory and ruminate on the ideas contained in it.Business[#item_full_content]
The public release of AI text generators, such as ChatGPT, has caused an enormous stir among both those who herald the technology as a great leap forward in communication as well as those who prophesy the technology’s dire effects. However, AI-generated text is notoriously buggy, and human evaluation remains the gold-standard in ensuring accuracy, especially when it comes to applications such as generating long-form summaries of complex texts. And yet, there are no accepted standards for human evaluation of long-form summaries, which means that even the gold-standard is suspect.The public release of AI text generators, such as ChatGPT, has caused an enormous stir among both those who herald the technology as a great leap forward in communication as well as those who prophesy the technology’s dire effects. However, AI-generated text is notoriously buggy, and human evaluation remains the gold-standard in ensuring accuracy, especially when it comes to applications such as generating long-form summaries of complex texts. And yet, there are no accepted standards for human evaluation of long-form summaries, which means that even the gold-standard is suspect.[#item_full_content]
The public release of AI text generators, such as ChatGPT, has caused an enormous stir among both those who herald the technology as a great leap forward in communication as well as those who prophesy the technology’s dire effects. However, AI-generated text is notoriously buggy, and human evaluation remains the gold-standard in ensuring accuracy, especially when it comes to applications such as generating long-form summaries of complex texts. And yet, there are no accepted standards for human evaluation of long-form summaries, which means that even the gold-standard is suspect.The public release of AI text generators, such as ChatGPT, has caused an enormous stir among both those who herald the technology as a great leap forward in communication as well as those who prophesy the technology’s dire effects. However, AI-generated text is notoriously buggy, and human evaluation remains the gold-standard in ensuring accuracy, especially when it comes to applications such as generating long-form summaries of complex texts. And yet, there are no accepted standards for human evaluation of long-form summaries, which means that even the gold-standard is suspect.Computer Sciences[#item_full_content]
Is it possible to build machine-learning models without machine-learning expertise?Is it possible to build machine-learning models without machine-learning expertise?Machine learning & AI[#item_full_content]
A panel of AI-enabled humanoid robots took the microphone Friday at a United Nations conference with the message: they could eventually run the world better than humans.A panel of AI-enabled humanoid robots took the microphone Friday at a United Nations conference with the message: they could eventually run the world better than humans.Robotics[#item_full_content]
Reservoir computing is a promising computational framework based on recurrent neural networks (RNNs), which essentially maps input data onto a high-dimensional computational space, keeping some parameters of artificial neural networks (ANNs) fixed while updating others. This framework could help to improve the performance of machine learning algorithms, while also reducing the amount of data required to adequately train them.Reservoir computing is a promising computational framework based on recurrent neural networks (RNNs), which essentially maps input data onto a high-dimensional computational space, keeping some parameters of artificial neural networks (ANNs) fixed while updating others. This framework could help to improve the performance of machine learning algorithms, while also reducing the amount of data required to adequately train them.[#item_full_content]
Reservoir computing is a promising computational framework based on recurrent neural networks (RNNs), which essentially maps input data onto a high-dimensional computational space, keeping some parameters of artificial neural networks (ANNs) fixed while updating others. This framework could help to improve the performance of machine learning algorithms, while also reducing the amount of data required to adequately train them.Reservoir computing is a promising computational framework based on recurrent neural networks (RNNs), which essentially maps input data onto a high-dimensional computational space, keeping some parameters of artificial neural networks (ANNs) fixed while updating others. This framework could help to improve the performance of machine learning algorithms, while also reducing the amount of data required to adequately train them.Computer Sciences[#item_full_content]
From cameras to self-driving cars, many of today’s technologies depend on artificial intelligence to extract meaning from visual information. Today’s AI technology has artificial neural networks at its core, and most of the time we can trust these AI computer vision systems to see things the way we do—but sometimes they falter. According to MIT and IBM research scientists, one way to improve computer vision is to instruct the artificial neural networks that they rely on to deliberately mimic the way the brain’s biological neural network processes visual images.From cameras to self-driving cars, many of today’s technologies depend on artificial intelligence to extract meaning from visual information. Today’s AI technology has artificial neural networks at its core, and most of the time we can trust these AI computer vision systems to see things the way we do—but sometimes they falter. According to MIT and IBM research scientists, one way to improve computer vision is to instruct the artificial neural networks that they rely on to deliberately mimic the way the brain’s biological neural network processes visual images.[#item_full_content]
From cameras to self-driving cars, many of today’s technologies depend on artificial intelligence to extract meaning from visual information. Today’s AI technology has artificial neural networks at its core, and most of the time we can trust these AI computer vision systems to see things the way we do—but sometimes they falter. According to MIT and IBM research scientists, one way to improve computer vision is to instruct the artificial neural networks that they rely on to deliberately mimic the way the brain’s biological neural network processes visual images.From cameras to self-driving cars, many of today’s technologies depend on artificial intelligence to extract meaning from visual information. Today’s AI technology has artificial neural networks at its core, and most of the time we can trust these AI computer vision systems to see things the way we do—but sometimes they falter. According to MIT and IBM research scientists, one way to improve computer vision is to instruct the artificial neural networks that they rely on to deliberately mimic the way the brain’s biological neural network processes visual images.Computer Sciences[#item_full_content]
Researchers at The Ohio State University have developed new software to aid in the development, evaluation and demonstration of safer autonomous, or driverless, vehicles.Researchers at The Ohio State University have developed new software to aid in the development, evaluation and demonstration of safer autonomous, or driverless, vehicles.Automotive[#item_full_content]
