Setting its sights on evolving graphics processing units in a growing universe of generative AI, Intel announced the release of several papers outlining efforts it is pursuing in what observers say is a multibillion-dollar opportunity in coming years for the semiconductor chip giant.Setting its sights on evolving graphics processing units in a growing universe of generative AI, Intel announced the release of several papers outlining efforts it is pursuing in what observers say is a multibillion-dollar opportunity in coming years for the semiconductor chip giant.Computer Sciences[#item_full_content]
A United Nations technology agency assembled a group of robots that physically resembled humans at a news conference Friday, inviting reporters to ask them questions in an event meant to spark discussion about the future of artificial intelligence.A United Nations technology agency assembled a group of robots that physically resembled humans at a news conference Friday, inviting reporters to ask them questions in an event meant to spark discussion about the future of artificial intelligence.Robotics[#item_full_content]
Mars rovers have teams of human experts on Earth telling them what to do. But robots on lander missions to moons orbiting Saturn or Jupiter are too far away to receive timely commands from Earth.Mars rovers have teams of human experts on Earth telling them what to do. But robots on lander missions to moons orbiting Saturn or Jupiter are too far away to receive timely commands from Earth.Robotics[#item_full_content]
Artificial intelligence seems perfect for creating massive sets of images needed to train autonomous cars and other machines to see their environment, but current generative AI systems have shortcomings that can limit their use. Now, engineers at Princeton have developed a software system to overcome those limits and quickly create image sets to prepare machines for nearly any visual setting.Artificial intelligence seems perfect for creating massive sets of images needed to train autonomous cars and other machines to see their environment, but current generative AI systems have shortcomings that can limit their use. Now, engineers at Princeton have developed a software system to overcome those limits and quickly create image sets to prepare machines for nearly any visual setting.Software[#item_full_content]
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]
