Neural networks have made a seismic impact on how engineers design controllers for robots, catalyzing more adaptive and efficient machines. Still, these brain-like machine-learning systems are a double-edged sword: Their complexity makes them powerful, but it also makes it difficult to guarantee that a robot powered by a neural network will safely accomplish its task.Neural networks have made a seismic impact on how engineers design controllers for robots, catalyzing more adaptive and efficient machines. Still, these brain-like machine-learning systems are a double-edged sword: Their complexity makes them powerful, but it also makes it difficult to guarantee that a robot powered by a neural network will safely accomplish its task.Robotics[#item_full_content]

Hong Kong’s government is testing the city’s own ChatGPT -style tool for its employees, with plans to eventually make it available to the public, its innovation minister said after OpenAI took extra steps to block access from the city and other unsupported regions.Hong Kong’s government is testing the city’s own ChatGPT -style tool for its employees, with plans to eventually make it available to the public, its innovation minister said after OpenAI took extra steps to block access from the city and other unsupported regions.Machine learning & AI[#item_full_content]

Social media offers a treasure trove of data for researchers to understand how organizations and individuals use the technology to communicate with and grow their base of followers. However, manually analyzing the content can be time consuming or, in some cases, simply impossible due to the volume of data. While machine-learning models can help, they present their own set of challenges.Social media offers a treasure trove of data for researchers to understand how organizations and individuals use the technology to communicate with and grow their base of followers. However, manually analyzing the content can be time consuming or, in some cases, simply impossible due to the volume of data. While machine-learning models can help, they present their own set of challenges.Machine learning & AI[#item_full_content]

A novel machine learning framework developed by IIASA researchers to estimate global rooftop area growth from 2020 to 2050 can aid in planning sustainable energy systems, urban development, and climate change mitigation, and has potential for significant benefits in emerging economies.A novel machine learning framework developed by IIASA researchers to estimate global rooftop area growth from 2020 to 2050 can aid in planning sustainable energy systems, urban development, and climate change mitigation, and has potential for significant benefits in emerging economies.Energy & Green Tech[#item_full_content]

A new study has revealed that people prefer artificial intelligence (AI) over humans when it comes to redistributive decisions.A new study has revealed that people prefer artificial intelligence (AI) over humans when it comes to redistributive decisions.Business[#item_full_content]

With the rapid development of AI technology, voice-controlled smart speakers are becoming increasingly popular due to their convenience and ability to control compatible home devices. Despite the rise in use, smart speakers often do not have screens and little-to-none of the visual information feedback common to manually operated devices. This aspect complicates their usability, thus providing room for research and subsequent improvement.With the rapid development of AI technology, voice-controlled smart speakers are becoming increasingly popular due to their convenience and ability to control compatible home devices. Despite the rise in use, smart speakers often do not have screens and little-to-none of the visual information feedback common to manually operated devices. This aspect complicates their usability, thus providing room for research and subsequent improvement.Consumer & Gadgets[#item_full_content]

Large language models (LLMs) can complete abstract reasoning tasks, but they are susceptible to many of the same types of mistakes made by humans. Andrew Lampinen, Ishita Dasgupta, and colleagues tested state-of-the-art LLMs and humans on three kinds of reasoning tasks: natural language inference, judging the logical validity of syllogisms, and the Wason selection task.Large language models (LLMs) can complete abstract reasoning tasks, but they are susceptible to many of the same types of mistakes made by humans. Andrew Lampinen, Ishita Dasgupta, and colleagues tested state-of-the-art LLMs and humans on three kinds of reasoning tasks: natural language inference, judging the logical validity of syllogisms, and the Wason selection task.Machine learning & AI[#item_full_content]

A team of programmers and AI specialists at Microsoft has developed an AI tool called SpreadsheetLLM that applies large language model capabilities to spreadsheets. In their study, now posted on the arXiv preprint server, the group developed SheetCompressor, an encoding framework that compresses spreadsheets effectively for use by large language models (LLMs).A team of programmers and AI specialists at Microsoft has developed an AI tool called SpreadsheetLLM that applies large language model capabilities to spreadsheets. In their study, now posted on the arXiv preprint server, the group developed SheetCompressor, an encoding framework that compresses spreadsheets effectively for use by large language models (LLMs).Software[#item_full_content]

Foundation models are massive deep-learning models that have been pretrained on an enormous amount of general-purpose, unlabeled data. They can be applied to a variety of tasks, like generating images or answering customer questions.Foundation models are massive deep-learning models that have been pretrained on an enormous amount of general-purpose, unlabeled data. They can be applied to a variety of tasks, like generating images or answering customer questions.Machine learning & AI[#item_full_content]

Imitation learning is a promising method to teach robots how to reliably complete everyday tasks, such as washing dishes or cooking. Despite their potential, imitation learning frameworks rely on detailed human demonstrations, which should include data that can help to reproduce specific movements using robotic systems.Imitation learning is a promising method to teach robots how to reliably complete everyday tasks, such as washing dishes or cooking. Despite their potential, imitation learning frameworks rely on detailed human demonstrations, which should include data that can help to reproduce specific movements using robotic systems.Robotics[#item_full_content]