Researchers have developed a new artificial intelligence (AI) framework that is better than previous technologies at analyzing and categorizing dialogue between individuals, with the goal of improving team training technologies. The framework will enable training technologies to better understand how well individuals are coordinating with one another and working as part of a team.Researchers have developed a new artificial intelligence (AI) framework that is better than previous technologies at analyzing and categorizing dialogue between individuals, with the goal of improving team training technologies. The framework will enable training technologies to better understand how well individuals are coordinating with one another and working as part of a team.[#item_full_content]

People hear a lot about blockchain technology in relation to cryptocurrencies like bitcoin, which rely on blockchain systems to keep records of financial transactions between people and businesses. But a crash in public trust in cryptocurrencies like TerraUSD—and therefore a massive drop in their market value—doesn’t mean their underlying technology is also worthless.People hear a lot about blockchain technology in relation to cryptocurrencies like bitcoin, which rely on blockchain systems to keep records of financial transactions between people and businesses. But a crash in public trust in cryptocurrencies like TerraUSD—and therefore a massive drop in their market value—doesn’t mean their underlying technology is also worthless.[#item_full_content]

Just making a small tweak to algorithms typically used to enhance images could dramatically boost computer vision recognition capabilities in applications ranging from self-driving cars to cybernetic avatars, RIKEN researchers have shown.Just making a small tweak to algorithms typically used to enhance images could dramatically boost computer vision recognition capabilities in applications ranging from self-driving cars to cybernetic avatars, RIKEN researchers have shown.[#item_full_content]

Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of machine-learning models used in applications like speech recognition and object detection. The work, for the first time, combines two architectures of self-supervised learning, contrastive learning and masked data modeling, in an effort to scale machine-learning tasks like event classification in single- and multimodal data without the need for annotation, thereby replicating how humans understand and perceive our world.Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of machine-learning models used in applications like speech recognition and object detection. The work, for the first time, combines two architectures of self-supervised learning, contrastive learning and masked data modeling, in an effort to scale machine-learning tasks like event classification in single- and multimodal data without the need for annotation, thereby replicating how humans understand and perceive our world.[#item_full_content]

Socrates once said, “It is not the size of a thing, but the quality that truly matters. For it is in the nature of substance, not its volume, that true value is found.”Socrates once said, “It is not the size of a thing, but the quality that truly matters. For it is in the nature of substance, not its volume, that true value is found.”[#item_full_content]

When interacting with another person, you likely spend part of your time trying to anticipate how they will feel about what you’re saying or doing. This task requires a cognitive skill called theory of mind, which helps us to infer other people’s beliefs, desires, intentions, and emotions.When interacting with another person, you likely spend part of your time trying to anticipate how they will feel about what you’re saying or doing. This task requires a cognitive skill called theory of mind, which helps us to infer other people’s beliefs, desires, intentions, and emotions.[#item_full_content]

The human brain has been called the most complicated object in the universe. Trying to replicate that still-unmatched capability for computing, scientists at Los Alamos National Laboratory have made a new interface-type memristive device, which their results suggest can be used to build artificial synapses for next-generation neuromorphic computing.The human brain has been called the most complicated object in the universe. Trying to replicate that still-unmatched capability for computing, scientists at Los Alamos National Laboratory have made a new interface-type memristive device, which their results suggest can be used to build artificial synapses for next-generation neuromorphic computing.[#item_full_content]

Kirigami takes pop-up books to a whole new level. The Japanese paper craft involves cutting patterns in paper to transform a two-dimensional sheet into an intricate, three-dimensional structure when partially folded. In the hands of an artist, kirigami can yield remarkably detailed and delicate replicas of structures in nature, architecture, and more.Kirigami takes pop-up books to a whole new level. The Japanese paper craft involves cutting patterns in paper to transform a two-dimensional sheet into an intricate, three-dimensional structure when partially folded. In the hands of an artist, kirigami can yield remarkably detailed and delicate replicas of structures in nature, architecture, and more.[#item_full_content]

The language models behind ChatGPT and other generative AI are trained on written words that have been culled from libraries, scraped from websites and social media, and pulled from news reports and speech transcripts from across the world. There are 250 billion such words behind GPT-3.5, the model fueling ChatGPT, for instance, and GPT-4 is now here.The language models behind ChatGPT and other generative AI are trained on written words that have been culled from libraries, scraped from websites and social media, and pulled from news reports and speech transcripts from across the world. There are 250 billion such words behind GPT-3.5, the model fueling ChatGPT, for instance, and GPT-4 is now here.[#item_full_content]

When machine-learning models are deployed in real-world situations, perhaps to flag potential disease in X-rays for a radiologist to review, human users need to know when to trust the model’s predictions.When machine-learning models are deployed in real-world situations, perhaps to flag potential disease in X-rays for a radiologist to review, human users need to know when to trust the model’s predictions.[#item_full_content]