Greenwashing scams, murky networks and poor oversight cloud the experiences of climate-conscious consumers and investors. Research from the University of Copenhagen demonstrates that we can create transparency in supply chains, genuinely green products and green financial markets by using distributed ledger technology (DLT).Greenwashing scams, murky networks and poor oversight cloud the experiences of climate-conscious consumers and investors. Research from the University of Copenhagen demonstrates that we can create transparency in supply chains, genuinely green products and green financial markets by using distributed ledger technology (DLT).[#item_full_content]

Cutting-edge technologies gave the world fake news, but researchers from the University of Waterloo’s Faculty of Engineering are developing even newer technology to stop it. Their innovative system—the first of its kind—relies on something already famous for underpinning Bitcoin and other cryptocurrencies—blockchain. But in addition to sophisticated machines, these researchers are enlisting humans to establish the truth. Their goal is a world where people have greater trust in the news they see and hear.Cutting-edge technologies gave the world fake news, but researchers from the University of Waterloo’s Faculty of Engineering are developing even newer technology to stop it. Their innovative system—the first of its kind—relies on something already famous for underpinning Bitcoin and other cryptocurrencies—blockchain. But in addition to sophisticated machines, these researchers are enlisting humans to establish the truth. Their goal is a world where people have greater trust in the news they see and hear.[#item_full_content]

An individual may bring their hands to their face when feeling sad or jump into the air when feeling happy. Human body movements convey emotions, which plays a crucial role in everyday communication, according to a team led by Penn State researchers. Combining computing, psychology and performing arts, the researchers developed an annotated human movement dataset that may improve the ability of artificial intelligence to recognize the emotions expressed through body language.An individual may bring their hands to their face when feeling sad or jump into the air when feeling happy. Human body movements convey emotions, which plays a crucial role in everyday communication, according to a team led by Penn State researchers. Combining computing, psychology and performing arts, the researchers developed an annotated human movement dataset that may improve the ability of artificial intelligence to recognize the emotions expressed through body language.[#item_full_content]

A team of computer scientists at the University of California Berkeley, working with one colleague from the University of California San Diego and another from Carnegie Mellon University, has created a large-scale dataset of 1 million real-world conversations to study how people interact with large language models (LLMs). They have published a paper describing their work and findings on the arXiv preprint server.A team of computer scientists at the University of California Berkeley, working with one colleague from the University of California San Diego and another from Carnegie Mellon University, has created a large-scale dataset of 1 million real-world conversations to study how people interact with large language models (LLMs). They have published a paper describing their work and findings on the arXiv preprint server.[#item_full_content]

Human sensory systems are very good at recognizing objects that we see or words that we hear, even if the object is upside down or the word is spoken by a voice we’ve never heard.Human sensory systems are very good at recognizing objects that we see or words that we hear, even if the object is upside down or the word is spoken by a voice we’ve never heard.[#item_full_content]

Computer vision algorithms have become increasingly advanced over the past decades, enabling the development of sophisticated technologies to monitor specific environments, detect objects of interest in video footage and uncover suspicious activities in CCTV recordings. Some of these algorithms are specifically designed to detect and isolate moving objects or people of interest in a video, a task known as moving target segmentation.Computer vision algorithms have become increasingly advanced over the past decades, enabling the development of sophisticated technologies to monitor specific environments, detect objects of interest in video footage and uncover suspicious activities in CCTV recordings. Some of these algorithms are specifically designed to detect and isolate moving objects or people of interest in a video, a task known as moving target segmentation.[#item_full_content]