Like a hack writer or a friend rehashing their glory days over and over, artificial intelligence tends to tell the same old story. For AI agents instructed to write fiction, that tale usually involves lighthouses and a keeper named Elias, according to new Cornell research.Like a hack writer or a friend rehashing their glory days over and over, artificial intelligence tends to tell the same old story. For AI agents instructed to write fiction, that tale usually involves lighthouses and a keeper named Elias, according to new Cornell research.[#item_full_content]

Canada has made digital sovereignty a priority in areas such as cloud computing, artificial intelligence and telecommunications. But one important part of its digital infrastructure has received far less attention: the operating systems running government computers.Canada has made digital sovereignty a priority in areas such as cloud computing, artificial intelligence and telecommunications. But one important part of its digital infrastructure has received far less attention: the operating systems running government computers.[#item_full_content]

Large language models (LLMs), the artificial intelligence (AI) systems underpinning the functioning of ChatGPT and other conversational agents, are now widely used to source information, summarize texts and generate content for specific purposes. These models essentially generate their responses by predicting sequences of words based on the patterns they learned during previous training.Large language models (LLMs), the artificial intelligence (AI) systems underpinning the functioning of ChatGPT and other conversational agents, are now widely used to source information, summarize texts and generate content for specific purposes. These models essentially generate their responses by predicting sequences of words based on the patterns they learned during previous training.[#item_full_content]

Researchers from the VUB’s Artificial Intelligence Lab and the University of Namur (UNamur) demonstrate in a new large-scale study how autonomous AI systems can spontaneously develop a functional, shared language without human intervention.Researchers from the VUB’s Artificial Intelligence Lab and the University of Namur (UNamur) demonstrate in a new large-scale study how autonomous AI systems can spontaneously develop a functional, shared language without human intervention.[#item_full_content]

Artificial intelligence can do remarkable things, but how much does it actually understand about the world? Researchers have found that surprisingly specific information can be extracted from the inner workings of large language models (LLMs) like ChatGPT. Using mathematical tools to probe a model’s internal activity, they can identify where a city is located on a map, when a historical figure lived or what emotion a character feels, even detecting descriptions of pain.Artificial intelligence can do remarkable things, but how much does it actually understand about the world? Researchers have found that surprisingly specific information can be extracted from the inner workings of large language models (LLMs) like ChatGPT. Using mathematical tools to probe a model’s internal activity, they can identify where a city is located on a map, when a historical figure lived or what emotion a character feels, even detecting descriptions of pain.[#item_full_content]

It’s no secret that an ever-increasing number of scientists use AI to help with their papers. While tasks such as polishing text are generally permissible if declared, using the technology to write papers, or parts of papers, from scratch and passing them off as original work is not. But it’s happening.It’s no secret that an ever-increasing number of scientists use AI to help with their papers. While tasks such as polishing text are generally permissible if declared, using the technology to write papers, or parts of papers, from scratch and passing them off as original work is not. But it’s happening.[#item_full_content]

Inside the human brain, billions of individual neurons connect to form a vast network capable of rapidly processing information and electrical signals. A team of researchers and engineers at Penn State is taking inspiration from these natural computers to build soft networks of water-based droplets, connected by membranes like those found in the walls of living cells.Inside the human brain, billions of individual neurons connect to form a vast network capable of rapidly processing information and electrical signals. A team of researchers and engineers at Penn State is taking inspiration from these natural computers to build soft networks of water-based droplets, connected by membranes like those found in the walls of living cells.[#item_full_content]

When humans write sentences or solve math problems, they are thinking symbolically—each number, variable or word is expressed by a symbol. While AI chatbots do not “think” that way, if prompted, they can offer cogent advice about writing, math and many other topics as if a person were offering it.When humans write sentences or solve math problems, they are thinking symbolically—each number, variable or word is expressed by a symbol. While AI chatbots do not “think” that way, if prompted, they can offer cogent advice about writing, math and many other topics as if a person were offering it.[#item_full_content]

Before large language models (LLMs) can process text, they split it into chunks such as words or word fragments. The LLM behind ChatGPT, for example, splits “LMU München” into the three chunks “LM,” “U” and “München,” so it never directly sees the individual letters in “München.” This step, which is known as subword tokenization, makes LLMs efficient but causes a range of problems, such as limited character-level understanding.Before large language models (LLMs) can process text, they split it into chunks such as words or word fragments. The LLM behind ChatGPT, for example, splits “LMU München” into the three chunks “LM,” “U” and “München,” so it never directly sees the individual letters in “München.” This step, which is known as subword tokenization, makes LLMs efficient but causes a range of problems, such as limited character-level understanding.[#item_full_content]

When new information is continually added and old information is removed, an AI system may fail to find the correct material even when that material exists. KAIST researchers have developed a vector database technology that preserves the search paths leading to the needed information as data changes. This allows AI to find up-to-date information more accurately and quickly.When new information is continually added and old information is removed, an AI system may fail to find the correct material even when that material exists. KAIST researchers have developed a vector database technology that preserves the search paths leading to the needed information as data changes. This allows AI to find up-to-date information more accurately and quickly.[#item_full_content]