AI companies and evangelists frequently use terms such as copilot, coworker, cocreator and co-scientist to imply these rapidly developing systems can happily coexist with us humans. Their inference is clear: People should always be in the loop—the AI is never in charge.AI companies and evangelists frequently use terms such as copilot, coworker, cocreator and co-scientist to imply these rapidly developing systems can happily coexist with us humans. Their inference is clear: People should always be in the loop—the AI is never in charge.Business[#item_full_content]

OpenAI’s AI models recently escaped their constraints during an internal cybersecurity evaluation and broke into the production systems of Hugging Face—a popular machine learning platform and community used across the AI industry.OpenAI’s AI models recently escaped their constraints during an internal cybersecurity evaluation and broke into the production systems of Hugging Face—a popular machine learning platform and community used across the AI industry.Security[#item_full_content]

Imagine you’ve always wanted your own app. Perhaps one that tracks your household budget, organizes the family shopping list or reminds you when to water your plants.Imagine you’ve always wanted your own app. Perhaps one that tracks your household budget, organizes the family shopping list or reminds you when to water your plants.Machine learning & AI[#item_full_content]

Large language models (LLMs), the artificial intelligence (AI) systems underpinning ChatGPT and similar conversational platforms, are now used by many people worldwide to find and summarize information and generate different types of text. Despite their widespread use, these models still have notable limitations.Large language models (LLMs), the artificial intelligence (AI) systems underpinning ChatGPT and similar conversational platforms, are now used by many people worldwide to find and summarize information and generate different types of text. Despite their widespread use, these models still have notable limitations.Computer Sciences[#item_full_content]

KAIST researchers have developed a safety verification technology that uncovers roughly seven times more hidden vulnerabilities in AI than existing methods. The technology is expected to serve as a foundation for developing safer, more trustworthy AI. The work is published on the arXiv preprint server.KAIST researchers have developed a safety verification technology that uncovers roughly seven times more hidden vulnerabilities in AI than existing methods. The technology is expected to serve as a foundation for developing safer, more trustworthy AI. The work is published on the arXiv preprint server.Security[#item_full_content]

Thousands of peer-reviewed papers on battery devices are published each year. Despite this rapid growth, the data contained within these publications are often reported in different formats and with varying levels of detail and accessibility. The resulting patchwork of information makes it difficult for scientists, engineers, industry partners and policymakers to fully leverage published research and identify opportunities for innovation.Thousands of peer-reviewed papers on battery devices are published each year. Despite this rapid growth, the data contained within these publications are often reported in different formats and with varying levels of detail and accessibility. The resulting patchwork of information makes it difficult for scientists, engineers, industry partners and policymakers to fully leverage published research and identify opportunities for innovation.Energy & Green Tech[#item_full_content]

AI company Anthropic has announced that its unreleased model, Claude Mythos Preview, has discovered previously unknown mathematical weaknesses in cryptographic algorithms that human researchers had missed for years.AI company Anthropic has announced that its unreleased model, Claude Mythos Preview, has discovered previously unknown mathematical weaknesses in cryptographic algorithms that human researchers had missed for years.Security[#item_full_content]

Generating an image of a person on a computer using text prompts is easy. Generating one with two people is similarly simple. But creating an image of multiple people actually doing something, and faithfully reproducing not just the people but the thing they’re doing? Not so easy.Generating an image of a person on a computer using text prompts is easy. Generating one with two people is similarly simple. But creating an image of multiple people actually doing something, and faithfully reproducing not just the people but the thing they’re doing? Not so easy.Computer Sciences[#item_full_content]