This book is a collection of writings by active researchers in the field of Artificial General Intelligence, on topics of central importance in the field. Each chapter focuses on one theoretical problem, proposes a novel solution, and is written in sufficiently non-technical language to be understandable by advanced undergraduates or scientists in allied fields.
This book is the very first collection in the field of Artificial General Intelligence (AGI) focusing on theoretical, conceptual, and philosophical issues in the creation of thinking machines. All the authors are researchers actively developing AGI projects, thus distinguishing the book from much of the theoretical cognitive science and AI literature, which is generally quite divorced from practical AGI system building issues.
In a significant step toward improving road safety, Johns Hopkins University researchers have developed an AI-based tool that can identify the risk factors contributing to car crashes across the United States and to accurately predict future incidents.
The tool, called SafeTraffic Copilot, aims to provide experts with both crash analyses and crash predictions to reduce the rising number of fatalities and injuries that happen on U.S. roads each year.
The work, led by Johns Hopkins University researchers, is published in Nature Communications.
In October 2024, Cyble also disclosed details of a sophisticated multi-stage attack campaign orchestrated by a Vietnamese threat actor that targeted job seekers and digital marketing professionals with Quasar RAT using phishing emails containing booby-trapped job description files.
BatShadow is assessed to be active for at least a year, with prior campaigns using similar domains, such as samsung-work[.]com, to propagate malware families including Agent Tesla, Lumma Stealer, and Venom RAT.
“The BatShadow threat group continues to employ sophisticated social engineering tactics to target job seekers and digital marketing professionals,” Aryaka said. “By leveraging disguised documents and a multi-stage infection chain, the group delivers a Go-based Vampire Bot capable of system surveillance, data exfiltration, and remote task execution.”
Google’s DeepMind division on Monday announced an artificial intelligence (AI)-powered agent called CodeMender that automatically detects, patches, and rewrites vulnerable code to prevent future exploits.
The efforts add to the company’s ongoing efforts to improve AI-powered vulnerability discovery, such as Big Sleep and OSS-Fuzz.
DeepMind said the AI agent is designed to be both reactive and proactive, by fixing new vulnerabilities as soon as they are spotted as well as rewriting and securing existing codebases with an aim to eliminate whole classes of vulnerabilities in the process.
Google has decided not to fix a new ASCII smuggling attack in Gemini that could be used to trick the AI assistant into providing users with fake information, alter the model’s behavior, and silently poison its data.
ASCII smuggling is an attack where special characters from the Tags Unicode block are used to introduce payloads that are invisible to users but can still be detected and processed by large-language models (LLMs).
It’s similar to other attacks that researchers presented recently against Google Gemini, which all exploit a gap between what users see and what machines read, like performing CSS manipulation or exploiting GUI limitations.
Engineering and health researchers at the University of Waterloo have developed a radar and artificial intelligence (AI) system that can monitor multiple people walking in busy hospitals and long-term care facilities to identify possible health issues.
The new technology—housed in a wall-mounted device about the size of a deck of cards—uses AI software and radar hardware to accurately measure how fast each person is walking. A paper on their work, “Non-contact, non-visual, multi-person hallway gait monitoring,” appears in Scientific Reports.
“Walking speed is often called a functional vital sign because even subtle declines can be an early warning of health problems,” said Dr. Hajar Abedi, a former postdoctoral researcher in electrical and computer engineering at Waterloo.
Behold Neural Viz, the first great cinematic universe of the AI era. It’s from a guy named Josh.
Could a simple blood test reveal how well someone is aging? A team of researchers led by Wolfram Weckwerth from the University of Vienna, Austria, and Nankai University, China, has combined advanced metabolomics with cutting-edge machine learning and a novel network modeling tool to uncover the key molecular processes underlying active aging.
Their study, published in npj Systems Biology and Applications, identifies aspartate as a dominant biomarker of physical fitness and maps the dynamic interactions that support healthier aging.
It has long been known that exercise protects mobility and lowers the risk of chronic disease. Yet the precise molecular processes that translate physical activity into healthier aging remain poorly understood. The researchers set out to answer a simple but powerful question: Can we see the benefits of an active lifestyle in elderly individuals directly in the blood—and pinpoint the molecules that matter most?