Category: News

Anthropic details cyber espionage campaign orchestrated by AIAI News Security leaders face a new class of autonomous threat as Anthropic details the first cyber espionage campaign orchestrated by AI. In a report released this week, the company’s Threat Intelligence team outlined its disruption of a sophisticated operation by a Chinese state-sponsored group – an assessment made with high confidence – dubbed GTG-1002 and detected
The post Anthropic details cyber espionage campaign orchestrated by AI appeared first on AI News.

 Security leaders face a new class of autonomous threat as Anthropic details the first cyber espionage campaign orchestrated by AI. In a report released this week, the company’s Threat Intelligence team outlined its disruption of a sophisticated operation by a Chinese state-sponsored group – an assessment made with high confidence – dubbed GTG-1002 and detected
The post Anthropic details cyber espionage campaign orchestrated by AI appeared first on AI News. Read More  

Meet SDialog: An Open-Source Python Toolkit for Building, Simulating, and Evaluating LLM-based Conversational Agents End-to-EndMarkTechPost How can developers reliably generate, control, and inspect large volumes of realistic dialogue data without building a custom simulation stack every time? Meet SDialog, an open sourced Python toolkit for synthetic dialogue generation, evaluation, and interpretability that targets the full conversational pipeline from agent definition to analysis. It standardizes how a Dialog is represented and
The post Meet SDialog: An Open-Source Python Toolkit for Building, Simulating, and Evaluating LLM-based Conversational Agents End-to-End appeared first on MarkTechPost.

 How can developers reliably generate, control, and inspect large volumes of realistic dialogue data without building a custom simulation stack every time? Meet SDialog, an open sourced Python toolkit for synthetic dialogue generation, evaluation, and interpretability that targets the full conversational pipeline from agent definition to analysis. It standardizes how a Dialog is represented and
The post Meet SDialog: An Open-Source Python Toolkit for Building, Simulating, and Evaluating LLM-based Conversational Agents End-to-End appeared first on MarkTechPost. Read More  

Visa builds AI commerce infrastructure for the Asia Pacific’s 2026 PilotAI News When Visa unveiled its Intelligent Commerce platform for Asia Pacific on November 12, it wasn’t just launching another payment feature—it was building AI commerce infrastructure to solve a crisis most merchants haven’t noticed yet: their websites are being flooded by AI agents, and there’s no reliable way to tell which ones are legitimate shoppers and which are malicious bots. 
The post Visa builds AI commerce infrastructure for the Asia Pacific’s 2026 Pilot appeared first on AI News.

 When Visa unveiled its Intelligent Commerce platform for Asia Pacific on November 12, it wasn’t just launching another payment feature—it was building AI commerce infrastructure to solve a crisis most merchants haven’t noticed yet: their websites are being flooded by AI agents, and there’s no reliable way to tell which ones are legitimate shoppers and which are malicious bots. 
The post Visa builds AI commerce infrastructure for the Asia Pacific’s 2026 Pilot appeared first on AI News. Read More  

New prediction breakthrough delivers results shockingly close to realityArtificial Intelligence News — ScienceDaily Researchers have created a prediction method that comes startlingly close to real-world results. It works by aiming for strong alignment with actual values rather than simply reducing mistakes. Tests on medical and health data showed it often outperforms classic approaches. The discovery could reshape how scientists make reliable forecasts.

 Researchers have created a prediction method that comes startlingly close to real-world results. It works by aiming for strong alignment with actual values rather than simply reducing mistakes. Tests on medical and health data showed it often outperforms classic approaches. The discovery could reshape how scientists make reliable forecasts. Read More  

Differentiating between human-written and AI-generated texts using linguistic features automatically extracted from an online computational toolcs.AI updates on arXiv.org arXiv:2407.03646v3 Announce Type: replace-cross
Abstract: While extensive research has focused on ChatGPT in recent years, very few studies have systematically quantified and compared linguistic features between human-written and Artificial Intelligence (AI)-generated language. This study aims to investigate how various linguistic components are represented in both types of texts, assessing the ability of AI to emulate human writing. Using human-authored essays as a benchmark, we prompted ChatGPT to generate essays of equivalent length. These texts were analyzed using Open Brain AI, an online computational tool, to extract measures of phonological, morphological, syntactic, and lexical constituents. Despite AI-generated texts appearing to mimic human speech, the results revealed significant differences across multiple linguistic features such as consonants, word stress, nouns, verbs, pronouns, direct objects, prepositional modifiers, and use of difficult words among others. These findings underscore the importance of integrating automated tools for efficient language assessment, reducing time and effort in data analysis. Moreover, they emphasize the necessity for enhanced training methodologies to improve the capacity of AI for producing more human-like text.

 arXiv:2407.03646v3 Announce Type: replace-cross
Abstract: While extensive research has focused on ChatGPT in recent years, very few studies have systematically quantified and compared linguistic features between human-written and Artificial Intelligence (AI)-generated language. This study aims to investigate how various linguistic components are represented in both types of texts, assessing the ability of AI to emulate human writing. Using human-authored essays as a benchmark, we prompted ChatGPT to generate essays of equivalent length. These texts were analyzed using Open Brain AI, an online computational tool, to extract measures of phonological, morphological, syntactic, and lexical constituents. Despite AI-generated texts appearing to mimic human speech, the results revealed significant differences across multiple linguistic features such as consonants, word stress, nouns, verbs, pronouns, direct objects, prepositional modifiers, and use of difficult words among others. These findings underscore the importance of integrating automated tools for efficient language assessment, reducing time and effort in data analysis. Moreover, they emphasize the necessity for enhanced training methodologies to improve the capacity of AI for producing more human-like text. Read More  

Bridging LMS and generative AI: dynamic course content integration (DCCI) for enhancing student satisfaction and engagement via the ask ME assistantcs.AI updates on arXiv.org arXiv:2504.03966v2 Announce Type: replace-cross
Abstract: Integration of Large Language Models (LLMs) with Learning Management Systems (LMSs) can enhance task automation and accessibility in education. However, hallucination where LLMs generate inaccurate or misleading information remains a challenge. This study introduces the Dynamic Course Content Integration (DCCI) mechanism, which dynamically retrieves course content from Canvas LMS and structures it within an LLM’s context window via prompt engineering, enabling the LLM-powered assistant, Ask ME, to deliver context-aware, curriculum-aligned responses while mitigating hallucinations. A mixed-methods pilot study grounded in Self-Determination Theory (autonomy, competence) and the Technology Acceptance Model (perceived usefulness, ease of use) evaluated DCCI’s effectiveness with 120 first-year programming students at E”otv”os Lor’and University. The course focused on foundational programming patterns in C#, including writing program specifications. We analyzed 14,746 logged interactions and a post-course survey completed by 101 students. User satisfaction was measured via a 5-point Likert scale (turn-level ratings), while the survey assessed usability, engagement, and ethical concerns. Results indicated high satisfaction (mean 4.65/5) and strong recognition of Ask ME’s ability to provide timely, contextually relevant answers to administrative and course-related queries. 78.06% agreed that Ask ME’s Canvas integration reduced platform switching, improving usability, engagement, comprehension, and topic exploration. Many students reported reduced hesitation to ask questions and increased motivation for self-directed learning, though concerns about over-reliance on AI and reduced student-teacher interaction emerged. This study demonstrates that DCCI enhances LLM reliability, student satisfaction, and engagement in AI-driven educational automation, while highlighting the importance of balancing

 arXiv:2504.03966v2 Announce Type: replace-cross
Abstract: Integration of Large Language Models (LLMs) with Learning Management Systems (LMSs) can enhance task automation and accessibility in education. However, hallucination where LLMs generate inaccurate or misleading information remains a challenge. This study introduces the Dynamic Course Content Integration (DCCI) mechanism, which dynamically retrieves course content from Canvas LMS and structures it within an LLM’s context window via prompt engineering, enabling the LLM-powered assistant, Ask ME, to deliver context-aware, curriculum-aligned responses while mitigating hallucinations. A mixed-methods pilot study grounded in Self-Determination Theory (autonomy, competence) and the Technology Acceptance Model (perceived usefulness, ease of use) evaluated DCCI’s effectiveness with 120 first-year programming students at E”otv”os Lor’and University. The course focused on foundational programming patterns in C#, including writing program specifications. We analyzed 14,746 logged interactions and a post-course survey completed by 101 students. User satisfaction was measured via a 5-point Likert scale (turn-level ratings), while the survey assessed usability, engagement, and ethical concerns. Results indicated high satisfaction (mean 4.65/5) and strong recognition of Ask ME’s ability to provide timely, contextually relevant answers to administrative and course-related queries. 78.06% agreed that Ask ME’s Canvas integration reduced platform switching, improving usability, engagement, comprehension, and topic exploration. Many students reported reduced hesitation to ask questions and increased motivation for self-directed learning, though concerns about over-reliance on AI and reduced student-teacher interaction emerged. This study demonstrates that DCCI enhances LLM reliability, student satisfaction, and engagement in AI-driven educational automation, while highlighting the importance of balancing Read More