How AGI became the most consequential conspiracy theory of our timeMIT Technology Review Are you feeling it? I hear it’s close: two years, five years—maybe next year! And I hear it’s going to change everything: it will cure disease, save the planet, and usher in an age of abundance. It will solve our biggest problems in ways we cannot yet imagine. It will redefine what it means to…
Are you feeling it? I hear it’s close: two years, five years—maybe next year! And I hear it’s going to change everything: it will cure disease, save the planet, and usher in an age of abundance. It will solve our biggest problems in ways we cannot yet imagine. It will redefine what it means to… Read More
Chatbots are surprisingly effective at debunking conspiracy theoriesMIT Technology Review It’s become a truism that facts alone don’t change people’s minds. Perhaps nowhere is this more clear than when it comes to conspiracy theories: Many people believe that you can’t talk conspiracists out of their beliefs. But that’s not necessarily true. It turns out that many conspiracy believers do respond to evidence and arguments—information that…
It’s become a truism that facts alone don’t change people’s minds. Perhaps nowhere is this more clear than when it comes to conspiracy theories: Many people believe that you can’t talk conspiracists out of their beliefs. But that’s not necessarily true. It turns out that many conspiracy believers do respond to evidence and arguments—information that… Read More
How to Build Ethically Aligned Autonomous Agents through Value-Guided Reasoning and Self-Correcting Decision-Making Using Open-Source ModelsMarkTechPost In this tutorial, we explore how we can build an autonomous agent that aligns its actions with ethical and organizational values. We use open-source Hugging Face models running locally in Colab to simulate a decision-making process that balances goal achievement with moral reasoning. Through this implementation, we demonstrate how we can integrate a “policy” model
The post How to Build Ethically Aligned Autonomous Agents through Value-Guided Reasoning and Self-Correcting Decision-Making Using Open-Source Models appeared first on MarkTechPost.
In this tutorial, we explore how we can build an autonomous agent that aligns its actions with ethical and organizational values. We use open-source Hugging Face models running locally in Colab to simulate a decision-making process that balances goal achievement with moral reasoning. Through this implementation, we demonstrate how we can integrate a “policy” model
The post How to Build Ethically Aligned Autonomous Agents through Value-Guided Reasoning and Self-Correcting Decision-Making Using Open-Source Models appeared first on MarkTechPost. Read More
IBM AI Team Releases Granite 4.0 Nano Series: Compact and Open-Source Small Models Built for AI at the EdgeMarkTechPost Small models are often blocked by poor instruction tuning, weak tool use formats, and missing governance. IBM AI team released Granite 4.0 Nano, a small model family that targets local and edge inference with enterprise controls and open licensing. The family includes 8 models in two sizes, 350M and about 1B, with both hybrid SSM
The post IBM AI Team Releases Granite 4.0 Nano Series: Compact and Open-Source Small Models Built for AI at the Edge appeared first on MarkTechPost.
Small models are often blocked by poor instruction tuning, weak tool use formats, and missing governance. IBM AI team released Granite 4.0 Nano, a small model family that targets local and edge inference with enterprise controls and open licensing. The family includes 8 models in two sizes, 350M and about 1B, with both hybrid SSM
The post IBM AI Team Releases Granite 4.0 Nano Series: Compact and Open-Source Small Models Built for AI at the Edge appeared first on MarkTechPost. Read More
An In-Depth Analysis of Cyber Attacks in Secured Platformscs.AI updates on arXiv.org arXiv:2510.25470v1 Announce Type: cross
Abstract: There is an increase in global malware threats. To address this, an encryption-type ransomware has been introduced on the Android operating system. The challenges associated with malicious threats in phone use have become a pressing issue in mobile communication, disrupting user experiences and posing significant privacy threats. This study surveys commonly used machine learning techniques for detecting malicious threats in phones and examines their performance. The majority of past research focuses on customer feedback and reviews, with concerns that people might create false reviews to promote or devalue products and services for personal gain. Hence, the development of techniques for detecting malicious threats using machine learning has been a key focus. This paper presents a comprehensive comparative study of current research on the issue of malicious threats and methods for tackling these challenges. Nevertheless, a huge amount of information is required by these methods, presenting a challenge for developing robust, specialized automated anti-malware systems. This research describes the Android Applications dataset, and the accuracy of the techniques is measured using the accuracy levels of the metrics employed in this study.
arXiv:2510.25470v1 Announce Type: cross
Abstract: There is an increase in global malware threats. To address this, an encryption-type ransomware has been introduced on the Android operating system. The challenges associated with malicious threats in phone use have become a pressing issue in mobile communication, disrupting user experiences and posing significant privacy threats. This study surveys commonly used machine learning techniques for detecting malicious threats in phones and examines their performance. The majority of past research focuses on customer feedback and reviews, with concerns that people might create false reviews to promote or devalue products and services for personal gain. Hence, the development of techniques for detecting malicious threats using machine learning has been a key focus. This paper presents a comprehensive comparative study of current research on the issue of malicious threats and methods for tackling these challenges. Nevertheless, a huge amount of information is required by these methods, presenting a challenge for developing robust, specialized automated anti-malware systems. This research describes the Android Applications dataset, and the accuracy of the techniques is measured using the accuracy levels of the metrics employed in this study. Read More
Bringing Vision-Language Intelligence to RAG with ColPaliTowards Data Science Unlocking the value of non-textual contents in your knowledge base
The post Bringing Vision-Language Intelligence to RAG with ColPali appeared first on Towards Data Science.
Unlocking the value of non-textual contents in your knowledge base
The post Bringing Vision-Language Intelligence to RAG with ColPali appeared first on Towards Data Science. Read More
Generative AI Hype Check: Can It Really Transform SDLC?KDnuggets Gen AI is reshaping the software development lifecycle (SDLC). Faster coding, texting, and documentation. But the fundamental transformation happens when it’s combined with human expertise.
Gen AI is reshaping the software development lifecycle (SDLC). Faster coding, texting, and documentation. But the fundamental transformation happens when it’s combined with human expertise. Read More
Collecting Real-Time Data with APIs: A Hands-On Guide Using PythonKDnuggets In this article, we’ll break down the essentials of using APIs for data collection — why they matter, how they work, and how to get started with them in Python.
In this article, we’ll break down the essentials of using APIs for data collection — why they matter, how they work, and how to get started with them in Python. Read More
Accelerating discovery with the AI for Math InitiativeGoogle DeepMind Blog The initiative brings together some of the world’s most prestigious research institutions to pioneer the use of AI in mathematical research.
The initiative brings together some of the world’s most prestigious research institutions to pioneer the use of AI in mathematical research. Read More
Microsoft Releases Agent Lightning: A New AI Framework that Enables Reinforcement Learning (RL)-based Training of LLMs for Any AI AgentMarkTechPost How do you convert real agent traces into reinforcement learning RL transitions to improve policy LLMs without changing your existing agent stack? Microsoft AI team releases Agent Lightning to help optimize multi-agent systems. Agent Lightning is a open-sourced framework that makes reinforcement learning work for any AI agent without rewrites. It separates training from execution,
The post Microsoft Releases Agent Lightning: A New AI Framework that Enables Reinforcement Learning (RL)-based Training of LLMs for Any AI Agent appeared first on MarkTechPost.
How do you convert real agent traces into reinforcement learning RL transitions to improve policy LLMs without changing your existing agent stack? Microsoft AI team releases Agent Lightning to help optimize multi-agent systems. Agent Lightning is a open-sourced framework that makes reinforcement learning work for any AI agent without rewrites. It separates training from execution,
The post Microsoft Releases Agent Lightning: A New AI Framework that Enables Reinforcement Learning (RL)-based Training of LLMs for Any AI Agent appeared first on MarkTechPost. Read More