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Google AI Ships a Model Context Protocol (MCP) Server for Data Commons, Giving AI Agents First-Class Access to Public StatsMarkTechPost

Google AI Ships a Model Context Protocol (MCP) Server for Data Commons, Giving AI Agents First-Class Access to Public StatsMarkTechPost

Google AI Ships a Model Context Protocol (MCP) Server for Data Commons, Giving AI Agents First-Class Access to Public StatsMarkTechPoston September 26, 2025 at 8:05 am Google released a Model Context Protocol (MCP) server for Data Commons, exposing the project’s interconnected public datasets—census, health, climate, economics—through a standards-based interface that agentic systems can query in natural language. The Data Commons MCP Server is available now with quickstarts for Gemini CLI and Google’s Agent Development Kit (ADK). What was released Why MCP
The post Google AI Ships a Model Context Protocol (MCP) Server for Data Commons, Giving AI Agents First-Class Access to Public Stats appeared first on MarkTechPost.

 Google released a Model Context Protocol (MCP) server for Data Commons, exposing the project’s interconnected public datasets—census, health, climate, economics—through a standards-based interface that agentic systems can query in natural language. The Data Commons MCP Server is available now with quickstarts for Gemini CLI and Google’s Agent Development Kit (ADK). What was released Why MCP
The post Google AI Ships a Model Context Protocol (MCP) Server for Data Commons, Giving AI Agents First-Class Access to Public Stats appeared first on MarkTechPost. Read More 

Daily AI News
Nano Banana Practical Prompting & Usage Guide KDnuggets

Nano Banana Practical Prompting & Usage Guide KDnuggets

Nano Banana Practical Prompting & Usage GuideKDnuggetson September 26, 2025 at 12:00 pm In this article we will take a look at what Nano Banana excels at, some tips and tricks for using the model, and lay out a series of example prompts and promoting strategies for getting the most out of using it.

 In this article we will take a look at what Nano Banana excels at, some tips and tricks for using the model, and lay out a series of example prompts and promoting strategies for getting the most out of using it. Read More 

Daily AI News
Ethical cybersecurity practice reshapes enterprise security in 2025 AI News

Ethical cybersecurity practice reshapes enterprise security in 2025 AI News

Ethical cybersecurity practice reshapes enterprise security in 2025AI Newson September 26, 2025 at 8:20 am When ransomware attacks like Akira and Ryuk began crippling organisations worldwide, the cybersecurity industry’s first instinct was predictable: build bigger walls, deploy more aggressive automated responses, and lock down everything. But there was a different problem emerging, according to Romanus Prabhu Raymond, Director of Technology at ManageEngine. The company’s customers were demanding aggressive containment features,
The post Ethical cybersecurity practice reshapes enterprise security in 2025 appeared first on AI News.

 When ransomware attacks like Akira and Ryuk began crippling organisations worldwide, the cybersecurity industry’s first instinct was predictable: build bigger walls, deploy more aggressive automated responses, and lock down everything. But there was a different problem emerging, according to Romanus Prabhu Raymond, Director of Technology at ManageEngine. The company’s customers were demanding aggressive containment features,
The post Ethical cybersecurity practice reshapes enterprise security in 2025 appeared first on AI News. Read More 

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Notes on LLM EvaluationTowards Data Science

Notes on LLM EvaluationTowards Data Scienceon September 25, 2025 at 4:55 pm A practical, step-by-step guide to building an evaluation pipeline for a real-world AI application
The post Notes on LLM Evaluation appeared first on Towards Data Science.

 A practical, step-by-step guide to building an evaluation pipeline for a real-world AI application
The post Notes on LLM Evaluation appeared first on Towards Data Science. Read More 

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Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2Towards Data Science

Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2Towards Data Scienceon September 25, 2025 at 12:32 pm Deploying a FastAPI + PostgreSQL recommender system as a web application on Render
The post Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 appeared first on Towards Data Science.

 Deploying a FastAPI + PostgreSQL recommender system as a web application on Render
The post Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 appeared first on Towards Data Science. Read More 

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AI News September 09 25 2025 | 24-Hour Intelligence Update

AI News September 09 25 2025 | AI Morning Brief Executive Summary Microsoft fundamentally alters the enterprise AI landscape. The software giant adds Anthropic’s Claude models to Copilot on Wednesday, ending OpenAI’s monopoly on its flagship AI assistant. Markets responded with caution as AI stocks declined for a second day, with Oracle announcing a $15 […]

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Latest AI News September 09 24 2025 | AI Morning Brief

AI News September 09 24 2025 | 24-Hour Intelligence Update Executive Summary Three major developments reshaped the AI landscape yesterday. OpenAI’s massive infrastructure expansion gained momentum with five new data center sites worth $400 billion. Microsoft made a strategic pivot by integrating Anthropic’s Claude models into Copilot, diversifying beyond OpenAI for the first time in […]

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Securing Educational LLMs: A Generalised Taxonomy of Attacks on LLMs and DREAD Risk Assessmentcs.AI updates on arXiv.org

Securing Educational LLMs: A Generalised Taxonomy of Attacks on LLMs and DREAD Risk Assessmentcs.AI updates on arXiv.orgon August 13, 2025 at 4:00 am arXiv:2508.08629v1 Announce Type: cross
Abstract: Due to perceptions of efficiency and significant productivity gains, various organisations, including in education, are adopting Large Language Models (LLMs) into their workflows. Educator-facing, learner-facing, and institution-facing LLMs, collectively, Educational Large Language Models (eLLMs), complement and enhance the effectiveness of teaching, learning, and academic operations. However, their integration into an educational setting raises significant cybersecurity concerns. A comprehensive landscape of contemporary attacks on LLMs and their impact on the educational environment is missing. This study presents a generalised taxonomy of fifty attacks on LLMs, which are categorized as attacks targeting either models or their infrastructure. The severity of these attacks is evaluated in the educational sector using the DREAD risk assessment framework. Our risk assessment indicates that token smuggling, adversarial prompts, direct injection, and multi-step jailbreak are critical attacks on eLLMs. The proposed taxonomy, its application in the educational environment, and our risk assessment will help academic and industrial practitioners to build resilient solutions that protect learners and institutions.

 arXiv:2508.08629v1 Announce Type: cross
Abstract: Due to perceptions of efficiency and significant productivity gains, various organisations, including in education, are adopting Large Language Models (LLMs) into their workflows. Educator-facing, learner-facing, and institution-facing LLMs, collectively, Educational Large Language Models (eLLMs), complement and enhance the effectiveness of teaching, learning, and academic operations. However, their integration into an educational setting raises significant cybersecurity concerns. A comprehensive landscape of contemporary attacks on LLMs and their impact on the educational environment is missing. This study presents a generalised taxonomy of fifty attacks on LLMs, which are categorized as attacks targeting either models or their infrastructure. The severity of these attacks is evaluated in the educational sector using the DREAD risk assessment framework. Our risk assessment indicates that token smuggling, adversarial prompts, direct injection, and multi-step jailbreak are critical attacks on eLLMs. The proposed taxonomy, its application in the educational environment, and our risk assessment will help academic and industrial practitioners to build resilient solutions that protect learners and institutions. Read More 

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Coconut: A Framework for Latent Reasoning in LLMsTowards Data Science

Coconut: A Framework for Latent Reasoning in LLMsTowards Data Scienceon August 12, 2025 at 5:54 pm Explaining Coconut (Training Large Language Models to Reason in a Continuous Latent Space) in simple terms
The post Coconut: A Framework for Latent Reasoning in LLMs appeared first on Towards Data Science.

 Explaining Coconut (Training Large Language Models to Reason in a Continuous Latent Space) in simple terms
The post Coconut: A Framework for Latent Reasoning in LLMs appeared first on Towards Data Science. Read More