Agentive AI

AI Agents and Data Handling at Scale The challenge of processing vast amounts of data with AI agents is a growing area of focus in the field. Recently, researchers have been exploring how to equip agents to handle large-scale datasets effectively within the context of AI frameworks. One key observation is that relying solely on […]

The date confusion experienced by some AI systems highlights a common problem: the accurate processing and presentation of temporal information. Several users have reported instances where AI models consistently displayed incorrect dates. This issue isn’t merely a cosmetic glitch; it underscores potential shortcomings in how these systems understand and manage time. The core issue frequently

The construction is underway. The question hangs in the air, repeated, almost a whisper: “They building Her, are they? Are they?” The repetitive nature highlights a sense of disbelief, perhaps a touch of apprehension. What exactly is being built? The imagery accompanying the text provides no immediate answers, leaving the reader to speculate. The subject,

The Gemini Live API is generating interest in the field of real-time interaction. Developers are eager to leverage its capabilities, particularly for creating applications that respond dynamically to user input. One key area of exploration involves multimodal input, where systems interpret both voice and camera data simultaneously. This enables a more intuitive and engaging user

The creation of AI agents based on television characters is an exciting development in the field of artificial intelligence. This project, now on its ninth day, focuses on building an AI agent modeled after Ross Geller from the popular sitcom *Friends*. The creators are using Blackbox AI to bring Ross’s personality to life. The goal

A widespread security flaw threatens over 1,500 AI projects. Recent research from ARIMLABS[.]AI has unveiled a critical vulnerability, designated CVE-2025-47241, within the Browser Use framework. This framework is a common component used in a large number of AI projects. The core problem is that this vulnerability allows for “zero-click agent hijacking.” This means an attacker

Many code review tools, including those powered by AI, primarily focus on the differences (diffs) between code versions. However, this approach often misses critical issues. Real bugs frequently lurk within the broader codebase, hidden in legacy logic, outdated assumptions, and forgotten code sections. This limited perspective can lead to regressions, increased technical debt, and delayed

The realm of AI agent development often involves interactions with Model Control Protocol (MCP) servers. A common approach is to establish a temporary connection, load necessary tools and instructions into memory, and then perform tasks. However, a persistent, always-on connection presents an alternative. The question arises: what situations might make an always-on connection to an