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5 Essential Security Patterns for Robust Agentic AIImage by Editor Introduction Agentic AI, which revolves around autonomous software entities called agents, has reshaped the AI landscape and influenced many of its most visible developments and trends in recent years, including…
Google has officially released Android Bench, a new leaderboard and evaluation framework designed to measure how Large Language Models (LLMs) perform specifically on Android development tasks. The dataset, methodology, and test harness have been made open-source and are publicly available…
OpenAI has introduced Codex Security, an application security agent that analyzes a codebase, validates likely vulnerabilities, and proposes fixes that developers can review before patching. The product is now rolling out in research preview to ChatGPT Enterprise, Business, and Edu…
In this article, you will learn how vector databases and graph RAG differ as memory architectures for AI agents, and when each approach is the better fit. Topics we will cover include: How vector databases store and retrieve semantically similar…
Liquid AI has released LFM2-24B-A2B, a model optimized for local, low-latency tool dispatch, alongside LocalCowork, an open-source desktop agent application available in their Liquid4All GitHub Cookbook. The release provides a deployable architecture for running enterprise workflows entirely on-device, eliminating API…
In this tutorial, we explore how we use Daft as a high-performance, Python-native data engine to build an end-to-end analytical pipeline. We start by loading a real-world MNIST dataset, then progressively transform it using UDFs, feature engineering, aggregations, joins, and…
Integrating Google Workspace APIs—such as Drive, Gmail, Calendar, and Sheets—into applications and data pipelines typically requires writing boilerplate code to handle REST endpoints, pagination, and OAuth 2.0 flows. Google AI team just released a CLI Tool (gws) for Google Workspace.…
OpenAI has released Symphony, an open-source framework designed to manage autonomous AI coding agents through structured ‘implementation runs.’ The project provides a system for automating software development tasks by connecting issue trackers to LLM-based agents.…
In this tutorial, we build an advanced Tree-of-Thoughts (ToT) multi-branch reasoning agent from scratch. Instead of relying on linear chain-of-thought reasoning, we design a system that generates multiple reasoning branches, scores each branch using a heuristic evaluation function, prunes weak…
