Ai

Introduction I’ve been doing a lot of research on AI agents recently, exploring different frameworks, architectures, and models. The speed of innovation is incredible, especially the recently released Large Language Models (LLMs) Claude Opus 4.6 and Claude Sonnet 4.6, and OpenAI’s GPT 5.3 Codex. What I’ve found is that it really helps to try different models and see which one fits your use case best. For example, Claude Opus 4.6 and GPT 5.3 Codex really take the time to understand the codebase before making changes when you use them in agent mode, they analyze the full context, read related files, and plan their edits rather than jumping straight to code generation. However, one good thing I find very helpful is to make multiple iterations with different models and compare the results side by side to see which one is better for your specific use case. This also gives you more insight into how different models approach the same problem, which can be very valuable when you’re building for example an AI agent. It’s also a learning process. ...

Exploring NotebookLM’s Audio Overview Feature Context Recently, Google introduced an exciting new feature for NotebookLM: Audio Overview. For those unfamiliar, NotebookLM is a personal AI-powered research assistant (powered by Gemini 1.5 Pro) designed for efficient summarization and note-taking. By uploading your documents, whether PDFs, websites, or text files, NotebookLM analyzes and organizes the content. This allows you to interact with it in various ways. The Audio Overview feature, in particular, caught my attention. It essentially creates a podcast-like experience where two AI hosts discuss your research topic in real time. This conversational format offers a unique way to engage with your content, which can make complex topics more accessible and enjoyable. What’s even better? You can guide the discussion by providing specific instructions, ensuring the conversation focuses on aspects most relevant to you. ...

Introduction In this blog post, we will explore how to integrate Azure Functions with the OpenAI extension. This integration allows you to use triggers and bindings with the powerful capabilities of OpenAI within your serverless functions. We will walk through the setup, configuration, and deployment of an Azure Functions project that uses the OpenAI extension, using Bicep templates for infrastructure as code. Prerequisites Before we begin, ensure you have the following tools and resources: ...

In today’s digital age, extracting text from images has become a common task in various domains, from document digitization to text analysis. Optical Character Recognition (OCR) engines like Tesseract have played a significant role in making this process efficient and accessible. However, improving the accuracy and usability of OCR systems remains a challenge. In this blog post, we’ll explore (based on two examples) how to enhance text extraction from images using Tesseract in conjunction with OpenAI’s Generative AI capabilities. ...