Browsing: Business & Startups

Most RAG demos stop at “upload a PDF and ask a question.” That proves the pipeline works. It doesn’t prove you understand it. These projects are designed to break in interesting ways. They surface bias, contradictions, forgotten context, and overconfident answers. That’s where real RAG learning starts. Once you’re through these, you would have an easier time understanding and fixing RAG systems. Read the tips at the end for pointers to help with building these projects: 1. RAG-powered Lawyer A RAG system that doesn’t accept your premise at face value. When you ask a question framed as a claim, it…

Image by Author   # Introduction  Learning AI today is not just about understanding machine learning models. It is about knowing how things fit together in practice, from math and fundamentals to building real applications, agents, and production systems. With so much content online, it is easy to feel lost or jump between random tutorials without a clear path. In this article, we will learn about the 10 of the most popular and genuinely useful GitHub repositories for learning AI. These repos cover the full spectrum, including generative AI, large language models, agentic systems, mathematics for ML, computer vision, real-world projects,…

The name Google has always been synonymous with technology, and things are no different in the age of AI. Google has quietly been the frontrunner in the AI revolution with a host of products that surprisingly few people know about. Of course, the showstoppers like Gemini and NotebookLM have been popular, but their capabilities have not been explored to the max by many. The level of integration that Google has enabled for these (and other) AI tools across its ecosystem is second to none. From workflows to education, Google’s AI is gradually changing our online habits, and these tools are…

Image by Editor   # Introduction  Running large language models (LLMs) locally only matters if they are doing real work. The value of n8n, the Model Context Protocol (MCP), and Ollama is not architectural elegance, but the ability to automate tasks that would otherwise require engineers in the loop. This stack works when every component has a concrete responsibility: n8n orchestrates, MCP constrains tool usage, and Ollama reasons over local data. The ultimate goal is to run these automations on a single workstation or small server, replacing fragile scripts and expensive API-based systems.   # Automated Log Triage With Root-Cause Hypothesis Generation…

In machine learning with categorical data, it is common to encode the categories as dummy variables (sometimes called one hot encoding) to encode categories as numerical values. This is a significant step since there are many algorithms that do not operate on other things other than numbers like linear regression. Nevertheless, there is one of the mistakes that beginners are likely to make. It is referred to as the dummy variable trap. This problem is better understood at the outset to avoid the confounding of model outcomes and other unwarranted flaws. What Are Dummy Variables and Why are They Important?  Most machine…

Image by Editor   # Introduction  Coding has traditionally been a major pillar of most software engineers’ and developers’ work, be it by implementing algorithms, building business logic, or maintaining complex systems. But due to the progress made by large language model (LLM)-powered applications like chatbots, this is rapidly changing. vibe coding entails using modern chatbot apps to specify software requirements and intent in natural language, and delegating to artificial intelligence (AI) the generation and modification of code, sometimes with little direct understanding of its inner logic. This article adopts an “expectations vs reality” approach to demystify, based on research of…

The beginning of a new year brings about a new sense of energy in most. One may argue that it is all psychological, as nothing changes other than the date. Agreed, to a point. Though it is psychological, the change is not just based on the onset of a “new year.” A deep-rooted logical reasoning is that the new year acts much like a complete “reset,” leading to a new “starting point” of sorts. Everything you do from now on can be easily mapped, in days, weeks, and months, all up to the next year. So if you have made…

Image by Author   # Introduction  At a high level, data science is about making sense of data and AI engineering is about building intelligent systems. But you need to know more than that to make a career choice. Data scientists work with data. Their job is to collect, clean, analyze, and model data to answer specific questions. Their work involves statistical analysis, predictive modeling, experimentation, and visualization, with the goal of producing insights that inform business decisions. AI engineers focus on building AI-powered applications. They design and implement systems that use AI models — such as chatbots, retrieval-augmented generation (RAG)…

Learning Python at the beginning feels deceptively simple. You write a few lines, the code runs, and it’s tempting to think you’ve got it. Then you try to build something on your own and… nothing works!? Turns out all the information you had learnt, didn’t find an outlet.  That’s where challenging projects matter. Not flashy ones. Not giant apps. Just projects that force you to think, break things, and slowly connect the dots between syntax and real behavior. This list is about fundamentals. The Python projects that would kickstart your programming journey. If you’re not a beginner then these Python…

Image by Editor   # Introduction  As we look forward to what may transpire in AI this year, it’s good to take stock of what happened in 2025. And a lot happened. It would be too much to go through everything, obviously, but focusing on ten of the top developments is certainly possible. The list is subjective, as quantifying and directly comparing such developments in any meaningful way would be impossible, but I believe this list we have come up with is representative of both the broad and the effectual nature of AI stories of 2025. While I would find it…