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Whenever I am to suggest a new AI tool to someone who is just starting out, there is one name I know can bring them unprecedented value. NotebookLM, the famous AI tool by Google, is just one-too-many solutions wrapped into a neat package of an “AI research tool.” It can summarise your notes, find you answers from deep within, create podcasts in seconds, and even help you learn with a plethora of visual aids. And now, Google has further improved it with a new upgrade – NotebookLM now has Cinematic Video Overview. The name of the latest NotebookLM feature is…

You don’t always go for a benchmark score to see which AI model fits your needs. Even the highest ranking models sometimes seem to miss the essence of a conversation entirely. What matters then is how fluid and helpful your conversations with AI are. Taking a step in this direction, OpenAI has now introduced an update to the GPT-5.3 Instant, with a focus on quick responses, but in a better way than ever before on ChatGPT. How? The new update marks improvement in core user experiences like tone, relevance, and conversational flow. OpenAI says that the GPT‑5.3 Instant is a…

Image by Author   # Introduction  Most engineers encounter system design when preparing for interviews, but in reality, it is much bigger than that. System design is about understanding how large-scale systems are built, why certain architectural decisions are made, and how trade-offs shape everything from performance to reliability. Behind every app you use daily, from messaging platforms to streaming services, there are careful decisions about databases, caching, load balancing, fault tolerance, and consistency models. What makes system design challenging is that there is rarely a single correct answer. You are constantly balancing cost, scalability, latency, complexity, and future growth. Should…

Image by Author   # Introduction  If you’ve been working with data in Python, you’ve almost certainly used pandas. It’s been the go-to library for data manipulation for over a decade. But recently, Polars has been gaining serious traction. Polars promises to be faster, more memory-efficient, and more intuitive than pandas. But is it worth learning? And how different is it really? In this article, we’ll compare pandas and Polars side-by-side. You’ll see performance benchmarks, and learn the syntax differences. By the end, you’ll be able to make an informed decision for your next data project. You can find the code…

Instruction-based image editing models are impressive at following prompts. But when edits involve physical interactions, they often fail to respect real-world laws. In their paper “From Statics to Dynamics: Physics-Aware Image Editing with Latent Transition Priors,” the authors introduce PhysicEdit, a framework that treats image editing as a physical state transition rather than a static transformation between two images. This shift improves realism in physics-heavy scenarios. AI Image Generation Failures You generate a room with a lamp and ask the model to turn it off. The lamp switches off, but the lighting in the room barely changes. Shadows remain inconsistent. The instruction is…

Image by Author   # Introduction  As a data scientist or analyst, you know that understanding your data is the foundation of every successful project. Before you can build models, create dashboards, or generate insights, you need to know what you’re working with. But exploratory data analysis, or EDA, is annoyingly repetitive and time-consuming. For every new dataset, you probably write almost the same code to check data types, calculate statistics, plot distributions, and more. You need systematic, automated approaches to understand your data quickly and thoroughly. This article covers five Python scripts designed to automate the most important and time-consuming…

Image by Editor   # Introduction  Data science projects usually begin as exploratory Python notebooks but need to be moved to production settings at some stage, which might be tricky if not planned carefully. QuantumBlack’s framework, Kedro, is an open-source tool that bridges the gap between experimental notebooks and production-ready solutions by translating concepts surrounding project structure, scalability, and reproducibility into practice. This article introduces and explores Kedro’s main features, guiding you through its core concepts for a better understanding before diving deeper into this framework for addressing real data science projects.   # Getting Started With Kedro  The first step to…

Time series data drives forecasting in finance, retail, healthcare, and energy. Unlike typical machine learning problems, it must preserve chronological order. Ignoring this structure leads to data leakage and misleading performance estimates, making model evaluation unreliable. Time series cross-validation addresses this by maintaining temporal integrity during training and testing. In this article, we cover essential techniques, practical implementation using ARIMA and TimeSeriesSplit, and common mistakes to avoid. What is Cross Validation? Cross-validation serves as a basic technique which machine learning models use to evaluate their performance. The procedure requires dividing data into various training sets and testing sets to determine…

Image by Author   Introduction  Agentic AI refers to AI systems that can make decisions, take actions, use tools, and iterate toward a goal with limited human intervention. Instead of answering a single prompt and stopping, an agent evaluates the situation, chooses what to do next, executes actions, and continues until the objective is achieved. An AI agent combines a large language model for reasoning, access to tools or APIs for action, memory to retain context, and a control loop to decide what happens next. If you remove the loop and the tools, you no longer have an agent. You…

Image by Editor   # Introduction  Creating a Product Requirements Document (PRD) is a common process in product management and a commonplace task in sectors like software development and the tech industry as a whole. But the story doesn’t end with a PRD, and the next big step is turning it into a product, e.g. a functioning software. This article follows up from this one, in which we turned a set of raw, messy pieces of information into a grounded PRD, and navigates you through the same use case (a mobile-friendly app called FloraFriend) to turn this PRD into a functioning…