Crack ML Interviews with Confidence: Data Preparation (20 Q&A)
Author(s): Shahidullah Kawsar Originally published on Towards AI. Data Scientist & Machine Learning Interview Preparation Data preparation is the foundation of every successful machine learning project. Before algorithms can learn, raw data must be collected, cleaned, understood, and transformed into a form …
TAI #198: Real-Time Speech AI Gets Serious: Google and OpenAI Race to Own the Voice Layer
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie Real-time speech AI has been progressing quietly for the past year, but the past few weeks have delivered enough to warrant a dedicated look. …
We Gave ChatGPT Our Raw Sales Data and Asked It to Build a Dashboard. A Senior Analyst Reviewed the Results.
Author(s): Gulab Chand Tejwani Originally published on Towards AI. We uploaded 14 months of real client sales data — 127,000 transactions, 8 product categories, 12 regions — to ChatGPT and asked it to build a complete analytics dashboard. Then I sat down …
The Smallest Thing in PyTorch Opens Half the GPU Stack
Author(s): Akilesh KR Originally published on Towards AI. This Image was generated by Gemini We are living in a time when AI systems are introduced with the kind of language people used to reserve for moon missions. Agents that browse.Agents that code.Agents …
From Extraction to Accuracy: Evaluating Extracted Invoice Data with LLM-as-a-Judge
Author(s): Krishnan Srinivasan Originally published on Towards AI. (A practical, end-to-end guide to building a ground-truth-based evaluation pipeline, complete with synthetic data and runnable SQL on Snowflake) In the earlier parts of this Agentic AI series, we explored how AI systems can …
Nobody Invented Attention. A Frustrated PhD Student Ran Out of Other Options.
Author(s): DrSwarnenduAI Originally published on Towards AI. Nobody Invented Attention. A Frustrated PhD Student Ran Out of Other Options. Dzmitry Bahdanau was not trying to invent the architecture that would eventually run inside every large language model on earth. Completely gibberish at …
Part 9: Data Manipulation in Data Merging and Joins
Author(s): Raj kumar Originally published on Towards AI. Every analysis that combines data from multiple sources faces the same fundamental question: how should these datasets align? Which records match? What happens when they don’t? These aren’t just technical decisions. They shape what …
Part 8: Data Manipulation in Grouping and Aggregation
Author(s): Raj kumar Originally published on Towards AI. Every business decision starts with a question. What are our total sales by region? Which product categories generate the most revenue? How do customer segments compare in profitability? These questions all share something in …
Part 7: Data Manipulation in Date and Time Handling
Author(s): Raj kumar Originally published on Towards AI. Time is the invisible thread that runs through almost every dataset you’ll encounter. Sales happen on specific dates. Transactions occur at precise moments. Events unfold across hours, days, and years. Yet despite how fundamental …
Does Water Break Math? DeepMind’s Physics-Informed Search for the $1,000,000 Singularity
Author(s): DrSwarnenduAI Originally published on Towards AI. Does Water Break Math? DeepMind’s Physics-Informed Search for the $1,000,000 Singularity There is a prize. Not the proof. Not the $1 million.The article discusses how DeepMind employed a Physics-Informed Neural Network to explore the Navier-Stokes …
I Built My Own Local AI Agent with OpenClaw + Obsidian: What Nobody Tells You
Author(s): Moun R. Originally published on Towards AI. A real field report on a VM Ubuntu setup: Docker, Telegram, persistent memory, guardrails, config errors, and genuinely useful lessons. Three weeks ago, I decided to stop paying for AI subscriptions I only use …
MCP (Model Context Protocol): Explained Simply
Author(s): Nisarg Bhatt Originally published on Towards AI. Here is something that does not get talked about enough. The AI tools you use every day, including ChatGPT, Claude, Cursor, whatever your favourite is, they all have the same quiet limitation. They know …
From Monolith to Microservices: A Developer’s Survival Guide in 2026
Author(s): FutureLens Originally published on Towards AI. From Monolith to Microservices: A Developer’s Survival Guide in 2026 The journey starting from monolithic architecture to microservices is a very big challenging nowadays yet rewarding one. As we are explore in the ins and …
TAI #195: GPT-5.4 and the Arrival of AI Self-Improvement?
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie Two stories dominated this week that look unrelated but tell the same story. On Wednesday, OpenAI released GPT-5.4, its most work-oriented frontier model to …
Oracle Is Firing 30,000 People to Pay for AI It Hasn’t Built Yet
Author(s): Menna Adly Originally published on Towards AI. If your company is “pivoting to AI,” your job might be funding the pivot. One desk. One cut badge. And a data center full of chalk outlines where the servers were supposed to go. …
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