You probably don’t need a Vector Database (Yet) for your RAG
Author(s): Thomas Reid Originally published on Towards AI. Numpy and/or SciKit-Learn might meet all your retrieval needs Right now, off the back of Retrieval Augmented Generation (RAG), vector databases are getting a lot of attention in the AI world. Image by Nano …
The 6 Essential Prompt Engineering Techniques: How to Get 10× Better Results from the Same LLM
Author(s): TANVEER MUSTAFA Originally published on Towards AI. Understanding Zero-Shot, Few-Shot, Chain-of-Thought, Self-Consistency, Tree of Thoughts, and ReAct You ask an LLM to analyze market trends. It gives a vague, generic response. Your colleague asks the same model with a different prompt …
Context Engineering: The 6 Techniques That Actually Matter in 2026 ( A Comprehensive Guide )
Author(s): Divy Yadav Originally published on Towards AI. Prompt engineering is dead. Context engineering is how production systems work now. Your RAG system returns perfect chunks. Your prompt is beautifully crafted But The LLM still hallucinates. Photo by AuthorThe article discusses the …
Latent Space: The Most Important Place That Doesn’t Exist
Author(s): Ampatishan Sivalingam Originally published on Towards AI. How AI navigates invisible dimensions to understand reality, and why you should care Every time you prompt an AI to create a “cyberpunk cat playing jazz,” you are navigating a multi-dimensional map you cannot …
20 Must Visit SQL Questions For Interviews
Author(s): Ananya Originally published on Towards AI. Q1. Find the total number of orders placed by a customer (101) in a day. Table: Order_Details cust_id | order_id | order_date Code: select date_trunc(‘day’, order_date) as day, cust_id as customers count(distinct order_id) as orders …
What Are World Models? The Blueprint for the Next Decade of AI
Author(s): Ampatishan Sivalingam Originally published on Towards AI. We built machines that can talk. Now we’re building machines that can think, plan, and imagine, before they ever act. A toddler reaches for a stack of wooden blocks. She doesn’t just see the …
The 6 Optimization Algorithms: How AI Learns to Learn 10× Faster with 50% Less Memory
Author(s): TANVEER MUSTAFA Originally published on Towards AI. The 6 Optimization Algorithms: How AI Learns to Learn 10× Faster with 50% Less Memory You’re training a language model with 175 billion parameters. Image generated by Author using AIThis article explores six optimization …
GPU and CPU Utilization While Running Open-Source LLMs Locally using Ollama
Author(s): Muaaz Originally published on Towards AI. Large Language Models (LLMs) are powerful, but running them locally requires significant hardware resources. Many users rely on open-source models due to their accessibility, as closed source models often come with restrictive licensing and high …
I Analyzed 5,000 DAX Measures. Here Are The 5 Patterns That Kill Performance.
Author(s): Gulab Chand Tejwani Originally published on Towards AI. 18 seconds for one measure. The dashboard was unusable. I analyzed 5,247 DAX measures to find what kills performance. 78% had these 5 patterns. Fix one, get 14x faster. He clicks “Refresh” on …
The Roadmap of Mathematics for Machine Learning
Author(s): Tivadar Danka Originally published on Towards AI. A complete guide to linear algebra, calculus, and probability theory Understanding the mathematics behind machine learning algorithms is a superpower. Here’s the full roadmap for you.This article presents a comprehensive curriculum that guides readers …
3 Game-Changing Tools for Modern Data Science
Author(s): Mohamed Abdelsalam Originally published on Towards AI. Introduction The rise of LLMs facilitates “vibe coding,” making it fast to generate initial Python scripts. However, this ease creates a false sense of progress. Building professional-grade data products requires more than quick scripts; …
I “Vibe Coded” Using Cursor (No Code Required)
Author(s): Adi Insights and Innovations Originally published on Towards AI. I “Vibe Coded” Using Cursor (No Code Required) Andrej Karpathy’s new philosophy changes everything. Here is how I built a RAG app by just talking to my computer. Here is how I …
7 Powerful Prompt Engineering Techniques That Transform LLM Performance
Author(s): TANVEER MUSTAFA Originally published on Towards AI. 7 Powerful Prompt Engineering Techniques That Transform LLM Performance Prompt engineering is the critical skill of crafting instructions that guide Large Language Models (LLMs) to produce reliable, structured outputs. This article explores how the …
Transformers v5 – Hugging Face’s Next Big Leap in Simple and Powerful AI Models
Author(s): Aniket Sanyal Originally published on Towards AI. Transformers v5 – Hugging Face’s Next Big Leap in Simple and Powerful AI Models Hugging Face has unveiled Transformers v5, the latest major release of its popular open-source library that powers many AI models …
The 4 Parameter-Efficient Fine-Tuning Methods: How to Adapt LLMs 100× Faster
Author(s): TANVEER MUSTAFA Originally published on Towards AI. The 4 Parameter-Efficient Fine-Tuning Methods: How to Adapt LLMs 100× Faster You want to customize GPT-3 for customer service. Traditional fine-tuning requires updating 175 billion parameters — 350GB storage per variant, weeks of training, …
Recent Posts
