Prompt Repetition Boosts LLM Accuracy 76% Without Latency Increase
Author(s): MKWriteshere Originally published on Towards AI. How repeating prompts twice improves the non-reasoning model accuracy from 21% to 97% while maintaining zero latency overhead I avoid reasoning models in production. Latency kills user experience, and the token costs add up quickly …
Building a Self-Updating Knowledge Graph From Meeting Notes With LLM Extraction and Neo4j
Author(s): Cocoindex Originally published on Towards AI. Transform unstructured meeting notes into a queryable knowledge graph with incremental updates — no full reprocessing required. Meeting notes are goldmines of organizational intelligence. They capture decisions, action items, participant information, and the relationships between …
Synthetic Data That Behaves: A Practical Guide to Generating Realistic Healthcare-Like Data Without Violating Privacy
Author(s): Abhishek Yadav Originally published on Towards AI. A hands-on guide to building synthetic data that looks, feels, and behaves like the real world without privacy risk Photo by Luke Chesser on Unsplash Healthcare organizations sit on treasure chests of data be …
Vector Databases: Unlocking the Future of Intelligent AI and Semantic Search
Author(s): Hayanan Originally published on Towards AI. How AI Learns Meaning, Not Just Keywords Modern AI systems are no longer judged by how fast they retrieve data, but by how well they understand it. As users interact with applications in increasingly natural …
How to Conduct a Literature Review in AI & Machine Learning
Author(s): Ayo Akinkugbe Originally published on Towards AI. A Technical Guide to Surveying, Synthesizing, and Positioning Your AI Research Photo by Kristine Wook on Unsplash What’s So Lit About a Lit Review? A literature review is the backbone of any meaningful research …
Why Your Power BI Report is Slow: A 10-Minute Performance Audit
Author(s): Gulab Chand Tejwani Originally published on Towards AI. The diagnostic framework that helped me fix a 43-second dashboard in 30 minutes — and saved my job The email came at 9:47 PM on a Thursday. Why Your Power BI Report is …
Can You Predict a Subway Delay Before Transit Officials Announce It?
Author(s): Charlie Taggart Originally published on Towards AI. How I used MBTA train telemetry and machine learning to call out service breakdowns 30+ minutes early I‘m consider myself a patient person. But nothing tests that patience like standing on a T platform …
The Complete Guide to Guardrails: Building AI Agents That Won’t Go Rogue
Author(s): Divy Yadav Originally published on Towards AI. Photo by Gemini Note: If you’re implementing guardrails soon, this is essential reading; pair it with LangChain’s official docs for edge cases. Let’s begin Picture this: You’ve built an AI agent to handle customer …
From Basic RAG to Advanced Retrieval: A Practical Roadmap Using the Modern RAG Stack
Author(s): Anubhav Originally published on Towards AI. Build intelligent, adaptive AI that understands and utilizes all your data sources General-purpose LLMs are incredible, but they have a fundamental blind spot: your data. Their knowledge was frozen at a specific point in time, …
Setting Up TensorFlow with GPU (CUDA): A Step-by-Step Installation Guide
Author(s): Muaaz Originally published on Towards AI. If you are writing Deep Learning code on a machine with a GPU, TensorFlow will default to running on the CPU. This happens because TensorFlow does not automatically select the best hardware. To use the …
Why 90% of Agentic RAG Projects Fail (And How to Build One That Actually Works in Production)
Author(s): Divy Yadav Originally published on Towards AI. Photo by Gemini Most enterprise AI pilots fail. McKinsey’s research found only 10–20% of AI proofs-of-concept scale beyond pilots. Why? Teams treat production systems like demos. I’ve seen companies spend six months building agentic …
This is How Google Finally Fixed AI Images: The Secret Sauce Behind “Nano Banana”
Author(s): Sayan Chowdhury Originally published on Towards AI. This is How Google Finally Fixed AI Images: The Secret Sauce Behind “Nano Banana” If you’ve been on the internet in the last six months, you’ve seen them: those hyper-realistic 3D figurines of your …
The “Sora” Trap: Why Meta’s V-JEPA 2 Proves That Hallucinating Pixels is Not “Planning”
Author(s): Siddharth M Originally published on Towards AI. While the world obsesses over AI video generation, a team at Meta just dropped a 1-Billion parameter “World Model” that plans robot actions by ignoring reality’s noise. Here is the definitive engineering deep dive …
Claude Just Broke Bioinformatics
Author(s): Gowtham Boyina Originally published on Towards AI. Anthropic’s secret plugin marketplace lets AI auto-search PubMed, analyze single-cell data, and generate publication-ready figures — no more switching tabs. (And it’s already live.) If you’ve used Claude Code for bioinformatics or research, you’ve …
We’ve Been Building AGI Wrong This Whole Time
Author(s): Gaurav Shrivastav Originally published on Towards AI. AGI isn’t about smarter models — it’s about giving them the right tools. I realized something uncomfortable last week. Image Credit: Nano Banana ProThe article discusses the misconception that advancing Artificial General Intelligence (AGI) …
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