Important LLM Papers for the Week From 12/01/2026 To 17/01/2026
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Large Language Models Research Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers must stay informed about the latest …
No Libraries No Shortcuts: Reasoning LLMs from Scratch with PyTorch — Part 2
Author(s): Ashish Abraham Originally published on Towards AI. The no BS Guide to implementing reasoning models from scratch with SFT & RL In Part 1 of this series, we laid the groundwork for understanding how reasoning large language models (LLMs) can be …
DAX Measure Library Architecture: From Messy to Maintainable
Author(s): Gulab Chand Tejwani Originally published on Towards AI. How we stopped wasting $93,600 per year searching for measures we’d already built The Slack message appeared at 2:37 PM on a Tuesday. DAX Measure Library ArchitectureThe article discusses the author’s struggle to …
Unlocking the Magic of Adam: The Math Behind Deep Learning’s Favorite Optimizer
Author(s): Raaja Selvanaathan DATCHANAMOURTHY Originally published on Towards AI. Source: Author At the heart of every deep learning model lies a simple goal: minimizing error. We measure this error using something called a cost Function (or objective function). But knowing the error …
AI Agents in 2026: The Data Problem No One Mentions
Author(s): Ahmed M. Abdelfattah Originally published on Towards AI. Why vendors promise 3–5 employee productivity but Forrester finds 0% improvement and what your data infrastructure needs before deployment works Google Cloud claims AI agents deliver productivity equivalent to hiring 3–5 employees. Forrester’s …
AI’s Next Strategic Phase: From Lab Curiosity to Core Economy Driver
Author(s): Vivek Acharya Originally published on Towards AI. AI’s Next Strategic Phase: From Lab Curiosity to Core Economy Driver AI is undergoing a profound strategic shift. Not long ago, success in AI was measured by flashy model demos and incremental accuracy gains. …
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, …
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