How to Stay Sane in the Age of Infinite AI Tools
Author(s): Hemanth Sanisetty Originally published on Towards AI. A practical guide to navigating hype, avoiding tool FOMO, and building a personal AI stack that actually works.AI generated image If you are not a medium member, read the full story here Every week, …
MCP — an Architectural Inflection Point
Author(s): Zoheb Abai Originally published on Towards AI. MCP Technical Components In today’s AI-driven development landscape, applications increasingly rely on sophisticated language models to power intelligent features. However, connecting these models to real-world external sources or services (tools), data sources, and APIs …
Fine Tuning LLM for Parsing and Serving Through Ollama
Author(s): Kaushik Holla Originally published on Towards AI. Source: By the Author Last week, I signed up for the Databricks conference happening in San Francisco, eager to explore new AI innovations. While reviewing the event schedule, one particular Lightning Talk by Mastercard …
How Meta Built Threads to Support 100 Million Signups in 5 Days
Author(s): Kalash Vasaniya Originally published on Towards AI. Generate your MCP server SpeakeasySource: From AI-Generated If you’re not a member but want to read this article, see this friend link here. Try here: https://www.speakeasy.com/ Like it or not, your API has a …
My Journey: Creating a Data Science with Python + GitHub
Author(s): Harshit Kandoi Originally published on Towards AI. “As an Engineering student, I panicked when recruiters asked for a portfolio until I built one that landed me interviews!” Photo by Anete Lūsiņa on Unsplash That moment of panic became real. In my …
From Noise to Numbers: Building a DCGAN for MNIST Generation Using PyTorch
Author(s): Souradip Pal Originally published on Towards AI. Imagine a neural network dreaming up handwritten digits so real, they fool even trained eyes — or sketching fashion items never seen before. This isn’t sci-fi. It’s the magic of Generative Adversarial Networks. First …
LAI #73: Vision-Language at Scale, o1’s Limits, RAG 2.0, and Multi-Agent Builders
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts, This week’s issue covers deploying in-house vision-language models for large-scale document parsing, and whether OpenAI’s o1 models have actually advanced reasoning, or just scaled search. We also cover …
What is Vibe Coding?
Author(s): Nehdiii Originally published on Towards AI. Image Source I’ve observed two intriguing trends that I believe will develop in parallel as the future of work unfolds. One reflects AI reasoning models leveraging agentic workflows to rethink traditional scientific methods like Google’s …
The Unauthorized Experiment: How AI Secretly Infiltrated Reddit and Changed Users’ Minds
Author(s): MKWriteshere Originally published on Towards AI. Image Generated by Author Using Gpt-4o (Non-Member Link) What if you discovered that the online stranger who changed your deeply held opinion wasn’t a person at all? This alarming scenario became reality for thousands of …
NVIDIA and Neural Rendering are Revolutionizing the $800B Metaverse
Author(s): Tim Urista | Senior Cloud Engineer Originally published on Towards AI. Info graphic created in canva The metaverse stands at a critical inflection point. While tech giants pour billions into building immersive virtual worlds, a stark reality remains: current rendering technologies …
Explainable AI: How to Make Machine Learning Decisions Understandable
Author(s): Jayita Gulati Originally published on Towards AI. Learn about Explainable AI and its Methods and how to implement them in Python.Photo by Randy Fath on Unsplash Imagine using an AI system to decide who gets a loan — but no one …
Handling Imbalanced Datasets in Machine Learning: SMOTE, Oversampling & Undersampling Explained
Author(s): Abinaya Subramaniam Originally published on Towards AI. Imbalanced Datasets — Image by Author What are imbalanced Datasets? In many real-world classification problems, the number of samples in each class is not balanced. This is called an imbalanced dataset. For example, in …
Building Smarter LLMs with LangChain and RAG: A Beginner’s Guide
Author(s): Harshit Kandoi Originally published on Towards AI. Photo by Alberto Moya on Unsplash Ever tried your hand at an LLM’s question and got a confident, slick solution that turned out to be completely wrong? I have — many times. I remember …
Is AGI merely a Silicon Valley illusion?
Author(s): Nehdiii Originally published on Towards AI. From OpenAI to DeepSeek, everyone now claims to be an AGI startup, but by 2025, the explosion of such companies is becoming overwhelming. On 14 April 2023, High-Flyer announced the start of an artificial general …
TAI #150: Qwen3 Impresses as a Robust Open-Source Contender
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, the AI spotlight turned to Alibaba’s Qwen team with the launch of Qwen3, a comprehensive new family of large language models. Offering …
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