OpenAI’s New API Voice Models Will Change the Way You Use AI
There are some obvious signs that can instantly differentiate between regular and advanced AI users. One, for instance, is the use of voice AI for daily tasks. While majority users still toil away on their keyboard for the perfect prompt, a person proficient in the use of AI now simply speaks to it....
Build an AI-Powered Learning Management System That Actually Trains People
Learn how to build an AI-powered Learning Management System from scratch using Ollama, FastAPI, and React. A step-by-step guide for beginner and intermediate developers.
Agent Memory Patterns in Cognitive Science and AI Systems
Memory shapes how humans think and how AI agents act. Without it, an agent only responds to the current input; with it, it can keep context, recall past actions, and reuse useful knowledge. AI memory spans short-term, episodic, semantic, and long-term memory, each with different design trade-offs ar...
10 AI Agents Every AI Engineer Must Build (with GitHub Samples)
If you’re an aspiring AI engineer looking to sharpen your skills, building AI agents is one of the most effective ways to get hands-on experience. AI agents represent practical applications of AI across domains, from personal assistants and recommendation systems to financial traders. Here are 10 AI...
Feature Engineering with LLMs: Techniques & Python Examples
Feature engineering is the foundation of strong machine learning systems, but the traditional process is often manual, time-consuming, and dependent on domain expertise. While effective, it can miss deeper signals hidden in unstructured data such as text, logs, and user interactions. Large Language ...
Anthropic’s 10 AI Agents are Redefining Finance Work
The headline may sound extreme here. Of course, Claude is not replacing CFOs tomorrow morning. But with the debut of Claude’s new Financial Services Solution by Anthropic, it has clearly moved to a new direction in the world of finance, one where AI does way more than crunch numbers or explain stuff...
Building a RAG system just got much easier. Google’s File Search tool for the Gemini API now handles the heavy lifting of connecting LLMs to your data. Chunking, embedding, indexing are all managed for you. And with the latest update, it’s gone multimodal. You can now search through both text and im...
ML Intern in Practice: From Prompt to a Shipped Hugging Face Model
Most ML projects do not fail because of model choice. They fail in the messy middle: finding the right dataset, checking usability, writing training code, fixing errors, reading logs, debugging weak results, evaluating outputs, and packaging the model for others. This is where ML Intern fits. It is ...
Projects are the bridge between understanding AI and actually building with it. While the last couple of years were dominated by generative models, the shift now is toward systems that can think in steps, use tools, and act with a clear objective. This guide brings together over 15 solved agentic AI...
AI chatbots are the new norm. What earlier was “ask Google” has now largely become “ask Claude”. And that is not just a change of platforms. The new form of conversational guidance goes a whole lot deeper than trying to find the best car for you or looking for an upskilling course. It now spills […]...
The “Robust” Data Scientist: Winning with Messy Data and Pingouin
This article uncovers the craftsmanship of using robust statistics in data science processes: illustrating what to do when data fail tests due to not meeting standard assumptions.
MemPalace Explained: Building Long-Term Memory for AI Agents Beyond RAG
Modern AI systems struggle with memory. They often forget past interactions or rely on Retrieval-Augmented Generation (RAG), which depends on constant access to external data. This becomes a limitation when building assistants that need both historical context and a deeper understanding of users. Me...