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....
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 […]...
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...
Grok Voice Think Fast 1.0: Build Voice AI Agents That Actually Think
Voice assistants that engage in back-and-forth communication are something you’ve likely experienced. But a voice assistant that provides rational, uninterrupted exchanges via spoken dialogue? That’s what xAI delivered with their Grok Voice Think Fast 1.0 in April 2026 and instantly, it became the t...
Compressing LSTM Models for Retail Edge Deployment: A Practical Comparison
There can be some practical constraints when it comes to deploying the AI models for retail environments. Retail environments can include store-level systems, edge devices, and budget conscious setup, especially for small to medium-sized retail companies. One such major use case is demand forecastin...
Google Deep Research Max: Build Autonomous AI Research Agents in Minutes
Google just changed how developers do research. On April 21, 2026, they launched Deep Research Max. It runs on Gemini 3.1 Pro and is not just another chatbot upgrade. This is an autonomous AI research agent. It plans, searches, reads, reasons, and writes, all from a single API call. By the end, you ...
Cursor V3 Explained: The AI Coding Agent That’s Replacing Traditional IDEs in 2026
In 2026, AI-powered coding tools began revolutionizing software development, with Cursor v3 emerging as a leading example. Unlike traditional development environments, Cursor v3 offers a new way for developers to interact with their code by utilizing AI agents that assist in coding tasks. Cursor v3 ...
DeepSeek-V4: The Most Powerful Open-Source Model Ever
The latest set of open-source models from DeepSeek are here. While the industry anticipated the dominance of “closed” iterations like GPT-5.5, the arrival of DeepSeek-V4 has ticked the dominance in the favour of open-source AI. By combining a 1.6 trillion parameter MoE architecture with a massive 1 ...
OpenAI is on a roll! While the company had everyone going gaga over its new image generation model, the ChatGPT Images 2.0, it decided now is not the time to stop. And lo and behold, out comes another banger from its offices, and mind you, this is the bigger one. The new version of its […]
The post ...
Design has traditionally required multiple roles working in sequence: a strategist to define the problem, a designer to shape the solution, and a developer to build it. This means coordinating timelines, aligning opinions, and going through rounds of iteration before anything tangible is created. Cl...
Build Human-Like AI Voice App with Gemini 3.1 Flash TTS
AI voice generation has a major problem. It works like a robot, reading a script phrase by phrase, with no feelings or emotions. It might be clever, but it matters less if there is no human feeling attached to it. The way the AI generates its voice makes it hard to feel like you’re having […]
The po...
Anthropic Launches Claude Opus 4.7 For “Most Difficult Tasks”
Artificial intelligence is rapidly developing. The minute we become accustomed to one breakthrough, another comes to shift our expectations. The new model, Claude Opus 4.7, that Anthropic introduced recently, is one such shift. The release tends to go beyond mere AI chatbots and makes AI a trusted, ...
OpenAI Announces GPT-5.4-Cyber But You Can’t Get it Just Yet
The question around AI, and I mean the pinnacle of AI, not your regular “write me an email”, is shifting. What used to be “what can it do for me?” has now become “who gets to use it?” We saw this recently with Anthropic’s Claude Mythos Preview – a supposed epitome of AI models that […]
The post Open...
Mastering Deep Agents: Context Engineering that Actually Works
Deep Agents can plan, use tools, manage state, and handle long multi-step tasks. But their real performance depends on context engineering. Poor instructions, messy memory, or too much raw input quickly degrade results, while clean, structured context makes agents more reliable, cheaper, and easier ...
We have come far in our series of Excel 101, exploring various functions and formulas of the service and how best to use them in real-world scenarios. For those who are new to this, make sure to check out the complete list of Excel functions that we have covered so far in the links shared […]
The po...
MiniMax M2.7 Goes Open-Weight to Let You Run Agents Locally
Following in the footsteps of the recently released Gemma 4, MiniMax has now made its latest model, MiniMax M2.7, completely open-weight. In simple terms, developers can now download the model, run it on their own systems, and start building with it. This is in contrast with the model being a comple...
Understanding BERTopic: From Raw Text to Interpretable Topics
Topic modeling uncovers hidden themes in large document collections. Traditional methods like Latent Dirichlet Allocation rely on word frequency and treat text as bags of words, often missing deeper context and meaning. BERTopic takes a different route, combining transformer embeddings, clustering, ...