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I just downloaded the latest 4 Billion parameter model. I hit ‘Run‘. After a while, the Google Colab instance crashes. Sounds familiar? Well this is bound to happen if we don’t pay attention to the required VRAM and what VRAM we are providing to the model. Quantization is something that can help you tackle this
Model Quantization Guide: Reduce Model Size 4x with PyTorch Read More »
Imagine stepping into your first data science interview—your palms are sweaty, your mind racing, and then… you get a question you actually know the answer to. That’s the power of preparation. With data science reshaping how businesses make decisions, the race to hire skilled data scientists is more intense than ever. For freshers, standing out
Top 100 Data Science Interview Questions and Answers (2026 Edition) Read More »
Agentic browsing is quickly becoming mainstream. People don’t just want AI agents to research products anymore. They want agents to actually buy things for them: compare options, place orders, handle payments, and complete the entire transaction. That’s where things started to break. Today’s commerce stack is fragmented. Every merchant, platform, and payment provider uses proprietary integrations. So even
How to Integrate Universal Commerce Protocol (UCP) with AI Agents? Read More »
AI-based coding agents are changing developer workflows. Proof – the arrival of Gemini 3 Pro in the Gemini CLI. It shows a significant advancement. For instance, it provides advanced reasoning, enhanced tool usage, and natural-language coding right in the terminal. Developers will be able to generate, fix, and refactor code without needing to break their flow by
Liquid Foundation Models (LFM 2) define a new class of small language models designed to deliver strong reasoning and instruction-following capabilities directly on edge devices. Unlike large cloud-centric LLMs, LFM 2 focuses on efficiency, low latency, and memory awareness while still maintaining competitive performance. This design makes it a compelling choice for applications on mobile
Large Language Models (LLMs) are the heart of Agentic systems and RAG systems. And building with LLMs is exciting until the scale makes them expensive. There is always a tradeoff for cost vs quality, but in this article we will explore the 10 best ways according to me that can slash costs for the LLM
10 Ways to Slash Inference Costs with OpenAI LLMs Read More »
Imagine a chatbot makes a joke, and the user gives it a negative feedback. The same agent is far funnier on the said topic a week later. This is what we mean by agent’s live adaptation. Most chat agents as of now are static programs in nature. They don’t really learn from user feedback during
Create an Agent that can Learn from Interactions using AutoGen Read More »
