Nitin

Building Robust Systems: Key Lessons from Designing Data-Intensive Applications Chapter 1

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Introduction If you’re involved in building software today, chances are you’re dealing with data. Lots of it. Maybe it’s user activity, sensor readings, financial transactions, or something else entirely. Martin Kleppmann’s phenomenal book, “Designing Data-Intensive Applications” (often called DDIA), is practically required reading for navigating this landscape. Let’s dive into some key takeaways from this essential … Read more

Tokenization

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Natural Language Processing (NLP) has revolutionized the way machines understand human language. But before models can learn from text, they need a way to break it down into smaller, understandable units. This is where tokenization comes in — a critical preprocessing step that transforms raw text into a sequence of meaningful components, or tokens. 🧠 … Read more

WebRTC Signaling & Connection Establishment

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What is Signaling in WebRTC, and Why is it Needed? WebRTC allows direct peer-to-peer (P2P) communication, but before two peers can connect, they need to exchange network and media information. This process is called signaling. Signaling is needed for: WebRTC does not define a signaling protocol. Developers must implement their own using available technologies like … Read more

WebRTC Fundamentals

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WebRTC (Web Real-Time Communication) is an open-source project that enables real-time communication between browsers and devices using peer-to-peer connections. It allows audio, video, and data sharing without requiring additional plugins or external software. How Does WebRTC Work? WebRTC works by establishing a direct connection between two peers (browsers or applications) to transmit media (audio/video) and … Read more

DeepSeek R1: A Deep Dive into Algorithmic Innovations

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The recent release of DeepSeek R1 has generated significant buzz in the AI community. While much of the discussion has centered on its performance relative to models like OpenAI’s GPT-4 and Anthropic’s Claude, the real breakthrough lies in the underlying algorithmic innovations that make DeepSeek R1 both highly efficient and cost-effective. This post explores the … Read more

Supervised Fine-Tuning (SFT)

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What is Supervised Fine-Tuning (SFT)? Supervised fine-tuning is a training strategy where a pre-trained language model is further refined on a carefully curated dataset of prompt-response pairs. The primary goal is to “teach” the model how to generate appropriate, contextually relevant, and human-aligned responses. Key points about SFT include: For many contemporary language models, SFT … Read more

Kokoro: High-Quality Text-to-Speech(tts) on Your CPU with ONNX

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The world of text-to-speech (TTS) has seen incredible advancements, but often these powerful models require hefty hardware like GPUs. But what if you could run a top-tier TTS model locally on your CPU? Enter Kokoro, a game-changing TTS model that delivers impressive results even on resource-constrained devices. Kokoro: Small but Mighty Kokoro stands out for … Read more

BM-25 Best Matching 25

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Introduction Understanding BM-25: A Powerful Algorithm for Information Retrieval Bm25 is an enhancement of the TF-IDF model that incorporates term frequency saturation and document length normalization to improve retrieval performance. When it comes to search engines and information retrieval, a vital piece of the puzzle is ranking the relevance of documents to a given query. … Read more

TF-IDF

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Introduction TF-IDF (Term Frequency-Inverse Document Frequency) is a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents (corpus). It combines two metrics: Term Frequency (TF) and Inverse Document Frequency (IDF). The TF-IDF value increases proportionally with the number of times a word appears in the … Read more