What is Zero-Shot Learning?
Zero-shot learning is when an AI solves a new task without needing examples. It just understands what to do based on your instructions.
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What is Tokenization?
Tokenization is how language models break down human language into pieces they can understand and process — it's the gateway to everything else in NLP.
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What is Retrieval-Augmented Generation?
Retrieval-Augmented Generation (RAG) lets AI systems find and use real information — so they're grounded in your data, not just what they were trained on.
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What are AI Agents?
AI agents are smart programs that can plan, decide, and act on their own to reach a goal — kind of like how AI code assistants write and refactor code for you without you micromanaging every step.
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What is a Large Language Model (LLM)?
Large Language Models (LLMs) are the brain behind AI tools like ChatGPT. They generate text by predicting the next word, trained on huge datasets.
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What is Prompt Engineering?
Prompt engineering is how you 'talk' to AI tools. It’s the art of crafting instructions that guide large language models to do what you want.
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What is JSON-RPC?
JSON-RPC is a minimal protocol for calling remote functions using JSON. It's used in LLMs, blockchains, and tools like MCP to standardize interop.
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What is a Vector Database?
Vector databases store meaning, not just data. They help AI tools retrieve relevant info based on semantic similarity — essential for modern search and LLM grounding.
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What is Function Calling in LLMs?
Function calling lets LLMs trigger tools and APIs with structured outputs — powering agents, plugins, and real-world actions.
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How Do LLMs Use Tools?
Tool use allows LLMs to access external APIs and services — turning them into intelligent orchestrators, not just predictors.
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What is an Embedding?
Embeddings are how AI understands language. They turn words into numbers — where closeness means similarity — and power everything from search to recommendations.
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What is Context Length in LLMs?
Context length determines how much information an LLM can process at once. Learn how it works, why it matters, and how devs work around its limits.
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What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open standard that lets AI models interact with tools, data, and prompts securely and predictably — making agentic AI simpler to build.
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What is Fine-Tuning in LLMs?
Fine-tuning in LLMs involves adapting pre-trained language models to specific tasks or domains, enhancing their performance and efficiency in specialized applications.
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What is CI/CD?
CI/CD is the automation backbone of modern software delivery — helping teams build, test, and ship faster and with fewer bugs.
Software DevelopmentRead
What is Docker?
Docker is a container platform that packages applications and their dependencies into lightweight, portable containers — making development, testing, and deployment more consistent and scalable.
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What is a JavaScript Engine?
JavaScript engines are the virtual machines inside browsers and runtimes like Node.js that parse, optimize, and execute your JavaScript code.
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What is a Virtual Machine?
Virtual Machines (VMs) are software that emulate complete computers, allowing you to run multiple operating systems on a single physical machine with strong isolation.
InfrastructureRead
What is Rust?
Rust is a modern programming language that blends the performance of C with safety guarantees, making it ideal for system programming, WASM, and scalable backends.
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What is Serverless?
Serverless is a cloud model where you run code without managing infrastructure. Write small functions, deploy them instantly, and let the cloud handle everything else.
InfrastructureRead
What is Kubernetes?
Kubernetes is a container orchestration platform that manages the deployment, scaling, and operation of containerized applications across clusters of machines.
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What is a Container?
Containers package your app and its dependencies into a single, isolated unit that can run anywhere — consistently and securely.
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What is a Transformer Model?
Transformers are the neural network architecture behind large language models like GPT and BERT, enabling massive parallelism and context-aware learning.
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What is WebAssembly (WASM)?
WebAssembly (WASM) is a powerful binary format that lets you run fast, compiled code in the browser or on the edge — giving web apps access to near-native speed.
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What is Sparse Activation?
Sparse activation is a neural network technique where only a subset of neurons are active for each input, enabling efficient scaling of large models like Mixture of Experts.
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What is Quantization?
Quantization is a technique for making AI models smaller and faster by reducing the precision of their weights and activations, enabling efficient deployment on edge devices.
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What is Model Pruning?
Model pruning is a technique for making neural networks smaller and faster by removing unnecessary weights or neurons, enabling efficient deployment on edge devices.
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What is Knowledge Distillation?
Knowledge distillation is a technique for creating smaller, more efficient AI models by transferring knowledge from larger models, enabling practical deployment while maintaining good performance.
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What is Mixture of Experts (MoE)?
Mixture of Experts (MoE) is a neural network architecture that enhances efficiency and scalability by activating only relevant sub-networks (experts) for each input.
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What are Tiny LLMs?
Tiny LLMs are compact language models designed for efficiency, enabling AI to run on edge devices and with limited resources while maintaining strong performance.
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What is Conditional Computation?
Conditional computation is a neural network technique where only relevant parts of the model are activated for each input, enabling efficient scaling and resource use.
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What is ELI5?
ELI5 stands for "Explain Like I'm 5" – a way of breaking down complex topics into simple, easy-to-understand explanations.
Our ELI5 guides explain tech using:
- Simple language without unnecessary jargon
- Real-world analogies that make sense
- Visual explanations when possible
- A focus on the concepts you actually need to understand
Who is this for?
Perfect for junior developers, career-switchers, or anyone trying to make sense of the fast-moving tech world.
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