DeFi

DeFi, short for Decentralized Finance, is a blockchain-based financial system that operates without traditional intermediaries like banks or brokers. It uses smart contracts on platforms like Ethereum to enable peer-to-peer financial services such as lending, borrowing, trading, and yield farming. The goal is to create open, permissionless, and transparent financial infrastructure accessible to anyone with an internet connection.

Also known as: Decentralized Finance, DeFi, Open Finance, Distributed Finance, Crypto Finance

🧊Why learn DeFi?

Developers should learn DeFi to build applications in the rapidly growing blockchain and cryptocurrency space, particularly for creating financial dApps (decentralized applications) that automate transactions and reduce reliance on centralized institutions. It's essential for roles in fintech, blockchain development, and when working on projects involving cryptocurrencies, tokenization, or innovative financial products like decentralized exchanges (DEXs) or lending protocols.

See how it ranks →

Compare DeFi

DeFi vs Traditional Finance→DeFi vs Centralized Finance→DeFi vs Fintech→

Learning Resources

DeFi Pulse Learn

Ethereum.org DeFi Guide

Coursera: Decentralized Finance (DeFi) Course

YouTube: DeFi Explained by Finematics

Book: 'The Infinite Machine' by Camila Russo

Related Tools

Ethereum Smart Contracts Blockchain Cryptocurrency Web3

Alternatives to DeFi

Traditional Finance Centralized Finance Fintech

Other Blockchain

Access Control is a fundamental security concept that governs how users, systems, or processes are granted or denied access to resources such as data, applications, or networks. It involves defining and enforcing policies to ensure that only authorized entities can perform specific actions, protecting against unauthorized use, modification, or disclosure. This is implemented through mechanisms like authentication, authorization, and auditing to maintain confidentiality, integrity, and availability in computing environments.

Access tokens are short-lived credentials used in authentication and authorization systems to grant secure access to protected resources, such as APIs or user data. They are typically issued by an authorization server after a user or application successfully authenticates, and they contain claims about the requester's identity and permissions. Tokens are commonly implemented using standards like OAuth 2.0 and OpenID Connect to enable stateless, scalable security in modern applications.

Ad-Based Monetization

Ad-based monetization is a revenue model where businesses generate income by displaying advertisements to users, typically in digital products like websites, mobile apps, or games. It involves integrating ad networks or platforms to serve ads, with revenue earned through models such as cost-per-click (CPC), cost-per-mille (CPM), or cost-per-action (CPA). This approach is common in free-to-use services, allowing developers to monetize user traffic without direct payments from end-users.

AI agents are autonomous systems that perceive their environment, make decisions, and take actions to achieve specific goals using artificial intelligence techniques. They combine machine learning, reasoning, and sometimes natural language processing to operate independently or semi-independently in dynamic environments. This concept is foundational in fields like robotics, game AI, and automated systems.

AI Integration refers to the process of incorporating artificial intelligence capabilities, such as machine learning models, natural language processing, or computer vision, into existing software systems, applications, or workflows. It involves connecting AI services, APIs, or custom models to enhance functionality, automate tasks, or provide intelligent insights. This enables systems to perform tasks like predictive analytics, automated decision-making, or personalized user experiences without building AI from scratch.

AI Safety is a multidisciplinary field focused on ensuring that artificial intelligence systems are developed and deployed in ways that are safe, reliable, and aligned with human values and intentions. It addresses risks such as unintended harmful behaviors, security vulnerabilities, and ethical concerns in AI systems, particularly as they become more advanced and autonomous. The goal is to prevent catastrophic outcomes and promote beneficial AI that serves humanity's interests.