Artificial Intelligence Guides

Learn Artificial Intelligence from the basics to intermediate level. Token Tool Hub offers practical guides on machine learning, neural networks, and AI’s role in blockchain and crypto

MEV Sandwich Detection at Scale: Implementation Guide + Pitfalls

Intermediate Track /

MEV Sandwich Detection at Scale: Implementation Guide + Pitfalls MEV Sandwich Detection at Scale is not a single heuristic and it is not a dashboard that flags a block as “bad”. It is an end to end engineering problem: ingesting blocks and traces reliably, reconstructing swap intent, labeling attacker-victim-attacker patterns, measuring confidence, and doing it […]

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AI Security Basics: Prompt Injection, Data Poisoning, and Safe Inputs (Complete Guide)

Beginner Track /

AI Security Basics: Prompt Injection, Data Poisoning, and Safe Inputs (Complete Guide) AI Security Basics is not about chasing the newest jailbreak prompt. It is about engineering systems so untrusted text cannot silently become trusted instructions, and so untrusted data cannot quietly shape what your model believes. This guide breaks down prompt injection, data poisoning,

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Building a Market Anomaly Detector: Volume Spikes, Wash Trading, and Alerts (Complete Guide)

Intermediate Track /

Building a Market Anomaly Detector: Volume Spikes, Wash Trading, and Alerts (Complete Guide) Building a Market Anomaly Detector is the fastest way to stop getting surprised by the same three enemies: sudden volume spikes, manufactured activity that looks real but is not, and late reactions when price already moved. This guide gives you a practical,

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Beginner to Using QuantConnect for Crypto Research and Backtests: Beginner Guide to Using QuantConnect for Crypto Research and Backtests

Beginner Track /

Beginner Guide to Using QuantConnect for Crypto Research and Backtests QuantConnect can feel intimidating at first because it sits at the intersection of code, market structure, and data engineering. This guide makes it simple: you will learn how to set up a safe research workflow, how crypto backtests lie when you ignore slippage and fees,

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Inference Compute Surge: AI Tools for On-Chain Demand Management

Applied AI /

Inference Compute Surge: AI Tools for On-Chain Demand Management Inference compute is becoming the daily operating cost of AI products, and Web3 apps need better demand controls before usage spikes become outages, treasury drains, or unsafe agent behavior. Training gets the headlines, but inference is the workload that runs every time a user asks a

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AI Blockchain Security Revolution: On-Chain Tools to Prevent Exploits

Applied AI /

AI Security Revolution: On-Chain Tools to Prevent Exploits AI Blockchain Security is changing Web3 because smart contract defense can no longer depend on slow manual review alone. Exploits move through predictable weaknesses: admin key exposure, unsafe upgrade paths, oracle assumptions, approval traps, token permission abuse, liquidity manipulation, bridge risk, and delayed response. The next security

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Real-Time On-Chain Aggregators: AI Tools for Data Fusion

Applied AI /

Real-Time On-Chain Aggregators: AI Tools for Data Fusion Real-time on-chain aggregators turn fragmented blockchain activity into decision-ready intelligence. Crypto markets no longer move only from price charts, news headlines, or delayed dashboards. A single bridge transfer, token contract update, wallet cluster movement, liquidation event, governance action, or liquidity withdrawal can change risk in minutes. The

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Verifiable AI Compute: ZK Tools for Decentralized Training

Applied AI /

Verifiable AI Compute: ZK Tools for Decentralized Training Verifiable AI compute turns model output into evidence-backed computation. As AI systems move closer to trading, token research, security monitoring, governance, risk scoring, and protocol automation, users need more than a confident result. They need proof that the output came from the expected model, the expected inputs,

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AI Inference Demand: On-Chain Compute Tools for Token Research

Intermediate Track /

AI Inference Demand: On-Chain Compute Tools for Token Research AI training creates models, but inference turns those models into always-on research systems. Every token alert, wallet-risk summary, agent decision, governance brief, contract scan explanation, market screen, and “what changed?” report consumes inference. As crypto research becomes more automated, builders need a safer way to connect

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InfoFi 2.0: Data Markets and AI Checkers for Tradable Signals

Applied AI /

InfoFi 2.0: Data Markets and AI Checkers for Tradable Signals InfoFi 2.0 treats information as a financial primitive, but it only works when data quality, provenance, incentives, and validation are designed together. In crypto, information can move markets before fundamentals are visible. Wallet flows, protocol health, oracle updates, liquidity shifts, governance behavior, liquidation pressure, and

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