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India May Fast-Track Big Tech Compliance Under Data...

Fast Flux Botnets Unmasked: Inside the Resilient Infrastructure...

Critical Windows SMB Client Vulnerability Enables Active Directory...

Whisper-Pair Exposed: How a Flawed Google Fast Pair...

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Fast Flux Botnets Unmasked: Inside the Resilient Infrastructure Powering Modern Cybercrime

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Whisper-Pair Exposed: How a Flawed Google Fast Pair Implementation Enables Silent Bluetooth Takeovers

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The Morris Worm: How a Graduate Experiment Triggered the World’s First Internet Security Crisis

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New MHA SOP Enables Faster Refunds for Cyber Fraud Cases Below ₹50,000

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Is “Free” Wi-Fi Actually Free? How India’s New Data Law Protects You

This image is an informational graphic for Token-Oriented Object Notation (TOON), a compact, human-readable serialization format for JSON data used in LLM prompts.The graphic is divided into three main horizontal sections:Header: Displays the project name "Token-Oriented Object Notation" and its tagline: "Compact, human-readable serialization of JSON data for LLM prompts."Workflow Section:Shows a flow diagram: JSON $\rightarrow$ encode() $\rightarrow$ TOON $\rightarrow$ LLM.A bar graph illustrates token savings, indicating that TOON uses approximately 30–60% fewer tokens than JSON.Includes a command-line instruction to try the tool: npx @toon-format/cli *.json.Comparison Footer:Average Tokens: A visual bar chart shows TOON's significantly lower token footprint compared to JSON.Retrieval Accuracy: Lists TOON at 73.9% accuracy versus JSON at 69.7%.Best For: Lists ideal use cases including repeated structures, tables, varying fields, and deep trees.
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TOON: How a New Data Format Slashes Your LLM Token Costs by 50% or More