[2026]
Data Infrastructure
AK Data Format →
An open-source standard designed to unify heterogeneous datasets into a single, highly optimized structure for LLM training and fine-tuning. Reduces data preprocessing time by providing consistent schemas for text, image, and structured data pairs across distributed systems.
complex_example.aid
/* 1. Global Attributes & Configuration */
// $schemaVersion="2.0" $environment="production" #strict_mode //
/* 2. Define Type with Metadata */
@LLM_Node /* Represents a processing unit */ <[ id: number,
model_name: string,
temperature: number,
is_active: bool ]>
/* 3. Data Collection (List) */
[ #high_priority $region="eu-west"
/* Positional Tuple (High Density) */
( 101, "gpt-4-turbo", 0.7, true ),
( 101, "gpt-4-turbo", 0.7, true ),
/* Multiline Strings (Backticks) */
( 102, "claude-3-opus (optimized)", 0.2, true ),
( 102, "claude-3-opus (optimized)", 0.2, true ),
/* Named Object (Flexible / Partial) */
{ #experimental id: 200, model_name: "llama-3-70b" /* temperature defaults to 0.0 */ }
{ #experimental id: 200, model_name: "llama-3-70b" /* temperature defaults to 0.0 */ }
]
------------------------------------------------------------------------------------------------ BENCHMARK SUMMARY: ------------------------------------------------------------------------------------------------ JSON █████████████████████░░░░ 6921 tok 0.16 ms AKCD ████████████████░░░░░░░░░ 5416 tok 4.69 ms AKD ███████████████████░░░░░░ 6488 tok 4.55 ms TOON █████████████████████████ 8198 tok 2.41 ms FORMAT TOKENS TIME (Total) AVG TIME/FILE VS JSON ---------------------------------------------------------------------- AICD 5416 4.69 ms 0.39 ms -21.7% AKD 6488 4.55 ms 0.38 ms -6.3% JSON 6921 0.16 ms 0.01 ms +0.0% TOON 8198 2.41 ms 0.20 ms +18.5% CONCLUSION: Switching to AKCD (AK Compact Data) saves 1505 tokens (21.7%) compared to JSON.------------------------------------------------------------------------------------------------
