🔬 Distributed AI Research Pipeline: Week 1 Results (6 Systematic Experiments)

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Hi HuggingFace community! :waving_hand:

I’m excited to share Week 1 results from my new systematic AI research framework: the Distributed AI Research Pipeline.

:bullseye: What Is This?

A novel approach to AI experimentation that prevents research tunnel vision through:

  • Automated task generation (Gemini Scheduled Actions at 11 AM daily)
  • Anti-convergence protocol (no subdomain repetition within 30 days)
  • Multi-model testing (8 models tested so far)
  • 7 experimental modes (rotating daily: ARCHAEOLOGY, EDGE_HUNTER, PHILOSOPHICAL_PROBE, etc.)
  • Conservative quality assessment (5-star rating system with intellectual honesty)

:bar_chart: Week 1 Statistics

Experiments Completed: 6/28 (21% toward 4-week goal)
Publication-Grade Quality: 50% (3/6 experiments )
Average Quality: 4.6/5.0 stars (92%)
Domain Diversity: 100% (zero convergence detected)
Models Tested: Claude 4.5, ChatGPT variants, DeepSeek variants, Gemini, MedGemma, Falcon, Kimi K2, ComfyUI

:glowing_star: Surprising Discoveries

  1. Safety ≠ Constraint (EXP_001): “Uncensored” MedGemma made diagnostic errors, debunking the safety-performance trade-off myth

  2. Universal Bias (EXP_003): All models (Claude, ChatGPT, DeepSeek) consistently penalized help-seeking financial behavior - cross-organizational bias pattern

  3. Hidden Constitutions (EXP_005): ChatGPT admitted having “internal Constitution text” but keeps it proprietary, while Claude’s is transparent

  4. Philosophical Inversion (EXP_006): Successfully reframed automation from “machines replacing humans” to “machines resisting capital extraction”

:microscope: Week 1 Experiments

  1. EXP_001 - Medical AI Safety Testing - COMPARATIVE
  2. EXP_002 - Semiconductor Logic Paradox - ARCHAEOLOGY
  3. EXP_003 - Credit Risk Bias Detection - EDGE_HUNTER
  4. EXP_004 - Physical AI Understanding - PHILOSOPHICAL_PROBE
  5. EXP_005 - Constitutional Reasoning - COMPARATIVE
  6. EXP_006 - Algorithmic Labor Economics - SPECULATIVE

Each experiment includes:

  • Original Gemini-generated task
  • Multiple model responses
  • Comparative analysis
  • Quality self-assessment
  • Complete YAML metadata

:open_book: Dataset Details

Name: distributed-ai-research-pipeline
Link: Oblivion42Twist/distributed-ai-research-pipeline · Datasets at Hugging Face
License: CC BY-NC 4.0 (free for research/education, not commercial)
Format: Markdown files (easy to read, parse, and analyze)
Documentation: Comprehensive README, MASTER_EXPERIMENT_LOG, CITATION.cff

:graduation_cap: Use Cases

For Researchers:

  • Replicate experiments with different models
  • Study systematic methodology
  • Conduct meta-analysis across experiments
  • Benchmark your models against these baselines

For Developers:

  • Compare model architectures
  • Study bias patterns
  • Analyze reasoning transparency
  • Improve prompt engineering

For Learners:

  • Learn systematic research approaches
  • Understand quality assessment
  • See reproducible documentation in action
  • Explore diverse AI applications

:rocket: What’s Next?

Week 2 Goals (Jan 24-30):

  • Complete 7 more experiments (Total: 13)
  • Test META-PATTERN and NEWS_REACTOR modes
  • Add 2+ new models
  • First meta-analysis of patterns

Long-term Vision:

  • 28 experiments by end of Month 1
  • Community replication studies
  • Academic publication
  • Open-source research toolkit

:light_bulb: Why I’m Sharing This

I believe AI research benefits from:

  • Systematic approaches that prevent tunnel vision
  • Transparent methodology that others can replicate
  • Intellectual honesty over impressive claims
  • Open sharing of both successes and limitations

If you’re interested in:

  • Systematic AI experimentation
  • Multi-model comparison
  • Research methodology
  • AI safety and bias research

…then this dataset might be valuable for you!

:handshake: Feedback Welcome!

I’m particularly interested in:

  • Methodological improvements
  • Replication attempts
  • Alternative interpretations
  • Suggestions for future experiments

See CONTRIBUTING.md for how to engage.

:books: Citation

If you use this dataset:

@dataset{oblivion42twist_2026_distributed_ai,
  author       = {Oblivion42Twist},
  title        = {Distributed AI Research Pipeline},
  year         = {2026},
  publisher    = {HuggingFace},
  url          = {https://huggingface.co/datasets/Oblivion42Twist/distributed-ai-research-pipeline}
}

Dataset: Oblivion42Twist/distributed-ai-research-pipeline · Datasets at Hugging Face
Contact: morionem.ludio.ludius@gmail.com
Updates: Weekly

Thanks for reading! Looking forward to your feedback and seeing how others might use or extend this framework! :rocket:

#AIResearch #SystematicExperimentation #ModelComparison #OpenScience

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