You're pledging to donate if the project hits its minimum goal and gets approved. If not, your funds will be returned.
What are this project's goals? How will you achieve them?
We currently have three top-line goals:
1. Senso Interno : To study and develop the 14-module bidirectional event bus that simulates a "Global Workspace." This scaffold manages cognitive pressure, curiosity-driven exploration, and self-model tracking to prevent state-drift during 8hr+ research cycles.
2. CausalVault: To build on our existing GraphRAG implementation (2,100+ relations) a persistent, auditable causal knowledge bridge. This allows the agent to maintain a high-fidelity "World Model" that compounds learning across sessions without catastrophic forgetting.
3. ForgeBox: To deliver a hardened, safety-critical execution sandbox optimized for autonomous software engineering (SWE) and scientific simulation. This environment enforces zero-network execution and kernel-level hardening, allowing for the safe testing of untrusted, autonomously generated hypotheses.
This funding ($50,000) is intended to provide working capital to support our transition from a prototype running on edge hardware to a professional research laboratory.
Infrastructure Scaling ($20,000): Subsidizing access to high-entropy flagship tiers (Claude Max, Gemini Ultra) to power ~10 deep research cycles per day.
Hardware Capital ($15,000): Procurement of a dual-RTX 4090 workstation to perform local mechanistic interpretability and embedding research.
Researcher Stipend ($12,000): Allowing the founder to focus 100% on architecture development and academic dissemination.
Security Audit ($3,000): Stress-testing the ForgeBox isolation layers.
SHARD LABS is currently led by a self-taught independent researcher based in Verona, Italy. Our track record is defined by extreme capital efficiency and architectural ingenuity:
3 Months of Iterative Research: Built 35+ iterations of the SHARD architecture (SSJ1-SSJ35) entirely on a $300 GEEKOM A5 mini-PC.
Empirical Breakthroughs: Achieved a 100% pass rate on a 14-task SWE benchmark suite where the underlying LLM baseline scored 87.7%.
Causal Evidence: Confirmed a +1.6 performance delta through controlled ablation tests, isolating the value of the meta-cognitive "Senso Interno" layer.
Autonomous Discovery: Successfully generated and validated 58+ cross-domain scientific hypotheses, including a verified experiment on mitigating catastrophic forgetting in neural networks.
The ambitious goal of building a "fully autonomous laboratory" is high-risk. The most likely cause of failure is the complexity of maintaining long-term reasoning coherence as the state-space grows.
However, even if the ultimate vision of a fully autonomous lab is not realized within the next 12 months, SHARD LABS will deliver:
Open Source Building Blocks: We will release the full technical specification and source code for the Senso Interno bus and the ForgeBox sandbox.
Datasets: 100+ autonomously generated and validated scientific hypotheses across Physics, Biology, and ML for the research community.
Dissemination: Documentation of the "Shadow Diagnostic" method for measuring emergent behaviors in agentic systems without relying on LLM self-reporting.
Zero. SHARD LABS has been entirely self-funded and developed independently by a solo researcher. To date, we have operated with zero external capital, utilizing personal edge hardware ($300 GEEKOM A5) to develop and validate 35+ architectural iterations over 3 months. This grant represents our first request for external funding, aimed at transitioning from a zero-budget functional prototype to a professional-grade research laboratory.
There are no bids on this project.