- An LLM might hallucinate a molecular structure violating valency rules.
A diffusion model might generate copyright-infringing audio.
99% plausible but 1% physically impossible = catastrophic failure. 🧵
#DeepTech #EnterpriseAI
AI landscape is bifurcating: - WRAPPER ECONOMY: Lightweight apps atop general LLMs. Fast, cheap, probabilistic. Plausible outputs.
DEEP TECH: Physics-informed, law-compliant architectures. Slow, expensive, deterministic. True outputs.
Enterprise can't afford wrappers. - Why wrappers fail critical applications:
LLMs predict tokens, not electron densities. They can't validate thermodynamic stability.
Diffusion models trained on scraped data create "black box" copyright risk.
No audit trail = no enterprise deployment. - Battery thermal runaway stages:
- 80-100°C: SEI decomposition
- 110-135°C: Separator melting, electrolyte breakdown
- >200°C: Cathode collapse, combustion
Challenge: Find electrolytes stable at >200°C.
Chemical space: 10^100 possibilities.
Random search fails. - Veriprajna workflow: GNoME (Graph Networks for Materials Exploration)
Graph Neural Networks treat molecules as graphs (atoms = nodes, bonds = edges).
E(3)-equivariant architecture respects physical symmetries.
Proposes thermodynamically stable candidates.
#MaterialsScience - GNoME predictions are probabilistic. Enterprise needs certainty.
Oracle: Density Functional Theory (DFT)
Quantum mechanical validation of formation energy & convex hull.
Only stable compounds (E_hull = 0) move to synthesis.
Physics validates AI. - The Flywheel:
1. GNoME generates 10k candidates
2. Uncertainty quantification selects 500 for DFT
3. DFT validates, feeds back ground truth
4. GNoME retrains, improves
5. Repeat
Hit rate: 80% (vs <1% random)
#ActiveLearning #DeepTech
Media black box problem: - Diffusion models trained on scraped copyrighted audio. Output = mathematical amalgamation of training data.
User can't verify provenance. If output mimics copyrighted work, user is liable.
Enterprise IP risk: non-negotiable.
Veriprajna copyright-safe pipeline: - → Demucs (Deep Source Separation) isolates licensed stems
→ RVC (Retrieval-Based Voice Conversion) from consented actors
→ C2PA cryptographic signing
100% auditable chain of title. White box, not black box.
#C2PA #MediaTech - For enterprises where failure = fire or lawsuit, probabilistic AI is unacceptable.
Veriprajna: Deterministic AI where physics and law validate neural outputs. - 📖 Read the full technical whitepaper here: https://veriprajna.com/whitepapers/deterministic-enterprise-engineering-truth-probabilistic-ai
📧 [email protected]
🌐 https://veriprajna.com
💬 WhatsApp: +919217059957
#DeepTech #EnterpriseAI