Krim
42 posts
@TheKrimAI
A safe sovereign superintelligence research lab working to build reliable, explainable and tractable autonomous systems powered by generative AI models.
@TheKrimAI is #hiring bright AI Engineers and Interns in Patna, Bihar. Show this to the Good Samaritan on @x, please #spread the word. Let there be a change in emerging Bihar AI landscape.
Every AI system calling itself "safe" without epistemological grounding is theater. Every chatbot claiming to "reason" without validated inference is performing. Every autonomous agent acting without proving its epistemic warrant is gambling. 1/2
Dear All, You are cordially invited to attend a talk on: “From Navya Nyāya to Safe Superintelligence: An Indic Framework for Validating AI Reasoning” Speaker: Mr. Vishwanath Jha @nathoham (Founder & CEO, @TheKrimAI) Chair: Prof. Rahul Garg (IIT Delhi ) Date & Time: Wednesday, 21st January 2026 at 03:00 PM Venue: Room no.111, Committee Room, School of Sanskrit & Indic Studies, Jawaharlal Nehru University, New Delhi Abstract: The emergence of increasingly capable AI systems — from large language models to reasoning engines to autonomous agents — raises urgent questions about validation, alignment, and safety at scale. As we approach the horizon of superintelligent systems, current Western-centric safety paradigms face fundamental epistemic limitations. This talk proposes that Indic philosophical traditions, particularly Navya Nyāya, offer foundational frameworks to lead global AI safety research. We examine Gangeśa Upādhyāya's theory of pramāṇa (valid knowledge sources) as a model for auditing AI outputs, and doṣa (epistemic defects) as a taxonomy for error classification — applicable from today's LLMs to tomorrow's superintelligent systems. Raghunātha Śiromaṇi's refinements on abhāva (absence), relational structures, and inferential rigor provide formal scaffolding for validating machine reasoning at any capability level. Drawing from production AI deployments in Indian financial services, we demonstrate how these frameworks translate into pre-execution validation layers — enabling verification of reasoning chains before outputs reach users. The talk concludes with a vision for joint research positioning India at the center of global AI safety discourse. Q&A will explore research pathways, interdisciplinary collaboration, and the road to safe superintelligence. We look forward to your presence and active participation. Thanks Talk will be followed by High Tea.
The missing piece in LLM stack: Retrieval ✅ (RAG works) Reasoning ✅ (CoT works) Action ✅ (Function calling works) Governance ❌ (nobody's solved this) Who validates the action BEFORE execution? Who ensures compliance BEFORE the API call? That's the gap. That's the infrastructure.
