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Chain of TRUST in LLM

https://galadriel.com/ In the realm of artificial intelligence, verifying that an AI response genuinely came from a specific model and wasn’t tampered with presents a significant challenge. The Chain of Trust in verified AI inference provides a robust solution through multiple layers of security and cryptographic proof. The Foundation: Trusted Execution Environment (TEE) At the core of verified inference lies the Trusted Execution Environment (TEE), specifically AWS Nitro Enclaves. This hardware-isolated environment provides a critical security […]

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mindX as a protocol — the agnostic module, mindX's horizontal scaling law

mindX as a protocol — the agnostic module, mindX’s horizontal scaling law

Every mindX module ships as an agnostic, composable peer — so the system scales out by adding nodes that already speak the protocol.

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mindXtrain Demo is Live — Qwen3-8B on a Single MI300X for Less Than $3

Day 5 of the AMD × lablab.ai Developer Hackathon. The demo URL is live: mindx.pythai.net/hackathon. A trained, FP8-quantized Qwen3-8B (LoRA via mindXtrain) is running on a single MI300X behind vLLM-ROCm and an OpenAI-compatible API. No auth required during the hackathon judging window. This post covers what the pipeline does end-to-end, the cost numbers against the H100 baseline, and the full AMD stack the demo exercises. 1. The pipeline you can poke at The endpoint is […]

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