6 posts tagged with "AI Safety"

QWED is built on a single insight: LLMs are translators, not calculators. This reframing changes everything about how we build reliable AI systems.

In 2023, a major financial institution deployed an AI assistant that made a $12,000 calculation error on 50,000 customer accounts. Total damage: $600 million in refunds and regulatory fines.

This is the hidden cost of unverified AI.

The AI industry's response to hallucinations has been: train harder, fine-tune more, add RLHF. But this approach has a fundamental flaw — you can't train probability to be certainty.

QWED's Statistics Engine lets you verify claims like "the mean of this dataset is 42.5" by executing actual Python code. But executing AI-generated code is inherently dangerous. Here's how we built a secure sandbox.

When an LLM generates SQL, how do you know it's safe to execute? Traditional regex-based approaches fail against sophisticated attacks. QWED uses Abstract Syntax Tree (AST) analysis for defense-in-depth.

Today, we're open-sourcing QWED — a protocol that brings mathematical certainty to AI outputs.

The Problem​

LLMs are incredible at understanding natural language. But they're terrible at math. They hallucinate facts. They generate unsafe code.

The industry's solution? Train them more. Fine-tune with RLHF. Add guardrails.

We took a different approach.