Pearl Research Labs

Congrats to our friends at @flappyairplanes

Exciting times ahead!

Privacy-preserving proof of inference is a key building block for AI safety. @DarioAmodei's call for AI slowdown & independent oversight raises a critical question / How can frontier labs prove their computations follow the rules, without revealing model weights, prompts, or private data?

Two complementary technologies are necessary to make this inference layer possible: Zero-Knowledge proofs (zk-SNARKs) can prove that Y = M(x), while keeping M and x private, and verify compliance using explicit policies. Proof-of-useful-work (PoUW) can
tie that evidence to actual, timestamped GPU computation, with a public immutable record and economic incentives for participation.

@prlnet is partnering with @attestable to build this trust layer for AI. Together, our complementary technologies can make AI objectively accountable, making verification economically sustainable and self-funding.

Today, we are announcing @prlnet's new and ultra-efficient floating-point PoUW scheme for NVIDIA Blackwell chips.

Floating-point arithmetic has been a notorious obstacle to efficient verification of compute for decades. Pearl’s FP scheme brings proof-of-useful-work technology to Blackwell FP computations on frontier LLMs, with NEAR-ZERO additional overhead over end-to-end inference on optimized vLLM.

The FP network upgrade specification is now available (github & whitepaper) and will soon serve frontier models on Pearl x @togethercompute's endpoints in production.

Explore the implementation:
github.com/pearl-research…
Whitepaper: pearlresearch.ai/Pearl_Whitepap…
Run Pearlified models on our endpoint:
pearlresearch.ai

The Pearl founders will be hosting another live AMA with the community!

Tuesday, September 15
6:00 PM CET · 12:00 PM ET · 16:00 UTC

We've been heads-down building, and the questions have been piling up — about the research, the roadmap, and where the network goes from here. On Tuesday, we're answering them.

Here's how it works: head to the ama-questions channel on our Discord and drop in whatever you'd like answered. Upvote the questions you care about most. The founders will open with the five that rise to the top, then it's an open floor for the rest of the session.

Come with good questions. We'll come with real answers.

discord.gg/joinpearl

Pearl started with a simple question:
Why should AI and blockchain mining compete for the same GPUs when the same computation could do both?
In this talk, Pearl co-founder @komargodski explains how that idea became a live proof-of-useful-work network turning AI inference into blockchain security with minimal overhead.