Justin Zhou

data, compute, memory // prev @meta

[Justin Zhou @rowanzhou]

@brezshares @justinweb33 like reading you shill $prl everyday, keep doing it :)

[Justin Zhou @rowanzhou]

over the past 2 months i swapped 1 btc into pearl-2:native.
i believe one day it could become 1,000 or even 10,000 btc.

friends who know me well have heard this in private for months. it's the first coin i've named in public since my old account @justinweb33 was suspended.

pearl is way better than bitcoin for the ai era. the key difference: the proof of work is matrix multiplication, the math underneath every ai model. bitcoin's work gets thrown away. pearl's work is the inference itself.

and it just got real. @prlnet's new floating-point scheme runs on nvidia blackwell with near-zero overhead on top of normal inference, and it's headed to frontier models on @togethercompute's endpoints. same gpu, same tokens, plus a coin.

there's a second market nobody is pricing: proof. with @attestable, pearl is building the layer that lets an ai lab prove what it computed without revealing weights or prompts. if ai gets regulated, every lab will need that.

every year the ai compute forecasts get revised up. nobody knows how big this gets.

i'll drop the good pearl reads in the comments if you want to go deeper.

[Pearl 中文社区 @pearl_cn]

如果你持有 pearl-2:native @prlnet
请留言告诉我

我将关注每一个pearl家人
祝愿你们都享受pearl人生

[Justin Zhou @rowanzhou]

@justinweb33 from chinese friend @0xYuxi https://t.co/FPMBnGod7x

[0xyuxi | 0x雨曦 @0xYuxi]

https://t.co/TSoV1JaEyX

[Justin Zhou @rowanzhou]

@justinweb33 a very fair take from @jeremiahrogers, a $ZEC believer:
https://t.co/L0KUIJfWX0

[Jeremiah @jeremiahrogers]

I am building a research interest and a small position in $PRL, which to disambiguate is from @prlnet.

The central feature of Pearl is that it is a proof-of-work system on top of GPUs and that the proof of work can be mixed in with AI inference workloads.

PRL calls this mining algorithm "proof of useful work". I don't like that name because as far as I can tell there is no actual proof that the work is useful, and I consider the transformation of energy into money inherently useful already -- as with Zcash or Bitcoin or many other coins.

That said, one might argue that ultimately hashrate and security will determine which commodity/internet asset is most valuable. I think PRL has a good shot at getting the highest hashrate and security of all chains.

One can also argue that as software is increasingly fluid, the actual code doesn't matter as much as the distribution (holders + hashrate) because the code is easy to modify or clone after the fact.

As AI consumes more energy, there may be marginally less energy available to secure other blockchains. I think this is already playing out as major Bitcoin miners switch to AI workloads.

If PRL gets successful mining distribution across many of the big server farms, and executes its software stack well to clone features from other cryptos, it may do well over time. That's a lot of IFs. So it is a small position.

Why now? The price has stabilized in a $0.20-$0.30 channel for a while after briefly going far higher. PRL has 100x the units of Bitcoin or Zcash, so consider it trading for $20-$30 in equivalent terms. If PRL is successful I could see it trading at 10-100x this value in a decade.

Some reasons NOT to buy now:
- The network is very early and the token is still very inflationary.
- Price may drop a lot before a real use case comes online.
- There's no proof that anyone will use this and it is not listed on any major exchange.
- It's not really clear what PRL *is* yet. Is it money? Is it some kind of industrial side-effect of inference?
- Other novel proof-of-work coins like Chia/XCH have failed.

Zcash and traditional equities are still my largest positions. PRL is sized like a high risk/reward angel bet in my portfolio (near 1%).

[Justin Zhou @rowanzhou]

@justinweb33 great article from @ZanaVentures, written on pearl's day 1 :)
https://t.co/fYLkykRbES

[Zana Ventures @ZanaVentures]

https://t.co/cg06S6yESg

[Justin Zhou @rowanzhou]

@justinweb33 privacy related staff https://t.co/hdOGKLEWla

[Pearl Research Labs @prlnet]

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:
https://t.co/FjwwSVoLSP
Whitepaper: https://t.co/6BqeEqQRgl
Run Pearlified models on our endpoint:
https://t.co/6bykpZhFTk

[Justin Zhou @rowanzhou]

@justinweb33 cofounder of pearl https://t.co/yuGGj8kDmK

[Omri Weinstein @WeinsteinOmri]

Pearl (@prlnet) has the fastest FP8 MoE Kernels for Blackwell chips!

Group-Matrix-Multiplication is one of the most optimized operations in AI. As a former researcher at @nvidia I can say firsthand that pushing the performance frontier of MatMuls is... Hard.

Pearl-GEMM is ~5% faster than prior state-of-art Quack (@tri_dao) and ~42% faster than Flashinfer on B200s.

https://t.co/HB1nbjnDn0

[Justin Zhou @rowanzhou]

jev is now on Openrouter

[OpenRouter @OpenRouter]

Jev by @typesafeai is now on OpenRouter, in beta.

Jev is a System One model. Instead of generating text, it takes your app's state plus a typed question and returns a typed decision with a probability attached. There is no JSON prompting, parsing layer, and nothing to validate against.

[Justin Zhou @rowanzhou]

最近有关注X Layer, 看得出来 X Layer 真真正正用实际行动推动 RWA 时代的链上创新和生态建设。

但有一个真诚的小建议：X Layer 的视觉一直是黑+灰，看着很专业，但却高冷的不敢靠近。品牌上主打New Money, 但是总给我一种Old Money的庄严感，缺少了点属于新年轻人的朝气。而且这个色调也不利于社区的形成，给人们一种疏离感，不够欣欣向荣。相比之下，@wallet 钱包的绿色就看着相对舒服些。@XLayerOfficial @star_okx @zakk_okx @EudemoniaCC

当前 X Layer 正是建社区、做生态的阶段，品牌色如果加一些温暖、有生命力的主色，视觉感上，更容易拉近和社区，builder们的距离。

总结来说，散发着一种，可远观的崇拜感，但是没有靠近和一起玩耍的勇气。

不知道大家怎么看

[X Layer @XLayerOfficial]

Community is everything 🤝

Our $5M RWA Liquidity Incentive Program continues with Round 2 of incentives allocated to selected RWA-ecosystem token pairs.

[Justin Zhou @rowanzhou]

@sph_eric their first preview model, even the official x account just registered a week ago, lol

[Justin Zhou @rowanzhou]

@cyodyssey 这个继续glm post training 的，强化了安全和科研的能力

[Atria ASI @AtriaASI]

Introducing Atria Dawn Preview:
From Research Questions to Verifiable Results.

Atria Dawn Preview is an agentic foundation model built for long-horizon tasks, helping researchers and engineers turn open-ended questions into executable, verifiable, and reproducible outcomes.

Explore Atria Dawn Preview:
🌐 Website: https://t.co/MDDspFiqYO
💻 GitHub: https://t.co/tNmLocadjT
🤗 Hugging Face: https://t.co/cyZod5oHbw
🤖 ModelScope: https://t.co/6BNi5vHFDl
🚀 Try Atria:
EN：https://t.co/Ap5aO2gQeu
ZH：https://t.co/cG16cQdx4j

[Justin Zhou @rowanzhou]

@evilcos 试试atria呢，今天刚看到他们发布

安全跑分挺高

[Atria ASI @AtriaASI]

Introducing Atria Dawn Preview:
From Research Questions to Verifiable Results.

Atria Dawn Preview is an agentic foundation model built for long-horizon tasks, helping researchers and engineers turn open-ended questions into executable, verifiable, and reproducible outcomes.

Explore Atria Dawn Preview:
🌐 Website: https://t.co/MDDspFiqYO
💻 GitHub: https://t.co/tNmLocadjT
🤗 Hugging Face: https://t.co/cyZod5oHbw
🤖 ModelScope: https://t.co/6BNi5vHFDl
🚀 Try Atria:
EN：https://t.co/Ap5aO2gQeu
ZH：https://t.co/cG16cQdx4j

[Justin Zhou @rowanzhou]

@wanghan_xu congrats. great work

[Justin Zhou @rowanzhou]

@shoucccc @alexocheema how about sglang?

[Justin Zhou @rowanzhou]

@AtriaASI when blockrun @BlockRunAI @bc1beat integrate?

[Atria ASI @AtriaASI]

Introducing Atria Dawn Preview:
From Research Questions to Verifiable Results.

Atria Dawn Preview is an agentic foundation model built for long-horizon tasks, helping researchers and engineers turn open-ended questions into executable, verifiable, and reproducible outcomes.

Explore Atria Dawn Preview:
🌐 Website: https://t.co/MDDspFiqYO
💻 GitHub: https://t.co/tNmLocadjT
🤗 Hugging Face: https://t.co/cyZod5oHbw
🤖 ModelScope: https://t.co/6BNi5vHFDl
🚀 Try Atria:
EN：https://t.co/Ap5aO2gQeu
ZH：https://t.co/cG16cQdx4j

[Justin Zhou @rowanzhou]

@AtriaASI this is insane! congrats team

[Justin Zhou @rowanzhou]

@bxiaokang 我们能等到fourmeme 被 Xlayer 吸血的那天吗