Exorbi Labs

Building infrastructure and tooling for decentralized AI economy on @0g_labs.

[Exorbi Labs @ExorbiLabs]

Ever wanted to learn how the @0G_labs tech stack works in detail?

Well, join us this weekend, and have a proper walk through on how to use https://t.co/pyndzC3NHX to understand and build on the 0G stack.

Join us on May 2, 2026 - 15:00 UTC.

[Satya Protocol @SatyaProtocol]

@SatyaProtocol comes with an on-chain escrow flow for model marketplaces:

- time-locked payments
- milestone-based releases
- dispute resolution
- automatic refund periods

Buyers get protection. Sellers get guaranteed settlement logic, everything enforced by smart contracts.

[Cyber @cyberX___]

I built a screen recorder that speaks Spanish better than I do.

Record in English → AI clones your voice → translates captions → dubs the audio → syncs your lips. All running locally on your pc.

AI inference powered by decentralized verifiable compute network, no centralized cloud, no black box.

Open source. Free.

[0G Labs (Home of Infinite AI) @0G_labs]

0G stopped hosting AI and started shipping it.

Meet 0GM-1.0-35B-A3B, our first proprietary model.
Trained on our own GPUs.
Open source under Apache 2.0.

Live now on https://t.co/pKyVVO51sn

[Exorbi Labs @ExorbiLabs]

Verifiable storage, compute, and ownership. Remove any pillar and the whole stack collapses back into trust me bro.

@SatyaProtocol builds all three.

[Satya Protocol @SatyaProtocol]

Most AI today still runs on trust.

You trust that the model you downloaded is the real one.
You trust that the provider actually ran the correct model.
You trust that creators will somehow keep getting royalties later.

But none of that is really verifiable.

[Exorbi Labs @ExorbiLabs]

One prompt. Zero corrections. Fully working momentum screener. 0GM-1.0 delivers on code.

Trained on @0G_labs' decentralized network.

[Sele @iv_dev3]

I tested the new 0GM-1.0-35B-A3B model with a simple prompt: “Build a Python function that takes a list of S&P 500 tickers and returns the three with the highest 30-day momentum, weighted by volume.”

On the first try, it returned fully working code, including the yfinance data fetching, momentum calculations, volume weighting, and edge-case handling, without needing any extra corrections or guidance. The full run from prompt to executable output is in the demo video below, and honestly, it just worked straight out of the box.

What makes this interesting isn’t just the coding ability. Models have been able to write functions like this for a while now. The bigger story is the infrastructure behind it. 0GM-1.0 is the first Mixture-of-Experts fine-tune built on Qwen3.6-35B-A3B, a 35B parameter model where only around 3B parameters are active at a time. More importantly, the model was trained entirely on @0G_labs Compute’s decentralized GPU network instead of a traditional centralized H100 cluster. That’s a pretty major shift from how people normally think frontier AI systems are built.

0G's benchmarks show the model outperforming several strong baselines in reasoning and math tasks, and the company has already demonstrated training models at even larger scales on decentralized infrastructure. That’s why this release feels important.

For years, the assumption was that decentralized AI infrastructure was promising but still far behind centralized compute providers. Releases like this are starting to challenge that idea in a serious way. The impressive part isn’t only that the model generated good code, it’s that it did it using a completely different approach to training and compute.

[Exorbi Labs @ExorbiLabs]

We just getting started

[Cyber @cyberX___]

Brought Huru to Adobe.

[Cyber @cyberX___]

Huru

[Cyber @cyberX___]

Build successful.

The waitlist application arrives by dawn. Get ready.

[Exorbi Labs @ExorbiLabs]

Join us here: https://t.co/QcqYcslnuc

[Exorbi Labs @ExorbiLabs]

Ever wanted to learn how the @0G_labs tech stack works in detail?

Well, join us this weekend, and have a proper walk through on how to use https://t.co/pyndzC3NHX to understand and build on the 0G stack.

Join us on May 2, 2026 - 15:00 UTC.

[Exorbi Labs @ExorbiLabs]

Book a seat for our upcoming LIVE lesson today, as we walk through the @0G_labs tech stack.

Book a seat: https://t.co/QcqYcslnuc

[Exorbi Labs @ExorbiLabs]

Ever wanted to learn how the @0G_labs tech stack works in detail?

Well, join us this weekend, and have a proper walk through on how to use https://t.co/pyndzC3NHX to understand and build on the 0G stack.

Join us on May 2, 2026 - 15:00 UTC.

[Exorbi Labs @ExorbiLabs]

Ever wanted to learn how the @0G_labs tech stack works in detail?

Well, join us this weekend, and have a proper walk through on how to use https://t.co/pyndzC3NHX to understand and build on the 0G stack.

Join us on May 2, 2026 - 15:00 UTC.

[Exorbi Labs @ExorbiLabs]

If you're building onchain AI agents handling real value, you need to verify your inference layer. Check out 0G Private Computer and start building with attested compute.

https://t.co/BGcGe9KeyR

[Exorbi Labs @ExorbiLabs]

Your AI agent has access to wallet keys and can execute transactions. You're sending those prompts to OpenAI's servers and hoping they don't look.

That's not a security model. That's prayer.

[0G Labs (Home of Infinite AI) @0G_labs]

https://t.co/zmJRIjwygH

[Exorbi Labs @ExorbiLabs]

This is the inference layer for the full 0G stack. Chain, compute, storage, and data availability all optimized for AI workloads.

Agents that think, remember, act, and settle with cryptographic proof.

[Ruru_arcade @minting_ruru]

AI killed coding as the bottleneck—understanding is the new skill/ allows you on what to think.

https://t.co/GL5QXioXnk helps you actually get 0G (not just read it) so you can build in the AI era.