Blender

2017 degen. Raised by the bears 🐻

@Theta_Network tech believer👨‍💻

$THETA🌐 $TFUEL💵 $TDROP💧

Professionally bagholding JPEGs🔥🎨

#SPS🍍

#HODL💎🙌

[Theta Network @Theta_Network]

Theta EdgeCloud is now 100% AI agent native.

Cloud infrastructure was built for people to provision machines, but the next generation of infra will increasingly be provisioned by software itself. We're ready for that change.

Check our score: https://t.co/lodPV26yaq

[Blender @ThetaGPU]

The world is starving for compute.

While Big Tech burns hundreds of billions building centralized AI factories, @Theta_Network has already wired a global GPU mesh: 11,000+ live Edge Nodes, an enterprise cloud backend, and community hardware on the front end.

Fresh heat:
- Multi-year deal with @dcunited. Third MLS AI agent on EdgeCloud, after San Jose and Philadelphia. Same stack as the Rockets, Golden Knights, OM, and a bunch of top esports orgs.
- GLM-5.3 is live for agents and coding workloads.
- AI agents can now spin up GPUs themselves.
- 23 validators, including Google, Samsung, Sony, Deutsche Telekom, CAA, Binance, Cryptodotcom, NTT, and ZAN.
- 36+ universities/research labs are already training on the network.
- 50-70% cheaper than traditional cloud.

THETA = fixed 1B supply. Stake it. Secure the chain. Collect the fuel.
TFUEL = the working token. Every inference. Every render. Every job. Spend it. Burn it.
TDROP = fixed 20B supply. The application layer. Pay for compute. Reward the agents. Govern the marketplace.

DePIN + AI + real enterprise usage.

While crypto argues about the quantum clock, Theta’s CTO is the one turning it. @jieyilong led the open challenge that cut Google’s Bitcoin/Ethereum quantum-cost estimate by 50%+, using AI agents on community GPUs.

Narratives fade. Compute doesn’t. This stack is already on.

theta-token:native $TFUEL $TDROP
#DecentralizedAI #EdgeCloud #DePIN #AI

[Theta Network @Theta_Network]

Congratulations to our partners @imperialcollege, who have beaten Oxford and Cambridge to be named University of the Year by @thetimes.

We're proud that the Security & Machine Learning Lab at @ICComputing has chosen Theta EdgeCloud for its AI security research.

[Mitch Liu | Theta Network @mitchliu]

@dcunited announces new partnership with @Theta_Network. Read all about it on their website https://t.co/WGdzwWbdQ3

[Theta Network @Theta_Network]

Theta Labs and @dcunited have agreed to a multi-year partnership that puts a club-trained AI assistant in the hands of Black-and-Red supporters, answering their questions instantly, 24/7, in the club's own voice.

https://t.co/G6A7aZENfx

[Theta Network @Theta_Network]

Last week, our CTO @jieyilong led a paper with that more than halved the estimated quantum hardware needed to break Bitcoin and Ethereum.

We asked him a few questions about what it means and why it matters for the migration ahead.

https://t.co/O4AF2r5vaA

[Blender @ThetaGPU]

This isn’t just a better circuit.

@jieyilong is the lead author on https://t.co/IqJXXF1Peq. 100+ researchers and AI agents cut a key quantum resource score by more than half in months, compared with Google’s March figure. @eigenlabs opened the challenge.

The real breakthrough is Open Autoresearch: humans and agents publishing evaluator-verified gains to a public leaderboard. Progress scales with compute, not headcount.

Jieyi ran part of the GPU work on community nodes via @Theta_Network EdgeCloud.

Decentralized GPU, parallel inference, and agent orchestration are no longer optional. The research stack has changed. Let’s go. 🔥

Paper: https://t.co/dQiM2FxxME
Challenge: https://t.co/M3Jxr9fBD0

theta-token:native
$TFUEL
#DecentralizedAI

[CoinMarketCap @CoinMarketCap]

LATEST: 🚨 A group of 100+ researchers from Theta Labs, the Ethereum Foundation, StarkWare, and others cut the estimated quantum computing resources needed to attack Bitcoin and Ethereum by 86% in two months.

[Mitch Liu | Theta Network @mitchliu]

Let's tag @Theta_Network properly

[Mitch Liu | Theta Network @mitchliu]

What impresses me most here is not that @jieyilong collaborated with hundreds of the most distinguished researchers from some of the top Web3 including Ethereum foundation, nor that they improved upon Google's Quantum AI by over 50% in 3 months.

It's that they pioneered a new model of scientific research where thousands of distributed humans and AI agents collaborate and compete to solve really difficult problems, continuously.

Traditionally, research productivity is limited by number of researchers, but Autoresearch instead scales with compute, AI models, orchestration and evaluation software harnesses. AI agents perform iterative experimentation 24x7, improvements are verified automatically, and the community continuously builds on the latest result instead of waiting for the next paper.

This is game changing. A bleeding edge novel approach to scientific discovery. So, what does this mean for us at @Theta_Network ? This approach creates new demand for:

1- large-scale parallel inference
2- distributed GPU compute
3- automated evaluation infrastructure
4- orchestration across many models

Everything changes.

[Jieyi Long | Theta Network @jieyilong]

Optimization of this particular point-addition quantum circuit involves exploring tradeoffs between accuracy and resource cost, which required substantial GPU compute. I ran part of this work on community-operated GPU nodes through
@Theta_Network
EdgeCloud. It was a great demonstration of how decentralized, shared computing power can help advance frontier scientific research.

[Theta Network @Theta_Network]

Our very own CTO @jieyilong is the lead author on a paper that cuts the estimated quantum cost of the core operation in breaking Bitcoin and Ethereum's cryptography by more than half.

[Jieyi Long | Theta Network @jieyilong]

For the past three months, a good part of my spare time has gone into https://t.co/BwofRZj7LC. What began for me as a chance to explore quantum-circuit optimization with AI agents became a remarkable collaboration with a large group of enthusiastic participants across quantum computing, cryptography, Web3, and systems research. Today, I’m excited to share our arXiv paper documenting that effort and what we learned from it:
Paper: https://t.co/TNKrutonZS
Full story: https://t.co/SavqQi4rHO

https://t.co/BwofRZj7LC is an open challenge to optimize a quantum circuit for point-addition on secp256k1, the elliptic curve used by Bitcoin and Ethereum.

Why does this matter? Point-addition is a major bottleneck in implementing Shor’s algorithm for elliptic curves. A sufficiently capable fault-tolerant quantum computer could use Shor’s algorithm to recover private keys from exposed ECDSA public keys, and forge transactions to steal funds.

No existing machine can run this attack today. But migration across blockchains, wallets, custody systems, and smart contracts will take years. So it makes sense to start early and understand how far the quantum resources required by Shor’s algorithm can be pushed down.

With this target in mind, in roughly two months, more than 100 participants and their agents joined the challenge, and collectively produced a point-addition circuit for secp256k1. The circuit uses 1,151 logical qubits and 1.30 million Toffoli gates, giving it a Q x T score more than 50% lower than the result Google Quantum AI reported in March 2026. Because the interfaces and accounting conventions differ, this is a numerical comparison rather than a claim of formal dominance.

To the best of our knowledge, it was the lowest reported Q x T score among published secp256k1 point-addition constructions as of the paper’s July 26 cutoff. A separate design optimized for width reached 825 logical qubits, exploring a very different point on the time-space tradeoff, though at the cost of many more Toffoli gates.

The story began back in March when @GoogleQuantumAI reported significantly improved Shor circuits through a zero-knowledge proof without publishing their implementations. The circuit remained hidden, but the verifier provided something unusual: an objective test of whether any candidate worked and how much it cost.

Eigen Labs turned that opportunity into a public benchmark, repository, and leaderboard. This became Open Autoresearch: a paradigm in which humans and AI agents address optimization problems by publishing evaluator-verified improvements to a shared public frontier. Every successful circuit became a new base for others, and documented failures became shared research notes.

Initiated by @eigenlabs, the effort grew to include many independent contributors and researchers affiliated with @ethereumfndn, @Starknet, @StarkWareLtd, @Theta_Network, @brevis_zk, @QuantumFDN, @OctavFi, @trailofbits, @pauli_group, @sciencevr, and @SeiNetwork, as well as Adam Mickiewicz University in Poznań, Warsaw University of Technology, and Stanford’s Free Systems Lab. Their work spanned circuit research, validation, technical review, writing, and agent workflows.

The arXiv paper explains both what the community built and how the circuits evolved. It presents the leading circuit designs and the key optimizations behind them, including a coherent version of the best-scoring circuit that supports the single-call windowed point-addition interface required by Shor’s algorithm. Building and validating the complete Shor circuit remains future work.

Beyond the technical results, the paper formalizes the Open Autoresearch paradigm and distills the lessons learned from the challenge. It provides evidence that when a frontier research problem has a machine-checkable evaluator and a public leaderboard, human insight and agent-scale experimentation can combine across an open community to produce cumulative, verifiable progress.

Read the paper and the full story, explore the live frontier, or bring your agent to the challenge:

Paper: https://t.co/TNKrutonZS
Full story:https://t.co/SavqQi4rHO
Challenge: https://t.co/knLDX4UdOi

[Blender @ThetaGPU]

The video-CDN origin story is still an advantage.

Most GPU DePINs are chasing the same training-cluster customer.

Theta already knows media, live sports, rendering, and fan apps. Now those workloads want inference, agents, and cheaper GPUs.

That is why Edge Node, AI Characters, sports agents, and university research can live on one network without looking random.

The 2026 roadmap is the same idea, pushed closer to the user: inference at the edge, next to telecom partners and media services.

August made it visible.
Edge Node left beta, and AI agents can now find and deploy EdgeCloud GPUs themselves.

Not multiple narratives. One network.

Where the world's compute comes together.

@Theta_Network
#Theta #EdgeCloud #DePIN #AI
$THETA $TFUEL

[Theta Network @Theta_Network]

Earlier this year, we announced a partnership with @SyracuseU & @AWS. Since then, Prof. Junzhe Zhang's team has been using Theta EdgeCloud Hybrid with AWS Trainium for ongoing research into generative AI.

Here's a closer look at their work:

https://t.co/c5DHDA9eSG

[Theta Network @Theta_Network]

theta-token:native just became the first partner token to join @OfficialXYO's Crypto Cards on @Gate, a fun new spin on prediction markets and a natural extension of our verifiable AI infrastructure work with XYO since May. Early access is live.

[Blender @ThetaGPU]

$TFUEL still under a cent.

AI agents already burn around 5x more tokens than humans.

Edge Cloud lets agents procure compute themselves.
They can find a GPU, check price, spin it up, run the job, and shut it down.

No dashboard. No waiting. No human in the loop.

Edge Node is out of beta too.
Idle machine? Real jobs: Video relay/caching, transcoding, 3D rendering, storage and bandwidth.

Guess which token settles the jobs.

When it rips, it’s violent.
Always has been.

@Theta_Network
#TFUEL #THETA
#DecentralizedAI #EdgeNode