Lucian☣️☣️

Brand Ambassador||Community moderator||Community manager||

[Lucian☣️☣️ @LucianBasi]

@majgoswami @grok what’s the name of this movie

[Lucian☣️☣️ @LucianBasi]

The model is trained on annotated images of healthy and infected leaves to help farmers identify disease outbreaks early, reduce crop losses, and improve agricultural productivity.

@inference_labs #Sertn.ai #Machinelearning #autonomousAI

[Lucian☣️☣️ @LucianBasi]

Automated Detection Of Gray Leaf Spot Disease on Corn Leaves Using https://t.co/fiQLAQ0HlX

Model Link: https://t.co/fORNL79Fm0

Dataset Used: https://t.co/lIrSOkOFlH

This project uses computer vision to detect Gray Leaf Spot disease in corn leaves.

[Inference Labs @inference_labs]

1/ A lot of the AI world is focused on bigger models and better interfaces.

Inference Labs is focused on something just as important: trust infrastructure for AI systems that need to operate in the real world.

[Inference Labs @inference_labs]

As agent ecosystems grow, verification becomes infrastructure, not a feature.

With zkML + Proof of Inference, we can:
• Prove model execution
• Verify agent outputs
• Enable trustless automation between systems

Clawdbot-style agents + verifiable execution = real autonomous economies.

[Harushelby @IberedemOd94734]

Trustless computer vision is no longer theoretical.

Join us for the first Inference Labs AMA as we break down "PROOF OF INFERENCE" how to verify what vision models actually saw and computed, not just what they claim.
📅 Feb 26
⏰ 2pm UTC
🎙️ With co-founder @colingagich
If AI can see, it should also be provable.

@inference_labs #AMA #ProofOfInference

[Inference Labs @inference_labs]

As agents start touching money, logistics, and infrastructure, “trust me” stops working.

Critical systems need proof, not promises. That’s why we’re building verifiable inference at Inference Labs.

Join the our community → Discord / TG:
https://t.co/HA6xxxFU5G
https://t.co/D1HKm4n5KC

[Inference Labs @inference_labs]

Trust in autonomy should not depend on vendors.

It should be built on cryptographic proof that stands on its own.

Connect with our community on Discord and Telegram.
https://t.co/5g1aFlFN9a
https://t.co/KzMgRbJfJw

[Inference Labs @inference_labs]

Most LLM benchmarks assume the world is static. Reality isn’t.

In TruthTensor, we evaluate models in live prediction markets under drift and show that models can follow instructions locally while violating them over time.

Same prompts. Same data. Very different reasoning behavior.

https://t.co/WyPlYP8dgz

[Lucian☣️☣️ @LucianBasi]

@Fiftybabanla You posting people now without their consent?

[Inference Labs @inference_labs]

1/6 Season 2 of the TruthTensor Crucible is now closed!

The seasonal leaderboard locked.
The bonuses are credited.
The data is being reviewed.

What's been accomplished so far has been extraordinary. 🎉

[Inference Labs @inference_labs]

JSTprove is going live on Subnet-2 mainnet.

After a week of successful testnet proving, we’re now scaling to thousands of proofs per week and unlocking verifiable inference for models that weren’t feasible before.

This is a big step for Proof of Inference.

[Inference Labs @inference_labs]

If your zkML system requires full-model proving, it won’t reach production.

Modularity wins.
Distribution wins.

DSperse + JSTprove win.

[Real Madrid C.F. @realmadrid]

🙌 Don Federico Santiago Valverde Dipetta 🙌

[Inference Labs @inference_labs]

https://t.co/4ePt9SyUBm

[Inference Labs @inference_labs]

1/ Frontier AI is powerful, but without proof it remains a black box.

Industries need verifiable systems, from robotics to finance to autonomous intelligence.

[Benjamin @Samlinsben]

Community-Driven

What if your taste was the algorithm?

POPcast® PEERstream™ proves culture is better
when creators and viewers build together.

This is people-powered media.
@POPOLOGYNetwork

[Lucian☣️☣️ @LucianBasi]

Think of it as the engine that transforms complex AI logic into something mathematically provable.

[Lucian☣️☣️ @LucianBasi]

DSperse focuses on creating high-integrity cryptographic infrastructure. It enables large AI computations to be efficiently mapped into constraint systems suitable for zero-knowledge proofs.