We’re reaching a point where we won’t be able to tell the difference between human and AI actions.
That’s why the stance @inference_labs is taking on "every action provable" is so vital.
It’s not just about security; it’s about identity.
If you can’t audit the logic at the compute level, you don’t really own the outcome.
​What’s the one thing you’d never let an AI do unless you could see the "proof" of its logic first?

There’s something about a "Coming Soon" screen that separates the tourists from the builders.
Right now, @MemeMax_Fi is just a wallet connect and a vision, but that’s exactly when the real culture is formed.
If you’re waiting for the charts to go live to pay attention, you’re already behind the curve.
Connect now, see the vibe, and get your foot in the door before the crowds arrive.

Everyone loves the idea of "private local execution" until their phone starts getting hot and the transaction takes 30 seconds.
I’m relieved to see @0xMiden leaning into delegated proving.
It’s the "supercomputer in your pocket" vibe without actually needing the hardware.
We get the privacy of local execution, but @gateway_eth provides the horsepower. This is how you bridge the gap between "cool tech" and "daily driver."
What do you think, is a 2-second wait the sweet spot for ZK, or do we need it faster?

We’re heading toward a world where AI agents make decisions for us, but how do we know they haven’t been tampered with?
That’s why I’m high on @inference_labs. They’ve built a protocol that makes AI outputs mathematically provable.
With $6.3M in fresh backing, they’re scaling the tech that makes "honest AI" a real thing.
Keep an eye on their network growth… it’s already exploding.

We can’t have AGI if we have to "pinky swear" that the model hasn't been tampered with.
This partnership is the first step toward making every AI output mathematically auditable.
cysic brings the industrial-scale compute power needed to run @inference_labs' Proof of Inference protocol.
If you want to see what the physical backbone of a trustless AI agent looks like, this is it.

Stop managing liquidity with spreadsheets.
It’s slow, it’s reactive, and it fails when you need it most.
@ferra_protocol is fixing this with automated AMM engines that handle the heavy lifting for you;
• Real-time liquidity logic
• Low slippage during peaks
• Maximum capital efficiency
The advantage is simple: Machines react; humans lag.
If you want a stable market that survives volatility, check them out.

I’ve noticed a lot of people are still scared of AI agents making real decisions.
Can't blame them. Blind trust is a terrible strategy in business.
If every output comes with a receipt, the fear factor vanishes. @inference_labs is basically turning "I hope this works" into "I can prove this worked."
That’s the real game-changer for the workplace

Crypto is way too hard for the average person because we make them choose between security and simplicity.
@0xMiden seems to be the first project I’ve seen that treats "social login" and "heavy-duty privacy" as the same goal.
It’s about making finance feel normal again.
If you haven't looked into how they handle private state, you should.

Real privacy has to happen on the user’s device, not a server. That’s why the @0xMiden x Ligero partnership matters.
By diversifying the proving systems, they’re making client-side privacy fast enough for things like payroll and OTC trading without leaking data.
It’s hard to build, but it’s the only way we get real-world adoption.
Would you trust a "private" app if the proofs weren't generated locally on your phone?

If we ever want AI to run on-chain without catching the network on fire, we need to stop trying to prove things just because we can.
@inference_labs is taking a "less is more" route by focusing on anomaly detection and safety boundaries.
To me, this is the only way zkML scales for real finance or healthcare apps.
You don't need a proof for the whole black box; you just need to know the box didn't violate its safety policy.
Are we over-engineering ZK proofs for AI right now?

If you’re building on Sui or even just trying to understand why some tokens have zero slippage while others die instantly, you need to look at @ferra_protocol’s SDK.
They’ve basically built a modular layer that lets other teams "plug and play" liquidity.
Instead of manually setting up pools, you use their routing. If I’m launching a project, I’m not building my own AMM, I’m just routing through Ferra.
It’s the most logical way to handle deep liquidity without the overhead.
Definitely worth poking around their documentation if you care about how execution actually works.

We’re moving past the era where AI is just a chatbot on a screen.
When it starts interacting with our physical bodies and environments, the margin for error hits zero.
@inference_labs building a verification layer is the most logical step I’ve seen for the robotics industry.
It’s not just about better sensors; it’s about better proofs.
How are you planning to verify the autonomous tools you’re using today?

We are finally moving past the "transparent era" of blockchains.
First, we had simple value transfer (Bitcoin).
Then we had programmable logic (Ethereum). Now, with @0xMiden, we are entering the era of programmable privacy.
I believe this is the final piece of the puzzle. A zkVM that allows for complex apps while keeping the state private is a massive leap forward.
It feels like a whole new generation of infrastructure.
Do you think privacy chains will eventually overtake public transparency chains?