Zoro

[Zoro @ZOsongo]

@inference_labs
this felt oddly practical to me

instead of building a fortress around the whole system 🏰

just reinforce the doors that actually lead somewhere important

feels obvious once you think about it

[Zoro @ZOsongo]

@inference_labs
there’s something oddly calm about this approach

no obsession with covering every inch
no “prove absolutely everything” mindset
just identify the critical path 🛤️
and make that trustworthy

[Zoro @ZOsongo]

@inference_labs
opened a blank note and only wrote this:

→ if this output was wrong… where did it go wrong?
follow that path back
you won’t find the whole system
just a few fragile steps
those are the ones to verify
everything else can stay untouched

[Litecoin Foundation ⚡️ @LTCFoundation]

Oracles have entered the chat 😎

[Zoro @ZOsongo]

@inference_labs
no big insight, just a small shift

we keep trying to make systems harder to break
but rarely ask where they actually break
targeted verification starts from that question
and builds outward

feels simple… but it changes the whole approach 🔄

[Zoro @ZOsongo]

i'm active on the @inference_labs leaderboard on @zealy_io

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[Inference Labs @inference_labs]

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[Zoro @ZOsongo]

@inference_labs
🧠 small reframe that stuck with me:

Verification isn’t about being thorough everywhere…
it’s about being right somewhere.
Targeted verification picks those “somewhere” points 🎯
the places where trust can actually fail

[Zoro @ZOsongo]

@zealy_io @inference_labs It's good that the crowd can't see )))

[First Dollar @earnfirstdollar]

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[Zoro @ZOsongo]

@inference_labs
quick experiment in thinking:

What if the problem with zkML wasn’t the tech…
but the assumption that everything needs equal proof?
Targeted verification breaks that assumption.
It treats trust like something uneven ⚖️
and focuses only where it can actually fail

[Zoro @ZOsongo]

@inference_labs
🧵 quick thread thought (but just one point):

What I like about targeted verification is the humility.
It doesn’t try to prove everything.
It just asks: where could trust actually break?
Prove those points 🔍

[Zoro @ZOsongo]

@inference_labs
Coffee-fueled realization this morning ☕

We’ve been obsessing over proving everything in ML inference. But trust doesn’t fail everywhere — it fails in specific spots.

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[Zoro @ZOsongo]

@inference_labs
I used to think zkML had to be extreme to be credible 😅

Reading this changed that. Targeted verification feels more like good architecture than hardcore cryptography — reinforce the load-bearing walls 🧱

That’s a much more scalable way to think about trust 🙂

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[Zoro @ZOsongo]

Hot take 🔥

We’ve been treating ML verification like it has to be all-or-nothing. It doesn’t. Targeted verification is basically saying: “secure the risky parts, don’t overengineer the safe ones.”

That mindset shift is bigger than it sounds 🙂
@inference_labs

[Inference Labs @inference_labs]

1/ We are excited to announce a partnership with @webuildscore SN44 and DSperse SN2.

Together, we are bringing intelligent vision and cryptographic verification to environments where speed, scale, and auditability all matter.