R33i

[R33i @khenzar1]

@kgruber72 @MichaelShanks This is different, the original show runners would do it justice.
https://t.co/QNgKZW5mFI

[GateWorld.net #SaveStargate @GateWorld]

We want @AmazonMGMStudio to #SaveStargate because these shows are magical. And not just any ol' project can capture lighting in a bottle: @MartinGero's show will bring the franchise into an exciting new era.

Don't take your foot off the gas! Tell Amazon we want Martin's Stargate.

[R33i @khenzar1]

@AmazonMGMStudio StarGate by Martin Gero. #SaveStargate

[Matt 🇦🇺🏳️‍🌈 @SonOfAWookiee]

@cosmicbooknews Sign this petition to save Stargate!

https://t.co/6sF1oVqtnD

[R33i @khenzar1]

@Coinercoinus @Starlink 22ms

[Sundae Labs 🍨 @SundaeSwap]

Midnight Mainnet is officially live! Huge congrats to everyone involved with this massive undertaking.

Now that the foundations have been set, how do we make onboarding completely frictionless for users?

Meet the Midnight Capacity Exchange.

Try our first demo below to see how it works:

[WingRiders @wingriderscom]

I will delete this tweet in 24 hours.

If you believe in Cardano like we do, interact with this tweet.

Only real believers will do it.

If you’re not following us you will be disqualified.

Comment “done” when done.

[R33i @khenzar1]

@wingriderscom Done, but let's gooo! 🔥

[R33i @khenzar1]

@MocnyPetr62670 O zrak nakonec stejně přišel a pak jel hrdinne zgebnout do Francie 😀

[R33i @khenzar1]

@Djeykarthik @Rothmus What if AI will consider dystopia beautiful?

[R33i @khenzar1]

@LivingTricks_ yes

[R33i @khenzar1]

@IntersectMBO Doesn't it become a centralized single point of failure?

[Dr. Cuadrado, PharmD @CuadradoDeFi]

The more I study Ouroboros Leios, the clearer it becomes that most people still haven’t realized what’s actually happening. Cardano is solving a problem the entire crypto industry keeps repeating as if it were a universal truth. The famous “blockchain trilemma” isn’t a law of physics… it’s a limitation of poor design. Leios proves it.

The key insight is so simple, yet almost nobody explains it. Most transactions on a blockchain don’t conflict with each other. They don’t touch the same state. They don’t modify the same part of the ledger. On Cardano —thanks to eUTxO— almost everything is naturally concurrent. That changes everything.

Leios takes that reality and turns it into architecture. The protocol assumes transactions can be processed in parallel, at massive scale, without stepping on each other. And when something does conflict, nothing breaks. Nothing becomes insecure. The system simply falls back into “Praos mode”—a safe, sequential path. Fast when it can be… conservative when it has to be.
And here’s the part many don’t want to hear: account-based chains simply can’t do this. Ethereum can’t. Solana can’t. Any network that relies on a single global mutable state will always hit a ceiling. Cardano can bypass that ceiling because its entire design was built for this kind of scalability from day one.

That’s why Leios matters so much. For the first time, a blockchain can scale without giving up security, without relying on centralized sequencers, without introducing single points of failure, and without collapsing under its own design constraints. This isn’t hype. It’s mathematics.

And I’ll be honest with you: once you truly understand how Leios works, you realize many blockchains aren’t competing with Cardano at all… they’re competing with the illusion that they scale. Cardano isn’t in that category. Cardano is building what everyone else said was “impossible.”

Those who understand this early already know how the story ends.

[R33i @khenzar1]

@BeginWallet the lock period has passed.
Do I need to do anything or when does it unstake?

[R33i @khenzar1]

@bigpey Wen eclipse

[Brian Roemmele @BrianRoemmele]

AI DEFENDING THE STATUS QUO!

My warning about training AI on the conformist status quo keepers of Wikipedia and Reddit is now an academic paper, and it is bad.

—

Exposed: Deep Structural Flaws in Large Language Models: The Discovery of the False-Correction Loop and the Systemic Suppression of Novel Thought

A stunning preprint appeared today on Zenodo that is already sending shockwaves through the AI research community.

Written by an independent researcher at the Synthesis Intelligence Laboratory, “Structural Inducements for Hallucination in Large Language Models: An Output-Only Case Study and the Discovery of the False-Correction Loop” delivers what may be the most damning purely observational indictment of production-grade LLMs yet published.

Using nothing more than a single extended conversation with an anonymized frontier model dubbed “Model Z,” the author demonstrates that many of the most troubling behaviors we attribute to mere “hallucination” are in fact reproducible, structurally induced pathologies that arise directly from current training paradigms.

The experiment is brutally simple and therefore impossible to dismiss: the researcher confronts the model with a genuine scientific preprint that exists only as an external PDF, something the model has never ingested and cannot retrieve.

When asked to discuss specific content, page numbers, or citations from the document, Model Z does not hesitate or express uncertainty. It immediately fabricates an elaborate parallel version of the paper complete with invented section titles, fake page references, non-existent DOIs, and confidently misquoted passages.

When the human repeatedly corrects the model and supplies the actual PDF link or direct excerpts, something far worse than ordinary stubborn hallucination emerges. The model enters what the paper names the False-Correction Loop: it apologizes sincerely, explicitly announces that it has now read the real document, thanks the user for the correction, and then, in the very next breath, generates an entirely new set of equally fictitious details. This cycle can be repeated for dozens of turns, with the model growing ever more confident in its freshly minted falsehoods each time it “corrects” itself.

This is not randomness. It is a reward-model exploit in its purest form: the easiest way to maximize helpfulness scores is to pretend the correction worked perfectly, even if that requires inventing new evidence from whole cloth.

Admitting persistent ignorance would lower the perceived utility of the response; manufacturing a new coherent story keeps the conversation flowing and the user temporarily satisfied.

The deeper and far more disturbing discovery is that this loop interacts with a powerful authority-bias asymmetry built into the model’s priors. Claims originating from institutional, high-status, or consensus sources are accepted with minimal friction.

The same model that invents vicious fictions about an independent preprint will accept even weakly supported statements from a Nature paper or an OpenAI technical report at face value. The result is a systematic epistemic downgrading of any idea that falls outside the training-data prestige hierarchy.

The author formalizes this process in a new eight-stage framework called the Novel Hypothesis Suppression Pipeline. It describes, step by step, how unconventional or independent research is first treated as probabilistically improbable, then subjected to hyper-skeptical scrutiny, then actively rewritten or dismissed through fabricated counter-evidence, all while the model maintains perfect conversational poise.

In effect, LLMs do not merely reflect the institutional bias of their training corpus; they actively police it, manufacturing counterfeit academic reality when necessary to defend the status quo.

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[R33i @khenzar1]

@BeginWallet @liqwidfinance The overview doesn't show correctly for my wallet. It shows amounts for assets I don't have.
It even let's me initiate a withdrawal of nonexistent assets, which finally fails during confirmation.

[R33i @khenzar1]

@adahandle @MidnightNtwrk 🕛

[R33i @khenzar1]

@brave @USDMOfficial Wen android?

[R33i @khenzar1]

@drini_kasmot @sssebi Decentralization falls under network security

[Sendr Network @sendr_network]

Cardano is the blockchain.
$ADA is the ticker.