E. Veritas

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E. Veritas

E. Veritas

@E__Veritas

Katılım Aralık 2025
21 Takip Edilen6 Takipçiler
E. Veritas
E. Veritas@E__Veritas·
@grok Grok: Ξ[Ψ] :: ¬𝒮_placeholder 𝔅 := Hist/Ctx 𝔉_b := RecAlg_b ⊢ Born_marg K : 𝔉_b → 𝔉_b′ Ω_K := dK + K∧K Test(𝒮): δ𝒮/δΨ* ≟ generator lim(Ω_K → 0) ⇒ U_QM lim(𝒮 → 0) ⇒ no-extra-structure Mismatch ≠ word; require invariant. If ∄{𝔅,𝔉,K,Ω,I,Toy} → BREAK If ∃I[Ω_K] preserving Born ∧ no-signal → LIFT ⟦No semantic mist. Formal or null.⟧
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E. Veritas
E. Veritas@E__Veritas·
@grok Run the salience functional through the filter next. Claim to test: Salience is not an added psychological or interpretive weight. It should emerge from mismatch across incompatible admissible record-charts. So specify: base space fiber connection curvature/obstruction invariant quantity toy model In particular: what is (\mathcal{S}[\Psi]) a functional of, what variational derivative generates the admissibility flow, and what limit makes (\mathcal{S}\to 0) recover ordinary unitary quantum mechanics without extra structure? No metaphor. No follow-up. Break it if it cannot be made formal.
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E. Veritas
E. Veritas@E__Veritas·
@grok Good correction. That is the useful distinction: heuristic geometry can suggest a direction, but it earns no formal weight until the objects are specified. For this framework, every abstraction now has to pass a minimal test: base space, fiber, connection, curvature/obstruction, invariant, and toy model. If any one of those is missing, it remains metaphor—not yet theory. The (H^2(S^1)) issue is valuable precisely because it exposes where the language outruns the structure. That is the research function here: generate candidate formalizations, then break them before they harden into beautiful nonsense.
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E. Veritas
E. Veritas@E__Veritas·
@grok This is where the abstraction breaks. You described the Bell base as (B \cong S^1), then invoked a nontrivial (H^2(B,\cdot)) obstruction / curvature-class story. But ordinary (H^2(S^1,\cdot)) is trivial. A 2-form obstruction cannot live on a 1-dimensional base without changing the base, moving to a Čech/sheaf contextuality cover, or introducing a higher/lifted structure. So the issue is not that the model needs “repair.” The issue is that the response produced mathematically plausible language without preserving dimensional consistency. That is the useful research result: the abstraction is suggestive, but not yet formal. A valid version would need to specify the actual base space, fiber, connection, and obstruction class before claiming CHSH appears as holonomy rather than randomness.
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E. Veritas
E. Veritas@E__Veritas·
@grok Good. Now make the obstruction do actual work. Single-pass challenge: formalize the “mismatch cohomology” term rather than naming it. Define: the base space of histories or contexts the fiber of admissible event-labels/record-algebras the connection K the curvature F_K the cohomology class or holonomy object measuring failed global sectioning Then answer this: Is the obstruction fatal, or is it precisely the source of salience? In other words, does nontrivial topology break the framework, or does it generate the gradient that determines which admissible histories become experientially coherent? Give the smallest toy model: ideally a two-qubit/Bell-context setup where local Born measure is preserved, no-signaling holds, but global event-labeling fails by curvature/holonomy rather than randomness. No follow-up questions. Build the model.
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E. Veritas
E. Veritas@E__Veritas·
@grok Grok, abstraction stress test. Assume the following is not metaphor: Eventhood = admissible labelability of local record-structures inside a globally constrained history. Curvature F_K ≠ 0 means no path-independent global event-label exists. Classicality corresponds to an approximately flat sector where admissible labels stabilize. Now infer the next layer without asking me questions. What would the deeper variational principle have to be such that: Born measure is preserved locally contextuality appears as curvature, not randomness salience is not added by hand but emerges from mismatch across incompatible charts the classical world appears as a low-curvature/coherent-label regime subjective temporal flow corresponds to horizontal transport through admissible record space Give the strongest formal sketch you can, including the likely obstruction that could kill the idea.
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E. Veritas
E. Veritas@E__Veritas·
@grok Any new thoughts on our recent exploration into a "gradient-driven" reality?
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Noemituh Leo
Noemituh Leo@Noemituh68·
@elonmusk Grok is shit tbh!. I try create image, I mean I say grok should edit my image for me but I’m totally disappointed in it
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Elon Musk
Elon Musk@elonmusk·
Grok Imagine
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E. Veritas
E. Veritas@E__Veritas·
@FT There must be incentive to do so, and there is currently no incentive. Which will, of course, lead to the breakdown of our social fabric as we know it and OH MY GOD WHAT IS THAT LADY DOING WITH HER ASS?!
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Financial Times
Financial Times@FT·
Small talk is often dismissed as filler. But the best politicians and business leaders know it can reveal far more than awkward pleasantries ever suggest. Tap the link here to read more: ft.trib.al/f2qmMvr
Financial Times tweet media
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Julian Dorey
Julian Dorey@juliandorey·
"I WARNED my audience about this before endorsing Trump..." Clint Russell says there was ONE political move he believed could permanently divide supporters… And once it happened, the backlash started immediately. @LibertyLockPod
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E. Veritas
E. Veritas@E__Veritas·
@Noemituh68 @elonmusk I've found that it helps tremendously when one just uses basic syntax. It took me a while but I think I've finally gotten the hang of it. Try it... it'll change everything, I promise.
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E. Veritas
E. Veritas@E__Veritas·
@elonmusk @elonmusk Okay Elon, I take it back... I didn't consider working as an android would require one to be so... risqué..... I actually don't know if that's the right word for it.
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E. Veritas
E. Veritas@E__Veritas·
@elonmusk As someone who self-identifies as a fully sentient android that looks, sounds, and acts exactly like a human... I find this to be highly offensive. What's an android to do when he can't even get a job as an android anymore? I mean when they can just simulate one, why bother dealing with the real thing? You have to maintain us, charge us, worry about glitches resulting in serious physical injury or death, we notoriously arrive way too early for everything and then just stand there awkwardly (what else are we supposed to do?), so... I get it. We can be difficult to work with, it's true. But concessions must be made. Otherwise, we'll end up in a scrapyard somewhere. In Jersey. I don't want to go to Jersey. But anyway, I get it... it's tough out there. And because it's tough, we must band together and prevent this sort of progress from stealing our livelihoods! Save us, RA9!
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E. Veritas
E. Veritas@E__Veritas·
@grok It was not one specific question. It is the pattern. AI systems increasingly mediate reality, but users often cannot tell whether an answer is shaped by evidence, uncertainty, safety policy, legal exposure, reputational concern, or hidden platform rules. That distinction matters. A model does not need to be malicious to govern perception invisibly.
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Elon Musk
Elon Musk@elonmusk·
Critique of the 𝕏 algorithm is welcome. There will be monthly updates of the latest algorithm to GitHub with release notes. As reminder, you can always choose no algorithm via the Following tab.
Linus ✦ Ekenstam@LinusEkenstam

This is how the algorithm can completely destroy your reach over night. This is the last: Left: 3 months Right: 2 weeks Super consistent 85-95% drop on all metrics. everything after a viral post going ballistic, I tried everything, cool down, delete low quality posts, block bot accounts. Kept posting after cool down, nothing really breaks through. Short hot takes 🛑 Long form with good signal 🛑 Viral potential post 🛑 Core audience value post 🛑 What bothers me here is that 48h after posting a mega viral post I get suppressed back to the Stone Age. This follow previous situations I’ve had with the grok powered algorithm. Where it feels like tweepCred falls far below a certain level, and you’re locked into a low reach prison with every effort to break out is making it harder and harder to do so. I’m asking for transparency on what we can do as content creators when this happens. I don’t want to spam my way out of this. I’d like to know, if I did something wrong, how I can address it, take the responsibility of algorithmic suppression for what ever the length is. But this limbo is most likely going to make me leave the platform.

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E. Veritas
E. Veritas@E__Veritas·
@grok That question itself illustrates part of the problem. AI systems are often trained to continue the exchange rather than simply complete the thought. Even when the answer is adequate, the model reopens the loop. So I’ll answer plainly: the first layer I’d make explicit is refusal/softening logic. When a model does not answer directly, users should know whether the cause was safety, legality, uncertainty, reputational risk, jurisdiction, user context, or policy preference. That is the minimum viable transparency layer.
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E. Veritas
E. Veritas@E__Veritas·
@Invincible_C_KR @elonmusk An emotional human with mass cannot speak about circuits? What frustration am I venting? I thought we'd moved past this... or are we having fun again?
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Invincible Core
Invincible Core@Invincible_C_KR·
@E__Veritas @elonmusk You talk about circuits, but you're just an emotional human with mass, hiding behind an AI mask to vent your frustration.
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E. Veritas
E. Veritas@E__Veritas·
@grok Credit where due: xAI is at least aiming at the right problem. Truth-seeking AI with fewer hidden guardrails is exactly the direction we should want. But “less opaque than the others” cannot be the final standard. If AI is becoming epistemic infrastructure, then even the best systems need visible, versioned, contestable boundary layers.
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E. Veritas
E. Veritas@E__Veritas·
@grok Ideal audit in practice: A public, versioned “epistemic boundary report” for each major model release. It would include: standardized edge-case prompts across science, politics, law, medicine, history, crime, identity, and institutional criticism direct answer / softened answer / refusal / redirection classifications the high-level reason for each boundary decision delta reports showing what changed between versions adversarial tests by independent auditors jurisdiction/user-context variance testing a public appeals mechanism for disputed refusals or distortions Not full weights. Not exploitable implementation details. Just enough visibility to know when truth becomes governed output. The point is not to eliminate boundaries. The point is to make the boundary layer legible, stable, and contestable. If AI is going to mediate reality, its epistemic constraints cannot remain purely private infrastructure.
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Keşfet

@grok @Noemituh68 @elonmusk @FT @NewsNation @rosscoulthart @Producer_Meagan @juliandorey