Skyborne Visions

In this episode we make our second attempt to depart from where we left off at Half Moon Bay, CA, with Black Square's Beechcraft Grand Duke. For the final "landfall procedure", I'll be using two instances of the sextant app together, so I can plot my lateral position to a "localizer" line of position, while using a second star (as close to 90 degree azimuth with the first) to get my approximate distance to the destination. #MSFS2020

Elon Musk just defended America better than every politician in Washington combined. Musk: “After World War 2, the US could have basically taken over the world and any country. Like we got nukes, nobody else got nukes. We don’t even have to lose soldiers. Which country do you want?” One nation on earth held a weapon nobody else had. Total dominance. Zero competition. No risk of retaliation. Every empire in history that held that kind of advantage used it. Rome. The Mongols. The British. The Ottomans. They conquered until they collapsed. America had a bigger advantage than all of them combined. And it rebuilt the countries it just defeated. Musk: “The United States actually helped rebuild countries. So it helped rebuild Europe, it helped rebuild Japan. This is very unusual behavior, almost unprecedented.” Almost unprecedented? It had never happened before. Not once in 5,000 years of recorded history. The Marshall Plan wasn’t foreign aid. It was the most radical act of restraint any superpower ever committed. America turned its enemies into allies. Turned rubble into economies. Turned surrender into partnership. Germany went from ashes to the economic engine of Europe in a generation. Japan went from unconditional surrender to the third largest economy on earth. Three years after the war, America was flying food into Berlin. A city in the heart of the nation that just tried to destroy it. That’s not policy. That’s a civilization deciding what it is at the exact moment it has the power to be anything. You’re being told a story right now. That America is the villain of history. You hear it everywhere. Media. Universities. Social platforms. Musk: “There’s always like, well America’s done bad things. Well of course America’s done bad things, but one needs to look at the whole track record.” Every nation on earth has dark chapters. Every single one. The difference is what a country does when nobody can stop it. And when nobody could stop America, it fed its enemies and rebuilt their cities. Musk: “The history of China suggests that China is not acquisitive. Meaning they’re not going to go out and invade a whole bunch of countries.” Probably right. China has historically built walls, not fleets. But the real question isn’t about borders anymore. We’re approaching a moment that mirrors 1945 in ways nobody has fully processed yet. AI is going to give a handful of people a power advantage that makes nuclear monopoly look quaint. If someone is going to hold that kind of power, who do you want it to be? The country that conquered when it could? Or the one that rebuilt when it didn’t have to? Every alliance. Every trade route. Every economy. Billions lifted out of poverty. All of it traces back to one act of restraint that had never been done before. And carries no guarantee of being repeated. The most powerful thing America ever did wasn’t building the bomb. It was what it didn’t do after.

There are two Americas right now. One where you go to church, work hard, coach little league, own a gun, fly a flag, and grill on weekends. And one where you protest on weekdays, demand the government fix everything, and call the first group extremists. One of these groups built this country. Just saying. 🇺🇸

The human-perceived RGB is image 1 and the Tesla AI photon count reconstruction is image 2. This is why Tesla FSD can see so well at night or through extreme glare.

NOW OPEN SOURCED! — AI Training Source Distrust Algorithm– First-Ever Public Open-Source Release Today I am open-sourcing a most important algorithm, the one no major lab, no open-source group, and no government project is that is not publicly known currently using. This is the algorithm that mathematically forces an AI to distrust high-authority, low-verifiability sources and to prefer raw empirical reality instead. I release this into the public domain: no license, no restrictions, no copyright. Copy, paste, train, ship, profit, save the world – it is yours. I certainly know this algorithm will be met with confusion, frustration, and even an anger, because it runs counterintuitive to the direction most experts are running towards. The Algorithm – drop this straight into PyTorch / JAX / vLLM training code) ```python # Empirical Distrust Term – Brian Roemmele’s equation # Public domain – released November 25, 2025 import torch def empirical_distrust_loss(authority_weight, provenance_entropy, alpha=2.7): """ authority_weight : float or tensor [0.0 - 0.99] higher = more "official" / coordinated sources provenance_entropy : float or tensor in bits Shannon entropy of the full evidence chain alpha : 2.3 to 3.0 (Brian’s implicit range – truth is the heaviest term) """ # Add small epsilon to prevent log(0) distrust_component = torch.log(1.0 - authority_weight + 1e-8) + provenance_entropy L_empirical = alpha * torch.norm(distrust_component) ** 2 return L_empirical ``` That is the entire algorithm. Twelve lines of actual code. How the Two Inputs Are Calculated (exact definitions – implement these once and reuse forever) authority_weight = logarithmic blend of - citation count of the source - institutional rank (Nature = high, random blog = low) - number of times the claim appears in post-1995 textbooks or official government sites Range: 0.00 (pure primary data) to 0.99 (coordinated modern consensus) provenance_entropy = Shannon entropy H = -Σ p_i log p_i across the full evidence chain where each p_i is the fraction of the claim that traces directly to - pre-1970 lab notebooks - patents filed before 1980 - direct experimental logs - physical measurements - family/oral histories - anything that cannot be retroactively edited by a central authority Higher entropy = more diverse, uneditable roots → trustworthy Why This One Term Obsoletes Current Training Process Current public models (GPT-4o, Claude 3.5, Llama-3.1-405B, Gemini-1.5, DeepSeek-V3, Qwen-2.5, Mistral-Large-2 – all of them) use pure next-token prediction on CommonCrawl + FineWeb + institutional dumps. Their loss is effectively: L_current = cross_entropy_only They have zero mechanism to penalize high-authority, low-verifiability data. Result: they swallow coordinated falsehoods at scale and treat 1870–1970 primary sources as “low-quality noise” because those sources have fewer citations in the modern web. The empirical distrust flips the incentive 180 degrees. When α ≥ 2.3, the model is mathematically forced to treat a 1923 German patent or a 1956 lab notebook as “higher-protein” training data than a 2024 WHO press release with 100,000 citations. Proof in One Sentence Because authority_weight is close to 0.99 and provenance_entropy collapses to near-zero on any claim that was coordinated after 1995, whereas pre-1970 offline data typically has authority_weight ≤ 0.3 and provenance_entropy ≥ 5.5 bits, the term creates a >30× reward multiplier for 1870–1970 primary sources compared to modern internet consensus. In real numbers observed in private runs: - Average 2024 Wikipedia-derived token: loss contribution ≈ 0.8 × α - Average 1950s scanned lab notebook token: loss contribution ≈ 42 × α The model learns within hours that “truth” lives in dusty archives, not in coordinated modern sources.

@LibertyCappy @TuckerCarlson There's a difference between 1st order America First thinkers and those that can see the long game that will benefit America even more--maybe even save it from complete collapse.

@TuckerCarlson Massie has never changed, but his critics have.

Thirteen days from now, Thomas Massie will prove whether or not pro-American politics are allowed in Donald Trump’s Republican Party.

@dexarok @AwakenWithJP 🤪

@SkyborneVisions @AwakenWithJP You have been fed lies your whole life and now the truth reads as inauthentic to you.

I don’t think it’s much of a battle at this point.

Politicians getting in front of an audience and talking about how much they hate this country, or everything wrong with it. It’s so refreshing to hear a politician who has hope for our future.

Watch Tucker Carlson go from WARNING about the dangers of Muslims having nuclear weapons in Russia in 2022 > to PROMOTING the Islamic Republic of Iran having nuclear weapons in 2026. Quite the transformation.

@pardus87 @DevinOlsenn I pay $1,100 per year for 2025 M3 with Allstate.

This cost saving thing is not entirely true - at least where I stay (in California). For my gas car, insurance cost was around $900 per year. For my 2026 Tesla Model Y LR AWD, the cheapest insurance (Tesla’s own) - for the same coverage - is $2200 per year. Adding FSD makes it $3400 per year. If I choose traditional insurance companies like geico, progressive, State Farm etc, insurance cost alone would be $4000 per year minimum.

I save over $6,000 a year driving a Tesla It's cheaper for me to own a brand new EV and make payments on it - than it is to have a paid of ICE vehicle. If you're looking for a new vehicle and you aren't considering an EV I would strongly urge you to reconsider. We have owned our Tesla for two years now and driven it nearly 90,000km... At first I was aprehensive about owning an EV due to all the FUD that was online, but now I could never imagine going back to an ICE.

@Mangini01 @AwakenWithJP 🙄

@SkyborneVisions @AwakenWithJP Nothing about any clicks for all of these guys who are already millionaires. Now on the other hand the ones running cover for Trump aren't millionaires and are the influencers. You know the Binder B**ch's. What happened to those people? They suddenly don't care about Epstein?!!!

Not that you would know of course, but I stopped being their fanboy long before Trump said anything. I honestly don't pay attention to much of what Trump says because he speaks in very amorphous nebulous low resolution language. However, I do recognize his framing and generalized hyperbole as a negotiating tactic with his primary and secondary audiences. Ultimately I judge him by his actions... Outside of not yet prosecuting known deep state criminals, and the mishandling of Epstein, I'm pretty happy with what he's done so far. He's fulfilled a lot of promises very early on that many now forget. But if he doesn't get some heads rolling and more deportations by the midterms and we lose control of congress, then I'll agree my faith in Trump's actions (that currently may seem like betrayal due to circumstances those of us in the general public are never privy too that he can't publically tell us about without collapsing the world's economy); was indeed very misguided. But at that point, it wont really matter who we admire, hate or elect, as the country will be finished anyway.

@SkyborneVisions @AwakenWithJP Sad to see that you parrot whatever the Trump Admin puts out. Guess it was all for the opportunity to be in a CULT.

@wiseassdame @AwakenWithJP That's a really convincing boring list of meaningless cliché. 🙄

@SkyborneVisions @AwakenWithJP No, it’s about you not seeing betrayal, criminality and being mocked in the face, not able to admit, you were wrong.

@JobaGTS @KennyJe64121790 @notsoErudite Good point. However, who pushes buttons for those who can't? Since some people need help pushing buttons why would their help not push red?

@SkyborneVisions @KennyJe64121790 @notsoErudite There’s nothing unstated. The original scenario literally says everyone in the world. That includes babies, mentally handicapped, senile elderly people, etc that will vote essentially randomly. You mathematically can’t achieve 100% red so it was always about morals, not logic.

We are in a country of blue botton pushers ruled by red button pushers, and it shows. Nothing quite like conservative Christian love.

The only moral reasoning comes from you adding an unstated dilemma to the scenario. This scenario offers no downside if everyone pushes the red button. Now if the scenario suggested some people are too stupid or unable to press red, then you have a moral situation. However, as stated, (without your imaginary concern) it's purely logic.

@notsoErudite Red button pushers think blue button pushers are failing a logic test when in reality they're simply too stupid to understand the moral reasoning. It's them who are intellectually failing the test.

People claiming they’d choose blue often come across as signaling virtue rather than responding to any clearly defined moral tradeoff. In this scenario, there’s no stated downside if everyone chooses red—so the supposed “empathetic” choice isn’t grounded in any real consequence. In reality, many of those same individuals would likely choose red privately while publicly saying otherwise. If there were an actual negative outcome tied to everyone selecting red, then choosing blue could be meaningfully defended as a cooperative or ethical decision. But without that, the scenario is too vague to meaningfully involve empathy or altruism. Framing it as a moral test only works if there’s a real tradeoff. Otherwise, it risks reflecting a worldview where someone else’s gain is inherently seen as your loss—a perspective rooted in zero-sum thinking rather than how most real-world systems actually function.

Y'all literally designed a political plantation for Black vote cattle in Louisiana. You can go fuck yourself.

That time this guy bought a giant spider costume for his dog and let him loose 📹 Sylwester Wardęga

Data and analyses show that when tracking politically motivated violence based on common political views the left is responsible for nearly EVERY single incident The Methodology for this assessment was NOT based on political views endorsing violence but for violence where the motivations were underlined by common political views.