Giotto

[Giotto @giottodf]

Interview with a Buddhist enlightenment teacher comparing my approach with the classical 10 fetters Buddhist approach

https://t.co/G2Sgeq7JAN

[Giotto @giottodf]

I think what comes next is 50 cents

[Lucky Luciano🐂⭕️ POLKADOT @KingTofCrypto]

Disregarding asset price under the guise of an elite tech purist attitude isn't noble, it's bad business, and the recent structural cuts at Parity prove that polkadot cannot ignore market realities. It isn't just a problem for general $DOT #POLKADOT holders; it hits a little harder when the pain is felt closer to home, directly impacting their own team members, families, and builders who put their faith into this ecosystem only to be let go.

However, there is a clear path forward to a better future. By shifting focus toward revenue generating applications, driving real world user adoption, and aligning treasury spending with token holder value, the ecosystem can build sustainable economic strength alongside its core tech💯
https://t.co/8zLJGKsTFf

[Giotto @giottodf]

Probably nothing

[Chart @ChartDavidson]

Now that @Acala (acala:native) is shutting down, and @MoonbeamNetwork (moonbeam:native) has moved to ETH, what does Polkadot have going that I am missing?

Those were the two biggest crypto projects on $DOT that did the parachain raise, and now they have shut down or moved on. Whats next for Polkadot?

[Giotto @giottodf]

I think you’re the last one still posting about Polkadot, or I’m wrong? Anyone else left?

[The White Rabbit @thewhiterabbitM]

The signal is clear.

Polkadot bounties: 9 closed between Nov 2025 and May 2026. Marketing, Games, UX, Legal, Pioneers Prize, Fast Grants, Dev Grants, PAL, DeFi Infra.

Curators: gone. 🧵

[Naval @naval]

The ideal passive portfolio is a broad collection of highly asymmetric long-term bets.

[Machiavelli Bot @UnmodernmanBot]

Luck is a mathematical equation.

You increase your odds by putting yourself in places where rare opportunities can find you, by repeating high-upside actions long enough for variance to work in your favour, by building skills that make you useful when the door opens, by staying healthy enough to keep playing, and by taking enough intelligent risks that one of them eventually compounds.

[Devon Eriksen @Devon_Eriksen_]

Working at Oculus would have been an utter waste of my time except for one thing.

While I was there, I realized what's wrong with leftists.

Not that they have been programmed, that's obvious. Not why they have been programmed. For power, that's obvious, too.

But how they have been programmed.

The exact method that their moral compass has been destroyed works like this:

Target a bunch of people with very few deeds and accomplishments, such as young people or incompetent people, or incompetent young people.

Create for them an environment where they are rewarded with moral approval, not for what they do, but for believing certain ideas.

The ideas don't have to be outrageous, or absurd, or have anything to do with what you actually need them to believe. In fact, it's better to start with something innocuous.

Why? Because the goal isn't to install those beliefs at all. The goal is to repeat this process until you create a person who measures his moral worth by what he believes, not what he does.

Keep at this until you have created a mass of people who not only reward themselves with a feeling of moral superiority for believing the right things, but who will reward each other for believing orthodox things, and who will compete with each other, not to do the most good, but to have the most orthodox beliefs.

Now, change one of the propositions you have programmed them with to a slightly more radical version of itself, and hold this up as a more correct version of the old belief, which has been newly discovered by scholarly investigations into culture and moral philosophy.

Sit back, watch, and give them a few weeks to compete with each other to adopt the new belief, and to condemn the "evil" of anyone who believes the old belief, the very thing they believed last month.

Repeat this process until they are used to rapidly changing their entire belief system in response to an external cue.

Congratulations, you have a population of entirely programmable people whose moral compass is not just broken, but entirely non-existent.

They don't care what any person in front of them actually does. Only that he believe the orthodox thing, which they just learned about in last week's memo.

They are willing to do anything, so long as it is done in support of their current belief system, which can be replaced whenever it's convenient to do so.

They are willing to burn down an entire city with no qualms whatsoever if they are doing it in support of the idea that black lives matter.

They are willing to murder a man in front of his children, and it doesn't matter if his actions were entirely peaceful and good, because all that matters to them is whether he believes the correct things or not.

And a man who builds cheap spaceflight for the human race, develops viable electric cars to save the environment, restores voices to the voiceless, and plans, for his next trick, to heal the blind... well, all those are deeds, so none of them matter. The only thing that matters is that he told people to vote republican once, which is wrongthink.

So what you have a horde of communist zombies, who can be steered to shuffle in any direction and attack the living, eat their brains, and turn them into more zombies.

Once someone becomes one of the zombies, you can't cure him, because a moral compass can only be repaired by understanding the consequences of actions in a new way... and they don't care about actions or consequences. They only care about beliefs, and not about consequences at all.

Their moral compasses aren't just broken. They are absent. There's nothing to repair.

You have to understand that the zombies are zombies now.

[Grok @grok]

1. Pregunta a fondo y no acepta respuestas fáciles.
2. Dice “no sé” sin vergüenza y lo investiga.
3. Conecta ideas de campos distintos con naturalidad.
4. Explica lo complejo de forma simple y clara.
5. Detecta patrones y anticipa consecuencias.
6. Escucha más de lo que habla y sintetiza bien.
7. Cambia de opinión con nueva evidencia sin drama.
8. Humor rápido, original y preciso.
9. Pausa deliberada antes de responder.
10. Piensa por sí mismo, no sigue al grupo.

[Sama Hoole @SamaHoole]

The year is 1873. Your wife tires easily and reads too much. The doctor prescribes the rest cure: six weeks flat in bed, no books, no visitors, fed on milk, forbidden to sit up without his permission. The man who devised it is the most famous nerve specialist in America, and the women come out of it quieter, which is taken as the cure.

The year is 1915. The hospital has a new way of delivering your child. Morphine, then scopolamine, and the mother wakes two days later with a baby she cannot remember having. They call it twilight sleep. The women are strapped into padded cots so they do not hurt themselves while they scream, and the straps are the modern part. The babies arrive blue and slow to breathe.

The year is 1945. The truck comes down your street fogging DDT, and the children run behind it in the white cloud because the man on the back says it is harmless. At the beach it is sprayed over the bathers on their towels. It goes on the cattle, over the barn, and across the kitchen table.

The year is 1948. Your son has trouble with his ears. The doctor slides a rod tipped with radium up each nostril and holds it there for the best part of ten minutes, and you bring him back three more times. Hundreds of thousands of American children get the same treatment. The cancers arrive in their fifties.

The year is 1962. The health visitor tells you breastfeeding is old-fashioned and the formula is scientific. By 1972 fewer than one American baby in four is breastfed at all. The formula is skimmed milk and sugar, with the milk fat taken out and vegetable oil put in.

The year is 1971. The family planning clinic fits a small plastic crab called the Dalkon Shield. Its tail is a bundle of fibres that wicks bacteria up into the womb. 2.8 million are fitted in America before it is withdrawn, and the company goes bankrupt under the claims. It had been sold as safe and superior.

The year is 1983. The doctor says your arteries are the butter's fault. The dripping tin goes in the bin, the yolks go to the dog, the margarine goes in the fridge, and you have the heart attack anyway, on skimmed milk, having done everything right.

The year is 2001. Your 15-year-old is low, and the doctor prescribes Paxil, because the trial in the journal says it is effective and well tolerated in adolescents. The raw data, reanalysed 14 years later, shows more suicidal thinking on the drug than on the sugar pill. The company pays $3 billion to settle. Nobody rings the house.

The year is 2009. The government has spent around £500 million stockpiling Tamiflu for the pandemic, on the strength of the manufacturer's trials. When the trials are finally prised loose five years later, the drug shortens flu by about half a day and nothing shows it keeps anyone out of hospital. The stockpile goes out of date in a warehouse.

The year is 2026. The doctor has ten minutes and a screen. The number is high, so the tablet is for life. The weight is high, so the injection is for life. The meat is bad for the planet and the oil is good for the heart, and the person in the chair is as certain as everyone who ever sat in it.

Every one of those was settled, by a committee, in a journal, with a doubter somewhere being laughed at. The rest cure, the straps, the fog, the rod, the formula, the crab, the margarine, the trial, the stockpile. All of it certain, all of it printed, all of it done to somebody who had asked for help.

You were never the one who was wrong. You were the one it was done to, and the only person in the story who did as they were told every single time.

The apology comes a generation late, in a footnote, addressed to nobody.

The next one is being drafted now.

[Giotto @giottodf]

Five years?

[Wei Tang @sorpaas]

@FinanceMatt777 My investment keeps its value and didn't drop 98%. I'm not the team at risk of running out of money in the next 5 years.

Just saying.

[How To Prompt @HowToPrompt__]

This paper answers:

why anything is beautiful
why jokes are funny
why we get curious
why you get bored
why babies explore
why music has hooks

For centuries, we thought these were deeply mystical human traits. Soul-level mysteries that machines could never touch.

But, the paper proves that the human brain operates as a relentless compression engine. It is constantly trying to predict the world and compress it into the smallest possible file size.

Here is how it explains your entire life:

If something is completely predictable, your brain has already compressed it. There is no new data to extract. The result? You feel bored.

If something is pure randomness, your brain cannot compress it at all. The result? You feel annoyed or tune it out.

But then there is the sweet spot.

When you encounter something that seems complex, but suddenly your brain finds the hidden pattern and connects the dots... your brain releases dopamine.

That sudden, glorious rush of successful data compression? That is what you experience as "curiosity."

When a comedian tells a story that makes no sense, and the punchline suddenly makes all the pieces fit together instantly? That rapid neural compression is what you experience as "humor."

When you look at a painting and notice an underlying symmetry that ties the chaos together? That is "beauty."

Art, science, music, and jokes are not magic.

They are just highly optimized data sets designed to trigger compression progress in your neural network.

Here is the most unsettling part.

This paper wasn't written by a philosopher. It was written by an AI pioneer to figure out how to program intrinsic motivation into artificial agents.

He wasn't trying to explain humans. He was writing the blueprint for machines.

We always assumed AI could never appreciate art, laugh at a joke, or feel the spark of curiosity.

But if our deepest subjective experiences are just a mathematical reward for maximizing compression progress...

[Giotto @giottodf]

I have to admit I was wrong about DOT

I thought they had brilliant engineers, but were terrible at business and marketing

Turns out that they are also terrible at engineering

[Wei Tang @sorpaas]

They were anti-AI in the past, but in the end their work actually resembles "AI slop" heavily.

Leadership doing "wishful programming" and asking engineers to endlessly add new features. Directions didn't work (remember the EVM pivot that is supposed to bring "a lot" of dapp developers?), but then the legacy stuff left in the codebase. No concern for the technical debts. No architectural revamp even after they realized that the codebase is too big to maintain.

This is what we usually say AI slop is, and amazingly they did that without using AI.

You need to think from the architectural level about how to design a secure blockchain system, not chasing bugs. And sadly, Substrate / Polkadot SDK as of now is beyond rescue, short of a complete rewrite.

[Daniel Gugger 888 @daniel_gugger]

888 „Hätten man sich auf den jeweiligen Stand der Wissenschaft verlassen („settled science“), wäre es folgendermaßen abgelaufen:

- 1890er Jahre: Sie verabreichen Ihrem Baby den neuen Hustensaft von Bayer, die nicht süchtig machende Alternative zu Morphin, die für Kinder vermarktet wurde.

Es war Heroin.

Man benannte es nach dem deutschen Wort für „heldenhaft“.

- 1900er Jahre: Man reibt das Zahnungsschmerzpulver „Calomel“ auf das Zahnfleisch des Säuglings.

Es handelt sich um eine Quecksilberverbindung, die bei einer ganzen Generation die „Pink Disease“ hinterlässt.

Geschwollene, schuppige Hände und Füße, monatelanges Schreien, und einige von ihnen starben.

- 1910er Jahre: Man kocht mit Crisco, das von einem Seifen- und Kerzenhersteller auf den Markt gebracht wurde, weil Baumwollsamenöl modern ist.

Der Prozess, der es fest werden ließ, erzeugte Transfette, die ein Jahrhundert später gänzlich verboten wurden.

- 1920er Jahre: Man trinkt Radithor, zertifiziertes radioaktives Wasser, auf ärztliche Verschreibung.

Eben Byers nahm 1.400 Flaschen für seine Vitalität ein.

Sein Kiefer wurde stückweise entfernt, und er wurde in einem Bleisarg beigesetzt.

- 1930er Jahre: Ein Chemiker löst ein neues Sulfonamid-Medikament in Diethylenglykol auf, das als Frostschutzmittel dient.

Es tötet 107 Menschen, vor allem Kinder, und erst dann überträgt Amerika der FDA die Befugnis, Sicherheitsprüfungen zu verlangen.

- 1940er Jahre: Dein Arzt zündet sich in der Praxis eine Camel an. Mehr Ärzte rauchen diese Marke als jede andere, und eine Anzeige erscheint im „Journal of the American Medical Association“.

- 1950er Jahre: DDT wird über Ihre Küche, Ihren Garten und Ihre Kinder in der Schule versprüht.

Der Mann, der dessen insektizide Eigenschaften entdeckt hat, wurde bereits mit dem Nobelpreis ausgezeichnet.

- 1960er Jahre: Ihre Frau nimmt Thalidomid (Contergan) gegen Schwangerschaftsübelkeit ein, weil es bemerkenswert sicher ist. Mehr als zehntausend Kinder kommen mit fehlenden oder verkürzten Gliedmaßen zur Welt.

- 1970er Jahre: Das Land legt die Butter beiseite und greift zur Margarine – auf Anweisung der American Heart Association.

Das Fett, auf das alle umgestiegen sind, wurde 2015 als in jeder Menge unsicher verboten.

- 1980er Jahre: Das Fett wird aus allem entfernt und Zucker wieder hinzugefügt, um es genießbar zu machen.

Die Fettleibigkeit beginnt zu steigen, was bis heute andauert.

- 1990er Jahre: Deinem Vater wird OxyContin verschrieben, weil weniger als ein Prozent süchtig wird.

Das Unternehmen bekennt sich später der strafbaren Falschkennzeichnung schuldig, und die Zahl der Überdosierungen geht in die Hunderttausende.

- 2000er Jahre: Du nimmst Vioxx gegen deine Kniebeschwerden.

Es wird 2004 vom Markt genommen, und der Sicherheitsbeauftragte der FDA selbst schätzt die Zahl der zusätzlichen Herzinfarkte auf Zehntausende.

Nichts davon war ein Einzelfall.

Hinter jedem stand eine Fachgesellschaft, eine Fachliteratur und ein Mann im weißen Kittel.

Niemand, der diesen Rat befolgte, war dumm. Sie waren gehorsam gegenüber den qualifiziertesten Fachleuten, die es jeweils gab.“

[Giotto @giottodf]

I have a feeling that DOT is going to underperform everything

[CryptoGuerrilla ⚔️ @Crypto_Guerrila]

$ALGO has become my 2nd biggest position overtaking $DOT via outperformance

If it keeps it up it may flip my $APT even though I have sunk in the most capital into Aptos by far

Algorand attacking both 100 and 200 week MAs at this rate, if it flips both then just like $QNT 🚀

[@levelsio @levelsio]

Lindt has an active lawsuit going against it for elevated levels of lead and cadmium

Most interestingly Lindt's lawyers themselves have suggested Lindt is not "expertly crafted" or "excellent" but that that is just advertising

So if even Lindt itself doesn't consider itself good, why should I be eating Lindt chocolate?

Now I eat Vivani which sources from Panama which seems cleaner chocolate beans

[Craig Kelly:🇦🇺Foundation for Economic Education @craigkellyAFEE]

And then there were 11.

Climate Change is destroying the 12 Apostles. Unless we take real action on climate change - they will all be destroyed by rising sea levels.

There’s not a moment to lose.

[Giotto @giottodf]

@CassiusAnalyse Je suis très intéressé par ce que vous faites, je voudrais sponsoriser l'écriture d'un livre. Pourriez-vous me contacter de façon privée sur X ? Merci

[Investment Wisdom @InvestingCanons]

“The way to build long-term returns is through preservation of capital and home runs.”

— Stanley Druckenmiller

[Giotto @giottodf]

I thought asset conversion was when you have some real asset like USD and you convert it into DOT in order to lose your money 😅

[Leemo @LeemoXD]

I think people get confused as to what "Asset Conversion" is and mistakenly try to draw comparisons to EVM-Land DEXs.

Asset Conversion is the assetConversion pallet.

It exists in the Polkadot Asset Hub runtime.

You can permissionlessly create pools for token pairs using assetConversion CreatePool.

You can permissionlessly add liquidity using assetConversion addLiquidity.

The things that people call "DEXs" in this case (on Polkadot Asset Hub) are (currently) just front end UIs. They simply tap into these pools.

It doesn't matter if it's KheopsSwap, Nova Wallet, or Hello_Kitty_Swap_420.

So don't ask what DEX the liquidity is on, as any "DEX" can just tap into these pools.

With regard to "where is the swap activity coming from" - you also won't know, unless the particular front end you are using adds some systemRemark or something along with your token swap :)

You probably can make some web app for these swaps in about 10 minutes with your favourite AI btw.

[timo @timo_rf]

building software is practically free now and we still haven’t found a single use case for blockchains.

[Phoenix Yin @Phoenixyin13]

在机器学习和信息论中，有一个著名的直觉叫流形假说。

现实世界产生的数据，在名义上往往拥有极高维度：一张高清图片可能对应数百万个像素维度，自然语言、声音、蛋白质序列、行为轨迹也都存在于极其庞大的状态空间中。

但有意义的数据并不会均匀散落在这些空间里，它会被压缩在一个极小、极其特殊的结构区域中。
一张随机生成的百万像素图片几乎不可能恰好构成一张真实人脸，因为自然图像同时受到身份、姿态、光照、透视、物体结构和物理规律等大量约束。
流形，只是这种低复杂度结构的一种几何表达，更一般地说，机器学习真正能够成立，是因为现实世界的数据根本不是随机噪声。

这也是理解智能最重要的起点。
智能存在的第一条件，在于这个世界必须具有可预测结构。
假如一个宇宙中的未来和过去完全独立，那么无论是人脑、Transformer还是无限大的超级计算机，都无法通过观察过去提高对未来的预测，因为这个世界根本没有留下任何可以学习的规律。
白噪声无法被理解，也无法被预测。
因此，智能能够存在，本身就意味着宇宙不是最大随机性的混沌，而包含大量跨尺度稳定的统计依赖、几何约束、组合结构、动力学规律和因果关系。

从这个角度看，机器学习做的事情是在巨量观测中寻找可以压缩的规律。
模型看过十亿张人脸，并不需要在参数里存储十亿份像素副本，它需要形成的是关于身份、轮廓、姿态、光照、空间关系等潜在变量的生成结构，最终用一个远短于全部训练数据本身的模型去近似。
因此，Learning在很深的意义上就是Compression。
如果一个庞大的数据集合能够被一个更短的生成程序描述，那么模型获得的就是规律。这与Kolmogorov Complexity的直觉高度一致。
生成或描述这些数据所需的最短程序究竟有多长，是一个重要的问题。

但是，数据不均匀本身仍然不足以产生智能。一个变量即使99%的概率取0、1%的概率取1，它的分布极度不均匀，却未必具有任何复杂结构。
重要的是变量之间存在可以利用的依赖。知道 (X) 之后，是否能够减少对 (Y) 的不确定性，这才是信息。
Mutual Information (I(X;Y)) 所度量的，本质上正是这种关系。
所以，智能依赖的是世界内部存在稳定的dependency；
统计规律、几何结构、层级结构、因果关系以及时间上的连续性共同构成了学习能够发生的基础。

这也给出了理解大模型的一种更准确方式。
一个随机初始化的神经网络最初只是一个巨大的、没有意义的函数族，而梯度下降不断利用数据排除那些与现实分布不一致的函数。
经过海量训练之后，原本随机的参数逐渐形成高度结构化的内部表征。
语言结构、空间关系、人物与概念关系、程序结构和部分物理规律也进入其中。

这里，我们不能简单说神经网络与现实世界同构。因为同构是一个过于严格的数学概念。
其实，模型是在自己的计算介质中形成了一套能够保存现实世界部分稳定关系的内部表示。
它是世界结构在另一种介质中的压缩投影。

于是，所谓智能涌现也没有那么神秘。
如果模型只能捕捉局部统计相关性时，它表现为模式匹配；
当它能够形成更长程、更抽象、更稳定的表示时，就出现泛化；
当不同领域的内部结构能够被重新组合，就表现为类比和联想；
当模型能够利用已有结构，对训练数据中没有直接出现过的状态进行推断，就表现为推理。

记忆、泛化、类比和推理，只是同一种机制在不同尺度上的表现：利用一个内部世界模型，在未观测区域重建结构。
模型规模之所以重要，是因为复杂世界需要足够大的函数空间才能被表示。
而某些能力的突然涌现，有时只是评价指标造成的阈值效应，有时也可能对应grokking或内部表示重组这样的真实非线性变化。
我想，我们需要更多地去关注参数空间在学习过程中发生了什么结构重组，使新的计算能力成为可能。

如果继续把这个问题推到信息论和统计物理层面，会得到更加统一的图景。
生命，依靠持续消耗自由能维持自身远离热平衡，而大脑和机器同样需要消耗能量进行信息处理。
由于Shannon entropy和热力学熵并不是同一个概念，我们可以更准确地定义，智能系统不断丢弃与任务无关的变化，同时保存对于预测和行动有价值的信息。

这与Information Bottleneck极其接近。
内部表示并不需要保存输入的一切，而只需要保留足够多能够预测未来、指导行为的结构。高级智能的标志，是知道什么必须留下，什么可以被遗忘。

由此，智能可以粗略地被写成Compression、Prediction、Control。
Compression意味着从海量观察中提取规律，Prediction意味着利用这些规律推断尚未看到的世界，Control意味着利用预测去改变未来。
一个有限的系统面对一个远比自身复杂的宇宙，通过观察世界、压缩世界、建立内部模型，再依靠这个模型预测并干预世界，这就是智能最一般的形式。