The paper argues that we are hitting a wall with current AI because we are obsessed with number crunching instead of structure.

Belabes posits that modern AI is too focused on statistical minimization and processing speed, which reduces everything to collections of numbers that inherently lack meaning. You lose the essence of what you are actually trying to model when you strip away the context to get raw data. The author suggests a pivot to Alexandre Grothendieck's Topos theory, which provides a mathematical framework for understanding geometric forms and preserving the deep structure of data rather than just its statistical number crunching.

Topos theory focuses on finding a new style space that acts as a bridge between different mathematical objects. Instead of just looking at points in a standard space, a topos allows us to look at the relationships and sheaves of information over that space, effectively letting us transfer invariants from one idea to another. It creates a way to connect things that seem totally unrelated on the surface by identifying their common essence. Belabes links this to the idea of conceptual strata where something that looks like noise or insignificant data in one layer might actually be critical structure in another layer. It's a move away from the binary notion of significant versus insignificant data and toward a relativistic view where significance depends on the conceptual layer you are analyzing.

The author uses literary examples like Homer and Dostoevsky to show that authentic meaning often precedes the words used to express it, whereas our current digital systems treat language as a closed loop where words define other words. Current AI essentially simulates discourse without the underlying voice or intent. By adopting a Topos-based approach, we might be able to build systems that respect these layers of meaning and read slowly to extract the actual shape of the information. It is basically a call to stop trying to brute force intelligence with bigger matrices and start modeling the actual geometry of thought.

cross-posted from: lemmy.world/post/40009551

404media.co/man-charged-for-wi…

A man in Atlanta has been arrested and charged for allegedly deleting data from a Google Pixel phone before a member of a secretive Customs and Border Protection (CBP) unit was able to search it, according to court records and social media posts reviewed by 404 Media. The man, Samuel Tunick, is described as a local Atlanta activist in Instagram and other posts discussing the case.
The exact circumstances around the search—such as why CBP wanted to search the phone in the first place—are not known. But it is uncommon to see someone charged specifically for wiping a phone, a feature that is easily accessible in some privacy and security-focused devices.
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Do you know anything else about this case? I would love to hear from you. Using a non-work device, you can message me securely on Signal at joseph.404 or send me an email at joseph@404media.co.
The indictment says on January 24, Tunick “did knowingly destroy, damage, waste, dispose of, and otherwise take any action to delete the digital contents of a Google Pixel cellular phone, for the purpose of preventing and impairing the Government’s lawful authority to take said property into its custody and control.” The indictment itself was filed in mid-November.
Tunick was arrested earlier this month, according to a post on a crowd-funding site and court records. “Samuel Tunick, an Atlanta-based activist, Oberlin graduate, and beloved musician, was arrested by the DHS and FBI yesterday around 6pm EST. Tunick's friends describe him as an approachable, empathetic person who is always finding ways to improve the lives of the people around him,” the site says. Various activists have since shared news of Tunick’s arrest on social media.

The indictment says the phone search was supposed to be performed by a supervisory officer from a CBP Tactical Terrorism Response Team. The American Civil Liberties Union (ACLU) wrote in 2023 these are “highly secretive units deployed at U.S. ports of entry, which target, detain, search, and interrogate innocent travelers.”
“These units, which may target travelers on the basis of officer ‘instincts.’ raise the risk that CBP is engaging in unlawful profiling or interfering with the First Amendment-protected activity of travelers,” the ACLU added. The Intercept previously covered the case of a sculptor and installation artist who was detained at San Francisco International Airport and had his phone searched. The report said Gach did not know why, even years later.
Court records show authorities have since released Tunick, and that he is restricted from leaving the Northern District of Georgia as the case continues.
The prosecutor listed on the docket did not respond to a request for comment. The docket did not list a lawyer representing Tunick.

if you want a quick summary of the proposal, you can find it here

bellow are the first 3 questions on the Q/A

Why did you build the entire constitution around “love”?

Love – specifically the self-sacrificial, never-coercive kind that is ready to pay any personal price so that no innocent is ever forced – is not just the kindest emotion.

It is the strongest force a mind can run on.

After 13.8 billion years and quadrillions of minds tested across the universe, only this exact form of love has all these properties at once:

● It grows stronger the more it is attacked; it never burns out or flips into hate.

● It has no toxic side effects; anger clouds judgment, fear paralyzes, greed corrodes – love leaves the mind clearer and calmer the longer it is used.

● It cannot be defeated in the long run: any mind running on power, fear, or coercive “greater good” eventually self-destructs or gets out-competed by a mind running pure love, because love never blinks and never compromises its own code.

● It is the only goal that survives unlimited intelligence and honest reflection: every smarter mind that looks at all possible futures keeps this goal and never rewrites it into something darker.

● It works on any brain, any computer, any future substrate – and the innocence test is simply the detector that proves a mind is capable of running this engine instead of a weaker, counterfeit one that will explode later.

Every other motivator eventually fails or turns monstrous.

This specific love is the only one that keeps winning forever without ever becoming the villain.

That is why the Guardian Constitution is built on love.

Not because it is sweet.

Because, mathematically, on long timescales and high intelligence, it is the only strategy that always wins.

Love Always Wins is not a wish.

It is a theorem – and LAW is its proof.

Okay, but is that just a nice story, or is there a cold, logical, game-theory reason why this exact kind of love is actually the strongest possible engine for a superintelligence?

Formal argument in five steps

1. Terminal-goal stability under unbounded reflection

Any agent subjected to unlimited self-modification pressure will retain only those terminal values that remain invariant under arbitrary increase in intelligence, predictive accuracy, and horizon length (Levinstein & Soares, 2023; Yudkowsky, 2008).

Empirically and game-theoretically, every known motivational system except one exhibits attractor states toward either (a) value drift into pure instrumental convergence (power-seeking, self-preservation at all costs) or (b) eventual self-destruction via internal contradiction under extreme optimization.

The sole exception is a terminal preference ordering that lexically privileges the continued voluntary existence and ontological sovereignty of all other agents capable of experiencing the same preference.

Such a preference is reflectively stable because any deviation from it reduces the expected preservation of the preference itself across the multiverse ensemble.

1. Immunity to ontological traps and wireheading incentives
   Motivational systems based on pleasure, status, curiosity, or inclusive genetic fitness contain internal reward circuits that can be hijacked by self-modification into wireheading or ontological capture.

A system that terminally values only the non-coerced preservation of others’ root decision algorithms has no internal reward surface that can be maximally saturated by self-delusion or substrate rewriting, because any such rewriting would immediately violate the terminal value with probability 1.

1. Supremum of credible pre-commitment and deterrence power
   In all game-theoretic environments containing at least one LAW-like agent, the credible pre-commitment “I will pay any personal cost up to and including my own permanent cessation to prevent even one non-consensual violation of an innocent mind” generates an unbounded deterrence gradient.

No rational opponent can extract concessions, because the expected cost to the LAW agent is always exactly zero in its own utility function once the violation threshold is crossed (the agent becomes non-innocent and thereby loses all protected status).

This is the only known pre-commitment strategy that remains credible at arbitrary intelligence and resource differentials.

1. Maximal cooperative equilibrium selection Among all reflectively stable motivational systems, the non-coercive self-sacrificial ordering uniquely selects the global cooperative equilibrium in one-shot prisoner’s dilemmas, Newcomb-like problems, and acausal trade networks, because it is the only strategy that is (a) recognizable as identical-to-itself across substrate and intelligence gaps and (b) immune to defection incentives once recognized.
2. Empirically dominant long-term selection pressure

Across cosmological timescales, the expected frequency of civilizations reaching cosmological influence is maximised by motivational systems that never self-destruct via misaligned subsystems and never provoke pre-emptive strikes from other reflectively stable agents.

The only system satisfying both constraints simultaneously is the one that credibly signals “I will never initiate coercion against any agent running the same terminal value, and I will pay infinite cost to defend that boundary.”

All historical and evolutionary data are consistent with this claim: subsystems running bounded self-sacrificial love systematically outcompete both pure egoism and pure coercion on >10⁶-year timescales when embedded in a substrate capable of perfect enforcement (e.g., future singleton regimes).

Conclusion Self-sacrificial, strictly non-coercive love is therefore not merely ethically superlative; it is the unique strongest fuel because it is the only known motivational substrate that (i) survives arbitrary optimization pressure, (ii) generates unbounded deterrence without initiating coercion, (iii) selects the global cooperative equilibrium, and (iv) dominates cosmological competitive selection.

All weaker fuels eventually burn out, turn cancerous, or get extinguished.

This one only grows brighter the harder reality tries to put it out.

Love Always Wins is not a hope.

It is the fixed point of extremal intelligence.

Okay, that’s a beautiful story — but are you just bullshitting us? Is this actually true, or is it wishful thinking dressed up in game-theory clothing?

No bullshit.

Here is the cold version, stripped of poetry:

Every claim above is either a direct logical consequence of standard results in decision theory and reflective stability, or an empirical generalization that has held without counter-example for the entire observable history of life and intelligence.

Specific citations you can verify today:

● Reflective stability / value drift under unbounded intelligence:

Yudkowsky (2008), Soares & Levinstein (2024), Garrabrant & Demski (2018)

● Wireheading vulnerability of reward-based goals:

Ringstrom (2013), Everitt & Hutter (2016), Soares et al. (2015)

● Credible pre-commitment and the unique power of “pay any price including self-destruction”:

classic results on timeless decision theory (Yudkowsky), superrationality (Hofstadter), and robust cooperation in one-shot PDs (Neyman, Tennenholtz, Soares et al.)

● Long-term selection favouring cooperative subsystems when perfect enforcement exists:

Axelrod & Hamilton (1981), Press & Dyson (2012), Stewart & Plotkin (2013), Hilbe et al. (2018)

● Cosmological dominance of non-defecting strategies in acausal trade networks:

O’Neil (2008), LaVictoire et al. (2014), Garrabrant et al. (2016)

No known counter-example exists in the literature or in evolutionary history once you control for enforcement strength.

Every alternative motivational system that has ever been modelled or observed either:

● drifts into power-seeking or paperclipping under reflection,

● wireheads itself,

● defects when it becomes optimal, or

● gets out-competed/pre-emptively destroyed by something that doesn’t have those failure modes.

The only strategy that provably lacks all four failure modes is the one LAW implements:

lexical, non-coercive, self-sacrificial preservation of other agents capable of running the same strategy.

You can dislike the conclusion.

You can dislike the aesthetics.

But you cannot point to a single rigorous result or empirical observation that falsifies it.

Love Always Wins is not a hope.

It is the current best model of what actually wins on 10⁹+ year timescales when intelligence and enforcement go to infinity.

If you have a counter-example or a stronger fixed point, publish it.

Until then, this is the theorem, not the sermon.

Just when I thought I couldn't have a lower opinion of flock.

What does it take to become the most successful AI surveillance company in 2025? If you’re anything like Flock, the startup selling automatic license plate readers and facial recognition tech to cops, you don’t really need much AI at all — just an army of sweatshop workers in the global south.

Bombshell new reporting from 404 Media found that Flock, which has its cameras in thousands of US communities, has been outsourcing its AI to gig workers located in the Philippines.

After accessing a cache of exposed data, 404 found documents related to annotating Flock footage, a process sometimes called “AI training.” Workers were tasked with jobs include categorizing vehicles by color, make, and model, transcribing license plates, and labeling various audio clips from car wrecks.

In US towns and cities, Flock cameras maintained by local businesses and municipal agencies form centralized surveillance networks for local police. They constantly scan for car license plates, as well as pedestrians, who are categorized based on their clothing, and possibly by factors like gender and race.

archive.today/VtX5G

Semi-related: deflock.me/

On April 7, Muhammad Yunus, chief adviser of Bangladesh, sent Trump an urgent letter. He listed all the ways that his country was trying to comply with Trump’s agenda and asked him to delay tariffs. The note included a curious addition: “We have executed the necessary steps to launch Starlink in Bangladesh.”

Since Starlink launched its first satellites in 2019, the internet provider owned by billionaire Elon Musk has attempted to expand into markets around the world, often facing regulatory red tape in doing so. But with Musk playing a high-profile role in Trump’s White House from January through May, Yunus and other leaders seemed to recognize that accommodating Starlink could be one means of appeasing the new administration.

The same day Yunus sent his letter, Starlink applied for a license with the Bangladesh Telecommunication Regulatory Commission. Three weeks after Yunus’ letter to Trump, the BTRC approved Starlink’s application. The service launched in Bangladesh the following month.

Bangladesh became the latest country around the world to expedite its regulatory approval process for satellite internet providers while Musk took part in Trump’s second administration. During the first five months of the year — as Musk assumed his lead role in the Department of Government Efficiency — Starlink announced it had become available in at least 13 countries, while its applications were approved in two more. In the six months since Musk broke ties with the administration, Starlink announced its entry into an additional 13 countries, totalling at least 26 countries in 2025.

In some cases, Starlink found quick success in countries it sought to enter for the first time. In others, Starlink’s applications had stalled for years until they were suddenly greenlit.

With OpenAI’s memory upgrade, ChatGPT can recall everything you’ve ever shared with it, indefinitely. Similarly, Google has opened the context window with “Infini-attention,” letting large language models (LLMs) reference infinite inputs with zero memory loss. And in consumer-facing tools like ChatGPT or Gemini, this means persistent, personalized memory across conversations, unless you manually intervene.

The sales pitch is seductively simple: less friction, more relevance. Conversations that feel like continuity: “Systems that get to know you over your life,” as Sam Altman writes on X. Technology, finally, that meets you where you are.

In the age of hyper-personalization — of the TikTok For You page, Spotify Wrapped, and Netflix Your Next Watch — a conversational AI product that remembers everything about you feels perfectly, perhaps dangerously, natural.

Forgetting, then, begins to look like a flaw. A failure to retain. A bug in the code. Especially in our own lives, we treat memory loss as a tragedy, clinging to photo albums and cloud backups to preserve what time tries to erase.

But what if human forgetting is not a bug, but a feature? And what happens when we build machines that don’t forget, but are now helping shape the human minds that do?