Tootfinder

Should we care about the spatial heterogeneity in coral reefs under unidirectional turbulent flows?
Akshay Patil, Clara Garc\'ia-S\'anchez
https://arxiv.org/abs/2506.03021

Should we care about the spatial heterogeneity in coral reefs under unidirectional turbulent flows?
In this work, we systematically investigate the similarities and differences observed between a hydraulically rough wall comprised of an array of cylinders, massive corals, and branching corals arranged in a staggered manner, along with a stochastically generated coral bed using a scale-resolving computational framework. Our data suggests that for all the flow parameters of interest, there is a substantial difference observed between the stochastic coral bed and the regularly arranged coral bed…

@… @… Possibly forking, but building from scratch appeals to me. (Except the UI part, which is the main reason I'm not doing it.)
I have opinions about how this kind of thing should work. Specifically, I don't want a "read i…

Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and this more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of manservant caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.

This https://arxiv.org/abs/2412.09433 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCC_…

Solving Multiagent Path Finding on Highly Centralized Networks
The Mutliagent Path Finding (MAPF) problem consists of identifying the trajectories that a set of agents should follow inside a given network in order to reach their desired destinations as soon as possible, but without colliding with each other. We aim to minimize the maximum time any agent takes to reach their goal, ensuring optimal path length. In this work, we complement a recent thread of results that aim to systematically study the algorithmic behavior of this problem, through the paramet…

This https://arxiv.org/abs/2505.09795 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Beyond Pairwise Learning-To-Rank At Airbnb
There are three fundamental asks from a ranking algorithm: it should scale to handle a large number of items, sort items accurately by their utility, and impose a total order on the items for logical consistency. But here's the catch-no algorithm can achieve all three at the same time. We call this limitation the SAT theorem for ranking algorithms. Given the dilemma, how can we design a practical system that meets user needs? Our current work at Airbnb provides an answer, with a working solutio…

Revisiting Noise-adaptive Transpilation in Quantum Computing: How Much Impact Does it Have?
Yuqian Huo, Jinbiao Wei, Christopher Kverne, Mayur Akewar, Janki Bhimani, Tirthak Patel
https://arxiv.org/abs/2507.01195

Revisiting Noise-adaptive Transpilation in Quantum Computing: How Much Impact Does it Have?
Transpilation, particularly noise-aware optimization, is widely regarded as essential for maximizing the performance of quantum circuits on superconducting quantum computers. The common wisdom is that each circuit should be transpiled using up-to-date noise calibration data to optimize fidelity. In this work, we revisit the necessity of frequent noise-adaptive transpilation, conducting an in-depth empirical study across five IBM 127-qubit quantum computers and 16 diverse quantum algorithms. Our…

On the Effect of Ruleset Tuning and Data Imbalance on Explainable Network Security Alert Classifications: a Case-Study on DeepCASE
Koen T. W. Teuwen, Sam Baggen, Emmanuele Zambon, Luca Allodi
https://arxiv.org/abs/2507.01571

On the Effect of Ruleset Tuning and Data Imbalance on Explainable Network Security Alert Classifications: a Case-Study on DeepCASE
Automation in Security Operations Centers (SOCs) plays a prominent role in alert classification and incident escalation. However, automated methods must be robust in the presence of imbalanced input data, which can negatively affect performance. Additionally, automated methods should make explainable decisions. In this work, we evaluate the effect of label imbalance on the classification of network intrusion alerts. As our use-case we employ DeepCASE, the state-of-the-art method for automated a…

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Dear @…

Academiccloud
Willkommen auf der Mastodon Instanz der AcademicCloud

This channel is an unofficial mirror of Bernadette Banner’s YouTube content. It is not affiliated with or endorsed by Bernadette Banner and may be removed if she requests.
She is one of my favorite creators on YouTube, so I’ve synchronized and published her videos on PeerTube, while the rest is currently being transcoded and should be available by tomorrow!

Classification with Reject Option: Distribution-free Error Guarantees via Conformal Prediction
Johan Hallberg Szabadv\'ary, Tuwe L\"ofstr\"om, Ulf Johansson, Cecilia S\"onstr\"od, Ernst Ahlberg, Lars Carlsson
https://arxiv.org/abs/2506.21802

Classification with Reject Option: Distribution-free Error Guarantees via Conformal Prediction
Machine learning (ML) models always make a prediction, even when they are likely to be wrong. This causes problems in practical applications, as we do not know if we should trust a prediction. ML with reject option addresses this issue by abstaining from making a prediction if it is likely to be incorrect. In this work, we formalise the approach to ML with reject option in binary classification, deriving theoretical guarantees on the resulting error rate. This is achieved through conformal pred…

Conformal Green functions and Yamabe metrics of Sobolev regularity
Rodrigo Avalos, Albachiara Cogo, Andoni Royo Abrego
https://arxiv.org/abs/2507.01674 htt…

Conformal Green functions and Yamabe metrics of Sobolev regularity
We provide a full resolution of the Yamabe problem on closed 3-manifolds for Riemannian metrics of Sobolev class $W^{2,q}$ with $q > 3$. This requires developing an elliptic theory for the conformal Laplacian for rough metrics and establishing existence, regularity and a delicate blow-up analysis for its Green function. Most of the analytical work is carried out in dimensions $n \geq 3$ and for $W^{2,q}$ Riemannian metrics with $q>\tfrac{n}{2}$ and should be of independent interest.

This https://arxiv.org/abs/2502.09377 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Fair Division via Resource Augmentation
We introduce and formalize the notion of resource augmentation for maximin share allocations -- an idea that can be traced back to the seminal work of Budish [JPE 2011]. Specifically, given a fair division instance with $m$ goods and $n$ agents, we ask how many copies of the goods should be added in order to guarantee that each agent receives at least their original maximin share, or an approximation thereof. We establish a tight bound of $m/e$ copies for arbitrary monotone valuations. For addi…

Really, Babas? I understand we all have the right to protect and potentially profit from our own IP, but this feels out of proportion.
St Michael's does incredible work in Herefordshire. Maybe the Barbarians' bigwigs should come and take a look.
Hereford hospice rugby team tackles Barbarians logo row - BBC News
https://…

Hereford hospice rugby team tackles Barbarians logo row
The Hospice Barbarians team is asked to tone down its logo by the official Barbarians FC.

I wonder where Ireland’s regulator got this idea?
https://mastodon.neilzone.co.uk/@neil/114751272606146547

Nothing I’m trying to write is "flowing"...it's all laborious.
I'm encouraged by "Your labor isn’t a sign of defeat" from @… wherein she quotes Verlyn Klinkenborg:
"if you accept that writing is hard work, And that’s what it feels like when you’re writing, Then everything is as it should be. Your labor is…

Feedbackless Feed
A (non)social feedbackless feed to nowhere

Managing level of detail through head-tracked peripheral degradation: a model and resulting design principles
Benjamin Watson, Neff Walker, Larry F Hodges
https://arxiv.org/abs/2506.21456

Managing level of detail through head-tracked peripheral degradation: a model and resulting design principles
Previous work has demonstrated the utility of reductions in the level of detail (LOD) in the periphery of head-tracked, large field of view displays. This paper provides a psychophysically based model, centered around an eye/head movement tradeoff, that explains the effectiveness of peripheral degradation and suggests how peripherally degraded displays should be designed. An experiment evaluating the effect on search performance of the shape and area of the high detail central area (inset) in p…

Time is On My Side: Dynamics of Talk-Time Sharing in Video-chat Conversations
Kaixiang Zhang, Justine Zhang, Cristian Danescu-Niculescu-Mizil
https://arxiv.org/abs/2506.20474

Time is On My Side: Dynamics of Talk-Time Sharing in Video-chat Conversations
An intrinsic aspect of every conversation is the way talk-time is shared between multiple speakers. Conversations can be balanced, with each speaker claiming a similar amount of talk-time, or imbalanced when one talks disproportionately. Such overall distributions are the consequence of continuous negotiations between the speakers throughout the conversation: who should be talking at every point in time, and for how long? In this work we introduce a computational framework for quantifying bot…

Citizen science study determines that more than one light per person is still on late at night in Germany #Germany

Citizen science study determines that more than one light per person is still on late at night in Germany
Nighttime satellite images have shown that cities are getting brighter, and light pollution is now recognized as an environmental issue. But how should local governments even begin the work of resolving this if nobody really knows what the sources of all this light are? A large citizen science project led by Dr. Christopher Kyba, at the time geographer at Ruhr University Bochum and the GFZ Helmholtz Center for Geosciences, is now shedding light on the matter.

Out of Control -- Why Alignment Needs Formal Control Theory (and an Alignment Control Stack)
Elija Perrier
https://arxiv.org/abs/2506.17846 https://…

Out of Control -- Why Alignment Needs Formal Control Theory (and an Alignment Control Stack)
This position paper argues that formal optimal control theory should be central to AI alignment research, offering a distinct perspective from prevailing AI safety and security approaches. While recent work in AI safety and mechanistic interpretability has advanced formal methods for alignment, they often fall short of the generalisation required of control frameworks for other technologies. There is also a lack of research into how to render different alignment/control protocols interoperable.…

This https://arxiv.org/abs/2502.00874 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDL_…

Paper Copilot Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
The rapid growth of submissions to top-tier Artificial Intelligence (AI) and Machine Learning (ML) conferences has prompted many venues to transition from closed to open review platforms. Some have fully embraced open peer reviews, allowing public visibility throughout the process, while others adopt hybrid approaches, such as releasing reviews only after final decisions or keeping reviews private despite using open peer review systems. In this work, we analyze the strengths and limitations of …

When I say that I wish the bubble would burst so we could start having actual conversation, this is the kind of thing I’m talking about.
In the meantime, not being a researcher myself in any kind of position to critique the paper, I’m happy to just look at it and cherry-pick the conclusion that I think is unequivocally helpful regardless: we all (students in school, students of life) should cultivate active, engaged minds that work with ideas by •doing• and •creating• instead of simply passively receiving.

The move to Windows 11 isn’t just about security updates.
It increases dependence on Microsoft through aggressive cloud integration,
forcing users to adopt Microsoft accounts and services.
It also leads to higher costs due to subscription and licensing models,
and reduces control over how your computer works and how your data is managed.
Furthermore, new hardware requirements will render millions of perfectly good PCs obsolete.
This is a turning point.

The end of Windows 10 is approaching, so it's time to consider Linux and LibreOffice - The Document Foundation Blog
The Document Foundation and LibreOffice support the international campaign @endof10 https://endof10.org/ The countdown has begun. On 14 October 2025, Microsoft will end support for Windows 10. This will leave millions of users and organisations with a difficult choice: should they upgrade to Windows 11, or completely rethink their work environment? The good news? You don’t […]

Threshold behavior of a social norm in response to error proneness
Quang Anh Le, Seung Ki Baek
https://arxiv.org/abs/2506.23907 https://

Threshold behavior of a social norm in response to error proneness
A social norm defines what is good and what is bad in social contexts, as well as what to do based on such assessments. A stable social norm should be maintained against errors committed by its players. In addition, individuals may have different probabilities of errors in following the norm, and a social norm would be unstable if it benefited those who do not follow the norm carefully. In this work, we show that Simple Standing, which has been known to resist errors and mutants successfully, a…

Also told everyone at work I need to focus and they should not expect me in any calls this week. What a relief to know I can still focus like I could years ago.

For me I use both type of laptops. The windows machine (soon going to #linux) and my #linux laptop (retiring after I convert the windows laptop) I use for serious photo editing, condo newsletters, some work related programming, personal items (like medical).
The Chromebook I use for light…

This https://arxiv.org/abs/2506.04168 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Horizon Reduction Makes RL Scalable
In this work, we study the scalability of offline reinforcement learning (RL) algorithms. In principle, a truly scalable offline RL algorithm should be able to solve any given problem, regardless of its complexity, given sufficient data, compute, and model capacity. We investigate if and how current offline RL algorithms match up to this promise on diverse, challenging, previously unsolved tasks, using datasets up to 1000x larger than typical offline RL datasets. We observe that despite scaling…

I have my share of issues with Parkrose Permaculture, but she has a lot of things I do strongly agree with. I can't stress enough that you never dehumanize your enemies. You can respond appropriately to violence. You can defend yourself from them by any means necessary. But you do not dehumanize them. You always limit your response to the minimum necessary to defend yourself.
There are a number of former Nazi skins who became antifascists after realizing they were wrong. Those folks tend to be some of the most dedicated because they feel a debt, and some of the most knowledgeable because they were there. Coming out of these types of cults, police included, is hard and takes time. A lot of us don't have the ability to work with them. But some do.
By repeatedly humanizing your opponent, you can break some of them. The #Seattle Police Department was not defunded but saw a massive reduction in numbers because their morale was destroyed. Some people will never change. Some people are broken and feel like they need the power. But if you change one person's mind, even give them something to think about, it's a crack. If even one cop quits, that's one less trained gun pointed at you in the future.
The 18 year old marines and federalized national guard troops out there are literally kids. A lot of them came from poor communities. They are being used in a way they haven't been trained to do, doing things they (should) have been told are not legal. They joined to get out of poverty, to go to college, or to "defend the American people" (regardless of how misguided that is). Few, if any, of them joined to abuse people. They will be especially open to persuasion.
Remind those troops that they are carrying out illegal orders, that they are being called on to violate their oath to protect the constitution, that they are suppressing the free speech of the fellow Americans they swore to defend. Remind them that the people they could be illegally arresting now are just like their parents, their neighbors, their families, the friends who didn't join. Remind them that this is the first step. They will be called on to kill Americans if they let this keep going.
Remind them ICE sleeps in hotels while they sleep on the ground. Remind them that their drunk and incompetent leadership thinks of them as disposable tools. Remind them that some of these people are out protesting *for them* against cuts to the VA and other services. Remind them that the people they're defending refuse to make college free so they can recruit from poor schools. Remind them that they will always be welcome when they're ready to join the side of freedom and justice.
When you dehumanize your enemies, you unify them. When you humanize your enemies, you can divide them. There is no weapon available to us right now so powerful as compassion.
https://youtu.be/YtWOYUDMsBw

An illustration of formal moduli problems with differential graded Lie algebras
Ethan Eugene Wynner
https://arxiv.org/abs/2506.12977 https://

An illustration of formal moduli problems with differential graded Lie algebras
This article provides an exposition to the topic of formal moduli problems, emphasizing its connections with differential graded Lie algebras, and mainly following from Jacob Lurie's DAG X: Formal Moduli Problems. As such, this paper should not be viewed as a presentation of original work, but rather a concise introduction to the subject in the form of a set of organized notes. I hoped to make this paper feel welcoming and insightful for the non-expert enjoyer of derived algebraic geometry, lik…

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn, Angelina Wang, Fernando Diaz, Flavio du Pin Calmon, Margaret Mitchell, Michael Ekstrand, Reuben Binns, Solon Barocas
https://arxiv.org/abs/2506.14652

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly applied. We argue that this narrow conception of rigor has contributed to the concerns raised by the responsible AI community, including overblown claims about AI capabilities. Our position is that a broader conception of what rigorous AI research and practice should entail is needed. We believe such a conception -- i…

In one of the more painful purchases I've done in a bit: just ordered 3 kits of Crucial DDR5 RAM for the MS-A2 servers. This will take them from 32GB -> 96GB which should work out a bit better for Proxmox. Unfortunately, my wallet is crying. If everything goes well, the RAM should get here just before the servers do.
#homelab

Microsoft has a new blog post on securing your organization against the Golden SAML attack. I wasn't familiar with this attack and learned that it only applies to organizations who use a delegated IdP like Active Directory Federation Services (ADFS). If you use ADFS, this should be on your reading list. #cybersecurity

Understanding and Mitigating Golden SAML Attacks | Microsoft Community Hub
Learn how Golden SAML attacks work and discover strategies to protect your identity infrastructure.

so why don't we make @… vice-president of the european commission in charge of tech sovereignity, digital and internet things? https://berthub.eu/articles/po…

"You should know Trump isn’t doing this on his own. The Hoover Institution has been plotting revenge against FDR since 1932. Groups like the Heritage Foundation and Heartland Foundation are generations old. The Federalist Society has been promising to overturn liberal justice since the 1960s. The Religious Right started working to overturn Roe v. Wade the day it was promulgated. All these groups have big money, and they play the long game.
What’s happening today is their platform, backed by their research. The fact it won’t work, that the 20th century won’t be put back into a bottle, that the Amendments put in place after 1865 somehow aren’t part of the “real” Constitution, is yet to be proven by events."
https://danafblankenhorn.substack.com/p/all-in-the-family

Neural models of multiscale systems: conceptual limitations, stochastic parametrizations, and a climate application
Fabrizio Falasca
https://arxiv.org/abs/2506.22552

Neural models of multiscale systems: conceptual limitations, stochastic parametrizations, and a climate application
This work explores key conceptual limitations in data-driven modeling of multiscale dynamical systems, focusing on neural emulators and stochastic climate modeling. A skillful climate model should capture both stationary statistics and responses to external perturbations. While current autoregressive neural models often reproduce the former, they typically struggle with the latter. We begin by analyzing a low-dimensional dynamical system to expose, by analogy, fundamental limitations that persi…

Choreographic Quick Changes: First-Class Location (Set) Polymorphism
Ashley Samuelson, Andrew K. Hirsch, Ethan Cecchetti
https://arxiv.org/abs/2506.10913 h…

Choreographic Quick Changes: First-Class Location (Set) Polymorphism
Choreographic programming is a promising new paradigm for programming concurrent systems where a developer writes a single centralized program that compiles to individual programs for each node. Existing choreographic languages, however, lack critical features integral to modern systems, like the ability of one node to dynamically compute who should perform a computation and send that decision to others. This work addresses this gap with $λ_{QC}$, the first typed choreographic language with \e…

To dig slightly deeper here, I think that there's a feedback loop between "fall in love/wait for your perfect match (and by the way girls the only career you should aspire to is the literally unattainable 'princess'" Disney stuff and this "my characters are complex I'm so sophisticated; they suffer but it's not intolerable and their lives are good enough despite the imperfections" crap that gets praised as so evocative of the human condition. In fact, I think it merely evokes the condition of its authors & fans who were poisoned by the Disney in their youth and who have remained bad as relationships ever since, though this is not exactly their fault. In any case, their white middle-aged wisdom-shaped-but-quite bitter and intricately-constructed-so-it's-hard-to-see-the-really-untrue-character-facets work ends up keeping their audience within the "romance is luck" cult by way of reassuring them that a middling romance with lots of doubt and complications is "just life" even though the author doesn't actually have any broader perspective on what life is than anyone else.
This has turned into a bit of a rant, but I think I'll just add that reading Mama by Nikkya Hargrove just before Dream State helped immensely to see how the distant & awkward parent-child relationships of the latter are not a product of human nature but instead of white western culture & capitalism.
(The defeatism about climate change is a whole nother dimension of wrong about Dream State, by that's a separate rant.)

Yotta: A Large-Scale Trustless Data Trading Scheme for Blockchain System
Xiang Liu, Zhanpeng Guo, Liangxi Liu, Mengyao Zheng, Yiming Qiu, Linshan Jiang
https://arxiv.org/abs/2506.19368

Yotta: A Large-Scale Trustless Data Trading Scheme for Blockchain System
Data trading is one of the key focuses of Web 3.0. However, all the current methods that rely on blockchain-based smart contracts for data exchange cannot support large-scale data trading while ensuring data security, which falls short of fulfilling the spirit of Web 3.0. Even worse, there is currently a lack of discussion on the essential properties that large-scale data trading should satisfy. In this work, we are the first to formalize the property requirements for enabling data trading in W…

Robust Committee Voting, or The Other Side of Representation
Gregory Kehne, Ulrike Schmidt-Kraepelin, Krzysztof Sornat
https://arxiv.org/abs/2506.18643 htt…

Robust Committee Voting, or The Other Side of Representation
We study approval-based committee voting from a novel perspective. While extant work largely centers around proportional representation of the voters, we shift our focus to the candidates while preserving proportionality. Intuitively, candidates supported by similar voter groups should receive comparable representation. Since deterministic voting rules cannot achieve this ideal, we develop randomized voting rules that satisfy ex-ante neutrality, monotonicity, and continuity, while maintaining s…

The Hitchhiker's Guide to Efficient, End-to-End, and Tight DP Auditing
Meenatchi Sundaram Muthu Selva Annamalai, Borja Balle, Jamie Hayes, Georgios Kaissis, Emiliano De Cristofaro
https://arxiv.org/abs/2506.16666

The Hitchhiker's Guide to Efficient, End-to-End, and Tight DP Auditing
This paper systematizes research on auditing Differential Privacy (DP) techniques, aiming to identify key insights into the current state of the art and open challenges. First, we introduce a comprehensive framework for reviewing work in the field and establish three cross-contextual desiderata that DP audits should target--namely, efficiency, end-to-end-ness, and tightness. Then, we systematize the modes of operation of state-of-the-art DP auditing techniques, including threat models, attacks,…

Generalized measurements for Bell tests in different probability spaces
Alfredo Luis
https://arxiv.org/abs/2506.07496 https://arxiv.o…

Generalized measurements for Bell tests in different probability spaces
Bell tests are of profound statistical nature. Besides physical considerations, the proper understanding of their implications should involve detailed statistical analyses. In this regard, recent works have shown that their consequences and interpretations depend on the probability space adopted. Some other recent works have also shown that generalized measurements may allow to further exploit the statistics of Bell-like tests. Following these ideas, in this work we show that one and the same e…

Levels of Autonomy for AI Agents
K. J. Kevin Feng, David W. McDonald, Amy X. Zhang
https://arxiv.org/abs/2506.12469 https://arxiv.org…

Levels of Autonomy for AI Agents
Autonomy is a double-edged sword for AI agents, simultaneously unlocking transformative possibilities and serious risks. How can agent developers calibrate the appropriate levels of autonomy at which their agents should operate? We argue that an agent's level of autonomy can be treated as a deliberate design decision, separate from its capability and operational environment. In this work, we define five levels of escalating agent autonomy, characterized by the roles a user can take when interac…

The more time goes on, the more conflicted I get about #AI. (or, more specifically, generative AI. I like causal AI a fair bit)
On one hand, I hate so much about it:
the needless environmental and electronic parts waste, the impact on labor, the monopolistic nature of main organizations driving it, the endless conversations about AGI and other absurdly utopian (or dystopian) futures, the widespread theft of IP and human work, the devaluation of labor and craft… so much of it is not okay at all.
On the other hand, I kinda get it?
I like to test software for myself, so I've been dipping my toes into some popular AI tools over the past couple of years. I have a paid subscription to ChatGPT (which I don’t feel great about, I know), and I have found genuine utility in it.
More so, I feel so conflicted when I talk to people I respect and who I think are very smart and creative and they tell me how in love they are with all of these AI tools, about the complex workflows they build, about their experiments with agentic AI and integrations... These people seem so excited, so alive, so joyous about the things that this technology allows them to do. They often wouldn't have had the skills / knowledge / financial capital to do some of those things with human efforts alone. And now I see them coding their own tools, doing complex data analysis, trying creative experiments with graphics / text / video...
And I feel like a total jerk going "BUT ACTUALLY THIS IS UNETHICAL AND INEFFICIENT AND YOU SHOULD STOP IT BECAUSE AI SUCKS".
The technology behind all these gen AI models does have real utility, and it has kicked off a lot of creativity from people who wouldn't have dabbled in those kinds of projects otherwise.
So I don't know how to feel. Because I can't let go of the guilt and the real problems and the awareness of how much empty hype there is.
#technology #artificialintelligence #genAI #ChatGPT

Trade Unionists Against the Benefit Cuts (UKPol)
Good letter, including both the principle of the thing and the likely outcomes in practice. Starmer & co should take note.
"We the undersigned are trade unionists opposed to the Universal Credit and Personal Independence bill, designed to restrict access to PIP and to reduce the sickness element (LCWRA) of UC. We believe this is shameful anti-worker and anti-working class legislation. ...
"Not only will these cuts cause increased financial hardship for some of those made vulnerable by a disabling society, but will also add considerable expenses and a much increased workload to workers in several sectors. This is because more people will be plunged into debt. More people will be served with eviction notices... Cutting incomes will push people further from work...
"The Disability Policy thinktank forecast that the cuts will lead to £1.2bn in extra costs for the NHS and local care services provided by councils, raising the alarm for both councillors and MPs whether the cuts will backfire even on their own economic terms."
Still accepting signatures:
#disability #benefits #unions #NHS #debt #UK #UKPol