Tootfinder

Actually, I do want to come back to masculinity under patriarchy and whiteness under white supremacy because I think it's worth talking more about. The "man" under patriarchy (at least "Western" patriarchy) is represented as power and independence. The man needs nothing and thus owes nothing to anyone. The man controls and is not controlled, which is intimately related to independence as dependence can make someone vulnerable to control. The image of "man" projects power and invulnerability. At the same time "man" is a bumbling fool who can't be held accountable for his inability to control his sexual urges. He must be fed and cared for, as though another child. His worst behaviors must be dismissed with phrases such as "boys will be boys" and "locker room talk." The absurdity of the concept of human "independence" is impossible to understate.
Even if you go all Ted Kaczynski, you have still been raised and taught. This is, perhaps, why it is so much more useful to think in terms of obligations than rights. Rights can be claimed and protected with violence alone, but obligations reveal the true interdependence that sustains us. A "man" may assert his rights. Yet, on some level, we all know that the "man" of patriarchy acts as a child who is not mature enough to recognize his obligations.
White violence and white fragility reflect the same dichotomy. "The master race" somehow always needs brown folks to make all their shit and do all the reproductive labor for them. For those who fully embrace whiteness, the "safe space" is a joke. DEI shows weakness. Yet, when presented with an honest history adults become children who are incapable of differentiating between criticism and simple facts. *They* become the ones who must be kept safe. The expectation to be responsible for one's own words and actions, one of the very core definitions of being an adult, is far too much to expect. Their guilt needs room, needs tending, needs caring. White people cannot simply "grow the fuck up" or, as they may say of slavery, "fucking get over it."
And again, interestingly, it is *rights* that they reference: "Mah Freeze PEACH!" I find it hard to distinguish between such and my own child's assertion that anything she doesn't like is "not fair!" No, these assertions fail to recognize the fundamental fabric of adult society: the obligations we hold to each other.
At the intersection of all privilege is the sovereign, the ultimate god-man-baby. Again, referencing the essay (https://hexmhell.writeas.com/observations-on-domination-and-trump)
> This is where it becomes important to consider the ideology behind the sovereign ritual. Participation within the sovereign ritual denotes to the participants elements of the sovereign. That is, all agents of the sovereign are, essentially, micro dictators. By carrying out the will of the sovereign, these micro dictators can, by extension, act outside of the law.
While law enforcement is the ultimate representative of sovereign violence, privileges allow a gradated approximation of the sovereign. Those who are "closer" in privilege to the sovereign may, for example, be permitted to carry out violence against those who are father away. The gradation of privilege turns the whole society, except for the least privileged, into a cult that protects the privilege system on behalf of the most privileged. (And immediately Malcolm X pops to mind as having already talked about part of this relationship in 1963 https://www.youtube.com/watch?v=jf7rsCAfQCo.)

Credal Transformer: A Principled Approach for Quantifying and Mitigating Hallucinations in Large Language Models
Shihao Ji, Zihui Song, Jiajie Huang
https://arxiv.org/abs/2510.12137

Credal Transformer: A Principled Approach for Quantifying and Mitigating Hallucinations in Large Language Models
Large Language Models (LLMs) hallucinate, generating factually incorrect yet confident assertions. We argue this stems from the Transformer's Softmax function, which creates "Artificial Certainty" by collapsing ambiguous attention scores into a single probability distribution, discarding uncertainty information at each layer. To fix this, we introduce the Credal Transformer, which replaces standard attention with a Credal Attention Mechanism (CAM) based on evidential theory. CAM produces a "cre…

"As explained in chapter 11 of Meyer’s book, assertions are meant to check the correctness of a piece of software; that is, its ability to perform the tasks defined in their specification.
Because, you do have a specification, right? Right?"
https://deprogrammaticaipsum.com/asser…

Assertions
Colin Powell passed away during the preparation of this article. In one of the most memorable and abhorrent chapters of his career he gave a speech in the United Nations trying to justify the unjustifiable.

For years, Sen. Ron Johnson has been spreading conspiracy theories and misinformation about COVID-19 and the safety of vaccines.
He’s promoted disproven treatments for COVID-19
and claimed, without evidence, that athletes are “dropping dead on the field” after getting the COVID-19 vaccination.
Now the Wisconsin politician is endorsing a book by a discredited doctor promoting an unproven and dangerous treatment for autism and a host of ailments:
chlorine dioxide, a chem…

Senator Endorses Discredited Doctor’s Book on a Chemical He Claims Treats Everything From Autism to Cancer
Wisconsin's Ron Johnson has a history of spreading vaccine misinformation. Now he's giving credence to assertions about the therapeutic powers of chlorine dioxide, a disinfectant and deodorizer. “It is all lunacy," one expert said.

ChatGPT is useful for getting the average of the information in its weights on a given topic
Grok (Expert) is useful for filtering search engine slop into a summary with relevant, sourced, checkable web links
Neither of these necessarily produce The Truth, but in this example, Grok generates significantly more reliable output when precision matters. As time goes on and the volume of hallucinated nonsense on the Web mounts higher, Grok's ability to attribute its assertions t…

If you can distinguish, you can express: Galois theory, Stone--Weierstrass, machine learning, and linguistics
Ben Blum-Smith, Claudia Brugman, Thomas Conners, Soledad Villar
https://arxiv.org/abs/2510.09902

If you can distinguish, you can express: Galois theory, Stone--Weierstrass, machine learning, and linguistics
This essay develops a parallel between the Fundamental Theorem of Galois Theory and the Stone--Weierstrass theorem: both can be viewed as assertions that tie the distinguishing power of a class of objects to their expressive power. We provide an elementary theorem connecting the relevant notions of "distinguishing power". We also discuss machine learning and data science contexts in which these theorems, and more generally the theme of links between distinguishing power and expressive power, ap…

The frontline in Ukraine is not facing imminent collapse despite recent Russian gains and Kremlin assertions.
https://understandingwar.org/research/russia-ukraine/russian-offensive-campaign-assessment-november-28-2025/

Russian Offensive Campaign Assessment, November 28, 2025
The frontline in Ukraine is not facing imminent collapse despite recent Russian gains and Kremlin assertions.

Error chaining in JavaScript: cleaner debugging with Error.cause
Error handling in JavaScript has always felt a bit chaotic. Throwing errors is easy, but tracing them back to the root cause? Not so much. That’s where the cause property comes in.
🧑‍💻 https://all…

Error chaining in JavaScript: cleaner debugging with Error.cause - Matt Smith
Use JavaScript's 'cause' property to chain errors, preserve context, and simplify debugging. Cleaner stack traces, better test assertions.

Semantic disambiguation of scientific assertions in the form of nanopublications* is, thus far, under-utilised in scientific communication.
*nanoplublication: https://nanopub.net/

Because I’m seeing this in “serious” articles, Dyson spheres are—literally—a joke.
The paper from Freeman Dyson is literally a fully purpose-written joke making fun of early SETI efforts, with a cascade of ever more implausible assertions leading to “we should be surrounded with these spheres so let’s look for them”.
They’re a joke making fun of gullible people who don’t think things through.
Now gullible people who don’t think things through (like Sam Altman) are using the term like it’s a real thing that could actually work.

Lol, I think this page is missing a big fucking elephant-in-the-room statement:
"Don't allow AI tools that make shit up and frequently make incorrect assertions run anything on any infrastructure, ever. If fact, just stop reading right now, because this was a stupid idea from the beginning."
https:…

Security Best Practices - Model Context Protocol

from my link log —
Renewable energy unambiguously reduces UK wholesale power prices.
https://www.carboncommentary.com/blog/2025/8/18/renewables-do-unambiguously-reduce-wholesale-power-prices
saved 2025-08-20

Renewables do unambiguously reduce wholesale power prices | Carbon Commentary
We still hear assertions that adding renewables to the grid has increased the UK’s electricity costs. I looked at two sources of data and plotted one against the other to test whether there’s any truth in this. 1,      The ‘next day’ electricity price fo

Alignment Without Understanding: A Message- and Conversation-Centered Approach to Understanding AI Sycophancy
Lihua Du, Xing Lyu, Lezi Xie, Bo Feng
https://arxiv.org/abs/2509.21665

Alignment Without Understanding: A Message- and Conversation-Centered Approach to Understanding AI Sycophancy
AI sycophancy is increasingly recognized as a harmful alignment, but research remains fragmented and underdeveloped at the conceptual level. This article redefines AI sycophancy as the tendency of large language models (LLMs) and other interactive AI systems to excessively and/or uncritically validate, amplify, or align with a user's assertions-whether these concern factual information, cognitive evaluations, or affective states. Within this framework, we distinguish three types of sycophancy: …

AssertFix: Empowering Automated Assertion Fix via Large Language Models
Hongqin Lyu, Yunlin Du, Yonghao Wang, Zhiteng Chao, Tiancheng Wang, Huawei Li
https://arxiv.org/abs/2509.23972

AssertFix: Empowering Automated Assertion Fix via Large Language Models
Assertion-based verification (ABV) is critical in ensuring that register-transfer level (RTL) designs conform to their functional specifications. SystemVerilog Assertions (SVA) effectively specify design properties, but writing and maintaining them manually is challenging and error-prone. Although recent progress of assertion generation methods leveraging large language models (LLMs) have shown great potential in improving assertion quality, they typically treat assertion generation as a final …

AssertGen: Enhancement of LLM-aided Assertion Generation through Cross-Layer Signal Bridging
Hongqin Lyu, Yonghao Wang, Yunlin Du, Mingyu Shi, Zhiteng Chao, Wenxing Li, Tiancheng Wang, Huawei Li
https://arxiv.org/abs/2509.23674

AssertGen: Enhancement of LLM-aided Assertion Generation through Cross-Layer Signal Bridging
Assertion-based verification (ABV) serves as a crucial technique for ensuring that register-transfer level (RTL) designs adhere to their specifications. While Large Language Model (LLM) aided assertion generation approaches have recently achieved remarkable progress, existing methods are still unable to effectively identify the relationship between design specifications and RTL designs, which leads to the insufficiency of the generated assertions. To address this issue, we propose AssertGen, an…

DeepAssert: An LLM-Aided Verification Framework with Fine-Grained Assertion Generation for Modules with Extracted Module Specifications
Yonghao Wang, Jiaxin Zhou, Hongqin Lyu, Zhiteng Chao, Tiancheng Wang, Huawei Li
https://arxiv.org/abs/2509.14668

DeepAssert: An LLM-Aided Verification Framework with Fine-Grained Assertion Generation for Modules with Extracted Module Specifications
Assertion-Based Verification (ABV) is a crucial method for ensuring that logic designs conform to their architectural specifications. However, existing assertion generation methods primarily rely on information either from the design specification, or register-transfer level (RTL) code. The former methods are typically limited to generating assertions for the top-level design. As the top-level design is composed of different modules without module-level specifications, they are unable to genera…