In a not so distant future, relationship compatibility is determined by an advanced algorithm enforced by the federal government. Participation is mandatory. Users must be paired with (or reassigned) to their ideal partner within one year or be transitioned to a permanent single lifestyle facility.

This story and the idea of using a raging storm as a metaphor for the trials that test relationships has been in my mind for a long time. Two people who are perfectly compatible and 100% in love are still going to get hit with challenges out of their control. Maybe it’s health, finances, loss of a job, death of a parent, etc. There are so many factors internal and external th

ShredOS is a USB bootable (BIOS or UEFI) small linux distribution with the sole purpose of securely erasing the entire contents of your disks using the program nwipe.

The four phases of the typical journey into coding

1. The Hand Holding Honeymoon is the joy-filled romp through highly polished resources teaching you things that seem tricky but are totally do-able with their intensive support. You will primarily learn basic syntax but feel great about your accomplishments.
2. The Cliff of Confusion is the painful realization that it's a lot harder when the hand-holding ends and it feels like you can't actually do anything on your own yet. Your primary challenges are constant debugging and not quite knowing how to ask the right questions as you fight your way towards any kind of momentum.
3. The Desert of Despair is the long and lonely journey through a pathless landscape where every new direction seems correct but you're frequently going in circles and you're starving for the resources to get you through it. Beware the "Mirages of Mania", like sirens of the desert, which will lead you astray.
4. The Upswing of Awesome is when

cross-posted from: https://programming.dev/post/22180123

It is predominantly easy to just accept bad conditions when an alternative is seemingly unfeasible. "I need this software", a lot of us will say when even presented with a better alternative. A lot of us will argue to our bones that being subject to cruelty from software developers is necessary for one potential gain or another. All of which creates a feedback loop of re-enforcement of this parasitic idea that proprietary software is somehow inescapable and we need to give up trying to do something about it. But we shouldn't give up and we should fight. Not just to switch from Windows to GNU / Linux, but to make it so Windows itself will start respecting you too.

...

With software a lot of people lose freedom all the time. Windows is so predominately used that I don't understand why people don't get crazy over this. Yet banning Windows would be a problem, arguably a worse problem, than all those people using it

It is predominantly easy to just accept bad conditions when an alternative is seemingly unfeasible. "I need this software", a lot of us will say when even presented with a better alternative. A lot of us will argue to our bones that being subject to cruelty from software developers is necessary for one potential gain or another. All of which creates a feedback loop of re-enforcement of this parasitic idea that proprietary software is somehow inescapable and we need to give up trying to do something about it. But we shouldn't give up and we should fight. Not just to switch from Windows to GNU / Linux, but to make it so Windows itself will start respecting you too.

...

With software a lot of people lose freedom all the time. Windows is so predominately used that I don't understand why people don't get crazy over this. Yet banning Windows would be a problem, arguably a worse problem, than all those people using it. You should have the right to use software that you want to use, the

...

Xu says that while it is likely studies that received AI-generated responses have already been published, she doesn’t think that LLM use is widespread enough to require researchers to issue corrections or retractions. Instead, she says, “I would say that it has probably caused scholars and researchers and editors to pay increased scrutiny to the quality of their data.”

“We don’t want to make the case that AI usage is unilaterally bad or wrong,” she says, adding that it depends on how it’s being used. Someone may use an LLM to help them express their opinion on a social issue, or they may borrow an LLM’s description of other people’s ideas about a topic. In the first scenario, AI is helping someone sharpen an existing idea, Xu says. The second scenario is more concerning “because it’s basically asking to generate a common tendency rather than reflecting the specific viewpoint of somebody who already knows what they think.”

If too many people use AI in that way, it could le

cross-posted from: https://programming.dev/post/22040366

Abstract

Browser fingerprinting is a growing technique for identifying and tracking users online without traditional methods like cookies. This paper gives an overview by examining the various fingerprinting techniques and analyzes the entropy and uniqueness of the collected data. The analysis highlights that browser fingerprinting poses a complex challenge from both technical and privacy perspectives, as users often have no control over the collection and use of their data. In addition, it raises significant privacy concerns as users are often tracked without their knowledge or consent.

Methods of Browser Fingerprinting

• A. HTTP Header Attributes
• B. Enumeration of Browser Plugins
• C. Canvas Fingerprinting
• D. WebGL Fingerprinting
• E. Audio Fingerprinting
• F. Font Fingerprinting
• G. Screen Fingerprinting
• H. WebRTC Fingerprinting
• I. CSS Fingerprinting
• J. Ad

Abstract

Browser fingerprinting is a growing technique for identifying and tracking users online without traditional methods like cookies. This paper gives an overview by examining the various fingerprinting techniques and analyzes the entropy and uniqueness of the collected data. The analysis highlights that browser fingerprinting poses a complex challenge from both technical and privacy perspectives, as users often have no control over the collection and use of their data. In addition, it raises significant privacy concerns as users are often tracked without their knowledge or consent.

Methods of Browser Fingerprinting

• A. HTTP Header Attributes
• B. Enumeration of Browser Plugins
• C. Canvas Fingerprinting
• D. WebGL Fingerprinting
• E. Audio Fingerprinting
• F. Font Fingerprinting
• G. Screen Fingerprinting
• H. WebRTC Fingerprinting
• I. CSS Fingerprinting
• J. Additional JavaScript Attributes
• K. Advanced Techniques Using Machine Learning