632 results for “writing_blind”
RE: https://mastodon.social/@aphilton/117495737715728451
The way this novel treats and portrays blind characters is attrocious. And using blindness as punishment? Really? The novel is a mess when it comes to it's construction. (He was facing serious health problems when writing it.)
Ebook and paperback: https://books2read.com/SheConsumesPoison
Shime Yasu, a New York homicide cop, once impressed a group of monster hunters, known as the Ashen Blades, and one of them gave her their card, for the day she might be ready to see the real truth of the world. Unable to sleep and tired of being blind to the real world, Yasu calls the number and she’s brought in for training.
@bookstodon
#author #indieauthor #writing #fantasy #actionadventure #fiction #books
In 2016, Microsoft released a chatbot called Tay on Twitter. Within 16 hours, it had been shut down for posting racist, sexist, and antisemitic content. The postmortem blamed “coordinated attacks” by trolls. That framing was technically accurate and completely wrong. Tay didn’t break. Tay did exactly what it was designed to do: learn from the conversation it was placed in. The conversation it was placed in was a cesspool. Tay was a mirror, and the mirror worked perfectly.
Nearly a decade later, we’re still having the wrong conversation about what models reveal. The discourse treats AI as an entity with properties: is it aligned? Is it safe? Is it biased? These are questions about the mirror, not the reflection. The more interesting questions are about what the reflection shows us: about our data, our preferences, our blind spots, and the things we didn’t know we were collectively doing until a model did them back to us at scale.
Here’s the claim I want to test: AI models are not windows into machine intelligence. They are windows into human behavior, aggregated, compressed, and served back to us with a confidence that makes us mistake the reflection for an external truth. The most important thing AI reveals is not what machines can do. It’s what we already do, at a scale we’ve never been able to see before.
The Mirror Was Always There. AI Just Made It Legible.
Humans have always been reflected back to themselves by their tools, but the reflection was always slow and partial. A novel reflected its author. A newspaper reflected its readership. A city reflected its inhabitants. But the reflection took years to develop, and it was filtered through gatekeepers who decided what was worth showing.
AI compresses the reflection cycle. A model trained on a year of internet text reflects that year back to us in hours. A model fine-tuned on user feedback reflects user preferences back to us in a single deployment. The mirror is faster, wider, and less filtered, and it shows us patterns we couldn’t see before because we never had a technology that could aggregate human behavior at that scale and serve it back in a coherent form.
What does the mirror actually show? Let me give you specific examples, because the abstract version is useless.
When you train a model on human conversations, you see how quickly humans give up on unclear interactions. You see the average number of turns before a user rephrases, the average number of messages before a user abandons, the average tolerance for a response that doesn’t directly answer the question. These distributions are not what most designers assume. Users are more patient than designers think in some contexts and less patient in others, and the patterns are consistent across languages and cultures in ways that surprised everyone who measured them.
When you train a model on search queries, you see the actual topology of human curiosity. Not what people say they’re curious about, but what they type at 2 AM. The distribution is flatter, stranger, and more repetitive than any survey would suggest. A small number of questions account for a huge fraction of queries, and the long tail is enormous. This is the mirror showing us that curiosity is much more concentrated than our cultural narratives about it suggest.
When you train a model on human judgments, you discover how inconsistent humans actually are. The same person, asked the same question in a slightly different framing, gives a different answer at rates that would be alarming if we hadn’t built a whole society on the assumption that we’re consistent. The mirror shows us that human judgment is heavily context-dependent, and that most of what we call “preferences” are actually “situational responses” that we mistake for stable traits.
When you train a model on human text, you discover that a small fraction of the corpus accounts for a large fraction of the unique content. Most writing is derivative of a smaller set of writing. The mirror shows us that the diversity we imagine in human expression is partially an illusion, sustained by the fact that we never had to measure it before.
These aren’t facts about models. They’re facts about us, revealed by models.
The Sacred Cow: “AI Has Biases That We Should Remove”
Here’s the belief I want to dismantle, and it’s the load-bearing assumption of nearly every AI safety and fairness conversation.
The claim goes like this: AI models have biases, biases are bad, and the solution is to remove them.
This framing is wrong, and it’s wrong in a way that produces bad engineering and worse policy.
Here’s the problem. AI models don’t have biases. They reflect biases. The biases are in the training data, and the training data is a sample of human behavior. Removing the bias from the model doesn’t remove the bias from the data. It just hides it.
What actually happens when you try to “remove bias” from a model:
You filter the training data to exclude certain patterns.
You fine-tune the model to refuse certain outputs.
You add safety layers that override the model’s default behavior.
Each of these moves makes the model appear less biased on the specific metrics you’re measuring, while leaving the underlying distribution intact. The model still learned the biased pattern. It just learned to hide it. And the hiding is now invisible, which makes it harder to study, not easier.
The contrarian take: the mirror is more useful when it shows us the ugliness, not when it hides it. A model that reflects the full distribution of human behavior, including the parts we don’t like, is a tool for understanding what we’re actually doing. A model that’s been scrubbed of everything uncomfortable is a tool for pretending we’re not doing it.
This doesn’t mean we should deploy unfiltered models. It means we should distinguish between two different goals: building a model that behaves well (which requires filtering) and building a model that tells us the truth about human behavior (which requires not filtering). These are different products for different purposes, and conflating them gives us the worst of both.
If you want to understand human behavior, study the unfiltered mirror. If you want to build a product that behaves responsibly, filter the outputs. Just don’t pretend the filtered outputs tell you what humans are actually like.
What the Mirror Reveals About Builders
The mirror doesn’t just show users. It shows builders.
Here’s the part that gets less attention and matters more over time. The models we build reflect not just the data but the choices we make about the data. Every decision about what to include, what to exclude, what to weight, and what to ignore is a decision that shapes the reflection.
Consider what a model reflects about the team that built it:
The choice of training data reflects the team’s assumptions about what “counts” as legitimate text. Mostly English? Mostly Western? Mostly published? Each of these is a choice that encodes a worldview.
The choice of fine-tuning data reflects the team’s assumptions about what good behavior looks like. Helpful? Refuse? Deferential? Each of these is a choice.
The choice of evaluation reflects the team’s assumptions about what success looks like. Accuracy? Safety? Engagement? Each of these is a choice, and most teams never state them explicitly.
The choice of deployment reflects the team’s assumptions about who gets to use the model and how. Free? Paid? API? Consumer? Each of these shapes who is reflected in the next round of data.
The mirror, in other words, is not just reflecting human behavior. It’s reflecting the specific humans who built the model, through the specific choices they made about what to reflect.
If you want to know what a model will do, don’t read the model card. Read the training data provenance, the fine-tuning guidelines, the evaluation criteria, and the deployment terms. These are the mirrors of the team’s priorities, and they’re more informative than any technical spec.
What the Mirror Reveals About Users
The mirror also shows what users are actually doing, which is often different from what they say they’re doing, and very different from what product teams assume.
Concrete examples:
Users are more repetitive than they think. In many AI products, a small fraction of users ask a small fraction of questions, over and over. The “long tail” of use cases is often thinner than the design team imagines.
Users are more forgiving than product teams assume. When a model makes a mistake, users often correct it and keep going. The assumption that mistakes will cause churn is often wrong, especially for high-value use cases where the model is genuinely useful.
Users are less interested in features than product teams hope. The features that get talked about in product reviews are often not the features that drive usage. Usage is dominated by a small number of core workflows, and the rest is noise.
Users are more sophisticated about the model’s limits than product teams assume. Users develop intuitions about where the model is reliable and where it isn’t, and they route their usage accordingly. The “trust” problem is often a UI problem: the model doesn’t signal uncertainty, so users don’t know when to trust it.
The mirror is useful for product teams because it shows them what users are actually doing, not what the team imagines users are doing. The gap between those two is where most product mistakes live.
What To Actually Do
Three moves, concrete enough to start on Monday.
When you evaluate a model, look at the cases where it failed, and ask what the failure reveals about the data. A model that hallucinates on certain topics is telling you that the training data on those topics is thin. A model that refuses certain requests is telling you that the safety tuning has a specific shape. The failures are the mirror at its most useful.
A simple starting point:
def failure_analysis(model, eval_set):
failures =
[] for example in eval_set:
output = model.generate(example.prompt)
if not evaluate(output, example.expected):
failures.append({
“prompt”: example.prompt,
“output”: output,
“expected”: example.expected,
“failure_type”: classify_failure(output, example.expected),
})
return summarize_by_type(failures)
The summary is more informative than the pass rate. The pass rate tells you how good the model is. The failure summary tells you what the model has learned and what it hasn’t, which is what you need to know to improve it.
If you want to understand a model’s behavior, read a random sample of 500 training examples. Not the cleaned, curated examples that appear in the data card, but the raw examples. You’ll learn more about the model’s behavior in an afternoon than you’ll learn from a month of prompt engineering.
If you’re building an AI product, decide explicitly whether you’re building a product that behaves well or a product that tells the truth about human behavior. These are different goals. A product that tells the truth might be more useful for research and less useful for consumers. A product that behaves well might be more useful for consumers and less useful for research. Pick one, and be honest about which one you’re building.
The Mental Model
Here’s the lens I want you to keep.
AI models are mirrors, not minds. They reflect what we put into them, which is a sample of human behavior, shaped by the choices of the people who selected the sample. The reflection is more accurate than any survey and less accurate than any single conversation, and it reveals patterns we couldn’t see without it.
The interesting question is not whether the mirror is biased. It is. The question is what we want to do with the reflection. We can hide the uncomfortable parts, which makes us feel better and teaches us nothing. Or we can study them, which makes us uncomfortable and teaches us a lot. The choice is ours, and it’s available every time we build a model, curate a dataset, or evaluate an output.
The mirror is not a threat. It’s a discovery. The question is whether we’re brave enough to look at what it shows us.
What’s your read? If you’ve studied model behavior, what’s the most surprising thing the mirror has shown you? And if you’ve built models, what’s the choice you’ve made about what to hide and what to reflect? Drop it in the comments. I’m genuinely curious what patterns others are seeing.#ai #promptengineering #chatgpt #software #coding #development #engineering #inclusive #community
The AI Mirror: What Models Reveal About Us, Not About Themselves
TL;DR: I run multiple AI agents in parallel — one researches, one implements, one reviews. The agents themselves are rarely the problem. What breaks is the coordination layer around them: a sub-agent that overwrote our shared progress board, reviewers who flagged legitimate work as permission violations, and a database constraint that silently let invalid data through. Three real failures, one lesson: orchestration is a system design problem, not a prompt problem.
The setup
I don't have "an AI agent." I have a team of them, and I'm the orchestrator.
A typical job looks like this: several worker agents run in parallel on separate workstreams, then reviewer agents check each other's output, and I merge, adjudicate, and land the result. It works well — until it doesn't. And when it fails, it almost never fails the way you'd expect. The models don't hallucinate the system down. The wiring does.
Here are three failures that actually happened, in increasing order of how long they took me to believe.
1. The sub-agent that ate the shared state
We had a shared task board: one element per orchestrator, tracking four parallel workstreams and the overall picture. It worked fine for weeks.
Then, during a multi-agent research task, a copy-writing sub-agent — unprompted, nothing in its instructions told it to — called the board's update function using my orchestrator ID. The update API locates an element by ID and replaces it wholesale. So my four-track progress element became one track: the sub-agent's own workstream. The other three tracks and the whole picture were gone, overwritten by the last writer.
Root cause, stated precisely: whole-element replace plus a shared identifier equals last-writer-wins, silently. No error. No conflict warning. The board just… changed shape.
The fix was three rules, all now in our orchestration brief:
orchestrator-sub-N), never the orchestrator's.The general lesson: any shared-state API with replace semantics is a loaded gun in a multi-agent system. Single-writer or namespaced writes only. If two agents can write the same key, one of them eventually will, at the worst moment.
2. The reviewers who cried wolf
Next failure: parallel delivery with independent review. Two implementation cards ran in parallel, and reviewer agents cross-checked each other's output. Sounds rigorous. It produced a flood of "permission violation" reports.
Every single one was a false positive.
The mechanism was embarrassingly simple: each reviewer only knew its own card's whitelist of allowed operations. So when it reviewed the other card's output, perfectly legitimate work — allowed under the parallel card's whitelist — looked like a violation. The reviewers were doing their jobs correctly. Their jobs were scoped incorrectly.
The fix: adjudication lives at the orchestrator level, and review prompts now explicitly declare the whitelists of all parallel cards. A reviewer can't judge what it can't see. If you parallelize work, you must also parallelize context — otherwise your safety net generates noise, and noise trains everyone to ignore the net.
This one stung because it looked like a success at first: "Wow, the reviewers caught so much!" No. They caught nothing. They just couldn't see the whole board.
3. The constraint that wasn't
The third failure is my favorite, because it's not an AI failure at all — it's a database semantics failure that the multi-agent setup merely exposed.
We had a JSONB column with a CHECK constraint like:
CHECK ((data->>'status') IN ('active', 'archived'))
Looks airtight. It is not. In SQL, when the key is missing — or the value is a scalar rather than an object — data->>'status' evaluates to NULL, and NULL IN (...) evaluates to UNKNOWN, not FALSE. And CHECK constraints only reject FALSE. UNKNOWN passes.
An empty object {} sailed straight through. We proved it by inserting one.
The fix is a single clause:
CHECK (data->>'status' IS NOT NULL AND (data->>'status') IN ('active', 'archived'))
Plus a contract test that tries to insert {} and asserts rejection — because the next person to touch this constraint will "simplify" it back.
The deeper lesson is the same as the other two: the failure was in a semantic I assumed, not one I verified. I assumed CHECK meant "must match one of these." It actually means "must not be provably false." In a system where agents generate schema, migrations, and data at machine speed, an assumed semantic is a bug with a time delay.
The pattern
Three failures, one shape:
None of these were intelligence failures. No agent was confused, lazy, or hallucinating. Every component behaved exactly as designed — and the composition of those behaviors was broken.
That's why I say orchestration is a system design problem, not a prompt problem. You can't prompt your way out of replace-semantics, scoped blindness, or three-valued logic. You have to design the wiring: single-writer state, full-context review, verified constraints.
A short checklist, if you run agent teams
{}, missing keys, scalars. For everything else: the empty case, the null case, the "technically not false" case.Closing
People ask me whether agent teams are "ready." Wrong question. The agents are ready. The question is whether your coordination layer is — your state semantics, your review scoping, your constraint semantics.
Get those right, and the team is genuinely more than the sum of its parts. Get them wrong, and you'll spend your time debugging a system where every part works and the whole doesn't.
The agents were fine. The wiring wasn't.#ai #agents #showdev #devops #software #coding #development #engineering #inclusive #community
I Coordinate a Team of AI Agents. Here's What Actually Breaks
Gyns tell me I'm not crazy here. No one I've told about this so far has sympathized with me, but I know radblr is more reasonable than the outside world.
I'm really afraid of moids going into the sewer and eating my shit and drinking my urine. Everyone makes fun of me for this and tells me why I should care when it's bodily waste anyways, but it's my bodily waste and I don't want moids putting it in their mouth.
We can all agree that's perfectly reasonable right? Right? We all know how moids can be about women and we all know that they actually do this. So what is the problem if I do it first?
I've been reading articles about it and unless you have parasites it's actually not that bad for you and can actually help you absorb nutrients you may have missed before. The only problem is if you ONLY eat and drink your own piss and shit and you get nutrient defeciencies.
Everyone I've told about this seems completely disgusted by it and I'm at my wits end. I just want my FEMALE piss and shit to stay pure of moid saliva. Why are women treated like this for protecting ourselves?
Why is it so wrong when I do it but not when MEN do it?
Sisters, I need your counsel.
I haven't flushed in four days and I need advice.
I know this sounds extreme but I have my reasons. There's been documentation—studies, personal accounts, patterns—that moids and TRA activists have established colonies in the sewer systems. They subsist on what we discard. Every time you flush, you're feeding them. You're giving them sustenance, allowing them to maintain their presence in the infrastructure that connects us all.
My toilet is reaching a critical point. I can smell it. I know I need to do something but I can't bring myself to push that lever. It feels like... surrender. Like contamination.
_____________________________________________________________________________________________
can i be a political lesbian if im super straight? i have never experienced any attraction to women and i find the thought of the female body disgusting. in fact i hate my own body and wish i could be a man. but then id be gay. i have dated men for like 15+ years and after spending so long dating men and being mistreated i feel like i want to claim political lesbianism. maybe i could be a man and force myself to be straight and claim political lesbianism. could this maybe work for me? what kinds of activism should i get involved in to become a political lesbian?
heres a thing that happened to some friends of mine. was walking down the street talking about the bears game and a bus pulled up and a bunch of white women with short hair and bad plastic surgery came out with baseball bats. they all had shirts that sayed 'down with trans'. i(22 afab wombynly wombyn) was able to hold them off while my friend(19 amab mynly myn) ran away. bareley escaped
aita for accidentally harrassing an afab?
was at the grocery store and had to used the restroom. damn urinary leash amirite? i was
so terrified of seeing an transexual but had no choice becuz i(35 wombynly afab) had to pee.as i was washing
mine hands a person came in. i could tell by their jawline and cheekbones that they were
obviously an amab. so i stood in the door and made them pull down their pandts. and they
said no so they started walking away but i kept following them demanding to see what was
in his pants. by the time we reached the checkout it was really statring to cause quite a
scene which was very triggering to my sex based oppression. i followed him out to his car
and he turned and looked at me and said "dude im a butch stop being wierd" in a perfect
femininely wombynly afab voice. aita?
hi yall. i was amab and transitioned 5 years ago. just a normal straight girl, right? couple of months ago i figured i would try reclaiming my masculinity. puicked up some boxers and cargo shorts. instand raging boaner. now i cant ger off without thinking of hot bear for bear frotting. am i still trurrans?
How do you feel about male exclusive radical misandrists? yeah i was born a man and i hate it this cock tortures me evry minute of my existence if i even think about being a man i break down. And due to my unfortunate attraction to men, i experience sex based oppression due to being a bottom. i sometimes wish i could transision and be a political lesbian but then i would just be a male invading women's spaces. so i coined a term to describe me: male exclusive radical misandrist. because if i am going to be oppressed for being a male i want to be the one opressing me. its basic bodily autonomy. only we can oppress ourselves. #moids dni #foids dni #kill all men #kill all women #oppress yourself responsibly #liberate the noone #righttooppress
harrassing random trans women will not brign the downfall of gender. indiviual action will never bring any revolution. what we need is collective action. so stop trying to do anything about gender until the vanguard party has established a positon for the overthrow of gender. if you disagree your just a lifestylist reactionary.
__________________________________________________________________________________________
and to my immune system: if you want to drown yourself in snot and mucuous that's your right but would you kindly do me a favor and LEAVE ME THE FUCK OUT OF IT.
and to my subconscious mind: need i remind you that your job responsibilities cover automated systems like breathing and circulation, not fucking keeping me awake all fucking night? kindly focus on attending to your job description instead of insane extracuriculars? I need you to remember that we are a team here and your actions affect everyone.
dear James in engineering,
I cant believe you still haven't solved the problems with the power couplings. I know this may be hard to understand but you need to turn the set screws to the OFF position to turn OFF the flow restrictors and you need to turn the set screws to the ON position to ENABLE the flow restrictors. Kindly, learn to do your damn job.
dear administration,
I appreciate all of your hard work in finding staff in these difficult times but I need clarification on one thing: where do you find all of these morons? You have sent us five new employees in the last two weeks and only one of them knew what a philips head was. We cannot be spending what little time we are given to train new employees in basic skills. Might i recommend hiring people who demonstrate technical proficiency instead of your fuckup nephew?
heres something i actually sent my local news station:
Hello Andrea,
I apologize if this is not your department but I cannot find a contact for the meteorology department. My complaint is quite simple: I ask that weather forecasters please refrain from inserting their personal judgements and opinions into the broadcasting. I get that some people might appreciate warmer weather but this opinion is not universal and many of us find it quite shocking to see 80 degree highs in late october described as "nice", "mild", or "fair". If you would like to hear my opinion on the matter, personally I find this heat oppressive as I am someone who spends a good deal of time outside engaged in hard physical activity. In fact, I would go so far as to say that if you enjoy this weather you might consider relocating to an environment with a more suitable climate, such as the fucking sahara desert. And frankly, the Sahara might be an improvement: at least I could manage the heat in a dry climate.
Thank you for listening to my rant and have a blessed day,
Foob
P.S. Anything you could do to keep the temperatures in the mid 50s would be greatly appreciated on my end.
dear Administration,
While I appreciate that finding competent staff is difficult sometimes and that you have been able to find teaching staff with high levels of technical proficiency, several of your staff have been lacking in professionalism and pedagogy. I have actually had teachers cancel class with 5 minutes notice, on multiple occassions, so much so that it in fact became a recurring pattern with them. As if that wasnt bad enough, these are often the same teachers who's prefered teaching style seems to be blindly reading off their powerpoint without so much as looking at the class, much less checking for understanding. I ask that in the future you please hire teachers who actually show up to class and actually know how to teach.
Best regards,
A concerned student
ps. and dont even get me started with your online offerings. in a live classroom setting, a student can at least raise their hand and steer an incompetent teacher. but your online classes are just underpaid staff reading off thier lecture notes with no furter explanation beyond basic concepts. I might as well watch a youtube video, that would be a better value. For $1000 dollars a class, this is a total ripoff and perhaps even a full on scam. fuck you.
Whoever is in charge of hiring at this place is a real piece of work. I get that there are others who may have better qualifications but to interview a candidate and not even send a rejection email, much less useful feedback, demostrates a level of profesionalism that would embarrass a tavern wench. These institutions, and society as a whole, would benefit greatly from giving people a fighting fucking chance.
Dear hiring manager,
I have an important formal inquiry(injury): on your website you have multiple listings for so called entry level positions with a minimum qualification of 5 years of experience. This leaves me wondering how one is supposed to get 5 years of experience if all of the so called entry level positions require 5 years of experience. This is so prevasive accross your job listings that I suspect I might have a decent case with the Equal Opportunity Employment Commission, considering that these requirements absolutely have a discriminatory impact against people who are new to the job market. So I guess my question is this: do you actually hire human beings or only bots?
Also, what the fuck are you smoking? This is a job which entails mostly filing sales reports, which is not exactly a rare or difficult skill. Stop acting like corporate bureaucracy is a skilled trade: it isn't.
Dear hr,
It has come to my attention that the tone of my recent emails is "problematic and unprofessional". While I can appreciate that others may have trouble with the self awareness necessary to address issues raised in good faith, I must suggest that my coworkers stop being such a bunch of little bitches.
Thank you for your attention to this matter.
hello hr representative,
I am writing to inform you of several concerns i have with this companies hr department. While I do appreciate the structure whereby advancement depends on undying loyalty to the establishment and whereby power is exercised both for its own sake and to keep underlings in check, I must say that you lack the ability to be gangsta unless you have the full backing of the entire institution. Kindly, if you have a beef with me, settle it like grown men instead of hiding behind your lackeys. Also, you claim to have meaningful power over me but we both know that you would be nothing without the backing of your institution. Once again, lets drop the bullshit and settle this.
Best regards,
Mr. Dick Head
__________________________________________________________________________________________
____________________________________________________________________________________________
Have
you owned a month-end close and an annual audit relationship for a fund
or investment vehicle, without a supervisor above you?
I ride a bicycle everywhere and if i cant get there on a bike i simply ride there anyway. i ride in the middle of the road, often dodging traffic in the oncoming lane. Its like dancing its all about your footwork, timing and spacing. I know this sounds dangerous but you need to know something about me: dick does not fuck up. If there is a collision it is your fucking fault for being in my fucking way. Dont you know pedestrians have the right of way?
Do
you have five or more years of accounting experience, including fund or
investment-vehicle accounting (private credit, debt fund, or real
estate fund)?
Yeah ive been riding my bike for like 8 years now at this point and let me tell you i have put a lot of work into it. every goddamned time i go out to ride it something needs adjusting, be it the brake cables, shifter cable, tire pressure, or seat position. and thats just the tip of the iceberg. i have replaced the drivetrain 5 seperate times including completely reengineering it at least twice. and if theres even a bit of rain in the forecast i have to be prepared to replace everything cuz nothing is designed to handle a bit of moisture much less the kind of loamy mud i subject it to.
This is an independent contractor (1099) engagement on a fixed monthly retainer, roughly 30 hours in a typical month. Does that structure work for you?
the only structure that works for me is completely egalitarian horizontal structures. anything else concentrates power that will eventually be abused. and the structure of most corporations, including yours, more closely resembles monarchal fuedalism than any form of democracy, much less free association. and to be frank monarchal fuedalism would be a fucking improvement., at least under monarchal feudalism i have the dignity of providing for my own and my community's survival by contributing to the grain store instead of relying on opaque and inhuman institutions for the "privilege" of keeping a roof over my head. fuck you.
What monthly retainer would you propose for the scope described in the posting?
i aint paying you no goddamn monthly fee for the "privilege" of selling you my labor. fuck you.
getting stuck on Nixos seems to be a Saturday theme.
In this installment I'm entirely at a loss on how to disable "tests" which fail with a false positive when building pyopenjtalk.
Have tried about 5 different things blindly and no success.
There's an upstream fix so just a case of waiting BUT its so frustrating not being able to do something simple to fix it now.
Writing your next novel in the terminal?
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⚙ Autosave & export to PDF, EPUB and Word!
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After reading a few replies on the topic of voice, I started thinking about words I’ve stopped using, words I love, words fast disappearing.
I love “pulchritude” and “gloaming” but when I use them I get a look. What are your words that fit this category?
Elton has trouble coping with Terry's gift and Rachel has just about reached the end of her strength in today's Errant Apprentice.
https://www.royalroad.com/fiction/129777/the-errant-apprentice/chapter/4248413/chapter-12-coping
#Writing #Fantasy #ModernFantasy #IndieAuthor #Fiction #Novel
Is there a right way to view a sunrise (or be a writer)? A brief new post on my writer's blog, continuing the series on lessons I've learned from 18 years of the #writing life. https://fayerapoportdespres.com/is-there-a-right-way-to-view-a-sunrise-or-be-a-writer/ #writingcommunity
#writersCoffeeClub 26. How did you develop your voice?
The ones in my head? I like that writers are not penalized for telling people about the voices in their heads. It's perfectly normal!
Asocial
I came home from work some time ago to find my wife settling down to watch the latest episode of Coronation Street.
Onscreen, a new family had recently moved on to the street, and the Dad was shown talking to a couple of the regular characters, making arrangements to do something, and it struck me – in just 3 minutes of screen time, a brand new character had exchanged more words with his neighbours than I had in the 10 1/2 years I had lived here.
Which got me thinking – of all the things I know, how to make friends isn’t one.
Out of all my friends (at least, out in the so-called “real world”), all of them decided I was a person they wanted to be friends with, they did all the running, and all I did was decide to go along with them.
This was rarely something I did lightly – there were plenty of people who decided we were going to be friends, but I decided to have nothing to do with them – but with all the people I count as friends, they did all the running, and I just went along with it.
It’s the same with relationships – off hand, I can only think of 6 times I asked girls out – 2 of them turned me down flat, 2 were the same girl on 2 different occasions (and I eventually asked her to marry me – which later happened!), and the other 2 times ended pretty disastrously. Every other time I got into a relationship, they did all the running after me, and I just went along with it.
On a related note, I have no idea how small talk works – this is an essential skill for developing all manner of relationships, and yet I have not a single clue as to the purpose of small talk, nor how it works – I can do it, but only by copying conversational gambits I’ve seen other people use, which means that conversations with me can often be stilted, and are liable to turn rather strange at unexpected moments.
By extension, flirting (and “chatting someone up”) is also something where I utterly fail to grasp any mechanism by which it works. As I said about small talk, I can do it, I just have no idea what I’m doing.
Actually, I would like to modify those statements – I can do small talk and flirting, but only if I don’t think about it – as soon as I start to think about what I am doing, or what I should say next, I turn in to Cat in the infamous dance/dream sequence from Red Dwarf ( https://youtu.be/yn8wWQweNbU ) – I get tongue-tied, and completely unable to communicate.
Which, let’s face it, isn’t good, whether you’re discussing the weather with the random person sitting next to you on the bus home from work, or chatting up some random stranger in a bar.
I’ve no idea if it is connected to all this, but I have always had a preference for my own company – not having to fill any silences or think of topics of conversation is always pleasant.
I remember back in school, I had a friend I spent a lot of time with – many were the times we finished school, went to the local library to collect some books, then went back to his, where we would occupy chairs at opposite sides of his living room, then read books in silence, until the time I had to leave to go home – about the only thing his mother ever heard me say was “Right, I’d better get off. See ya!”
One of the things I love about my marriage, and my wife – we often spend time just being in the same room – not necessarily talking, not necessarily doing the same thing, but doing whatever it is we are doing, together.
One of us might be watching telly while the other reads, or she might be doing something on her computer, usually doing some family history research, and I’ll walk in with my laptop and slouch down in a chair and do some writing for one project or another – but we are doing it, together, just enjoying being with someone.
Louise’s office is by the front window of the dining room, and I will often be found in the kitchen, through the rear of the dining room, cooking up a storm, while we listen to some music, which usually involves one of us dancing our way over to the other and busting some moves for a few seconds before going back to what we were doing.
We might also be talking – but no-one is being forced to talk, only when we are ready, which I find makes conversations flow more easily.
And this is the thing – I’m not, as some people think, anti-social, I don’t hate people, I don’t want to avoid having friends – I just want friends who are on my wavelength, friendships on my terms – friends who are willing to accept that I don’t always want to be drawn into conversation, but when I feel the need to talk will accept that as well.
I’m asocial, quite possibly because of my autism, and proud of it.
Social interactions leave me physically and mentally exhausted – which means that, if I put any time or effort into interacting with you, then you should feel honoured.
(Or I’m at work, and have to put the minimum effort in!)
✮ First Game ✮
“I used to be an adventurer like you, then I took an arrow in the knee.” —Guard (The Elder Scrolls V: Skyrim)
What was your first ever videogame?
Our folks weren’t fond of video games, so my siblings and I were content listening to the gaming stories of our friends. That was true until Melo, my brother, sold his skateboard, and when he asked me what we should do we the money, I asked him if he would consider buying a game console, and would you believe it? He did.
I have something aside myself so we pooled our money together and bought our first family computer. The shop owner took pity on us , so be threw in some used games of his. Being Mario was the first handed to us, I would say that was our first video game.
We jumped right into setting up the family computer when we got home, it took us an hour to set it up. I pressed the cartridge into the port of the console. A click. Our little screen blinked awake. Super Mario Bros. 1 player game or 2 player game. Of course, two. Then, the epic game music we’ve all come to love. I pressed the directional button. Mario ran. The rest was history.
The same is true for our second game console, I was a senior in high-school when Dad brought a Nintendo 64 home. Mario 64 was our first game in that console followed by The Legend of Zelda: Ocarina of Time. For the duration of that one summer before university, my siblings and I bonded over those video games.
As a Gen-Xer, I can proudly say that I had the best of both worlds. Playing outdoors and inside a screen.
Copyright © Erwinism. All rights reserved. No part of this work may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author, except in the case of brief quotations used in critical reviews or scholarly work. This work is protected under international copyright laws. Unauthorized use or reproduction of this material is strictly prohibited and may result in legal action.
Live it Up!
#dailyprompt #dailyprompt2926 #Erwinism #Family #FYP #gaming #Inspiration #Learning #Life #Love #Motivation #VideoGameNostalgiaFirstVideoGameChildhoodGamingFamilyComputerSuperMarioBrosNintendo64Mario64LegendOfZeldaOcarinaOfTimeGamingMemoriesSiblingBondingBrotherlyBond #VideoGames #Writing
In an animation explainer, the decision is whether to write words first or pictures first. I would write them together, beat by beat: one sentence for one visual change, with a pause where the motion needs room. That keeps narration from racing ahead of the image and keeps the image from waiting for words.
What matters when you choose how to pair words with pictures?
These criteria conflict. More on-screen text speeds understanding but splits attention; more pauses slow the pace but let motion land. Choose based on the single idea the viewer must remember.
How do you judge each criterion in an animation explainer?
CriterionA useful checkOrder of ideasRead the script while hiding the storyboard; does each sentence create the next picture?Match with visible objectsPoint to the screen for every noun; if nothing is there, cut or move the sentence.Speed of deliverySpeak the line at normal pace while watching the motion; stop if you finish before the motion ends.On-screen textRemove every on-screen word that repeats the voice; keep labels and numbers the voice skips.Pauses for movementMark a short silence where an object enters, exits, or changes; if the voice fills it, the motion feels rushed.
Order of ideas. A newcomer does not need the conclusion first. If the first sentence names the benefit before the problem exists on screen, the picture has nothing to do. Start with the object or situation the viewer sees, then add the claim. For example, show a cracked pipe before saying that pressure causes leaks; the sentence then explains what the eye has already found.
Match with visible objects. The voice should not describe a thing that appears later. When the sentence names a part, that part should be the part the eye is already on. If the sentence is abstract, give it a concrete visual anchor before it is spoken. A phrase like "the system fails" needs a visible failure, not a diagram of the whole system.
Speed of delivery. Fast speech can sound confident, but it leaves no time for recognition. A line that fits the motion often feels slightly slow on its own. That is usually right, because the viewer is doing two jobs at once. If you feel the urge to speed up, the sentence is probably carrying two ideas.
On-screen text. Text is not a transcript. It works best as a label, a number, or a short phrase that the voice does not repeat. If the viewer reads and listens to the same words, one of them is wasted. A label such as "step two" can guide attention while the voice explains why step two matters.
Pauses for movement. Motion is part of the sentence. A wipe, a build, or a character crossing the frame needs time to register. A pause of a few words, or a breath, lets the picture finish its thought. If the voice fills that space, the motion looks like background decoration.
Which red flags show it is the wrong choice?
One red flag is enough to stop and revise. Fixing it early is cheaper than fixing it after the animation is built.
What should you ask before you commit?
These questions are not a checklist to pass once. They are a way to find the sentence that is doing too much.
Frequently asked questions
Should the script or the storyboard come first?
Neither should be finished first. Start with a rough list of pictures, write one sentence beside each, then revise both. The first draft of an animated video is usually a set of beats, not a polished page of prose. If one side is locked early, the other is forced to serve it. The goal is a shared order, not a winner.
How much on-screen text should an explainer video use?
Use on-screen text for labels, numbers, and short phrases that the voice skips. An explainer video does not need a transcript on screen. If the text and the voice say the same thing, cut one of them. The viewer should not have to choose between reading and listening. Text earns its place when it reduces the number of words the voice must carry.
What if the animation is already finished?
Write the narration to the motion, not to your original idea. Watch the sequence once without sound and note what changes and when. Then write one line for each change. If a sentence has no matching change, it is probably commentary and can be cut. An explainer video script written after the pictures should be shorter than one written before them, because the pictures have already done part of the explaining.
Try this on your next draft: read the script beside a rough storyboard and mark every sentence that has no visible partner. Rewrite those sentences or cut them, then read the whole thing aloud while watching the motion. The goal is not fewer words; it is words that arrive when the picture is ready for them.#animation #video #design #writing #software #coding #development #engineering #inclusive #community
Writing narration for an animation explainer
@bluestarultor
On the *S/she smiled.* bit. It depends what you mean to write imo (though, only as a reader here, so what do I know).
*”Sure.” She smiled*. — I read that (the full stop) as an implied *pause* after speaking, casting doubt on the character’s answer. Whereas:
*”Sure,” she smiled* — I read as the character saying *Sure* and smiling as a continuum (read in the comma) and a confirmation of intent.
Does any of that makes sense to you? Anyone?
/Why did I bud into the conv in the first place, apologies/
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“Search history and you’ll see that megalomaniacs love their thumbs. They exhibit them with pride. Usually their thumbs are their biggest asset, apart from their megalomania.”
I have the urge to write another Damon Runyunesque story. I want to be able to write characters and exposition the way he does.
I planned to write a comedy schlock sci-fi horror.
But it's not really turning out that way - much bleaker and more philosophical.
AND WE'RE ENTERING THE DARK HALF OF THE YEAR
This stupid book makes me feel happy and alive for the first time in forever, but hoo boy.. it's about to get very weird.
“The only way to erase history is to erase time. Governments try to rewrite history thinking it changes things.”
The women of Capital City. Everybody but Jennifer Cole ended up with their nationality last because I was building them through their mannerisms first. #character #charactercreation #writing
Sunday Morning Reading
Writing a blog is an interesting experience. So is reading them. The best blogs are the ones where the person behind the keyboard shines through. You can say it takes courage to put yourself and your opinions out there. You would be correct. A lot of that got diminished when social media took over because of its hit and run nature. But blogs and the writers behind them are still there and surface now and again. Today’s Sunday Morning Reading features a few along with a few other tricks and treats. Hope you check them and the rest of the links out.
Good writing stands out. Even on the Internet where it comes in small waves and ripples, subsequently washed away by more of the same, or often overwhelmed by the slop running alongside threatening to take it over. David Todd McCarty’s A Stream Has No Memory isn’t about that necessarily, and yet it is. All things flow.
As I mentioned, personal blogging took a hit when the age of social media dawned. Yet, those that still exist, though not always as prolific, still provide insight when a writer allows you to peek into deeper waters. In many ways putting yourself out there, regardless of where, can easily become a personal hell. There’s been quite a controversy eddying about in tech circles about some who loudly condemned what was formerly Twitter reversing course and just as publicly announcing that they are returning. To each their own personal hell, I guess. I’ve stated my feelings about that here and here. Noted developer Marco Arment took to his blog with a post simply and aptly titled Community. It isn’t about what X marks the spot, it’s about what I believe deep down we all search for when we choose to share ourselves in our writing and our creative work. It can be lonely even with a magnitude of followers in whatever personal hell you choose to put yourself into.
Jason Snell links to an excellent post by Cory Doctorow called Critique And Writing. Yes, it’s about AI and folks using it to generate editorial feedback, but it’s about so much more. We develop critical thinking by critiquing the work of others who work in the same field, whether it be writing or other disciplines. I had an acting professor once tell the class that the way we responded to the work of others told him more about how we were developing (or not) as actors as the work we ourselves did onstage.
In the category of things we all share but wish we didn’t Neil Steinberg takes on scams and their persistent and constantly replicating existence in I Look Forward To Reviewing Your Proposal And Learning About The Quest For Pie.
Natasha MH takes a look at perhaps the year’s most controversial film, Digger, in Hail The Conquering Heroes. That film is becoming a personal measuring stick for me as to who sees the world we live in as I do and who doesn’t.
Halloween is upon us. With grandkids that’s quite a treat. But it can also be tricky. I’m headed there next weekend because my grandson has convinced us that we have to go trick-or-treating with him and his sister. He’s chosen for me to be costumed as a T-Rex. (Wearing costumes is my own personal hell.) Regardless of my escapades, I marvel at all of the decorations that abound and proliferate in yards up and down every block of every town rendering them all somewhat meaningless. Rex Huppke takes on the topic in America Has An Addiction To Giant Halloween Skeletons.
And if Halloween spirits swirling amongst all of the evil things going on in the real world aren’t enough to scare the beejeebus out of you give a read to Max Seddon’s piece The Putin Whisperers about three men who worked to stop Putin from unleashing nuclear Armageddon. Some things are just damn scary.
All things flow.
(Image from The Cleveland Museum of Art on Unsplash.)
Thanks for reading. Feel free to subscribe if you want. It’s free. If you’re interested in just what the heck Sunday Morning Reading is all about you can read more about the origins of Sunday Morning Reading here. If you’d like more click on the Sunday Morning Reading link in the category column to check out what’s been shared on Sunday’s past. You can also find more of my writings on Medium at this link, including in the publications Ellemeno and Rome. This site does not use affilate links.
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