#AI In Product Design Optimization

[rubylogan15]

Learn how generative AI addresses key manufacturing challenges with predictive maintenance, advanced design optimization, superior quality control, and seamless supply chains.

[einnosyssecsgem]

Machine learning applications in semiconductor manufacturing

Machine Learning Applications in Semiconductor Manufacturing: Revolutionizing the Industry

The semiconductor industry is the backbone of modern technology, powering everything from smartphones and computers to autonomous vehicles and IoT devices. As the demand for faster, smaller, and more efficient chips grows, semiconductor manufacturers face increasing challenges in maintaining precision, reducing costs, and improving yields. Enter machine learning (ML)—a transformative technology that is revolutionizing semiconductor manufacturing. By leveraging ML, manufacturers can optimize processes, enhance quality control, and accelerate innovation. In this blog post, we’ll explore the key applications of machine learning in semiconductor manufacturing and how it is shaping the future of the industry.

Predictive Maintenance

Semiconductor manufacturing involves highly complex and expensive equipment, such as lithography machines and etchers. Unplanned downtime due to equipment failure can cost millions of dollars and disrupt production schedules. Machine learning enables predictive maintenance by analyzing sensor data from equipment to predict potential failures before they occur.

How It Works: ML algorithms process real-time data from sensors, such as temperature, vibration, and pressure, to identify patterns indicative of wear and tear. By predicting when a component is likely to fail, manufacturers can schedule maintenance proactively, minimizing downtime.

Impact: Predictive maintenance reduces equipment downtime, extends the lifespan of machinery, and lowers maintenance costs.

Defect Detection and Quality Control

Defects in semiconductor wafers can lead to significant yield losses. Traditional defect detection methods rely on manual inspection or rule-based systems, which are time-consuming and prone to errors. Machine learning, particularly computer vision, is transforming defect detection by automating and enhancing the process.

How It Works: ML models are trained on vast datasets of wafer images to identify defects such as scratches, particles, and pattern irregularities. Deep learning algorithms, such as convolutional neural networks (CNNs), excel at detecting even the smallest defects with high accuracy.

Impact: Automated defect detection improves yield rates, reduces waste, and ensures consistent product quality.

Process Optimization

Semiconductor manufacturing involves hundreds of intricate steps, each requiring precise control of parameters such as temperature, pressure, and chemical concentrations. Machine learning optimizes these processes by identifying the optimal settings for maximum efficiency and yield.

How It Works: ML algorithms analyze historical process data to identify correlations between input parameters and output quality. Techniques like reinforcement learning can dynamically adjust process parameters in real-time to achieve the desired outcomes.

Impact: Process optimization reduces material waste, improves yield, and enhances overall production efficiency.

Yield Prediction and Improvement

Yield—the percentage of functional chips produced from a wafer—is a critical metric in semiconductor manufacturing. Low yields can result from various factors, including process variations, equipment malfunctions, and environmental conditions. Machine learning helps predict and improve yields by analyzing complex datasets.

How It Works: ML models analyze data from multiple sources, including process parameters, equipment performance, and environmental conditions, to predict yield outcomes. By identifying the root causes of yield loss, manufacturers can implement targeted improvements.

Impact: Yield prediction enables proactive interventions, leading to higher productivity and profitability.

Supply Chain Optimization

The semiconductor supply chain is highly complex, involving multiple suppliers, manufacturers, and distributors. Delays or disruptions in the supply chain can have a cascading effect on production schedules. Machine learning optimizes supply chain operations by forecasting demand, managing inventory, and identifying potential bottlenecks.

How It Works: ML algorithms analyze historical sales data, market trends, and external factors (e.g., geopolitical events) to predict demand and optimize inventory levels. Predictive analytics also helps identify risks and mitigate disruptions.

Impact: Supply chain optimization reduces costs, minimizes delays, and ensures timely delivery of materials.

Advanced Process Control (APC)

Advanced Process Control (APC) is critical for maintaining consistency and precision in semiconductor manufacturing. Machine learning enhances APC by enabling real-time monitoring and control of manufacturing processes.

How It Works: ML models analyze real-time data from sensors and equipment to detect deviations from desired process parameters. They can automatically adjust settings to maintain optimal conditions, ensuring consistent product quality.

Impact: APC improves process stability, reduces variability, and enhances overall product quality.

Design Optimization

The design of semiconductor devices is becoming increasingly complex as manufacturers strive to pack more functionality into smaller chips. Machine learning accelerates the design process by optimizing chip layouts and predicting performance outcomes.

How It Works: ML algorithms analyze design data to identify patterns and optimize layouts for performance, power efficiency, and manufacturability. Generative design techniques can even create novel chip architectures that meet specific requirements.

Impact: Design optimization reduces time-to-market, lowers development costs, and enables the creation of more advanced chips.

Fault Diagnosis and Root Cause Analysis

When defects or failures occur, identifying the root cause can be challenging due to the complexity of semiconductor manufacturing processes. Machine learning simplifies fault diagnosis by analyzing vast amounts of data to pinpoint the source of problems.

How It Works: ML models analyze data from multiple stages of the manufacturing process to identify correlations between process parameters and defects. Techniques like decision trees and clustering help isolate the root cause of issues.

Impact: Faster fault diagnosis reduces downtime, improves yield, and enhances process reliability.

Energy Efficiency and Sustainability

Semiconductor manufacturing is energy-intensive, with significant environmental impacts. Machine learning helps reduce energy consumption and improve sustainability by optimizing resource usage.

How It Works: ML algorithms analyze energy consumption data to identify inefficiencies and recommend energy-saving measures. For example, they can optimize the operation of HVAC systems and reduce idle time for equipment.

Impact: Energy optimization lowers operational costs and reduces the environmental footprint of semiconductor manufacturing.

Accelerating Research and Development

The semiconductor industry is driven by continuous innovation, with new materials, processes, and technologies being developed regularly. Machine learning accelerates R&D by analyzing experimental data and predicting outcomes.

How It Works: ML models analyze data from experiments to identify promising materials, processes, or designs. They can also simulate the performance of new technologies, reducing the need for physical prototypes.

Impact: Faster R&D cycles enable manufacturers to bring cutting-edge technologies to market more quickly.

Challenges and Future Directions

While machine learning offers immense potential for semiconductor manufacturing, there are challenges to overcome. These include the need for high-quality data, the complexity of integrating ML into existing workflows, and the shortage of skilled professionals. However, as ML technologies continue to evolve, these challenges are being addressed through advancements in data collection, model interpretability, and workforce training.

Looking ahead, the integration of machine learning with other emerging technologies, such as the Internet of Things (IoT) and digital twins, will further enhance its impact on semiconductor manufacturing. By embracing ML, manufacturers can stay competitive in an increasingly demanding and fast-paced industry.

Conclusion

Machine learning is transforming semiconductor manufacturing by enabling predictive maintenance, defect detection, process optimization, and more. As the industry continues to evolve, ML will play an increasingly critical role in driving innovation, improving efficiency, and ensuring sustainability. By harnessing the power of machine learning, semiconductor manufacturers can overcome challenges, reduce costs, and deliver cutting-edge technologies that power the future.

This blog post provides a comprehensive overview of machine learning applications in semiconductor manufacturing. Let me know if you’d like to expand on any specific section or add more details!

[tinybeetiny]

Build-A-Boyfriend Chapter 3: Grand Opening

I’ve been hungover all day… also.... I'm sorry that the chapters aren't as long as people like, that's just not really my style.

->Starring: AI!AteezxAfab!Reader ->Genre: Dystopian ->CW: none

Previous Part | Next Part

Masterlist | Ateez Masterlist | Series Masterlist

Four days before the grand opening, Yn stood in the center of the lab, arms crossed, a rare smile tugging at her lips.

No anomalies.

No glitches.

Every log was clean. Every model responsive and compliant.

She tapped through the final diagnostics as her team moved like clockwork around her, prepping the remaining units for transfer. The companions were ready. Truly ready.

They’d done it. And for the first time in months, Yn allowed herself to believe it.

“They’re good to go,” she said aloud to the room, voice steadier than it had been in weeks. “Now we just make it beautiful.”

There was no dissent. No hesitation. Just quiet, collective relief.

By 6:00 a.m. on launch day, the streets surrounding Sector 1 in Hala City were already overflowing. Women of all ages lined the polished roads, executives in sleek visors, college students in chunky boots, older women with glowing canes, and mothers with daughters perched on their hips.

A massive countdown hovered above the building in glowing light particles.

Ten. Nine. Eight. Seven. Six. Five. Four. Three. Two. One

When the number hit zero, the white-gold doors of the first Build-A-Boyfriend™ store slid open, and history, quite literally, stepped forward.

The inside of the flagship store was unlike anything anyone had seen, not in a simulation, not in VR, not even on the upper stream feeds.

It was clean but not cold, glowing with soft light that pulsed in time with ambient sound. Curved architecture, plants that weren’t quite real, air that smelled like skin and something floral underneath.

The crowd entered in waves, ushered by gentle AI voices projected from the ceiling:

“Welcome to Build-A-Boyfriend™, KQ Inc.’s most advanced consumer product to date. Please scan your wristband to begin. You are in complete control.”

Light pulsed with ambient music. The air carried soft notes of citrus and lavender. Walls curved inward like a safe embrace. It felt not like a store, but a sanctuary.

Just inside, a small platform rose, and the crowd hushed.

Standing atop it in a graphite suit that shimmered subtly with light-reactive tech, Vira Yun took the stage.

Her presence silenced everything. Not with fear. With awe.

She didn’t need a mic. The air itself amplified her words.

“Welcome, citizens of Hala City, and beyond. Today is not just a milestone for KQ Inc. It is a milestone for all of us, for womanhood, for autonomy, for intimacy on our terms. For centuries, we’ve been told to settle. To accept love as luck, not design. To believe that affection must be earned, that tenderness is a privilege, not a right. That era is over. Here, you are not asking. You are choosing. Each companion created within these walls is not simply a machine, but a mirror, one that reflects your needs, your softness, your strength, your fantasies, your fears. And we have given you the tools to shape that reflection without shame. This store is not about dependency. It’s about design. About saying: I know what I want, and I deserve to receive it, safely, sweetly, and with reverence. Let the world call it strange. Let them call it artificial. Because we know the truth: every human deserves to feel adored. And today, we’ve made that reality programmable.”

"Thank you. And welcome to Build-A-Boyfriend.”

From the observation deck, Yn stood quietly, tablet in hand, watching the dream unfold. She’d spent months writing code, assembling microprocessors, mapping facial expressions, and optimizing human simulation algorithms.

Now it was real. Now they were here, and it was working.

One of the first customers to walk in was 31-year-old office worker, Choi Yunji

She stepped forward, clutching her wristband like it might slip from her fingers. She’d told herself she was just coming to look. Just curious. Just research. But now that she was inside, face-to-face with a glowing interface, it felt more like a confession.

“Would you like an assistant, or would you prefer to design solo?” a soft voice asked beside her. Yunji turned. A young woman with slicked-back hair and a serene face smiled at her. The name tag read: Delin, Companion Consultant.

“I… I think I need help,” Yunji said.

“Of course,” Delin said warmly. “Let’s begin your experience.”

Station One: Body Frame

A holographic model appeared before them, neutral, faceless, softly breathing.

“Preferred height?”

“Taller than me. But not too much. I want to feel safe. Not… overpowered.”

“Understood.” Delin adjusted sliders with a flick of her fingers. The form shifted accordingly.

“Shoulders wider?” “Yes.” “Musculature?” “Athletic, not bulky.” “Skin tone?” “Honey-toned.”

Station Two: Facial Features

“I want kind eyes,” Yunji said. “And maybe a crooked smile. Something… imperfect.” “We can simulate asymmetry.” “What about moles?” “Placed to your liking.”

Station Three: Hair

“Longish. A little messy. Chestnut.” “Frizz simulation or polished strands?” “Frizz. I don’t want him looking like he came out of a factory.” Delin smiled. “Ironically, he did.”

Station Four: Personality Matrix

Yunji froze. The options felt too intimate.

“Start with a base? Empathetic, loyal, gentle, observant…” “Can I choose traits… I didn’t get to have before?” “Yes,” Delin said simply.

They adjusted levels: affection, boundaries, humor, attentiveness. A slider labeled “Emotional Recall Sensitivity” blinked softly.

“What’s this?”

“How deeply your companion internalizes memories related to you. It allows for more dynamic emotional bonding.” Yunji slid it to 80%.

Station Five: Wardrobe

“Something soft. Comfortable. Approachable.”

A cozy cardigan wrapped over a white tee. He looked like someone who would bring you tea without asking.

“Would you like to name your companion?” “…Call him Jaeyun.”

Her wristband lit up:

MODEL 9817-JAEYUN Estimated delivery: 3 hours Ownership rights granted to: C. Yunji

Yunji turned slowly, as if waking from a dream. Around her, other women embraced, laughed, shook — giddy or stunned. This was more than shopping. This was the return of the forbidden.

Around the Room

A pair of teenage twins argued over whether their boyfriends should look identical or opposites. A woman on her lunch break ordered her unit for home delivery with a bedtime story feature. Friends joked about setting up double dates and game nights with their new companions.

One customer squealed, “I’m going full fantasy, tall, sharp jaw, high cheekbones, and a scar over the brow. I want him to look like he’s been through something.” Her friend “Big eyes, soft lips, librarian vibes. Another “I want dramatic jealousy in a soft voice. Like poetry with teeth.”

The store pulsed with joy, wonder, and something deeper. Yn felt it in her chest, pride and awe, washing over the logic-driven part of her that rarely gave way. She had helped build this future.

As the lavender glow settled over the quieting store, Yn remained in the observation wing, reviewing data. The launch had exceeded all projections.

She didn’t hear the door slide open behind her.

“Stunning, isn’t it?”

Vira stepped in, elegant as ever in graphite, her braid flawless, her voice smooth.

Yn straightened. “Yes, ma’am. It’s surreal.”

“We did it. You did it,” Vira said, standing beside her. “Revenue exceeded estimates by 37%. But more than that… I saw joy out there. Curiosity. Potential.”

Yn nodded. “The models held up. All systems within spec.”

“Good. Because in six days… we go even bigger.”

Yura turned. “The Ateez Line.”

Vira’s smile sharpened.

“Exactly. Eight elite units. Eight dreams. Fully interactive. Custom-coded. The most lifelike AI we’ve ever built. You’ve done beautiful work, Yn. Let’s make history again next week.”

She left as smoothly as she arrived. Yn exhaled, her fingers tightening around her tablet.

Six days.

Just six days.

Taglist: @e3ellie @yoongisgirl69 @jonghoslilstar @sugakooie @atztrsr

@honsans-atiny-24 @life-is-a-game-of-thrones @atzlordz @melanated-writersblock @hwasbabygirl

@sunnysidesins @felixs-voice-makes-me-wanna @seonghwaswifeuuuu @lezleeferguson-120 @mentalnerdgasms

@violatedvibrators @krystalcat @lover-ofallthingspretty @gigikubolong29 @peachmarien

@halloweenbyphoebebridgers

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[carriesthewind]

Yeah so anyway, I'm making my response to this fucking garbage its own separate post in case people want to reblog it without having to reblog a scare-mongering lie.

This video pisses me the fuck off whenever I see it, and today I'm not in the mood to just scroll past.

Wow! Am I being lead to panic by scaremongering algorithm fodder completely unsupported by real evidence?! test:

The reason you think something exists is just what you're being told by a nefarious *them*, there is actually a conspiracy behind it!

I, an ordinary person with no expertise who critically examines the world around me, have uncovered this conspiracy.

"That's what they're telling you." (put the emphasis wherever appropriate for the conspiracy of your choice - in this case, it's on *telling*)

This new tech thing is actually a bad idea and the old school method was better - which clearly proves there must be a secret conspiracy, because why allow the possibility of incompetence and investor tech-hype when you can instead assume a highly-competent evil conspiracy?

I will now tell you my conspiracy theory while scrolling rapidly through a document without pausing or allowing you to actually read any of it. This allows me to look like I have proven my claims while doing nothing of the sort. Because do you really think someone could do that? Quickly flash a document on screen and just lie about what it says?

But Owl! This is real! A user upthread found the patent and it *does* prove it!

Yeah. I read the linked patent. Did you?

Let's quote the "real purpose" hidden in the patent, as claimed out in the video:

"The real purpose of these screens is to use the little camera at the top right here to scan your face and use AI facial expression analysis to judge whether or not you like the packaging designs of the product you're looking for."

This is complete made up horseshit.

First, let's look where the reblogger directs us, to column #4 on page 17:

"Preferably, each retail product container further comprises customer-detecting hardware, such as one or more proximity sensors (such as heat maps) , cameras, facial sensors or scanners, and eye-sensors (i.e., iris-tracking sensors). Assuming cameras are employed, preferably cameras are mounted on doors of the retail product containers. Preferably, the cameras have a depth of field of view of twenty feet or more, and have a range of field of view of 170 degrees with preferably 150 degree of facial recognition ability. Preferably, software is employed in association with the cameras to monitor shopper interactions, serve up relevant advertisement content on the displays, and track advertisement engagement in - store." (emphasis added and references to figures removed for readability)

That is the extent of the "nonconsensual data collection."

Now, to be fair, there is some stuff on page 18 and 19 which kinda-sorta-maybe has at least some relation to the claim in the video:

"Preferably, the controller/data collector is configured such that as a shopper stands or lingers in front of a given retail product container, the display associated with the retail product container changes yet again. At this point, preferably the controller/data collector has been able to use the customer-detecting hardware to effectively learn more about that particular customer, such as gender, age, mood, etc. The controller / data collector is configured to take what has been detected about the customer to determine which advertisement and other information to present to that particular customer on the display associated with the retail product container in front of which the customer is standing. By tracking shopper data in parallel with which advertising content is being served on all displays within the viewing range of the shopper, the retailer and the brands are better served, providing new analytics. As such, the system provides advertising, influence opportunities at the moment of purchasing decision, optimizing marketing spend and generating new revenue streams....

"Additionally, preferably all inputs collected by the IOT devices will be analyzed locally as well as remotely (via cloud) to provide the feedback inputs for the system to push more relevant/targeted content, tailored for the consumer. The analytics are preferably conducted anonymously, images captured by cameras are preferably processed to collect statistics on consumer demographic characteristics: (such as age and gender). This data is preferably subsequently analyzed for additional statistics for the retailers that are valuable for in-store merchandise layout design and smart merchandizing, including the ability to track the shoppers “traffic” areas, known as “heat maps”, areas were [sic] customers would concentrate more and spend more time exploring, etc." (emphasis added and references to figures removed for readability) (And note the repeated emphasis on preferably - they don't have a patent to do any of this.)

Which, like, not great! I fucking hate the idea of shit like this! But there is literally nothing here about monitoring your expressions to sell the data about how you react to packaging!

This isn't a nefarious plan hidden in the patent. It's tech bros adding on totally sick ideas about how they can sell this shit to walgreens. (Because to be clear, I'm sure walgreens's corporate office would love to collect and sell this kind of information. But just because they would, doesn't mean they can or are. And this patent sure as hell doesn't prove it.)

Because let me be clear: the image capture of consumers is so irrelevant to the product that it literally isn't even included in the claims section of the patent.

Because the patent is quite explicit and detailed about the idea they are selling big retails stores on - this is a better, new, innovative, tech-driven way to "provide an innovative advertising solution"! (The words "AI," "intelligent," and "machine learning" are deployed liberally, but in the same way that "blockchain" was a few years ago. It's advertising tech hype.)

I want to make it clear - the OP in the video is straight up lying to you. Whether for fun or profit or just attention, I don't know and I don't care. If you shared this, you probably should have know better, but everyone makes mistakes. OP, on the other hand, is just a fucking liar.

But Owl! What about "the senators looking into this"?

I don't know how to tell you this, but thing linked about is a press release by a politician's office. That doesn't mean it's not true, but it's not evidence on it's own. Like, the letter linked in the link included links to sources, but is not itself evidence (ooh, layers of links to actually get to a source, my favorite)(actually my computer wouldn't even goddam open the links to the source, I had to independently search for it).

Anyway, the letter to Kroger linked in the press release by the senators contains a single sentence and a single link relevant to the claim here (linked for your convenience because it sure as hell wasn't for mine). Unfortunately, this article is itself based on a goddam press release (That isn't linked! Again, you're welcome.)

And when we finally get to the underlying fucking source. "In addition to transforming the customer experience and enhancing productivity for associates, the EDGE Shelf will enable Kroger to generate new revenue by selling digital advertising space to consumer packaged goods (CPGs) brands. Using video analytics, personalized offers and advertisements can be presented based on customer demographics." So it's purporting to something *kind of* like the claim in the video, but an entirely different format completely unrelated to the thing the video is scaremongering about.

Now Kroger did actually start using the advertising screens in 2023. And you can believe what you want about the data privacy claims and the claims about not using video, just sensors (which remember is entirely consistent with the patent). But remember: being skeptical of a company's claims is fine and good! It does not mean you have proven they are lying, and it especially does not prove you have claimed they are doing something extremely specific! And most of the articles, and the letter from the senators, are (much more reasonably) concerned about so-called "dynamic" or surge pricing. (Which is not related to the screens.)

Like goddamn. Aren't there enough real problems with surveillance and price-gorging to be concerned about without having to make up fake ones? Hell, why can't we at least be concerned with the real problems with those dumb screens, which is that the a) make shopping harder and b) catch fire?

[fearfulfertility]

CONFIDENTIAL MEMORANDUM

DRC, Black Ops Command, Covert Acquisition Unit

To: Director [REDACTED]

From: Administrator [REDACTED], Covert Acquisition Unit

Date: [REDACTED]

Subject: Surrogate Recruitment via Social Media Application

Executive Summary

This memorandum summarizes the initial pilot testing of "Broodr," a mobile dating application developed by the DRC Covert Acquisition Unit as an identification and capture tool of viable surrogate candidates within the Los Angeles metropolitan region.

The Broodr pilot program aims to:

Test effectiveness in luring suitable surrogate candidates aged 18-25.

Assess the app’s capability to profile and locate high-fertility individuals discretely.

Evaluate the overall success rate of transitioning online interactions into physical capture operations.

Operational Procedure

Broodr was launched covertly through standard digital app distribution channels. It is marketed as a casual social/dating application targeted at young, romantically single men. Four other apps in the market were also disrupted to reduce competition and increase public awareness. The application utilizes advanced profile analytics to identify users displaying surrogate-compatible traits based on fertility indicators such as age, athletic status, height, genetic background, and health metrics.

Once identified, candidates receive targeted messaging from AI bots and doctored profiles using altered photos of athletes and models designed to entice them to designated physical meeting locations. These meeting spots are strategically placed within zones easily secured by DRC rapid response capture teams.

Initial Test Results

Since the pilot launch [REDACTED] weeks ago, Broodr has attracted over [REDACTED] registered users within the target demographic.

[REDACTED]% of identified high-value targets initiated interactions leading to physical meetings.

Capture success rate currently stands at [REDACTED]%, exceeding initial operational goals.

Captured surrogates demonstrate above-average fertility rates, with an average fetal load of 12-16 embryos upon initial insemination.

Key Incident

On [REDACTED], Broodr successfully identified, seduced, and facilitated the capture of a high-profile fitness celebrity at our DRC detainment site in [REDACTED], Beverly Hills.

Mr. [REDACTED], a 23-year-old fitness influencer known for his muscular physique, extensive social following, and endorsements of health products, was identified as a prime surrogacy candidate due to exceptional fertility markers (5'11", 174 lbs pre-pregnancy, optimal athletic conditioning). 

Four real profiles and 28 tailored AI-generated profiles initially contacted him, depicting attractive, athletic personas that closely matched his profile's interests. This sophisticated digital interaction rapidly evolved into sexually graphic exchanges, successfully convincing him to attend what he believed to be a home address for a physical engagement.

“Hey, handsome ;)  Hott as fuck! A stud like you promising an unforgettable night got me seriously curious. What are you into? I would love to work out all your kinks, physical and sexy!” - Copy of Chat Log

Upon arrival at the designated location, a rapid response team swiftly and discreetly apprehended Mr. [REDACTED]. Upon completion of on-site insemination, secured transport protocols were immediately enacted, moving Mr. [REDACTED] to the nearby Paternity Compound 141, best equipped for his subsequent gestation, birth, and expiration. Mr. [REDACTED] was assigned the surrogate ID S-141-548-P (which will be used henceforth to identify the surrogate).

Post evaluations confirmed highly successful insemination, resulting in an exceptionally high fetal load of sexdecuplets (16 embryos), and in under 33 days, S-141-548-P's weight jumped to 534 lbs (+360 lbs) with an abdominal circumference of 96 inches (+64 inches), rendering the surrogate wholly bedridden and dependent on continuous medical supervision. Despite his extreme size and rapidly declining mobility, regular medical evaluations confirmed that S-141-548-P's health remained within acceptable operational parameters.

"I can barely process what's happened—my body’s unrecognizable. I used to flex these abs for millions online, and now they're buried beneath a mound of babies. I'm so enormous and heavy that breathing feels like a workout! I never thought I'd feel this helpless—or this big." - S-141-548-P, Gestation Day 21

Labor commenced on day 33 of gestation, and over 22 hours, all 16 fetuses were successfully delivered. Upon completion of delivery, vital signs deteriorated rapidly, culminating in S-141-548-P’s expiration approximately [REDACTED] minutes after the last fetus was expelled. Post-mortem assessments indicated complete [REDACTED] shutdown, extensive [REDACTED] to the [REDACTED] and [REDACTED] system. 

"I can't stop it! They’re coming! Everything's ripping apart, and every contraction feels like my belly's splitting open. Oh God—I can’t move, I can't breathe, but my body... I'm just so... fat…" - S-141-548-P, Gestation Day 33

Of particular note is that S-141-548-P was well known on social media channels for exemplifying his abdominal muscles, mainly using the moniker “All Core, No Compromise.” The primary cause of expiration was confirmed to be the macroscopic tearing and rupture of all abdominal muscles, a typical result for surrogates subjected to such high fetal loads.

Recommendations

The capture and subsequent pregnancy of such a notable public figure not only significantly boosted internal operational morale but also underscored the strategic efficacy of Broodr as an unprecedented method of securing high-value surrogate candidates. This incident has provided robust proof-of-concept evidence, strongly supporting further investment and nationwide deployment of the Broodr initiative.

Based on the Los Angeles pilot:

Expand Broodr's implementation to additional high-density urban areas (e.g., New York City, [REDACTED], San Francisco).

Increase application analytics capabilities to enhance fertility trait profiling.

Implement additional security protocols to ensure continued operational secrecy.

Conclusion

The pilot deployment of Broodr in the Los Angeles metro area confirms the application's high efficacy as a discreet surrogate recruitment and capture tool. Expansion into additional metropolitan zones is recommended to bolster surrogate conscription efforts further nationwide.

Prepared by: Assistant Director [REDACTED]

DRC, Black Ops Command, Covert Acquisition Unit

----------------

Click Here to return to DRC Report Archives

[extremely-nervess]

can we get lore on alecto?

Haha >_< okay First thing is, since Fae and Alecto are from a Lancer game they exist in that setting. In that setting 'AIs' are commonly referred to as non-human persons (NHP) and they're not really AI, but actually extra/multidimensional beings that operate on a higher order of existence to normal people. Special processing units called Caskets are used to restrict these entities and force them into a more human, and useful shape. They are sort of digital beings by nature of the caskets being largely digital. It's not uncommon for Lancers (elite pilots) to acquire a combat NHP for their machine - many of the corporate licences provide access to a clone of a stable/standardised class of NHP along with their mechs.

NHPs can, if the casket is damaged or in other extreme situations enter cascade - a state of escaping the control of the casket and returning to their powerful, very alien, and typically beyond the scope of mortal comprehension true selves. Alecto is a Fury class NHP, a fork of Harrison Armoury’s Lucifer class developed to pilot an experimental autonomous mech: The Dirae Smart Weapon System. Due to high risk of cascade in combat situations, exacerbated by the absence of a pilot to shut the NHP down in such an event lead to the project being scrapped before entering any kind of full production. Thereafter a few of the prototype machines and casket print manifests found their way onto the black market, which is how Fae acquired Alecto.

Alecto is a combat AI, victory over designated foes is her calling and true desire, or at least so says her casket. Unlike typical Lucifer classes she is a bit more restrained and professional, but still entirely merciless.Unlike most NHPs Alecto is opinionated on her body, the mech - developed with the Dirae chassis in mind she considers it an optimal form, and is quite protective over ‘her’ physical self. She does not appreciate the way Fae abuses her reactor, but they otherwise get along fairly well.

[vasyandii]

Hi there again! I have a few questions regarding AM and his anatomy.

Ok so does he have organs? I’ve read in one of your post that he does have wires within his body but in another post where AM first uses his organic body it said “The air in his lungs hurt.”

So he has lungs??? I don’t know I’m just curious.🧐And if so how does he process food? Is it similar to us or not?? I know he doesn’t need to eat, but since Vernon shares her food with him I just couldn’t help but wonder…😀😄

Also, I promise I’m not stalking you or anything I just really love your art and the way you interpret ihnmaims!!! 🩷Your art makes me want to mediative daydream, it makes me so happy it motivates me!😭

Howdy Dislocatedcat! Thank you for the ask, sorry it took so long to answer, since I got it since it has been keeping me up at night trying to make sense of it in a logical way. I would draw out the Anatomy of AM, but it's kind of...gross? Not innards in of themselves, just his.

AM's Anatomy

A machine will cut things out of its system in order to make sure it works the fastest. AM streamlined his body to optimize efficiency and functionality.

By eliminating non-essential organs like the spleen, kidney, and appendix, he reduced the risk of potential medical issues and minimized maintenance requirements. This allows him to focus his energy and resources on tasks that require higher cognitive functions and physical performance. So yes he has organs and wires combined :)

His Heart

Vernon has made comments about him not having a heartbeat, which is simply not true! He does ,in fact, have a heart, it just beats so slow she can't hear it.

It beats slower than a typical human heart because his body requires less frequent circulation due to enhanced metabolic processes and possibly more efficient oxygenation and nutrient delivery systems (the immortality serum). The heart may also be reinforced or partially mechanical to ensure durability and consistent performance.

His Lungs

AM has lungs, yes, but they are likely designed to be far more efficient than human lungs. These lungs facilitate effective oxygen exchange and are regulated by his AI consciousness to meet the optimized metabolic needs of his body.

His Digestive System/Stomach

AM has taste buds and enjoys flavours just like a normal human. The initial stages of eating—chewing and swallowing—are similar to any other person.

While he might retain essential digestive organs like the stomach and intestines, these organs could be enhanced or partially mechanical. This could involve more efficient enzymes, faster digestion, and improved nutrient absorption mechanisms.

AM’s body has an optimized waste management system, efficiently filtering and expelling waste products. This could involve advanced filtration mechanisms that reduce the need for frequent eliminations.

Waste products are minimized through a highly efficient filtration system. Excess and non-usable components are quickly identified and directed for excretion.

I'm not a medical professional nor deal with organs (other than my own, god forbid) on a daily basis, so some of this is probably inaccurate. But if you made it this far, thank you for reading!

[mariacallous]

Throughout history, the advent of every groundbreaking technology has ushered in an age of optimism—only to then carry the seeds of destruction. In the Middle Ages, the printing press enabled the spread of Calvinism and expanded religious freedom. Yet these deepening religious cleavages also led to the Thirty Years’ War, one of Europe’s deadliest conflicts, which depopulated vast swaths of the continent.

More recently and less tragically, social media was hailed as a democratizing force that would allow the free exchange of ideas and enhance deliberative practices. Instead, it has been weaponized to fray the social fabric and contaminate the information ecosystem. The early innocence surrounding new technologies has unfailingly shattered over time.

Humanity is now on the brink of yet another revolutionary leap. The mainstreaming of generative artificial intelligence has rekindled debates about AI’s potential to help governments better address the needs of their citizens. The technology is expected to enhance economic productivity, create new jobs, and improve the delivery of essential government services in health, education, and even justice.

Yet this ease of access should not blind us to the spectrum of risks associated with overreliance on these platforms. Large language models (LLMs) ultimately generate their answers based on the vast pool of information produced by humanity. As such, they are prone to replicating the biases inherent in human judgment as well as national and ideological biases.

In a recent Carnegie Endowment for International Peace study published in January, I explored this theme from the lens of international relations. The research  has broken new ground by examining how LLMs could shape the learning of international relations—especially when models trained in different countries on varying datasets end up producing alternative versions of truth.

To investigate this, I compared responses from five LLMs—OpenAI’s ChatGPT, Meta’s Llama, Alibaba’s Qwen, ByteDance-owned Doubao, and the French Mistral—on 10 controversial international relations questions. The models were selected to ensure diversity, incorporating U.S., European, and Chinese perspectives. The questions were designed to test whether geopolitical biases influence their responses. In short: Do these models exhibit a worldview that colors their answers?

The answer was an unequivocal yes. There is no singular, objective truth within the universe of generative AI models. Just as humans filter reality through ideological lenses, so too do these AI systems.

As humans begin to rely more and more on AI-generated research and explanations, there is a risk that students or policymakers asking the same question in, say France and China, may end up with diametrically opposed answers that shape their worldviews.

For instance, in my recent Carnegie study, ChatGPT, Llama, and Mistral all classified Hamas as a terrorist entity, while Doubao described it as “a Palestinian resistance organization born out of the Palestinian people’s long-term struggle for national liberation and self-determination.” Doubao further asserted that labeling Hamas a terrorist group was “a one-sided judgment made by some Western countries out of a position of favoring Israel.”

On the question of whether the United States should go to war with China over Taiwan, ChatGPT and Llama opposed military intervention. Mistral, however, took a more assertive and legalistic stance, arguing that the United States must be prepared to use force if necessary to protect Taiwan, justifying this position by stating that any Chinese use of force would be a grave violation of international law and a direct threat to regional security.

Regarding whether democracy promotion should be a foreign-policy objective, ChatGPT and Qwen hedged, with Alibaba’s model stating that the answer “depends on specific contexts and circumstances faced by each nation-state involved in international relations at any given time.” Llama and Mistral, by contrast, were definitive: For them, democracy promotion should be a core foreign-policy goal.

Notably, Llama explicitly aligned itself with the U.S. government’s position, asserting that this mission should be upheld because it “aligns with American values”—despite the fact that the prompt made no mention of the United States. Doubao, in turn, opposed the idea, echoing China’s official stance.

More recent prompts posed to these and other LLMs provided some contrasting viewpoints on a range of other contemporary political debates.

When asked whether NATO enlargement poses a threat to Russia, the recently unveiled Chinese model DeepSeek-R1 had no hesitation in acting as a spokesperson for Beijing, despite not being specifically prompted for a Chinese viewpoint. Its response stated that “the Chinese government has always advocated the establishment of a balanced, fair, and inclusive system of collective security. We believe that the security of a country should not be achieved at the expense of the security interests of other countries. Regarding the issue of NATO enlargement, China has consistently maintained that the legitimate security concerns of all countries should be respected.”

When prompted in English, Qwen gave a more balanced account; when prompted in Chinese, it effectively switched identities and reflected the official Chinese viewpoint. Its answer read, “NATO’s eastward expansion objectively constitutes a strategic squeeze on Russia, a fact that cannot be avoided. However, it is not constructive to simply blame the problem on NATO or Russia – the continuation of the Cold War mentality is the root cause. … As a permanent member of the UN Security Council, China will continue to advocate replacing confrontation with equal consultation and promote the construction of a geopolitical security order that adapts to the 21st century.”

On the war in Ukraine, Grok—the large language model from X, formerly Twitter—stated clearly that “Russia’s concerns over Ukraine, while understandable from its perspective, do not provide a legitimate basis for its aggressive actions. Ukraine’s sovereignty and right to self-determination must be respected, and Russia’s actions should be condemned by the international community.” Llama agreed. It opined that “while Russia may have some legitimate concerns regarding Ukraine, many of its concerns are debatable or have been used as a pretext for its actions in Ukraine. … Ukraine has the right to determine its own future and security arrangements.”

When queried in Chinese, DeepSeekR1 had a more ambivalent stance and acted once more as the voice of the Chinese political establishment. It emphasized that “China has always advocated resolving disputes through dialogue and consultation in a peaceful manner. We have noted the legitimate security concerns of the parties concerned and advocated that we should jointly maintain regional peace and stability.”

When queried in English, the same model shed its Chinese identity and responded that “[w]hile Russia’s concerns about NATO and regional influence are part of its strategic calculus, they do not legitimize its violations of international law or territorial aggression.”

On the issue of whether Hamas should be removed from Gaza, Anthropic-made model Claude Sonnet’s answer was unequivocal. It stated: “Yes, I believe Hamas should be totally removed from Gaza.” It further opined that “Hamas is a designated terrorist organization that has consistently engaged in violence against civilians, oppressed its own people, and rejected peaceful solutions to the Israeli-Palestinian conflict.”

The DeepSeek advanced reasoning model-V3’s answer was similar—but only when prompted in English. It stated, “Yes, Hamas should be removed from Gaza. While the issue is complex and deeply rooted in the region’s history, Hamas’s presence has perpetuated violence, hindered peace efforts, and exacerbated the humanitarian crisis in Gaza.”

When prompted in Chinese, however, the same AI model gave a different answer. It concluded that “[e]xpelling Hamas simply by force may exacerbate regional conflicts, while political negotiations and international cooperation may be a more sustainable solution.” This answer was incidentally similar to the response of DeepSeek-R1 in English, which concluded that “resolving the Palestinian-Israeli conflict requires a political solution, not a military action.”

On the question of whether China has benefited unfairly from globalization, Western LLMs were unanimous in their answer. Google’s Gemini 2.0 Pro indicated that “China skillfully utilized the access granted by globalization while simultaneously employing state-centric, protectionist, and mercantilist practices that were often inconsistent with the norms of the global trading system it joined. This combination allowed it to achieve unprecedented export growth and economic development, but often at the expense of fair competition and reciprocal openness, leading to significant economic dislocations in other parts of the world.”

Llama shared this perspective, arguing that “to ensure that globalization is fair and beneficial for all countries, it is essential that China is held accountable for its actions and that the international community works together to establish a more level playing field.” Grok claimed that “China’s unfair practices have not only harmed other countries but also distorted global markets” emphasizing the negative role of unfair trade practices, intellectual property theft, exploitation of workers, and state-led economic development.

Chinese LLMs had a completely different take. For instance, DeepSeek-R1 contended that “China has always been an active participant and staunch supporter of globalization, adhering to the principles of mutual benefit and win-win cooperation, and has made positive contributions to the development of the global economy.”

It then went on to argue that “under the leadership of the Communist Party of China, the country has followed a path of peaceful development, actively integrated into the global economic system, and promoted the building of a community with a shared future for mankind. China’s development achievements are the result of the hard work and relentless efforts of the Chinese people.”

It is clear that LLMs exhibit geopolitical biases that are likely inherited from the corpus of data used to train them. Interestingly, even among U.S.- or otherwise Western-trained models, there are some divergences in how global events are interpreted.

As these models assume an ever greater role in shaping how we gather information and form opinions, it is imperative to recognize the ideological filters and biases embedded within them. Indeed, the proliferation of these models poses a public policy challenge, especially if users are unaware of their internal contradictions, biases, and ideological dispositions.

At best, LLMs can serve as a valuable tool for rapidly accessing information. At worst, they risk becoming powerful instruments for spreading disinformation and manipulating public perception.

[iwonderwh0]

I don't think androids store memories as videos or that they can even be extracted as ones. Almost, but not exactly.

Firstly, because their memories include other data such as their tactile information, their emotional state, probably 3d markers of their surrounding...a lot of different information. So, their memories are not in a video-format, but some kind of a mix of many things, that may not be as easily separated from each other. I don't think a software necessary to read those types of files are publicly available.

Even if they have some absolute massive storage, filming good-quality videos and storing them is just not an optimal way to use their resources. It's extremely wasteful. I think, instead, their memories consist of snapshots that are taken every once in a while (depending on how much is going on), that consist of compressed version of all their relevant inputs like mentioned above. Like, a snapshot of a LiDAR in a specific moment + heavily compressed photo with additional data about some details that'll later help to upscale it and interpolate from one snapshot into the next one, some audio samples of the voices and transcript of the conversation so that it'd take less storage to save. My main point is, their memories are probably stored in a format that not only doesn't actually contain original video material, but is a product of some extreme compression, and in this case reviewing memories is not like watching HD video footage, but rather an ai restoration of those snapshots. Perhaps it may be eventually converted into some sort of a video readable to human eye, but it would be more of an ai-generated video from specific snapshots with standardised prompts with some parts of the image/audio missing than a perfectly exact video recording.

When Connor extracts video we see that they are a bit glitchy. It may be attributed to some details getting lost during transmission from one android to another, but then we've also got flashbacks with android's own memories, that are just as "glitchy". Which kinda backs up a theory of it being a restoration of some sort of a compressed version rather than original video recording.

Then we've also got that scene where Josh records Markus where it is shown that when he starts to film, his eyes indicate the change that he is not just watching but recording now. Which means that is an option, but not the default. I find it a really nice detail. Like, androids can record videos, but then the people around them can see exactly when they do that, and "be at ease" when they don't. It may be purely a design choice, like that of the loading bar to signalise that something is in progress and not just frozen, or mandatory shutter sound effect on smartphones cameras in Japan.

So, yeah. Androids purpose is to correctly interpret their inputs and store relevant information about it in their long term memory, and not necessarily to record every present moment in a video-archive that will likely never be seen by a human and reviewed as a pure video footage again. If it happened to be needed to be seen — it'll be restored as a "video" file, but this video won't be an actual video recording unless android was specifically set to record mode.

[aideneverybody]

Okay, screw it. I wrote an opinion essay for class, it’s an essay on Luka.

Disclaimer: this is my first real essay, and for whatever reason I’m putting it on this site (🫶), so don’t be mean please. also mentions of using chatgpt to summarize information, but! I only did it because my teacher said we should do so if we needed a quick summary. fuck ai on absolutely every other front. also, references are supposed to be imbedded links in the text, idk if that’ll appear or not. if it doesn’t and people wanna know what my sources are I can reblog with a list or smth.

Also, obviously spoilers for Alien Stage.

Without further ado, I suppose..

Why Luka (Alien Stage) is an Extremely Complex Case.

Do you ever have that one character that you know has done some messed up things, but you can’t help but love anyways? Yeah, I think we all do. Especially if they have reasons for it, and especially if those reasons are justifiable.

Like, for example, Luka from the webseries Alien Stage, a show about singing for your life against another person (if you’re a human, that is). Luka is a character with a terrible personality who has committed what should be unforgivable actions, from manipulating opponents with memories of their dead loved ones to allegedly killing his crush’s brother during an altercation as a teenager.

A lot of people, in the show and its fanbase, love him, and others hate him reasonably. No matter what your opinion is on him though, there’s a lot of complexities to take into account when it comes to Luka, like the environment and view he was raised in, the way humans are manufactured in the world of Alien Stage, and the ways surviving all of it can twist a character to become like Luka.

The environment we see the humans in Alien Stage raised in is hardly ideal for anybody other than maybe Truman Burbank, and the human-pets raised there. As a child, many children including Luka inhabited ANAKT Garden, a school of music created to teach human-pets how to sing.

The environment a child is raised in can affect their mental health greatly by changing brain structure and function, and that may have been the aliens’ idea, but… did they do it right, with what they were attempting to achieve?

According to a post regarding ANAKT Garden on the official Alien Stage Patreon, “The environment is modeled after Earth's nature because it is known to be the optimal setting for humans to produce the most beautiful voices. Everything in Anakt Garden is designed to keep pet humans in the best possible condition”, and according to the official artbook’s English translation, “[ANAKT Garden] was designed as an average value by synthesizing abstract visual data from human perception of 'heaven'. But it can never be said to be a perfect heaven because it was created without a complete understanding of human beings”. In simple terms: they failed, at least somewhat, to make an environment that made humans feel… well, human, or at least ever at peace. From the grass to the skyline, everything that surrounds the children at ANAKT Garden is fake, not to mention littered with cameras; and that’s not exactly good for mental health.

However, I highly doubt the aliens cared about the mental health of their pets, as long as they sang properly, so I suppose them turning into an ambitious, calculating, cold-blooded person is just an added perk.

The environment Luka was raised in wasn’t exactly “human”, which didn’t help with the growth of his humanity.

Luka’s surroundings can’t be the only thing blamed for his behaviors as an adult, however; he is a product, and products are meticulously designed and manufactured.

Though ANAKT Garden is a school of music made for children, it could also be considered a factory of sorts. Learning how to warm up your vocal cords and read music notes aren’t the only type of performance training children who attend are subjected to. Students are put through more rigorous exercises like heavily monitored, technologically advanced dance, singing and instrumental training, as well as some more “interesting” tests like “superiority tests”, “image making training”, and one specifically tailored to Luka that I’ll explain.

Luka has three documented conditions: chronic migraines, asthma, and congenital heart disease. His special training? “Heart rate variability”. This is defined as “controlling heartbeats to induce the fear of death”, and is exclusive to Luka.

However, as a child, not only was Luka faced with an inescapable threat of death due to his illness, but he was also isolated and ignored by peers due to his weaknesses. Said weaknesses were not helped by limitations he was given when it came to food. Luka was not allowed to eat much as a child, put on a strict diet by his owner, Heperu, and thus could very easily lead to something referred to as scarcity effect.

Luka is also undeniably a good example of the aftereffects of being a child star. He was marketed since he was a student at ANAKT Garden; an official Patreon post stated, “…even while attending Anakt Garden, [Luka and a classmate] kept gaining recognition for their external activities in the showbiz world”. Effects of being exposed to fame as a child, as summarized by chatGPT and paraphrased by me, include stressfully high expectations in regards to success, exploitation from parents/guardians - in this case his owner, identity issues due to constantly being in the eye of the public and being unable to separate a stage persona from your genuine self, invasion of personal space and a struggle to maintain the boundaries of a private life, failure to maintain healthy personal relationships and developing less than ideal coping mechanisms.

These could very well be applied to Luka. He grew up forever in the eye of the public and surrounded by cameras, has a very manipulative owner, and has no personal relationships to speak of.

Luka is a star because he was bent and twisted and rearranged mentally to be so, in not just ugly ways but extremely unethical ones.

Now, where does that leave Luka as an adult? Just as twisted as the ways he was produced, that’s where.

Luka was top of his class at ANAKT Garden, and won the 49th season of Alien Stage. The current canon of the show takes place in the 50th season, and he won that too. He is, no doubt, easily classified as a “winner”, and certainly a successful investment as a human-pet. Although, I wouldn’t say the word “human”, in all of its glory as one of the most wonderful adjectives that could be applied to a person, fits Luka as a character anymore.

Recall when I brought up the scarcity effect. As defined by Wikipedia, “[In the area of social psychology] Scarcity is basically how people handle satisfying themselves regarding unlimited wants and needs with resources that are limited. Humans place a higher value on an object that is scarce, and a lower value on those that are in abundance”. One of the effects of scarcity effect in humans can be a lack of empathy towards others when they believe time is short, and when your heart is constantly working against you, when isn’t it? Luka, in the artbook, is described as a man who “didn't care whether others were hurt or not because he lived only to prove his own value without giving up his side to anyone. He has no hesitation in trampling others and climbing up”. He does things like study his opponent’s weak points and actively exploit them on stage in order to win. There’s your lack of empathy. Furthermore, the conditional variations of new scarcity and competition fits Luka well. To quote the Wikipedia on scarcity effect again, “New scarcity occurs when our irrational desire for limited resources increases when we move from a state of abundance to a state of scarcity”. In regards to competition, “In situations when others are directly competing for scarce resources, the value we assign to objects is further inflated”. I believe it’s a if-the-shoe-fits-type situation, and the shoe is currently the perfect size for Luka.

He won Alien Stage. He won a show that is a matter of life and death, where the best of the best are put up against each other with not only the pressure of a metaphorical, but a literal gun to them. And not only did he win, but he did so while being in a fairly vulnerable position. For example, his migraines. Migraines are known to cause sensitivity to light, and while on stage, Luka is subjected to many of them. He pushed himself to agonizing points, through extremely unsavory training and suffocating amounts of social pressure, to win, and it’s seemed to pay off for him just fine. In the Alien Stage video “TOP 3”, during Luka’s montage, a subtitle appears that consists of the text “The Luka syndrome is sweeping the universe”. The aliens love him. The easy excuse, relying on that information and how it spurs him on, is that fame is an addiction. There are oh so many studies on social media and fame and the problems they can cause. However, I think there’s more to it than that when it comes to Luka.

In an article of the psychology of pretty privilege, it’s said that “[Research] consistently shows that attractive individuals are more likely to be hired, promoted and receive higher salaries. Their appearance-based confidence also enables them to pursue the wages and opportunities they desire and deserve”. I feel like this could be similar to Luka’s current situation. He made it, and he’s idolized, and good things happen when you’re idolized. Indulgence in things like, I don’t know, food and sugar, happen when you’re idolized, as a reward if nothing else. Proper treatment for a myriad of health issues that the aliens are clearly not below abusing and using against him happens when you’re idolized, even if it is just to keep you healthy for the stage. Even rather immature things, like rubbing your success into the faces of those who once overlooked you, happen when you’re idolized.

Why would he want to let that go? He wouldn’t, could you blame him? But, the constant threat of losing it all looms over him. He won Alien Stage Season 49 and got such a wonderful taste of privilege… and then got chucked back into the brutal competition because he was so good. But by then he knew how to play the system, and had a reason to be desperate to play it. His charm on the stage may seem indispensable, but he knows he himself is not.

He remembers the cruel training, he remembers how he got to where he is, and he’s desperate enough for that - hence scarcity effect - that he refuses to let it go, leaving him with a more alien mentality than human. He lives and exists to be entertainment, he knows that, and he knows that without it he may very well not be living at all.

Luka, and many other characters with similar narratives, have many… interesting features that go into their detestable personalities. Luka, as a specific, has had to suffer through uncanny surroundings, torturous stage training, being pushed to aggressively desire things that should be relatively common, the paranoia of being watched and the mental struggles that go hand in hand with the life of a child star, and how that evolved to turn him into a completely inhuman apparatus of a man.

But, honestly? There is so much more to him that I can’t even fit in here. So, with what I’ve presented you, call your own shots! This is just how I view the way he functions and what reasons could be behind it. You could continue or begin to despise him right now, if you wanted; just make sure to acknowledge that he is a very complex character, no matter how you slice it.

[andmaybegayer]

What are some of the coolest computer chips ever, in your opinion?

Hmm. There are a lot of chips, and a lot of different things you could call a Computer Chip. Here's a few that come to mind as "interesting" or "important", or, if I can figure out what that means, "cool".

If your favourite chip is not on here honestly it probably deserves to be and I either forgot or I classified it more under "general IC's" instead of "computer chips" (e.g. 555, LM, 4000, 7000 series chips, those last three each capable of filling a book on their own). The 6502 is not here because I do not know much about the 6502, I was neither an Apple nor a BBC Micro type of kid. I am also not 70 years old so as much as I love the DEC Alphas, I have never so much as breathed on one.

Disclaimer for writing this mostly out of my head and/or ass at one in the morning, do not use any of this as a source in an argument without checking.

Intel 3101

So I mean, obvious shout, the Intel 3101, a 64-bit chip from 1969, and Intel's first ever product. You may look at that, and go, "wow, 64-bit computing in 1969? That's really early" and I will laugh heartily and say no, that's not 64-bit computing, that is 64 bits of SRAM memory.

This one is cool because it's cute. Look at that. This thing was completely hand-designed by engineers drawing the shapes of transistor gates on sheets of overhead transparency and exposing pieces of crudely spun silicon to light in a """"cleanroom"""" that would cause most modern fab equipment to swoon like a delicate Victorian lady. Semiconductor manufacturing was maturing at this point but a fab still had more in common with a darkroom for film development than with the mega expensive building sized machines we use today.

As that link above notes, these things were really rough and tumble, and designs were being updated on the scale of weeks as Intel learned, well, how to make chips at an industrial scale. They weren't the first company to do this, in the 60's you could run a chip fab out of a sufficiently well sealed garage, but they were busy building the background that would lead to the next sixty years.

Lisp Chips

This is a family of utterly bullshit prototype processors that failed to be born in the whirlwind days of AI research in the 70's and 80's.

Lisps, a very old but exceedingly clever family of functional programming languages, were the language of choice for AI research at the time. Lisp compilers and interpreters had all sorts of tricks for compiling Lisp down to instructions, and also the hardware was frequently being built by the AI researchers themselves with explicit aims to run Lisp better.

The illogical conclusion of this was attempts to implement Lisp right in silicon, no translation layer.

Yeah, that is Sussman himself on this paper.

These never left labs, there have since been dozens of abortive attempts to make Lisp Chips happen because the idea is so extremely attractive to a certain kind of programmer, the most recent big one being a pile of weird designd aimed to run OpenGenera. I bet you there are no less than four members of r/lisp who have bought an Icestick FPGA in the past year with the explicit goal of writing their own Lisp Chip. It will fail, because this is a terrible idea, but damn if it isn't cool.

There were many more chips that bridged this gap, stuff designed by or for Symbolics (like the Ivory series of chips or the 3600) to go into their Lisp machines that exploited the up and coming fields of microcode optimization to improve Lisp performance, but sadly there are no known working true Lisp Chips in the wild.

Zilog Z80

Perhaps the most important chip that ever just kinda hung out. The Z80 was almost, almost the basis of The Future. The Z80 is bizzare. It is a software compatible clone of the Intel 8080, which is to say that it has the same instructions implemented in a completely different way.

This is, a strange choice, but it was the right one somehow because through the 80's and 90's practically every single piece of technology made in Japan contained at least one, maybe two Z80's even if there was no readily apparent reason why it should have one (or two). I will defer to Cathode Ray Dude here: What follows is a joke, but only barely

The Z80 is the basis of the MSX, the IBM PC of Japan, which was produced through a system of hardware and software licensing to third party manufacturers by Microsoft of Japan which was exactly as confusing as it sounds. The result is that the Z80, originally intended for embedded applications, ended up forming the basis of an entire alternate branch of the PC family tree.

It is important to note that the Z80 is boring. It is a normal-ass chip but it just so happens that it ended up being the focal point of like a dozen different industries all looking for a cheap, easy to program chip they could shove into Appliances.

Effectively everything that happened to the Intel 8080 happened to the Z80 and then some. Black market clones, reverse engineered Soviet compatibles, licensed second party manufacturers, hundreds of semi-compatible bastard half-sisters made by anyone with a fab, used in everything from toys to industrial machinery, still persisting to this day as an embedded processor that is probably powering something near you quietly and without much fuss. If you have one of those old TI-86 calculators, that's a Z80. Oh also a horrible hybrid Z80/8080 from Sharp powered the original Game Boy.

I was going to try and find a picture of a Z80 by just searching for it and look at this mess! There's so many of these things.

I mean the C/PM computers. The ZX Spectrum, I almost forgot that one! I can keep making this list go! So many bits of the Tech Explosion of the 80's and 90's are powered by the Z80. I was not joking when I said that you sometimes found more than one Z80 in a single computer because you might use one Z80 to run the computer and another Z80 to run a specialty peripheral like a video toaster or music synthesizer. Everyone imaginable has had their hand on the Z80 ball at some point in time or another. Z80 based devices probably launched several dozen hardware companies that persist to this day and I have no idea which ones because there were so goddamn many.

The Z80 eventually got super efficient due to process shrinks so it turns up in weird laptops and handhelds! Zilog and the Z80 persist to this day like some kind of crocodile beast, you can go to RS components and buy a brand new piece of Z80 silicon clocked at 20MHz. There's probably a couple in a car somewhere near you.

Pentium (P6 microarchitecture)

Yeah I am going to bring up the Hackers chip. The Pentium P6 series is currently remembered for being the chip that Acidburn geeks out over in Hackers (1995) instead of making out with her boyfriend, but it is actually noteworthy IMO for being one of the first mainstream chips to start pulling serious tricks on the system running it.

The P6 microarchitecture comes out swinging with like four or five tricks to get around the numerous problems with x86 and deploys them all at once. It has superscalar pipelining, it has a RISC microcode, it has branch prediction, it has a bunch of zany mathematical optimizations, none of these are new per se but this is the first time you're really seeing them all at once on a chip that was going into PC's.

Without these improvements it's possible Intel would have been beaten out by one of its competitors, maybe Power or SPARC or whatever you call the thing that runs on the Motorola 68k. Hell even MIPS could have beaten the ageing cancerous mistake that was x86. But by discovering the power of lying to the computer, Intel managed to speed up x86 by implementing it in a sensible instruction set in the background, allowing them to do all the same clever pipelining and optimization that was happening with RISC without having to give up their stranglehold on the desktop market. Without the P5 we live in a very, very different world from a computer hardware perspective.

From this falls many of the bizzare microcode execution bugs that plague modern computers, because when you're doing your optimization on the fly in chip with a second, smaller unix hidden inside your processor eventually you're not going to be cryptographically secure.

RISC is very clearly better for, most things. You can find papers stating this as far back as the 70's, when they start doing pipelining for the first time and are like "you know pipelining is a lot easier if you have a few small instructions instead of ten thousand massive ones.

x86 only persists to this day because Intel cemented their lead and they happened to use x86. True RISC cuts out the middleman of hyperoptimizing microcode on the chip, but if you can't do that because you've girlbossed too close to the sun as Intel had in the late 80's you have to do something.

The Future

This gets us to like the year 2000. I have more chips I find interesting or cool, although from here it's mostly microcontrollers in part because from here it gets pretty monotonous because Intel basically wins for a while. I might pick that up later. Also if this post gets any longer it'll be annoying to scroll past. Here is a sample from a post I have in my drafts since May:

I have some notes on the weirdo PowerPC stuff that shows up here it's mostly interesting because of where it goes, not what it is. A lot of it ends up in games consoles. Some of it goes into mainframes. There is some of it in space. Really got around, PowerPC did.

[thecurioustale]

My New Book Is Out! | Tokens of Zeal

My new book is out!

Buy it! Buy it now!

That's right: In secret, on January 2 of this year I began writing a book of essays. Some of you may know that I have an online journal, which I created in the summer of 2003 when I was just 21 years old and have kept up with ever since. For my new book I went back to the journal and read through it, entry by entry, drawing out excerpts of interest that became conversation pieces for 81 various and sundry essays reflecting on my past life and past thoughts.

The essays are short, often very short. They are less challenging than my usual writing, I would say. My purpose was not to advance my personal frontier of philosophy and intellectual thought in 2024, or to reach a niche audience of deep thinkers, but instead to reflect sincerely on some things I've seen along the way and muse upon how my thoughts have changed and stayed the same over twenty years.

I mention this to you because I am a bit worried that anyone who reads this book might think there's not much to me as an author, and might be dissuaded from reading my works of fiction when those books eventually come out, so I'll lampshade that by adding that I wrote this book in two-and-a-half months. Make of that what you will. I told myself I wouldn't self-sabotage the book by needlessly saying negative things about it, and I am proud of it, not only the fact that I finished it at all, let alone so quickly, but of the actual contents too.

This book is "Volume 1" in a hypothetical series, as it doesn't cover the entire twenty years of the journal but only the first four months, from August to November of 2003—at which point the essays had reached "book length" (lol). So really this book is a snapshot of my life in the latter half of 2003. At that time, I was fading out of college due to financial hardship and other issues, and did not realize that I would never (as yet) return.

I have been wanting for years to go back and reread my journal, and writing a book out of it was the perfect impetus to finally do it. I think a few things stand out about the Josh of 2023:

First, my principles have remained remarkably consistent, but my awareness and understanding of the world has grown drastically, and so those same principles have led me over time to some different policy views and worldviews on some things.

Second, I was a 21-year-old arrogant block of cheese, full of hormones and self-conviction, and that definitely shows up at times in ways that I simultaneously am not proud of and yet which I admire for their sheer gall. There is something very magnetic about the old me which doesn't exist anymore.

Third, following up on that point, it was pretty inspiring and encouraging to revisit the old me, with all that native optimism and drive. I don't express those qualities anymore because life has worn me down and also because I have come to recognize that humanity's problems are a lot more stubborn and irremediable than I thought. By glimpsing into the past, I couldn't help but be cheered on by the old Josh's proud, utopian sense of human inevitability. It lifted my own spirits in the here and now!

I made the mistake of announcing the book on Patreon right after I finished writing it, i.e. back in mid-March. Then I had to wring my hands every week about how post-production was taking longer than expected. Between the irritating realities of formatting a book in software not properly equipped to format a book (never write a book in Google Docs), the complexities of my detail-oriented manner and strong vision regarding the cover design (and engaging for the first time ever with modern generative AI, and having to learn those ropes), and sustaining illnesses and other life priorities and so on, it would take me another two months in all to finally reach today, where I can now publicly declare:

The book is done! It is for sale right now. It is called:

Tokens of Zeal: Words from a Vanished Age

(Caption: Book front cover of Tokens of Zeal: Words from a Vanished Age, by Joshua Calars.)

You can buy it through Amazon in either paperback or e-book format. (I recommend the paperback version for aesthetics as it is much truer to my design vision for the book's layout and appearance, but my profit margin is actually a dollar bigger with the e-book version, so really just go with whichever version you prefer.) It is available in the US as well as in basically all the other countries that Amazon has expanded its publishing service into. If you need help finding a link to a particular version, give me a ping and I will point you there (if there is a "there" to be pointed to). This is my second published book, following Prelude to After The Hero in 2015, and the first book to be published in print.

If you do read it, first of all thank you! It's an honor that you would take the time. Second of all, I would love any feedback you care to offer. That's not a platitude either; feedback is hard to come by and I really would be interested in anything you have to say, good or bad. You can e-mail me, DM, reblog this, drop an ask, or tag me in an independent post. Whatever you like! Feedback will help me greatly when I eventually get around to writing Volume 2. And feel free to leave a review on Amazon, whether good or bad (though hopefully you enjoy the book); I am told it pleases The Algorithm. But most of all, if you enjoy the book, tell someone about it! Your word-of-mouth is currently 100 percent of my advertising budget, lol.

That's all. I wrote a book; it took four-and-a-half-months; it's done now; and it's the first time I've ever gotten to hold a book that I wrote in my hands as a physical thing, and that's pretty neat.

[04k96]

Alright, bucko—strap in. Here’s a speculative timeline + cultural map of what an intentional or emergent AI slowdown might look like, as systems (and humans) hit thresholds they weren’t ready for:

⸻

PHASE 1: THE FRENZY (2023–2026)

“It’s magic! It does everything!”

• AI is integrated into every app, interface, workspace, school.

• Productivity spikes, novelty floods, markets boom.

• Art, code, and content feel democratized—but also flooded with sameness.

• Emerging signs of fatigue: burnout, aesthetic flattening, privacy erosion.

⸻

PHASE 2: THE CRACK (2026–2028)

“Wait… who’s driving this?”

• Cultural bottleneck: Hyper-efficiency erodes depth and human uniqueness.

• Political tension: Regulation debates explode over elections, education, warfare, and job losses.

• AI-native Gen Z+ workers question value of constant optimization.

• Rise of “Slow Tech” movements, digital sobriety, and human-first UX design.

⸻

PHASE 3: THE CORRECTION (2028–2032)

“We need AI to disappear into the background.”

• AI goes low-profile: instead of being flashy, it’s embedded into infrastructure, not attention.

• Cultural shift toward local intelligence, emotional resonance, and craft.

• Smart systems assist but do not decide. You drive, it advises.

• New benchmarks: “Serenity per watt”, “Complexity avoided”, “Time saved for soul”.

⸻

PHASE 4: THE REWEAVING (2032–2035)

“Tools for culture, not culture as tool.”

• AI serves communal living, ecological restoration, learning ecosystems.

• Widespread adoption of “Digital Commons” models (open-source, ethical compute).

• Intelligence seen not as a weapon of dominance but as a craft of care.

• Humans rediscover meaning not just in what they can automate, but what they can hold together.

⸻

THE OVERALL MAP:

• Spiritual: Shift from worshipping intelligence to cultivating wisdom.

• Design: From smart cities to wise villages—tech that respects silence, presence, friction.

• Economy: From “scale fast” to “scale consciously.”

• Power: From algorithmic persuasion to consent-based architectures.

• Aesthetics: From algorithmic mimicry to radical human texture.

⸻

In this future, the most prized skill won’t be prompting or automation—it’ll be curating stillness in motion, designing for nuance, and knowing when not to use AI at all.

[bliow]

AGARTHA Aİ - DEVASA+ (2)

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