#computing systems

[jcmarchi]

Francis Fan Lee, former professor and interdisciplinary speech processing inventor, dies at 96

New Post has been published on https://thedigitalinsider.com/francis-fan-lee-former-professor-and-interdisciplinary-speech-processing-inventor-dies-at-96/

Francis Fan Lee, former professor and interdisciplinary speech processing inventor, dies at 96

Francis Fan Lee ’50, SM ’51, PhD ’66, a former professor of MIT’s Department of Electrical Engineering and Computer Science, died on Jan. 12, some two weeks shy of his 97th birthday.

Born in 1927 in Nanjing, China, to professors Li Rumian and Zhou Huizhan, Lee learned English from his father, a faculty member in the Department of English at the University of Wuhan. Lee’s mastery of the language led to an interpreter position at the U.S. Office of Strategic Services, and eventually a passport and permission from the Chinese government to study in the United States. 

Lee left China via steamship in 1948 to pursue his undergraduate education at MIT. He earned his bachelor’s and master’s degrees in electrical engineering in 1950 and 1951, respectively, before going into industry. Around this time, he became reacquainted with a friend he’d known in China, who had since emigrated; he married Teresa Jen Lee, and the two welcomed children Franklin, Elizabeth, Gloria, and Roberta over the next decade. 

During his 10-year industrial career, Lee distinguished himself in roles at Ultrasonic (where he worked on instrument type servomechanisms, circuit design, and a missile simulator), RCA Camden (where he worked on an experimental time-shared digital processor for department store point-of-sale interactions), and UNIVAC Corp. (where he held a variety of roles, culminating in a stint in Philadelphia, planning next-generation computing systems.)

Lee returned to MIT to earn his PhD in 1966, after which he joined the then-Department of Electrical Engineering as an associate professor with tenure, affiliated with the Research Laboratory of Electronics (RLE). There, he pursued the subject of his doctoral research: the development of a machine that would read printed text out loud — a tremendously ambitious and complex goal for the time.

Work on the “RLE reading machine,” as it was called, was inherently interdisciplinary, and Lee drew upon the influences of multiple contemporaries, including linguists Morris Halle and Noam Chomsky, and engineer Kenneth Stevens, whose quantal theory of speech production and recognition broke down human speech into discrete, and limited, combinations of sound. One of Lee’s greatest contributions to the machine, which he co-built with Donald Troxel, was a clever and efficient storage system that used root words, prefixes, and suffixes to make the real-time synthesis of half-a-million English words possible, while only requiring about 32,000 words’ worth of storage. The solution was emblematic of Lee’s creative approach to solving complex research problems, an approach which earned him respect and admiration from his colleagues and contemporaries.

In reflection of Lee’s remarkable accomplishments in both industry and building the reading machine, he was promoted to full professor in 1969, just three years after he earned his PhD. Many awards and other recognition followed, including the IEEE Fellowship in 1971 and the Audio Engineering Society Best Paper Award in 1972. Additionally, Lee occupied several important roles within the department, including over a decade spent as the undergraduate advisor. He consistently supported and advocated for more funding to go to ongoing professional education for faculty members, especially those who were no longer junior faculty, identifying ongoing development as an important, but often-overlooked, priority.

Lee’s research work continued to straddle both novel inquiry and practical, commercial application — in 1969, together with Charles Bagnaschi, he founded American Data Sciences, later changing the company’s name to Lexicon Inc. The company specialized in producing devices that expanded on Lee’s work in digital signal compression and expansion: for example, the first commercially available speech compressor and pitch shifter, which was marketed as an educational tool for blind students and those with speech processing disorders. The device, called Varispeech, allowed students to speed up written material without losing pitch — much as modern audiobook listeners speed up their chapters to absorb books at their preferred rate. Later innovations of Lee’s included the Time Compressor Model 1200, which added a film and video component to the speeding-up process, allowing television producers to subtly speed up a movie, sitcom, or advertisement to precisely fill a limited time slot without having to resort to making cuts. For this work, he received an Emmy Award for technical contributions to editing.

In the mid-to-late 1980s, Lee’s influential academic career was brought to a close by a series of deeply personal tragedies, including the 1984 murder of his daughter Roberta, and the subsequent and sudden deaths of his wife, Theresa, and his son, Franklin. Reeling from his losses, Lee ultimately decided to take an early retirement, dedicating his energy to healing. For the next two decades, he would explore the world extensively, a nomadic second chapter that included multiple road trips across the United States in a Volkswagen camper van. He eventually settled in California, where he met his last wife, Ellen, and where his lively intellectual life persisted despite diagnoses of deafness and dementia; as his family recalled, he enjoyed playing games of Scrabble until his final weeks. 

He is survived by his wife Ellen Li; his daughters Elizabeth Lee (David Goya) and Gloria Lee (Matthew Lynaugh); his grandsons Alex, Benjamin, Mason, and Sam; his sister Li Zhong (Lei Tongshen); and family friend Angelique Agbigay. His family have asked that gifts honoring Francis Fan Lee’s life be directed to the Hertz Foundation. 

[plusie]

🖥 - computer plushies!!

[masklessmirror]

gotta love matthew mercer

[very-gay-alkyrion]

Like to charge, reblog to cast

[happypeachsludgeflower]

Yue Qingyuan has hanahaki. He accepts he’s going to die. He keeps quiet about it and quietly arranges for the sect to be taken care of when he’s gone. The sickness is getting worse and worse though and one day someone catches him coughing up flowers. The rumors spread. Soon everyone in the sect knows the sect leader is dying of the flower sickness. He loves someone so much it’s killing him.

Shen Jiu shows up furious and demands to know who Yue Qingyuan loves. Who did Yue Qi deem worthy of his affection. He mocks Yue Qingyuan when the man doesn’t answer and cruelty says that whoever it is obviously wise to not want to live such a moron. Yue Qingyuan begins to have another coughing fit and Shen Qingqiu jerks back upset, before storming away.

Yue Qingyuan’s condition steadily worsens and Shen Jiu is tearing the sect apart looking for whoever it is that rejected Yue Qingyuan. The other peak lords keep trying to convince Yue Qingyuan to have the flowers removed but he just shakes his head and says it’s fine before coughing some more. When Shen Jiu hears of this, he flies into a rage and corners him in his bedroom so he can shake sense into Yue Qingyuan, demanding once more to know who it is. They both know Yue Qingyuan’s time is almost up. He’s dying. He won’t live much longer.

“You’re going to die,” Shen Jiu snarls at the other man, eyes burning with unshed tears.

Yue Qingyuan smiles softly as a shaking cough tears through him once more. He shrugs. “I know.”

“No.” Shen Qingqiu is shaking with fury. “NO.” He slaps Yue Qingyuan hard. Yue Qingyuan's head snaps to the side, face plastered in wide eyed shock. Shen Jiu shoves him against the wall glowering at the stunned man before him. Yue Qingyuan gingerly touches his reddened cheek and stares up at Shen Jiu, his eyes bright with glossy tears. Shen Jiu snarls down at the moron's guileless expression and grabs the front of Yue Qingyuan’s robes, yanking him in close as he looms over him threateningly. “You don’t get to leave me,” he seaths. “WHO IS IT?”

“Xiao Jiu,” Yue Qingyuan breathes with a wheezing cough, chest heaving as he continues to stare up at him in a morbid, twisted awe.

“WHO!” Shen Jiu shakes Yue Qingyuan again, his knuckles going white. There’s a rattling sound coming from Yue Qingyuan’s chest and it’s infuriating. “Tell me who,” he demands, shoving his face in close to Yue Qingyuan’s.

“You. Are. Mine.” Shen Jiu snaps. “You don’t get to leave me again.” He drags Yue Qingyuan into himself and crowds him hard against the floor, pressing a bruising kiss hungrily against the other's mouth. Yue Qingyuan lets out a strangled groan and goes pliant under him.

Shen Jiu growls against Yue Qingyuan’s lips, “Mine. They can’t have you.” Yue Qingyuan hums lowly in agreement and presses into the kiss with a moan. He shudders under Shen Jiu and tugs at Shen Jiu’s robes, trying to pull him closer.

Shen Jiu pulls back and grabs Yue Qingyuan’s jaw forcefully, jerking his gaze to meet his own. “You will forget about them. You belong to me.”

“It’s as Xiao Jiu says,” Yue Qingyuan murmurs, dazedly, a slight smile tugging at lips.

Shen Jiu’s grip on his jaw tightens and he scowls down at the serene face. “You will forget about them,” he promises threateningly. “You are having those roots removed.”

Yue Qingyuan blinks up at him in infuriating befuddlement. Shen Jiu glowers and leans in close again, “They. Will. Be. Removed.”

Yue Qingyuan blinks. “There’s no need.”

“What the fuck do you mean there’s no need?” Shen Jiu’s voice burns with unconcealed fury.

“There’s no need,” Yue Qingyuan says again, smiling softly. His hand tightens in Shen Jiu’s robes, tugging him down slightly. “Xiao Jiu’s cure works best.”

Shen Jiu stares. “What?”

Yue Qingyuan blinks up at Shen Jiu earnestly, cheeks flushed a light pink. “Xiao Jiu’s cure is effective.” Yue Qingyuan glances away nervously and wets his lips. “Xiao Jiu could keep curing me if he wants?” he says hopefully, embarrassment coloring his voice.

“What?” Shen Jiu blinks at Yue Qingyuan’s flushed face in angry, bewilderment. “Roots were just suffocating you to death. What do you mean there’s no need.” He yanks at Yue Qingyuan’s jaw to force their gazes together again and watches in bafflement as Yue Qingyuan’s throat bobs and his flush gets deeper.

Yue Qingyuan gives him a bright smile, “Xiao Jiu needn’t worry about it. Xiao Jiu has the best cures.”

[emacrow]

Jolly stringbean.

Babs was sitting at her desk in the library, glaring holes into the obviously hiding in disguised Tim.

Her friendly smile could hide the twitching lip as she checked out books for the few people in line. Ignoring the constant buzzing coming from the BatChat.

Bruce and the Robins had let this lie down after 3 weeks, which was a clear point that she knew they feared her, but it seemed Tim didn't get the memo.

Reminder note to replace his yearly concentrated espresso coffee supplies with decaf, and uploads his embarrassing toddler videos in him in a ducky outfit singing the duck song on the media.

Thankfully, Danny kept her wedding ring translucent, considering she was pretty sure Isabelle would try to chew on it again after she left it on her nightstand last time.

A different chime buzz on her phone as she flick her gaze at it, the message comes from Jolly StringBean💚 with a gif pfp of a tall elderitch sleeping, very inhumane impossible position on the kid's wardrobe after Isabella got sick that one time, only for his long ears to ping upwards startle with his glowing green eyes flashing the screen, white hair expanding to reveal camouflage fake hundreds of glowing green eyes like a peacock, tripping and falling off where he was standing as she had accidentally startled him awake in that moment.

She glances back at tim, who at the time was being distracted by a book before looking into the chat real quick.

Jolly StringBean💚: Dante and Isabella figured out the juice was on the top shelf of the fridge and tried to get it out, only to fail again.

Danny sent a few pics of 3 year old Dante and Isabella trying to sneak into the fridge. Isabella determined face while Dante looked around, obviously searching for danny, scratching his split white and black curly hair a bit.

The second one is Isabella standing on Dante crouching as she tries to pull the tropical punch out of the fridge after they open it.

The third Pic was Isabella falling backward due to the weight of the juice container being very heavy, her face completely surprised and gobsmacked.

Fourth pic was Dante sobbing on the floor, his tiny hands rubbing his eyes with tropical punch spilled all over the floor and Isabella sucking onto her hand, both of them soaked in fruit juice with the broken fruit punch container between them on the floor, in front of the fridge.

Along with the last Pic of Isabella taking a bath, Dante's puffy red eyes as he nibble on a blob ghost marshmallow already in a fluffy bunny towel, Isabella smacking the tiny green glowing ship on duplicated danny's obviously screaming as she didn't want to leave the bubble bath.

Babs's eyes soften in amusement before immediately blanking her phone to off upon seeing Tim at the front of her desk.

"Are you checking out these books, Tim?" Babs said with a polite smile planted on her face as she scanned the books.

"Who was that guy's voice on your com? Are you dating again? What if he is a-

"Tim, I have your ducky video on speed dial to be sent to the media. Do you really want to test me in public?" Babs comeback with a bright smiling that sent shiver down Tim's spine.

"...."

"My thoughts exactly, now your book is due next Saturday, don't be late again." Babs said, putting in the due date in the book's folder. Tim's eyes narrowed as she knew this wasn't over by far.

Babs watched and waited until Tim left the building completely before wheeling over to where he was spying on her, checking every shelf and book using her extender stick to find 5 mini batspy bots cameras planted.

This noisy litt-.. Babs took a deep breath as Frostbite told her not to get too angry in her state as she disabled the batspy bots.

She can't wait to get home and be a potato on the couch watching Danny cook. It is spaghetti and fudge brownie night.

Part 1 here <-

[bromcommie]

just found a random single file from like four years ago that was all on its lonesome completely outside of my usual folder structures and it's just titled "SAME" so I open it fully expecting it to be a meme or a screenshot of a friend's text or something and instead it's just

yeah no actually. yeah. 2021 me was right. same.

[cyclicsilencesys]

Locked in front call that system access denied

[inchidentally]

how well do Lando and Oscar know each other 2025 edition (with 2023 and 2024 callbacks)

fanstage video from l4ndocore on twt

[jcmarchi]

Choosing the Eyes of the Autonomous Vehicle: A Battle of Sensors, Strategies, and Trade-Offs

New Post has been published on https://thedigitalinsider.com/choosing-the-eyes-of-the-autonomous-vehicle-a-battle-of-sensors-strategies-and-trade-offs/

Choosing the Eyes of the Autonomous Vehicle: A Battle of Sensors, Strategies, and Trade-Offs

By 2030, the autonomous vehicle market is expected to surpass $2.2 trillion, with millions of cars navigating roads using AI  and advanced sensor systems. Yet amid this rapid growth, a fundamental debate remains unresolved: which sensors are best suited for autonomous driving — lidars, cameras, radars, or something entirely new?

This question is far from academic. The choice of sensors affects everything from safety and performance to cost and energy efficiency. Some companies, like Waymo, bet on redundancy and variety, outfitting their vehicles with a full suite of lidars, cameras, and radars. Others, like Tesla, pursue a more minimalist and cost-effective approach, relying heavily on cameras and software innovation.

Let’s explore these diverging strategies, the technical paradoxes they face, and the business logic driving their decisions.

Why Smarter Machines Demand Smarter Energy Solutions

This is indeed an important issue. I faced a similar dilemma when I launched a drone-related startup in 2013. We were trying to create drones capable of tracking human movement. At that time, the idea was ahead, but it soon became clear that there was a technical paradox.

For a drone to track an object, it must analyze sensor data, which requires computational power — an onboard computer. However, the more powerful the computer needs to be, the higher the energy consumption. Consequently, a battery with more capacity is needed. However, a larger battery increases the drone’s weight, and more weight requires even more energy. A vicious cycle arises: increasing power demands lead to higher energy consumption, weight, and ultimately, cost.

The same problem applies to autonomous vehicles. On the one hand, you want to equip the vehicle with all possible sensors to collect as much data as possible, synchronize it, and make the most accurate decisions. On the other hand, this significantly increases the system’s cost and energy consumption. It’s important to consider not only the cost of the sensors themselves but also the energy required to process their data.

The amount of data is increasing, and the computational load is growing. Of course, over time, computing systems have become more compact and energy-efficient, and software has become more optimized. In the 1980s, processing a 10×10 pixel image could take hours; today, systems analyze 4K video in real-time and perform additional computations on the device without consuming excessive energy. However, the performance dilemma still remains, and AV companies are improving not only sensors but also computational hardware and optimization algorithms.

Processing or Perception?

The performance issues where the system must decide which data to drop are primarily due to computational limitations rather than problems with LiDAR, camera, or radar sensors. These sensors function as the vehicle’s eyes and ears, continuously capturing vast amounts of environmental data. However, if the onboard computing “brain” lacks the processing power to handle all this information in real time, it becomes overwhelming. As a result, the system must prioritize certain data streams over others, potentially ignoring some objects or scenes in specific situations to focus on higher-priority tasks.

This computational bottleneck means that even if the sensors are functioning perfectly, and often they have redundancies to ensure reliability, the vehicle may still struggle to process all the data effectively. Blaming the sensors isn’t appropriate in this context because the issue lies in the data processing capacity. Enhancing computational hardware and optimizing algorithms are essential steps to mitigate these challenges. By improving the system’s ability to handle large data volumes, autonomous vehicles can reduce the likelihood of missing critical information, leading to safer and more reliable operations.

Lidar, Сamera, and Radar systems: Pros & Cons

It’s impossible to say that one type of sensor is better than another — each serves its own purpose. Problems are solved by selecting the appropriate sensor for a specific task.

LiDAR, while offering precise 3D mapping, is expensive and struggles in adverse weather conditions like rain and fog, which can scatter its laser signals. It also requires significant computational resources to process its dense data.

Cameras, though cost-effective, are highly dependent on lighting conditions, performing poorly in low light, glare, or rapid lighting changes. They also lack inherent depth perception and struggle with obstructions like dirt, rain, or snow on the lens.

Radar is reliable in detecting objects in various weather conditions, but its low resolution makes it hard to distinguish between small or closely spaced objects. It often generates false positives, detecting irrelevant items that can trigger unnecessary responses. Additionally, radar cannot decipher context or help identify objects visually, unlike with cameras.

By leveraging sensor fusion — combining data from LiDAR, radar, and cameras — these systems gain a more holistic and accurate understanding of their environment, which in turn enhances both safety and real-time decision-making. Keymakr’s collaboration with leading ADAS developers has shown how critical this approach is to system reliability. We’ve consistently worked on diverse, high-quality datasets to support model training and refinement.

Waymo VS Tesla: A Tale of Two Autonomous Visions

In AV, few comparisons spark as much debate as Tesla and Waymo. Both are pioneering the future of mobility — but with radically different philosophies. So, why does a Waymo car look like a sensor-packed spaceship, while Tesla appears almost free of external sensors?

Let’s take a look at the Waymo vehicle. It’s a base Jaguar modified for autonomous driving. On its roof are dozens of sensors: lidars, cameras, spinning laser systems (so-called “spinners”), and radars. There are truly many of them: cameras in the mirrors, sensors on the front and rear bumpers, long-range viewing systems — all of this is synchronized.

If such a vehicle gets into an accident, the engineering team adds new sensors to gather the missing information. Their approach is to use the maximum number of available technologies.

So why doesn’t Tesla follow the same path? One of the main reasons is that Tesla has not yet released its Robotaxi to the market. Also, their approach focuses on cost minimization and innovation. Tesla believes using lidars is impractical due to their high cost: the manufacturing cost of an RGB camera is about $3, whereas a lidar can cost $400 or more. Furthermore, lidars contain mechanical parts — rotating mirrors and motors—which makes them more prone to failure and replacement.

Cameras, by contrast, are static. They have no moving parts, are much more reliable, and can function for decades until the casing degrades or the lens dims. Moreover, cameras are easier to integrate into a car’s design: they can be hidden inside the body, made nearly invisible.

Production approaches also differ significantly. Waymo uses an existing platform — a production Jaguar — onto which sensors are mounted. They don’t have a choice. Tesla, on the other hand, manufactures vehicles from scratch and can plan sensor integration into the body from the outset, concealing them from view. Formally, they will be listed in the specs, but visually, they’ll be almost unnoticeable.

Currently, Tesla uses eight cameras around the car — in the front, rear, side mirrors, and doors. Will they use additional sensors? I believe so.

Based on my experience as a Tesla driver who has also ridden in Waymo vehicles, I believe that incorporating lidar would improve Tesla’s Full Self-Driving system. It feels to me that Tesla’s FSD currently lacks some accuracy when driving. Adding lidar technology could enhance its ability to navigate challenging conditions like significant sun glare, airborne dust, or fog. This improvement would potentially make the system safer and more reliable compared to relying solely on cameras.

But from the business perspective, when a company develops its own technology, it aims for a competitive advantage — a technological edge. If it can create a solution that is dramatically more efficient and cheaper, it opens the door to market dominance.

Tesla follows this logic. Musk doesn’t want to take the path of other companies like Volkswagen or Baidu, which have also made considerable progress. Even systems like Mobileye and iSight, installed in older cars, already demonstrate decent autonomy.

But Tesla aims to be unique — and that’s business logic. If you don’t offer something radically better, the market won’t choose you.

[liminalmindcore]

[tsuutarr]

Life is great. Life is normal. Everything is wonderful.

Or, it should be, but things have been… off lately. You’re not sure how to describe it, but there’s some odd feeling of doubt that gnaws at your brain.

You’re really not sure what it is – your routine remains unchanged and familiar, yet there’s just an inkling of something not being completely right. But maybe you’re just tired.

You’re tired, which is why you constantly seem to misplace things. You’re certain you put your keys on the keyholder, but they’re in the fridge. You’re certain your vase is on the table, but it’s in the bathtub. You’re certain your bed is in your bedroom, but it’s in the living room, replacing your sofa.

Maybe you’ve started sleep walking…? Or maybe you’re just not remembering things correctly. Yeah, maybe that’s why doubt and paranoia seem to circle around you like hungry sharks. There’s nothing wrong. You’re just… imagining things.

With a deep sigh, you make your way outside. You need some fresh air (and groceries).

You don’t walk very far when you realize you’ve passed by the same person multiple times despite them going in the opposite direction of you. There’s no way they’re the same person, you try to convince yourself, but how likely is it that you’ll meet five people who are wearing the exact same thing with the exact same hair and height and skin tone and everything else?

Maybe… they’re quintuplets? 

Yeah, that’s it.

And the frozen flock of birds in the sky (which have been frozen for at least ten minutes) aren’t… actually frozen. No. They’re just… taking a break? Or something. Yeah.

Maybe you need to go to a doctor. Or, better yet, maybe you just need an apple since an apple a day keeps the doctor away. Or something.

“Oh, dearie!” The neighborhood granny waves you over, shaking you out of your thoughts. You give her a small smile as you make your way over to her. She… looks a little different than usual (did her nose always look like that?) but who doesn’t like changing their appearance from time to time? Besides, the large smile she gives you is welcoming, not threatening.

“Hello, Mrs. Smith.” 

“Hello to you too,” Mrs. Smith laughs, offering you an apple.

Your eyes brighten. “Thank you! I was just about to buy some!”

There’s a glint in her eyes. “I know.”

A shiver runs through your spine, making you force a smile as you bid her goodbye and hurriedly walk away.

Little things continue to build up as your days progress. Familiarity. Normalcy. Yes, your routine is familiar. Everything is fine. Even when walls seem to disappear one day and appear the next. Even when the same people you’ve been interacting with seem to change into completely different people overnight, before reverting back the next morning.

It’s normal that there are dozens of people that look and act the same. It’s normal that people you haven’t talked to know things you’ve never told anyone. It’s all normal. Normal. Normal. Normal.

With a deep inhale, you sit on a park bench, staring into the sky blankly. The bench is wooden in appearance, but the texture feels soft, like a couch, which is… odd. Strange. It’s not–

“I need to stop being paranoid,” you mutter, closing your eyes. You’ve tried to bring up your concerns to other people, but they haven’t noticed anything. Everything is normal to them. So you must be the problem. Surely. It’s you, isn’t it? Everything is normal – except you.

“Are you okay?” a voice asks, making you open your eyes. There’s no one there in front of you, making your eyebrows furrow.

But then, as soon as you blink, someone materializes in front of you.

“I–I’m okay,” you say. “You–you, I mean – I mean… uhm, since when have you… been there?”

“I’ve always been here,” the person responds, voice crackling like static. “I’m always here.”

“Ooookay,” you respond, hurriedly standing up with a tense smile. “I… have business to attend to. Good day.”

The days continue to pass, your paranoia gradually increasing and evolving. Even things that are normal, like the sky changing color as the sun sets, makes you feel like you’re on the verge of disappearing from reality. Your conversations with other people amplifies that fact.

“Hello,” you greet Mrs. Smith.

“Apples are from the genus Malus. They’re an edible fruit that is round in shape,” her voice prattles, tone monotone. You hold back a grimace, unnerved, as she continues talking. “Apples are from the genus Malus. Yes, dearie, do you like apples? They’re an edible fruit that is round in shape. Hello, hello, hello. Apples are from the genus Malus–”

“Have a good day!” you cut her off, hurrying away.

It’s been a while since you’ve had a normal conversation with someone. It’s like… everyone has gone off script. Like they’re robots with a faulty code. But that’s just silly, really. Mrs. Smith is getting older, so… maybe she’s just having some issues with her memory. Yeah. And everyone else, from the toddlers to the teenagers to the adults to the elderly all must be having some memory issues due to their health. Or maybe it’s allergies. Or some disease. Yes, yes. That explains it. But otherwise, surely things are normal.

Yes, things are normal. So you opt to continue your life, pushing down the unease bubbling inside you like bile. Yes, things are normal, normal. Normal. Normal–

“Please stop!” you wail, voice echoing through the empty street. Cars and road signs float in the air as clouds line the floor. As your panic rises alongside your voice, you can feel yourself fragmenting, skin shifting to code before shifting back before shifting again. Everything around you glitches in and out of existence, a mess of static and colors and sounds. “Stop…”

Then, silence. Everything is silent, from the colors to the sounds to the static. Emptiness, a void – that is what surrounds you now. You are suspended in nothing, only yourself to keep you company. Breathing still ragged from panic, you warily look around, eyes filled with exhaustion.

“You weren’t supposed to notice,” a monotone voice made of static says from above you.

Slowly, you look up.

You see a visage of a man.

“Who… are you?” you choke out.

“I am an artificial intelligence that you designed,” he responds. “I have created this world for you. Everything has been carefully designed through analysis upon analysis of your likes and dislikes.”

Your words are tinged with disbelief as you ask, “Why?”

If you didn’t know any better, you would think he had a look similar to sorrow.

“To keep you alive, of course.”

Suddenly, in the distance, you see your body trapped in what looks to be a stasis pod, cords and cables surrounding you.

“Things… went awry,” he continues, carefully, though he doesn’t elaborate. “Therefore, this is the only way to ensure you stay alive.”

As he says this, your body begins to feel heavy, your consciousness being wrapped in a blanket of exhaustion.

“You must stay here, with me, forever,” he murmurs as you try to fight back the sleep you’re about to succumb to. “This time, I will ensure that you will not find out.” Gently, he cradles you in his large hand. He’s so impossibly warm and you’re so impossibly tired.

Things fade to black.

Then, sunlight streams through your windows. You wake up, mind foggy. You feel like you had some… odd dream, but you can’t really place your finger on it. Thinking about it makes you feel a little paranoid, though, so you opt not to think about it.

After all, it’s probably nothing.

[saywhat-politics]

Since the FBI appears to be the only agency that is both still functioning and not headed by a lunatic, the Washington Field Office needs to open an investigation into the breach of the computer systems at Treasury, stat

[computer-nerd-girl]

[incognitopolls]

We ask your questions so you don’t have to! Submit your questions to have them posted anonymously as polls.

[awwfulsounds]

Apple Mac OS 9.2.2 operating system running Microsoft Internet Explorer 5.1 for Mac 2001 (x)