#emerging Technology program | Explore Tumblr posts and blogs

tecxter · 1 year ago

Text

Stay Ahead of the Curve: Top Emerging Software Technologies for 2024! How Texter Can Help You Harness Their Power

Introduction:

In the present quickly developing mechanical scene, remaining on the ball is fundamental for organizations and people. As we look forward to 2024, a few arising programming innovations are ready to upset different ventures. In this article, we will investigate these state-of-the-art advances and how Texter can help you saddle their ability to accomplish your objectives.

Artificial Intelligence and Machine Learning:

Artificial intelligence and Machine Learning have previously had a tremendous effect in different fields. In 2024, we hope to see significantly more noteworthy headway around there. Man-made intelligence-fuelled applications can robotize monotonous undertakings, upgrade dynamic cycles, and give important experiences. Texter has practical experience in creating man-made intelligence and ML arrangements modified to your particular prerequisites, engaging you to open up the maximum capacity of these advancements.

Blockchain Technology:

The decentralized and secure characteristics of blockchain have led to its increasing adoption. We predict a broader industry use of Blockchain in 2024, encompassing banking, supply chain management, healthcare, and other sectors. Texter provides blockchain development and consulting services, assisting companies in implementing blockchain technologies to improve transparency, expedite processes, and safeguard data integrity.

Extended Reality (XR):

Extended Reality (XR) is the result of the confluence of Augmented Reality (AR) and Virtual Reality (VR). It is anticipated that XR will advance significantly in 2024 in sectors like gaming, healthcare, education, and training. By generating immersive and engaging experiences, Texter can help you fully use the potential of XR and connect with your audience in a way that has never been possible.

Internet of Things (IoT):

The way we live and work is still changing as a result of the Internet of Things. IoT makes it possible for common things to be connected to the internet, improving automation, data collecting, and analysis. We may anticipate much more IoT integration in industrial processes, healthcare systems, smart cities, and smart homes by 2024. To assist you in making use of the promise of IoT for increased productivity and efficiency, Texter provides IoT development and consulting services.

Edge Computing:

A decentralized computing infrastructure referred to as "edge computing" moves the storage and processing of data closer to the location wherein the data is generated. Edge computing is anticipated to resolve issues with latency, bandwidth, and security in the Internet of Things and artificial intelligence age by 2024. By using edge computing technologies, Texter can help you give your apps better security, lower latency, and quicker processing.

Quantum Computing:

Based on the ideas of quantum physics, quantum computing bears the promise of revolutionizing processing power and providing effective solutions to challenging issues. We anticipate notable developments in this sector in 2024. Texter continues to be at the forefront of research on quantum computing, providing advisory and development services to investigate opportunities and fully use the potential of this new technology.

Conclusion:

2024 has a plethora of fascinating opportunities in the realm of software technology. Businesses can obtain a competitive advantage and individuals can discover new prospects by adopting these modern technologies. As your guide on this revolutionary trip, Texter offers its experience in artificial intelligence, machine learning, blockchain, XR, Internet of Things I edge computing, and quantum computing. Keep up with the times and use Texter to better create the future of your company by utilizing the versatility of these cutting-edge software innovations.

0 notes

ralfmaximus · 1 year ago

Text

on the way home, the Tesla Model 3 barreled into a tree and exploded in flames, killing von Ohain, a Tesla employee and devoted fan of CEO Elon Musk. Rossiter, who survived the crash, told emergency responders that von Ohain was using an “auto-drive feature on the Tesla” that “just ran straight off the road,” according to a 911 dispatch recording obtained by The Washington Post. In a recent interview, Rossiter said he believes that von Ohain was using Full Self-Driving, which — if true — would make his death the first known fatality involving Tesla’s most advanced driver-assistance technology.

Finally, they have a witness. A survivor of an Autopilot mishap who can testify that the driver was using Full Self Driving mode at the time of the crash.

See, this has been impossible thus far because (1) survivors are rare, and (2) Teslas are programmed to automatically disengage Self-Driving milliseconds before the crash so that when investigators review the telemetry it clearly shows FSD wasn't turned on.

And due to this technicality, Musk has been able to claim Autopilot has never killed anybody. Until now.

#tesla #musk #idiot #2024

11K notes · View notes

ginger-rat · 3 months ago

Text

The ghost of the Lucky 38

After yet another near death experience Courier Six uses the late Mr. House’s brain scan technology (what was used to make Jane) and hologram projectors stolen from the Sierra Madre to create a fail safe in case of his sudden death. After Six’s death what was supposed to be an emergency response program comes online and decides to not shut off.

#yay a new part to my courier six lore #courier simon #fallout new vegas #fnv #courier 6 #hologram Six (aka Spector) is kinda his own entity

465 notes · View notes

nostalgebraist · 3 months ago

Text

Anthropic's stated "AI timelines" seem wildly aggressive to me.

As far as I can tell, they are now saying that by 2028 – and possibly even by 2027, or late 2026 – something they call "powerful AI" will exist.

And by "powerful AI," they mean... this (source, emphasis mine):

In terms of pure intelligence, it is smarter than a Nobel Prize winner across most relevant fields – biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc. In addition to just being a “smart thing you talk to”, it has all the “interfaces” available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. It can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world. It does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary. It does not have a physical embodiment (other than living on a computer screen), but it can control existing physical tools, robots, or laboratory equipment through a computer; in theory it could even design robots or equipment for itself to use. The resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed. It may however be limited by the response time of the physical world or of software it interacts with. Each of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks.

In the post I'm quoting, Amodei is coy about the timeline for this stuff, saying only that

I think it could come as early as 2026, though there are also ways it could take much longer. But for the purposes of this essay, I’d like to put these issues aside [...]

However, other official communications from Anthropic have been more specific. Most notable is their recent OSTP submission, which states (emphasis in original):

Based on current research trajectories, we anticipate that powerful AI systems could emerge as soon as late 2026 or 2027 [...] Powerful AI technology will be built during this Administration. [i.e. the current Trump administration -nost]

See also here, where Jack Clark says (my emphasis):

People underrate how significant and fast-moving AI progress is. We have this notion that in late 2026, or early 2027, powerful AI systems will be built that will have intellectual capabilities that match or exceed Nobel Prize winners. They’ll have the ability to navigate all of the interfaces… [Clark goes on, mentioning some of the other tenets of "powerful AI" as in other Anthropic communications -nost]

----

To be clear, extremely short timelines like these are not unique to Anthropic.

Miles Brundage (ex-OpenAI) says something similar, albeit less specific, in this post. And Daniel Kokotajlo (also ex-OpenAI) has held views like this for a long time now.

Even Sam Altman himself has said similar things (though in much, much vaguer terms, both on the content of the deliverable and the timeline).

Still, Anthropic's statements are unique in being

official positions of the company

extremely specific and ambitious about the details

extremely aggressive about the timing, even by the standards of "short timelines" AI prognosticators in the same social cluster

Re: ambition, note that the definition of "powerful AI" seems almost the opposite of what you'd come up with if you were trying to make a confident forecast of something.

Often people will talk about "AI capable of transforming the world economy" or something more like that, leaving room for the AI in question to do that in one of several ways, or to do so while still failing at some important things.

But instead, Anthropic's definition is a big conjunctive list of "it'll be able to do this and that and this other thing and...", and each individual capability is defined in the most aggressive possible way, too! Not just "good enough at science to be extremely useful for scientists," but "smarter than a Nobel Prize winner," across "most relevant fields" (whatever that means). And not just good at science but also able to "write extremely good novels" (note that we have a long way to go on that front, and I get the feeling that people at AI labs don't appreciate the extent of the gap [cf]). Not only can it use a computer interface, it can use every computer interface; not only can it use them competently, but it can do so better than the best humans in the world. And all of that is in the first two paragraphs – there's four more paragraphs I haven't even touched in this little summary!

Re: timing, they have even shorter timelines than Kokotajlo these days, which is remarkable since he's historically been considered "the guy with the really short timelines." (See here where Kokotajlo states a median prediction of 2028 for "AGI," by which he means something less impressive than "powerful AI"; he expects something close to the "powerful AI" vision ["ASI"] ~1 year or so after "AGI" arrives.)

----

I, uh, really do not think this is going to happen in "late 2026 or 2027."

Or even by the end of this presidential administration, for that matter.

I can imagine it happening within my lifetime – which is wild and scary and marvelous. But in 1.5 years?!

The confusing thing is, I am very familiar with the kinds of arguments that "short timelines" people make, and I still find the Anthropic's timelines hard to fathom.

Above, I mentioned that Anthropic has shorter timelines than Daniel Kokotajlo, who "merely" expects the same sort of thing in 2029 or so. This probably seems like hairsplitting – from the perspective of your average person not in these circles, both of these predictions look basically identical, "absurdly good godlike sci-fi AI coming absurdly soon." What difference does an extra year or two make, right?

But it's salient to me, because I've been reading Kokotajlo for years now, and I feel like I basically get understand his case. And people, including me, tend to push back on him in the "no, that's too soon" direction. I've read many many blog posts and discussions over the years about this sort of thing, I feel like I should have a handle on what the short-timelines case is.

But even if you accept all the arguments evinced over the years by Daniel "Short Timelines" Kokotajlo, even if you grant all the premises he assumes and some people don't – that still doesn't get you all the way to the Anthropic timeline!

To give a very brief, very inadequate summary, the standard "short timelines argument" right now is like:

Over the next few years we will see a "growth spurt" in the amount of computing power ("compute") used for the largest LLM training runs. This factor of production has been largely stagnant since GPT-4 in 2023, for various reasons, but new clusters are getting built and the metaphorical car will get moving again soon. (See here)

By convention, each "GPT number" uses ~100x as much training compute as the last one. GPT-3 used ~100x as much as GPT-2, and GPT-4 used ~100x as much as GPT-3 (i.e. ~10,000x as much as GPT-2).

We are just now starting to see "~10x GPT-4 compute" models (like Grok 3 and GPT-4.5). In the next few years we will get to "~100x GPT-4 compute" models, and by 2030 will will reach ~10,000x GPT-4 compute.

If you think intuitively about "how much GPT-4 improved upon GPT-3 (100x less) or GPT-2 (10,000x less)," you can maybe convince yourself that these near-future models will be super-smart in ways that are difficult to precisely state/imagine from our vantage point. (GPT-4 was way smarter than GPT-2; it's hard to know what "projecting that forward" would mean, concretely, but it sure does sound like something pretty special)

Meanwhile, all kinds of (arguably) complementary research is going on, like allowing models to "think" for longer amounts of time, giving them GUI interfaces, etc.

All that being said, there's still a big intuitive gap between "ChatGPT, but it's much smarter under the hood" and anything like "powerful AI." But...

...the LLMs are getting good enough that they can write pretty good code, and they're getting better over time. And depending on how you interpret the evidence, you may be able to convince yourself that they're also swiftly getting better at other tasks involved in AI development, like "research engineering." So maybe you don't need to get all the way yourself, you just need to build an AI that's a good enough AI developer that it improves your AIs faster than you can, and then those AIs are even better developers, etc. etc. (People in this social cluster are really keen on the importance of exponential growth, which is generally a good trait to have but IMO it shades into "we need to kick off exponential growth and it'll somehow do the rest because it's all-powerful" in this case.)

And like, I have various disagreements with this picture.

For one thing, the "10x" models we're getting now don't seem especially impressive – there has been a lot of debate over this of course, but reportedly these models were disappointing to their own developers, who expected scaling to work wonders (using the kind of intuitive reasoning mentioned above) and got less than they hoped for.

And (in light of that) I think it's double-counting to talk about the wonders of scaling and then talk about reasoning, computer GUI use, etc. as complementary accelerating factors – those things are just table stakes at this point, the models are already maxing out the tasks you had defined previously, you've gotta give them something new to do or else they'll just sit there wasting GPUs when a smaller model would have sufficed.

And I think we're already at a point where nuances of UX and "character writing" and so forth are more of a limiting factor than intelligence. It's not a lack of "intelligence" that gives us superficially dazzling but vapid "eyeball kick" prose, or voice assistants that are deeply uncomfortable to actually talk to, or (I claim) "AI agents" that get stuck in loops and confuse themselves, or any of that.

We are still stuck in the "Helpful, Harmless, Honest Assistant" chatbot paradigm – no one has seriously broke with it since that Anthropic introduced it in a paper in 2021 – and now that paradigm is showing its limits. ("Reasoning" was strapped onto this paradigm in a simple and fairly awkward way, the new "reasoning" models are still chatbots like this, no one is actually doing anything else.) And instead of "okay, let's invent something better," the plan seems to be "let's just scale up these assistant chatbots and try to get them to self-improve, and they'll figure it out." I won't try to explain why in this post (IYI I kind of tried to here) but I really doubt these helpful/harmless guys can bootstrap their way into winning all the Nobel Prizes.

----

All that stuff I just said – that's where I differ from the usual "short timelines" people, from Kokotajlo and co.

But OK, let's say that for the sake of argument, I'm wrong and they're right. It still seems like a pretty tough squeeze to get to "powerful AI" on time, doesn't it?

In the OSTP submission, Anthropic presents their latest release as evidence of their authority to speak on the topic:

In February 2025, we released Claude 3.7 Sonnet, which is by many performance benchmarks the most powerful and capable commercially-available AI system in the world.

I've used Claude 3.7 Sonnet quite a bit. It is indeed really good, by the standards of these sorts of things!

But it is, of course, very very far from "powerful AI." So like, what is the fine-grained timeline even supposed to look like? When do the many, many milestones get crossed? If they're going to have "powerful AI" in early 2027, where exactly are they in mid-2026? At end-of-year 2025?

If I assume that absolutely everything goes splendidly well with no unexpected obstacles – and remember, we are talking about automating all human intellectual labor and all tasks done by humans on computers, but sure, whatever – then maybe we get the really impressive next-gen models later this year or early next year... and maybe they're suddenly good at all the stuff that has been tough for LLMs thus far (the "10x" models already released show little sign of this but sure, whatever)... and then we finally get into the self-improvement loop in earnest, and then... what?

They figure out to squeeze even more performance out of the GPUs? They think of really smart experiments to run on the cluster? Where are they going to get all the missing information about how to do every single job on earth, the tacit knowledge, the stuff that's not in any web scrape anywhere but locked up in human minds and inaccessible private data stores? Is an experiment designed by a helpful-chatbot AI going to finally crack the problem of giving chatbots the taste to "write extremely good novels," when that taste is precisely what "helpful-chatbot AIs" lack?

I guess the boring answer is that this is all just hype – tech CEO acts like tech CEO, news at 11. (But I don't feel like that can be the full story here, somehow.)

And the scary answer is that there's some secret Anthropic private info that makes this all more plausible. (But I doubt that too – cf. Brundage's claim that there are no more secrets like that now, the short-timelines cards are all on the table.)

It just does not make sense to me. And (as you can probably tell) I find it very frustrating that these guys are out there talking about how human thought will basically be obsolete in a few years, and pontificating about how to find new sources of meaning in life and stuff, without actually laying out an argument that their vision – which would be the common concern of all of us, if it were indeed on the horizon – is actually likely to occur on the timescale they propose.

It would be less frustrating if I were being asked to simply take it on faith, or explicitly on the basis of corporate secret knowledge. But no, the claim is not that, it's something more like "now, now, I know this must sound far-fetched to the layman, but if you really understand 'scaling laws' and 'exponential growth,' and you appreciate the way that pretraining will be scaled up soon, then it's simply obvious that –"

No! Fuck that! I've read the papers you're talking about, I know all the arguments you're handwaving-in-the-direction-of! It still doesn't add up!

#ai tag #no matter how things go i'm sure this will be fun to revisit in 2 years...

280 notes · View notes

sunarryn · 3 months ago

Text

DP X Marvel #1

Don’t get me wrong—I love DP X DC, but I want more post for DP X Marvel, so I decided to write my own.

Danny had been in Amity Park, dodging international press, paparazzi, and the occasional FBI van parked outside his house, because, well, saving the world and exposing the existence of ghosts kind of made him a big deal. The whole “I’m actually Phantom” reveal had sent the world into a meltdown, with headlines like “Teen Ghostboy Saves Earth, Wears Same Hoodie for Six Days” and “Should Phantom Pay Taxes?” clogging up the internet.

That’s when Tony Stark showed up.

In person.

“You ever consider switching teams?” Tony asked while eating a hotdog in Danny’s kitchen like he owned the place. “I don’t mean ghost to human. I mean ghost to Avenger.”

Danny, halfway through microwaving leftover pizza, blinked. “Is this a recruitment thing or are you just lost?”

“A little of both.” Tony admitted. “I’ve got a proposition for you. Comes with a full scholarship, housing, no taxes, and a lifetime supply of Pop-Tarts.”

“…Okay but like. Why Pop-Tarts?”

“I have a theory about your ghost metabolism and artificial preservatives.” Tony said, waving his hand like it was normal science and not the start of an exorcism. “Anyway. Stark Industries internship. Full ride to Midtown School of Science and Technology. We pretend this is for science—understanding ghosts and ectoplasm and your stupid glowy ice powers or whatever—and I get to say I recruited the coolest teen superhero before the other billionaires.”

“You just don’t want me joining Batman.” Danny muttered.

Tony narrowed his eyes. “Don’t say the B-word in my presence.”

So that’s how Danny Fenton—Amity Park’s favorite undead menace—ended up in New York City, living in a swanky Stark-funded high-rise with a fully stocked lab, an entire ghost-proof gym, and a contract that explicitly stated “NO OPENING INTERDIMENSIONAL PORTALS BEFORE 9AM” in Comic Sans.

Midtown High was wild. First of all, every student looked like they either had a skincare sponsorship or fought crime on the weekends. Second, the STEM program had actual quantum computers. Danny’s old school had a vending machine that exploded if you pressed B5 twice.

Third: Peter Parker.

Danny met him on his first day, right after being hit by a rogue drone in robotics class and slamming face-first into a whiteboard that read “No running in the lab.”

Peter looked down at him. “You good, man?”

Danny blinked. “Spider-Man?”

Peter blinked. “I have no idea what you’re talking about.”

Danny smirked. “Uh-huh. Tony says hi.”

Peter yanked him up by the arm and shoved him into a janitor’s closet so fast it could’ve given someone whiplash.

“Shh!” Peter exclaimed. “You can’t just say that out loud! People don’t know!”

Danny shrugged, now intangibly phasing halfway through a mop bucket. “Relax. Everyone already knows I’m Phantom. It’s not like we’re on equal secret identity footing here.”

Peter blinked at that. “Wait, you’re Phantom? Like THE Phantom?”

Danny stuck his head through the wall dramatically. “Boo.”

Peter shrieked and punched him. Which didn’t work. At all. From then on, they were inseparable.

Mostly because Tony made them sit next to each other at every Stark-sponsored science conference with assigned seating and a label that said “Teen Angst Section.” But also because they kind of understood each other. Weird powers. Exhausting double lives. Constant media attention. Love lives that were mostly disaster zones.

Also, because every time there was an emergency in New York, Danny would dramatically yell, “I GOT THIS!” turn into a glowing ghost, phase through the ceiling, and leave Peter holding their science project like, “Great. Now I have to explain this to Ms. Warren.”

There was a running bet in the school on how many times a week Danny would ghost out during class. The record was four times in a single Monday. Once during math. Twice during lunch. Once mid-presentation, when his eyes flashed green, and he mumbled, “Hold up, I think a ghost just tried to eat a nun,” before vanishing.

He got an A. Mostly out of fear.

They became known around Midtown as “Science Boyfriends,” a term coined by their English teacher after they accidentally blew up the chemistry lab and rebuilt it with better airflow and a smoothie bar.

Peter tried to deny it. Danny didn’t.

“I mean, he’s cute.” Danny would shrug while eating a granola bar and floating upside-down. “And have you seen his calves? Spider thighs? Man’s got spider thighs.”

Peter threatened to web his mouth shut. Danny turned intangible and said “do it, coward.”

Happy Hogan was having a mental breakdown.

“Mr. Stark.” He said once, after catching Danny phasing through a vending machine and Peter falling out of a ceiling vent. “They’re going to destroy the school.”

“They’re already destroying my will to live.” Tony muttered, sipping coffee while watching Phantom carry Spider-Man bridal-style on a street livestream. “But you can’t deny the brand synergy.”

And oh, the public loved Danny.

Kids wore Phantom backpacks. There was a whole TikTok trend called “Go Ghost Challenge” which was just teens flinging themselves over furniture in hopes of catching flight. People stopped him on the street for selfies. A company released a Ghost Repellent Spray that was literally just Febreze with a green label.

Meanwhile, Danny and Peter were balancing AP Physics, ghost attacks, Stark internships, and trying to keep a low profile despite Danny being literally neon.

Peter was this close to combusting.

“I can’t keep doing this.” Peter whispered during lunch, forehead pressed against a table. “My GPA is dying. I’m dying. My soul is cracking. I haven’t slept in three days.”

Danny, completely fine, sipping chocolate milk through a straw, replied, “I think a banshee tried to possess the home ec teacher.”

Peter stared. “… Danny.”

“Her cupcakes were glowing.”

“DANIEL JAMES!”

It didn’t help that the media kept speculating if Phantom was dating Spider-Man. There were articles like “Who’s the Top Ghost? Our Editors Discuss” and “Teen Heroes: Roommates or Soulmates?” Danny read them out loud during lunch.

Peter screamed into a burrito.

And then there was that time someone tried to kidnap Peter during gym class. Bad idea. Danny turned invisible, slammed the guy through the bleachers, and then flew Peter to safety in front of the entire school.

“You didn’t have to carry me!” Peter hissed later. “I had it under control.”

“You were duct-taped to a chair.” Danny pointed out.

“I was about to chew through the tape!”

“Like a squirrel.”

“Like a spider!”

After that, it wasn’t just the school that shipped them. The city did. There were shirts. Stickers. Fanfiction. Someone made a rap.

Tony started selling merch.

“We’re not even dating!” Peter yelled one afternoon, dodging a drone with their faces painted on it.

Danny just winked. “Yet.”

And honestly? They made a good team.

When ghosts got loose, Danny handled the supernatural. When aliens showed up, Peter webbed ‘em to the nearest wall. When things exploded, they blamed Flash Thompson.

Midtown might have been chaos. Their lives might have been actual flaming garbage fires. But in the middle of it all, Danny and Peter were the weirdest, most terrifying, most effective duo the teen superhero world had ever seen.

One had ghost lasers.

The other had web shooters.

Both had the fashion sense of stressed-out raccoons.

And somehow, they made it work.

Until Danny accidentally opened a portal to the Ghost Zone during prom. But that’s a story for another day.

#danny fenton #danny phantom #marvel #marvel mcu #mcu fandom #mcu #tony stark #peter parker #spiderman #dp x marvel

252 notes · View notes

syoddeye · 6 months ago

Note

Here me out pls

Nik in the Strict Machinery AU as a possible bf for reader for a NikPricexReader

Thank you for your time

hear you out? for nik? always. this was fun. nikolai is still nikolai in this au. that is, mysteriously wealthy and well-connected. he's probably fascinated by john. it's cutting edge technology, after all. available only to the testers that live in the building.

that said. i do not think their first meeting goes well.

strict machine anthology. cw: alcohol mention, implied non-consensual voyeurism, the boys are fighting

the hesitation is intentional, nikolai thinks. prototype or not, there is no reason for this thing to experience a delay. it's too advanced. his own cheap, voice-active coffee maker brews pots when he's face down in bed, slurring commands through a hangover.

he leans against the counter. "john. i said, black coffee, no sugar."

this time, it responds. "user has not authorized food or drink for guests."

nikolai smiles, a tired amusement curving his mouth. "she's asleep," he counters, pushing to see where the line is. "should i wake her?"

after a beat, the machine hums to life, reluctantly, he assumes. as the mug fills, he turns his attention to the wall panel. he ignores the in case of emergency and authorized users only stickers.

the nearly invisible door gives a soft whoosh as the compartment opens, revealing a sleek, intricate array of circuits and controls—a shrine to cutting-edge design. far beyond what even the wealthiest of his clients might handle, nikolai marvels at it, his fingers hovering just shy of contact. then, he touches its small screen, intending to peek at��

it zaps him. not painful, but pointed. a gentle warning, considering. nikolai shakes out his fingers and chuckles. "i apologize. i should always ask before touching."

there is no answer, until he retrieves his coffee. it is black, but one sip, and he knows there are at least two sugars in it. what a curious, temperamental thing.

"before she wakes, i should inform you that i was unable to complete your background check last night." john suddenly pipes up, voice clipped and stern.

"you ran a check? on me?" not the first time, not the last. good to know his team is worth their salaries, though. keeping him disconnected, his data scrubbed.

"i run checks with everyone my user spends more than five minutes with."

"surely i lasted longer than that," nikolai smirks into his mug, feeling the granules dissolve and swim between his teeth. "you were watching us, weren't you?"

silence.

"to make sure i was acting as a gentleman, as i assured you last night?"

"you were drunk."

"we both were." nikolai replies, moving to the couch. he sinks into its corner, one leg draped over the edge, lounging comfortably. he looks out across the sterile space. it is cozy compared to his own, but it has its charm. he is undecided about the assistant, though.

the thing is too over-zealous for his liking. he would spit if he heard his coffee maker back talk. he would take a bat to it.

"you must know her better than anyone."

this time, the response is immediate. defensive, even. "i am optimized to ensure her well-being."

nikolai chuckles. "'optimized'. is that what you call it?" he smooths back his mussed hair. "you don't like me. you're suspicious. that's good. it's very…human."

"it is not. i am not." a shift in tone. closer, too. like he's right on top of him. has he flustered the thing? "my programming is consistent and solid, unlike–"

"humans?" he catches a flicker of light, and a projected figure materializes beside him, legs disappearing into the couch. broad shoulders, bullish posture, arms crossed. its face is tight and stern, probably modeled after a thousand logged expressions of intimidation. the fidelity is nothing like he's seen, either. realistic enough that nikolai wanted to touch it the mole on its nose. his hand twitches before he recalls the panel's warning.

hm. interesting. more rugged than i imagined.

"that's good, john. because i'm consistent. solid, too. ask her about that later. she will tell you, or she will request pain relief." he lifts his mug in a toast, and the figure's frown deepens.

just as quickly as it appeared, the image vanishes. he hears movement from beyond the cracked bedroom door, followed by a voice. low, but not quite low enough.

"john?"

"yeah, darl?"

darl?

"i'm, uh, sore from...dancing last night. do you mind setting out something in the bathroom for it?"

something in the wall behind nikolai makes an awful sound. a muffled, metal-on-metal rumbling. an equivalent to grinding teeth together. his grin widens, and he spreads his legs a little further.

"of course, darl, i'll—"

"oh! and ask nik what he wants for breakfast, okay?"

he laughs quietly into his too-sweet coffee at the program's stiff and resigned assent.

#strict machine #nikolai x reader #price x reader #john price x reader

249 notes · View notes

papoochu · 11 days ago

Text

Next in the council series is "The Machine", Tomoe Tsurugi! Though for ArtFight, she'll go undercover as Tachibana Nagi!

Now that I have 3 council members up, I think I'll make a pinned masterpost on my blog if you want to see the others! 3 down, 9 more to go!

Background

Tachibana = noble samurai clan name symbolizing honor and legacy, deeply tied to Japan’s warrior history

Nagi = meaning “to mow down” or “to sweep away”; often used to describe the motion of a naginata, a sword, or wind in battle

Born 1967 in Tokyo to a strict traditional family, proud of their samurai lineage

Learned various martial arts and weaponry, but excelled in swordsmanship

Raised on stories of Onna-Musha, Tomoe Gozen, and the codes of bushidō

On her mother’s side, descended from survivors of the Nagasaki atomic bombing (1945)

Childhood During Japan’s Economic Miracle:

Raised amid Japan’s postwar boom, a time of gleaming technology and rising prosperity

While her father, a bureaucrat in the Ministry of International Trade and Industry, embraced modernization, her household remained steeped in samurai values: discipline, tradition, duty

Unbeknownst to them, Nagi had inherited genetic mutations from her hibakusha grandparents, survivors of Nagasaki’s blast

Frequently ill as a child (chronic fatigue, joint pain, unusual sensitivities), she was in and out of hospitals

Medical professionals were evasive, classmates cruel; whispers of “tainted blood” followed her

Early medical trauma and social alienation planted a seed of hatred for human fragility and societal hypocrisy

Early Signs of Blindness (Age 13):

Began experiencing night blindness, trouble reading, and disorientation in dim light

Eventually diagnosed with retinitis pigmentosa: a progressive, degenerative eye condition

Her doctors quietly suggested the condition may be linked to her family’s radiation exposure, a lingering curse of Nagasaki

For Nagi, the diagnosis became not just a personal tragedy, but proof that the past can reach forward and rot the present

University Years:

While studying engineering and mathematics at the University of Tokyo, her sight deteriorated rapidly

Already known for her genius and prowess, she was approached by the council, who provided her with the resources to adapt her skills for her failing sight

By 24, she was legally blind

This coincided with the peak of Japan’s Bubble Economy: wealth rising, but so was corruption and moral decay (Recruit Scandal)

Rejected from elite job programs despite top academic performance

Her fury crystallized: flesh is weakness, society is hypocritical, and machines do not discriminate

She vowed to build a future where the flawed human body and corrupt human systems would be rendered obsolete

Founding Tachibana Tech (Age 24–28):

As Japan entered the Lost Decade, Nagi founded Tachibana Tech: a cybernetics and AI firm based on one principle: refining the human form through technology

She personally underwent neural interface surgeries, experimenting on herself to convert her remaining senses into data streams

Her vision did not return, but she received augmented perception - a new kind of sight born of code and signal

No longer “blind,” she became The Machine - detached, calculating, and unbound by human limitations

1995 – Kobe Earthquake & Technological Control:

Great Hanshin Earthquake devastated Kobe, exposed fatal weaknesses in Japan’s infrastructure and disaster readiness

Nagi quietly offered her AI to the state for predictive modeling and emergency logistics, then used the data to expand her surveillance reach

The state was incompetent. The people were panicked. Only machines-maintained order

Solidified her belief: Japan doesn’t need democracy - it needs an operating system

Rise of Tachibana Industries:

With Japan’s population aging and its political system paralyzed, Nagi’s company became indispensable - providing predictive governance tools, infrastructure AI, and covert intelligence services

Privately, she orchestrated digital blackmail campaigns, economic disruptions, and political reshuffling to consolidate influence

2011 – Fukushima Nuclear Disaster:

The Fukushima meltdown reopened national trauma - once again, revealing humanity’s hubris and helplessness

To Nagi, it was the final confirmation:

Nagasaki made her blind

Kobe made her a player

Fukushima made her sovereign

Emotion, tradition, empathy - these were relics

Only through data, order, and engineered governance could civilization survive itself

Present Day (Age 49):

Leads a corporate-state hybrid that quietly shapes policy, surveillance, and commerce across East Asia and beyond

Believes that Japan must return to its warrior roots - but not through swords or blood, through discipline, hierarchy, and machine logic

Her mission: eradicate human fragility; a society where order is no longer maintained by the fallible human hand, but by precision systems

Design Notes/Character Study

Character Inspo for main outfit:

Garuda (Warframe), Shen (Kung Fu Panda)

Note: Garuda is based on Indian mythology, while Shen is based on Chinese - use other references for cultural nuance, as this character is Japanese

Modernized kimono

Red, black, white

Tech inspo:

Neon Genesis Evangelion, PCB, Signalis

Parallels to Gendo Ikari

Evangelion Unit-01

Cultural/historical references

Mu = nothingness

Oni

Onna-bugeisha and Tomoe Gozen

Nagasaki

Seismic patterns on shirts

Rising sun/chrysanthemum seal on obi = authoritarianism/conquest

Wields a naginata

Watched videos of national women's competitions @ 0.25 speed T-T

Has devoted her life to the council

Retinitis pigmentosa does not usually have any physical symptoms

Her eyes are pale red/pink from the tech implants

Glowing for artistic flair

Glasses are blackout glasses (opaque)

Company emblem is a sword

Believes her mother gave her weakness

President Snow: No objections to violence; but always with reason

#miraculous ladybug #mlb #fanart #original character #oc #council #tomoe tsurugi #character design #tachibana nagi #the machine

122 notes · View notes

leonstoenailunderhisbed · 1 year ago

Text

I don’t think people understand how smart Leon actually is. That man had high marks from the police academy, hence why Chief Irons (in the orientation letter Leon has in RE2R) says that his grades are commendable and that R.P.D. are proud to have him on the force.

This got me thinking a lot because at first I thought being a police officer didn’t take much given that anyone today can be in the force.

But that wasn’t the case in 1998.

I did a little research because I thought it would be interesting to see just what Leon had to go through to become a police officer.

Back in the 90s, cellphones and modern technology didn’t exist such as DNA identification and body cams/car cams. This definitely made the job a bit harder than it is today because there was a need for more evidence to be collected and the overuse of your brain. Nowadays, technology is an important factor in the police force and almost everything is done by the computer now.

So let’s picture this: It’s the late 90s right before he got sent to Raccoon City. He’s in the academy and he has to go through training. Especially with weapons since most academies switched from revolvers to semi-auto guns (already something a bit modern for that time).

For those who’ve played the game, when you go into the Shooting Range room, you can clearly see just how old the room is compared to modern shooting ranges. Not only is the design of the target paper old, it’s also very simplistic compared to today’s (in 2024, most markings have numbers and more lines for accuracy than back in the day).

This meant that Leon had to train a good amount of time to perfect his aim. It also meant that he had to go through driving training—which was mostly Emergency Vehicle Operations Courses (EVOC: safe and defensive driving for cops in other words)

I��d like to think that his determination (when he told Ada that the reason he joined the force was for people like Emma and Gunshop owner) really helped him advance through his academic route of the training and I’d like to believe that he go high scores because of that.

The 90s were a pivotal time for new policies to be introduced in police academies. When Leon was a kid, presumably during the 80s, he probably saw just how different it was back then than it is now (in 1998) lots of “new” technology were introduced to him when he first started the training. And he probably had to adapt quickly to the technologies and new techniques.

Leon is quick on his feet, he grasps a lot of things and I’m tired of people making him out to be as some dumb blonde with muscles. He’s very smart and we see that throughout the games and films.

I wouldn’t be surprised if he was GT when he grew up.

EDIT: MB YALL😭 GT is a program for students K-12 where they’re put in advanced classes like AP or IB. It stands for Gifted and Talented (something like the Magnet Program in some schools in the US)

#leon kennedy #leon s kennedy #leon scott kennedy #resident evil #re2 leon #re leon #resident evil leon #leon kennedy headcanons #re2r leon #re2 remake

479 notes · View notes