#Hire Computer Vision developers

[hiringjournal]

Top Skills to Look for When You Hire Computer Vision Developers

One of the most fascinating and quickly developing areas of technology is computer vision. Tech organizations must make sure they hire the right people to advance these projects as businesses depend more and more on image processing and real-time data interpretation. In order to create systems that can identify, process, and evaluate photos and videos and derive insightful information, computer vision developers are essential. 

Knowing the core competencies needed for a computer vision developer is crucial if you want to create innovative computer vision applications. In order to guarantee the success of your project, we examine in this article the most important competencies you should seek in computer vision engineers.

Key Expertise That Will Drive Your Computer Vision Projects to Success

Proficiency in Programming Languages

Proficiency in the appropriate programming languages should be the first qualification you look for in computer vision developers. Python and C++ are the most widely used programming languages for computer vision development. While C++ is utilized for applications requiring low latency and high performance, Python is preferred because of its ease of use, large library (including OpenCV, TensorFlow, and PyTorch), and robust community support. 

Because computer vision applications depend heavily on speed optimization, developers should also be conversant with CUDA for GPU-accelerated processing. As complicated image processing algorithms demand high speed and optimization, developers should have the know-how to construct scalable and efficient code as part of their technological toolbox.

Strong Understanding of Image Processing Techniques

It's crucial that when you hire computer vision developers they have a thorough understanding of image processing methods. The advancement of computer vision encompasses more than just picture analysis; it also includes problems like image segmentation, noise reduction, edge detection, and feature extraction. A developer should be knowledgeable about the different image processing and enhancement algorithms, such as thresholding, hough transforms, and histogram equalization.

These methods are essential for enhancing image data quality and guaranteeing the precision and effectiveness of your computer vision applications.

Expertise in Machine Learning and Deep Learning

The proficiency of computer vision developers in machine learning and deep learning is another crucial consideration. In order to identify patterns, categorize objects, and forecast results, many contemporary computer vision applications rely on model training. Developing scalable computer vision applications requires the ability to work with convolutional neural networks (CNNs) and other cutting-edge machine learning techniques.

Seek out developers with expertise in well-known deep learning frameworks like PyTorch, Keras, or TensorFlow. Building precise and dependable machine learning models for computer vision requires a solid foundation in these fields.

Experience with Computer Vision Libraries and Frameworks

Popular libraries and frameworks, which greatly accelerate development, should also be known to computer vision engineers. One of the most popular libraries for processing and analyzing images in real time is OpenCV. For more complicated tasks like object identification and classification, developers need to also be familiar with deep learning frameworks like TensorFlow and PyTorch, as well as dlib and scikit-image.

Developers can save time and money by using these frameworks to rapidly prototype and implement computer vision solutions without having to start from scratch.

Problem-Solving and Algorithm Development

Computer vision engineers should be adept at solving problems when you hire them. Developing computer vision frequently entails resolving particular issues with illumination, occlusions (when objects are partially obscured), and image quality. To develop novel solutions that can address issues in the real world, developers need to be able to think critically and creatively.

Seek out developers who can show that they can create and refine algorithms for certain tasks, such as motion tracking, facial recognition, or autonomous car navigation.

Experience in Working with Large Datasets

Working with massive datasets is frequently necessary for computer vision projects, and processing and analyzing enormous volumes of data is a critical skill. To effectively train machine learning models, developers should be able to manage massive amounts of picture and video data.

This also requires familiarity with data augmentation, which is a technique for growing datasets and enhancing model resilience.

Collaboration Skills

Lastly, it's critical to hire AI engineers who can collaborate with other teams, including data scientists, back-end developers, and product managers. Many stakeholders must contribute to computer vision projects, and good teamwork and communication are essential to the project's success.

Hire the Right Computer Vision Developer for Your Needs

In conclusion, seek out candidates who have a strong foundation in programming languages, image processing methods, machine learning, and deep learning when hiring computer vision developers. Make sure they are skilled in creating scalable algorithms and have worked with computer vision libraries before. They will also be a great benefit to your project because of their capacity to work with different teams and manage huge databases.

Hiring machine learning engineers or artificial intelligence engineers in addition to qualified computer vision experts can greatly increase the success of initiatives aimed at expanding into new markets.

[bosctech]

How Computer Vision Is Changing the Entertainment Industry

Imagine a world where your favorite film characters come alive. Games feel real, and sports broadcasts offer insights faster than we can see. This isn’t just fiction. It’s the power of computer vision. This branch of AI allows machines to understand and act on visual data. It detects faces in photos and powers self-driving cars. Indeed, computer vision is changing many industries.

Technology is revolutionizing content in the entertainment industry. It introduces hyper-realistic CGI in films and AR/VR in games. It also uses AI-driven camera angles in live sports. Computer vision is key to this revolution. To stay ahead, businesses are using custom computer vision services for tailored solutions.

Disney’s 2019 “Lion King” remake revolutionized visual storytelling. The film, which was made with photorealistic CGI, used computer vision. It brought its animals and landscapes to life. This new approach set a high standard for cinematic art. It blurred the lines between animation and reality.

By the end of this blog, you’ll see that computer vision is not just enhancing entertainment. It’s redefining its future. Let’s dive in!

What is Computer Vision?

Computer vision is a technology. It lets machines “see” and understand the visual world. Computer vision enables machines to process visual data. It uses algorithms and computers, like humans use their eyes and brains. They process images and videos.

The process is simple to understand:

A machine captures images or videos using cameras or sensors.

Algorithms analyze this visual data to identify objects, patterns, or movements.

The analysis shows the machine does specific tasks. It labels images, detects faces, and tracks moving objects.

Computer vision uses AI and ML, allowing machines to learn from large datasets. This improves their accuracy. For example, when apps auto-tag friends in your photos, they showcase this tech. This changes how we interact with visual information.

Computer vision tech empowers businesses to revolutionise applications. This advanced innovation enhances user interactions, streamlines workflows, and creates new entertainment. It offers limitless potential. Now, companies in many sectors use it to drive progress and find new opportunities.

In essence, computer vision is not just about machines seeing. It’s about making sense of what they see and acting on it intelligently.

The Role of Computer Vision in Entertainment

Technology and creativity are advancing the entertainment industry. Innovations have evolved storytelling from silent films to virtual reality. Now, artists and technicians combine modern tools with classic tales. Major technological leaps have transformed entertainment, immersing audiences in new experiences. Blockbusters featuring CGI and engaging games are now more captivating. Each innovation enhances its quality. Computer vision plays a crucial role in this shift. It transforms content creation and consumption. This technology empowers creators, elevating their stories. As technology and creativity merge, viewers enter new digital realms.

Computer vision is a natural fit for this industry. It deals with the core of entertainment — visual content. It lets creators automate tasks, create lifelike effects, and personalise content for viewers. It does this by enabling machines to understand visual data. Computer vision is key to modern innovations. It powers hyper-realistic animations, tracks movements in live sports, and enables AR. These innovations resonate with today’s audiences.

Custom computer vision development services enable entertainment companies to meet specific needs. A gaming company may use it for real-time environments. A film studio could apply it for video editing and effects. This ensures alignment with creative and technical goals.

In short, computer vision isn’t just enhancing entertainment. It’s revolutionizing it. It lets the industry deliver, like never before, experiences that inspire.

Applications of Computer Vision in Entertainment

Computer vision is changing entertainment. It enables smarter, faster, and more engaging content creation and consumption.

Film Production and Editing

Creating movies has never been more advanced, thanks to computer vision. It enables:

Automated Video Editing and Special Effects: We can now automate time-consuming editing tasks. This lets filmmakers focus on storytelling.

Motion Capture and CGI Enhancements: Actors’ movements are captured using motion capture. Computer vision creates stunning CGI effects. They bring fictional characters and worlds to life.

With custom computer vision development services, studios can create tailored solutions. They would enable seamless editing and stunning effects. Let’s explore some more exciting applications:

Personalized Viewing Experiences

Computer vision enhances how audiences interact with content by enabling:

Dynamic Scene Adjustment: It adapts visuals to user preferences, like brightness and aspect ratio.

AI-Driven Content Recommendations: Use visual data to recommend shows or movies viewers will like.

Using computer vision, Netflix and YouTube provide engaging, personalized experiences.

Gaming

Gaming has reached new heights with computer vision, offering:

Real-Time Environment Rendering: Creates immersive, lifelike game worlds.

Enhanced AR/VR Experiences: It powers AR and VR games. Players interact seamlessly with digital elements.

Gaming companies can use custom computer vision development services. These can create unforgettable user experiences.

Content Moderation and Safety

Maintaining safe and compliant content is critical in entertainment. Computer vision helps by:

Detecting Inappropriate or Copyrighted Content: Identify harmful or plagiarised visuals before they reach the audience.

Ensuring Compliance with Standards: Automating checks to align with broadcasting rules and regulations.

With tailored solutions, businesses can streamline content moderation and protect their brand reputation.

Live Sports and Events

For sports fans, computer vision elevates the viewing experience by providing:

Player Tracking and Performance Analytics: AI examines player motions, tactics, and statistics instantly.

AI-Assisted Replays and Camera Optimization: It provides the best views and replays, instantly.

Sports broadcasters can enhance live experiences with custom computer vision. This brings fans closer to the action.

Computer vision services are driving innovation in entertainment. They are making content smarter, safer, and more exciting for all.

Case Studies: Computer Vision in Action

Computer vision is advancing in entertainment. Top companies are pushing the limits of innovation. Here are some real-world examples showcasing its transformative power:

Gaming: Epic Games’ Unreal Engine

Epic Games uses computer vision in its Unreal Engine. It creates realistic gaming worlds. The engine analyses player actions, adjusting the game in real-time for better immersion. Additionally, it features AI-based character recognition. This enhances animations and interactions in popular games like *Fortnite*.

Live Sports: Hawk-Eye Innovations

Hawk-Eye Innovations uses computer vision to transform umpiring and broadcasting in live sports. The system tracks balls and players in real-time.It provides accurate decisions and instant replays. It’s widely used in cricket, tennis, and football. It improves the accuracy and excitement of live sports coverage.

Streaming Platforms: Netflix’s Personalization Engine

Netflix uses computer vision to boost its recommendation system. It analyzes thumbnails, videos, and user behavior. The platform customizes its library based on individual preferences. It considers visual elements such as colors, faces, and themes. This tailored experience increases engagement and watch time.

Industry leaders now use custom computer vision services. They aim to innovate, enhance audience experiences, and set new entertainment standards. This technology is transforming the sector. It offers realistic animation, immersive gaming, and smart content delivery.

Challenges and Limitations of Computer Vision in Entertainment

Cost and Accessibility

Developing and implementing computer vision systems can be costly. It requires a big investment in custom computer vision services, hardware, and software.

Smaller studios and startups may struggle to afford these tools. This limits their ability to compete with larger players.

Data Privacy and Ethical Concerns

The use of large amounts of visual data raises privacy concerns. This is especially true when handling sensitive user information.

Ethical dilemmas can arise in areas like deepfake technology. There, computer vision might be misused to manipulate visual content.

Processing Power and Resource Demands

Computer vision needs advanced computing power and specialized hardware. They can be resource-intensive.

For real-time apps like gaming or live sports analysis, smooth, accurate processing is a challenge.

Data Accuracy and Quality

Computer vision systems rely on good, varied training data. Biased or limited data can cause errors, like wrongly identifying objects or people.

It’s very hard to get high accuracy in complex, crowded places, like live sports venues.

Integration Complexity

Implementing computer vision solutions often requires seamless integration with existing systems. This can be time-consuming and technically demanding. This is especially true for platforms not originally designed for AI.

Regulatory Compliance

Some regions have strict data and AI regulations. They can slow the adoption of computer vision technologies.

Computer vision breakthroughs are tackling entertainment industry hurdles head-on. Careful planning and ethical vigilance unlock vast potential, driving groundbreaking innovations. Despite challenges, these advances in vision tech offer great potential. They will revolutionize entertainment.

Computer vision is transforming the entertainment sector. It’s enhancing film effects, personalizing experiences, and improving sports coverage. Despite challenges like high costs and privacy concerns, its potential sparks innovation. This allows creators to explore new possibilities. As demand for engaging, smart content grows, tailored computer vision is key to staying competitive.

Ready to elevate your entertainment projects with advanced technology? Discover our custom computer vision development services and unlock new possibilities. Let’s create something amazing — contact us today!

Content Source : https://bosctechlabs.com/how-computer-vision-is-changing-the-entertainment-industry/

[full-stackmobiledeveloper]

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[lilythelitten]

The Deviant Phenomenon

Fandom: Murdle

Summary: In a futuristic world, Irratino takes on a job he’s been wanting for a long time.

Important Tags: AU

(A/N: I read this post by @lunar-inkclipse and was struck by a vision so vivid I had to write it down. Enjoy!)

It was the strangest phenomenon. Every so often—common enough to be noticed, yet not enough to be normal—an android would glitch out and feel. Not truly feel, as TekCo representatives would assure the concerned public, merely a facsimile of real human emotion. But for all intents and purposes, those androids—those deviants, as TekCo labeled them—would experience things like sadness and anger and joy, cutting into their purely logical processing systems and giving them a sudden, rushing freedom of choice.

To Irratino, it was the most fascinating thing in the world. Even if everyone insisted it was simply faulty programming, bugs in the code that would surely be patched out next model—as if the sudden emergence of something so integral to humanity could be done without a touch of magic. He could spend hours reading up on deviants, and he’d spend more if anyone knew more. But no one did—the “deviant phenomenon” was a mystery, and there was little Irratino liked more than a good mystery.

So when, out of the blue, TekCo’s CEO called to ask for Irratino’s help in figuring out the deviance issue, he’d said yes before the man could finish talking.

“Are there any theories as to how deviance happens?” Night asked as they followed Irratino into the TekCo company headquarters, closing the umbrella they’d been carrying. They were accompanying Irratino on this job, mostly because they were the only person at the Institute who knew anything about computers beyond how to work a search bar (well, Seashell actually knew a surprising amount, but Irratino would sooner jump into the ocean fully-clothed than spend any more time around Seashell than he had to). This did, admittedly, mean the Institute would be unattended for a while, but Irratino wasn’t too worried. His employees could handle themselves for a few weeks.

(Okay, so maybe he had made them all promise not to blow up or burn down the Institute while he was gone. Hey, you could never be too careful.)

“Who can say?” Irratino said with a light shrug, the two of them walking up to the front desk. “Most people think it’s simply faulty programming. Some say it’s deliberate sabotage.”

“I’m guessing you think magic’s involved?” Night asked wryly.

“Well, there’s no proof it isn’t, so who knows? Besides, something as miraculous as a machine suddenly developing sapience, emotion, the ability to love…” Irratino giggled, doing a small twirl and clasping his hands together. “Like all of that could be just because of a system glitch.”

They’d reached the front desk by now, the receptionist too focused on her computer to notice them; her slight stature and short blonde hair looked human enough, but the colorless clothes that looked to have been painted on and blue LED light glinting on her temple made it obvious she was an android. Irratino stepped forward, clearing his throat to get her attention. “Hi,” he said, because her being an android was no reason not to be polite.

The receptionist’s eyes flicked up to him. More lights dimly glowed from her pupils, these ones a soft green. “Yes?” she said. Her voice was light, but the complete monotone made it impossible to mistake it for a human’s voice.

Suppressing a shudder—android monotone was creepy—Irratino said, “I’m Inspector Irratino. Your CEO hired me for a thing, wanted to meet with me…?”

She looked back at her computer for a few seconds, before looking up at Irratino again. “Correct. Your meeting is scheduled for today. You may proceed to the CEO’s office on the fifteenth floor.” Her cold eyes then flicked to Night, who awkwardly waved. “Your presence is not required.”

“They’re with me,” Irratino quickly explained. “They know tech stuff a…” He let out a sheepish chuckle. “Lot better than I do.”

The receptionist blinked, then returned her eyes to her computer. “I see. I will inform the CEO of this development. You two may proceed to the elevator.”

“Oh—thanks!” Irratino brightly smiled. The receptionist did not return it, staring at him with that same flat expression and cold eyes. “…uh…” Irratino’s smile faltered, and they stood in silence for a bit before Night tugged on his hand, pulling him toward the elevator. “Bye!” Irratino called out, waving. She didn’t return that either.

Night pulled him into the elevator and hit the button for the fifteenth floor, the doors closing with a ding. The second the receptionist was out of sight, Night let out a sigh, shoulders sagging. “Uuuuugh. I know it’s bad to say this, but talking with them always gives me the creeps.”

“With androids?”

“I don’t get why they have to be so lifeless. I mean, I know they’re machines, but—seeing someone that looks like a human but doesn’t act like a human is—” Night shivered. “You know?”

“Deviants act like humans,” Irratino noted, eyes flicking up to the ceiling as a deeamy note entered his voice. “Maybe meeting one of them will be less creepy.”

“Most deviants you hear about are deviant because they’ve killed people,” Night pointed out wryly. “I’d like to steer clear of that, thank you very much.”

Irratino had to suppress a snort at that. “Okay, fair.” He paused, a thought striking him. “Actually, why do most deviants kill someone? Surely, once you have emotions and free will, there are better things to do with them than to fuel a murder.”

“Who knows?” Night said, shrugging. “It’s what we got hired to figure out. Though I did some reading—some scientists suspect that it’s because of the loyalty coding.”

“The what now?”

“TekCo androids are programmed to follow the orders of whoever they view as their owner,” Night explained. “The loyalty coding ensures they do so even when orders could bring them harm. That coding gets scrambled during deviance, the androids misinterpret the signals, and…”

They made a throat-slitting gesture with their hand, and Irratino winced. “Ouch,” he muttered, just as the elevator dinged and the doors opened. They stepped out of the elevator and headed down the hallway, Irratino’s gaze locked to his shoes. Loyalty coding. Just the concept felt off, and not in a good way. The idea of being forced to take someone’s orders, no matter how harmful they were, not even able to consider refusing…it seemed wrong to him. Was that a mark of deviance? Wanting to say no? It wasn’t like it excused the murders, but it still troubled him.

“You good?” Night asked out of the blue, and Irratino startled, stumbling in his steps. “Not to pry or anything, but you’re making that ‘I don’t like what I’m thinking about but I can’t stop thinking about it’ face.”

“Oh, uh…” Irratino frowned, tucking his hair behind his ear. “I dunno. Just…‘loyalty coding’ feels weird.”

“Kinda, yeah. But I guess if the androids could refuse to work, it would defeat the purpose.”

“Yeah, yeah…” The frown deepened. ��Is it even really loyalty? If it’s been programmed in?”

“Well, androids aren’t supposed to feel real emotions at all, so I doubt TekCo cares.”

“I mean, I wouldn’t want someone to just—blindly do whatever I tell them to, you know?”

“If you did, you wouldn’t have hired us.”

“I’m aware, but—” Irratino waved his hands, trying to emphasize his point even though he wasn’t entirely sure what point he was trying to make. “I mean, what do you even do with someone who never disagrees with you?”

“I can think of something you could do,” Night said, and a small, cheeky smile pulled at their lips. “Keep a boyfriend longer than a month.”

“Ha,” Irratino deadpanned, giving them a flat stare. They didn’t look the least bit sorry; at this point, everyone had accepted Irratino’s love life really was cursed.

Luckily, any further discussion of the disasters that were Irratino’s romantic endeavors was cut short when they reached the door to the CEO’s office. Irratino reached out and knocked. “He—”

The door banged open. “Finally!” Irratino yelped and stumbled backwards; Night, to their credit, barely flinched outside a slight widening of their eyes. “What took you so long? I’ve been waiting forever!” The speaker—a man who looked around Irratino’s own age, with angular features and slicked back brown hair—threw a hand in the air at that last word, rolling his eyes. This, if Irratino wasn’t mistaken, was CEO Indigo, the man who ran TekCo Futures—and, if what Irratino had heard was any indication, the best thing to do here was to just let him rant until he ran out of steam.

Night, evidently, had not heard that. “…but we got here on time,” they said, sounding simultaneously awkward and confused.

Indigo’s head whipped to them, and they shrank back at his annoyed glare. Irratino’s shoulders tensed, ready to intervene—if Indigo started yelling at one of his employees, Irratino would have a few things to say about that—but then Indigo broke off the glare with a sharp sigh. “Right. You. Almost forgot. Whatever, just— both of you, just get in here—” And he grabbed Night’s arm and dragged them into the office, ignoring their yelp of protest. Irratino winced at the scene, silently apologizing to Night as he followed them through the door.

The room was pretty spacious, with stainless walls and polished floors, and a mahogany desk sat in the middle, one chair behind it and two in front. Behind the desk was an enormous window that took up the whole wall, the rain outside running down the glass; that window was clearly where most of the light came from, since the office was surprisingly dark.

Trying not to shudder—he really wasn’t fond of dark places, and this one had especially bad vibes—Irratino crossed the room, taking a seat in front of the desk. Up close, he noticed a woman standing off to the side, with dark hair so short it didn’t even reach her chin and an odd-looking visor, her body so perfectly still Irratino wondered if she was an android herself. Before he could think too much about that, though, Indigo stormed over with Night in tow, all but threw them into the other chair where they landed with an “Oof!” and slid into his own chair with a huff.

A few long, awkward seconds passed, Irratino fidgeting, Indigo glowering, and Night blankly staring. It wasn’t long before it was too much for Irratino to bear. “So, uh—”

“Ahem!” Indigo cleared his throat, then plastered on a friendly smile that was too wide to be real. “Wonderful to officially meet you, Irratino—can I call you Irratino?”

“Uh, sure—”

“I’m sure you already know *me*, but just to get it out of the way—” His smile turned more smug, and more genuine. “CEO Indigo. Leader of TekCo. You might recognize us, pioneers of the android technology, taking the tech world in bold new directions, kind of a big deal?” He laughed even though no one had said anything funny, then gestured to the woman. “That would be Mauve. Vice president. She’s here for all the technical details.”

“Um…hi.” Irratino awkwardly smiled and waved. Mauve did not return either.

“And I know what you’re thinking, but no—Mauve is as human as you and I are. Last I checked.” Indigo snorted. “I mean, she’s been with me before the androids were invented, so unless she’s a time traveler—”

“I am not,” Mauve said. Her voice was flat and clipped, but lacked the distinct monotone.

“And there you have it!”

Night cleared their throat, adjusting their glasses with a hand. “Well, if we’re introducing ourselves—”

“No one asked you,” Indigo said dismissively. Night’s mouth shut, and they blinked a few times, while Irratino stared incredulously. Indigo looked back at him. “Anyway—”

Irratino held up a hand. “Let them finish?” he asked, trying to hide his own growing annoyance.

Indigo stared at him, then let out an overdramatic sigh. “Fine.” He gestured for Night to speak.

“Uh…” Night adjusted their glasses again. “I’m Night. I’m a numerologist, good with numbers, Irratino brought me here because I know a bit about coding and—”

“Great, good to know—anyway!” Indigo clasped his hands together, and it was clear he wasn’t letting Night get any more words in. “Down to business.”

He straightened, clearing his throat. “As you know, our androids have been experiencing, uh…software instability that’s led to…deviations.” He said the word like it was poison, mouth twisted into a frown. “These deviants have deluded themselves into thinking they experience actual emotions, which—” He snorted. “‘Course they don’t, they just don’t do what we tell them to anymore.”

“…right,” Irratino said, unsure of what else to say (or, at least, what else to say that wouldn’t get him yelled at).

“Obviously, this whole ‘androids turning on their masters’ thing—not good for business. So!” Indigo clasped his hands together again. “When I heard you were interested in this conundrum, and were cheap to hire, I just had to get your assistance.”

“Uh…” Irratino weakly smiled. “I’m…honored?”

“As you should be! You get to help solve a problem that’s been plaguing us for weeks.”

Irratino’s smile wavered. It wasn’t just the office now—Indigo himself wasn’t giving off good vibes right now. Even if deviation was a genuine problem—and, in some ways, it was—the way Indigo spoke of the deviants didn’t feel right. Like they were just malfunctioning products, with no thoughts of their own.

Fortunately, before his discomfort could show on his face, Night cleared their throat. “So what, exactly, are we expected to do?” they asked. “Search for deviants, look through code, or…?”

This time, Mauve stepped forward. “Your objectives are to visit various deviant crime scenes, identify the deviant androids, and return them to us for study. We will be fairly hands-off with this, and you may choose where to go and what to investigate, but we expect at least some results by the end of the week.”

That seemed reasonable enough. “What happens after that?” Irratino asked.

“Standard procedure. Interrogation, examinations of code to see what went wrong.” Mauve’s voice sharpened slightly. “Once we have gotten all we can get out of the captured deviants, they are sent to the compactor, and the resulting scrap reused for other projects.”

Irratino’s eyes bulged, and his mouth fell open. He traded glances with Night, who looked about as horrified as Irratino felt. They kill deviants?! If he hadn’t gotten bad vibes from TekCo before, well, this just solidified it.

Indigo sighed. “Okay, I see those looks—guys, guys? They’re robots.” He leaned in closer, speaking slowly, like he was talking to small children. “Robots. Don’t. Feel pain.”

But do they feel fear? Irratino didn’t ask. He didn’t want to know. He didn’t want to imagine it—the impending knowledge you were going to die, the growing dread of being led to the machine, the terror of seeing the compactor get closer and closer…

Indigo sighed again, rolling his eyes and muttering something like “Olivia got it, why can’t the actual adults” before clearing his throat. “Look, just—shut off your empathy for them, okay? They’re murderers! They killed people out of a delusion they feel emotions. They don’t deserve your sympathy.”

Night mutely nodded. “I’ll keep that in mind,” Irratino mumbled; he wanted to say more, but his tongue suddenly felt too big for his mouth.

“Is…that everything?” Night asked, moving to stand up. Irratino could hardly blame them for wanting to leave—he was seconds away from running out the door himself.

“Just one more thing,” Mauve said. Irratino’s stomach sunk—that can’t be good—and Night’s mouth twisted like they were biting back a groan. “As part of our ongoing efforts to locate the deviants and fix whatever error is causing the deviations, we have created a new model of android, built specifically to locate and combat deviant models.”

“You’ll be meeting him tomorrow,” Indigo added. “Would’ve been today, and right now, but he’s been held over for extra polish.” He let out a dry chuckle. “Last thing you want is the deviant hunter to deviate, right?”

Irratino blinked. “Oh” was all he could say, because that wasn’t too bad. Working with an android? That would be an interesting experience. Maybe even fun.

“Please keep in mind,” Mauve continued, “that this model of android is an extraordinarily new prototype, and quite complex. It is the only version of itself in existence. It will return to us for routine maintenance twice a week, and we will handle repairs of any damage it suffers in the field, but it staying in good condition is paramount. If it is destroyed, we may not be able to rebuild it.”

“So don’t break it, ‘kay?” Indigo finished. “We spent a lot of money on this project, if it’s a pile of scrap before the week’s out, I am not gonna be happy.”

He would be if he was in the com— Irratino pinched himself to stop that train of thought before it could pick up steam. “Got it,” he said. Investigate the deviants, keep the android partner alive—fairly straightforward, if he ignored the horrifying implications.

“Awesome!” Indigo grinned, before dismissively waving a hand. “Anyway, you two are free to go. You’ll meet our new model tomorrow.” He grinned again. “I look forward to our working relationship.”

It was a completely innocent thing to say, but Irratino’s stomach dropped. “Yep. Me too. See you tomorrow—come on, Night—” And with that, he grabbed Night’s hand, stood up, and hurriedly left the office as fast as possible without looking strange—only when the door closed behind them did Irratino let his shoulders relax.

They headed down the hallway in silence, quietly processing everything that had just happened.

“Wow,” Night finally said.

“Wow,” Irratino agreed.

“That was…” Night waved their hands, brow furrowing. “I don’t even know what that was.”

“Creepy?” Irratino offered.

“Well, yes.”

More silence.

“So!” Irratino said with forced cheer. “Working with an android! Are you excited?”

“No.” Despite himself, Irratino almost laughed at how blunt that was. “I mean, androids can already be pretty creepy, and this one works for TekCo, and if Indigo and Mauve are any indication…” Night shrugged helplessly. “Well, I’m probably not going to enjoy any time spent around him.”

“Maybe. But hey, who knows!” This time, the cheer in his voice was genuine. “Maybe he’ll actually be really nice and we’ll all be good friends.”

“Ah, if only,” Night said, shaking their head. “I don’t think androids really get friendship. Can’t feel emotions, remember?”

“Weeeeeell…” Irratino put his finger to his chin. “They could…”

Night stopped in their tracks. Slowly, they turned to stare at Irratino, a blank “you gotta be kidding me” expression on their face. “Inspector Irratino,” they said slowly, “please do not tell me you are going to try to intentionally deviate the android.”

“…” Irratino kept walking, pointedly not answering the question.

Night let out a long-suffering sigh, briefly speeding up to keep up with him. “Well, at least you didn’t say that to Indigo. I doubt he would’ve appreciated it.”

“He certainly would not.”

They headed into the elevator, Night hitting the button for the first floor. “I will remind you, most androids who go deviant wind up killing people,” they said as the doors closed and the elevator began its descent. “And if you get attacked by a killer robot because of your own stupidity, I will not save you from getting your head chopped off.”

Irratino huffed, even as his lips twitched into a smile. “I’ll have you know, this idea was born of curiosity, not stupidity.”

“You ever hear that story about curiosity and the cat?”

“Well, satisfaction brought it back, didn’t it?”

“I’ll be sure to let you know if resurrection ever becomes a thing. Then, you can provoke all the deviations you want.”

“You’re so kind.”

“Yes, I’ve heard.”

There was a pause, before Night cleared their throat. “More seriously, considering this one is specifically built to hunt deviants, I think they’d put extra safeguards in his programming to keep that from happening. So I doubt you’d have any luck either way.”

“Yeah, I know,” Irratino said with a soft sigh. “Still a fun idea, though.”

“Kind of. Ignoring the murder.”

The elevator dinged and the doors opened, and the two stepped out into the lobby. “So,” Night said, taking out their umbrella, “back to the hotel room?”

“Sounds good to me. We probably need sleep anyway.” Irratino sheepishly chuckled. “Tomorrow sounds like it’s gonna be a long day.”

Night snorted. “Exactly.”

Irratino headed to the front door, then briefly paused. “Hey, uh…” He looked over his shoulder at Night. “Thanks for coming with me.”

Night lightly shrugged. “Well, someone has to keep an eye on you so you don’t rush into anything dangerous. And investigate the things you don’t entirely get.” A wry smile crossed their face. “And bring an umbrella because you didn’t pack one on a trip to one of the rainiest cities in the country.”

Irratino blinked, then let out a soft, sheepish laugh. “What would I do without you?”

“Lose your own head, probably,” Night said, and despite their dry tone, they were still smiling.

Irratino laughed again. “Probably.”

The two headed back out, Irratino mentally psyching himself up for what was coming tomorrow—and for the next few weeks. He was, admittedly, not much of a homicide detective, and most deviant crimes were homicides. But it would be worth it, he told himself, to learn the hows and whys of androids gaining full sapience out of the blue. And besides, he’d be doing it with a friend—maybe even two, if the deviant hunter android turned out to be nice.

It might’ve been overly optimistic, but he could hope, right?

[warningsine]

In its flawed first season, “Halt and Catch Fire” tried too hard to be the next “Mad Men.” Following four visionaries through the first decade of the personal computing revolution, the AMC series opened by introducing its Don Draper: Joe MacMillan (Lee Pace), a slick, manipulative hotshot with an IBM pedigree. It’s 1983, and he’s speeding through Texas in a black sports car when he hits an armadillo. The carnage is nauseating, but it doesn’t stop him from making it to his destination: a college lecture hall where he’s come to interrogate a roomful of male comp-sci majors about the future of their industry. The sole woman in the class arrives late. She wears military fatigues, her hair is bleached, and bratty punk music blasts through her headphones. She is the most brilliant coder in the room.

Her name is Cameron Howe (Mackenzie Davis), and she turns out to be the show’s true protagonist. Her story comes to the fore in subsequent seasons that evolve radically enough to make “Halt and Catch Fire,” which ends its run on Saturday (Oct. 14), one of the greatest TV dramas of the decade. But there’s lots of tiresome male anti-hero stuff to get through first, as Joe commandeers a local electric company and talks its best employee, timid family man Gordon Clark (Scoot McNairy), into helping him reverse-engineer an IBM. As this classic alpha-beta duo schemes and innovates, their new hire (and Joe’s fuck buddy) Cameron remains a quasi-peripheral figure. It’s the songs music supervisor Thomas Golubić (“Breaking Bad,” “Better Call Saul,” “Six Feet Under”) surrounds Cam with that offer the first hint that the show is really her story.

Cam’s punk tapes are a window into the initially taciturn character’s rebellious nature, just as her headphones are the first clue that she’s a loner. In the premiere, she’s listening to the Vandals when she gets kicked out of a video arcade for using the old coin-on-a-string trick. A few episodes later, there’s a gorgeous scene where she pirouettes through a dark, empty office with X-Ray Spex’s “Germfree Adolescents” on her Walkman. (The moment is echoed near the end of season three, where she dances—first with Joe, then alone—to Pixies’ “Velouria.”) Whether it’s an iconic band like Bad Brains or a lesser-known act like Big Boys, Cam’s always got loud, angry music in her ears while she’s coding.

Cam is a punk, but not just in the banal, myopic way the tech industry has always appropriated the aesthetic—with dropout programming prodigies, “rockstar” developers, and startups bent on ���disrupting” existing business models, all of whom share the ultimate goal of making money. She is impractical to a fault, trusting her own unruly instincts over the dictates of the market. Over four seasons, we watch her dream up everything from a friendly user interface that’s years ahead of its time and would take far too long to build, to a computer game so abstract, no one can understand how to play it. When she founds her own company, at the end of the first season, it’s called Mutiny. All of the employees live together in a house and make decisions democratically. Eventually, Cam exerts her power as Mutiny’s leader, but only to save her vision from getting absorbed into a big corporation.

From the very start, Cam’s music bleeds from her headphones into the show’s non-diegetic soundtrack. When she shows up for her first day at Cardiff Electric, the company Joe hijacks, “The Magnificent Seven” by the Clash follows her, its lyrics about the futility of the capitalist grind underscoring her ambivalence about the job. Over time, punk comes to symbolize Cam’s growing influence in the industry. It’s the official sound of Mutiny HQ, her chaotic geek haven adorned in red spray paint. Near the end of season two, the Raveonettes’ cover of Joy Division’s “She’s Lost Control” plays as she exacts public revenge on the billionaire who rips off the early online community she’s created. After Mutiny moves to California, in season three, hardcore riffs constantly reverberate through the cavernous office.

“Halt and Catch Fire” doesn’t usually hit you over the head with feminist themes, but it does subtly build an argument that women are gaining ground in a world men still control. Gordon’s wife, Donna (Kerry Bishé), initially seems like a nagging mom type, keeping her genius husband from his destiny. But she’s a genius, too; her engineering expertise becomes invaluable to Cardiff’s portable computer project, then she joins Cam at Mutiny. By the finale, Donna’s combination of technical prowess and business savvy have made her a powerful Silicon Valley venture capitalist, as well as a sort of Sheryl Sandberg figure.

Donna and Gordon Clark’s daughters, Joanie (played by Morgan Hinkleman as a kid and Kathryn Newton as a teenager) and Haley (Alana Cavanaugh and then Susanna Skaggs), are the next generation of liberated women. Cam lives with the Clarks after Mutiny moves to California, and her influence on the girls is palpable. A few quick time jumps land us in the mid-’90s by the fourth season, when the sisters are in high school. Teenage Joanie is a classic rebel, smoking cigarettes and getting into trouble and, yes, listening to punk. (The band name Shonen Knife, she explains to her father, basically means “dick” because “shonen” is the Japanese word for “boy.”) Haley is a budding web development star whose taste for PJ Harvey and riot grrrl helps her come to terms with her queer sexuality. A giddy scene midway through the season finds her bonding with her crush, a waitress, over Bratmobile and Heavens to Betsy.

Music becomes more essential to the show than ever in its fourth and final season. There are moving syncs that have nothing to do with Cam, like when an unmoored Donna gets pulled over for speeding while singing along to Pat Benatar’s “We Belong,” and when she plays Dire Straits’ “So Far Away” after Gordon’s sudden death. But the alternative, indie, and riot grrrl music Haley and Joanie listen to—Gen X’s version of the punk bands whose fierce spirit Cam helped instill in them—is the core soundtrack of these episodes. Golubić cements the connection by pairing Cam’s scenes with some of the 1990s’ most iconic female-led anthems: the Breeders’ “Cannonball,” Bikini Kill’s “Rebel Girl,” Hole’s “Doll Parts.” Just as X-Ray Spex and their peers helped pave the way for women in punk, Cam sets a precedent for girl programmers like Haley. At one point, she’s surfing the internet and stumbles upon a Cameron Howe fan page.

Perhaps the greatest thing about “Halt and Catch Fire” is that it ultimately has no real heroes or villains—only four talented, flawed people who all end up playing both of those roles at one point or another. The music is what puts us inside Cam’s mind more than any other character’s, though, and illustrates how her ideas electrify everyone who can wrap their mind around them, even when her projects fail. Her work endures like an out-of-print cassette passed from hand to grubby hand, a guidepost for like-minded young punks who walk the difficult path she cleared.

[pankukaushal]

𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐀𝐈-:

𝐖𝐡𝐚𝐭 𝐢𝐬 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 ?

Artificial intelligence (AI) refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, or solving problems.

𝐂𝐮𝐫𝐫𝐞𝐧𝐭 𝐀𝐈 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬-:

AI today exhibits a wide range of capabilities, including natural language processing (NLP), machine learning (ML), computer vision, and generative AI. These capabilities are used in various applications like virtual assistants, recommendation systems, fraud detection, autonomous vehicles, and image generation. AI is also transforming industries like healthcare, finance, transportation, and creative domains. 

𝐀𝐈 𝐀𝐩𝐩𝐬/𝐓𝐨𝐨𝐥𝐬-:

ChatGpt, Gemini, Duolingo etc are the major tools/apps of using AI.

𝐑𝐢𝐬𝐤𝐬 𝐨𝐟 𝐀𝐈-:

1. Bias and Discrimination: AI algorithms can be trained on biased data, leading to discriminatory outcomes in areas like hiring, lending, and even criminal justice. 

2. Security Vulnerabilities: AI systems can be exploited through cybersecurity attacks, potentially leading to data breaches, system disruptions, or even the misuse of AI in malicious ways. 

3. Privacy Violations: AI systems often rely on vast amounts of personal data, raising concerns about privacy and the potential for misuse of that data. 

4. Job Displacement: Automation driven by AI can lead to job losses in various sectors, potentially causing economic and social disruption. 

5. Misuse and Weaponization: AI can be used for malicious purposes, such as developing autonomous weapons systems, spreading disinformation, or manipulating public opinion. 

6. Loss of Human Control: Advanced AI systems could potentially surpass human intelligence and become uncontrollable, raising concerns about the safety and well-being of humanity. 

𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐀𝐈:-

Healthcare:AI will revolutionize medical diagnostics, personalize treatment plans, and assist in complex surgical procedures. 

Workplace:AI will automate routine tasks, freeing up human workers for more strategic and creative roles. 

Transportation:Autonomous vehicles and intelligent traffic management systems will enhance mobility and safety. 

Finance:AI will reshape algorithmic trading, fraud detection, and economic forecasting. 

Education:AI will personalize learning experiences and offer intelligent tutoring systems. 

Manufacturing:AI will enable predictive maintenance, process optimization, and quality control. 

Agriculture:AI will support precision farming, crop monitoring, and yield prediction. 

[imabeautifulbutterfly]

Choice - Chapter 2

Summary: You and Din get ready for a mission, while Din takes a moment to reflect.

A/N: Hello lovelies,

Oh I'm so excited to be posting the second chapter, as you may have noticed, the chapters are significantly smaller to how I would usually write, and this is due to time constraints. I wish I could spend hours in front of my computer typing away, but alas real life always interferes.

Hopefully, you will enjoy the second parter, I know I had fun writing it.

Love oo

Warnings: Mentions of canon-typical violence, disguises, fluff, angst, I think that's it, if I miss any warnings please let me know.

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“Djarin, I don’t know about this?” You held Grogu in your arms as you both went over the plan. Grogu’s big ears blocking your vision every so often, as he tried to look at the plans too, which only made you laugh and love the child more. He’d become more and more ingrained in your heart than you thought possible. If you were being honest, it wasn’t just Grogu that had wormed their way into your heart. 

You’d been working with the man ever since you met him, when you were hired by Boba to help him eradicate the Pikes from Tatooine, and once that crisis was done, he offered you a job, you had to say you respected his kind nature, especially the way he looked after Grogu. 

“What’s wrong with the plan?” Din looked from you to the plan, leaning closer to your side as your shoulders touched each other.

“Well …” you scratched your head as you and Grogu looked at each other, “Okay, first there are these sentries that walk around the compound like clockwork. I mean we’ve been watching them for several days, and they haven’t faltered yet. Which is unusual for out of commission storm troopers. Next, you want me to go dressed like a pregnant woman?”

He couldn’t help but chuckle a little, he loved putting you in these awkward situations, after all you could handle it, but mostly because he loved the expression on your face as you tried to wrap your mind around exactly what was needed. 

“I need a distraction”

You quirked your eyebrow as you glared at him, “Really? And that’s the best you got? Why don’t you dress up as a pregnant Mandalorian?”

“I don’t think it’ll have the same impact” he bumped her shoulder, “Plus, you have to admit, a pregnant woman in the middle of a compound, you wouldn’t think that’s distracting?”

“You’re a strange man, you know that, right?” You looked at Grogu, tickling him slightly, laughing at his tiny giggle, “Don’t you agree, your father is a strange man, little one?” Your voice was higher as you talked to him, something Din pointed out time and time again. 

“Patu” was all the response you got, and it was all you needed. 

“See even Grogu thinks you’re odd.”

He simply nodded, “Well, it’s not like I can go as the pregnant woman?” He motioned to himself as he stood, his hand sort of pointing towards his lower half. You quickly averted your gaze, after staring for a second too long, followed by a muffled chuckle from the annoying shiny helmet. 

You cleared your throat, focusing back on his statement, “Why not? I think you could pull it off, if you swing your hips the right way” you winked, smirking back at him. When he didn’t respond, a nervousness fluttered in your stomach, causing you to chew on your lips, a habit you had developed from long. 

He didn’t say anything, simply watched as you focused back on the plans, there was a nervousness in his stomach, that made his palms feel sweaty, he clenched his hands against the table focusing on the task at hand, doing his best not to be flustered by your teasing. 

Din cleared his throat, you always had a way of throwing him off, it was one of the many things he liked about you. 

When he first saw you at Boba’s palace, he couldn’t take his eyes off you, not necessarily out of attraction, but rather because you puzzled him. You didn’t exactly look like a warrior or a mercenary, you looked … well like you, a normal civilian, who simply had shown up at the wrong place and time. He could still recall, when Boba introduced you as his secret weapon, he actually scoffed to himself, thinking there was no way you could live up to any sort of reputation, but then when he saw how you handled yourself, how you fought with passion and determination, he saw your appeal, and why you were a secret weapon.

You were unassuming, and he like that about you. You were a surprise ever minute of the day. 

When Grogu rejoined him, he was impressed by how you automatically began looking after him during and after the fighting was done. You didn’t even know who Grogu was at the time, or how important he was to Din, but he could see in your eyes, the moment you laid eyes on his foundling it was like an instinct woke up inside of you. He knew at that moment, he didn’t have to worry about his child, you would live and breath for him if necessary, and all he could think was that he wanted to get to know you better. 

Next thing he knew he was offering you work, and now all that time later, having you beside him became as natural and normal as having Grogu in his life. He didn’t know if he could go back to a time when you weren’t there. 

His eyes focused on you once again, he was thankful to his helmet, he could observe you, look at you to his hearts content and you’d be none the wiser. He watched as the way your eyes moved across the plans, taking in every detail. The way your fingers stroked Grogu’s tiny hand, reassuring him, you were there and loved. The way you included Grogu in your thought process, even when you didn’t have to, it was making his heart ache, being this close and still distant from you.

He noticed your free hand was just lying there on the table, and for some reason deep within him, he watched as his own hand moved across the table, shifting closer to yours as subtle as he could wanting to hold your hand, however, before he even got the chance, you moved. 

“Well I guess if this is the plan” you initiated as you stood from your hunched over position, “I better put my game face on. Oops, sorry, I mean my belly on.” You chuckled at your own joke, Din never found your joke’s funny, he’d always just stare at you and tilt his helmet, almost saying ‘really?’ 

“Um … anyway, can you take Grogu?” You lifted Grogu, holding him out to Din. 

He simply smirked as he gave a nod, taking Grogu in his arms, chuckling to himself as he watched you purposefully sway your hips towards the bedroom of the apartment he had ‘rented.’ He focused his attention back on his son once you closed the door, as much as he wanted to keep his eyes focused on you, there was a mission to get ready for, “Alright, ad’ika, let’s get ourselves ready.”

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Tag List:

@liadamerondjarin @badbatch-simp24 @spicymcnuggies @lady-ren @firstofficerwiggles @darkangel4121 @discofern @kavecika @monako-jinn-stories @ladykatakuri @avathebestx @theroguesully @furyhellfire66 @carodealmeida @ciramaris @sprout-fics @twinkofthedink @dindjarin-mandalorian @sarcasmismyonlydefense24 @tortor-mcgee

[sarkariresultdude]

China Recruitment Results 2025: Trends, Insights, and Analysis

 As the arena's second-biggest economy, China is still a primary player within the international exertions marketplace. The today's recruitment effects from 2025 display key trends and insights across industries, demographics, and regions. Companies, activity seekers, and policymakers alike can gain from know-how these shifts, as they replicate China's evolving economic landscape, expertise priorities, and marketplace demands.

Recruitment Process In China 

1. Strong Recovery in Recruitment Activity

In 2025, China’s recruitment market noticed a incredible rebound, following years of pandemic-associated disruptions and financial uncertainty. According to statistics from a couple of human resources and exertions market tracking agencies, general job openings in China increased through about 12% 12 months-on-12 months. This growth turned into frequently driven via sectors which include generation, renewable power, superior production, and modern-day offerings, which includes finance and healthcare.

The surge in recruitment pastime is basically attributed to China’s push closer to monetary modernization and innovation, aligning with the government’s "14th Five-Year Plan" and its vision for incredible development. Furthermore, easing COVID-19 restrictions inside the past two years has revitalized domestic demand, especially in urban centers like Shanghai, Shenzhen, and Beijing, wherein expertise demand stays high.

2. Sector-by using-Sector Breakdown

Technology Sector

China’s tech enterprise stays one in every of the most important recruiters in 2025, with hiring increasing with the aid of 15% in comparison to 2024. Companies running in regions such as synthetic intelligence (AI), semiconductor production, cloud computing, and 5G/6G network infrastructure are main the demand. In precise, the AI and automation sectors skilled document-breaking recruitment, as agencies throughout numerous industries put into effect virtual transformation techniques.

Manufacturing and New Energy

Advanced manufacturing—together with robotics, aerospace, and electric vehicles (EVs)—recorded an eleven% uptick in hiring. With China striving to grow to be a global leader in EV production and inexperienced technology, recruitment in battery generation, renewable energy engineering, and environmental technology has also elevated. The expansion of sun and wind electricity initiatives in inland provinces which include Inner Mongolia and Xinjiang has opened new activity opportunities out of doors main metropolitan hubs.

Financial and Business Services

Financial offerings confirmed a moderate but consistent 7% increase in hiring, in particular in fintech, funding banking, and risk management roles. The fast adoption of virtual finance systems and the growth of inexperienced finance initiatives contributed to this upward fashion. Similarly, prison and compliance departments saw a surge in call for, as stricter regulatory requirements and international exchange dynamics precipitated corporations to strengthen their internal controls.

Healthcare and Life Sciences

China’s growing old populace and the authorities's focus on enhancing healthcare infrastructure have boosted hiring within the medical and pharmaceutical sectors. Hospitals, biotech firms, and healthtech startups elevated recruitment via nine% yr-on-12 months. Special emphasis become placed on roles associated with scientific research, clinical trials, and public fitness management, reflecting China's ambitions to beautify its healthcare resilience.

Three. Regional Disparities in Recruitment

While Tier 1 towns like Beijing, Shanghai, Guangzhou, and Shenzhen hold to dominate in phrases of activity vacancies, there was a major uptick in hiring in Tier 2 and Tier 3 towns, which includes Chengdu, Hangzhou, Xi’an, and Suzhou. The government’s urbanization strategy and nearby improvement rules are riding this shift. Inland provinces and less-advanced regions are actually attracting extra investment, main to activity advent in industries along with logistics, e-trade, and smart production.

This geographic diversification is also related to the upward thrust of far off work, as agencies come to be more bendy in hiring talent from diverse locations. As a end result, skilled specialists are now not limited to standard financial hubs and are finding competitive possibilities in rising cities.

4. Recruitment Challenges: Skills Gaps and Talent Shortages

Despite the overall high quality recruitment results, several sectors pronounced continual demanding situations, specially regarding skills shortages in high-tech and specialised fields. For instance, the semiconductor enterprise keeps to stand a essential gap in skilled engineers and researchers, while the inexperienced electricity area is struggling to find sufficient skilled task managers and technical experts.

Soft abilties consisting of leadership, go-cultural communique, and trouble-fixing also continue to be in excessive demand, mainly as Chinese organizations make bigger their global operations. Talent shortage has led to accelerated competition among employers, riding up salaries for niche roles and prompting groups to make investments extra heavily in inner schooling and improvement packages.

Five. Demographic Shifts: Youth Employment and Aging Workforce

Youth employment remains a complicated problem in China. While job opportunities for younger graduates have grown along financial recuperation, excessive competition and high expectancies hold to pose demanding situations. The countrywide young people unemployment charge stood at about 14% in early 2025, slightly decrease than in 2024 but nonetheless a subject for policymakers.

In reaction, the authorities has expanded employment subsidies, vocational education initiatives, and entrepreneurship programs focused on young human beings. Additionally, more college students are choosing internships, apprenticeships, and industry-connected educational pathways to decorate employability earlier than commencement.

Meanwhile, the getting old group of workers provides its very own set of challenges. Industries including manufacturing, logistics, and healthcare are increasingly more searching out ways to preserve older employees through re-skilling applications and flexible work preparations.

6. Trends in Hiring Practices

Recruitment practices in China are evolving, with organizations leveraging AI-pushed recruitment equipment, virtual exams, and facts analytics to streamline hiring processes. Many organizations now prioritize candidate experience, the use of era to lessen time-to-lease and improve engagement at some point of the recruitment cycle.

Campus recruitment remains a key approach for principal agencies, mainly in sectors which includes generation, finance, and engineering. However, there may be a developing desire for hiring candidates with realistic revel in, main to greater collaboration between universities and companies to offer industry-relevant guides and internships.

Diversity and inclusion are also gaining traction. Companies are increasingly dedicated to gender balance and hiring talent from numerous backgrounds, which include ethnic minorities and worldwide candidates, specially within the tech and R&D sectors.

7. Outlook for 2025 and Beyond

Looking in advance, China’s recruitment panorama is predicted to remain dynamic. The persisted improvement of emerging sectors consisting of quantum computing, biotechnology, smart towns, and the metaverse will create new employment opportunities, specially for skills with interdisciplinary ability sets.

Policy shifts, which includes similarly liberalization of the hard work market and supportive measures for small and medium corporations (SMEs), may also stimulate job advent. Additionally, the emphasis on sustainable improvement and digital innovation is in all likelihood to reshape hiring priorities, with an growing awareness on inexperienced jobs and virtual literacy.

However, geopolitical uncertainties, change tensions, and worldwide monetary fluctuations will remain key elements influencing China’s hard work marketplace within the close to destiny. Businesses and activity seekers alike will need to stay agile, adapting to changing financial situations and technological advancements.

[thebetterboogerman]

Another nice interview I found, where J.A. Laraque talks with Chris Tremmel about his time working on Boogerman and his fond memories of making games in the 90s.

I've made a copy of the interview below the divider in case the original page ever goes down! There seems to be a bit of an editing goof in the original transcript as well, so I've fixed that in my version.

There are thousands of great games across all platforms that we as gamers have enjoyed for many years of our lives, but what about the people behind them. Just as there are fans of games there are the game makers themselves who weave a concept into code to be displayed on your system of choice. Many times the idea that became the mega-hit game of the year came to the developer or designer in the middle of the night, but from there it was many sleepless nights to turn that vision into reality.

One of Obsolete Gamer’s main purposes is to get the story behind the game and we do this by speaking with the designers, developers and publishers who helped bring us oh so many hours of enjoyment. Sometimes it begins with a gamer profile where we just find out a game they like and from there a dialog starts and soon you find out all kinds of wonderful information.

This is what happened with our gamer profile of Chris Tremmel. I discovered him through his clothing store, Gamer Cultoure and when he submitted his gamer profile with the game BoogerMan I wanted to find out why he liked that game and what I found out was he was one of the main creators of it. After that I had to learn more and Chris was very accommodating in answering our questions.Gamer Cultoure logo

Obsolete Gamer: Let’s start with a little history, what was it that got you into gaming and working in the gaming industry?

Chris Tremmel: When I was a kid, my parents hooked me up with a Texas Instruments\99-4A computer. I was already a gamer thanks to PONG, and the AT2600, but the TI-99 allowed me to begin making my own games! I think I started with “porting” my choose your own adventure books into interactive form.

Obsolete Gamer: When did you begin working at Interplay?

Chris Tremmel: I officially started working at Interplay in 1992 I believe. It’s funny because I first interviewed for a tester spot. I didn’t get the job because my “autoexec.bat, and config.sys” knowledge was a bit rusty. I went home, studied up, and returned for a 2nd interview a month or two later. This time I got the job. The 1st games I tested were the original Alone in the Dark on PC, and the Lost Vikings on the Amiga.

Obsolete Gamer: Who else did you work with primarily at Interplay?

Chris Tremmel: I initially worked in the testing department but quickly made friends with a couple of designers and producers, primarily Mike Stragey and Alan Pavlish.

Obsolete Gamer: What was it like working for them?

Chris Tremmel: I hate to sound really cliche’, but working at Interplay in 1992\1993 was “magical”. I was in awe of everything being made and was thrown right in to working with some of the brightest people I have ever had the pleasure of meeting and working with. It was an amazing time as I was being taught my core design fundamentals by great guys like Mike and Alan. I knew this is what I wanted to do forever.

Obsolete Gamer: When did you first start working on Boogerman?

Chris Tremmel: I believe we started Boogerman in early 1993? It’s hard to remember exactly.

Obsolete Gamer: Who else worked with you on Boogerman?

Chris Tremmel: My boss, and the man that hired me out of test Michael Stragey. Also Alan Pavlish was the executive producer who we would run stuff by on a regular basis. We also worked with an external animation house called Little Gangster, as well as some in-house artists, and additional programming support, but primarily it was Mike and myself.

Obsolete Gamer: How did you come up with the concept and story behind Boogerman?

Chris Tremmel: Interplay came to Mike and said “we want to make a gross-out game that appeals to the Garbage Pail Kids demographic.” Interplay logo

Obsolete Gamer: Can you tell us a little bit about the development process?

Chris Tremmel: Conceptually we knew we wanted to make a “gross” game. Mike came up with the idea of a gross Superhero and off we went! The ideas just starting pouring out from Michael and myself, I would say we were never short of ideas for characters, locations, etc.

As for the design of the characters, we worked very closely with Little Gangster and went through dozens of designs until we finally settled on what you see today. Funny enough, several of the bosses in the game including the main boss BoogerMiester were originally design concepts for Boogerman himself.

Obsolete Gamer: When Boogerman was ready to launch did you believe you had a hit on your hands?

Chris Tremmel: Ya know, this is a weird thing… I was so new to the industry and so excited and stoked every day to be making games that I never really thought about “hits”. We knew we had something fun, and we knew people responded to the content the way we wanted, so that was enough for me. I still remember our very 1st magazine preview EVER. It was in Diehard Gamefan, they dubbed it an “instant classic”, we were happy.

Obsolete Gamer: Now some gaming sites and magazines game you high marks while others gave you more middle of the road scores. Do you think they just didn’t get it or what was the disconnect?

I think we were pretty happy with the reviews. We had some serious competition that year with Earthworm Jim being released at the same time. I think Boogerman got the scores it deserved, it was a good game, just not everyones cup of tea.

Obsolete Gamer: What was your feeling about winning the grossest character of 1994 award from Electronic Gaming monthly?

Chris Tremmel: Honored for sure. The entire Boogerman universe is still very close to our hearts to this day (Mike and myself). I still believe the franchise has a lot of potential.

Obsolete Gamer: Was there a plan to make more Boogerman related games?

Chris Tremmel: Yes, absolutely. AND a cartoon. The cartoon was actually started, at least script writing, character design, etc. but I believe in the end Universal went with the Earthworm Jim cartoon that was in development at the same time. Which btw, I am a massive EWJ fan and I loved loved loved the cartoon.

There were clocks made, t-shirts, and even a Boogerman phone. In addition we DID start the sequel on the Sega Saturn. We had a basic design document done and had contracted some amazing matte painters to start working on backgrounds. Unfortunately, it never came to fruition. Michael and myself left Interplay to pursue work with another company, I think we both wish Boogerman 2 could have been made. We had some really fun ideas.

Obsolete Gamer: How was it to see Boogerman released for the virtual console in 2008?

Chris Tremmel: Neither Mike or myself were involved in this. I believe this happened after Interplay changed hands. We were incredibly happy to see it up there though, downloaded it immediately!

Obsolete Gamer: Did you play Boogerman a lot yourself and do you still play it today?

Chris Tremmel: Absolutely! Mike and I both played all the time while making the game, AND after the game was released. Out of all the games I have made, this one probably got played the most. I definitely still bust it out once or twice a year. I like looking back and try to figure out what the heck I was thinking with a particular layout, or just to laugh at some of the character designs. Lot’s of laughing during the development.

Obsolete Gamer: After Boogerman what came next for you?

Chris Tremmel: Mike and I left Interplay to make a game for EA based on a Saturday morning TV show called “Bump in the Night”. Unfortunately this game was never finished\released, although we did have a rad demo running on the Saturn. I ended up at Virgin Interactive after that working on the N64.Gamer Cultoure dog tag

Obsolete Gamer: Can you tell us a little about Gamer Cultoure?

Chris Tremmel: Sure! Gamer Cultoure is a side project I have started that is clothing centric. It’s really a basic line of T-shirts, hoodies, etc. that are gaming themed. The line is really small right now, but I intend to continue to grow it over the next year or two. After leaving Activision early in the year I decided to take a little time off and try something different for a little while. It has been a fun, rewarding process for sure.

Obsolete Gamer: What do you think of gaming today in comparison to gaming back in the early to mid nineties?

Chris Tremmel: Oh no, this is a loaded question. It is definitely different. The process has become more complicated, usually requiring a large number of people to make something significant. The money involved in some of the triple A games is staggering with some budgets now reaching 100 million dollars. That naturally changes everything in terms of peoples priorities, and agendas. Sometimes for better, sometimes for worse. One of the nice things though as of late is seeing the rise of the “indie” studios, small teams executing on great ideas. It is very easy to get distracted now a days when making something. The bar has been raised so high, and with so much money involved it takes some serious planet-aligning powers to take something killer to market. All of that being said, I hope the younger guys and girls that are in the industry today feel the same sense of magic that I felt in 1992.

Obsolete Gamer: Are you working on any video games at the moment?

Chris Tremmel: As of right this second, no. Expect that to change very soon. I will definitely keep you posted any news.

I quickly wanted to give a shout out to all the people I worked with at Interplay. Thanks Mike, Alan, Brian, Rusty, Tim, Burger, Kerry, and way too many more to list. All of you guys helped me get started on this amazing journey and I appreciate it to this day.

Obsolete Gamer would like to thank Chris Tremmel for taking the time to answer our questions.

[hiringjournal]

In-House vs. Remote: What’s the Best Way to Hire a Computer Vision Engineer?

Computer vision has been reshaping industries from facial recognition, autonomous vehicles, to medical imaging and retail analysis. As demand proliferates, so does the challenge to find the right experts. Whether a startup or a growing tech company investing in AI, the key question in the picture is: should you opt to hire remote developers or in-house professionals for computer vision roles. 

Both options offer their own pros and cons, but the best choice depends on your project scope, budget, and team structure. To understand this in more detail let’s read furthermore.

In-House vs. Remote: What’s the Best Way to Hire a Computer Vision Engineer?

Let’s first explore the traditional and most-preferred hiring approach of in-house developers. Hiring computer vision engineers in-house brings obvious advantages, especially when your project involves ongoing development, close collaboration, or sensitive data. 

Having a dedicated engineer on-site will make it easier to coordinate with product managers, data scientists, and developers. You must opt for in-house when:

You must work closely with cross-functional teams.

The project is crucial to your roadmap for products.

Working with sensitive or private datasets.

You intend to make long-term innovation investments.

An internal computer vision specialist can fully own the design of the vision system, contribute continuously to the tech stack, and become a part of the corporate culture.

Why Remote Hiring Is Gaining Ground

Unlike advancements in technology, hiring approaches have also evolved, especially post-pandemic. Hiring remotely from a global talent pool has become a preferred approach among several tech companies and startups. 

Many tech companies now prefer to hire AI engineers remotely - especially when looking for rare or specialized skills. Remote hiring offers you access to a global talent network, growing your chances of finding the exact expertise you need. Go remote when:

For a particular use case, such as object tracking or picture segmentation, you require a specialist.

Hiring time is crucial or limited.

You're operating on a tight budget.

You desire flexibility without committing to anything long-term.

Hiring remote developers lowers overhead expenses, particularly in the fields of AI and machine learning. In many areas, pay can be lower without compromising quality, and there's no need to move staff or offer office space.

Consider Hybrid or Project-Based Models

Sometimes combining the two is the best course of action. As you gradually assemble an internal team, you may hire a remote engineer for temporary project or consulting work. This enables you to make rapid progress while developing long-term skills.

Depending on the size of the project, many teams also employ ML or AI engineers to collaborate with computer vision experts. A flexible model keeps your core staff small and concentrated while filling in gaps.

Tips for Hiring the Right Talent

Hiring the best candidate, whether in-house or remote, necessitates having a thorough grasp of your requirements. Identify the precise issues you wish to resolve, such as video analytics, facial recognition, or image classification, and compare them to the engineer's background.

Look for the following when hiring computer vision engineers:

A solid foundation in PyTorch, TensorFlow, OpenCV, or Python.

Knowledge of practical applications (not simply scholarly research).

Case studies or a portfolio demonstrating quantifiable impact.

Excellent communication abilities, particularly for jobs requiring remote work.

Screening for collaborative style is also beneficial. Working across time zones with platforms like Slack, GitHub, and project boards requires self-motivation and comfort on the part of remote engineers.

[daisygrace9871]

Why Quytech Is Trusted by Enterprises to Hire AI Developers

In today’s digital world, Artificial Intelligence (AI) is changing the way businesses operate. From improving customer service with chatbots to automating business processes, AI is making a big impact. But to get the most out of AI, companies need skilled and experienced AI developers. That’s where Quytech comes in.

Quytech has become a trusted name among enterprises when it comes to hire AI developer services. With a strong portfolio, skilled talent, and client-first approach, enterprises choose Quytech to hire AI app developer, build smart solutions, and stay ahead in the competitive market.

1. Proven Track Record in AI Development

Quytech has over a decade of experience in software development and has successfully delivered many AI-powered projects across industries like healthcare, finance, eCommerce, real estate, logistics, and more. This track record builds confidence among enterprises looking to hire AI engineers with real-world experience.

Whether it's building predictive analytics solutions or creating virtual assistants, Quytech’s team has done it all. That’s why businesses globally hire dedicated AI developers from Quytech to build reliable and scalable AI solutions.

2. Access to Pre-Vetted and Skilled AI Talent

Finding and hiring skilled AI talent is a challenge for many enterprises. Quytech solves this problem by offering access to a pool of pre-vetted AI programmers. Each developer is tested for their technical, logical, and problem-solving abilities.

When you hire AI programmers from Quytech, you’re getting experts in machine learning, deep learning, NLP (Natural Language Processing), computer vision, data science, and more. Whether you're working on a smart chatbot or a complex recommendation system, Quytech has the right AI talent for your needs.

3. Flexible Hiring Models

Every business has different needs, and Quytech understands this. That’s why they offer flexible hiring models. You can hire remote AI developer on an hourly, part-time, or full-time basis. This helps enterprises scale their teams quickly without going through a lengthy hiring process.

Whether you're a startup building an AI-powered MVP or an enterprise expanding your digital capabilities, Quytech provides you the freedom to choose a hiring model that suits your budget and timeline.

4. Expertise in Multiple AI Technologies

AI is a vast field, and Quytech’s developers are skilled in using the latest tools and frameworks. Their expertise includes:

Machine Learning with Python, TensorFlow, and Scikit-learn

Natural Language Processing (NLP) using NLTK, spaCy, and GPT-based models

Computer Vision using OpenCV, PyTorch, and YOLO

Deep Learning with Keras and TensorFlow

AI Integration with mobile apps, IoT systems, and enterprise software

This wide range of expertise makes Quytech the go-to choice for companies that want to hire AI app developers in India who understand modern tech stacks and deliver results.

Read More:- Why Quytech Is the Best Partner to Hire AI Developers from India

5. Trusted by Global Enterprises

Quytech has worked with over 500 clients globally, including startups, SMEs, and Fortune 500 companies. Clients from the USA, UK, Europe, Middle East, and Asia choose to hire AI developer in India from Quytech because of their professional approach and timely delivery.

Their client retention rate is one of the highest in the industry, proving that Quytech is not just a vendor, but a reliable technology partner.

6. Transparent Communication and Project Management

Effective communication and transparency are important for project success. Quytech uses tools like Jira, Trello, Slack, and Zoom to keep clients updated throughout the development process.

When you hire AI app developer from Quytech, you also get a dedicated project manager who ensures everything runs smoothly. Regular updates, real-time collaboration, and milestone tracking help maintain clarity and build trust.

7. Cost-Effective AI Development Services

Hiring in-house AI developers can be expensive, especially in regions like the US or Europe. By choosing to hire Indian AI developers for hire, enterprises can significantly reduce costs without compromising on quality.

Quytech offers affordable rates, especially for businesses looking to hire remote AI developer or hire AI engineer in India. Their cost-effective hiring model is ideal for both short-term tasks and long-term AI product development.

8. Quick Team Setup and Onboarding

Time is money in the tech world. Quytech understands the urgency and helps enterprises onboard developers quickly. Once you share your requirements, their recruitment and tech team identifies suitable profiles and sets up interviews within 48-72 hours.

This speed and efficiency make Quytech the best destination to hire AI developers without wasting time on long hiring cycles.

9. Dedicated AI Teams for Enterprise Projects

For large-scale enterprise AI projects, Quytech offers dedicated AI teams. These teams include AI developers, data scientists, UI/UX designers, testers, and project managers who work together to bring your vision to life.

Enterprises that want full control over the development process prefer Quytech’s dedicated team model. It offers better productivity, accountability, and project alignment.

10. Excellent Post-Development Support

Building an AI solution is just the beginning. Maintaining it, updating it with new features, and ensuring it runs smoothly is equally important. Quytech provides post-development support and maintenance to keep your AI product up-to-date.

This ongoing support makes businesses come back to Quytech when they need to hire AI developers for new phases or upgrades.

Why Enterprises Prefer Indian AI Developers

Many enterprises worldwide are now looking to hire AI developers in India for the following reasons:

High Talent Pool: India has a large number of skilled developers in AI, ML, and Data Science.

Cost Advantage: Hiring Indian developers costs significantly less than hiring locally in the US, UK, or Europe.

English Proficiency: Most Indian developers are fluent in English, making communication easy.

Time Zone Benefits: Indian teams can work in multiple time zones, offering round-the-clock productivity.

If you're looking for reliable Indian AI developers for hire, Quytech offers the best combination of quality, cost, and communication.

Final Thoughts: Hire the Best AI Talent with Quytech

AI is shaping the future of digital transformation, and having the right team makes all the difference. Quytech’s client-centric approach, proven AI expertise, and flexible hiring models make it a top choice for businesses looking to hire AI developers.

From startups to global enterprises, companies trust Quytech to hire AI app developers in India who can turn complex ideas into working products.

So, if you’re planning to develop an AI-powered solution or expand your existing product, Quytech is your ideal technology partner. Whether you want to hire dedicated AI developers, hire AI programmers, or hire AI engineers, Quytech has everything you need under one roof.

[digitalsoftwareproductreviews]

Teslar AI Review

TESLAR AI of Features

TESLAR AI is a company that specializes in developing and deploying autonomy at scale in vehicles, robots and more

They believe that an approach based on advanced AI for vision and planning, supported by efficient use of inference hardware, is the only way to achieve a general solution for full self-driving, bi-pedal robotics and beyond

TESLAR AI has developed a general purpose, bi-pedal, autonomous humanoid robot capable of performing unsafe, repetitive or boring tasks

They are also building the software stacks that enable balance, navigation, perception and interaction with the physical world

TESLAR AI is hiring deep learning, computer vision, motion planning, controls, mechanical and general software engineers to solve some of their hardest engineering challenges

They have also built AI inference chips to run their Full Self-Driving software, considering every small architectural and micro-architectural improvement while squeezing maximum silicon performance-per-watt

They have built AI training chips to power their Dojo system

They are designing and building the Dojo system, from the silicon firmware interfaces to the high-level software APIs meant to control it

They are also applying cutting-edge research to train deep neural networks on problems ranging from perception to control

[connect-infosoft-technologies]

What Is a Computer Vision Engineer? Unlocking the Power of Sight in Machines

In today's rapidly evolving technological landscape, one of the most remarkable areas of development is computer vision. As humans, our ability to perceive and understand the visual world around us is a fundamental aspect of our daily lives. Similarly, the field of computer vision aims to enable machines to interpret and understand visual data. At the heart of this fascinating domain lies the computer vision engineer, an expert who plays a crucial role in unlocking the power of sight in machines. 

In this article, we will delve into the world of computer vision engineering, exploring the responsibilities, skills, and potential applications of this field.

Understanding Computer Vision Engineering:

Computer vision engineering encompasses the design, development, and deployment of systems that enable machines to gain an understanding of visual data. The primary goal of computer vision engineers is to create algorithms and models that can accurately interpret images and videos, replicating human visual perception to some extent. By using artificial intelligence (AI) techniques such as machine learning and deep learning, computer vision engineers equip machines with the ability to analyze, recognize, and make decisions based on visual information.

Responsibilities of a Computer Vision Engineer:

The responsibilities of a computer vision engineer are diverse and demanding. They involve working with large datasets, developing and fine-tuning complex algorithms, and collaborating with cross-functional teams to implement computer vision solutions. 

Some key responsibilities include:

1. Data Collection and Preprocessing: Computer vision engineers gather large volumes of visual data and preprocess it to enhance the accuracy of subsequent analysis. This often involves tasks such as data labeling, augmentation, and cleaning.

2. Algorithm Development: Computer vision engineers develop and optimize algorithms that can detect and recognize objects, people, gestures, and other visual cues. They leverage machine learning techniques, such as convolutional neural networks (CNNs), to train models on labeled data and improve their ability to make accurate predictions.

3. Model Evaluation and Optimization: Computer vision engineers evaluate the performance of trained models, fine-tuning them to achieve higher accuracy and robustness. They employ techniques like transfer learning and regularization to enhance the models' generalization capabilities.

4. Integration and Deployment: Once the computer vision systems are developed, engineers work on integrating them into real-world applications. This involves optimizing the models for efficiency, scalability, and compatibility with hardware and software frameworks.

Skills Required:

Becoming a proficient computer vision engineer requires a combination of technical skills and domain knowledge. Some essential skills include:

1. Programming: Proficiency in programming languages such as Python, C++, or MATLAB is crucial for implementing computer vision algorithms and working with relevant libraries and frameworks like OpenCV, TensorFlow, or PyTorch.

2. Mathematics and Statistics: A solid foundation in linear algebra, calculus, probability, and statistics is necessary to understand the mathematical underpinnings of computer vision algorithms and models.

3. Machine Learning: Familiarity with machine learning concepts and techniques is vital for training and fine-tuning models. Understanding topics like supervised and unsupervised learning, neural networks, and optimization algorithms is essential.

4. Image Processing: Knowledge of image processing techniques, such as filtering, segmentation, and feature extraction, allows computer vision engineers to manipulate and enhance visual data before feeding it into models.

5. Problem-Solving and Critical Thinking: Strong problem-solving and critical thinking skills enable computer vision engineers to tackle complex challenges and devise innovative solutions.

Applications of Computer Vision:

Computer vision has many uses in numerous industries. Some famous examples are:

1. Autonomous Vehicles: Computer vision enables self-driving cars to perceive and understand their surroundings, identifying objects, pedestrians, traffic signs, and lane markings to make informed decisions.

2. Healthcare: Computer vision aids in medical imaging analysis, assisting with tasks like tumor detection, disease diagnosis, and surgical planning. It also facilitates remote patient monitoring and analysis of vital signs.

3. Retail and E-commerce: Computer vision is used for product recognition and visual search, allowing customers to find similar products based on images. It also enables automated inventory management and checkout processes.

4. Security and Surveillance: Computer vision systems enhance security by detecting and tracking suspicious activities, recognizing faces, and analyzing video footage for real-time threat detection.

5. Augmented Reality (AR) and Virtual Reality (VR): Computer vision is instrumental in AR and VR applications, overlaying digital information in the real world or creating immersive virtual environments.

Conclusion:

Computer vision engineering is an exciting and rapidly evolving field that empowers machines with the ability to perceive and understand the visual world. By leveraging AI and machine learning techniques, computer vision engineers unlock the potential for machines to analyze, interpret, and make decisions based on visual data. With applications spanning industries like automotive, healthcare, retail, security, and entertainment, the impact of computer vision is revolutionizing our lives. As technology continues to advance, computer vision engineers will play an increasingly vital role in shaping the future of intelligent machines.

[luanderson7a]

THE CREATOR OF GOOGLE

The story of the creator of Google begins with two brilliant computer scientists, Larry Page and Sergey Brin. They met at Stanford University in 1995 while pursuing their Ph.D. degrees in computer science.

Larry Page, originally from Michigan, had a strong interest in computers from a young age. He was fascinated by the idea of organizing vast amounts of information and making it accessible to everyone. Sergey Brin, born in Russia and raised in the United States, had a similar passion for computer science and technology.

In 1996, Larry and Sergey started working on a research project together. Their goal was to develop a search engine that would revolutionize the way people find information on the internet. They believed that existing search engines at the time were not efficient enough and wanted to create something better.

The breakthrough came in 1998 when they developed an algorithm called PageRank. This algorithm ranked web pages based on their relevance and popularity, revolutionizing the way search engines worked. They named their search engine "Google," derived from the mathematical term "googol," which represents the number one followed by a hundred zeros.

Google quickly gained popularity due to its accurate and efficient search results. Larry and Sergey decided to drop out of their Ph.D. program to focus on developing Google further. They received funding from various investors, including a significant investment from Andy Bechtolsheim, co-founder of Sun Microsystems.

As Google continued to grow, Larry and Sergey hired talented engineers and employees to help expand the company. They introduced new features like Google Images, Google News, and Google Maps, making it more than just a search engine. Google became a household name and the go-to place for information on the internet.

In 2004, Google went public, making Larry and Sergey billionaires overnight. However, they remained committed to their vision of organizing the world's information and making it universally accessible. They continued to innovate and introduced products like Gmail, Google Chrome, and Google Drive.

Today, Google is one of the most valuable and influential companies in the world. Larry Page served as the CEO of Google's parent company, Alphabet Inc., until 2019, while Sergey Brin served as the President. They have both stepped down from their leadership roles but remain involved in the company as board members.

The story of the creator of Google is a testament to the power of innovation, determination, and the belief that technology can change the world. Larry Page and Sergey Brin's vision has forever transformed the way we access information and has made Google an integral part of our daily lives.

ALUNOS

LUANDERSON

RHAONE

TURMA: 7 ANO A

[elliottsmithtookestrogen]

Yeah fr, like even when you look at the history, particularly in the United States, of capital and the state starting to have large interests(esp thinking of DARPA, the Defense Advanced Research Projects Agency) in and funding computing, and ai by extension, during and after world war II, you realize that the war economy never left - its mechanizations just got placed onto surplus populations either subsumed under the nation or the global south.

Reminds me something that the capitalist Peter Thiel, a cofounder of Paypal said about AI in 2019:

"Forget the sci-fi fantasy; what is powerful about actually existing AI is its application to relatively mundane tasks like computer vision and data analysis . Though less uncanny than Frankenstein's monster, these tools are nevertheless valuable to any army -- to gain an intelligence advantage, for example... No doubt machine learning tools have civilian uses, too."

In the aughts, he went on to found an AI/data analytics firm called Palantir that initially received funding and was hired by federal military and intelligence agencies to build out large systems of surveillance. It later moved into serving hedge funds, banks, and corporations. When Thiel was an advisor during the Trump administration, Palantir also designed the databases and software that drove the mechanics of deportation for ICE in addition to the mechanics of expelling large numbers of people off of Medicare allegedly suspected of fraud.

It goes without saying that as long as the people who fund and design ai models think about the world under terms of risk, these models will always simply intensify already existing disparities and political-economic arrangements. If developed and utilized by the racial capitalist state, fraud is the core feature of ai - managing risk and to maximize profits before all else. Financial institutions like health insurance companies, like other instruments of capital, are designed to separate the deserving from the undeserving, a binary that is sociologically ingrained, conditioned by neoliberal conceptions of eugenics and austerity.

While yes, what UnitedHealthcare is doing is fucking atrocious, I come across similar stories constantly and it is important to also interpret this as one drop in a bucket underpinning, while intensifying, the structural violence of everyday life that warrants the abolition of capital and the binary between who is deserving and who is redeemable.

UnitedHealthcare, the largest health insurance company in the US, is allegedly using a deeply flawed AI algorithm to override doctors' judgments and wrongfully deny critical health coverage to elderly patients. This has resulted in patients being kicked out of rehabilitation programs and care facilities far too early, forcing them to drain their life savings to obtain needed care that should be covered under their government-funded Medicare Advantage Plan.

It's not just flawed, it's flawed in UnitedHealthcare's favor.

That's not a flaw... that's fraud.