#Computer Vision System Online Help

[typewritingyip]

The Arcturus Missions

Part Thirty - Instinct

Part Twenty-Nine

———

Communication, defined as the imparting or exchanging of information or news. Also defined as the means of sending or receiving information, such as phone lines or computers. 

The transmission of information, whether from person to person or person to thing of other species or from person to technology and back again. It’s a generally understood foundation of society, whether through vocalization or other non-verbal signs. 

Communication has evolved over time, exchanging information for generations and invocation has expanded the definition. Whether with writing systems, radio, and exchanging data through computers or relay satellites. 

A loss of communication can be a striking blow, whether it’s someone cutting another person off or the loss of an entire crew of pilots, it hits the soul hard. 

MECHA had lost communication with five pilots and was maintaining the lie of remaining in contact with Arcturus One for the very reason, it is a striking blow to lose contact with someone.

A relay satellite had been set up with the crew, so that were anything to happen to them as was expected, the retrieval of data would eventually reach Earth.  

What was not expected was the relay satellite to be set up thirty light years away from Earth, there was no precedent for that. 

Unknown timeframe for reconnection. The number in command back on Earth kept growing larger. 

—

The attack had started just before sunrise, now the sun had set and most of the other mecha had been recalled for a retreat to form a line of defense. Dozens of unfamiliar mecha were coming in from the city to defend it and honestly, Hound had never seen anything like it.

He was crouched behind some cover in the field still, checking through his systems to get his arm fully back online now that he had not only some basic cover but covering fire. Had Megatron screamed in his ear to get back towards the line, yes, but were his implants and suit practically screaming at him to keep going also yes. So now he was crouched just behind a rock while he was going through parts of his suits data. 

This had never been his strong suit, usually Hound left it up to the techs back at base, but right now he needed access to some of his old tech that the engineers had said was too difficult to remove. Like actual night vision for his cameras, not the overlay they claimed he needed. 

Each suit for Arcturus had gone through a massive overhaul to prepare for space, the engineers back home figured there would be some kind of space battle or something but instead they were fighting on foreign planets.

All the air tight seals and things were tremendously helpful, especially for places that had toxic atmospheres like most of the planets in the Archa system, but a lot of the planet side protocols had been disabled. Hound had been working at it but in the six months they’d be fighting, he hadn’t really had to fight at night. At least this many Quintessons. 

His comm crackled briefly, “Hound, you need to move.” Mirage was the only one currently connected to his comm, as every time he went to the main line his translator had a hard time and Megatron was shouting painfully loudly, “I need a moment Mirage,” several gun blasts went just over his head, before his suit learched and he brought his cameras back up. 

Now he was fighting with his screens while tangled up in a Quint he didn’t see coming, swearing loudly, one more blaster shot whistled past his audio pickups before Mirage spoke again, “I’m not going to have a clear shot, heading your way.” Hound flung back his good arm, hitting the Quintesson in the beak, “No, no stay back there. I’ve got this.” He could hardly see what he was fighting. 

The dragging seconds felt like minutes, trying to fight off the alien while closing out the issues with his suit, “Goddamnit, just work you hunk of junk!” His arm was still coming back online, one of his screens was searching for the night vision mode, and he was fighting the Quintesson that had wrapped its tentacles around him.

This was not how he wanted today to go.

Digging his gun into the Quint’s body, he fired in rapid succession, splatting his mech with green blood and guts. It screamed and Hound yelled, digging his good arm into it and tearing it apart, pulling the remains off. 

It was only then that he was nearly blinded as his world erupted in a bright green, turning the near pitch black landscape into the familiar sand dunes of earlier that day, covered in the enemy, “Oh.” His neck tingled and burned as other more dormant systems started to come online, bringing the world outside more into focus than it had been in years, “Oh no.” he took a breath and raised his gun, before stalking towards the next Quintesson. 

—

If he were being honest with himself, the shot that had shattered his visor was slightly terrifying, but Sunny was anything but honest with himself when he needed to focus. 

The shuttle was loaded and he lowered himself to the seat next to Bluestreak, sighing slowly, “So, it’s all sand?” Blue shrugged slightly, taking apart and cleaning his rifle now though his hands were shaking lightly, “Not all sand, but most of it.” Nodding a bit, Sunny leans back and closes his eyes.

”I bet Hound is having a blast then.” Blue hums but then looks over, “Why do you say that?” Sunny chuckled lightly, “He was stationed in a few sandy places over the years, way back when he first became a pilot, even before he was a pilot.” Sunny adjusted his microphone and disconnected from his suit with a groan.

His suit sank slightly in its seat ever so slightly and Bluestreak chuckled slightly, “Not sand like here, like nothing but sand.” Sunstreaker smiled, tugging his microphone close, “Yeah, I know what you mean. All of Earth doesn’t look like Florida.” Eyes still close and helmet off, he couldn’t see the weird look that Bluestreak shot him.

Blue shifts and clears his throat, “Sunny, you’ll have to explain Earth to me a bit more, it doesn’t look like where we spent the last day?” Sunny sighed but smiled, “Not all of it, and not every country either.” He yawned and stretched on his chair, grabbing the water pouch nearby.

Before Bluestreak could ask another question, the shuttle shook and started to rise, then Ironhide’s voice came over the speakers, “Alright mechs, this is the moment we’ve been dreading. Get any rest you need now, fuel if you have to, but I expect a silent shuttle for the next few hours. Either you're eating, sleeping, or shutting up.” There was a quiet murmur around, “The Quintessons are invading New Kaon, it’s going to be a long while before any of us get a break because the prime is going.”

Half the shuttle groaned and the rest were swearing, Bluestreak lowers his head with a quiet curse.

Sunstreaker frowns a bit, keeping his voice quiet, “What’s wrong with Joan coming along?” Bluestreak glanced over, keeping his own voice low, “Either means it’s bad or something bad has happened. Ironhide didn’t say, so it’s probably both.” Sunny sat there for a moment, frowning, “You going to be alright Blue?” Bluestreak nodded a bit, taking his limp hand, “Yeah, yeah it’s just, none of us want this to get as bad as last time.” And there was a tone to what he said that made Sunny worry his lip.

He had to bite back what he was thinking, ‘I think it already is.’ Instead, he sent a ping to Blue as he got up, connecting the camera with a sad smile, “Get some rest Blue, we’re going to be here for a bit.” Bluestreak hummed and leaned his head against Sunny’s shoulder, or the shoulder of his suit. 

No one was saying anything, most trying to bunk down to sleep, and a few were eating. 

Nothing good could come from an attack on New Kaon. 

—

This was probably the most awkward situation Breakdown had been in since he first moved to the United States. Sat on a shuttle craft with the hustle and bustle that was apparently normal for a Prime, while being told to just stay and wait. 

People were coming and going while he was just sitting there in his mech, it felt weird, being connected again even though it hadn’t even been the two full weeks he was supposed to take. Not like before, when it had been months without his suit while it was being prepped for this mission. 

It was simply that this time felt off and it was hard to place. 

Breakdown had to try very hard not to bounce his foot, sitting back heavily in both his piloting chair and the seat of the shuttle. Sighing deeply, he rubs his face tiredly. That was the one thing still lingering, how tired he was. 

Another mech brings on yet another crate before they finally start to strap it all down, Breakdown watched out of one of his secondary cameras and slowly a few different mechs came aboard.

Optimus Prime was still the most distinct out of all of them and he looked pissed, talking quietly with Elita-One before she bowed her head and moved towards the front of the ship.

Breakdown lowered his head and stared at his feet, hands clenched awkwardly at his sides, after a moment someone clears their throat and he looked up. Optimus was wearing his battle mask, but it was easy to tell that he was giving an awkward smile, “Breakdown, how are you feeling?” He gawks for a second then shifts his weight, “Uh, better, better thank you sir.” He clears his throat painfully. 

Optimus’s smile relaxed a bit, “Optimus is fine.” he sighed slowly, “You should know what we’re going into.” Nodding, Breakdown shifts and sits up, crossing his arms comfortably, “What is the mission?” Optimus nods and stands, gesturing, “I’ll show you a map.” Breakdown eases himself off the seat and follows, arms falling back to his sides. Moving much slower than he used to, head just now starting to ache. 

He hadn’t been in this part of any of the shuttles he’d been on, usually it was kept for those in command, one or two mechs were working in there, one he recognized as Red Alert. 

The table turned on with a flicker, “This is New Kaon. It is an old decepticon settlement from the last war. Not a colony of Cybertron, so I have been reminded.” If Breakdown didn’t know better, he would think that Optimus sounded bitter. 

Both the mecha at the command chairs winced.

”The Quintessons are attempting to surround the city, though their main command ship has crashed according to reports, it appears to be in this area.” He highlights an area just east of the city, “I’m afraid to say that I don’t know currently where Hound is located.” Breakdown stared at the map and gestures, “Likely as close to the crash site as he could be, anything we can learn from you all will be important to send back home, even if we do not return ourselves.” He continued to stare at the map.

Even as everyone in the room stared at him like he had grown a second head, “We have every intention of ensuring your safety.” Breakdown hummed, “That is not our thought, sir.” He glanced up, “We are to destroy the Quintessons, at all cost, even our lives.” He looked back at the map and gestures, “Do you know who is protecting this area? It appears to be a weak point.” And Optimus stared at him.

—

His suit felt alive, he felt alive for the first time in years. The total connection to your suit you could only get when your base coding it properly connected. It was dangerous, but thrilling. It exacerbated overuse and likely would lead to the crash, but unlocking his night vision brought back all the old instincts of hunter coding. 

Sometimes on Earth, they would decommission specific suits from certain classes when other things were needed more. Hunter class was a dwindling group, but the compatibility test for it was different from striker class. Usually military, they were the best at tracking and killing the enemy. In this case, the Quintessons. 

Hound had been a Hunter class for the first two years of his piloting career and it had ended his marriage, when he was offered the switch to Striker, he took it. He could still remember the surgery of removing some of the older implants and wiring made specifically for the old way his mecha used to work. 

Now, there were other hybrid mecha, pilot 3141, 17741, 17740, and a list of others who hadn’t survived the conversion but they were out there. 

It was as if there weren’t screens in front of him anymore and he was on his feet, as if the world around him was just that, around him and not his suit. It was a familiar old feeling and it filled him with dread.

Being a hunter class had almost ruined his life, it’s why his suit and him were striker class, but this focus, that was all hunter. Taking a slowly and deep breath, he was able to find the positives, he didn’t feel like an animal in a suit. He felt like himself but bigger, calmer and again still all him.

”Hound, you alright? I’m getting a lot of heavy breathing.” Mirage sounded concerned and that was enough, as his arm finally finished adjusting and he could actually see, it brought him back to a better state, “Uh, yeah. I’m alright, I had to switch some stuff around so I could see it being so dark.” He nodded a bit, gun firing with ease as he dispatched a Quintesson quickly. 

Another thing to ground him, Hunter’s usually didn’t have guns, he hadn’t back then and certainly not one like this. 

“I’m good Mirage, you have my six still?” He took a slow deep breath, even as he tore apart a screeching Quint, “Yeah, I’ve got you. Just try to hang to my right side, alright?” He grinned, gun firing into the gaping would he had just made with his hands in the Quintessons side, “Got it.” And he kept moving.

It was a deadly calm, the familiarity of moving through the enemy, of dispatching them with ease.

What had Megatron said, kill the damned things, as many as you can, as fast as you can. Being a hybrid of hunter and striker in this moment let him actually do that. 

Even if they kept coming, he’d be able to do that. 

Mirage kept checking in, even as he lost track of time, their conversation kept to a minimum for focus, his focus was every way that he could pull these things apart and let Mirage get off a few shots. It was a flow, the moons moving across the sky together. 

When Hound saw the spacecraft break the atmosphere, he thought for a moment that it was more attack ships. Gun humming up and glowing brightly at his side, taking slow and deep breaths while he watched, “Oh slag.” Mirage broke him out of his trance, “It’s another attack ship?” With a shaky breath, Mirage shook his head slowly, “No, that’s the Prime’s ship.” Hound’s stomach sank.

Nodding slowly, he took a breath, “How long have we been fighting if he’s here so fast?” It felt like not that long ago he’d been stuck listening in on the couples spat, though now he saw it as more an argument between commanders. Mirage was quiet on the other side of the line, “Around, as you say it, a day and a half? Full solar cycle and some.” Hound closed his eyes for a moment, almost too ingrained in the suit he had to take the moment to check on himself and not the suit. 

He was starving, thirsty, and likely needed more than just food and water. Keeping his eyes shut, it was the only way he was able to physically control his actual body. Water pouch first, taking off the oxygen mask to drink, then down one of his dwindling stash of protein bars. None of the space food was fast enough. Readjusting the mask back to his face, he took a deep breath.

The small tanks were now cleaning the air available in the larger tanks, but it certainly smelled better than his cockpit did. 

“Sorry, so, day and a half… The fact that he’s here is a bad thing, right?” Mirage stared at the descending ship, “Very.” Hound sighed, “Fuck.” Biting back a smile, Mirage nodded, “Oh yeah, definitely.” Glancing back around, Hound stared at the horizon instead before getting back into his coding.

Gun humming again, he scanned the horizon, closing his eyes for another moment before adjusting the cameras again, screens becoming like lenses as he stared. 

—

The ship wasn’t the largest in the Cybertronian fleet, far from it when compared to some of the older ships, but this one was energy efficient and fast. Megatron had been watching its descent, knowing exactly who was on board and dreading every moment of it. Adjusting several of his soldiers' positions gave him enough room to go back to command and likely shout at his conjunx for his endless idiocy. 

Command was practically empty, most of those who would normally be here either in the field or back on Cybertron if they had not hopped aboard Optimus’s craft. He was developing a helm ache. 

Although energy efficient, it didn’t make it any less loud as it landed, and Megatron lowered his helm for a moment before straightening. Heading outside with his helm high and a scowl on his face. 

Optimus looked different, significantly different, and it almost brought him to a stand still. Since the peace treaty, they had both been lucky enough to keep their paint fresh, weapons lowered, and not wear horrible expressions. 

Megatron could remember the early days of peace, how before they started speaking he’d see Optimus itching at the gold filigree that littered his frame. How he struggled to keep his battle mask open during important moments, and how relieved he seemed to be to not carry a gun or his axe.

Far from the claims that he was a gentle soul who hated violence, more so the relief of a soldier who could finally lower his pack to the floor. Still within reach, always ready to grab it, but able to let some of the weight slide off his shoulders.

Now however, he was distinctly reminded of who had been across that battle field from him for eons. 

Optimus looked like that hated enemy in this moment, but different, so different it tugged at Megatron’s spark. He had grown used to the mech looking like his Prime, his conjunx, that Optimus looking like his old enemy almost made his tanks turn. 

Taking a vent, Megatron moved forward as the bay door to the ship opened, “Optimus—“ Optimus looked at him and it almost burned, “Ah, Lord High Protector.” Frowning slightly, Megatron moved forward, “Optimus,” Who held up a servo and turned to Elita at his left, “Elita, if you don’t mind I would appreciate you heading into command, the Lord Protector and I will join you shortly.” She bows her head slightly and moves inside. Not sparing Megatron a glance, which made his tanks sink.

Optimus waited for her to be within command before looking back to Megatron, “Since you insisted that I not bring the United Cybertronian Army, nor open the space bridge, I thought I would offer that helping hand in person.” Megatron stared, and thought one thing, frag.

Clearing his vocalizer, Megatron hoped to smooth this over, “Optimus—“ “I did not fly all the way from Cybertron to talk, Lord Protector. You mentioned that I should not waste your time with trivial matters, we can go into command and speak of strategy with my commanders once they have both arrived.” Megatron frowned again, shaking his helm slightly, “Both?” Optimus started into command, paint not quiet shining but also not dull, just different.

”Ironhide is not far behind, he will land within the Joor.” He threw aside the trap that was the door for command, moving in and standing at the active battle map, frown evident in his optics. 

Taking a vent, Megatron followed and moved to stand at the table as well, glancing towards Elita briefly. She did not look entirely happy to be here, “My Prime, I am going to retrieve our supplies and the unit.” Optimus nodded, “Of course, I would suggest sending Breakdown to the line or to Knockout, whichever you deem necessary.” She nodded and moved out quickly.

Megatron cleared his vocalizer yet again, “Optimus, I fear there was a misunderstanding.” Bowing his head slightly, Optimus looks at the table and starts drawing adjustments, “I understood you perfectly fine Lord Protector, my audial passed to spec during their last check. There was no misunderstanding other than perhaps your stance in this war.” Megatron’s mouth went dry.

Shifting at the head of the table, Optimus circles several locations, “I will place Elita, Ironhide, and myself incharge of these regions. Since we are going to have three humans planet side I am going to request that they be placed under the watch of my commanders.” Megatron slowly lowered a hand to the table, “Optimus, Hound is under my command.” “And I’m sure that he has been listening to your orders and following through with precision.” Megatron growled lightly. 

“Optimus, what is going on? What do you want from me?” The other mech looked up from the table, “For you to follow through with the expectations of your position.” Megatron balled his fists, “I have been doing just that, protecting Cybertron and overseeing this conflict.” Optimus tilted his head slightly, “And here I thought your sole focus was on New Kaon and your people.” Taking a slow vent, Megatron looked away.

His mouth was drier than the sand outside, “And here is where I believe we had our misunderstanding.” Optimus scoffed, “And yet you proclaimed yourself sovereign of New Kaon, which you are not. You are Cybertron’s Lord High Protector, which does not align with what you proclaimed meer joors ago.” He took a deep vent as Elita returned, “Ironhide’s ship is breaching the atmosphere.” Nodding again, he bent back over the map, “If you will excuse me Lord Protector, we will reconvene once Ironhide and his unit have landed. You are dismissed.” 

Megatron stared for a long moment, servos still fists before storming out.

Optimus sighed deeply and lowered his head for a moment, optics off, venting slowly. Elita stood there, silent as always, until he needed her to say something or she needed to intervene. Glancing back up, he looks to her, before back to the table, “How would you redesign the line commander? And where do you think will be the best placement for the humans?” She moved forward, “Well, it depends on how well they will listen.” It was a familiar comfort, the pair of them in a command room, where Ironhide would join them shortly. A much needed comfort. 

—

Hound’s comm crackled, “Hound, you might want to return to command.” He really didn’t, gun firing very loudly at a distant Quintesson, “Breakdown and Sunstreaker are here.” The voice was Red Alert, he almost didn’t recognize the mech over comms. 

Looking back, the small encampment that was command was the only thing that was lighten up yet, a bright green in his vision, “Breakdown is supposed to be resting for another few days.” His voice only wavered slightly, “He arrived with the Prime. Fall back in the next minute, seekers are going to fly overhead.” Sighing slowly, he nodded and started backwards.

Once he heard the screen of seeker engines he ran, briefly glancing towards where Mirage was before focusing on reaching command safely.

He could make them out as he deactivated the night vision, yellow standing out more than the blue, but the pair were clearly talking. He couldn’t help but smile, having been away for longer than either of them have. It was nice to know there were some of your own kind nearby. 

“Ah! As it’s said, look what the tide brought in.” Breakdown waves at him, both him and Sunny pinging him with video comms. He quickly answered and turned on his own camera, Sunny immediately winced, “Damn Hound, when was the last time you slept?” Hound tried very hard not to roll his eyes.

Though Breakdown was nodding, “You look incredibly tired.” Hound came over and rested a hand on each of their shoulders, “I’m fine. I slept sometime yesterday, ate a little bit of go.” Probably a few hours before, but it was alright.

Sunstreaker shook his head a bit, “Come on Hound, don’t be like that.” Breakdown nodded, and Hound sighed, “And to think, I missed you guys.” He smiled and so did they.

“So, what are the two of you doing here? BD, you’re supposed to be resting and Sunny, I thought you were placed with Ironhide.” Sunny nodded, “Oh I was, Joan called him in.” Hound nodded slowly, “I think calling the Prime that on private comms is fine, but we should refer to him as the Prime otherwise.” 

Breakdown nodded slowly, “He is a very interesting man, one of his commanders, Elita-One, came to retrieve me after Jazz called to clear my health. I was cleared, but we were on the shuttle over here together. He kept making sure that I was alright before he got quiet.” Hound hummed.

He couldn;t help but glance over towards command, “Yeah, he had an argument with Megatron.” He sighed slowly, shaking his head, “Come on, we’ll sit and talk, eat. Unplug for a minute.” Sunstreaker was nice enough to rest a hand on his back, walking him towards a nearby heater.

”How’s the oxygen here?” Breakdown lifted a hand, likely tapping at a screen, “Not bad, but certainly not good. I would stick to tanks.” Sunstreaker groaned, “I just got off a toxic planet.” And Hound laughed, sitting down, “Welcome to New Kaon.” Sunny grumbled as he sat down.

Hound finally unplugged, shivering as his implants had left his skin wet and now cold. He pulled his helmet off and then the oxygen mask, wrinkling his nose, “Oh god.” Sunstreaker looked away and Breakdown looked sympathetic.

Leaning forward, he tried not to throw up again, “Drink some water Hound, take a rest. You look pale.” Breakdown kept his voice quiet and slowly, Hound nodded and grabbed his water pouch. Drinking slowly. 

—

Ironhide almost stormed into command, “And how did the Quints get this far into Cybertronian space with this many ships? One or two on Cybertron, sure, but this is ridiculous.” His fist collided with the table.

Barely sparing him a glance, Optimus was still drawing out strategy, “Welcome to New Kaon, Ironhide, I would appreciate it if you could retrieve the Lord High Protector from wherever he slunk off to.” Frowning, Ironhide leaned on the table, “And why can’t you—“ Elita was glaring sharply and he was quick to shut his mouth, “Uh, yes, My Prime.” He turned on the spot and went back outside. 

Seekers were still screaming through the air, the only light available was those of optics or explosions and blasts.

He wasn’t far, having taken control of a distanced cannon and had tried blowing off steam firing on the enemy. Ironhide clears his throat, “Lord High Protector, the Prime requests your presence.” Megatron looked over, nodded, “Of course.” They were all slagged if those two were fighting.

Moving back into command, they were joined by Knockout and Flatline, who were talking intensely in the other half of command, “It’s just shattered and he seems totally fine with it!” Knockout vented deeply, “Welcome to life with humans, we will repair it after this is dealt with.” They moved through to the other half of command, dropping the tarp over the door. 

Now it was just Optimus, Megatron, Elita, and Ironhide standing around the command table. Projection map marked up with adjustments made by Optimus and Elita. Megatron scowled down at it before looking back to Optimus, his spark aching. 

Taking a vent, Optimus gestures towards the table, “Here is the plan, for the moment, I would suggest that we institute it as soon as possible.” he rocked back lightly on his peds, an old habit from the war, “Optimus, if I may?” He barely spared him a glance. “You may not, Lord Protector. We lack the time and some of us the patience to listen to your attempts to placate my ‘emotions’ as you said, they are not my probity nor should they be yours.” 

Optimus paused and looked at Megatron, “Or would you rather, how did you say it, be content to lose this war?” All the warmth drained from Megatron’s face, his energon running cold. Ironhide was gawking, taking a moment to look at Elita who briefly shook her head, he gulped and looked back to the table. 

Glancing around the table, Optimus took in his commanders for a moment before looking back, “Ironhide, I want you and half of your unit to take the north side. Elita, to the south with the other half of his unit. Wherever Mirage is placed, I want Bluestreak on the opposite. I need to speak with Hound, Sunstreaker and Breakdown before they reenter the field. I will take the west with this group here.” He lightly circles a unit on the map.

”And Megatron will take the east, the seekers will continue to fire from above but have them cycle out more often, less they will exhaust themselves.” His servos were shaking lightly, “The sooner we get out there, the better off we will be since there are no more reinforcements.” Optimus shot a brief glare at Megatron before straightening, “You have your orders. I suggest that you follow them.” He spared glances around to Ironhide and Elita before they both were quick to leave.

Muttering to each other as they went, Optimus tried incredibly hard not to roll his optics, even as his helm pounded. His servos were still shaking ever so slightly. 

They all maintained some things from these from the war, one of Optimus’ were the tremors. 

Megatron was watching his hands, so he folded them comfortably behind his back, “Well?” Optimus’s tone was not quite cold, but certainly not filled with warmth either, “I would suggest, unless you need fuel, returning to the field. As not to waste ‘precious time’.” Optimus moved away from the table, grabbing up an all too familiar blaster before leaving command himself, not sparing Megatron a second glance.

His mouth was still incredibly dry and he likely did need to fuel, but it would be impossible to keep it in his tanks. With a growl, he stormed out after Optimus, but the mech was already gone. 

———

A/N

I thought this chapter was 4.5k, its actually 5.2 so uh… enjoy?

But in all seriousness, the megop in this chapter is probably the longest you’re going to get. If it weren’t important to the story it would have happened behind the scenes.

But this chapter feels wild to me, it’s long and now I’ve written probably right around 100k words for Arcturus as a whole though that does include stuff I haven’t posted yet. But that’s still a lot.

Than you all so much for your kind words, questions, likes, all of it.

Tags

@lunarlei68 @whirlywhirlygig @loop-hole-319 @pixillandjester @alek-the-witch @not-a-moose-in-disguise @goddessofwind8water @neurologicalglitch @dersereblogger @pixel-transformers @mrcrayonofdoom @wireplaces @twilightfreefaller @original-blog-name-2 @devilangel657 @robbin-u @miniartistme @starwold @tea-enthusiasm @valeexpris606 @celticdoggo @bird599 @agentsquirrelsgotrobots @aquaioart @thatwandercat @artdagz @seisha974 @halenhusky309 @leethepiper @cat-cassette @blue-wrens @sirassban @cosmique-oddity @garbageenthusiast @xervias @azulabutterfly @fryseem @spring-mc @echo-circuit @aghostsnail @wooblewooble @ask-glory-haddock-and-others @nonsscrapheap @magichats @iminahole247 @omgflyingderpywhale @thetrexartist @naaaafam @elegantmantaray @emichusai @waterlilykitty @diabolichare @ham4ponyo @osqindaxend @sunnyvibesanddoodles @ratatatata248 @ijustneedausernaneplease4444444 @sprook-children 

And once again thank you to @Keferon for this amazing AU!

Also thank you @sightseertrespasser for your help with the mech suit class stuff, it gave me the right thing to fill a plot whole I was writing myself into.

[dronebiscuitbat]

Oil is Thicker Then Blood (Part 98)

N was first, climbing down into a small hole in the ceiling, using night vision to make sure the room was safe.

There was flesh piled in the corner, crawling up the wall to reach nearly the ceiling, black tendrils lie dormant all across the floor like living tripwires. One wrong touch and…

Uzi's head poked from the ceiling.

“Can I come down or what?”

N scanned the rest of the room, the control room screens were still online by some miracle, though several of them were busted and several more were tangled in a web of eldritch goo however, let's hope that wouldn't be an issue.

“H-hang on, if you touch the floor we'll trigger a reaction.” He flew up to come face to face with her, “Let me carry you.”

She reached out for him, landing into his hold as her tail lit up the room in a purple glow, taking in the room.

“Damn. This place will be gone in a couple days. We better get out of here fast.” She pointed out, eyelights training on the faintly glowing console. “Bring me over yeah?”

He nodded, hovering over to where she could leap onto the control panel without touching the floor.

[SYSTEM LOCKDOWN : ENTER PASSKEY]

Read the slightly cracked, incredibly dusty monitor and Uzi sighed, mumbling under her breath. “Yeah of course it's on lockdown…”

She pressed a few buttons, getting an error noise on each touch- the entire control panel was completely unresponsive.

“I'm going to have to plug in. Make sure my body doesn't fall.” She turned back to her boyfriend, who ceased his paranoid looking around to meet her eyes; worry creased his frame.

“Uzi this computer has been out here for ages… who knows what sort of virus it has. Plus…” He gestured to the black, slimy tendrils snaking up some of the monitors. “Who knows what this stuff does to computers.”

She nodded. “Yeah.”

“But the keyboards locked up, and we need the data off this old thing. What other choice do we have?”

“I-I could-”

“No.” Uzi interupted him. “If these things trigger you're the only one that can burn it away. We'd both be sitting ducks.”

He sighed heavily, the knowledge that she was right didn't help his nerves any, his core yanked painfully in protest.

No it's dangerous.

She could get hurt, the kit could be hurt.

Don’t let her go.

“Hey. I got this. You trust me?” She asked, cocking her head with a confident smirk, God, how long had it been since he'd seen that? It's been so much exhaustion and doubt lately…

“Of course I do.” He replies, hovering close just to give her a quick kiss on the lips before parting. “Just be careful, okay?”

She nods. “Duh.” And she reaches for the port above her core, forcing the hatch open, “Ow! Agh… that's not meant to come open without prep I guess.” She hissed under her breath, and fished around in her pocket for a linking cable. “There you are.”

She plugged one end into herself before hunting for an interface port on the console, taking a moment to find it.

She does, it's next to a big red button that was currently pulsing red- she made a mental note to avoid touching it.

“Wish me luck.” Was the last thing she said before she plugged herself into the control panel, body locking up as code crashed into her firewall. Her body winced. She barely felt N keep her steady as she was hit with a flood of errors.

Plugged into another drone, the experience was euphoric, you were connected to another conscious, a soul. But this computer wasn't sentient; and what little AI it possessed was broken beyond the point of functioning. So all the sensation she felt was just her own- and the faint screaming of a dying AI.

ERROR- MEMORY FAILING

ERROR- DATA BACKUP FAILED

ERROR- HARDWARE FAILURE

“Yeah, no shit.” She mumbled, feeling her mouth move as she refocused. Okay, the information had to be in here somewhere…

She began to push through the ocean of errored code, feeling the system push back hard against her firewall. N was right, this thing probably had a thousand viruses it was itching to share with her, let's just hope her firewall held up.

She felt her consciousness leave the confines of her physical body, leaving it behind as she searched through poorly organized files; some were completely corrupted, others were fine, just not useful.

Time lost meaning, the system of the console was incredibly vast, and it quickly became clear she was searching for a needle in a haystack, a dot of purple among a sea of white.

She began to worry, perhaps the information they were looking for had already been corrupted?

That is, until she ran into an encrypted wall of cascading code, denser then the scattering of loose data she'd been able to access thus far.

She pushed against it, purple meeting default white, as strings of encryption appeared on her visor, N watching over her diligently.

[ENTER PASSKEY]

She sighed- or whatever passed for an entirely digital equivalent, beginning to work through the encryption with her own hardware, the solver aiding in her speed.

1s and 0s turned to scrambled letters and white space made to make any unwanted guest have trouble finding the passkey, but a mixture of determination and robotic advantage let Uzi make quick work of it.

P-A-S-S-W

“Oh for- the password is password, I could've just guessed it!” Her body suddenly shouted, startling N and then making him laugh. “Pfft-haha!”

Refocusing, she was able to push her code through the systems firewall, it wasn't entirely painless but she got through.

There was only a single file.

Transmission- Classified [TITANUM-28]

The file was an audio recording, with a set of coordinates attached. She played it, beginning a download into her own system.

“This is Doctor Rosemont, Transmitting from Lab 18. Something… happened.” There was screaming in the background- and a colossal roar.

“The genetic experiments have been a success, modifications to our old C.R.I.S.P.R technology has allowed us a greater range of genetic wiggle room…” There's a crash, and the sound of rapid- panicked gunfire.

“U-Unfortunatly, Subject 5 has uh… escaped.”

There's the sound of shattering glass, and low, feral growling. “If you receive this message, know that Titanium-28 is compromised! I repeat! Titanium-28 is-” The transmission ends with a blood curdling scream and a roar.

The coordinates to the planet are attached labeled very clearly with [QUARANTINED]

A single image is also attached, a satellite view of a planet covered in red and green trees and a canopy so thick you couldn't even see through it from orbit, like images she'd seen of earth, a good portion of the planet was covered in water.

She felt N start to shake her, his voice muffled from the distance her code was from her body.

“UZI! WE GOTTA MOVE!”

Next ->

[transpondster]

HOW MUCH BETTER is the world since the arrival of what Nicholas Carr calls our modern “technologies of connection”—cell phones, personal computers, the internet, social media, artificial intelligence? As we watch these systems undermine democracy, flood our lives with misinformation and deepfakes, transform our children into screen-obsessed zombies, and threaten to eradicate us entirely, we might be tempted to respond with a hollow laugh. But to what extent are these bleak scenarios real? What about being able to navigate by GPS almost anywhere in the world, or call for help when stranded in the middle of nowhere, or stream any song we desire? The cost-benefit calculation is complicated and nuanced, requiring us to find a course between apocalyptic visions of civilizational decline and the naive utopianism of Silicon Valley. Carr established himself as an astute commentator on information technology in his 2010 book The Shallows: What the Internet Is Doing to Our Brains, in which he argued that Google and the internet are, in the words of his formative essay in The Atlantic, “making us stupid.” In his new book Superbloom: How Technologies of Connection Tear Us Apart, he expands that analysis to encompass social media and digital communication technologies, asking how they are changing us individually and collectively. As the book’s subtitle implies, the diagnosis is not promising. But if these systems are indeed tearing us apart, the reasons are neither obvious nor simple. Carr suggests that this isn’t really about the evil behavior of our tech overlords but about how we have “been telling ourselves lies about communication—and about ourselves.” Carr takes his title from an event in 2019, when weather conditions produced an unusually abundant bloom of poppies in a canyon near Los Angeles. When an Instagram and YouTube influencer posted pictures of herself among the flowers, the hashtag #superbloom went viral, and before long, the place was overrun, a traffic officer was injured, online discourse curdled, and the media began speaking of “Flowergeddon.” Carr argues that the #superbloom event exemplifies the problems with these new media. “We spend our days sharing information, connected as never before, but the more we communicate, the worse things seem to get.” Isn’t that just the opposite of what was supposed to happen? “Well before the net came along,” says Carr, “[the] evidence was telling us that flooding the public square with more information from more sources was not going to open people’s minds or engender more thoughtful discussions. It wasn’t even going to make people better informed." “Every new medium,” wrote social theorist John Durham Peters, “is a machine for the production of ghosts.”

The Case for Kicking the Stone | Los Angeles Review of Books

[omeletcat]

Hey! I recently started following your blog and I'd like to ask you some rather important questions before I start offering advice and my thoughts.

Why are you making a game? And for who?

Cause I don't wanna get in the way of your creativity just because you're not making "a game for me".

Like, as an example, I mostly play games on controllers, when I play games, and you tying so many of the mechanics and controls to the mouse means using controller input will not be very easy to add, if possible at all

But ... If you don't like playing games with a controller, and wanna see how much you can do with the keyboard/mouse inputs, then it is definitely the right decision to tie all these mechanics to that! But if me pointing this out makes you go "Oh right! There are people who mostly use controllers and I definitely wanna make my game work for them as well!" then it's a valid thing to point out that your game could prove hard to make work with a controller as input.

This is, btw, important to keep in mind when receiving critiques from others from your end, are they giving you tips/ideas/etc. that align with your vision of what you want to make, and following their advice will help you? Or are their points valid from their point of view, but would just muddy your vision and trying to accommodate it would mean falling into the trap of trying to please everyone, failing to make a good game for anyone?

Ty for asking! I'm mostly making this game because i think its fun and i rly wanna make something cool that people will enjoy. My ultimate dream is to make something so cool that it would be worth making fanart for! For the who part idrk, for people like me who like the kind of game i am making? ALSO TYSM FOR TELLING ME ABOUT THE CONTROLLER THING I had a rly small thought about smth like that ages ago but brushed it off thinking i should focus on making the core mechanics first. But yea you're totally right! implementing this combat system with a controller would be hard, especially since i mostly grew up playing with the wii.. and like a playstation controller three times. What i usually play is in random free stuff i could find online. I am unsure how it would work/how it even works when you apply a controller to a computer to play a game with it but i am definitely gonna think about this!! The core idea is the aiming, i could either change the mouse aiming to aiming with a joystick and moving a mouse like thingy around but i feel that wouldn't rly work.

The current aiming mechanic works kinda like this the screen is divided into 8 area's (4 directions and one for close and long range attacks) to attack you press either left or right mouse click and depending on if the mouse is in the central area or outside of it it will give a different attack for attacks that have a specific direction, the 4 area's decide where the attack will be aimed thanks to the mouse position. I could make it so that the player selects the area's like an option button? I can't rly explain it, imagine a list of buttons and moving the joystick to go down, imagine that but with these area's! This would work best for attacks are directed to a certain area like Rae's blast attack.

It has 4 directions and only aims at those parts. So for this attack it would work great. You move around the selector and switch around between them to aim pick a direction and if its far or close. But for some other attacks like Luca's main it aims towards the mouse position and doesn't pick a direction depending on where the mouse is, I am unsure how i would do this if i pick the idea of switching between zone's. I may just make it so the direction the player is moving while attacking is where it is aiming. Because when the player is attacking you can't move. I think that would work out. HOWEVER I am unsure how I would add this, how to detect if the player is using a controller, and a bunch of other things, i'm pretty sure i can add controller inputs in the settings and make those work for basic movements and attacks, but i would need to add a few extra things to fully make it compatible for controllers.

Sry if this rambling is kinda messy but they are the first idea's that come to mind how i would make the game playable for controller!! THANK YOU SO MUCH FOR SHARING THIS!! I would have never thought about making it playable for controller if you wouldn't have helped me!!

You said you had more advice/thoughts so if you want to please share!! Any advice is be insanely helpful!

[teqful]

How-To IT

Topic: Core areas of IT

1. Hardware

• Computers (Desktops, Laptops, Workstations)

• Servers and Data Centers

• Networking Devices (Routers, Switches, Modems)

• Storage Devices (HDDs, SSDs, NAS)

• Peripheral Devices (Printers, Scanners, Monitors)

2. Software

• Operating Systems (Windows, Linux, macOS)

• Application Software (Office Suites, ERP, CRM)

• Development Software (IDEs, Code Libraries, APIs)

• Middleware (Integration Tools)

• Security Software (Antivirus, Firewalls, SIEM)

3. Networking and Telecommunications

• LAN/WAN Infrastructure

• Wireless Networking (Wi-Fi, 5G)

• VPNs (Virtual Private Networks)

• Communication Systems (VoIP, Email Servers)

• Internet Services

4. Data Management

• Databases (SQL, NoSQL)

• Data Warehousing

• Big Data Technologies (Hadoop, Spark)

• Backup and Recovery Systems

• Data Integration Tools

5. Cybersecurity

• Network Security

• Endpoint Protection

• Identity and Access Management (IAM)

• Threat Detection and Incident Response

• Encryption and Data Privacy

6. Software Development

• Front-End Development (UI/UX Design)

• Back-End Development

• DevOps and CI/CD Pipelines

• Mobile App Development

• Cloud-Native Development

7. Cloud Computing

• Infrastructure as a Service (IaaS)

• Platform as a Service (PaaS)

• Software as a Service (SaaS)

• Serverless Computing

• Cloud Storage and Management

8. IT Support and Services

• Help Desk Support

• IT Service Management (ITSM)

• System Administration

• Hardware and Software Troubleshooting

• End-User Training

9. Artificial Intelligence and Machine Learning

• AI Algorithms and Frameworks

• Natural Language Processing (NLP)

• Computer Vision

• Robotics

• Predictive Analytics

10. Business Intelligence and Analytics

• Reporting Tools (Tableau, Power BI)

• Data Visualization

• Business Analytics Platforms

• Predictive Modeling

11. Internet of Things (IoT)

• IoT Devices and Sensors

• IoT Platforms

• Edge Computing

• Smart Systems (Homes, Cities, Vehicles)

12. Enterprise Systems

• Enterprise Resource Planning (ERP)

• Customer Relationship Management (CRM)

• Human Resource Management Systems (HRMS)

• Supply Chain Management Systems

13. IT Governance and Compliance

• ITIL (Information Technology Infrastructure Library)

• COBIT (Control Objectives for Information Technologies)

• ISO/IEC Standards

• Regulatory Compliance (GDPR, HIPAA, SOX)

14. Emerging Technologies

• Blockchain

• Quantum Computing

• Augmented Reality (AR) and Virtual Reality (VR)

• 3D Printing

• Digital Twins

15. IT Project Management

• Agile, Scrum, and Kanban

• Waterfall Methodology

• Resource Allocation

• Risk Management

16. IT Infrastructure

• Data Centers

• Virtualization (VMware, Hyper-V)

• Disaster Recovery Planning

• Load Balancing

17. IT Education and Certifications

• Vendor Certifications (Microsoft, Cisco, AWS)

• Training and Development Programs

• Online Learning Platforms

18. IT Operations and Monitoring

• Performance Monitoring (APM, Network Monitoring)

• IT Asset Management

• Event and Incident Management

19. Software Testing

• Manual Testing: Human testers evaluate software by executing test cases without using automation tools.

• Automated Testing: Use of testing tools (e.g., Selenium, JUnit) to run automated scripts and check software behavior.

• Functional Testing: Validating that the software performs its intended functions.

• Non-Functional Testing: Assessing non-functional aspects such as performance, usability, and security.

• Unit Testing: Testing individual components or units of code for correctness.

• Integration Testing: Ensuring that different modules or systems work together as expected.

• System Testing: Verifying the complete software system’s behavior against requirements.

• Acceptance Testing: Conducting tests to confirm that the software meets business requirements (including UAT - User Acceptance Testing).

• Regression Testing: Ensuring that new changes or features do not negatively affect existing functionalities.

• Performance Testing: Testing software performance under various conditions (load, stress, scalability).

• Security Testing: Identifying vulnerabilities and assessing the software’s ability to protect data.

• Compatibility Testing: Ensuring the software works on different operating systems, browsers, or devices.

• Continuous Testing: Integrating testing into the development lifecycle to provide quick feedback and minimize bugs.

• Test Automation Frameworks: Tools and structures used to automate testing processes (e.g., TestNG, Appium).

19. VoIP (Voice over IP)

VoIP Protocols & Standards

• SIP (Session Initiation Protocol)

• H.323

• RTP (Real-Time Transport Protocol)

• MGCP (Media Gateway Control Protocol)

VoIP Hardware

• IP Phones (Desk Phones, Mobile Clients)

• VoIP Gateways

• Analog Telephone Adapters (ATAs)

• VoIP Servers

• Network Switches/ Routers for VoIP

VoIP Software

• Softphones (e.g., Zoiper, X-Lite)

• PBX (Private Branch Exchange) Systems

• VoIP Management Software

• Call Center Solutions (e.g., Asterisk, 3CX)

VoIP Network Infrastructure

• Quality of Service (QoS) Configuration

• VPNs (Virtual Private Networks) for VoIP

• VoIP Traffic Shaping & Bandwidth Management

• Firewall and Security Configurations for VoIP

• Network Monitoring & Optimization Tools

VoIP Security

• Encryption (SRTP, TLS)

• Authentication and Authorization

• Firewall & Intrusion Detection Systems

• VoIP Fraud DetectionVoIP Providers

• Hosted VoIP Services (e.g., RingCentral, Vonage)

• SIP Trunking Providers

• PBX Hosting & Managed Services

VoIP Quality and Testing

• Call Quality Monitoring

• Latency, Jitter, and Packet Loss Testing

• VoIP Performance Metrics and Reporting Tools

• User Acceptance Testing (UAT) for VoIP Systems

Integration with Other Systems

• CRM Integration (e.g., Salesforce with VoIP)

• Unified Communications (UC) Solutions

• Contact Center Integration

• Email, Chat, and Video Communication Integration

[mindfulmusinghub]

Maximizing corporate social responsibility impact : partnering with Marpu Foundation for sustainable development goals:

Marpu Foundation an NGO, dedicated to harness individual potential for positive change through innovative, empathy-led projects promoting sustainability and social empowerment. Believing in the power of collective efforts and partnerships to be a beacon of transformation, to craft a future that's equitable, compassionate, and sustainable.

One of India’s youth activist, environmentalist and  leading social entrepreneur, Kadiri Raghu Vamshi – The Environment Man, known for his relentless quest of innovative solutions to social challenges. As the founder of Marpu Foundation, His enterprising leadership in environmental protection, sustainable development, and social advocacy is directed towards empowering citizens to embrace social responsibility. He was awarded India’s prestigious Chakra award in 2019 for his vision in empowering citizens to be socially responsible.

This blog delves into the symbiotic relationship integrating Corporate Social Responsibility (CSR) efforts with the Sustainable Development Goals (SDGs) to devise innovative solutions for critical societal challenges, Along with spotlighting the distictive approach of Marpu Foundation and its remarkable success stories.

In the realm of sustainable development, the synergy between CSR and SDGs emerges as a potent catalyst for positive transformation. Marpu Foundation spearheads initiatives in volunteering, sustainable development, and environmental conservation. Their unwavering support for women and advocacy for crucial causes amplify their impact nationwide. They works closely with many partners and reaches out widely to create big changes in communities all over India. This combination allows for a more coordinated and impactful approach to addressing social challenges at both local and global levels.

Through its unique approach and steadfast dedication, the Marpu Foundation exemplifies how businesses can magnify their social responsibility impact while advancing the global agenda for sustainable development. The NGO is truly making a significant impact in both Chennai and Pune, as well as in Jaipur and Surat through its multifaceted initiatives aimed at addressing various social and environmental challenges. As we forge ahead, let us draw inspiration from the triumphs of the Marpu Foundation :

The attempts of Marpu Foundation in Chennai have brought a significant change in addressing water quality, safety, and connectivity issues together with equipping more than 20 with solar power panels.

CSR projects in Chennai and Pune, showcases a commendable commitment to the society,   

Digital Literacy Program: by providing computer and internet training to 10,000 underprivileged children and youth, the foundation has not only equipped them with essential digital skills but also opened doors to online education and job opportunities.       

 Solar Power for Schools: Installing solar power panels in government schools didn’t just reduce electricity costs but also promotes environmental sustainability by decreasing carbon emissions and ensuring reliable electricity access.

Rainwater Harvesting Systems: Implemented rainwater harvesting systems in schools and community centres to combat water scarcity. This initiative not only ensures access to water for various purposes but also promotes water conservation which is crucial for sustainable development in cities like Chennai and Pune.

 Sustainable Livelihoods Program: Offered training and support for women and youth in entrepreneurship skills, helping them kickstart their own small businesses. This not only creates jobs but also boosts economic independence. By specifically targeting marginalized communities, the foundation is championing inclusive economic growth and uplifting livelihoods.

The Waste Management Initiatives: By annually diverting more than 500 tons of waste from landfills. Their emphasis on composting, recycling, and upcycling, to actively foster an economy and promote sustainable waste management practices. These efforts not merely lessen environmental harm but also stimulate innovation and resource efficiency, opening new lanes for progress.

In Jaipur, the focus is on improving educational opportunities for underprivileged communities. They introduce creative educational initiatives designed to meet various needs. They build partnerships with organizations and institutions to maximize their influence.

Businesses in Surat could consider engaging with Marpu Foundation for their CSR activities for several reasons like local impact and expertise experience in executing successful CSR initiatives offering businesses the opportunity to partner with an organization experienced in driving impactful projects. 

Overall, Marpu Foundation's holistic approach to social and environmental issues underscores their dedication to creating a better future for generations to come. Through their collaborative efforts and innovative solutions, they are leaving a lasting impact on communities across the nation inspiring others to take responsibility for the well-being of society and the environment.

By: Hiba Siyad

[mindyourtopics44]

25 Python Projects to Supercharge Your Job Search in 2024

Introduction: In the competitive world of technology, a strong portfolio of practical projects can make all the difference in landing your dream job. As a Python enthusiast, building a diverse range of projects not only showcases your skills but also demonstrates your ability to tackle real-world challenges. In this blog post, we'll explore 25 Python projects that can help you stand out and secure that coveted position in 2024.

1. Personal Portfolio Website

Create a dynamic portfolio website that highlights your skills, projects, and resume. Showcase your creativity and design skills to make a lasting impression.

2. Blog with User Authentication

Build a fully functional blog with features like user authentication and comments. This project demonstrates your understanding of web development and security.

3. E-Commerce Site

Develop a simple online store with product listings, shopping cart functionality, and a secure checkout process. Showcase your skills in building robust web applications.

4. Predictive Modeling

Create a predictive model for a relevant field, such as stock prices, weather forecasts, or sales predictions. Showcase your data science and machine learning prowess.

5. Natural Language Processing (NLP)

Build a sentiment analysis tool or a text summarizer using NLP techniques. Highlight your skills in processing and understanding human language.

6. Image Recognition

Develop an image recognition system capable of classifying objects. Demonstrate your proficiency in computer vision and deep learning.

7. Automation Scripts

Write scripts to automate repetitive tasks, such as file organization, data cleaning, or downloading files from the internet. Showcase your ability to improve efficiency through automation.

8. Web Scraping

Create a web scraper to extract data from websites. This project highlights your skills in data extraction and manipulation.

9. Pygame-based Game

Develop a simple game using Pygame or any other Python game library. Showcase your creativity and game development skills.

10. Text-based Adventure Game

Build a text-based adventure game or a quiz application. This project demonstrates your ability to create engaging user experiences.

11. RESTful API

Create a RESTful API for a service or application using Flask or Django. Highlight your skills in API development and integration.

12. Integration with External APIs

Develop a project that interacts with external APIs, such as social media platforms or weather services. Showcase your ability to integrate diverse systems.

13. Home Automation System

Build a home automation system using IoT concepts. Demonstrate your understanding of connecting devices and creating smart environments.

14. Weather Station

Create a weather station that collects and displays data from various sensors. Showcase your skills in data acquisition and analysis.

15. Distributed Chat Application

Build a distributed chat application using a messaging protocol like MQTT. Highlight your skills in distributed systems.

16. Blockchain or Cryptocurrency Tracker

Develop a simple blockchain or a cryptocurrency tracker. Showcase your understanding of blockchain technology.

17. Open Source Contributions

Contribute to open source projects on platforms like GitHub. Demonstrate your collaboration and teamwork skills.

18. Network or Vulnerability Scanner

Build a network or vulnerability scanner to showcase your skills in cybersecurity.

19. Decentralized Application (DApp)

Create a decentralized application using a blockchain platform like Ethereum. Showcase your skills in developing applications on decentralized networks.

20. Machine Learning Model Deployment

Deploy a machine learning model as a web service using frameworks like Flask or FastAPI. Demonstrate your skills in model deployment and integration.

21. Financial Calculator

Build a financial calculator that incorporates relevant mathematical and financial concepts. Showcase your ability to create practical tools.

22. Command-Line Tools

Develop command-line tools for tasks like file manipulation, data processing, or system monitoring. Highlight your skills in creating efficient and user-friendly command-line applications.

23. IoT-Based Health Monitoring System

Create an IoT-based health monitoring system that collects and analyzes health-related data. Showcase your ability to work on projects with social impact.

24. Facial Recognition System

Build a facial recognition system using Python and computer vision libraries. Showcase your skills in biometric technology.

25. Social Media Dashboard

Develop a social media dashboard that aggregates and displays data from various platforms. Highlight your skills in data visualization and integration.

Conclusion: As you embark on your job search in 2024, remember that a well-rounded portfolio is key to showcasing your skills and standing out from the crowd. These 25 Python projects cover a diverse range of domains, allowing you to tailor your portfolio to match your interests and the specific requirements of your dream job.

If you want to know more, Click here:https://analyticsjobs.in/question/what-are-the-best-python-projects-to-land-a-great-job-in-2024/

[neworange]

Project Driven Learning - Dumped in notion today's morning😅

Vision

[ ] Job But in a good organization that I can be proud of

[ ] Worked for interesting companies at the beginning of my career which are also easier to get into and can provide valuable experience and a learning environment

[ ] I want to build visionary solutions for an organization like Sundar Pichai did for Google.

Projects

[ ] Meaningful projects - projects that I want to use myself

[ ] Find clone development projects of popular apps

[ ] I'll just have to build Just good enough projects

[ ] Project Matrix - Value / Complexity / Skills / Scope

[ ] Projects that are not just learning coding and development but also cloud computing and other skills

[ ] Don’t just build what you are passionate about but build what resonates with the target audience for which you are going to be applying for

[ ] What’s the enterprise-level business problem for which a solution can be coded equivalent to the exercises I’ve done from the book

[ ] Enterprise level Solving some Business Problems

System

[ ] Build the developer's Brain

[ ] Setting up a system to efficiently complete projects after projects

[ ] Build using AI and Google → Do the same projects using tutorials → Build a similar project of my own on my own

[ ] Keep reflecting to improve the project system and workflow

[ ] What are the outcomes of working on that project?

[ ] Pivot when projects not working or when gotten stuck

[ ] Which projects to take

[ ] Each project must have Skill/ challenge/ value/ purpose criteria

[ ] aligned with your immediate goals, if not add to the project backlog

[ ] Create mini frameworks to build project-efficient, effective and robust solutions.

[ ] Learn from the experts - So many online have built projects with so many functional things

[ ] How they approach building a new project

[ ] How they plan to Strategically set up for success

[ ] How they start a project from scratch

[ ] How do they plan architecture?

[ ] Build a project-building system and improve it along the way while building and learning

Resources

[ ] Theory management by reflecting on the progress of the project

[ ] Cross-check the concepts learnt in the theory

[ ] Find books & courses with enterprise-level application project

[ ] Full in-depth tutorials with examples

[ ] Reverse engineer Portfolios and Github

[ ] Research the expert people in building projects.

[ ] Medium, Github contributors

[ ] Udemy SDE project tutorials

[ ] Workshop → Software Development

[ ] Job boards require analysis to practice skills for software engineering

[ ] Agile certification

[ ] Cloud Certification

[ ] Software development online communities to ask for help and feedback and get to know about new things

High-Quality Questions

[ ] How to become a GitHub star

[ ] How to become an open-source star

[ ] what it takes to create a software from scratch till deployment

[ ] How to become a modern software engineer

[ ] What are the skills apart from coding and development?

[ ] What skills to acquire to go from to great engineer

Profession

[ ] Gather a network of support system

To help out of the stuck zone

Get feedback on stuck projects

[ ] Find a few developer friends

[ ] Ask them if they have built projects and hosted them on GitHub

[ ] Ask them to give feedback on my progress & help me make it functional

[ ] Software development online communities to get to know about new things

[callofdutymobileindia]

Artificial Intelligence Course in London: Everything You Need to Know Before Enrolling

As artificial intelligence (AI) reshapes industries across the globe, London has emerged as a major hub for aspiring professionals seeking quality AI education. With a thriving tech ecosystem, access to world-class faculty, and numerous career opportunities, enrolling in an Artificial Intelligence course in London can be a game-changing decision for your future.

Whether you're a beginner hoping to break into the field or a professional looking to sharpen your machine learning skills, London offers a diverse range of programs designed to meet every learning need.

Why to Enroll Artificial Intelligence course in London?

London is not just the capital of the UK—it's also one of Europe’s most dynamic centers for innovation and technology. Here's why studying AI here is a smart move:

Global AI Ecosystem: London is home to cutting-edge startups, global tech companies, and AI research labs. This environment provides exposure to real-world applications and networking opportunities.

Industry Demand: With sectors like finance, healthcare, retail, and logistics adopting AI rapidly, demand for skilled professionals has surged. This means job opportunity are both abundant and diverse.

Access to Experts: Courses in London often feature instructors with industry and academic experience, providing insights that go beyond textbooks.

Hybrid Learning Opportunities: Many institutions now offer flexible options—online, offline, or hybrid—making it easier to balance education with other commitments.

What You’ll Learn in an AI Course?

A well-structured AI and ML course in London typically covers the following core areas:

Foundations of Artificial Intelligence

Machine Learning Algorithms

Deep Learning and Neural Networks

Natural Language Processing (NLP)

Computer Vision

Data Science and Big Data Integration

Ethics in AI

Capstone Projects with Real-World Datasets

Advanced programs may also include agentic AI systems, reinforcement learning, and hands-on training using tools like TensorFlow, PyTorch, and OpenAI frameworks.

Who Should Enroll in an AI Course?

An Artificial Intelligence course in London is ideal for:

Students: Graduates in computer science, engineering, mathematics, or related fields.

Working Professionals: Those in IT, data analytics, business intelligence, or automation.

Career Switchers: Professionals from non-technical backgrounds interested in transitioning to the AI space.

Entrepreneurs & Innovators: Looking to integrate AI into their products or startups.

No matter your background, London-based courses often include foundation modules to help you build the required technical base.

Career Opportunities After Completing Artificial Intelligence course in London

Artificial Intelligence (AI) is transforming industries worldwide, and London is at the forefront of this revolution. As a global technology hub, the city offers abundant opportunities for professionals with AI expertise. Completing an AI course in London can serve as a gateway to diverse, high-demand careers across multiple sectors.

1. Core AI and Machine Learning Roles

Graduates of AI programs are well-positioned for technical roles that involve building and optimizing intelligent systems. These include:

Machine Learning Engineer – Develop algorithms and predictive models used in real-time systems.

Data Scientist – Analyze large datasets to draw insights and create data-driven strategies.

AI Researcher – Conduct academic or industrial research in neural networks, reinforcement learning, and deep learning.

Computer Vision or NLP Engineer – Specialize in areas such as image recognition or language understanding.

These roles are prevalent in tech companies, research labs, and even government institutions.

2. AI in Industry-Specific Applications

AI is increasingly applied in various sectors, offering opportunities to integrate technical knowledge with domain-specific expertise:

Healthcare – Roles in diagnostics, drug discovery, and personalized medicine with institutions like NHS AI Lab or startups such as Babylon Health.

Finance – Fraud detection, credit scoring, and algorithmic trading with firms like HSBC, Barclays, and FinTech startups.

Retail and E-commerce – AI-driven recommendation engines, demand forecasting, and customer analytics.

Marketing and Advertising – Use of AI in customer segmentation, ad targeting, and behavior analysis.

London’s diverse economy ensures that AI professionals can find roles aligned with their interests and skills.

3. Product and Strategic Roles

Beyond purely technical positions, AI knowledge opens doors to strategic and managerial roles:

AI Product Manager – Bridge the gap between technical teams and business stakeholders.

AI Consultant – Advise companies on implementing AI solutions to drive efficiency and innovation.

Business Intelligence Analyst – Leverage AI tools to inform executive decision-making.

These roles often combine AI proficiency with communication and leadership skills.

4. Research and Academic Opportunities

For those inclined toward academia or policy, London is home to renowned research institutions such as Imperial College London, UCL, and the Alan Turing Institute. Opportunities include:

PhD Programs in AI

Research Assistant or Associate roles

Policy and Ethics Research in AI Governance

Final Thoughts

Choosing to enroll in anArtificial Intelligence course in London is more than just a learning decision—it’s a strategic career investment. With access to advanced technologies, real-world case studies, and an innovation-driven environment, London equips you with the skills to thrive in an AI-first world.

Whether you're launching your career, pivoting into a new domain, or scaling up your expertise, the right course can open doors to global opportunities. London remains one of the best places to gain not only theoretical knowledge but also practical experience that employers truly value.

As AI continues to revolutionize how the world works, there’s never been a better time—or place—to master it.

[styrishai295]

Machine Learning Course for Beginners: A Comprehensive Guide to Getting Started

What is Machine Learning?

At its core, machine learning (ML) is a subset of artificial intelligence (AI) that enables computers to learn from data and make decisions or predictions without being explicitly programmed for each task. Instead of coding every rule, ML algorithms identify patterns and relationships within data to generate outcomes.

Why Enroll in an Online Machine Learning Course for Beginners?

Online courses offer flexibility, affordability, and access to expert instructors. A machine learning course online typically covers foundational topics such as supervised and unsupervised learning, data preprocessing, model evaluation, and common algorithms like linear regression, decision trees, and neural networks. These courses often include hands-on projects that reinforce learning and build your portfolio.

Key Topics Covered in a Beginner’s Machine Learning Course

Understanding Data and Features: Learning how to clean, preprocess, and select relevant features.

Supervised Learning: Techniques where models are trained on labeled data, such as classification and regression.

Unsupervised Learning: Methods like clustering and dimensionality reduction applied to unlabeled data.

Model Evaluation: Metrics like accuracy, precision, recall, and F1-score.

Overfitting and Underfitting: Strategies to improve model generalization.

Recommended Resources for Beginners

Several platforms offer beginner-friendly courses, including Coursera, edX, Udacity, and DataCamp. Many of these platforms provide free trials and introductory courses suitable for newcomers.

Practical Machine Learning Projects

To solidify your understanding, engaging in real-world projects is essential. Some popular machine learning projects for beginners include:

Iris Flower Classification: Using the classic Iris dataset to classify flower species.

Titanic Survival Prediction: Predicting passenger survival based on features like age, sex, and class.

Handwritten Digit Recognition: Using the MNIST dataset to recognize handwritten numbers.

Customer Churn Prediction: Analyzing customer data to predict churn rates.

These projects help you apply theoretical knowledge, learn to handle data, and fine-tune models.

AI Tutorial for Beginners: Understanding the Basics

Artificial Intelligence (AI) is a broader field that encompasses machine learning, natural language processing, computer vision, and more. For beginners, an AI tutorial for beginners provides a gentle introduction to these concepts, demystifying how machines can be taught to perform intelligent tasks.

What is AI?

AI involves creating systems that can perform tasks that typically require human intelligence, such as understanding language, recognizing images, making decisions, or solving problems.

Types of AI

Narrow AI: Systems designed for specific tasks (e.g., virtual assistants like Siri or Alexa).

General AI: Hypothetical systems with human-like intelligence (not yet realized).

How AI Relates to Machine Learning

While AI is the overarching field, machine learning is a subset focused on algorithms that learn from data. Many modern AI applications rely heavily on ML techniques, making understanding both essential.

Basic Concepts in AI

Natural Language Processing (NLP): Teaching machines to understand and generate human language.

Computer Vision: Enabling machines to interpret visual information.

Robotics: Designing intelligent robots capable of perception and action.

Getting Started with AI

Beginners can start with free tutorials, videos, and introductory courses that cover fundamental concepts, popular algorithms, and basic programming skills in Python or R.

Combining Learning: Online Machine Learning Course and Projects

Enrolling in a machine learning course for beginners is an excellent way to systematically learn the concepts, gain practical experience, and work on machine learning projects that enhance your skills. These projects often involve datasets from Kaggle or UCI Machine Learning Repository, providing real-world scenarios to apply your knowledge.

Why Practical Projects Matter

Projects help you understand data handling, feature engineering, model selection, and evaluation. They also build your portfolio, which is valuable when seeking internships or jobs in AI and ML.

Resources to Find Projects

Many online courses include project modules, and platforms like Kaggle host competitions suitable for beginners. Additionally, GitHub repositories often showcase beginner-friendly ML projects.

[bostoninstituteofanalytics1]

Artificial Intelligence Course in Chicago: Your Complete 2025 Guide

Artificial Intelligence (AI) is no longer just a futuristic concept — it’s a core driver of innovation across industries. From voice recognition and self-driving cars to predictive analytics and AI-powered automation, the technology is reshaping our world. As the demand for AI professionals grows, cities like Chicago are becoming popular destinations for AI education and career opportunities.

If you're looking to build or advance your career in AI, this comprehensive guide to Artificial Intelligence courses in Chicagowill help you navigate your options, understand what to expect, and choose the right learning path for your goals.

Why Study Artificial Intelligence in Chicago?

Chicago is more than just the Windy City — it’s an emerging tech hub with a growing AI ecosystem, home to prestigious universities, innovation labs, and Fortune 500 companies investing heavily in automation and data science.

1. Thriving Tech and Startup Scene

Chicago has made a name for itself in fintech, healthtech, and logistics innovation. Startups and enterprises in these sectors are rapidly adopting AI technologies, making the city a hotspot for AI jobs and experimentation.

2. Access to Top Institutions

World-renowned universities and specialized institutes in Chicago offer AI and machine learning courses aligned with current industry standards. These include both academic degrees and professional certifications.

3. Robust Career Opportunities

Chicago is home to major employers like Google, IBM, McDonald’s Tech Lab, Morningstar, and United Airlines — all of which leverage AI for operations and customer engagement.

4. Supportive Learning Environment

From university incubators to community tech groups and AI-focused meetups, Chicago offers plenty of support for learners and aspiring professionals.

What Does an Artificial Intelligence Course in Chicago Cover?

An Artificial Intelligence course in Chicago provides a well-rounded curriculum that balances theoretical foundations with real-world applications. You can expect most programs to include:

1. AI Foundations

Overview of AI history and evolution

Applications across sectors (healthcare, finance, retail, etc.)

Introduction to key AI concepts and terminologies

2. Machine Learning & Deep Learning

Supervised and unsupervised learning

Neural networks and deep learning architectures

Use of frameworks like TensorFlow, PyTorch, and Keras

3. Natural Language Processing (NLP)

Sentiment analysis

Language models (e.g., ChatGPT, BERT)

Building chatbots and text-based AI systems

4. Computer Vision

Image classification and object detection

Real-time video processing

Applications in surveillance, healthcare, and automotive

5. Programming for AI

Python for AI and data science

Data cleaning, visualization, and modeling

Use of libraries like NumPy, pandas, Scikit-learn

6. Ethical and Responsible AI

Fairness, accountability, and transparency in AI

Data privacy and algorithmic bias

Societal impact of AI systems

7. Capstone Projects

Many AI courses in Chicago culminate in a hands-on project or portfolio, allowing students to apply their skills in real-world scenarios.

Types of AI Courses Available in Chicago

1. University Degree Programs

Major universities in Chicago offer undergraduate and graduate programs in AI or related fields such as computer science and data science.

Examples:

Bachelor of Science in Artificial Intelligence

Master’s in Machine Learning or Data Science

PhD programs with AI research tracks

Top Institutions:

University of Chicago

Northwestern University

DePaul University

Illinois Institute of Technology

2. Professional Certificate Programs

Designed for working professionals and career changers, these short-term programs focus on building job-ready AI skills.

Typical Duration: 3–12 months Mode: Online, hybrid, or on-campus Topics: Generative AI, machine learning, NLP, AI product development

3. AI Bootcamps in Chicago

Bootcamps are immersive, accelerated programs that teach AI fundamentals through projects and real-world case studies.

Popular Providers:

Flatiron School

General Assembly

BrainStation

Local institutes offering in-person or hybrid training

4. Corporate and Custom AI Training

Companies in Chicago are increasingly offering internal AI upskilling programs. Several training providers offer customized corporate workshops tailored to specific industries such as finance, retail, and logistics.

Who Should Take an AI Course in Chicago?

Artificial Intelligence is not just for coders. Professionals from all backgrounds are encouraged to enter this field. AI courses are ideal for:

College students or recent graduates in STEM fields

Data analysts and software developers looking to upskill

IT professionals and engineers interested in automation

Business leaders wanting to integrate AI into operations

Career changers seeking a high-growth, future-proof path

Many Chicago-based programs offer beginner to advanced-level courses, ensuring there's a path for everyone.

Career Paths After an AI Course in Chicago

Completing an AI course in Chicago can lead to a wide range of job opportunities in the city’s fast-evolving tech market.

High-Demand Roles:

AI Engineer

Machine Learning Engineer

Data Scientist

AI Product Manager

NLP Engineer

Computer Vision Specialist

Robotics Engineer

Top Industries Hiring AI Professionals in Chicago:

Finance & Insurance – Predictive modeling, fraud detection

Healthcare – Medical imaging, patient care automation

Retail & E-commerce – Recommendation systems, demand forecasting

Logistics & Transportation – Route optimization, autonomous systems

Marketing & Advertising – AI-driven customer segmentation and targeting

Final Thoughts

The demand for AI professionals is surging, and the opportunities in a city like Chicago are vast and diverse. Whether you’re a student aiming to future-proof your career, a professional seeking to pivot into AI, or a business leader exploring AI integration — now is the time to invest in AI education.

A well-structuredArtificial Intelligence course in Chicago can equip you with the skills, experience, and credentials needed to stand out in this competitive field. With access to expert instruction, practical training, and a vibrant tech ecosystem, Chicago offers an ideal environment for launching or advancing your career in AI.

If you’re ready to take the next step, explore programs that align with your goals, offer strong mentorship, and emphasize real-world applications. The future of technology is being built today — and with the right training, you can be part of that transformation.

[alexanderallen13728]

Decoding CCTV Costs in NZ: Budgeting for Your Home or Business Security System

In today's world, security is a top priority for both homeowners and business owners in New Zealand. Protecting your property, assets, and people provides invaluable peace of mind. CCTV (Closed-Circuit Television) systems are a cornerstone of modern security, acting as a powerful visual deterrent, providing crucial evidence in case of incidents, and allowing for remote monitoring.

If you're considering installing a CCTV system, whether for your home or business, one of the first and most significant questions is: how much will it actually cost?  

Understanding the investment required for a CCTV system goes beyond simply looking at the price of cameras online. A complete, effective system involves various components and, crucially, professional installation tailored to your specific property. Costs can vary significantly based on the system's complexity, the number of cameras needed, and the type of technology chosen.

This article aims to provide a detailed breakdown of CCTV system costs in NZ, decoding the price tag associated with the hardware components and the vital factor of professional installation labour. We'll explore how different factors influence the final price and offer typical cost ranges for standard setups to help you budget effectively for your security investment.  

Why Invest in CCTV Security? (Beyond the Cost)

Before we delve into the numbers, let's quickly recap the value proposition that justifies the investment in CCTV:

Deterrence: Visible cameras are a major deterrent to potential intruders or vandals.  

Evidence: Recorded footage provides invaluable evidence for police and insurance claims in case of theft, vandalism, or other incidents.  

Monitoring: Allows you to check on your property remotely via smartphone or computer.  

Peace of Mind: Knowing your property is being monitored provides reassurance.  

A CCTV system is an active layer of defence and vigilance for your property.  

The Components: Breaking Down CCTV Hardware Costs

A functional CCTV system is typically made up of several key hardware components, each contributing to the overall cost:  

Cameras: These are the 'eyes' of your system. Their cost varies dramatically based on type and features.  

Price Range (Indicative per Camera):

Basic (Indoor only, low resolution, limited night vision): $50 - $150+ per camera

Mid-Range (Outdoor rated, 2MP-4MP resolution, good IR night vision, basic motion detection): $150 - $400+ per camera

High-End (4K+ resolution, advanced analytics, long-range IR, specialised types like PTZ - Pan/Tilt/Zoom, anti-vandal, covert): $400 - $1,500+ per camera (PTZ and specialist cameras can be several thousand dollars each)

Factors Influencing Camera Price:

Resolution: Higher resolution (e.g., 4K/8MP) costs more than lower resolution (e.g., 2MP/1080p) but provides clearer images allowing for better detail (e.g., facial recognition, license plates).

Features: Analytics (object detection, line crossing), audio capabilities (microphone, speaker), built-in storage (SD card slot), Wide Dynamic Range (WDR - for challenging lighting), advanced night vision technologies increase price.

Durability & Type: Outdoor cameras require weatherproofing (IP rating) and sometimes vandal resistance (IK rating), adding cost. Different camera types (dome for discreet indoor/outdoor, bullet for obvious deterrence/longer range, PTZ for controllable view) have different price points reflecting their complexity and features.  

Recorder (NVR/DVR): This is the central hub that receives video feeds from the cameras, processes them, allows live viewing, and manages recording to storage.  

DVR (Digital Video Recorder): Used for older analog cameras or newer Analog HD cameras (transmit video over coaxial cable).

NVR (Network Video Recorder): Used for IP cameras (transmit video over network/Ethernet cable). Generally more powerful and more expensive than DVRs for the same number of channels but support higher resolutions and advanced IP camera features.  

Price Range (Indicative): Varies based on the number of camera channels it supports (e.g., 4, 8, 16, 32 cameras) and its processing capabilities/features.

4 or 8 Channel Basic DVR/NVR: $200 - $500+

8 or 16 Channel Mid-Range NVR/DVR: $500 - $1,200+

16+ Channel High-End/Commercial Grade NVR/DVR: $1,200 - $5,000+ (or significantly more for large enterprise systems)

Storage (Hard Drives): Video footage needs to be stored, typically on Hard Disk Drives (HDDs) installed within the NVR or DVR.  

Price: Based on storage capacity, measured in Terabytes (TB). Surveillance-grade HDDs (designed for continuous recording) are recommended and cost more than standard PC drives.  

Factors Influencing Storage Needs: The number of cameras, their resolution, recording quality (compression settings), frame rate (frames per second), whether you record continuously or only on motion detection, and how many days or weeks of footage you wish to retain. More cameras, higher resolution, continuous recording, and longer retention times require significantly more storage capacity, increasing costs.  

Indicative HDD Cost (Surveillance Grade): Expect to pay roughly $150 - $300+ for a 2TB or 4TB drive. Larger drives (6TB, 8TB, 10TB+) cost proportionally more.

Cabling and Connectors: For wired systems, cables are needed to transmit video (and often power for IP cameras over Ethernet via Power over Ethernet - PoE).  

Cost: Depends on the type of cable (coaxial + power vs. Ethernet/network cable), the total length of runs needed for all cameras back to the recorder, and the cost of connectors, junction boxes, conduit, etc. More cameras and larger properties require significantly more cabling, adding cost.

Power Supplies: Cameras need power. This can be provided centrally via the recorder (PoE for IP cameras) or via separate power supplies/injectors.  

The Installation Factor: Labour Costs and Expertise

Once you have the components, they need to be installed and configured correctly. Professional installation labour is a significant, often equal to or exceeding the hardware cost, component of the total price, and for good reason.

Why Professional Installation is Costly (and Highly Recommended):

Work at Height: Cameras are often installed high up on exterior walls, under eaves, or on poles for optimal viewing angles and security. This requires working safely at height, using ladders or potentially scaffolding.  

Running Cables: This is a major labour component for wired systems. Cables need to be run neatly and discreetly from each camera location back to the recorder. This involves feeding cables through walls, ceilings, crawlspaces, roof cavities, or within conduit externally. It requires skill, specialised tools (fish tapes, cable pullers), and time to avoid damaging the building structure and achieve a tidy result.  

Electrical Work: While low voltage cabling (like network cable) doesn't always require an electrician for the cable run itself, connecting power supplies, integrating with existing electrical circuits, or ensuring compliance requires expertise. Many reputable security installers are qualified electricians or work directly with them, ensuring all electrical connections are safe and compliant with NZ standards. This is crucial for safety and avoiding legal issues.

Optimal Placement and Aiming: Professionals know where to position cameras to maximise coverage, minimise blind spots, avoid glare, and ensure they are angled correctly for the intended purpose (e.g., capturing faces at an entry point). Poor placement can render cameras useless.  

System Configuration: Configuring the recorder (setting up recording schedules, motion detection zones, remote access via network/internet, user permissions), integrating with network settings, and ensuring everything is working optimally requires technical knowledge.

Weatherproofing: Outdoor cameras and their connections need to be properly sealed and protected from the elements to ensure longevity and reliability. Poor weatherproofing leads to premature failure.  

Safety and Compliance: Working with electricity and at height carries risks. Qualified installers adhere to safety protocols and ensure the installation complies with all relevant NZ standards and codes.  

Role of a Qualified Electrician: Any work involving connecting a CCTV system's power supply directly to the mains wiring, installing new power points, or making connections that fall under regulated electrical work in NZ must be performed by a registered electrician.

Firms like Redline Electrical, being qualified electricians with security system experience, can provide a comprehensive service ensuring both the security system installation and any necessary electrical work are done safely and compliantly.  

Indicative Professional Installation Labour Cost: This is highly variable per camera point based on the difficulty of the cable run and access. Expect rates ranging roughly from $150 - $400+ per camera point.

For an entire system, installation labour could range from $500 - $2,000+ for a standard home system (e.g., 4 cameras with reasonably straightforward cable runs) and significantly more for complex or larger installations in businesses or larger properties. Labour often constitutes 40% - 60%+ of the total installed cost.  

Project Specifics: How Your Property & Needs Influence the Final Quote

The unique aspects of the property and your security requirements are key drivers of the final cost:

Number of Cameras: More cameras directly increase the total cost of components (cameras, recorder channels, storage) and significantly increase installation labour (more mounting points, more cable running).  

Property Size and Layout: Larger properties require more cameras for adequate coverage and longer, more complex cable runs. Multi-story buildings, properties with challenging access (e.g., difficult roof spaces, solid walls), or finished interiors needing minimal disruption add complexity and increase installation time and cost.  

System Type (Wired vs. Wireless, IP vs. Analog):

Wired: Higher initial installation labour cost due to cable running, but generally more reliable long-term. Component costs for Analog HD can be lower than IP, but IP offers more features.  

Wireless: Lower initial cable running labour, but potentially higher cost for robust wireless cameras and potential ongoing costs (battery replacement, dealing with connectivity issues). May require more units to cover areas if signal is poor.

IP vs. Analog HD: IP systems typically have higher component costs (cameras, NVRs, higher storage needs for high resolution) and require more networking knowledge for setup. Analog HD has lower component costs but is limited in resolution/features.

Complexity of Cable Runs: Running cables discreetly within walls and ceilings costs significantly more in labour than simply running cables externally in conduit or along skirting boards.

Required Features: Systems needing advanced analytics, PTZ cameras, high 4K+ resolution across multiple cameras, or integration with other security systems add substantial cost to components and often installation/configuration time.

Storage Requirements: Needing many weeks/months of continuous recording history significantly increases the cost of hard drives.

Location in NZ: Labour rates vary by region across the country.

Budgeting for Your CCTV System: Typical Cost Ranges

Combining the costs of components and professional installation, here are some indicative total installed cost ranges for standard CCTV setups in NZ. These are rough estimates and can vary widely based on all the factors discussed. Always obtain a specific quote.

Basic Home System (e.g., 4x entry-level Analog HD or basic IP cameras, simple DVR/NVR, adequate storage for a week+): $1,500 - $3,000+ Total Installed. Focuses on essential coverage and recording.

Mid-Range Home / Small Business (e.g., 4-8x mid-range IP or higher-end Analog HD cameras, better NVR/DVR, increased storage): $3,000 - $6,000+ Total Installed. Offers clearer images and more features.

Larger Home or Business / More Complex (e.g., 8-16+ higher-res/featured IP cameras, robust NVR/NVR, substantial storage, complex layout/cable runs): $6,000 - $15,000+ Total Installed. Caters to larger properties or more detailed surveillance needs.

Extensive / High-Security / Commercial Systems: Can range from $15,000 upwards into the tens or even hundreds of thousands depending on scale, complexity, and features.

Getting a Quote and Ensuring Value

To get an accurate budget for your specific home or business, contact a few reputable security installers or qualified electricians specialising in security systems in your area of NZ.

Provide details about your property (size, layout, number of stories, construction type) and your security goals (what areas need covering, what detail level you need - e.g., identifying faces at entry, monitoring vehicles).

Request a detailed quote that itemises the costs of components (specifying camera models, recorder type/channels, storage capacity) and breaks down the installation labour cost (e.g., per camera point, or an estimate for the total installation time/cost).

Ask about the system type (wired IP, wired Analog HD, wireless IP) and discuss which is most suitable and cost-effective for your needs and property layout, balancing initial cost with reliability and performance.

Inquire about warranty details for components and workmanship.

Prioritise getting quotes from qualified professionals, especially those who are registered electricians or work closely with them, as they can ensure the installation is safe, compliant, and effectively implemented, offering better value and peace of mind than a cheaper, unqualified installer.

Budgeting Tips

Budget for the total installed cost, including hardware and professional labour.

Allocate a small contingency (5-10%) for minor unforeseen issues during installation or minor adjustments to the plan.

Consider the ongoing costs: electricity for wired cameras (usually low), potential data usage for remote viewing, and possible future maintenance or replacement of components.

For hardwired systems, factor installation labour as a significant, often near 50%, portion of the total budget.

Conclusion: An Investment in Peace of Mind and Protection

Investing in a CCTV system for your home or business in New Zealand is an investment in security, deterrence, and peace of mind. Understanding the costs involved is crucial for effective budgeting. The total price comprises the cost of the system components (cameras, recorder, storage, cabling) and the significant factor of professional installation labour.  

Costs vary widely based on the number and type of cameras, the complexity of the recorder and storage needed, the type of system chosen (wired/wireless, IP/analog), and critically, the layout and accessibility of your property which dictates installation difficulty and time. Typical installed costs for standard home/small business systems in NZ range from $1,500 to $6,000+, escalating significantly for larger or more complex setups.  

Budgeting accurately requires breaking down these components, understanding the factors that influence price, and obtaining detailed quotes from reputable NZ installers or qualified electricians specialising in security systems.

Prioritising quality components and professional installation ensures you get a reliable, effective security system that provides genuine long-term value and protection for your investment, offering priceless peace of mind.

[nidhimishra5394]

On-shelf availability solution market experiencing robust demand due to rising interest in real-time intelligence

In today’s competitive retail landscape, ensuring that products are available on shelves when customers are ready to buy is more than a logistics challenge it is a strategic imperative. The On-Shelf Availability (OSA) solution market has emerged as a critical enabler for retailers and suppliers aiming to enhance customer satisfaction, drive sales, and reduce operational inefficiencies. As consumer expectations evolve and technological capabilities expand, the on-shelf availability solution market is undergoing rapid transformation, fueled by innovations in automation, data analytics, and artificial intelligence.

Understanding On-Shelf Availability

On-shelf availability refers to the presence of products in the right place, at the right time, and in the right quantities on store shelves. When products are out of stock, not only do sales suffer, but customer loyalty can be eroded. Research indicates that out-of-stock events result in lost sales of up to 8% for retailers, a significant figure in a low-margin industry.

OSA solutions are designed to combat this problem through real-time monitoring, predictive analytics, and responsive replenishment systems. These tools provide end-to-end visibility into the supply chain and store operations, enabling proactive identification and resolution of availability issues.

Market Drivers

Several factors are propelling the growth of the OSA solution market:

Rising Consumer Expectations: Today’s consumers expect seamless shopping experiences, both in physical stores and online. The inability to find desired products in-store often drives them to competitors or online alternatives. OSA solutions help retailers meet these expectations consistently.

Technological Advancements: The integration of IoT, AI, computer vision, and machine learning is revolutionizing how retailers monitor inventory. Smart shelves, RFID tagging, and shelf-scanning robots are increasingly being deployed to automate data collection and improve accuracy.

Shift to Omnichannel Retail: With retailers operating across multiple channels, maintaining accurate inventory across platforms is essential. OSA solutions ensure that inventory data is synchronized, enabling better fulfillment strategies such as buy-online-pick-up-in-store (BOPIS).

Supply Chain Disruptions: Global events such as the COVID-19 pandemic have highlighted the fragility of supply chains. In response, retailers are investing in OSA tools that provide early warnings for potential stockouts and optimize replenishment processes.

Focus on Operational Efficiency: Retailers are under pressure to control costs while improving service levels. OSA solutions support these objectives by reducing manual labor, minimizing inventory holding costs, and streamlining in-store operations.

Competitive Landscape and Key Players

The OSA solution market is characterized by a mix of established technology firms and innovative startups. Key players include Zebra Technologies, SAP, Oracle, Avery Dennison, and Trax. These companies offer diverse solutions ranging from handheld inventory scanners to sophisticated AI-powered image recognition systems that assess shelf conditions.

Retailers are also partnering with supply chain technology vendors and consultants to implement tailored OSA strategies. Customization, scalability, and integration with existing retail systems are critical factors influencing vendor selection.

Challenges to Market Growth

Despite its potential, the OSA solution market faces several challenges:

High Implementation Costs: Advanced OSA technologies can be capital-intensive, particularly for small and mid-sized retailers. The cost of sensors, infrastructure, and training can be prohibitive without clear short-term ROI.

Data Integration Issues: OSA tools must integrate seamlessly with point-of-sale (POS), ERP, and warehouse management systems to be effective. Data silos and legacy systems can hinder real-time visibility.

Privacy Concerns: Some OSA technologies, especially those involving video and image capture, raise concerns about customer privacy and data security.

Change Management: Organizational resistance to adopting new technologies can delay or limit the impact of OSA implementations. Training and leadership support are essential to ensure successful adoption.

Outlook and Opportunities

The future of the OSA solution market appears robust, with steady growth anticipated across global regions. North America and Europe are currently leading in adoption, but Asia-Pacific is expected to experience the highest growth rate due to the expansion of modern retail and e-commerce.

Emerging trends include the use of generative AI to forecast demand with higher precision, edge computing for real-time analytics at the store level, and integration with sustainability initiatives to reduce waste through smarter inventory practices.

Retailers that embrace OSA solutions not only stand to improve availability and reduce lost sales but also gain a competitive edge through enhanced operational agility and customer loyalty. As technology matures and becomes more affordable, broader adoption across all retail tiers is expected.

[humahira]

Technology & Innovation Trends in 2025: A New Era of Transformation

As we move deeper into 2025, the world continues to experience rapid advancements in technology and innovation. These changes are reshaping industries, transforming everyday life, and creating new opportunities for businesses and individuals alike. From artificial intelligence to quantum computing, the trends we’re witnessing are no longer on the horizon—they’re here, and they’re accelerating.

1. AI Agents and Autonomous Systems

Artificial intelligence has evolved far beyond simple automation. In 2025, we're seeing the rise of AI agents—autonomous software entities capable of executing tasks with minimal human input. These agents are increasingly being used in fields like legal services, supply chain management, and customer support. Unlike static AI models, agents can plan, learn from their environment, and carry out complex sequences of actions independently. This development is especially significant in enterprise settings, where AI agents can reduce costs and boost operational efficiency.

2. Synthetic Workforce

The concept of a synthetic workforce is no longer science fiction. With advancements in robotics and machine learning, AI-driven robots are taking on roles that once required human dexterity, decision-making, and adaptability. In logistics, for instance, robots can now navigate complex warehouse environments and handle delicate packaging. In agriculture, autonomous drones and harvesters are improving yields and reducing labor costs. This shift is transforming the labor market and pushing businesses to invest in human-machine collaboration strategies.

3. Quantum Computing Gains Traction

Quantum computing has transitioned from experimental labs to commercial reality. In 2025, major tech companies are offering early-stage quantum services that promise to solve problems classical computers cannot handle—such as drug discovery, cryptography, and optimization tasks in finance and logistics. Though we're still in the “noisy intermediate-scale quantum” (NISQ) phase, breakthroughs in qubit stability and error correction suggest a future where quantum advantage becomes mainstream in select industries.

4. Mixed Reality and Spatial Computing

With the rise of devices like Apple Vision Pro and Meta’s latest headsets, mixed reality (MR) is becoming more practical. MR, which blends physical and digital environments, is being adopted in education, manufacturing, design, and healthcare. In corporate training, immersive simulations help employees gain real-world experience without real-world risk. In retail, MR offers virtual product try-ons and showroom experiences that reduce return rates and improve customer satisfaction.

5. AI-Optimized Energy Grids

To address climate change and energy inefficiency, 2025 is seeing the rollout of smart grids enhanced with AI. These grids dynamically manage electricity distribution based on real-time demand and supply, integrating renewable sources like solar and wind more effectively. AI algorithms can also detect faults before they cause blackouts, improving grid resilience and sustainability. This is a crucial development for cities aiming to reduce carbon emissions and meet sustainability targets.

6. Synthetic Biology in Manufacturing

A lesser-known but impactful trend is the rise of synthetic biology in industrial applications. Instead of using petrochemicals, companies are engineering microbes to produce everything from textiles to biodegradable plastics. This innovation has profound implications for reducing waste, lowering carbon emissions, and creating a circular economy. Startups in this field are attracting significant venture capital as consumers and regulators alike demand greener alternatives to traditional manufacturing.

7. Digital Identity and Decentralized Systems

The need for secure and portable digital identities is becoming critical as more services move online. In 2025, blockchain-powered self-sovereign identity (SSI) systems are being adopted for everything from healthcare access to voting and financial transactions. These systems give users control over their personal data, reducing the risks of identity theft and centralized data breaches.

Conclusion

The technology and innovation trends of 2025 are defining a new digital era—one where AI agents, quantum computing, and immersive realities are not just possibilities but operational realities. Businesses that stay informed and adaptable will be better equipped to thrive in this fast-changing environment. At the same time, these advancements call for thoughtful governance, ethical oversight, and societal dialogue to ensure technology serves humanity, not the other way around.

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Merging design and computer science in creative ways

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Merging design and computer science in creative ways

The speed with which new technologies hit the market is nothing compared to the speed with which talented researchers find creative ways to use them, train them, even turn them into things we can’t live without. One such researcher is MIT MAD Fellow Alexander Htet Kyaw, a graduate student pursuing dual master’s degrees in architectural studies in computation and in electrical engineering and computer science.

Kyaw takes technologies like artificial intelligence, augmented reality, and robotics, and combines them with gesture, speech, and object recognition to create human-AI workflows that have the potential to interact with our built environment, change how we shop, design complex structures, and make physical things.

One of his latest innovations is Curator AI, for which he and his MIT graduate student partners took first prize — $26,000 in OpenAI products and cash — at the MIT AI Conference’s AI Build: Generative Voice AI Solutions, a weeklong hackathon at MIT with final presentations held last fall in New York City. Working with Kyaw were Richa Gupta (architecture) and Bradley Bunch, Nidhish Sagar, and Michael Won — all from the MIT Department of Electrical Engineering and Computer Science (EECS).

Curator AI is designed to streamline online furniture shopping by providing context-aware product recommendations using AI and AR. The platform uses AR to take the dimensions of a room with locations of windows, doors, and existing furniture. Users can then speak to the software to describe what new furnishings they want, and the system will use a vision-language AI model to search for and display various options that match both the user’s prompts and the room’s visual characteristics.

“Shoppers can choose from the suggested options, visualize products in AR, and use natural language to ask for modifications to the search, making the furniture selection process more intuitive, efficient, and personalized,” Kyaw says. “The problem we’re trying to solve is that most people don’t know where to start when furnishing a room, so we developed Curator AI to provide smart, contextual recommendations based on what your room looks like.” Although Curator AI was developed for furniture shopping, it could be expanded for use in other markets.

Another example of Kyaw’s work is Estimate, a product that he and three other graduate students created during the MIT Sloan Product Tech Conference’s hackathon in March 2024. The focus of that competition was to help small businesses; Kyaw and team decided to base their work on a painting company in Cambridge that employs 10 people. Estimate uses AR and an object-recognition AI technology to take the exact measurements of a room and generate a detailed cost estimate for a renovation and/or paint job. It also leverages generative AI to display images of the room or rooms as they might look like after painting or renovating, and generates an invoice once the project is complete.

The team won that hackathon and $5,000 in cash. Kyaw’s teammates were Guillaume Allegre, May Khine, and Anna Mathy, all of whom graduated from MIT in 2024 with master’s degrees in business analytics.

In April, Kyaw will give a TedX talk at his alma mater, Cornell University, in which he’ll describe Curator AI, Estimate, and other projects that use AI, AR, and robotics to design and build things.

One of these projects is Unlog, for which Kyaw connected AR with gesture recognition to build a software that takes input from the touch of a fingertip on the surface of a material, or even in the air, to map the dimensions of building components. That’s how Unlog — a towering art sculpture made from ash logs that stands on the Cornell campus — came about.

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Gesture Recognition for Feedback-Based Mixed Reality and Robotic Fabrication of the Unlog Tower Video: Alexander Htet Kyaw

Unlog represents the possibility that structures can be built directly from a whole log, rather than having the log travel to a lumber mill to be turned into planks or two-by-fours, then shipped to a wholesaler or retailer. It’s a good representation of Kyaw’s desire to use building materials in a more sustainable way. A paper on this work, “Gestural Recognition for Feedback-Based Mixed Reality Fabrication a Case Study of the UnLog Tower,” was published by Kyaw, Leslie Lok, Lawson Spencer, and Sasa Zivkovic in the Proceedings of the 5th International Conference on Computational Design and Robotic Fabrication, January 2024.

Another system Kyaw developed integrates physics simulation, gesture recognition, and AR to design active bending structures built with bamboo poles. Gesture recognition allows users to manipulate digital bamboo modules in AR, and the physics simulation is integrated to visualize how the bamboo bends and where to attach the bamboo poles in ways that create a stable structure. This work appeared in the Proceedings of the 41st Education and Research in Computer Aided Architectural Design in Europe, August 2023, as “Active Bending in Physics-Based Mixed Reality: The Design and Fabrication of a Reconfigurable Modular Bamboo System.”

Kyaw pitched a similar idea using bamboo modules to create deployable structures last year to MITdesignX, an MIT MAD program that selects promising startups and provides coaching and funding to launch them. Kyaw has since founded BendShelters to build the prefabricated, modular bamboo shelters and community spaces for refugees and displaced persons in Myanmar, his home country.

“Where I grew up, in Myanmar, I’ve seen a lot of day-to-day effects of climate change and extreme poverty,” Kyaw says. “There’s a huge refugee crisis in the country, and I want to think about how I can contribute back to my community.”

His work with BendShelters has been recognized by MIT Sandbox, PKG Social Innovation Challenge, and the Amazon Robotics’ Prize for Social Good.

At MIT, Kyaw is collaborating with Professor Neil Gershenfeld, director of the Center for Bits and Atoms, and PhD student Miana Smith to use speech recognition, 3D generative AI, and robotic arms to create a workflow that can build objects in an accessible, on-demand, and sustainable way. Kyaw holds bachelor’s degrees in architecture and computer science from Cornell. Last year, he was awarded an SJA Fellowship from the Steve Jobs Archive, which provides funding for projects at the intersection of technology and the arts. 

“I enjoy exploring different kinds of technologies to design and make things,” Kyaw says. “Being part of MAD has made me think about how all my work connects, and helped clarify my intentions. My research vision is to design and develop systems and products that enable natural interactions between humans, machines, and the world around us.”