#scalable data engineering

[creolestudios]

Choosing a Data Engineering Consultant: Your Complete Guide: Find the perfect data engineering consultant with our guide. Explore critical factors like flexibility, compliance, and ongoing support.

[mkcecollege]

As this synergy grows, the future of engineering is set to be more collaborative, efficient, and innovative. Cloud computing truly bridges the gap between technical creativity and practical execution. To Know More: https://mkce.ac.in/blog/the-intersection-of-cloud-computing-and-engineering-transforming-data-management/

[pitlanepeach]

Radio Silence | Chapter Six

Lando Norris x Amelia Brown (OFC)

Series Masterlist

Summary — Order is everything. Her habits aren't quirks, they're survival techniques. And only three people in the world have permission to touch her: Mom, Dad, Fernando.

Then Lando Norris happens.

One moment. One line crossed. No going back.

Warnings — Autistic!OFC, still quite angsty (sry), strong language.

Notes — Lots of plot, we're closing out the 2019 year in this one! Not much Lando in this one (Im still mad at him). This gets crazy. I can’t wait to hear your thoughts!

Want to be added to the taglist? Let me know! - Peach x

2019

Two weeks after Spa, Amelia stood outside her dad’s office at the MTC with a manila file in her hands and the taste of copper in her mouth.

The door was open, but she still knocked.

Zak looked up, startled, like he wasn’t used to seeing her there anymore — and maybe he wasn’t. She’d stayed away from the MTC for the past few weeks.

“Hey,” he said, getting up too quickly. “You want to come in?”

She stepped inside, cringing when her new trainers squeaked against the floor. Her arms were stiff from holding the file too tight. “Brought you something,” she said, and handed it over. No eye contact. She stared at a plaque on his shelf instead — a dusty one from 2007, still etched with a podium that felt like another lifetime.

Zak took the file and sat back down behind his desk. “You put this together?”

She nodded once. “It’s just data. Analysis. Trends.”

He opened the folder and started flipping through, slower than she wanted, be he was a much slower reader than she was. Pages of her notes, charts, predictive modelling, comparative pace metrics, aero versus power unit deltas from the season so far. Even some basic projections based on engine supplier performance curves over the last six years.

He hesitated, eyes scanning the pages. “What is this, Amelia?”

“McLaren’s had a better season,” she said, not bothering to hide the way her nose scrunched. “You’ll probably finish fourth in the Constructors’. Best of the rest. Everyone is going to be very happy.”

He looked up at her, sensing the ‘but’ before she even said it.

“I am not,” she said. “I don’t think we should be happy with fourth. I think we should be aiming for much higher.”

Zak leaned back slightly in his chair, file still open in front of him. “Amelia…”

“I think we should drop Renault after next season,” she said, cutting him off.

He blinked. “Jesus,” he muttered. “That’s a big swing.”

“I’ve run the numbers,” she said, a little sharper now. “Reliability. Raw power. Upgrade cycles. Driver feedback. Even manufacturer investment in long-term hybrid development. Renault is… not consistent, and they’re not progressing fast enough. Mercedes is more efficient, more stable, more scalable. If we want consistent podiums, a chance at race wins, then we need to align with a manufacturer that knows how to win. Not just how to score points.”

Zak sat back again, slower this time, like the weight of the idea was physically pressing into him. He tapped the edge of the file absently with his fingers.

“You know how much this would rock the boat, right?” he said. “We’ve spent years building this partnership. Renault’s got skin in the game. Contracts. Commitments. There’ll be consequences if we walk away.”

“I know,” she said. “But you always said we should act like a front-running team, even when we weren’t. So act like one. Make a decision like one.”

Zak was quiet. Still.

“I started working on this after Hockenheim,” she added, voice lower now. “I just… didn’t show anyone.”

He closed the file. “This isn’t a light suggestion, Amelia.” He sighed. 

“I know,” she said again. “But I think it’s the right one.”

He exhaled slowly and rubbed a hand across his mouth, then looked at her; really looked at her.

She was calmer than she’d been the last time they’d spoken. Still paler than usual, still guarded, but steadier somehow. Like something had hardened and solidified inside her in the silence of the past few weeks.

“I’ll take it to the board,” he said finally. “Quietly. Just to test the water. No promises.”

“Okay,” she said.

There was a beat. She stared at the paperweight on his desk, the one she’d bought him for Father’s Day when she was thirteen.

“I just want us to stop being afraid of wanting more,” she added, softer now. “That’s all.”

Zak didn’t respond right away.

And as she turned to go, hand already on the doorframe, he couldn’t help but ask, “You didn’t just do this for him, did you?”

She paused. “No,” she said. “I did it for the team. I did it for you.”

She walked out. 

— 

The press release dropped on a Thursday.

A neatly timed, efficiently worded, professionally curated announcement: McLaren Racing to become Mercedes-AMG Powertrain customer team from 2021 onwards.

Quotes from her dad. From Toto. From Andreas.

A photo of a handshake she wasn’t in.

No mention of the folder. No mention of the analysis. No mention of her. 

Of course there wasn’t. She hadn’t expected it.

Not really.

And yet she sat at her desk, surrounded by pages and pages of sketches of cooling architecture redesigns, and felt… strange.

Not angry. Not exactly.

Not proud either.

Mostly just quiet.

She clicked out of the article. Closed her browser. Opened a new tab, then immediately forgot why.

When she'd handed her dad the folder two weeks ago, it hadn’t even been about recognition. She hadn’t cared about credit. She’d just wanted them to be better. To try harder. To take a worthwhile risk. 

And when he’d said, I’ll take it to the board, she’d believed him.

She just didn’t think that would be the end of it.

He hadn’t spoken to her about it since. No follow-up. No texts. No update. No “you were right.” Not even a half-hearted thank-you over dinner or a passing “good job” in the hallway.

The decision had come. And it had come without her.

Which made sense. She wasn’t a department head. She wasn’t on the executive team. She didn’t even have an official job title.

She wasn’t owed anything.

But still… still, she sat there with her heart lodged high in her throat and her fingernails digging crescents into the seam of her jeans, wondering why she suddenly felt like a ghost.

Why it felt like this was supposed to mean something.

And why it hurt so much to realise that her dad was okay with taking her work, her time, her thinking, the thing she’d built, and not giving her even a whisper of recognition.

Because he was used to it.

Used to her just handing things over for free.

And the worst part was, he wasn’t the only one.

She’d been doing this for years, hadn’t she? Offering up all the sharpest pieces of herself like they were scraps. Little theories, little fixes, the way she could spot patterns no one else could, pick through race data like thread. Suggestions left on the kitchen counter, ideas floated during test weekends, whispers passed to engineers when no one else was listening. Quiet contributions, all of them. Invisible fingerprints.

She’d given it away. All of it. Every clever thought, every hard-earned observation; just laid it down, like it didn’t belong to her in the first place.

And now someone else got the credit. Again. And she wasn’t even surprised.

She was just tired. And quietly furious.

— 

The house smelled like woodsmoke and dog shampoo. Roscoe was already halfway into Amelia’s lap, snoring, his head heavy against her stomach as Lewis slid a mug of tea across the coffee table.

“Don’t get too comfortable,” he said, settling into the armchair across from her. “He’ll try and sleep there all day.”

“I won’t complain about that,” she murmured, scratching behind Roscoe’s ears. He was a big dog, solid and heavy. He felt a bit like her weighted blanket. Anchoring. 

Outside the windows, snow clung to the corners of Lewis’ sprawling. Quiet. Still. The way winter was meant to be. Amelia pulled her sleeves down over her hands and stared at the steaming mug.

Lewis leaned back, watching her over the rim of his cup. “You keeping up with the silly season chaos this year?”

“As always.” She nodded. 

“Gasly back to AlphaTauri, Hulkenberg out, Ocon sliding into Renault. There will be a bit of a bloodbath next year.” He said. 

She nodded, though her mind was elsewhere.

Lewis gave her a second longer before asking, “What about Lando? You two—”

“I don’t want to talk about Lando,” she said quickly, too quickly. Her eyes stayed on Roscoe’s fur.

Lewis didn’t press. He just leaned forward, brows faintly furrowed. “Right. Okay.” 

They let the silence settle again. Roscoe shifted in his sleep, his paws twitching as if chasing something through a dream. Then, quietly, Amelia spoke. “The Mercedes-McLaren deal,” she said, voice low. “That was mine.”

Lewis blinked, gave himself a second to repeat her words in his head, and then said. “What?”

“McLaren dropping Renault, becoming a Mercedes customer team.” She rubbed a thumb over Roscoe’s collar. “I ran all the projections. Power unit deltas, reliability, development pace, all of it. I put together the entire case. Handed it to my dad in a file. And two weeks later, they made the announcement.”

Lewis stared at her. “You’re serious?”

She nodded, swallowing. “No one said anything. Not to me. And I wasn’t… part of the meeting, or the rollout. He never even followed up. I just saw it in the press release like everyone else.” Her voice wavered, but didn’t break. “And I know I don’t work for McLaren. But I thought; I thought maybe it would mean something.” 

Lewis’s jaw twitched and his eyes looked darker than they usually did. “Amelia. That… that’s a big deal, you know that? That was your intellectual property.” 

“I know.” She hugged her arms tight around herself. “It just… it feels wrong to be angry. Like I should’ve known better. Like it’s my fault for not asking for anything in return. For just giving it away.”

“That’s not on you,” Lewis said, voice hardening. “That’s on him. Your dad. And on the team. They’ve taken advantage of you. You should get credit. You should get a bloody job offer and a signing bonus. Not… whatever the fuck this is.” 

She sniffed. “I don’t have a degree.”

Lewis scoffed. “So what? Since when does a piece of paper mean more than years of proven genius?”

That made her pause.

“You are one of the sharpest minds I’ve seen in this sport,” he said. “And I’ve been in it a long time. You see things before they happen. You think ahead of the curve. That’s what teams dream of having. And if McLaren can’t see that, if your own dad can’t see that, it’s not because it’s not there. It’s because he doesn’t know how to recognise it in you.”

She nodded. She already knew exactly what the problem was. “He doesn’t know how to see me as anything but his daughter.”

“Toto does,” Lewis said. “And that offer is still on the table, by the way.” 

Amelia looked away, cheeks flushing. 

“I’m not trying to pressure you. I just want you to know that you’ve got options,” Lewis said, softer now. “Real ones. And you don’t have to keep waiting around for your dad to finally recognise your potential.” 

She didn’t answer, but her hands were steady on Roscoe’s back now. And when she finally did glance at him, there was something a little sharp in her chest. Something that felt a lot like clarity.

— 

WhatsApp Groupchat — 2019 F1 Grid

Lewis H. @Lando You are an absolute prick.

Sebastian V. Good morning to you too?

Daniel R. Shit. What’d he do this time?

Charles L. Ah, this does not seem good.

Lando N. what the fuck did i do

Lewis H. You ghosted her. Like a child.

Carlos S. What??????????

George R. Wait are you serious?

Lewis H. Dead serious.

Lando N. oh my god can you not it’s literally none of your business ok

Max V. You’re an idiot, Norris.

Pierre G. Landooooo bro.

Alex A. Yeah nah that’s rough. You ghosted her? I actually thought you liked her, man.

Daniel R. She was so nice. Bet she feels like shit now.

Sebastian V. Is she okay? @Lewis

Lewis H. She’s fine. Too good for him anyway.

George R. I can’t believe this. Didn’t he literally write his racing number on her shoes? Or was that a fever dream??

Max V. @George He did. He’s just a right dickhead.

Carlos S. 😐 Told you not to screw it up, @Lando

Lando N. ok fucksake i get it You can all stop now i already feel like a piece of shit

Charles L. Why would you ghost her when she is so pretty and smart? I do not understand.

Daniel R. He’s still a kid. Dumb as hell. He’ll regret it in a few months, trust me.

Lewis H. He should be regretting it already.

Max V. Extremely dumb move. I wouldn’t have ghosted her and I’m famously difficult.

Sebastian V. Maybe I will set her up with my younger brother. He’s very clever. And rich.

George R. Is it weird if I throw my uncle’s name in the hat? He’s only 24. Really lovely guy.

Carlos S. My cousin Carlo is already in love. He will be thrilled to know she’s single.

Lando N. fuck off i get it I’m the villain Jesus christ can we drop it now

Daniel R. Glad you’re finally on the same page, mate!

Alex A. You could’ve just talked to her. Didn’t need to ghost her. That was cold, man.

Kimi R. 👍

— 

Interlagos was hot and loud and humming with tension, and Amelia made sure to stay pressed to the edges of it; a shadow against the garage walls, an expressionless face hidden behind a pair of black sunglasses.

It was her first time at any track since before Belgium. Her first time being in the same place as Lando since he’d decided that she was not worth knowing. And she was careful. Careful to keep to service corridors and briefing rooms, careful not to risk running into him. She wasn’t sure what would happen if she looked did. 

Nothing, probably. He would just ignore her, like he had been for two months. 

She had just slipped away from the hospitality bar, iced-coffee in hand, when a voice called out to her from the outside deck; warm, accented.

“Chica! Are you too busy to stop and talk with a very ignorant old man?”

She turned and found Carlos Sainz Sr. waving her over, a bottle of water in one hand and a wary smile on his sun-worn face.

“I was just—” she started, but he was already rising from his seat, gesturing for her to come join him. 

“Come, come. Sit. I have good seats here.”

She hesitated for a breath, then nodded and climbed the short steps up to the guest viewing area. The chaos of pit lane sprawled out below. Mechanics scrambled. Tyres stacked like soldiers. Race engines sang in the background, vicious and alive.

“Gracias,” she murmured, sliding into the chair beside him.

He nodded, then stared at her for a long, quiet second. “I wanted to say,” he said, his English thick with Madrid roots, but kind. “I think that… earlier in the year, I judged you too quickly.”

Amelia frowned at him. “Yes, you did.”

He sighed and nodded. “I assumed that you were just a pretty girl in the paddock.” He said. “And you see, my son has a terrible habit of becoming fixated on pretty things. But I realise now that I was wrong. You were there to, eh, help. To fix.” He sounded worn, like he’d had to work hard to say that out loud. 

She shrugged, staring out at the grandstands. They were full. “I was upset about it, I think. But it was not a big deal.”

“It was,” Carlos said, serious now. “It was a very big deal. My son made that clear to me. You are very clever. A real asset to the McLaren team.” He told her, firm and steady. 

She didn’t have anything to say to that. Just gave him a tight, (hopefully) polite smile and turned her eyes to the pit-lane as the cars peeled out of the garage to line up on the grid.

The race was long, and she stayed on the balcony throughout it all. Heat shimmered off the asphalt. Pit strategies flexed and fractured as the laps ticked down, and through it all, Amelia sat with her hands still in her lap, her mind sharper than the TV graphics overhead.

And when Carlos Sainz, the younger one, made it to third after a messy, brilliant final few laps, when the checkered flag waved and the paddock exploded into cheers and disbelief, she turned to his father and smiled, truly smiled, for the first time all day.

“Felicidades,” she said, voice soft but real. “That was very well done.”

Carlos Sr. beamed, pride etched into every line of his face. He stood up quickly, hurrying down to find his son and the rest of the team.

Amelia stayed.

The viewing deck emptied fast. Celebration echoed below. But she just slipped back into the motorhome, past the catering crew and out of the line of sight, into a quiet alcove near the storage lockers where no one would think to look for her.

She sat down on the floor, pressed her back against the cool wall, and closed her eyes.

She was proud. Of Carlos. Of the car she had helped make faster. Of the whisper of her fingerprints across the strategy that had put him on the podium.

But the truth still sat heavy on her ribs; that it had all happened without her. That even here, even now, she felt like a ghost.

— 

The paddock at night after a race was one of her favourite places in the world. Empty water bottles clattered in the wind, discarded tyre blankets lay forgotten in corners, and the once-buzzing garages now hummed low and tired beneath the fluorescent lights. Amelia walked slowly, hands in her pockets, trainers scuffing against the tarmac, the cool Brazilian evening pulling the heat from her skin.

She passed the Mercedes motorhome, its sleek black exterior reflecting the dim light. Through the tinted glass, she caught a glimpse of Toto Wolff, head bent in conversation with one of his engineers. Calm. Assured. In control.

She didn’t stop walking, but something in her twisted. Guilt, maybe. Or the quiet ache of uncertainty.

Red Bull had been circling for a while. Quiet at first; emails she half-dismissed, a few engineers asking her strangely specific questions, casual feelers through people she didn’t realise even knew her name. Then Christian on Dutch TV, mentioning her potential. Helmut at COTA, watching her from the edge of the pit wall like a cowboy evaluating livestock. And Adrian Newey, who bypassed all of them and emailed her directly in early November. Short. Direct. Complimentary in a way that didn’t feel rehearsed.

She hadn’t told her dad. Not yet.

Nothing was official, anyway.

“Brown,” came a voice behind her.

She turned, blinking as Max strode over from the Red Bull suite. His jacket was unzipped, and he still reeked faintly of champagne. Hair a bit damp. Grin lazy.

“Christian asked me to make sure you knew where to go,” he said, lifting his brows. “You’ve got ten minutes before Jos starts vibrating.”

She pulled a face. “Is everyone going to be there? Like… your dad is going to be there?”

“Obviously. It’s Red Bull. We are very theatric,” he said, deadpan. “Zusje, you are the most in-demand person in Formula 1 right now, of course everybody wants to be in the room when we finally win the battle for your brain.”

She narrowed her eyes at him. “Don’t call me that. Zusje. I don’t know what it means.”

“Little sister,” he said, Dutch accent thick, shrugging as he fell into step beside her. “It suits you. You talk just as much as I do, and you are equally annoying as me. We will give Christian many headaches, I think.”

“I always carry ibuprofen in my handbag.” She tried to joke, but it came out flat. 

Max looked at her for a moment, but then he grinned, so she imagined he must have thought her joke was funny. At least somewhat. “Adrian’s been trying to steal you since Canada.” He told her. 

She sighed. “That explains the espresso machine he sent to me during the summer break. I was very confused.”

He gave her a look. “You kept it?” He asked curiously. 

She nodded. “It is a good machine. Expensive.”

“Of course it was. It’s Adrian.” Max shrugged. 

They stopped a few feet from the Red Bull motorhome, which buzzed under the night lights like it was wired into a different voltage. Something kinetic hung in the air; possibility, maybe. Restlessness. Momentum.

She stared. “This feels like betrayal.”

Max rolled his eyes. “It is not betrayal.”

He nudged her shoulder. She recoiled, glaring at him. He raised his hands in defence. “Sorry. Sorry.” Then, quieter, he said. “You’ve outgrown the shadows, zusje. It is not your fault that your dad doesn’t know what to do with you. But we do. Adrian does. Christian definitely does. You belong somewhere that doesn’t try to keep you small.” 

She started to chew on her bottom lip anxiously, “Do you really think that I am worth all of this?”

He didn’t even blink. “I think you’re going to make me a world champion, Amelia Brown.”

— 

The Yas Marina Circuit gleamed beneath the Abu Dhabi sun, all smooth marble floors and overly modern hospitality suites. It felt more like a luxury mall than a racetrack, but Amelia liked it. Everything was polished, controlled. 

She slipped through the back corridors of the McLaren unit with practiced ease, unnoticed as usual. It was early, quiet, the calm before the chaos of FP1.

In Carlos’s driver room, she placed a neatly bound packet on the table beneath the television. His telemetry from the entire season, annotated and colour-coded: green for improvements, yellow for repeat tendencies, red for danger zones. She’d included braking inconsistencies, corner exit deltas, and fuel load trends, with suggestions tailored to the 2020 chassis.

He’d get it. He always did. Carlos read data like scripture.

In Lando’s room, she left the same. A different binder. Different tendencies. More throttle hesitation in traffic, sharper degradation when chasing, lapses in tire preservation across high-deg circuits. A note in the front, written in her smallest, sharpest handwriting.

You are an asshole. You are also better than your instincts. Learn the difference between fast and frantic. Good luck.

She didn’t linger. She didn’t need to. No one would know she’d been there except the two of them, and even then, it didn’t matter anymore. She’d done it. Helped them. One last time.

She turned down the corridor toward the exit, and almost walked straight into a man who was standing too stiffly in her path.

He was older, expensively dressed, with the familiar face of someone she’d seen on enough pit walls to know he didn’t belong there out of curiosity. Adam Norris. 

He looked her up and down, his voice clipped. “Ah. Amelia, is it?”

“That’s right.” She muttered. 

“I suppose we haven’t met.” He said. 

“No,” she said. “Not really.”

He hesitated. A beat passed. Two.

“I’ve… heard you’re very capable,” he said finally. “Talented. Bright.” He said it like he didn’t really believe it. 

She tilted her head. Frowned at him. “Did you tell Lando to stay away from me?”

He flinched, just barely. “I advised him to focus on his career.”

She smiled, but it didn’t reach her eyes. It wasn’t a happy smile. “You should teach your son better manners.”

She didn’t wait for a response. She stepped around him, slow, deliberate, and kept walking. Past the orange panels, past the McLaren logo, past the team she’d poured her entire self into. 

By the time the sun dipped below the grandstands and the lights came on for the weekend's final showdown, she was long gone from the paddock. A flight booked for her under a new team name. A seat at a new table. A blank page waiting for her red inked scrawl.

Red Bull knew she was coming.

They just didn’t know what she was prepared to become.

— 

The Browns’ living room was filled with the scent of cinnamon, pine, and whatever Christmas candle Tracy had been obsessed with that week. The fireplace crackled softly, fairy lights twinkled around the windows, and somewhere in the background, Ella Fitzgerald was crooning something vintage and sentimental.

Amelia sat cross-legged on the floor in sweatpants and a hoodie, half-watching as her dad unwrapped a book about American muscle cars from the 1960s. He grinned like a kid, holding it up for Tracy to see.

“This is great,” Zak said. “I’ve been looking for this one.”

“I know,” Tracy said, leaning in to kiss his cheek before returning to her place at the table with a glass of wine. “I listen, you know. I’m a good wife.”

Amelia smiled faintly. She hadn’t said much all day. She’d made breakfast. Helped put the chicken in the oven. Unwrapped the gifts they handed her; socks, a new set of sketching pencils, a silver pen engraved with her initials, and said thank you each time. But the weight in her chest hadn’t lifted, not even when her mother handed her a plate stacked high with garlicky roast potatoes. 

Zak was still talking, flipping through the book, animated now. “I’ve got such a good feeling about next season,” he said, his eyes bright. “The team’s in a good place. Carlos is dialled in, Lando’s matured a lot. And the Mercedes power unit; I know we’re still with Renault this year, but it’ll be a game-changer for us in twenty-one. Might be the year we really start bothering the top three again.”

Amelia swallowed hard. Her fork hovered above her plate, untouched. She glanced down at her food. It was getting cold. Her stomach turned.

Across the table, Tracy watched her. Her gaze was soft but sharp, a mother’s intuition in full force.

“Everything okay, Amelia?” She asked gently.

Amelia nodded. “Yeah,” she said, quickly. “Just tired. Long few months.”

Tracy didn’t push, but Amelia could tell she wasn’t convinced.

Her phone buzzed once, facedown on the table beside her glass of water. She flipped it over, half expecting a message from Carlos, or worse, from her dad, who had a terrible habit of sending her random articles from F1Tech like she wasn’t sitting five feet away.

But it wasn’t Carlos.

iMessage — 17:02pm

Vrolijk Kerstfeest,

Can’t wait for you to build my championship-winning car. – M.V. 

She exhaled, barely more than a breath. The corner of her mouth lifted. Not a smile, not really, but the closest she’d come to one all day. She tapped her fingers against the table, hiding the message beneath her palm.

Of all the gifts she’d been given that morning — the socks, the pen, the awkward hug from her dad that still smelled faintly of cinnamon and gasoline — this was the only one that made her feel something. Recognition.

She glanced at her dad, still rambling about wind tunnel simulations and team morale like the world hadn’t shifted beneath their feet. Then she looked back down at her plate, her fork still untouched.

She hadn’t told him yet. She didn’t know when she would.

Maybe she wouldn’t at all.

Maybe she’d take a page out of his book. 

— 

“Red Bull Racing Hire Amelia Brown as Technical Design Intern, Working Under Adrian Newey”

— Motorsport.com

Red Bull Racing Announces Amelia Brown as New Technical Design Intern “Mini Newey” Joins Office of the CTO Ahead of 2020 F1 Season

Red Bull Racing has officially confirmed the addition of Amelia Brown to its technical department, naming her as a Technical Design Intern working directly under Chief Technical Officer Adrian Newey.

Brown, 19, has quietly gained a reputation in Formula 1 circles for her analytical precision and instinctive approach to problem-solving. Though never officially affiliated with a team, her behind-the-scenes contributions have turned heads up and down the paddock — especially within the aerodynamic development community.

“She’s one of the sharpest minds I’ve come across in years,” said Newey in a brief statement. “She has an innate understanding of car behaviour, balance, and airflow mapping that’s rare at any level of engineering, let alone someone so early in their career.”

While her appointment as an “intern” may sound modest, Red Bull insiders are already referring to Brown as “Mini Newey,” a nod to the technical savant under whom she will be working and a reflection of the high expectations within the team.

Team Principal Christian Horner added, “We’ve always prided ourselves on fostering talent, and Amelia represents the next generation of creative engineering thought. Her insight, even during early informal conversations, has already helped shape some of our thinking going into 2020.”

When asked about her appointment, Brown declined to comment directly, but sources inside the team say she will be working across simulation, aero development, and design review cycles throughout the season.

“She’s not here to make coffee,” said Gianpiero Lambiase, Verstappen's race engineer. “She’s here to change the game.”

Red Bull Racing’s 2020 challenger is set to be unveiled in Bahrain next month. Whether Brown’s influence will be visible from day one remains to be seen — but if early whispers are any indication, she won’t stay behind the curtain for long.

NEXT CHAPTER

[adafruit]

🎄💾🗓️ Day 4: Retrocomputing Advent Calendar - The DEC PDP-11! 🎄💾🗓️

Released by Digital Equipment Corporation in 1970, the PDP-11 was a 16-bit minicomputer known for its orthogonal instruction set, allowing flexible and efficient programming. It introduced a Unibus architecture, which streamlined data communication and helped revolutionize computer design, making hardware design more modular and scalable. The PDP-11 was important in developing operating systems, including the early versions of UNIX. The PDP-11 was the hardware foundation for developing the C programming language and early UNIX systems. It supported multiple operating systems like RT-11, RSX-11, and UNIX, which directly shaped modern OS design principles. With over 600,000 units sold, the PDP-11 is celebrated as one of its era's most versatile and influential "minicomputers".

Check out the wikipedia page for some great history, photos (pictured here), and more -

And here's a story from Adafruit team member, Bill!

The DEC PDP-11 was the one of the first computers I ever programmed. That program was 'written' with a soldering iron.

I was an art student at the time, but spending most of my time in the engineering labs. There was a PDP-11-34 in the automation lab connected to an X-ray spectroscopy machine. Starting up the machine required toggling in a bootstrap loader via the front panel. This was a tedious process. So we ordered a diode-array boot ROM which had enough space to program 32 sixteen bit instructions.

Each instruction in the boot sequence needed to be broken down into binary (very straightforward with the PDP-11 instruction set). For each binary '1', a diode needed to be soldered into the array. The space was left empty for each '0'. 32 sixteen bit instructions was more than sufficient to load a secondary bootstrap from the floppy disk to launch the RT-11 operating system. So now it was possible to boot the system with just the push of a button.

I worked with a number DEC PDP-11/LSI-11 systems over the years. I still keep an LSI-11-23 system around for sentimental reasons.

Have first computer memories? Post’em up in the comments, or post yours on socialz’ and tag them #firstcomputer #retrocomputing – See you back here tomorrow!

[probablyasocialecologist]

Google search really has been taken over by low-quality SEO spam, according to a new, year-long study by German researchers. The researchers, from Leipzig University, Bauhaus-University Weimar, and the Center for Scalable Data Analytics and Artificial Intelligence, set out to answer the question "Is Google Getting Worse?" by studying search results for 7,392 product-review terms across Google, Bing, and DuckDuckGo over the course of a year.  They found that, overall, "higher-ranked pages are on average more optimized, more monetized with affiliate marketing, and they show signs of lower text quality ...  we find that only a small portion of product reviews on the web uses affiliate marketing, but the majority of all search results do."  They also found that spam sites are in a constant war with Google over the rankings, and that spam sites will regularly find ways to game the system, rise to the top of Google's rankings, and then will be knocked down. "SEO is a constant battle and we see repeated patterns of review spam entering and leaving the results as search engines and SEO engineers take turns adjusting their parameters," they wrote.

[...]

The researchers warn that this rankings war is likely to get much worse with the advent of AI-generated spam, and that it genuinely threatens the future utility of search engines: "the line between benign content and spam in the form of content and link farms becomes increasingly blurry—a situation that will surely worsen in the wake of generative AI. We conclude that dynamic adversarial spam in the form of low-quality, mass-produced commercial content deserves more attention."

[mbari-blog]

Meet MBARI: This team develops innovative new technology to map the seafloor 🤖🗺️

With marine life and ecosystems facing a rising tide of threats, the ocean exploration community needs nimble, cost-effective tools for measuring and monitoring ocean health. MBARI’s Control, Modeling, and Perception of Autonomous Systems Laboratory, known as the CoMPAS Lab is up to the challenge.

MBARI scientists and engineers build and adapt advanced technology that enhances ocean data collection. Led by engineer Giancarlo Troni, the CoMPAS Lab team develops scalable marine technology that can easily be modified for use in a wide variety of vehicles and platforms. 

Working with other teams across MBARI, the CoMPAS Lab leverages vehicles like the MiniROV to deploy and test new tools in Monterey Bay's submarine canyon and then adapt them for other mobile platforms. By sharing open-source design specifications and advanced algorithms with the wider ocean exploration community, we hope to expand access to MBARI’s engineering innovations.

MBARI technology is transforming what we know about the ocean and its inhabitants. Our scientists, engineers, and marine operations staff work together to create innovative tools for a more sustainable future where autonomous robots and artificial intelligence can track ocean health in real time and help us visualize ocean animals and environments. Studying our blue backyard is revealing our connection to the ocean—how it sustains us and how our actions on land may be threatening its future.

We’re spotlighting various teams at MBARI to showcase the different ways we’re studying the largest environment on Earth. We hope this series inspires a new generation of ocean explorers. Dive in.

[spacetimewithstuartgary]

New data model paves way for seamless collaboration among US and international astronomy institutions

Software engineers have been hard at work to establish a common language for a global conversation. The topic—revealing the mysteries of the universe. The U.S. National Science Foundation National Radio Astronomy Observatory (NSF NRAO) has been collaborating with U.S. and international astronomy institutions to establish a new open-source, standardized format for processing radio astronomical data, enabling interoperability between scientific institutions worldwide.

When telescopes are observing the universe, they collect vast amounts of data—for hours, months, even years at a time, depending on what they are studying. Combining data from different telescopes is especially useful to astronomers, to see different parts of the sky, or to observe the targets they are studying in more detail, or at different wavelengths. Each instrument has its own strengths, based on its location and capabilities.

"By setting this international standard, NRAO is taking a leadership role in ensuring that our global partners can efficiently utilize and share astronomical data," said Jan-Willem Steeb, the technical lead of the new data processing program at the NSF NRAO. "This foundational work is crucial as we prepare for the immense data volumes anticipated from projects like the Wideband Sensitivity Upgrade to the Atacama Large Millimeter/submillimeter Array and the Square Kilometer Array Observatory in Australia and South Africa."

By addressing these key aspects, the new data model establishes a foundation for seamless data sharing and processing across various radio telescope platforms, both current and future.

International astronomy institutions collaborating with the NSF NRAO on this process include the Square Kilometer Array Observatory (SKAO), the South African Radio Astronomy Observatory (SARAO), the European Southern Observatory (ESO), the National Astronomical Observatory of Japan (NAOJ), and Joint Institute for Very Long Baseline Interferometry European Research Infrastructure Consortium (JIVE).

The new data model was tested with example datasets from approximately 10 different instruments, including existing telescopes like the Australian Square Kilometer Array Pathfinder and simulated data from proposed future instruments like the NSF NRAO's Next Generation Very Large Array. This broader collaboration ensures the model meets diverse needs across the global astronomy community.

Extensive testing completed throughout this process ensures compatibility and functionality across a wide range of instruments. By addressing these aspects, the new data model establishes a more robust, flexible, and future-proof foundation for data sharing and processing in radio astronomy, significantly improving upon historical models.

"The new model is designed to address the limitations of aging models, in use for over 30 years, and created when computing capabilities were vastly different," adds Jeff Kern, who leads software development for the NSF NRAO.

"The new model updates the data architecture to align with current and future computing needs, and is built to handle the massive data volumes expected from next-generation instruments. It will be scalable, which ensures the model can cope with the exponential growth in data from future developments in radio telescopes."

As part of this initiative, the NSF NRAO plans to release additional materials, including guides for various instruments and example datasets from multiple international partners.

"The new data model is completely open-source and integrated into the Python ecosystem, making it easily accessible and usable by the broader scientific community," explains Steeb. "Our project promotes accessibility and ease of use, which we hope will encourage widespread adoption and ongoing development."

[usafphantom2]

Introducing F-21: The Latest 4th Generation Fighter Plane from Lockheed Martin

Lockheed Martin F-21

Taking its game forward, Lockheed Martin has proposed an improved version of the popular F-16 at Aero India 2019 called the F-21 and claims it will be the most advanced, 4th generation Fighter Aircraft in the world.

Lockheed Martin had earlier offered its F-16 has claimed that the F-21 will be specifically configured for the Indian Air Force and will strengthen India’s path to an advanced airpower future.

An option for new production, the F-21 will have a slew of the latest state of the art technological advancements and improvements that include a new radar system, stealth detection capabilities, and electronics design that add a lot of value to the already iconic aircraft.

F-21 will be based on a proven platform, with a new branding

TATA-Lockheed Martin F-21

“The F-21 is different, inside and out,” said Vivek Lall, vice president of Strategy and Business Development for Lockheed Martin Aeronautics.

Lockheed Martin has long said it plans to shift its F-16 production lines to India in cooperation with Tata. It has gone so far as to suggest it could establish an F-16 production line in the country regardless of whether it wins the MRCA deal or not.

For years, Lockheed Martin has been lobbying India for MMRCA contract in excess of 100 fighter jets. India traditionally bought its defence technology from and Russia, but recently, it has been buying American military technology, including the P-8 Poseidon and AH-64 Apache attack helicopter.

Now that there is a difficult competition between Lockheed Martin’s F-16, Boeing’s F/A-18E/F Super Hornet, the Swedish Gripen, French Rafale, European Eurofighter Typhoon, and Russian MiG-35. Lockheed Martin had to increase the stakes.

F-21 will be nimble, carry decent ordnance, and have lower costs to maintain

Weapon Systems of Lockheed Martin F-21

The F-21 will incorporate an upgraded mission computer, a state of the art avionics and includes multi-function displays. With a Central, Pedestal Display will help improve the crew’s situational awareness through Real-Time processing of the flight data.

In addition, the F-21 will also come with an upgradable display generator, a link-16 data link, HF/UHH/VHF multiple frequency radio communication support as well as IFF (identification friend or foe) enhancements.

The three original computers will be replaced with a single modular mission computer which provides far higher computing power to the avionics and weapons systems in addition to providing accurate targeting, air to air strike performances and information capabilities.

According to Lockheed Martin, the F-21 will be capable of providing affordable and scalable advanced combat capabilities through its Active Electronically Scanned Array radar. The Central Pedestal Display also provides a high-resolution display with colour maps, zoom functionality and Night vision systems, thereby helping to keep the aircraft in an enhanced state of Battle Awareness.

The Aircraft will also be capable of integration with the FLIR laser system and navigation as well as reconnaissance pods. The F-21 is also upgraded with state of the art threat warning systems, jammers, electronic countermeasure equipment pods and chaff and infrared flare dispensers to take care of complex and varied battlefield situations.

What will be the future of F-21?

As of now, the F-21 is just a concept. The F-21 will be tailor-made to meet the requirements of the Indian Airforce and will be a 4.5+ generation fighter if the company wins the estimated $18-billion order for the 115 planes.

Officially known as the “Fighting Falcon” commonly known as the Viper by pilots and crew, The F-16 is one of the most renowned and battle-tested supersonic fighter aircraft in the world. This single engine, multirole aircraft developed by Lockheed Martin (formerly General Dynamics), was developed originally for the United States Air Force and is now regarded as the most successful all-weather multirole fighter aircraft.

Entering into production almost four decades back in 1976, more than 4500 F-16 aircraft have been built and although no more bought by the United States Air Force, improved versions are being built for various export customers.

@defenseaviation.com

[freelancebrandscaling]

Freelance Brand Scaling Secrets: Empowering Brands to Dominate

Imagine a system designed not just for freelancers, but for brands—transforming ordinary companies into market powerhouses.

Freelance Brand Scaling is about more than generating ad copy or driving traffic; it’s about building an integrated brand growth engine that scales every facet of your business which is critical in today's world. Most "brand scaling" services out there focus on running Facebook ads. That’s child’s play. We take a full-stack approach—an elite-level, SEO-backed, AI-driven system designed to dominate your niche, multiply your ROAS, and create long-term sustainable growth.

We harness the precision of SEO, the art of funnel optimization, and the cutting-edge capability of AI to help your brand not only get noticed but become unforgettable. Think of it as a complete transformation toolkit that positions your brand as the leader in your market, turning every digital interaction into an opportunity for growth.

Our strategy is built on three core pillars:

SEO Mastery:

We engineer your online presence to rise above the noise. By optimizing your website and content with data-driven SEO techniques, we ensure that your brand consistently appears at the top of search results—attracting qualified, organic traffic that converts.

Funnel Optimization:

Every brand needs a roadmap to conversion. We create customized marketing funnels that seamlessly guide prospects through a journey—from initial awareness to final purchase. Whether it’s a compelling landing page, a series of nurturing emails, or an engaging video sales letter, each element is crafted to eliminate friction and maximize conversion rates.

AI-Powered Copy:

In a world where words make or break your brand, our AI-enhanced copy generation produces persuasive, tailor-made messaging that resonates with your audience. Using the best practices of legendary copywriters and the latest in artificial intelligence, we create copy that not only captures attention but drives real, measurable results.

This isn’t just about doing more—it’s about doing better. We help brands break free from the limitations of traditional marketing by combining timeless creative insights with modern digital strategies. The result? A dynamic, scalable brand that commands premium pricing, builds a loyal customer base, and dominates its market niche.

Step into a future where your brand isn’t just surviving—it’s thriving. Embrace a system that turns every click into a conversion, every interaction into an opportunity, and every campaign into a success story. With our Freelance Brand Scaling Secrets, you’re not just investing in marketing; you’re investing in a legacy of growth and excellence. Are you ready to empower your brand to dominate the marketplace? The future belongs to those who scale smarter!

[itidoltechnologies]

Outsourcing in 2025: Why India is Leading the Way in the Tech Revolution

In 2025, the global business landscape is evolving at lightning speed, and outsourcing remains a pivotal factor in helping companies stay competitive, innovative, and cost-effective. While outsourcing has long been a key business strategy, India has solidified its position as the global leader in this space, especially in technology. As organizations worldwide turn to outsourced tech solutions to fuel their growth, Indian companies, especially those like IT Idol Technologie, are leading the charge by reshaping the future of the tech landscape.

Outsourcing in 2025: The Need for Agility, Efficiency, and Innovation

As businesses face the pressure of rapidly evolving markets, the need for flexibility, innovation, and efficiency has never been more crucial. Outsourcing allows organizations to tap into global talent pools, access specialized expertise, and scale faster than ever before. In 2025, companies are increasingly turning to outsourced partners to help them adapt to new challenges, innovate with cutting-edge technologies, and deliver results quickly and cost-effectively.

Outsourcing offers a multitude of benefits: businesses can reduce overhead costs, enhance operational efficiency, and gain access to top-tier talent without the complexities of recruitment and training. In the tech industry, these advantages are particularly significant, as companies look for ways to stay ahead of the curve without draining resources.

India: The Epicenter of Outsourcing Excellence

Why has India become the go-to destination for outsourcing? The answer lies in its unique combination of highly skilled talent, cost-effective services, and a growing tech ecosystem. India has long been the leader in IT outsourcing, but in 2025, it has taken that legacy to new heights. Indian companies are not only providing basic IT services but are now at the forefront of delivering cutting-edge tech solutions, from custom software development to cloud services, data engineering, and more.

With a vast pool of highly educated professionals and a robust tech ecosystem, India offers the perfect environment for businesses looking to leverage outsourcing in the tech space. Indian tech companies have evolved to meet the growing demand for more complex and specialized services, and this is where firms like IT Idol Technologies are making a significant impact.

IT Idol Technologies: Leading the Paradigm Shift in Tech Outsourcing

IT Idol Technologies is at the heart of this transformation. As a forward-thinking outsourcing partner, IT Idol is helping businesses navigate the challenges of the digital age by offering tailored tech solutions that drive growth and innovation. Whether it’s custom software development, mobile app development, cloud computing, or digital commerce, IT Idol Technologies is leading the way in delivering high-quality, scalable, and cost-effective services that enable businesses to stay competitive.

The key to IT Idol’s success lies in its deep understanding of the tech landscape and its ability to adapt to the unique needs of each client. By leveraging its expertise in emerging technologies and staying ahead of industry trends, IT Idol ensures that businesses can continue to innovate while benefiting from the efficiency and cost savings that outsourcing provides.

How IT Idol Technologies is Helping Businesses Thrive in 2025

In 2025, companies are looking for outsourcing partners who can offer more than just basic services—they need a strategic ally who can provide innovative solutions that drive growth. IT Idol Technologies offers just that, with its specialized focus on high-demand areas like:

Custom Software Solutions: Helping businesses build tailored software to optimize operations and solve complex problems.

Mobile App Development: Developing native and cross-platform apps that engage users and enhance customer experiences.

Cloud Computing: Enabling businesses to scale quickly, securely, and cost-effectively with cloud-based solutions.

Digital Commerce: Providing comprehensive e-commerce solutions that help businesses reach customers and increase sales.

IT Idol’s ability to combine technical expertise with a customer-centric approach makes it a standout partner for businesses looking to stay ahead of the competition.

Unlock the Power of Outsourcing with IT Idol Technologies

As outsourcing continues to be a driving force in the global tech landscape, India remains the leader, offering businesses the ability to access top-tier talent and innovative solutions. IT Idol Technologies is at the forefront of this shift, providing companies with the tools and expertise they need to thrive in 2025 and beyond.

Ready to take your business to the next level? Whether you need custom software, mobile apps, cloud computing, or digital commerce solutions, IT Idol Technologies is here to help. Contact us today to discover how we can help you leverage the power of outsourcing to accelerate growth and innovation in your business.

[besttimeblogs]

Powering the Next Wave of Digital Transformation

In an era defined by rapid technological disruption and ever-evolving customer expectations, innovation is not just a strategy—it’s a necessity. At Frandzzo, we’ve embraced this mindset wholeheartedly, scaling our innovation across every layer of our SaaS ecosystem with next-gen AI-powered insights and cloud-native architecture. But how exactly did we make it happen?

Building the Foundation of Innovation

Frandzzo was born from a bold vision: to empower businesses to digitally transform with intelligence, agility, and speed. Our approach from day one has been to integrate AI, automation, and cloud technology into our SaaS solutions, making them not only scalable but also deeply insightful.

By embedding machine learning and predictive analytics into our platforms, we help organizations move from reactive decision-making to proactive, data-driven strategies. Whether it’s optimizing operations, enhancing customer experiences, or identifying untapped revenue streams, our tools provide real-time, actionable insights that fuel business growth.

A Cloud-Native, AI-First Ecosystem

Our SaaS ecosystem is powered by a cloud-native core, enabling seamless deployment, continuous delivery, and effortless scalability. This flexible infrastructure allows us to rapidly adapt to changing market needs while ensuring our clients receive cutting-edge features with zero downtime.

We doubled down on AI by integrating next-gen technologies from a bold vision that can learn, adapt, and evolve alongside our users. From intelligent process automation to advanced behavior analytics, AI is the engine behind every Frandzzo innovation.

Driving Digital Agility for Customers

Innovation at Frandzzo is not just about building smart tech—it’s about delivering real-world value. Our solutions are designed to help organizations become more agile, make smarter decisions, and unlock new growth opportunities faster than ever before.

We partner closely with our clients to understand their pain points and opportunities. This collaboration fuels our product roadmap and ensures we’re always solving the right problems at the right time.

A Culture of Relentless Innovation

At the heart of Frandzzo’s success is a culture deeply rooted in curiosity, experimentation, and improvement. Our teams are empowered to think big, challenge assumptions, and continuously explore new ways to solve complex business problems. Innovation isn’t a department—it’s embedded in our DNA.

We invest heavily in R&D, conduct regular innovation sprints, and stay ahead of tech trends to ensure our customers benefit from the latest advancements. This mindset has allowed us to scale innovation quickly and sustainably.

Staying Ahead in a Fast-Paced Digital World

The digital landscape is changing faster than ever, and businesses need partners that help them not just keep up, but lead. Frandzzo persistent pursuit of innovation ensures our customers stay ahead—ready to seize new opportunities and thrive in any environment.We’re not just building products; we’re engineering the future of business.

[paradoxcase]

I just saw a job description with a fascinating set of technical red flags:

Milliseconds matter! Performance is key! Optimizing database access, algorithms, choosing the right data structures, in general working to design performant systems.

This is a C# job. Usually, if optimization actually really matters in a piece of software, it would be written in C or C++, or maybe Go, not C#. So this means that either they used the wrong language for their stack (and have no intent to switch) or they don't know what actually makes good software good and just put this on the job description to make it look sharp.

We write code from the ground up. We don’t use a lot of frameworks, packages, etc. Not a lot of macro-level stuff. Core software engineering chops is what we’re looking for.

Translation: "We like to waste a lot of time reinventing the wheel".

Our suite of systems is vast and varied. There are web services (REST, SOAP, hybrid), windows services, daemons, websites, libraries, command line tools, windows apps.

"Our services have no consistent interface, or guiding design principles, and getting them to interact with each other sensibly will be a nightmare."

We have plans to redesign several of the older systems, which will be a lot of fun.

"Our legacy codebase is so bad that we finally decided we couldn't fix it and instead are throwing it all out and starting over again."

There are a lot of system interfaces, both within our own suite as well as across teams in the organization. Plenty of opportunities for collaboration with a lot of smart people.

"We mentioned earlier that our services have no consistent interface, but have we also mentioned that there are a lot of them?"

We have immediate needs for refactoring and several enhancements to allow us to scale up to meet increased loads.

"The technical debt is so bad that even management thinks it's time to refactor."

We work with LOTS of data (many, many TB) & it comes fast! Scalability & heavy transactional loads, heavy reporting are common challenges for us. We solve a lot of interesting and tricky problems. Often not your typical collect/save/display that you get at other places. Not snapping into established frameworks. Working across tiers as required. Opportunities for more advanced coding.

Normally this wouldn't be a red flag, but when combined with the rest of the job description, it just really hammers home the point that it's going to be a huge pain in the ass to work with this codebase and a lot of "clever" hacky shit will probably be required.

[govindhtech]

Google Cloud’s BigQuery Autonomous Data To AI Platform

BigQuery automates data analysis, transformation, and insight generation using AI. AI and natural language interaction simplify difficult operations.

The fast-paced world needs data access and a real-time data activation flywheel. Artificial intelligence that integrates directly into the data environment and works with intelligent agents is emerging. These catalysts open doors and enable self-directed, rapid action, which is vital for success. This flywheel uses Google's Data & AI Cloud to activate data in real time. BigQuery has five times more organisations than the two leading cloud providers that just offer data science and data warehousing solutions due to this emphasis.

Examples of top companies:

With BigQuery, Radisson Hotel Group enhanced campaign productivity by 50% and revenue by over 20% by fine-tuning the Gemini model.

By connecting over 170 data sources with BigQuery, Gordon Food Service established a scalable, modern, AI-ready data architecture. This improved real-time response to critical business demands, enabled complete analytics, boosted client usage of their ordering systems, and offered staff rapid insights while cutting costs and boosting market share.

J.B. Hunt is revolutionising logistics for shippers and carriers by integrating Databricks into BigQuery.

General Mills saves over $100 million using BigQuery and Vertex AI to give workers secure access to LLMs for structured and unstructured data searches.

Google Cloud is unveiling many new features with its autonomous data to AI platform powered by BigQuery and Looker, a unified, trustworthy, and conversational BI platform:

New assistive and agentic experiences based on your trusted data and available through BigQuery and Looker will make data scientists, data engineers, analysts, and business users' jobs simpler and faster.

Advanced analytics and data science acceleration: Along with seamless integration with real-time and open-source technologies, BigQuery AI-assisted notebooks improve data science workflows and BigQuery AI Query Engine provides fresh insights.

Autonomous data foundation: BigQuery can collect, manage, and orchestrate any data with its new autonomous features, which include native support for unstructured data processing and open data formats like Iceberg.

Look at each change in detail.

User-specific agents

It believes everyone should have AI. BigQuery and Looker made AI-powered helpful experiences generally available, but Google Cloud now offers specialised agents for all data chores, such as:

Data engineering agents integrated with BigQuery pipelines help create data pipelines, convert and enhance data, discover anomalies, and automate metadata development. These agents provide trustworthy data and replace time-consuming and repetitive tasks, enhancing data team productivity. Data engineers traditionally spend hours cleaning, processing, and confirming data.

The data science agent in Google's Colab notebook enables model development at every step. Scalable training, intelligent model selection, automated feature engineering, and faster iteration are possible. This agent lets data science teams focus on complex methods rather than data and infrastructure.

Looker conversational analytics lets everyone utilise natural language with data. Expanded capabilities provided with DeepMind let all users understand the agent's actions and easily resolve misconceptions by undertaking advanced analysis and explaining its logic. Looker's semantic layer boosts accuracy by two-thirds. The agent understands business language like “revenue” and “segments” and can compute metrics in real time, ensuring trustworthy, accurate, and relevant results. An API for conversational analytics is also being introduced to help developers integrate it into processes and apps.

In the BigQuery autonomous data to AI platform, Google Cloud introduced the BigQuery knowledge engine to power assistive and agentic experiences. It models data associations, suggests business vocabulary words, and creates metadata instantaneously using Gemini's table descriptions, query histories, and schema connections. This knowledge engine grounds AI and agents in business context, enabling semantic search across BigQuery and AI-powered data insights.

All customers may access Gemini-powered agentic and assistive experiences in BigQuery and Looker without add-ons in the existing price model tiers!

Accelerating data science and advanced analytics

BigQuery autonomous data to AI platform is revolutionising data science and analytics by enabling new AI-driven data science experiences and engines to manage complex data and provide real-time analytics.

First, AI improves BigQuery notebooks. It adds intelligent SQL cells to your notebook that can merge data sources, comprehend data context, and make code-writing suggestions. It also uses native exploratory analysis and visualisation capabilities for data exploration and peer collaboration. Data scientists can also schedule analyses and update insights. Google Cloud also lets you construct laptop-driven, dynamic, user-friendly, interactive data apps to share insights across the organisation.

This enhanced notebook experience is complemented by the BigQuery AI query engine for AI-driven analytics. This engine lets data scientists easily manage organised and unstructured data and add real-world context—not simply retrieve it. BigQuery AI co-processes SQL and Gemini, adding runtime verbal comprehension, reasoning skills, and real-world knowledge. Their new engine processes unstructured photographs and matches them to your product catalogue. This engine supports several use cases, including model enhancement, sophisticated segmentation, and new insights.

Additionally, it provides users with the most cloud-optimized open-source environment. Google Cloud for Apache Kafka enables real-time data pipelines for event sourcing, model scoring, communications, and analytics in BigQuery for serverless Apache Spark execution. Customers have almost doubled their serverless Spark use in the last year, and Google Cloud has upgraded this engine to handle data 2.7 times faster.

BigQuery lets data scientists utilise SQL, Spark, or foundation models on Google's serverless and scalable architecture to innovate faster without the challenges of traditional infrastructure.

An independent data foundation throughout data lifetime

An independent data foundation created for modern data complexity supports its advanced analytics engines and specialised agents. BigQuery is transforming the environment by making unstructured data first-class citizens. New platform features, such as orchestration for a variety of data workloads, autonomous and invisible governance, and open formats for flexibility, ensure that your data is always ready for data science or artificial intelligence issues. It does this while giving the best cost and decreasing operational overhead.

For many companies, unstructured data is their biggest untapped potential. Even while structured data provides analytical avenues, unique ideas in text, audio, video, and photographs are often underutilised and discovered in siloed systems. BigQuery instantly tackles this issue by making unstructured data a first-class citizen using multimodal tables (preview), which integrate structured data with rich, complex data types for unified querying and storage.

Google Cloud's expanded BigQuery governance enables data stewards and professionals a single perspective to manage discovery, classification, curation, quality, usage, and sharing, including automatic cataloguing and metadata production, to efficiently manage this large data estate. BigQuery continuous queries use SQL to analyse and act on streaming data regardless of format, ensuring timely insights from all your data streams.

Customers utilise Google's AI models in BigQuery for multimodal analysis 16 times more than last year, driven by advanced support for structured and unstructured multimodal data. BigQuery with Vertex AI are 8–16 times cheaper than independent data warehouse and AI solutions.

Google Cloud maintains open ecology. BigQuery tables for Apache Iceberg combine BigQuery's performance and integrated capabilities with the flexibility of an open data lakehouse to link Iceberg data to SQL, Spark, AI, and third-party engines in an open and interoperable fashion. This service provides adaptive and autonomous table management, high-performance streaming, auto-AI-generated insights, practically infinite serverless scalability, and improved governance. Cloud storage enables fail-safe features and centralised fine-grained access control management in their managed solution.

Finaly, AI platform autonomous data optimises. Scaling resources, managing workloads, and ensuring cost-effectiveness are its competencies. The new BigQuery spend commit unifies spending throughout BigQuery platform and allows flexibility in shifting spend across streaming, governance, data processing engines, and more, making purchase easier.

Start your data and AI adventure with BigQuery data migration. Google Cloud wants to know how you innovate with data.

[johndjwan]

OEM|ODM active optical cable | AOC Cable | Fibrecross

Our next-gen AOC Cable delivers ultra-fast, reliable data transfer that transforms data centers, high-performance computing, and enterprise networking. With its compact design and fiber-optic technology, you get unmatched speed, reduced latency, and scalability—empowering your infrastructure to thrive in today's digital age.

Whether you're optimizing your network for massive data loads or building a cutting-edge tech solution, our AOC Cable is engineered for performance and efficiency. Embrace the power of fiber optics and unlock a new realm of possibilities!

[shantitechnology]

How Small and Mid-Sized Engineering Firms Can Benefit from ERP

In today’s competitive business landscape, manufacturers and engineering companies in India are under constant pressure to improve efficiency, reduce costs, and enhance productivity.  The adoption of ERP for manufacturing companies in India has become more than just a trend—it is a necessity for survival and growth.  Manufacturing ERP software in India is specifically designed to address the unique challenges faced by the industry, offering seamless integration, automation, and data-driven decision-making capabilities.

If you are an engineering or manufacturing business looking to streamline your operations, this blog will help you understand why ERP software for engineering companies in India is essential and how choosing the best ERP for the engineering industry can revolutionize your operations.

Why ERP is Essential for Manufacturing and Engineering Companies

1.  Streamlining Operations and Enhancing Efficiency

One of the biggest challenges faced by manufacturing and engineering companies is managing various processes such as inventory, procurement, production, and distribution.  Manufacturing ERP software in India centralizes data, enabling real-time monitoring and control over every aspect of the business.  This eliminates redundant tasks, reduces manual errors, and improves efficiency.

2.  Improved Supply Chain Management

A well-integrated ERP system ensures smooth coordination with suppliers, vendors, and distributors.  With ERP for manufacturing companies in India, businesses can track raw materials, monitor supplier performance, and optimize procurement processes, reducing delays and ensuring a seamless supply chain.

3.  Enhanced Data-Driven Decision Making

With access to real-time data analytics and comprehensive reporting, ERP software for engineering companies in India empowers businesses to make informed decisions.  Managers can analyze production trends, forecast demand, and identify areas for improvement, leading to better business outcomes.

4.  Cost Reduction and Higher Profitability

Automation of processes helps in minimizing waste, reducing operational costs, and increasing profitability.  The best ERP for the engineering industry ensures resource optimization by tracking inventory levels, reducing excess stock, and eliminating inefficiencies in production planning.

5.  Compliance and Quality Control

Manufacturers must adhere to strict industry standards and regulatory requirements.  Manufacturing ERP software in India helps in maintaining compliance by providing documentation, audit trails, and quality control measures, ensuring that all products meet industry regulations.

Key Features of the Best ERP for Engineering Industry

Choosing the right ERP solution is crucial for achieving maximum benefits.  Here are some key features to look for in an ERP software for engineering companies in India:

Comprehensive Production Planning & Control – Ensures seamless coordination between different production units.

Inventory & Material Management – Tracks stock levels, raw materials, and procurement processes efficiently.

Financial Management – Integrates accounting, payroll, and financial reporting for better fiscal control.

Supply Chain Management – Enhances supplier relationships and improves procurement efficiency.

Customer Relationship Management (CRM) – Manages customer interactions, sales pipelines, and service requests.

Business Intelligence & Reporting – Provides real-time insights for strategic decision-making.

Scalability & Customization – Adapts to the growing needs of your business with modular functionalities.

Top ERP Software Providers in India

India is home to some of the top ERP software providers, offering advanced solutions for engineering and manufacturing businesses.  Companies like Shantitechnology (STERP) have emerged as leaders in providing industry-specific ERP solutions that cater to the unique requirements of manufacturing and engineering firms.

Why Choose STERP?

STERP is one of the top ERP software providers in India, offering customized ERP solutions specifically designed for the engineering and manufacturing industries.  Here is why STERP stands out:

Industry-Specific Solutions – Tailored to meet the challenges of the manufacturing and engineering sectors.

Cloud & On-Premise Options – Flexible deployment models to suit different business needs.

User-Friendly Interface – Easy to use, with intuitive dashboards and real-time analytics.

Excellent Customer Support – Dedicated support teams for implementation and ongoing assistance.

Scalable Solutions – Designed to grow with your business, ensuring long-term usability and return on investment.

How to Implement ERP for Maximum Success

Step 1:  Assess Business Needs

Understand your business requirements and identify key areas that need improvement.  Choose a solution that aligns with your industry needs.

Step 2:  Choose the Right ERP Software

Selecting the best ERP for the engineering industry involves comparing features, scalability, pricing, and vendor support.

Step 3:  Customization & Integration

Ensure that the ERP system integrates seamlessly with your existing tools and is customizable to fit your unique business processes.

Step 4:  Training & Support

Invest in training programs to ensure that your team is comfortable using the new system.  Opt for a provider that offers continuous support and upgrades.

Step 5:  Monitor & Optimize

Post-implementation, continuously monitor the system’s performance, gather feedback, and make necessary optimizations to enhance efficiency.

Future Trends in ERP for Manufacturing and Engineering

The ERP landscape is evolving rapidly, with emerging trends shaping the future of ERP for manufacturing companies in India.  Some key trends to watch include:

AI & Machine Learning Integration – Automating predictive maintenance and process optimization.

Cloud-Based ERP Solutions – Offering flexibility, remote accessibility, and cost savings.

IoT-Enabled ERP – Enhancing real-time tracking of production and inventory.

Mobile ERP – Allowing on-the-go access for better decision-making.

Blockchain for Supply Chain Management – Ensuring transparency and security in transactions.

Conclusion

Investing in ERP software for engineering companies in India is no longer an option—it is a necessity for businesses looking to stay ahead in the competitive market.  Whether you are a small manufacturer or a large-scale engineering firm, having the best ERP for the engineering industry can drive efficiency, improve decision-making, and enhance overall profitability.

With industry leaders like Shantitechnology (STERP) offering cutting-edge solutions, businesses can achieve digital transformation effortlessly.  As one of the top ERP software providers in India, STERP continues to empower manufacturing and engineering companies with tailored ERP solutions.

Are you ready to revolutionize your business with ERP?  Contact STERP today and take the first step towards seamless automation and unmatched efficiency!

[mokahr]

MokaHR: A Leading ATS for Enterprise Recruitment Management

In today's competitive business landscape, attracting and hiring top talent is more critical than ever. For large enterprises, managing the recruitment process efficiently and effectively can be a significant challenge. This is where Applicant Tracking Systems (ATS) come into play. One such leading solution is MokaHR, designed specifically to address the needs of enterprise-level recruitment management. In this article, we will explore what an ATS is, how MokaHR stands out in the market, and why it is essential for modern recruitment strategies.

What is an Applicant Tracking System (ATS)?

An Applicant Tracking System is a software solution that streamlines the recruitment process. It helps HR teams manage job postings, track candidate applications, screen resumes, schedule interviews, and communicate with candidates. The primary goals of an ATS include:

Centralizing Recruitment Data: All candidate information is stored in one place, making it easy to manage and retrieve.

Enhancing Efficiency: Automating routine tasks such as resume screening and interview scheduling saves time and reduces administrative workload.

Improving Candidate Experience: A well-designed ATS provides a smooth application process, which can enhance the employer’s brand and attract high-quality candidates.

Introduction to MokaHR

MokaHR (https://www.mokahr.io/)  is a leading ATS that has been specifically engineered for enterprise-level recruitment management. It offers a robust and scalable platform tailored to meet the demands of large organizations. With its comprehensive suite of features, MokaHR ensures that every stage of the hiring process is optimized for efficiency and effectiveness.

Key Attributes of MokaHR:

Enterprise Focus: MokaHR is built to handle the complex recruitment needs of large companies, offering high performance even when processing thousands of applications.

User-Friendly Interface: The platform is designed with usability in mind, making it easy for HR teams to navigate and operate, regardless of their technical expertise.

Integration Capabilities: MokaHR seamlessly integrates with other HR systems and tools, ensuring a cohesive and efficient human resource management ecosystem.

Key Features and Benefits of MokaHR

1. Streamlined Recruitment Process

MokaHR automates many aspects of recruitment, such as resume parsing, candidate screening, and scheduling interviews. This automation reduces manual errors and allows HR professionals to focus on strategic decision-making rather than administrative tasks.

2. Enhanced Data Management

With centralized data storage, HR teams can easily access and analyze candidate information. This helps in tracking recruitment metrics, monitoring candidate progress, and making data-driven hiring decisions.

3. Improved Candidate Experience

The platform provides candidates with a smooth and transparent application process. Features like real-time application tracking and prompt communication ensure that candidates remain engaged and informed throughout the recruitment cycle.

4. Scalability and Flexibility

Designed for enterprise-level needs, MokaHR scales effortlessly as the organization grows. Whether handling a high volume of applications or integrating with various other HR systems, MokaHR adapts to evolving business requirements.

5. Advanced Analytics and Reporting

MokaHR’s built-in analytics tools allow HR teams to generate detailed reports on key recruitment metrics. These insights help in refining recruitment strategies and improving overall hiring effectiveness.

Why Enterprise-Level Recruitment Management Needs MokaHR

For large organizations, the recruitment process is complex and requires a system that can manage high volumes of data and candidates efficiently. MokaHR meets these challenges by offering:

Automation of Routine Tasks: Frees up HR professionals to focus on strategic planning and candidate engagement.

Data-Driven Decision Making: Provides actionable insights through advanced analytics, enabling continuous improvement in recruitment strategies.

Seamless Integration: Works harmoniously with other HR tools and systems, ensuring a unified approach to talent management.

Enhanced Employer Branding: A smooth and professional recruitment experience can significantly boost the company’s reputation in the talent market.

Conclusion

In the realm of enterprise recruitment management, having a robust and reliable ATS is not just an advantage—it’s a necessity. MokaHR stands out as a leading solution, offering an integrated, efficient, and user-friendly platform that addresses the complex needs of large organizations. By automating key recruitment processes, managing vast amounts of data, and providing actionable insights, MokaHR empowers enterprises to attract, assess, and hire the best talent in a competitive market.

Adopting a system like MokaHR can transform recruitment from a cumbersome, manual process into a strategic advantage, ensuring that enterprises are well-equipped to meet current and future hiring challenges.