#Customized Web Scraping Company

[actowiz1]

Customized Web Scraping & Data Collection Company USA | UK | UAE

As a customized Web Scraping company in the USA, UK, UAE, we do web crawling, Data Extraction, auto quality checks as well as offer usable structured data. We provide web scraping and data extraction services to the world's most popular brands.

Know more: https://www.actowizsolutions.com/

[mariacallous]

Less than three months after Apple quietly debuted a tool for publishers to opt out of its AI training, a number of prominent news outlets and social platforms have taken the company up on it.

WIRED can confirm that Facebook, Instagram, Craigslist, Tumblr, The New York Times, The Financial Times, The Atlantic, Vox Media, the USA Today network, and WIRED’s parent company, Condé Nast, are among the many organizations opting to exclude their data from Apple’s AI training. The cold reception reflects a significant shift in both the perception and use of the robotic crawlers that have trawled the web for decades. Now that these bots play a key role in collecting AI training data, they’ve become a conflict zone over intellectual property and the future of the web.

This new tool, Applebot-Extended, is an extension to Apple’s web-crawling bot that specifically lets website owners tell Apple not to use their data for AI training. (Apple calls this “controlling data usage” in a blog post explaining how it works.) The original Applebot, announced in 2015, initially crawled the internet to power Apple’s search products like Siri and Spotlight. Recently, though, Applebot’s purpose has expanded: The data it collects can also be used to train the foundational models Apple created for its AI efforts.

Applebot-Extended is a way to respect publishers' rights, says Apple spokesperson Nadine Haija. It doesn’t actually stop the original Applebot from crawling the website—which would then impact how that website’s content appeared in Apple search products—but instead prevents that data from being used to train Apple's large language models and other generative AI projects. It is, in essence, a bot to customize how another bot works.

Publishers can block Applebot-Extended by updating a text file on their websites known as the Robots Exclusion Protocol, or robots.txt. This file has governed how bots go about scraping the web for decades—and like the bots themselves, it is now at the center of a larger fight over how AI gets trained. Many publishers have already updated their robots.txt files to block AI bots from OpenAI, Anthropic, and other major AI players.

Robots.txt allows website owners to block or permit bots on a case-by-case basis. While there’s no legal obligation for bots to adhere to what the text file says, compliance is a long-standing norm. (A norm that is sometimes ignored: Earlier this year, a WIRED investigation revealed that the AI startup Perplexity was ignoring robots.txt and surreptitiously scraping websites.)

Applebot-Extended is so new that relatively few websites block it yet. Ontario, Canada–based AI-detection startup Originality AI analyzed a sampling of 1,000 high-traffic websites last week and found that approximately 7 percent—predominantly news and media outlets—were blocking Applebot-Extended. This week, the AI agent watchdog service Dark Visitors ran its own analysis of another sampling of 1,000 high-traffic websites, finding that approximately 6 percent had the bot blocked. Taken together, these efforts suggest that the vast majority of website owners either don’t object to Apple’s AI training practices are simply unaware of the option to block Applebot-Extended.

In a separate analysis conducted this week, data journalist Ben Welsh found that just over a quarter of the news websites he surveyed (294 of 1,167 primarily English-language, US-based publications) are blocking Applebot-Extended. In comparison, Welsh found that 53 percent of the news websites in his sample block OpenAI’s bot. Google introduced its own AI-specific bot, Google-Extended, last September; it’s blocked by nearly 43 percent of those sites, a sign that Applebot-Extended may still be under the radar. As Welsh tells WIRED, though, the number has been “gradually moving” upward since he started looking.

Welsh has an ongoing project monitoring how news outlets approach major AI agents. “A bit of a divide has emerged among news publishers about whether or not they want to block these bots,” he says. “I don't have the answer to why every news organization made its decision. Obviously, we can read about many of them making licensing deals, where they're being paid in exchange for letting the bots in—maybe that's a factor.”

Last year, The New York Times reported that Apple was attempting to strike AI deals with publishers. Since then, competitors like OpenAI and Perplexity have announced partnerships with a variety of news outlets, social platforms, and other popular websites. “A lot of the largest publishers in the world are clearly taking a strategic approach,” says Originality AI founder Jon Gillham. “I think in some cases, there's a business strategy involved—like, withholding the data until a partnership agreement is in place.”

There is some evidence supporting Gillham’s theory. For example, Condé Nast websites used to block OpenAI’s web crawlers. After the company announced a partnership with OpenAI last week, it unblocked the company’s bots. (Condé Nast declined to comment on the record for this story.) Meanwhile, Buzzfeed spokesperson Juliana Clifton told WIRED that the company, which currently blocks Applebot-Extended, puts every AI web-crawling bot it can identify on its block list unless its owner has entered into a partnership—typically paid—with the company, which also owns the Huffington Post.

Because robots.txt needs to be edited manually, and there are so many new AI agents debuting, it can be difficult to keep an up-to-date block list. “People just don’t know what to block,” says Dark Visitors founder Gavin King. Dark Visitors offers a freemium service that automatically updates a client site’s robots.txt, and King says publishers make up a big portion of his clients because of copyright concerns.

Robots.txt might seem like the arcane territory of webmasters—but given its outsize importance to digital publishers in the AI age, it is now the domain of media executives. WIRED has learned that two CEOs from major media companies directly decide which bots to block.

Some outlets have explicitly noted that they block AI scraping tools because they do not currently have partnerships with their owners. “We’re blocking Applebot-Extended across all of Vox Media’s properties, as we have done with many other AI scraping tools when we don’t have a commercial agreement with the other party,” says Lauren Starke, Vox Media’s senior vice president of communications. “We believe in protecting the value of our published work.”

Others will only describe their reasoning in vague—but blunt!—terms. “The team determined, at this point in time, there was no value in allowing Applebot-Extended access to our content,” says Gannett chief communications officer Lark-Marie Antón.

Meanwhile, The New York Times, which is suing OpenAI over copyright infringement, is critical of the opt-out nature of Applebot-Extended and its ilk. “As the law and The Times' own terms of service make clear, scraping or using our content for commercial purposes is prohibited without our prior written permission,” says NYT director of external communications Charlie Stadtlander, noting that the Times will keep adding unauthorized bots to its block list as it finds them. “Importantly, copyright law still applies whether or not technical blocking measures are in place. Theft of copyrighted material is not something content owners need to opt out of.”

It’s unclear whether Apple is any closer to closing deals with publishers. If or when it does, though, the consequences of any data licensing or sharing arrangements may be visible in robots.txt files even before they are publicly announced.

“I find it fascinating that one of the most consequential technologies of our era is being developed, and the battle for its training data is playing out on this really obscure text file, in public for us all to see,” says Gillham.

[mostlysignssomeportents]

Kashmir Hill’s “Your Face Belongs to Us”

This Friday (September 22), I'm (virtually) presenting at the DIG Festival in Modena, Italy. That night, I'll be in person at LA's Book Soup for the launch of Justin C Key's "The World Wasn’t Ready for You." On September 27, I'll be at Chevalier's Books in Los Angeles with Brian Merchant for a joint launch for my new book The Internet Con and his new book, Blood in the Machine.

Your Face Belongs To Us is Kashmir Hill's new tell-all history of Clearview AI, the creepy facial recognition company whose origins are mired in far-right politics, off-the-books police misconduct, sales to authoritarian states and sleazy one-percenter one-upmanship:

https://www.penguinrandomhouse.com/books/691288/your-face-belongs-to-us-by-kashmir-hill/

Hill is a fitting chronicler here. Clearview first rose to prominence – or, rather, notoriety – with the publication of her 2020 expose on the company, which had scraped more than a billion facial images from the web, and then started secretly marketing a search engine for faces to cops, spooks, private security firms, and, eventually, repressive governments:

https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial-recognition.html

Hill's original blockbuster expose was followed by an in-depth magazine feature and then a string more articles, which revealed the company's origins in white nationalist movements, and the mercurial jourey of its founder, Hoan Ton-That:

https://www.nytimes.com/interactive/2021/03/18/magazine/facial-recognition-clearview-ai.html

The story of Clearview's technology is an interesting one, a story about the machine learning gold-rush where modestly talented technologists who could lay hands on sufficient data could throw it together with off-the-shelf algorithms and do things that had previously been considered impossible. While Clearview has plenty of competitors today, as recently as a couple of years ago, it played like a magic trick.

That's where the more interesting story of Clearview's founding comes in. Hill is a meticulous researcher and had the benefit of a disaffected – and excommunicated – Clearview co-founder, who provided her with masses of internal communications. She also benefited from the court documents from the flurry of lawsuits that Clearview prompted.

What emerges from these primary sources – including multiple interviews with Ton-That – is a story about a move-fast-and-break-things company at the tail end of the forgiveness-not-permission era of technological development. Clearview's founders are violating laws and norms, they're short on cash, and they're racing across the river on the backs of alligators, hoping to reach the riches on the opposite bank without losing a leg.

A decade ago, they might have played as heroes. Today, they're just grifters – bullshitters faking it until they make it, lying to Hill (and getting caught out), and the rest of us. The founders themselves are erratic weirdos, and not the fun kind of weirdos, either. Ton-That – who emigrated to Silicon Valley from Australia as a teenager, seeking a techie's fortune – comes across as a bro-addled dimbulb who threw his lot in with white nationalists, MAGA Republicans, Rudy Guiliani bagmen, Peter Theil, and assorted other tech-adjascent goblins.

Meanwhile, biometrics generally – and facial recognition specifically – is a discipline with a long and sordid history, inextricably entwined with phrenology and eugenics, as Hill describes in a series of interstitial chapters that recount historical attempts to indentify the facial features that correspond with criminality and low intelligence.

These interstitials are woven into a-ha moments from Clearview's history, in which various investors, employees, hangers-on, competitors and customers speculate about how a facial-recognition system could eventually not just recognize criminals, but predict criminality. It's a potent reminder of the AI industry's many overlaps with "race-science" and other quack beliefs.

Hill also describes how Clearview and its competitors' recklessness and arrogance created the openings for shrewd civil libertarians to secure bipartisan support for biometric privacy laws, most notably Illinois' best-of-breed Biometric Information Privacy Act:

https://www.ilga.gov/legislation/ilcs/ilcs3.asp?ActID=3004&ChapterID=57

But by the end of the book, Hill makes the case that Ton-That and his competitors have gotten away with it. Facial recognition is now so easy to build that – she says – we're unlikely to abolish it, despite all the many horrifying ways that FR could fuck up our societies. It's a sobering conclusion, and while Hill holds out some hope for curbing the official use of FR, she seems resigned to a future in which – for example – creepy guys covertly snap photos of women on the street, use those pictures to figure out their names and addresses, and then stalk and harass them.

If she's right, this is Ton-That's true legacy, and the legacy of the funders who handed him millions to spend building this. Perhaps someone else would have stepped into that sweaty, reckless-grifter-shaped hole if Ton-That hadn't been there to fill it, but in our timeline, we can say that Ton-That was the bumbler who helped destroy something precious.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/09/20/steal-your-face/#hoan-ton-that

[elsa16744]

Healthcare Market Research: Why Does It Matter? 

Healthcare market research (MR) providers interact with several stakeholders to discover and learn about in-demand treatment strategies and patients’ requirements. Their insightful reports empower medical professionals, insurance companies, and pharma businesses to engage with patients in more fulfilling ways. This post will elaborate on the growing importance of healthcare market research. 

What is Healthcare Market Research? 

Market research describes consumer and competitor behaviors using first-hand or public data collection methods, like surveys and web scraping. In medicine and life sciences, clinicians and accessibility device developers can leverage it to improve patient outcomes. They grow faster by enhancing their approaches as validated MR reports recommend. 

Finding key opinion leaders (KOL), predicting demand dynamics, or evaluating brand recognition efforts becomes more manageable thanks to domain-relevant healthcare market research consulting. Although primary MR helps with authority-building, monitoring how others in the target field innovate their business models is also essential. So, global health and life science enterprises value secondary market research as much as primary data-gathering procedures. 

The Importance of Modern Healthcare Market Research 

1| Learning What Competitors Might Do Next 

Businesses must beware of market share fluctuations due to competitors’ expansion strategies. If your clients are more likely to seek help from rival brands, this situation suggests failure to compete. 

Companies might provide fitness products, over-the-counter (OTC) medicines, or childcare facilities. However, they will always lose to a competitor who can satisfy the stakeholders’ demands more efficiently. These developments evolve over the years, during which you can study and estimate business rivals’ future vision. 

You want to track competing businesses’ press releases, public announcements, new product launches, and marketing efforts. You must also analyze their quarter-on-quarter market performance. If the data processing scope exceeds your tech capabilities, consider using healthcare data management services offering competitive intelligence integrations. 

2| Understanding Patients and Their Needs for Unique Treatment  

Patients can experience unwanted bodily changes upon consuming a medicine improperly. Otherwise, they might struggle to use your accessibility technology. If healthcare providers implement a user-friendly feedback and complaint collection system, they can reduce delays. As a result, patients will find a cure for their discomfort more efficiently. 

However, processing descriptive responses through manual means is no longer necessary. Most market research teams have embraced automated unstructured data processing breakthroughs. They can guess a customer’s emotions and intentions from submitted texts without frequent human intervention. This era of machine learning (ML) offers ample opportunities to train ML systems to sort patients’ responses quickly. 

So, life science companies can increase their employees’ productivity if their healthcare market research providers support ML-based feedback sorting and automation strategies. 

Besides, hospitals, rehabilitation centers, and animal care facilities can incorporate virtual or physical robots powered by conversational artificial intelligence (AI). Doing so is one of the potential approaches to addressing certain patients’ loneliness problems throughout hospitalization. Utilize MR to ask your stakeholders whether such integrations improve their living standards. 

3| Improving Marketing and Sales 

Healthcare market research aids pharma and biotechnology corporations to categorize customer preferences according to their impact on sales. It also reveals how brands can appeal to more people when introducing a new product or service. One approach is to shut down or downscale poorly performing ideas. 

If a healthcare facility can reduce resources spent on underperforming promotions, it can redirect them to more engaging campaigns. Likewise, MR specialists let patients and doctors directly communicate their misgivings about such a medicine or treatment via online channels. The scale of these surveys can extend to national, continental, or global markets. It is more accessible as cloud platforms flexibly adjust the resources a market research project may need. 

With consistent communication involving doctors, patients, equipment vendors, and pharmaceutical brands, the healthcare industry will be more accountable. It will thrive sustainably. 

Healthcare Market Research: Is It Ethical? 

Market researchers in healthcare and life sciences will rely more on data-led planning as competition increases and customers demand richer experiences like telemedicine. Remember, it is not surprising how awareness regarding healthcare infrastructure has skyrocketed since 2020. At the same time, life science companies must proceed with caution when handling sensitive data in a patient’s clinical history. 

On one hand, universities and private research projects need more healthcare data. Meanwhile, threats of clinical record misuse are real, having irreparable financial and psychological damage potential. 

Ideally, hospitals, laboratories, and pharmaceutical firms must inform patients about the use of health records for research or treatment intervention. Today, reputed data providers often conduct MR surveys, use focus groups, and scan scholarly research publications. They want to respect patients’ choice in who gets to store, modify, and share the data. 

Best Practices for Healthcare Market Research Projects 

Legal requirements affecting healthcare data analysis, market research, finance, and ethics vary worldwide. Your data providers must recognize and respect this reality. Otherwise, gathering, storing, analyzing, sharing, or deleting a patient’s clinical records can increase legal risks. 

Even if a healthcare business has no malicious intention behind extracting insights, cybercriminals can steal healthcare data. Therefore, invest in robust IT infrastructure, partner with experts, and prioritize data governance. 

Like customer-centricity in commercial market research applications, dedicate your design philosophy to patient-centricity. 

Incorporating health economics and outcomes research (HEOR) will depend on real-world evidence (RWE). Therefore, protect data integrity and increase quality management standards. If required, find automated data validation assistance and develop or rent big data facilities. 

Capture data on present industry trends while maintaining a grasp on long-term objectives. After all, a lot of data is excellent for accuracy, but relevance is the backbone of analytical excellence and business focus. 

Conclusion 

Given this situation, transparency is the key to protecting stakeholder faith in healthcare data management. As such, MR consultants must act accordingly. Healthcare market research is not unethical. Yet, this statement stays valid only if a standardized framework specifies when patients’ consent trumps medical researchers’ data requirements. Healthcare market research is not unethical. Yet, this statement stays valid only if a standardized framework specifies when patients’ consent trumps medical researchers’ data requirements. 

Market research techniques can help fix the long-standing communication and ethics issues in doctor-patient relationships if appropriately configured, highlighting their importance in the healthcare industry’s progress. When patients willingly cooperate with MR specialists, identifying recovery challenges or clinical devices’ ergonomic failures is quick. No wonder that health and life sciences organizations want to optimize their offerings by using market research. 

[lensnure-solutions]

Lensnure Solutions is a passionate web scraping and data extraction company that makes every possible effort to add value to their customer and make the process easy and quick. The company has been acknowledged as a prime web crawler for its quality services in various top industries such as Travel, eCommerce, Real Estate, Finance, Business, social media, and many more.

We wish to deliver the best to our customers as that is the priority. we are always ready to take on challenges and grab the right opportunity.

[castleashorses]

Mrs. Lovett’s pie shop had been the spot for many a patron as of late, but she sold nary a pie in that same time. The semi constant flow of neighbors had come to gift her their condolences for the loss of her, now late, husband Albert, but none felt the need to buy something.

Most sought her with pity in their eyes, knowing that Albert was the purse strings that held her entire operation together. But the money had dwindled with his health and with it the quality of her goods. She estimated she’d be out of money before the end of the year, a scant 2 and a half months. A hard timeframe to cut a profit and stay viable on the financially bleak Fleet Street. Mrs. Mooney held the market and Mrs. Lovett, well she held the gaze of a few lads who would indulge in her company over a pie or two. So she would smile, wink, let her touch linger a moment too long, just to put a pence or two in the till. Never anything more, but enough to keep them coming back for the promise of it.

Albert never noticed, if he did he never cared enough to say so, they often just lived together alone, except for the nights when they’d share a bed and the very rare romp. In a passive peacefulness with financial security and a life plagued with boredom and little else.

She did have a fondness for him, she wouldn’t have been able to manage if she didn’t but he was twice her age, in poor health, and a lumbering fellow she’d been heavily encouraged to wed. Stability was the goal and it was easily check off with him.

Her family had no prospects, no means to elevate her status, but with Albert she moved up a peg, she could have some control over her life and with it a quaint shop.

But that would soon be taken too if she couldn’t scrape together enough money to keep herself afloat.

After the acceptable mourning period passed, fewer people dropped until they stopped altogether. A month she noted to herself, that’s how long it takes for someone to forget about a pretty, young widow left to hang in her own web.

So it came as a surprise to her when the bell on her shop door chimed one afternoon.

‘A customer?!’ She whispered to herself as she hurried from the parlor where she’d been haunting the cabinets looking for things she could sell for a pence or two.

Before her, in the middle of her shop stood a man surrounded in the afternoon light. She stared, confused, examining him with curiosity, perhaps he said hello, but she didn’t hear it. Her mind somehow wanders back to reality to greet him.

“You must be lost,” she retorts, doing a scan of him from head to toe, he doesn’t seem to get the joke and she deduces quickly he’s not from around here. So she restarts, “What can I get ya?!”

It’s chipper and grating and reeks of desperation.

He seems nervous, cloaked in a black wool jacket, a crisp white shirt, and suspenders. She always liked a fella in suspenders. A handsome man, young, maybe a little older than her, clean shaven, with a brightness in his eyes.

“I had spoken to a Mrs. Talbert about needing a residence and she said you may be able to help.” He sticks his hand out awkwardly, “Benjamin, Benjamin Barker.”

“Nellie Lovett.” And she takes his soft hand with a firm grip. Electricity thrumming through her at the touch. Soft hands, not a laborer.

She is, however, confused. Mrs. Talbert ran a small shop down the street selling hats and other wears with her husband. They weren’t particularly close, a polite hello in the local town square, a few pleasantries. She was successful and a step above her station, a beacon of propriety who had no qualms elevating her image by scandalizing another’s.

Now why would Mrs. Talbert be sending a young man her way… oh.

The young widow needed a young fellow to revive her image. A woman living alone maintaining a business without a husband, scandalous. An easy and quick match if they wished to avoid becoming pariahs. At least she had good taste.

Perhaps she thought she’d be saving her from being pushed onto the streets to service the sailors.

“The room, upstairs. She said you had a room upstairs that may be available.”

She had mentioned it briefly to others who ran in the woman’s social circle. No one keeps a secret it seems. They also likely told her she was running out of money as well. Seems Mrs. Talbert found a way to provide Nellie with some income and a good scandal.

She crosses to him and finds a way to touch him again, giving him a little pat that’s just innocuous enough to pass as friendly. “Oh yes! Yes love of course. Sit, sit, I’ll get some ale and we can chat, eh?”

She takes the seat across from him and offers him the beer, though he doesn’t immediately go for it. Instead he sits up straight and gives her his full attention. Nice to get that without the accompanying bleary eyes for once

“Awfully well dressed for Fleet Street ain’t ya? Mustn’t be from ‘round here.”

He gives her an embarrassed smile, “Close enough.” Though his accent says farther.

It’s quiet as his eyes wander around the room, noticing a painting of a distinguished man on the farthest corner almost out of sight. He assumes her father, perhaps now long gone.

“Do you live here alone?” And he asks with sincerity, more so than most of the others who’d come to ogle, and it sends a sharp pang through her chest as it dawns on her.

“Alone? Yes.” She starts to sink into the feeling before returning to her senses and lightening the mood, “Me poor Albert died this fall, God rest his soul, but I make do.”

“A widow, at such a young age, I’m sorry.”

She would tend to forget her age. Albert being so much older she felt older by proxy, until someone like Benjamin entered her space.

“Tis alright,” she leans further onto the table toward him, “ya never know when a new opportunity will come calling.” Her pointed gaze causes him to drop his eyes to the table.

Too much Nellie, too much.

“How bout a tour?” And stands walking to his corner of the table, a little too close. He considers it, probably wondering about her intentions in having him alone in a private space. The rumors it could illicit for such a strapping young man.

“I don’t think it would be…” and before he can say ‘proper’ or ‘appropriate’ she cuts him off and tugs at his sleeve, “come now love, can’t be setting up without seeing it first.”

She can tell he hasn’t encountered a person like her before. Forward, almost too much, and void of any care for her reputation, or his.

On the contrary she’d love for the gossips to spout off about how she took the handsome young man up the stairs alone.

As they climb the stairs she prattles on, “So, the room ain’t much, there’s a main room, a bedroom, and small kitchen.“ She leaves the door ajar, for his sake, since he still seems uneasy.

“Kinda bare innit it?”

“Oh, no this is perfect.”

He moves around the room mentally placing objects.

She leans against the door frame to start her interrogation.

“What did you say it was ya did?”

“I didn’t. I’m a barber. If it’s alright by you I had hopes of turning this into my own shop.”

Her eyes glow at their shared entrepreneurial spirit. A barber and a baker, she indulges the idea of them running the building as a pair.

“Not at all dear. In fact,” she sidles next to him her shoulder pressed into his as they stand looking down at a vacant spot. “I’d say this spot right here, would be the perfect spot for a barber’s chair.”

He looks down where their bodies meet and then back to her. Whatever fascination may have washed over him is gone quickly as he moves to examine the other corners, but it’s enough to make her feel lightheaded.

“It’s yours then.”

The smile that glosses over his face as he surveys the space a final time is a sight she’ll stamp on this day, and look back on fondly.

He starts for the door, “Should we head downstairs and sort the details?”

“Oh aren’t ya a funny thing!”

And his puzzled look tells her he definitely isn’t from around here, “No details to sort dear, you move in when you like. Rent’ll be on the first of the month.”

He wants it, the room that is, but maybe he’d want her too. But she calms her impatient heart, in good time. She’d work her way into his heart, his life, his bed.

Maybe a small wedding, and a baby, one with her eyes and his crooked smile.

“Well then Mrs. Lovett,” no call me Nellie she wants to say, “I think we have a deal.”

This time when they shake he drapes his other hand over hers and pats. Progress. She yearns to be touched by him over and over, but this will do. Patience.

He’s out the door and on the landing as she fusses with the lock. The space between them minimal. She turns and they’re near flush, she wants to reach up and pull him to her lips, but in a blink he’s descending the stairs and out of sight.

When she catches up she finds him waiting at the counter, “Forget something, Benjamin?” If he won’t call her Nellie, then she won’t call him Mr. Barker.

He’s smiling and lite, “Well now I must have a good sense of the establishment below me, shouldn’t I?” She’s touched that he’s actually going to buy something, that he cares enough to make the effort to start a good relationship with his neighbor. “Two pies please.”

“Quiet the appetite!” She winks at him.

“Oh my wife must sample the goods as well!”

Her heart falls along with the muscles in her face.

“Oh you’re married?”

“Newlyweds actually, last May. She should be coming round from the market soon, I know she’d love to meet you.”

And as if on cue the door bell chimes and in walks a young woman, above her station, in a beautiful gown and bonnet holding a basket of goods and a beautiful bouquet of daisies.

Suddenly she feels old and pungent like a gillyflower discarded on the cobblestone left to rot.

But her lack of cheer doesn’t seem to effect Mr. Barker, it is of course Mr. Barker now, when he rushes to bring her forth and show off his chestnut haired bride.

“Mrs. Lovett this is my wife, Lucy.”

She doesn’t extend her hand, just nods, and Lucy does the same in return. Her hand landing on his chest as she tucks herself closer to his side.

“A pleasure.”

A curse.

—————-

They make quick work of their move and Mrs. Lovett keeps a close eye on the progress as she wanders up from time to time to offer them refreshments and food.

Lucy, while not outwardly annoyed with her, does seem to avoid any unnecessary interaction. Mr. Barker on the other hand always gladly accepts her offerings and she without evidence deduces one of them grew up on harder times than the other. He married up, same as she did.

At night when it’s quiet and she’s alone in her dark room she stares at the ceiling wondering where he may be standing, if it’s above her or in his shop but then the sound of heels dance across her ceiling and her mood sours.

The bitter sting of envy that rolls through her at the fantasy that she could have been the one upstairs if only she’d somehow met a man she never knew right before she knew him. If only she had been born with more to offer.

She buries her head when the noises leave the floor and move to thumping against the wall.

He comes down every so often to chat, spend some money, and then inevitably leave.

She knows Lucy is always lingering close by, keeping a close eye. Mrs. Lovett tries to keep her hands off him but the occasional touch or lingering exchange in money isn’t something she avoids or something Mr. Barker outright rejects, so she indulges.

Lucy only pops down on her own to pay the rent. It’s always a quick transaction smothered in pleasantries and haste.

One day when Mr. Barker takes an extended break from his customers he sits for his meal, a rare occurrence, especially solo. The shop is empty and she takes advantage of the privacy, plopping down in the chair beside him.

He’s sweet, interested, “How’s business?”

She looks around at the empty space, “Never been better.” And it gets a chuckle out of him.

“I do enjoy your company though, nice to see a friendly face voluntarily come in here.”

The smile is sincere and she’s moved by it enough to reach out and grasp his hand and give it a gentle squeeze. He doesn’t pull it away immediately, more finds a new task for it. Lifting a beaker of beer to his lips.

They both startle when the bell chimes and Lucy comes in, that sweet smile plastered on her face. She eyes the beer in his hand.

“My love, there’s a customer who needs attending upstairs.”

He presses the napkin to his mouth before standing and bidding Mrs. Lovett a good day.

Lucy however remains, exasperation closing in around her normally bright demeanor. He is her husband after all.

She conjures up a pitiful face, “He’s too polite to say it, naive even, but I see it so I will say it instead.” She can feel a burn at her feet, slowly rising up her. “I know what you’re doing and it won’t work. I’m sorry Mrs. Lovett, I truly am for your plight and your loss but Benjamin is my husband and you cannot go about indulging in these fantasies.”

There’s sincerity laced in there somewhere but she refuses to see it.

Her silence is met with a heavy, disappointed sigh from Lucy as she leaves without another word.

She spends her day conjuring up hurtful words, water-logging her pillow with the ache of knowing Lucy is ultimately right. She’s not the one he loves, right now at least. That shred of hope that will carry her from now on.

A month passes before she sees him again. She wonders if Lucy told him about their last meeting. Wonders if that’s why he has avoided her.

But she relishes in the sight of him. Her wounds starting to scab as he comes bounding elation. Perhaps he missed her too.

He passes off the rent to her and she’s shocked Lucy didn’t bring it down herself.

“Mrs. Lovett would you happen to have any sweets you could spare?”

“Needing a bit of sugar there Mr. Barker?”

“Oh no, not for me, Lucy’s been having a craving for something sweet.”

She’s not piecing it together and he can tell.

“Surely she’s spoken to you, about… oh well, I guess I can be the harbinger of good news. Lucy and I are to welcome a baby this summer.”

And with a pair of seamstress scissors the finale thread is cut.

She can’t even summon a proper smile, but it doesn’t affect his jubilation.

“Oh,” is what comes out. She forces herself to summon an interest, for his sake, “congratulations are in order then.”

He beams, clearly proud of himself and doting on his wife like the respectable husband he is.

“Let me…” and she’s a little scattered as she turns to find the doorway to the small kitchen behind her, “let me just check in the back, love.” The ache of the word.

As soon as she’s out of view she tips against the wall and just sobs silently. Covering her mouth when she needs to suck in a noisy breath. She can’t go back out there, she can’t let go of the future she imagined for them, him, proud as a peacock, marrying the widow Lovett, parading her around the town square arm and arm with her belly swollen with his child, be taken away. She’ll need time to grieve its loss.

So she calls out, “I don’t seem to have any, dear. Excuse me though I need to check on me pies.”

She waits beyond the threshold until she’s sure he’s gone. Walking back to the counter, exhausted and red eyed, she allows her body to dramatically to fall over the wooden counter.

Her cheek resting along the cutting board. All the tension in her body gone at once.

She hears the bell on the door and without even looking up hurls a pie violently toward whoever dared to interrupt her. Never bothering to look up and see who the lucky patron was.

Despite the finality in his news, it takes her a few days to mentally work around the obstacle of a child and her eventual future with Benjamin. She still can’t tame that small hope that he’d be hers, one day, somehow.

From then on Lucy never brings the rent down, and the only time Mrs. Lovett sees her is when she can summon up a good enough reason to visit upstairs.

“Oh a customer asked if you pomade the hair.” A lie.

“Did ya hear a creaking this morning? I heard a creaking and scratchin’. Maybe the rodents have found a new nest in the wall.” Another lie.

She gets good at lying, cobbling together a world of her own imaginings. Finds that it’s a better place to exist than reality.

Lucy grows tired of her intrusions and starts cutting her off at the door before she can set foot inside. But her stomach grows too big and she’s no longer able to keep her locked out. She tries to become a friend, a confidant to her husband but it becomes apparent after a few hearty conversations that he’s grown unfocused and drifts elsewhere when she chatters. So she eventually locks herself out. Pining from afar.

She keeps his name on the tip of her lips as she rustles her own sheets. Always keeping the image of him at the forefront of her lustful mind.

——————————

Mrs. Lovett is very aware the night Lucy goes into labor, half the neighborhood is. The grunts and screams echo off the stone buildings.

It’s a hard delivery from what she can hear and Benjamin eventually wanders down the stairs after several hours, presumably sent away by the doctor. At this hour the doors are locked so he knocks on the shop door instead. Normally she wouldn’t hear it but she’s wide awake, anticipating the cries of a child at any moment.

“I’m sorry to wake you Mrs. Lovett…” and she doesn’t even let him finish his sentence before she’s ushering him inside, her simple blue robe dragging across the wooden floor, a wisp of cloth underneath. He’s clad in a hastily tucked in shirt and trousers, looking all the worse for wear.

His eyes are red, he’s been crying, coupled with exhaustion he looks a fright. “Come now, don’t get yourself all worked up. How is she doing?” In truth she doesn’t care. She’s yet to decide her feelings on the baby. In a way, that she knows is wrong, she wishes the hardship of her labor might claim her, leaving him a widow with a child she could care for.

He shrugs as she sits him at a table. His head immediately dropping into his hands.

“I don’t know honestly. I’m not terribly familiar with the process.”

“Well coming from a woman, it all seems normal to me dear. These things take time. Come now drink have a little ale, it’ll calm your nerves.”

She sits with him quietly, occasionally checking in between his sips.

The night carries on into dawn and then mid afternoon. The screams die down at last, a tiny wail replacing them.

The baby, at last.

Benjamin is met at the door a few moments later to find the doctor already coming to collect him. A girl she can hear him announce, ushering the new father out.

Mrs. Lovett can’t help herself and follows a few paces behind into the sinking daylight, but stops at the stairs. Even she knows this isn’t her moment to sully.

She stands there for several minutes just staring at the landing before turning to head back inside. The moment she’s at the counter she hears the crazed thumps of shoes rushing around. She peeks back outside in time to see Benajmin being pushed onto the landing of the stairs a tiny white bundle of blankets awkwardly situated invites arms.

“Everything alright up there love?” And he catches her eye in a panic before she bounds up the stairs.

He meets her halfway, begging her to hold the babe as he returns upstairs shouldering the door until he can force it open. She hears him cry out as his daughter gives a rousing yell in return.

She’s heard the cries of grief before, what it likely means.

She immediately regrets her earlier thoughts and wishes she could undo them. Her blinders have dropped in light of the reality of the moment. Her mind shaming her for taking a predatory interest in their life and hopeful dissolution.

She had hoped Lucy would just go away, not die. Never die.

She coos down at the tiny girl and cuddles her close, for once overcome with emotion for Lucy’s wellbeing.

She feels out of place and no one is returning to check on the wee girl so she takes the baby downstairs. Her cries continue as she sets herself down in a corner booth of the pie shop. With her pinky finger scrubbed red and raw washed she offers it to the hungry babe to suckle on.

She’d never been taught what substitutes a breast in these situations, never had a need to, so she gives her a lackluster distraction instead.

She briefly wonders if she herself could persuade her body to dredge up some nourishment, she’d heard tale of such a thing happening from the bawdy Mrs. Craney but the old bat also believed there was a horse living in her attic. So she takes the thought and stows it away for another time.

An hour passes before she hears the bell on the door. She’s surprised to find the doctor standing there, eyes cast downward, covered in blood. For a woman so well acquainted with the messiness of death it churns her stomach a little.

He motions toward the stairs, “Perhaps seeing the child will pull him from his reverie.”

And she nods and starts for the door but the doctor gently stops her, “Cows milk will do if she can thrive, every 3 hours. God help her.”

His passive remark only steels Mrs. Lovett’s resolve. She’ll have none of that talk, shrugging the old man’s hand off her shoulder before heading to the kitchen, grabbing what’s left of the milk, a spoon, and a tea towel.

When she opens the door to the barber’s shop she can see an invisible path of pain to the Barker’s open bedroom door. Peaking in she recoils at the aggressive visual of red stains on white sheets, Benjamin on his knees holding Lucy’s greying hand.

The baby starts to cry, and he turns, eyes red and bloodshot, “Leave me! Leave me now I said!”

And it’s so hard and furious she turns and retreats back to a chair in the barber’s shop careful to stay out of his eye-line.

She sets down the milk and begins to solve the puzzle of feeding the girl. After the spoon fails to produce anything other than a mess she rigs a system with the tea towel where the milk drips down a twisted corner that the baby can suckle. Anything to get her belly full.

She can’t help feeling a maternal swell toward the sight below hers as she lets herself take in the image. So small and warm.

Motherless.

So she hugs her tighter.

The baby drifts off to sleep and she can’t put her down, too afraid her chest will stop rising and no one will notice, so she attempts to breach the threshold of the room again with her in tow.

This time he’s despondent, void of any life. It’s almost worse than the angry grief he sported earlier.

Feeling safe he’s past that, she crouches down beside him, sits on the floor and lays his daughter on her lap, across her billowing skirt.

He looks at his daughter, finally, and his hand reaches for Mrs. Lovett’s. Grabs it so tight it starts to tingle. And gives them both a pained smile. She’ll burn it into her memory.

He says nothing and after several minutes, pulls his hand from hers as they sit on that floor, all together for hours. Mrs. Lovett avoids looking at Lucy, she doesn’t have a right to capture that image for eternity, she saw enough earlier. It isn’t until the child wakes again, hungry that she starts to stand.

She tries to coax him downstairs for a meal. The thick summer air causing the windows of his bedroom to steam and it’s only a matter of time before someone comes to collect the body, but he refuses to leave her.

“She needs to eat.”

“So feed her.” he groans back.

She leaves without another word. If he wishes to disregard the life of his daughter for that of his dead wife then she’d be better equipped to spearhead her survival.

She nestles her close that night, feels maternal for once, a feeling she always thought would accompany warmth on the opposite side of her bed, but such is not the case tonight.

The daylight has gone as her eyes flutter open several minutes after shutting them to the sound of a commotion upstairs. They’ve come to get Lucy.

When the whole ordeal is over he still doesn’t come for his daughter. Not even a day old and she’s really only known the touch of a stranger.

Several days pass, she has no idea how he’s faring upstairs but she allows him his grief.

She cares for the baby, who still has no name, no mother, and by his own choice, no father.

Perhaps it’s the lack of sleep or growing resentment leads that prompts it but she’s reached her limit.

When the little girl becomes colicky and wails endlessly Mrs. Lovett can take no more. With the babe in her arms she ascends the stairs to find him seated in his barbers chair, a horrid smell assaults her upon entry, and from behind she can see a light beard grown over his jaw.

“I understand the grief you must be feelin’ Mr. Barker but your daughter needs her father. Yer the only parent she has.”

When he doesn’t acknowledge her she steps closer, louder, “Benjamin are you listening to me.”

“You’re doing a fine job.” But it’s not a compliment, it’s laced in anger.

“I’m the only one who has cared enough to make sure she lives. Don’t cha think Lucy would want you to as well.”

“You speak like you knew her. I knew her, I loved her.”

“I didn’t need to know Lucy to know a mother would want her child to live.”

He turns his chair toward her and she immediately sees the torn look on his face. Conflicted by grief and joy and the albatross known as Mrs. Lovett weaving them together.

“Thank you for caring for her.”

She’s not sure he means it but the sad smile that ghosts across her lips doesn’t care, he needs reassurance.

“Come now, ya both could use a bath and a warm meal.”

She reaches out and puts her hand on his shoulder to urge him forward and while he tenses he doesn’t recoil.

———-

She feeds them both, him with his head down in he’s from his bowl and her guzzling away on a cloth. He seems slightly curious about the system she’s rigged,

“What is this?”

“Her dinner.”

He quirks an eyebrow, “this is how you’ve fed her?”

“Have a better idea?”

“Well you know… can’t you…”

“Breastfeed her, are you serious?” And she scoff at him, “Men know nothing.”

She rolls her eyes before continuing her lesson, “I don’t think simply wishing makes it happen. You gotta have a baby to feed a baby Mr. Barker.”

“Oh.” And she can hear it. She’s taken away a little more of the light he had finally recaptured.

She knows it’s not so but she attempts to humor him.

“Who knows though, maybe there’s a way, I can quietly ask ‘round.”

He just nods. Nothing.

After baths are drawn she retires to her room with the baby.

“Come along” she tells him but he’s reluctant to follow.

“Oh now dear this is hardly the time for seduction. Come I’ll show you how to put her down.”

She lays her on the bed, it’ll do till they can move the bassinet downstairs. She’s completely given up the idea of moving the child back upstairs. Best to keep her as far removed from that room as possible.

She sits on the edge of the bed and rubs the child’s chest in soft circles. He sits on the other side and watches intently. Imagining she’s an entirely different person she’s sure.

It’s the first moment she sees him truly look at his daughter. His eyes well up with love and tenderness for a change. He loves his little girl in this moment and by association she hopes he loves her too. She always hopes he loves her, just a little bit.

“What will ya call her?”

“Johanna.” He says softly.

“Pretty little Johanna. I think it suits her.”

[azikarue]

Life in Color : Chapter 26 : Pirate

King, Queen | FFN Rating: K+ | FFN Link ❖ “It’s a shame you have a moral compass now; we could be making a killing off of these parts.”

King rolled his eyes at his sister’s rueful remark. He shot a look her way, but she wasn’t paying attention, too busy running her fingers along a tray of attack rings like they were precious jewels. King recognized them at once as her personal collection of favorites from their parts-hunting days, all carefully packed in a custom case. They were one of the last things they’d placed in the storage unit before closing it up. King hadn’t thought he’d see them again so soon.

Though, he hadn’t thought a company like BEGA would come along and lock away all beyblading parts and components behind a membership, either.

“Pack a box and come on,” he ordered, already feeling agitated from the cramped space and his own intentions hanging over his head.

Ever since their stint with Dr. K and their loss against the Bladebreakers, King and Queen had done their best to give up their old ways and battle fairly. King, especially, found himself exhausted by all the dishonesty and the tangled web of lies and half-truths they’d been fed to further Dr. K’s agenda.

In retrospect, he realized that he’d lost sight of the reason he began beyblading in the first place when he started focusing on the parts he had, instead of how far he could push himself in battle. He knew it came from the days when he and Queen used to gamble their own parts in an effort to build the beyblades of their dreams.

Back then, that was the only access they had to top of the line parts. By the time they could buy them on their own, they’d gotten too greedy and preferred to steal what they wanted. It took battling Tyson to make him realize that the parts weren’t what made them good – it was all the battles they fought as they built their collection and the opponents who forced them to level up.

With that realization, the whole BEGA takeover immediately rubbed him the wrong way.

They were putting too much weight on the pro title, handing kids membership cards and telling them that was all they needed when, in reality, it took years of hard work and discipline to reach the top. Refusing to sell parts to anyone without a BEGA ID made things even worse because it made buying parts feel like a luxury. Kids were waving their BEGA cards around and stripping entire shelves of blading gear because they could, but most of them hadn’t fully mastered their beginner blades yet.

Not only that, but it happened too fast. King had learned the hard way what happened when you blindly trusted a loser with an ego making big promises. The ‘moral compass’ Queen made fun of hated seeing a bunch of kids taken advantage of.

And if Tyson wasn’t backing BEGA…

Well, King didn’t consider it a good sign.

“Whenever you’re ready,” Queen sighed. She had a cardboard box in her arms and a bored expression on her face. King knew she thought he was blowing the BEGA thing out of proportion, but at least she agreed to help. Even if part of the reason she did was because she’d get a suped up blade out of the deal; her own case of parts was on top of the box she was carrying.

King sifted through a few more boxes until he was able to put one together that had a decent variety of parts. He closed it up, wincing at the grating sound of cardboard scraping, and hoisted it onto his shoulder. With a nod of his head, Queen followed him out of their storage unit. Her foot only tapped a little bit waiting for him to lock it up.

Back out on the streets, they turned in unison and headed towards the nearest subway station. When they’d gotten the storage unit, King purposefully chose one a handful of stops away from their apartment. He didn’t want it to be inconvenient, but it felt less tempting to pore through their stash of amassed parts if they weren’t right down the street. And, with the reputation they’d garnered for themselves, it was safer to keep most of their parts away from home.

Over the past year of walking the straight and narrow, they hadn’t made a single trip out to the unit, though they paid for it monthly. Instead, they honed their skills with the beyblades they had, replacing parts as needed with the handful they kept laying around.

Carrying the boxes through the city, now, felt illicit.

Queen didn’t seem bothered. When they took their seats on the train, she plucked a lethal-looking attack ring from her collection and twirled it around in her fingers.

“Stop frowning, King,” she said without taking her eyes off the attack ring. “We’re not doing anything illegal and BEGA isn’t combing the streets of Tokyo for unaccounted-for parts.”

King’s frown, ever-present these days, deepened as the doors hissed shut. “Technically, we’re in possession of stolen property,” he said, keeping his voice low even though the only other people in their car had headphones on. “In case you forgot how we have so many parts in the first place.”

Queen just laughed and said, “If you want to get technical about it, they’re winnings. We didn’t steal anything.”

“Tell that to all the kids who ever begged us to let them keep their beyblades,” he shot back, angry at her flippancy. To Queen this might be an amusing jaunt into their past habits, but King felt like they were taking steps backward on a slippery slope. “If all you’re looking to do is get your kicks on a power trip and make other bladers miserable again, then I can do this without you.”

Anger flashed in Queen’s eyes.

King balled his hands into fists on top of the box in his lap and leveled her with a fixed stare.

“I mean it,” he said. “If you want to face off against somebody, make it the cocky bladers who hold their precious BEGA memberships over other people’s heads. I don’t even care if you ask them to put their parts on the line once our stores run low. But these—,” he paused to rap on the top of the box and make sure he had Queen’s attention, “—are for anybody who needs parts but doesn’t have access to them.

“The sport of beyblading isn’t something some company can buy and sell as it pleases. If BEGA wants to limit parts sales to its members, I’ll sell them to everyone else myself at a fraction of the cost.”

Queen sat in stunned silence for a minute. “A fraction?” she asked and raised both of her eyebrows.

“We got them for free,” King reminded her with a halfhearted glare. If there weren’t going to be certain risks and costs involved, he wouldn’t charge at all.

His sister laughed and sat back in her seat.

“You had me at ‘put their parts on the line’,” she said, tossing the attack ring in the air and catching it in her fist. “There are plenty of gullible losers out there buying parts because they have a magic card that lets them. I’d love to take them down a peg.”

King sighed. At least she had spirit. Maybe her own moral compass would come with time. In the meanwhile, there were just as many struggling beybladers out there as there were gullible losers, and he would do whatever he could to get them the parts that they needed.

[dizzlesprite]

The Art of Internet Style: Producing Spectacular Online Experiences

""

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Read more here https://www.gibsongirlspublishing.com/

[foodspark-scraper]

Tapping into Fresh Insights: Kroger Grocery Data Scraping

In today's data-driven world, the retail grocery industry is no exception when it comes to leveraging data for strategic decision-making. Kroger, one of the largest supermarket chains in the United States, offers a wealth of valuable data related to grocery products, pricing, customer preferences, and more. Extracting and harnessing this data through Kroger grocery data scraping can provide businesses and individuals with a competitive edge and valuable insights. This article explores the significance of grocery data extraction from Kroger, its benefits, and the methodologies involved.

The Power of Kroger Grocery Data

Kroger's extensive presence in the grocery market, both online and in physical stores, positions it as a significant source of data in the industry. This data is invaluable for a variety of stakeholders:

Kroger: The company can gain insights into customer buying patterns, product popularity, inventory management, and pricing strategies. This information empowers Kroger to optimize its product offerings and enhance the shopping experience.

Grocery Brands: Food manufacturers and brands can use Kroger's data to track product performance, assess market trends, and make informed decisions about product development and marketing strategies.

Consumers: Shoppers can benefit from Kroger's data by accessing information on product availability, pricing, and customer reviews, aiding in making informed purchasing decisions.

Benefits of Grocery Data Extraction from Kroger

Market Understanding: Extracted grocery data provides a deep understanding of the grocery retail market. Businesses can identify trends, competition, and areas for growth or diversification.

Product Optimization: Kroger and other retailers can optimize their product offerings by analyzing customer preferences, demand patterns, and pricing strategies. This data helps enhance inventory management and product selection.

Pricing Strategies: Monitoring pricing data from Kroger allows businesses to adjust their pricing strategies in response to market dynamics and competitor moves.

Inventory Management: Kroger grocery data extraction aids in managing inventory effectively, reducing waste, and improving supply chain operations.

Methodologies for Grocery Data Extraction from Kroger

To extract grocery data from Kroger, individuals and businesses can follow these methodologies:

Authorization: Ensure compliance with Kroger's terms of service and legal regulations. Authorization may be required for data extraction activities, and respecting privacy and copyright laws is essential.

Data Sources: Identify the specific data sources you wish to extract. Kroger's data encompasses product listings, pricing, customer reviews, and more.

Web Scraping Tools: Utilize web scraping tools, libraries, or custom scripts to extract data from Kroger's website. Common tools include Python libraries like BeautifulSoup and Scrapy.

Data Cleansing: Cleanse and structure the scraped data to make it usable for analysis. This may involve removing HTML tags, formatting data, and handling missing or inconsistent information.

Data Storage: Determine where and how to store the scraped data. Options include databases, spreadsheets, or cloud-based storage.

Data Analysis: Leverage data analysis tools and techniques to derive actionable insights from the scraped data. Visualization tools can help present findings effectively.

Ethical and Legal Compliance: Scrutinize ethical and legal considerations, including data privacy and copyright. Engage in responsible data extraction that aligns with ethical standards and regulations.

Scraping Frequency: Exercise caution regarding the frequency of scraping activities to prevent overloading Kroger's servers or causing disruptions.

Conclusion

Kroger grocery data scraping opens the door to fresh insights for businesses, brands, and consumers in the grocery retail industry. By harnessing Kroger's data, retailers can optimize their product offerings and pricing strategies, while consumers can make more informed shopping decisions. However, it is crucial to prioritize ethical and legal considerations, including compliance with Kroger's terms of service and data privacy regulations. In the dynamic landscape of grocery retail, data is the key to unlocking opportunities and staying competitive. Grocery data extraction from Kroger promises to deliver fresh perspectives and strategic advantages in this ever-evolving industry.

[firespirited]

Long post. Press j to skip.

I AM SICK OF THE STUPID AI DEBATES, does it imagine, is it based on copyrightable material, are my patterns in there?

That's not the point.

I briefly got into website design freelancing (less than 3 months) before burn out.

The main reason was that automation had begun for generating stylesheets in somewhat tasteful palettes, for automatically making html/xml (they really haven't learned to simplify and tidy code though, they just load 50 divs instead of one), for batch colourising design elements to match and savvy designers weren't building graphics from scratch and to spec unless it was their day job.

Custom php and database design died with the free bundled CMS packages that come with your host with massive mostly empty unused values.

No-one has talked about the previous waves of people automated out of work by website design generators, code generators, the fiverr atomisation of what would have been a designers job into 1 logo and a swatch inserted into a CMS by an unpaid intern. Reviews, tutorials, explanations and articles are generated by stealing youtube video captions, scraping fan sites and putting them on a webpage. Digitally processing images got automated with scripts stolen from fan creators who shared. Screencaps went from curated processed images made by a person to machine produced once half a second and uploaded indiscriminately. Media recaps get run into google translate and back which is why they often read as a little odd when you look up the first results.

This was people's work, some of it done out of love, some done for pay. It's all automated and any paid work is immediately copied/co-opted for 20 different half baked articles on sites with more traffic now. Another area of expertise I'd cultivated was deep dive research, poring over scans of magazines and analysing papers, fact checking. I manually checked people's code for errors or simplifications, you can get generators to do that too, even for php. I used to be an english-french translator.

The generators got renamed AI and slightly better at picture making and writing but it's the same concept.

The artists that designed the web templates are obscured, paid a flat fee by the CMS developpers, the CMS coders are obscured, paid for their code often in flat fees by a company that owns all copyright over the code and all the design elements that go with. That would have been me if I hadn't had further health issues, hiding a layer in one of the graphics or a joke in the code that may or may not make it through to the final product. Or I could be a proof reader and fact checker for articles that get barely enough traffic while they run as "multi snippets" in other publications.

The problem isn't that the machines got smarter, it's that they now encroach on a new much larger area of workers. I'd like to ask why the text to speech folks got a flat fee for their work for example: it's mass usage it should be residual based. So many coders and artists and writers got screwed into flat fee gigs instead of jobs that pay a minimum and more if it gets mass use.

The people willing to pay an artist for a rendition of their pet in the artist's style are the same willing to pay for me to rewrite a machine translation to have the same nuances as the original text. The same people who want free are going to push forward so they keep free if a little less special cats and translations. They're the same people who make clocks that last 5 years instead of the ones my great uncle made that outlived him. The same computer chips my aunt assembled in the UK for a basic wage are made with a lot more damaged tossed chips in a factory far away that you live in with suicide nets on the stairs.

There is so much more to 'AI' than the narrow snake oil you are being sold: it is the classic and ancient automation of work by replacing a human with a limited machine. Robot from serf (forced work for a small living)

It's a large scale generator just like ye olde glitter text generators except that threw a few pennies at the coders who made the generator and glitter text only matters when a human with a spark of imagination knows when to deploy it to funny effect. The issue is that artists and writers are being forced to gig already. We have already toppled into precariousness. We are already half way down the slippery slope if you can get paid a flat fee of $300 for something that could make 300k for the company. The generators are the big threat keeping folks afraid and looking at the *wrong* thing.

We need art and companies can afford to pay you for art. Gig work for artists isn't a safe stable living. The fact that they want to make machines to take that pittance isn't the point. There is money, lots of money. It's not being sent to the people who make art. It's not supporting artists to mess around and create something new. It's not a fight between you and a machine, it's a fight to have artists and artisans valued as deserving a living wage not surviving between gigs.

[rhube]

It's the same as the advertising data scam, where a million companies have been founded scraping the web for your 'interests' and 'demographics', which is fed to advertising companies who won't actually invest in good advertising that's fun and engaging (those 80s Clark's shoes ads, anyone? if you were a small AFAB, 40 years on, you know) and they just fire flashing auto-play ads at you every 3 minutes, not selling you anything, but making apps and websites unusable.

I'm sure I'm preaching to the choir here, but most of the tech industry is in a toxic, codependent relationship with VCs who demand an impossible return on investment. The VCs don't expect to own any company more than 4 years, so everything has to be 'fast, fast, fast!' to create the illusion of a profit every quarter.

No one has the time for research. No one cares if anything actually works. Or if they do, they work themselves into burnout and get fired for quit or made redundant in the latest round of 'cutting salaries makes selectively presented graphs go up!'

AI is perfect for this. It's everything NTFs and Blockchain was, but sanitised for the mainstream and putting out the intoxicating aroma of, 'You can replace your workers with this, and all it costs is the planet and the arts!' And VCs never cared about the planet or the arts.

Tech companies require huge investment, so they are all hoping to attract that sweet, sweet, VC money, so the industry is locked in a pattern of 'move fast and break things' with zero time for reflection on whether they've actually done anything that made people's lives better. But because the industry is generally paid three, four, five times the average salary, it's very hard to convince a lot of well-rewarded tech bros that the do not in fact shit gold and puke rainbows.

I say this knowing full well I am reblogging from a techy who isn't like that, but many are, and even where the devs, the tech writers, the UI designers, the researchers, QA etc all work under a harmonious Agile ethos of trying to do the best job they can, respecting one another and the customers, upper management and executives generally just Don't. And those people ultimately dictate what everyone else does.

Having got myself all worked up, I remembered a thing.

Brain fog vagueness, but I heard on Radio 4 for that they (UK people, possibly the government, I can't remember) are planning to or hoping to make investment more transparent to small investors. If you have a pension, you are almost certainly a stock holder. But unlike Goldman Sachs, you don't get an invite to quarterly meetings where companies report on how well they are doing. Big capitalist companies don't generally care if there have been a lot of layoffs behind the numbers going up, but you do. Big capitalist companies don't care if staff are still getting good benefits, but you do. Big capitalist companies don't give a shit about DEI, but you do.

And it's your money. Your investment. And you have a right to ask the questions that make it clear you value people and useful products over money. You have a right to be in those meetings. You have to right to know they're happening.

That's the idea anyway. Apparently, companies are resisting it as 'impossible', but this guy who knows more about stuff than me seemed to think it was perfectly possible to send an email to every person who is an investor. The main reason they don't want you there is they want to move fast and break things and make cash cash money, and you actually care about what gets broken.

I'll shut up now.

part of what pisses me off so much about AI is how confident all pro-AI people are that it can do basically anything when there's literally no evidence that it can do anything even remotely well. it really feels like the only thing keeping this industry going is the refusal of anyone with any amount of money and power to hit these losers with a [citation needed]

[mariacallous]

The open internet once seemed inevitable. Now, as global economic woes mount and interest rates climb, the dream of the 2000s feels like it’s on its last legs. After abruptly blocking access to unregistered users at the end of last month, Elon Musk announced unprecedented caps on the number of tweets—600 for those of us who aren’t paying $8 a month—that users can read per day on Twitter. The move follows the platform’s controversial choice to restrict third-party clients back in January.

This wasn’t a standalone event. Reddit announced in April that it would begin charging third-party developers for API calls this month. The Reddit client Apollo would have to pay more than $20 million a year under new pricing, so it closed down, triggering thousands of subreddits to go dark in protest against Reddit’s new policy. The company went ahead with its plan anyway.

Leaders at both companies have blamed this new restrictiveness on AI companies unfairly benefitting from open access to data. Musk has said that Twitter needs rate limits because AI companies are scraping its data to train large language models. Reddit CEO Steve Huffman has cited similar reasons for the company’s decision to lock down its API ahead of a potential IPO this year.

These statements mark a major shift in the rhetoric and business calculus of Silicon Valley. AI serves as a convenient boogeyman, but it is a distraction from a more fundamental pivot in thinking. Whereas open data and protocols were once seen as the critical cornerstone of successful internet business, technology leaders now see these features as a threat to the continued profitability of their platforms.

It wasn’t always this way. The heady days of Web 2.0 were characterized by a celebration of the web as a channel through which data was abundant and widely available. Making data open through an API or some other means was considered a key way to increase a company’s value. Doing so could also help platforms flourish as developers integrated the data into their own apps, users enriched datasets with their own contributions, and fans shared products widely across the web. The rapid success of sites like Google Maps—which made expensive geospatial data widely available to the public for the first time—heralded an era where companies could profit through free, mass dissemination of information.

“Information Wants To Be Free” became a rallying cry. Publisher Tim O’Reilly would champion the idea that business success in Web 2.0 depended on companies “disagreeing with the consensus” and making data widely accessible rather than keeping it private. Kevin Kelly marveled in WIRED in 2005 that “when a company opens its databases to users … [t]he corporation’s data becomes part of the commons and an invitation to participate. People who take advantage of these capabilities are no longer customers; they’re the company’s developers, vendors, skunk works, and fan base.” Investors also perceived the opportunity to generate vast wealth. Google was “most certainly the standard bearer for Web 2.0,” and its wildly profitable model of monetizing free, open data was deeply influential to a whole generation of entrepreneurs and venture capitalists.

Of course, the ideology of Web 2.0 would not have evolved the way it did were it not for the highly unusual macroeconomic conditions of the 2000s and early 2010s. Thanks to historically low interest rates, spending money on speculative ventures was uniquely possible. Financial institutions had the flexibility on their balance sheets to embrace the idea that the internet reversed the normal laws of commercial gravity: It was possible for a company to give away its most valuable data and still get rich quick. In short, a zero interest-rate policy, or ZIRP, subsidized investor risk-taking on the promise that open data would become the fundamental paradigm of many Google-scale companies, not just a handful.

Web 2.0 ideologies normalized much of what we think of as foundational to the web today. User tagging and sharing features, freely syndicated and embeddable links to content, and an ecosystem of third-party apps all have their roots in the commitments made to build an open web. Indeed, one of the reasons that the recent maneuvers of Musk and Huffman seem so shocking is that we have come to expect data will be widely and freely available, and that platforms will be willing to support people that build on it.

But the marriage between the commercial interests of technology companies and the participatory web has always been one of convenience. The global campaign by central banks to curtail inflation through aggressive interest rate hikes changes the fundamental economics of technology. Rather than facing a landscape of investors willing to buy into a hazy dream of the open web, leaders like Musk and Huffman now confront a world where clear returns need to be seen today if not yesterday.

This presages major changes ahead for the design of the internet and the rights of users. Twitter and Reddit are pioneering an approach to platform management (or mismanagement) that will likely spread elsewhere across the web. It will become increasingly difficult to access content without logging in, verifying an identity, or paying a toll. User data will become less exportable and less shareable, and there will be increasingly fewer expectations that it will be preserved. Third-parties that have relied on the free flow of data online—from app-makers to journalists—will find APIs ever more expensive to access and scraping harder than ever before.

We should not let the open web die a quiet death. No doubt much of the foundational rhetoric of Web 2.0 is cringeworthy in the harsh light of 2023. But it is important to remember that the core project of building a participatory web where data can be shared, improved, critiqued, remixed, and widely disseminated by anyone is still genuinely worthwhile.

The way the global economic landscape is shifting right now creates short-sighted incentives toward closure. In response, the open web ought to be enshrined as a matter of law. New regulations that secure rights around the portability of user data, protect the continued accessibility of crucial APIs to third parties, and clarify the long-ambiguous rules surrounding scraping would all help ensure that the promise of a free, dynamic, competitive internet can be preserved in the coming decade.

For too long, advocates for the open web have implicitly relied on naive beliefs that the network is inherently open, or that web companies would serve as unshakable defenders of their stated values. The opening innings of the post-ZIRP world show how broader economic conditions have actually played the larger role in architecting how the internet looks and feels to this point. Believers in a participatory internet need to reach for stronger tools to mitigate the effects of these deep economic shifts, ensuring that openness can continue to be embedded into the spaces that we inhabit online.

WIRED Opinion publishes articles by outside contributors representing a wide range of viewpoints. Read more opinions here. Submit an op-ed at ideas@wired.com.

[mostlysignssomeportents]

This day in history

On SEPTEMBER 24th, I'll be speaking IN PERSON at the BOSTON PUBLIC LIBRARY!

#20yrsago AnarchistU, Toronto’s wiki-based free school https://web.archive.org/web/20040911010603/http://anarchistu.org/bin/view/Anarchistu

#20yrsago Fair use is a right AND a defense https://memex.craphound.com/2004/09/09/fair-use-is-a-right-and-a-defense/

#20yrsago Bounty for asking “How many times have you been arrested, Mr. President?” https://web.archive.org/web/20040918115027/https://onesimplequestion.blogspot.com/

#20yrsago What yesterday’s terrible music https://www.loweringthebar.net/2009/09/open-mike-likely-to-close-out-legislators-career.htmlsampling ruling means https://web.archive.org/web/20040910095029/http://www.lessig.org/blog/archives/002153.shtml

#15yrsago Conservative California legislator gives pornographic account of his multiple affairs (including a lobbyist) into open mic https://www.loweringthebar.net/2009/09/open-mike-likely-to-close-out-legislators-career.html

#15yrsago Shel Silverstein’s UNCLE SHELBY, not exactly a kids’ book https://memex.craphound.com/2009/09/09/shel-silversteins-uncle-shelby-not-exactly-a-kids-book/

#10yrsago Seemingly intoxicated Rob Ford gives subway press-conference https://www.youtube.com/watch?v=WbcETJRoNCs

#10yrsago Amazon vs Hachette is nothing: just WAIT for the audiobook wars! https://locusmag.com/2014/09/cory-doctorow-audible-comixology-amazon-and-doctorows-first-law/

#10yrsago Dietary supplement company sues website for providing a forum for dissatisfied customers https://www.techdirt.com/2014/09/08/dietary-supplement-company-tries-suing-pissedconsumer-citing-buyers-agreement-to-never-say-anything-negative-about-roca/

#10yrsago New wind-tunnel tests find surprising gains in cycling efficiency from leg-shaving https://www.theglobeandmail.com/life/health-and-fitness/health/the-curious-case-of-the-cyclists-unshaved-legs/article20370814/

#10yrsago Behind the scenes look at Canada’s Harper government gagging scientists https://www.cbc.ca/news/science/federal-scientist-media-request-generates-email-frenzy-but-no-interview-1.2759300

#10yrsago Starred review in Kirkus for INFORMATION DOESN’T WANT TO BE FREE https://www.kirkusreviews.com/book-reviews/cory-doctorow/information-doesnt-want-to-be-free/

#10yrsago Steven Gould’s “Exo,” a Jumper novel by way of Heinlein’s “Have Spacesuit, Will Travel” https://memex.craphound.com/2014/09/09/steven-goulds-exo-a-jumper-novel-by-way-of-heinleins-have-spacesuit-will-travel/

#5yrsago Important legal victory in web-scraping case https://arstechnica.com/tech-policy/2019/09/web-scraping-doesnt-violate-anti-hacking-law-appeals-court-rules/

#5yrsago Whistleblowers out Falwell’s Liberty University as a grifty, multibillion-dollar personality cult https://web.archive.org/web/20190910000528/https://www.politico.com/magazine/amp/story/2019/09/09/jerry-falwell-liberty-university-loans-227914

#5yrsago Pinduoduo: China’s “Groupon on steroids” https://www.wired.com/story/china-ecommerce-giant-never-heard/

#5yrsago Notpetya: the incredible story of an escaped US cyberweapon, Russian state hackers, and Ukraine’s cyberwar https://www.wired.com/story/notpetya-cyberattack-ukraine-russia-code-crashed-the-world/

#5yrsago NYT calls for an end to legacy college admissions https://www.nytimes.com/2019/09/07/opinion/sunday/end-legacy-college-admissions.html

#5yrsago Purdue’s court filings understate its role in the opioid epidemic by 80% https://www.propublica.org/article/data-touted-by-oxycontin-maker-to-fight-lawsuits-doesnt-tell-the-whole-story

#1yrago Saturday linkdump, part the sixth https://pluralistic.net/2023/09/09/nein-nein/#everything-is-miscellaneous

The paperback edition of The Lost Cause, my nationally bestselling, hopeful solarpunk novel is out this month!

[wedesignyouny]

Top 10 AI SDR Platforms in California to Supercharge Your Sales Pipeline

In today’s rapidly evolving sales landscape, integrating artificial intelligence into your sales development process is no longer optional—it’s essential. Sales Development Representatives (SDRs) are the backbone of B2B pipeline generation, and AI-driven SDR platforms are revolutionizing how companies in California generate leads, qualify prospects, and close deals.

Here’s a deep dive into the top 10 AI SDR platforms in California that are helping businesses streamline sales outreach, boost efficiency, and significantly increase conversion rates.

Landbase – AI-Powered Lead Discovery and Outreach

Headquartered in California, Landbase is leading the AI SDR revolution with its data-enriched platform tailored for outbound prospecting. It intelligently combines real-time data with machine learning to identify high-value leads, craft personalized messages, and engage prospects at the right moment.

Key Features:

Dynamic lead scoring

AI-personalized email sequences

CRM integrations

Smart outreach timing

Perfect for B2B sales teams looking to optimize every touchpoint, Landbase turns raw data into real opportunities.

Apollo.io – Intelligent Prospecting and Sales Automation

Based in San Francisco, Apollo.io is one of the most trusted platforms for AI sales engagement. It offers a comprehensive B2B database, AI-assisted messaging, and real-time sales analytics. Its automation features help SDRs reduce manual work and spend more time closing.

Top Tools:

Smart email templates

Data enrichment

Predictive lead scoring

Workflow automation

Apollo.io is a go-to choice for tech startups and enterprises alike.

Outreach – AI Sales Engagement That Converts

Outreach.io, a Seattle-headquartered company with a strong presence in California, provides one of the most powerful AI SDR platforms. It transforms how sales teams operate by offering AI-driven recommendations, sentiment analysis, and performance insights.

What Sets It Apart:

AI-guided selling

Multichannel engagement (email, calls, LinkedIn)

Machine learning-powered insights

Cadence optimization

Outreach is ideal for scaling sales organizations needing data-driven performance tracking.

Cognism – AI Lead Generation with Global Reach

Though originally based in the UK, Cognism has made a strong mark in the California tech ecosystem. Its AI SDR tool helps teams identify ICP (ideal customer profile) leads, comply with global data regulations, and execute personalized outreach.

Highlighted Features:

AI-enhanced contact data

Intent-based targeting

GDPR and CCPA compliance

Integrated sales intelligence

Cognism is perfect for international sales development teams based in California.

Clay – No-Code Platform for AI Sales Automation

Clay enables SDRs to build custom workflows using a no-code approach. The platform empowers sales teams to automate prospecting, research, and outreach with AI scraping and enrichment tools.

Noteworthy Tools:

LinkedIn automation

Web scraping + lead enrichment

AI content generation

Zapier and API integrations

California-based startups that value flexibility and custom workflows gravitate toward Clay.

Lavender – AI-Powered Sales Email Assistant

Lavender isn’t a full-stack SDR platform but is one of the most innovative tools on the market. It acts as an AI email coach, helping SDRs write better-performing sales emails in real time.

Key Features:

Real-time writing feedback

Personalization suggestions

Email scoring and A/B testing

AI grammar and tone check

Sales reps using Lavender have reported higher open and reply rates—a game-changer for outreach campaigns.

Regie.ai – AI Content Generation for Sales Campaigns

California-based Regie.ai blends copywriting and sales strategy into one AI platform. It allows SDRs to create personalized multichannel sequences, from cold emails to LinkedIn messages, aligned with the buyer’s journey.

Top Capabilities:

AI sales sequence builder

Persona-based content creation

A/B testing

CRM and outreach tool integrations

Regie.ai helps your SDR team speak directly to prospects’ pain points with crafted messaging.

Exceed.ai – AI Chatbot and Email Assistant for SDRs

Exceed.ai uses conversational AI to engage leads via email and chat, qualify them, and book meetings—all without human intervention. It’s a great tool for teams with high inbound traffic or looking to scale outbound efficiency.

Standout Features:

Conversational AI chatbot

Lead nurturing via email

Calendar integration

Salesforce/HubSpot compatibility

California companies use Exceed.ai to support their SDRs with 24/7 lead engagement.

Drift – AI Conversational Marketing and Sales Platform

Drift combines sales enablement and marketing automation through conversational AI. Ideal for SDRs focused on inbound sales, Drift captures site visitors and guides them through intelligent chat funnels to qualify and schedule calls.

Core Tools:

AI chatbots with lead routing

Website visitor tracking

Personalized playbooks

Real-time conversation data

Drift’s AI makes the customer journey frictionless, especially for SaaS companies in Silicon Valley.

Seamless.AI – Real-Time Lead Intelligence Platform

Seamless.AI uses real-time data scraping and AI enrichment to build verified B2B contact lists. With its Chrome extension and integration capabilities, SDRs can access lead insights while browsing LinkedIn or corporate sites.

Essential Features:

Verified contact emails and numbers

Real-time search filters

AI-powered enrichment

CRM syncing

Its ease of use and data accuracy make it a must-have for SDRs targeting California’s competitive tech market.

How to Choose the Right AI SDR Platform for Your Business

With numerous AI SDR tools available, selecting the right one depends on your business size, target market, tech stack, and sales strategy. Here are some quick tips:

Define your goals: Are you looking to scale outbound outreach, improve response rates, or automate email campaigns?

Assess integrations: Ensure the platform integrates seamlessly with your existing CRM and sales tools.

Consider customization: Choose a platform that allows flexibility for custom workflows and sequences.

Look at analytics: Prioritize platforms that offer robust data and insights to refine your strategy.

Final Thoughts

Adopting an AI SDR platform isn’t just a competitive advantage—it’s a necessity in California’s high-stakes, fast-moving sales environment. Whether you’re a startup in Palo Alto or an enterprise in Los Angeles, leveraging these AI tools can dramatically enhance your pipeline growth and sales performance.

Take the next step in modernizing your sales process by choosing the AI SDR platform that best aligns with your business needs. Let technology do the heavy lifting so your team can focus on what they do best—closing deals.

[tau-i]

Let's talk about linux viruses, because they absolutely do exist. In fact, they are pretty popular: Since web servers are almost universally linux, linux machines are a incredibly lucrative target already, and indeed ARE targeted by many viruses. Why does nobody seem to notice? Well, that's simple. Getting a virus built for, say a RHEL server with a LAMP stack to run on, say Ubuntu is very difficult, to the point that one developer rather infamously set out to try to MAKE a server virus run on his personal machine, and actually ended up giving up, and manually scraping the bitcoin wallet so he could send the virus folks a few dollars out of pity. The distributions break up the potential target space, and the modular nature of the operating system breaks up the attack surface: if you write a worm that leverages a SystemD vulnrability to hide itself, it will fall flat on its face when it encounters a OpenRC based machine. Yes, popularity would degrade this reality: android has a healthy malware ecosystem, for example, but not destroy it. There are plenty of cases where software runs on one phone, but not another, and plenty of data breaches that compromise, say Samsung, but leave HTC untouched.

If anything, when money gets involved, the space would become even more fractious. Everyone wants free money. In a OS with closed terms, that looks like protecting your intellectual property zealously to maintain your advantage. However, from day ONE, Linus Torvalds made that explicitly illegal with regards to his kernel. So a different dynamic dominates in the linux space: If there's a buck to be made, half a dozen folks pile in as quick as they can. For examples of this see Squid Game Linux, AmongOS, Hanah Montana Linux, Ubuntu Christian Edition, Sabily (Muslim prayer utilities preinstalled), and Ubuntu Satanic Edition.... If anything, a world where Linux was widespread would see desktops just as fracticious as Android was today: every laptop manufacturer would have their own version of Linux which they customize to their own ends. Some of those would have deals with, say, Crowdstrike to do their security push updates. Others would have deals with different companies, for any number of reasons. So when Crowdstrike or one of their peers had a whoopsie, sure some computers wouldn't boot, but most would never notice.

Yes, some of Linux' advantages are down to the userbase, but there ARE some that are inherent, either to the software design, or the ideology that the open source movement forces upon parts of that operating system, that would still hold true if it becomes as popular as Windows.

hey i was gonna make a post of my own but i realized i dont know enough about linux to like. really talk about it beyond "well a lotta places like hospitals/military places run legacy software and theyre super dependent on it and it would be a ton of work to switch over" and "well if everyone started using linux then the hackers would probably also Start Using Linux, like how nobody used to target macs when they were uncommon" so as a smart person who knows things about computers do u have a general response to the ppl pointing to the crowdstrike thing and going "see??? this is why everyone should switch to linux"

like. i also plan on switching to linux but that just feels like switching all of our eggs to a different basket u kno

I find that Linux advocates tend to inappropriately conflate "this specific problem would not have affected Linux operating systems" with "problems of this type would not affect Linux operating systems", when the former typically doesn't imply the latter.

Would the specific mechanism by which the Crowdstrike vendor accidentally bricked millions of Windows computers have affected Linux platforms? No.

Could an inadequately vetted security update have bricked a Linux platform? Absolutely.

The fact that you don't see much of the latter has less to do with Linux in itself, and more to do with the fact that, as a specialist operating system, Linux users as a group tend to have an above-average level of compliance with security best practices. The level of compliance that's reasonable to expect for a mass-market operating system changes things considerably – if everybody and their dog was running Linux, you can bet your ass there'd be millions of Linux platforms set up to just automatically accept and apply whatever updates come down the pipeline without human oversight or a validated recovery path, too.

[crawlxpert01]

Scraping Grocery Apps for Nutritional and Ingredient Data

Introduction

With health trends becoming more rampant, consumers are focusing heavily on nutrition and accurate ingredient and nutritional information. Grocery applications provide an elaborate study of food products, but manual collection and comparison of this data can take up an inordinate amount of time. Therefore, scraping grocery applications for nutritional and ingredient data would provide an automated and fast means for obtaining that information from any of the stakeholders be it customers, businesses, or researchers.

This blog shall discuss the importance of scraping nutritional data from grocery applications, its technical workings, major challenges, and best practices to extract reliable information. Be it for tracking diets, regulatory purposes, or customized shopping, nutritional data scraping is extremely valuable.

Why Scrape Nutritional and Ingredient Data from Grocery Apps?

1. Health and Dietary Awareness

Consumers rely on nutritional and ingredient data scraping to monitor calorie intake, macronutrients, and allergen warnings.

2. Product Comparison and Selection

Web scraping nutritional and ingredient data helps to compare similar products and make informed decisions according to dietary needs.

3. Regulatory & Compliance Requirements

Companies require nutritional and ingredient data extraction to be compliant with food labeling regulations and ensure a fair marketing approach.

4. E-commerce & Grocery Retail Optimization

Web scraping nutritional and ingredient data is used by retailers for better filtering, recommendations, and comparative analysis of similar products.

5. Scientific Research and Analytics

Nutritionists and health professionals invoke the scraping of nutritional data for research in diet planning, practical food safety, and trends in consumer behavior.

How Web Scraping Works for Nutritional and Ingredient Data

1. Identifying Target Grocery Apps

Popular grocery apps with extensive product details include:

Instacart

Amazon Fresh

Walmart Grocery

Kroger

Target Grocery

Whole Foods Market

2. Extracting Product and Nutritional Information

Scraping grocery apps involves making HTTP requests to retrieve HTML data containing nutritional facts and ingredient lists.

3. Parsing and Structuring Data

Using Python tools like BeautifulSoup, Scrapy, or Selenium, structured data is extracted and categorized.

4. Storing and Analyzing Data

The cleaned data is stored in JSON, CSV, or databases for easy access and analysis.

5. Displaying Information for End Users

Extracted nutritional and ingredient data can be displayed in dashboards, diet tracking apps, or regulatory compliance tools.

Essential Data Fields for Nutritional Data Scraping

1. Product Details

Product Name

Brand

Category (e.g., dairy, beverages, snacks)

Packaging Information

2. Nutritional Information

Calories

Macronutrients (Carbs, Proteins, Fats)

Sugar and Sodium Content

Fiber and Vitamins

3. Ingredient Data

Full Ingredient List

Organic/Non-Organic Label

Preservatives and Additives

Allergen Warnings

4. Additional Attributes

Expiry Date

Certifications (Non-GMO, Gluten-Free, Vegan)

Serving Size and Portions

Cooking Instructions

Challenges in Scraping Nutritional and Ingredient Data

1. Anti-Scraping Measures

Many grocery apps implement CAPTCHAs, IP bans, and bot detection mechanisms to prevent automated data extraction.

2. Dynamic Webpage Content

JavaScript-based content loading complicates extraction without using tools like Selenium or Puppeteer.

3. Data Inconsistency and Formatting Issues

Different brands and retailers display nutritional information in varied formats, requiring extensive data normalization.

4. Legal and Ethical Considerations

Ensuring compliance with data privacy regulations and robots.txt policies is essential to avoid legal risks.

Best Practices for Scraping Grocery Apps for Nutritional Data

1. Use Rotating Proxies and Headers

Changing IP addresses and user-agent strings prevents detection and blocking.

2. Implement Headless Browsing for Dynamic Content

Selenium or Puppeteer ensures seamless interaction with JavaScript-rendered nutritional data.

3. Schedule Automated Scraping Jobs

Frequent scraping ensures updated and accurate nutritional information for comparisons.

4. Clean and Standardize Data

Using data cleaning and NLP techniques helps resolve inconsistencies in ingredient naming and formatting.

5. Comply with Ethical Web Scraping Standards

Respecting robots.txt directives and seeking permission where necessary ensures responsible data extraction.

Building a Nutritional Data Extractor Using Web Scraping APIs

1. Choosing the Right Tech Stack

Programming Language: Python or JavaScript

Scraping Libraries: Scrapy, BeautifulSoup, Selenium

Storage Solutions: PostgreSQL, MongoDB, Google Sheets

APIs for Automation: CrawlXpert, Apify, Scrapy Cloud

2. Developing the Web Scraper

A Python-based scraper using Scrapy or Selenium can fetch and structure nutritional and ingredient data effectively.

3. Creating a Dashboard for Data Visualization

A user-friendly web interface built with React.js or Flask can display comparative nutritional data.

4. Implementing API-Based Data Retrieval

Using APIs ensures real-time access to structured and up-to-date ingredient and nutritional data.

Future of Nutritional Data Scraping with AI and Automation

1. AI-Enhanced Data Normalization

Machine learning models can standardize nutritional data for accurate comparisons and predictions.

2. Blockchain for Data Transparency

Decentralized food data storage could improve trust and traceability in ingredient sourcing.

3. Integration with Wearable Health Devices

Future innovations may allow direct nutritional tracking from grocery apps to smart health monitors.

4. Customized Nutrition Recommendations

With the help of AI, grocery applications will be able to establish personalized meal planning based on the nutritional and ingredient data culled from the net.

Conclusion

Automated web scraping of grocery applications for nutritional and ingredient data provides consumers, businesses, and researchers with accurate dietary information. Not just a tool for price-checking, web scraping touches all aspects of modern-day nutritional analytics.

If you are looking for an advanced nutritional data scraping solution, CrawlXpert is your trusted partner. We provide web scraping services that scrape, process, and analyze grocery nutritional data. Work with CrawlXpert today and let web scraping drive your nutritional and ingredient data for better decisions and business insights!

Know More : https://www.crawlxpert.com/blog/scraping-grocery-apps-for-nutritional-and-ingredient-data