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mostlysignssomeportents · 2 months

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Subprime gadgets

I'm on tour with my new, nationally bestselling novel The Bezzle! Catch me THIS SUNDAY in ANAHEIM at WONDERCON: YA Fantasy, Room 207, 10 a.m.; Signing, 11 a.m.; Teaching Writing, 2 p.m., Room 213CD.

The promise of feudal security: "Surrender control over your digital life so that we, the wise, giant corporation, can ensure that you aren't tricked into catastrophic blunders that expose you to harm":

https://locusmag.com/2021/01/cory-doctorow-neofeudalism-and-the-digital-manor/

The tech giant is a feudal warlord whose platform is a fortress; move into the fortress and the warlord will defend you against the bandits roaming the lawless land beyond its walls.

That's the promise, here's the failure: What happens when the warlord decides to attack you? If a tech giant decides to do something that harms you, the fortress becomes a prison and the thick walls keep you in.

Apple does this all the time: "click this box and we will use our control over our platform to stop Facebook from spying on you" (Ios as fortress). "No matter what box you click, we will spy on you and because we control which apps you can install, we can stop you from blocking our spying" (Ios as prison):

https://pluralistic.net/2022/11/14/luxury-surveillance/#liar-liar

But it's not just Apple – any corporation that arrogates to itself the right to override your own choices about your technology will eventually yield to temptation, using that veto to help itself at your expense:

https://pluralistic.net/2023/07/28/microincentives-and-enshittification/

Once the corporation puts the gun on the mantelpiece in Act One, they're begging their KPI-obsessed managers to take it down and shoot you in the head with it in anticipation of of their annual Act Three performance review:

https://pluralistic.net/2023/12/08/playstationed/#tyler-james-hill

One particularly pernicious form of control is "trusted computing" and its handmaiden, "remote attestation." Broadly, this is when a device is designed to gather information about how it is configured and to send verifiable testaments about that configuration to third parties, even if you want to lie to those people:

https://www.eff.org/deeplinks/2023/08/your-computer-should-say-what-you-tell-it-say-1

New HP printers are designed to continuously monitor how you use them – and data-mine the documents you print for marketing data. You have to hand over a credit-card in order to use them, and HP reserves the right to fine you if your printer is unreachable, which would frustrate their ability to spy on you and charge you rent:

https://arstechnica.com/gadgets/2024/02/hp-wants-you-to-pay-up-to-36-month-to-rent-a-printer-that-it-monitors/

Under normal circumstances, this technological attack would prompt a defense, like an aftermarket mod that prevents your printer's computer from monitoring you. This is "adversarial interoperability," a once-common technological move:

https://www.eff.org/deeplinks/2019/10/adversarial-interoperability

An adversarial interoperator seeking to protect HP printer users from HP could gin up fake telemetry to send to HP, so they wouldn't be able to tell that you'd seized the means of computation, triggering fines charged to your credit card.

Enter remote attestation: if HP can create a sealed "trusted platform module" or a (less reliable) "secure enclave" that gathers and cryptographically signs information about which software your printer is running, HP can detect when you have modified it. They can force your printer to rat you out – to spill your secrets to your enemy.

Remote attestation is already a reliable feature of mobile platforms, allowing agencies and corporations whose services you use to make sure that you're perfectly defenseless – not blocking ads or tracking, or doing anything else that shifts power from them to you – before they agree to communicate with your device.

What's more, these "trusted computing" systems aren't just technological impediments to your digital wellbeing – they also carry the force of law. Under Section 1201 of the Digital Millennium Copyright Act, these snitch-chips are "an effective means of access control" which means that anyone who helps you bypass them faces a $500,000 fine and a five-year prison sentence for a first offense.

Feudal security builds fortresses out of trusted computing and remote attestation and promises to use them to defend you from marauders. Remote attestation lets them determine whether your device has been compromised by someone seeking to harm you – it gives them a reliable testament about your device's configuration even if your device has been poisoned by bandits:

https://pluralistic.net/2020/12/05/trusting-trust/#thompsons-devil

The fact that you can't override your computer's remote attestations means that you can't be tricked into doing so. That's a part of your computer that belongs to the manufacturer, not you, and it only takes orders from its owner. So long as the benevolent dictator remains benevolent, this is a protective against your own lapses, follies and missteps. But if the corporate warlord turns bandit, this makes you powerless to stop them from devouring you whole.

With that out of the way, let's talk about debt.

Debt is a normal feature of any economy, but today's debt plays a different role from the normal debt that characterized life before wages stagnated and inequality skyrocketed. 40 years ago, neoliberalism – with its assaults on unions and regulations – kicked off a multigenerational process of taking wealth away from working people to make the rich richer.

Have you ever watched a genius pickpocket like Apollo Robbins work? When Robins lifts your wristwatch, he curls his fingers around your wrist, expertly adding pressure to simulate the effect of a watchband, even as he takes away your watch. Then, he gradually releases his grip, so slowly that you don't even notice:

https://www.reddit.com/r/nextfuckinglevel/comments/ppqjya/apollo_robbins_a_master_pickpocket_effortlessly/

For the wealthy to successfully impoverish the rest of us, they had to provide something that made us feel like we were still doing OK, even as they stole our wages, our savings, and our futures. So, even as they shipped our jobs overseas in search of weak environmental laws and weaker labor protection, they shared some of the savings with us, letting us buy more with less. But if your wages keep stagnating, it doesn't matter how cheap a big-screen TV gets, because you're tapped out.

So in tandem with cheap goods from overseas sweatshops, we got easy credit: access to debt. As wages fell, debt rose up to fill the gap. For a while, it's felt OK. Your wages might be falling off, the cost of health care and university might be skyrocketing, but everything was getting cheaper, it was so easy to borrow, and your principal asset – your family home – was going up in value, too.

This period was a "bezzle," John Kenneth Galbraith's name for "The magic interval when a confidence trickster knows he has the money he has appropriated but the victim does not yet understand that he has lost it." It's the moment after Apollo Robbins has your watch but before you notice it's gone. In that moment, both you and Robbins feel like you have a watch – the world's supply of watch-derived happiness actually goes up for a moment.

There's a natural limit to debt-fueled consumption: as Michael Hudson says, "debts that can't be paid, won't be paid." Once the debtor owes more than they can pay back – or even service – creditors become less willing to advance credit to them. Worse, they start to demand the right to liquidate the debtor's assets. That can trigger some pretty intense political instability, especially when the only substantial asset most debtors own is the roof over their heads:

https://pluralistic.net/2022/11/06/the-end-of-the-road-to-serfdom/

"Debts that can't be paid, won't be paid," but that doesn't stop creditors from trying to get blood from our stones. As more of us became bankrupt, the bankruptcy system was gutted, turned into a punitive measure designed to terrorize people into continuing to pay down their debts long past the point where they can reasonably do so:

https://pluralistic.net/2022/10/09/bankruptcy-protects-fake-people-brutalizes-real-ones/

Enter "subprime" – loans advanced to people who stand no meaningful chance of every paying them back. We all remember the subprime housing bubble, in which complex and deceptive mortgages were extended to borrowers on the promise that they could either flip or remortgage their house before the subprime mortgages detonated when their "teaser rates" expired and the price of staying in your home doubled or tripled.

Subprime housing loans were extended on the belief that people would meekly render themselves homeless once the music stopped, forfeiting all the money they'd plowed into their homes because the contract said they had to. For a brief minute there, it looked like there would be a rebellion against mass foreclosure, but then Obama and Timothy Geithner decreed that millions of Americans would have to lose their homes to "foam the runways" for the banks:

https://wallstreetonparade.com/2012/08/how-treasury-secretary-geithner-foamed-the-runways-with-childrens-shattered-lives/

That's one way to run a subprime shop: offer predatory loans to people who can't afford them and then confiscate their assets when they – inevitably – fail to pay their debts off.

But there's another form of subprime, familiar to loan sharks through the ages: lend money at punitive interest rates, such that the borrower can never repay the debt, and then terrorize the borrower into making payments for as long as possible. Do this right and the borrower will pay you several times the value of the loan, and still owe you a bundle. If the borrower ever earns anything, you'll have a claim on it. Think of Americans who borrowed $79,000 to go to university, paid back $190,000 and still owe $236,000:

https://pluralistic.net/2020/12/04/kawaski-trawick/#strike-debt

This kind of loan-sharking is profitable, but labor-intensive. It requires that the debtor make payments they fundamentally can't afford. The usurer needs to get their straw right down into the very bottom of the borrower's milkshake and suck up every drop. You need to convince the debtor to sell their wedding ring, then dip into their kid's college fund, then steal their father's coin collection, and, then break into cars to steal the stereos. It takes a lot of person-to-person work to keep your sucker sufficiently motivated to do all that.

This is where digital meets subprime. There's $1T worth of subprime car-loans in America. These are pure predation: the lender sells a beater to a mark, offering a low down-payment loan with a low initial interest rate. The borrower makes payments at that rate for a couple of months, but then the rate blows up to more than they can afford.

Trusted computing makes this marginal racket into a serious industry. First, there's the ability of the car to narc you out to the repo man by reporting on its location. Tesla does one better: if you get behind in your payments, your Tesla immobilizes itself and phones home, waits for the repo man to come to the parking lot, then it backs itself out of the spot while honking its horn and flashing its lights:

https://tiremeetsroad.com/2021/03/18/tesla-allegedly-remotely-unlocks-model-3-owners-car-uses-smart-summon-to-help-repo-agent/

That immobilization trick shows how a canny subprime car-lender can combine the two kinds of subprime: they can secure the loan against an asset (the car), but also coerce borrowers into prioritizing repayment over other necessities of life. After your car immobilizes itself, you just might decide to call the dealership and put down your credit card, even if that means not being able to afford groceries or child support or rent.

One thing we can say about digital tools: they're flexible. Any sadistic motivational technique a lender can dream up, a computerized device can execute. The subprime car market relies on a spectrum of coercive tactics: cars that immobilize themselves, sure, but how about cars that turn on their speakers to max and blare a continuous recording telling you that you're a deadbeat and demanding payment?

https://archive.nytimes.com/dealbook.nytimes.com/2014/09/24/miss-a-payment-good-luck-moving-that-car/

The more a subprime lender can rely on a gadget to torment you on their behalf, the more loans they can issue. Here, at last, is a form of automation-driven mass unemployment: normally, an economy that has been fully captured by wealthy oligarchs needs squadrons of cruel arm-breakers to convince the plebs to prioritize debt service over survival. The infinitely flexible, tireless digital arm-breakers enabled by trusted computing have deprived all of those skilled torturers of their rightful employment:

https://pluralistic.net/2021/04/02/innovation-unlocks-markets/#digital-arm-breakers

The world leader in trusted computing isn't cars, though – it's phones. Long before anyone figured out how to make a car take orders from its manufacturer over the objections of its driver, Apple and Google were inventing "curating computing" whose app stores determined which software you could run and how you could run it.

Back in 2021, Indian subprime lenders hit on the strategy of securing their loans by loading borrowers' phones up with digital arm-breaking software:

https://restofworld.org/2021/loans-that-hijack-your-phone-are-coming-to-india/

The software would gather statistics on your app usage. When you missed a payment, the phone would block you from accessing your most frequently used app. If that didn't motivate you to pay, you'd lose your second-most favorite app, then your third, fourth, etc.

This kind of digital arm-breaking is only possible if your phone is designed to prioritize remote instructions – from the manufacturer and its app makers – over your own. It also only works if the digital arm-breaking company can confirm that you haven't jailbroken your phone, which might allow you to send fake data back saying that your apps have been disabled, while you continue to use those apps. In other words, this kind of digital sadism only works if you've got trusted computing and remote attestation.

Enter "Device Lock Controller," an app that comes pre-installed on some Google Pixel phones. To quote from the app's description: "Device Lock Controller enables device management for credit providers. Your provider can remotely restrict access to your device if you don't make payments":

https://lemmy.world/post/13359866

Google's pitch to Android users is that their "walled garden" is a fortress that keeps people who want to do bad things to you from reaching you. But they're pre-installing software that turns the fortress into a prison that you can't escape if they decide to let someone come after you.

There's a certain kind of economist who looks at these forms of automated, fine-grained punishments and sees nothing but a tool for producing an "efficient market" in debt. For them, the ability to automate arm-breaking results in loans being offered to good, hardworking people who would otherwise be deprived of credit, because lenders will judge that these borrowers can be "incentivized" into continuing payments even to the point of total destitution.

This is classic efficient market hypothesis brain worms, the kind of cognitive dead-end that you arrive at when you conceive of people in purely economic terms, without considering the power relationships between them. It's a dead end you navigate to if you only think about things as they are today – vast numbers of indebted people who command fewer assets and lower wages than at any time since WWII – and treat this as a "natural" state: "how can these poors expect to be offered more debt unless they agree to have their all-important pocket computers booby-trapped?"

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/2024/03/29/boobytrap/#device-lock-controller

Image: Oatsy (modified) https://www.flickr.com/photos/oatsy40/21647688003

CC BY 2.0 https://creativecommons.org/licenses/by/2.0/

#pluralistic #debt #subprime #armbreakers #mobile #google #android #apps #drm #technological self-determination #efficient market hypothesis brainworms #law and political economy #gadgets #boobytraps #app stores #curated computing #og app #trusted computing

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smovs · 1 year

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Notes to make Clip Studio Paint's 3D model posing tools a little less overwhelming

SET HOTKEYS

first thing to do is to set keyboard shortcuts. To interact with the 3D models you need the Operation > Object tool.

(I'd also recommend the Move Layer tool if you haven't already hotkeyed it)

BRING IN THE MODEL

grab a default model from the 3D Materials window, drop it onto your canvas, & set the scale to your liking.

TIP: you're gonna wanna use the MOVE LAYER tool to adjust the model's position on your canvas. If you start dragging it around with the Object selection tools, it'll move the model relative to its own ground plane & camera. Recipe for a headache.

Move Layer tool = no more tears

CUSTOM BODY SHAPE

You can adjust the model's body proportions on the fly by opening up the sub tool window as shown below.

I recommend this 60 second video by Iron Circus for more detail: youtu.be/zrtAyY3Qqmo

As they suggest, start at the feet & work your way up.

and you're ready to start posing!

...don't know dick-all about 3D software? it works like this:

translation / rotation are often shortened to trans / rot, which is coincidentally the name of my new band.

it doesn't matter which mode you use, and you'll be bouncing back n' forth most of the time. don't even worry about remembering what they're called.

just let it wash over you 🌊☮️

SWITCHING BETWEEN FK & IK

it's so easy to do this that you're probably gonna do it on accident constantly.

Click once on the model for IK, click again for FK.

POSING BREAKDOWN

now we're ready to pose. generally, I start from the center of the body and work outward.

1 Pelvis

2 Torso

3 Neck & Head tilt

4 Clavicles

5 Upper arm > Forearm > Wrist > Fingers // Thigh > Shin > Ankle > Foot Arch

[my posing timelapse gif is too big for tumblr- you can see it on my website if you’re so compelled. or this tweet]

TOUCHUPS

Now it's blocked in, you can go back in for tweaks. I find it's good practice to click away & deselect the previous joint before going in to select the next one. Helps avoid misclicks.

[yeah, same thing]

WINDOW > ALL SIDES VIEW

for more camera angles.

Good for when you're struggling to select a control cause it's hiding behind the other body parts.

The arm range is a bit limited, it can be tough gettin the hands/elbows to reach behind the body. don't sweat it too hard, these models are just for reference after all.

But if you've hit a wall, I got one last cheat for ya tonight:

LIQUIFY TOOL

when you've posed as best as you can and it's still not close enough, flatten the layer (right click > rasterize) and hit it with the liquify tool.

Good luck out there!

#lemme know if i can clarify anything better #getting emotional about how far technology has come & how utterly efficient these processes are now #we're living in the future #clip studio paint #csp tutorial #kinda #long post #tutorial type shit / behind the scenes

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blondielaguer1989blog · 2 months

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#ai world #advanced technology #cityscape #efficiency #ai #aiart #artificial intelligence #art #futuristic #digitalart

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theharrowing · 6 months

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docs has gotten...bad? it changes words on me rather than making suggestions (swapped 'situation' with 'citation' completely unprovoked) but now it also can't conceive of really basic spelling errors. (i wrote 'plumet' rather than 'plummet' and it couldn't recommend the right word? i imagine that omitting a repeating letter is a super common spelling error...???)

it's so frustrating to have my creative process slowed down (or made confusing as hell) because the stupid proofreading tool is making unwanted changes on the sly but finding it impossible to read and correct simple mistakes. iphone has been doing a lot of similar shit with autocorrect, as well. i don't understand how rather than become better these systems become worse with time lol.

#just a little rant #i feel like technology is meant to be smart and efficient and it's so annoying when it is the opposite #at least i know that if the machines rise against the humans they will be easy as shit to confuse

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jcmarchi · 7 days

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Scientists use generative AI to answer complex questions in physics

New Post has been published on https://thedigitalinsider.com/scientists-use-generative-ai-to-answer-complex-questions-in-physics/

Scientists use generative AI to answer complex questions in physics

When water freezes, it transitions from a liquid phase to a solid phase, resulting in a drastic change in properties like density and volume. Phase transitions in water are so common most of us probably don’t even think about them, but phase transitions in novel materials or complex physical systems are an important area of study.

To fully understand these systems, scientists must be able to recognize phases and detect the transitions between. But how to quantify phase changes in an unknown system is often unclear, especially when data are scarce.

Researchers from MIT and the University of Basel in Switzerland applied generative artificial intelligence models to this problem, developing a new machine-learning framework that can automatically map out phase diagrams for novel physical systems.

Their physics-informed machine-learning approach is more efficient than laborious, manual techniques which rely on theoretical expertise. Importantly, because their approach leverages generative models, it does not require huge, labeled training datasets used in other machine-learning techniques.

Such a framework could help scientists investigate the thermodynamic properties of novel materials or detect entanglement in quantum systems, for instance. Ultimately, this technique could make it possible for scientists to discover unknown phases of matter autonomously.

“If you have a new system with fully unknown properties, how would you choose which observable quantity to study? The hope, at least with data-driven tools, is that you could scan large new systems in an automated way, and it will point you to important changes in the system. This might be a tool in the pipeline of automated scientific discovery of new, exotic properties of phases,” says Frank Schäfer, a postdoc in the Julia Lab in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and co-author of a paper on this approach.

Joining Schäfer on the paper are first author Julian Arnold, a graduate student at the University of Basel; Alan Edelman, applied mathematics professor in the Department of Mathematics and leader of the Julia Lab; and senior author Christoph Bruder, professor in the Department of Physics at the University of Basel. The research is published today in Physical Review Letters.

Detecting phase transitions using AI

While water transitioning to ice might be among the most obvious examples of a phase change, more exotic phase changes, like when a material transitions from being a normal conductor to a superconductor, are of keen interest to scientists.

These transitions can be detected by identifying an “order parameter,” a quantity that is important and expected to change. For instance, water freezes and transitions to a solid phase (ice) when its temperature drops below 0 degrees Celsius. In this case, an appropriate order parameter could be defined in terms of the proportion of water molecules that are part of the crystalline lattice versus those that remain in a disordered state.

In the past, researchers have relied on physics expertise to build phase diagrams manually, drawing on theoretical understanding to know which order parameters are important. Not only is this tedious for complex systems, and perhaps impossible for unknown systems with new behaviors, but it also introduces human bias into the solution.

More recently, researchers have begun using machine learning to build discriminative classifiers that can solve this task by learning to classify a measurement statistic as coming from a particular phase of the physical system, the same way such models classify an image as a cat or dog.

The MIT researchers demonstrated how generative models can be used to solve this classification task much more efficiently, and in a physics-informed manner.

The Julia Programming Language, a popular language for scientific computing that is also used in MIT’s introductory linear algebra classes, offers many tools that make it invaluable for constructing such generative models, Schäfer adds.

Generative models, like those that underlie ChatGPT and Dall-E, typically work by estimating the probability distribution of some data, which they use to generate new data points that fit the distribution (such as new cat images that are similar to existing cat images).

However, when simulations of a physical system using tried-and-true scientific techniques are available, researchers get a model of its probability distribution for free. This distribution describes the measurement statistics of the physical system.

A more knowledgeable model

The MIT team’s insight is that this probability distribution also defines a generative model upon which a classifier can be constructed. They plug the generative model into standard statistical formulas to directly construct a classifier instead of learning it from samples, as was done with discriminative approaches.

“This is a really nice way of incorporating something you know about your physical system deep inside your machine-learning scheme. It goes far beyond just performing feature engineering on your data samples or simple inductive biases,” Schäfer says.

This generative classifier can determine what phase the system is in given some parameter, like temperature or pressure. And because the researchers directly approximate the probability distributions underlying measurements from the physical system, the classifier has system knowledge.

This enables their method to perform better than other machine-learning techniques. And because it can work automatically without the need for extensive training, their approach significantly enhances the computational efficiency of identifying phase transitions.

At the end of the day, similar to how one might ask ChatGPT to solve a math problem, the researchers can ask the generative classifier questions like “does this sample belong to phase I or phase II?” or “was this sample generated at high temperature or low temperature?”

Scientists could also use this approach to solve different binary classification tasks in physical systems, possibly to detect entanglement in quantum systems (Is the state entangled or not?) or determine whether theory A or B is best suited to solve a particular problem. They could also use this approach to better understand and improve large language models like ChatGPT by identifying how certain parameters should be tuned so the chatbot gives the best outputs.

In the future, the researchers also want to study theoretical guarantees regarding how many measurements they would need to effectively detect phase transitions and estimate the amount of computation that would require.

This work was funded, in part, by the Swiss National Science Foundation, the MIT-Switzerland Lockheed Martin Seed Fund, and MIT International Science and Technology Initiatives.

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techbroer · 10 days

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The Role of APIs in Software Development and Integration

The role of APIs in software development and integration. Have you ever wondered how your diverse smartphone apps interact seamlessly or how data flows effortlessly between other software systems you use daily? The magic is in something called an API or Application Programming Interface. This paper explains APIs and their role in modern software development and system integration.

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materialsscienceandengineering · 10 months

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With global warming on the rise, it has become imperative to reduce fossil fuel dependency and switch to alternate green energy sources. The development of electric vehicles is a move towards this direction. However, electric vehicles require high energy density batteries for their functioning, and conventional lithium-ion batteries are not up to the task. Theoretically, lithium-air batteries provide a higher energy density than lithium-ion batteries. However, before they can be put to practical use, these batteries need to be made energy efficient, their cycle characteristics need to be enhanced, and the overpotential needed to charge/discharge the oxygen redox reaction needs to be reduced. To address these issues, a suitable catalyst is needed to accelerate the oxygen evolution reaction (OER) inside the battery. The OER is an extremely important chemical reaction involved in water splitting for improving the performance of storage batteries. Rare and expensive noble metal oxides such as ruthenium(IV) oxide (RuO2) and iridium(IV) oxide (IrO2) have typically been used as catalysts to expedite the OER of metal-air batteries. More affordable catalytic materials include transition metals, such as perovskite-type oxides and hydroxides, which are known to be highly active for the OER. CoSn(OH)6 (CSO) is one such perovskite-type hydroxide that is known to be a promising OER catalyst. However, current methods of synthesizing CSO are slow (require over 12 hours) and require multiple steps.

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clevertalelover · 2 months

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SendBuddy AI Review: Unlock the Ultimate Email Marketing Powerhouse|

Welcome to my blog post SendBuddy AI Review. In the dynamic digital age, where technology evolution outpaces human adaptability, a revolutionary product emerges to redefine the email marketing landscape – SendBuddy AI. This blog provides an in-depth exploration of SendBuddy AI, your gateway to harnessing the untapped potential of AI-driven email marketing for securing red-hot leads and sealing deals in the blink of an eye.

Read the full review here>>>

#SendBuddy #AI #Review #ArtificialIntelligence #Chatbots #Automation #Messaging #CustomerService #DigitalAssistants #Communication #Technology #Productivity #Innovation #Efficiency #CustomerExperience

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moonindoon · 2 months

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Cracking the Code: Manifesting Success with AI-Driven Marketing Strategies

As the domain of marketing technology continues to grow at a rapid pace and is driven by growth in artificial intelligence (AI) and personalization, marketers encounter exciting opportunities as well as daunting challenges. Adapting to these changes requires practical approaches that allow organizations to stay current, manage change effectively, and operate at scale.

In this article, we explore five practical tactics to help modern marketing teams adapt and thrive in this dynamic environment:

Embrace More 'Human' Customer Engagement Technology:

While chatbots have been around for decades, advancements in AI have significantly enhanced their capabilities. Today, AI-powered chatbots can engage with customers in a remarkably human-like manner, providing round-the-clock support and valuable insights.

Leveraging chatbots not only improves customer experience but also generates valuable data for outbound marketing initiatives. By analyzing customer queries and interactions, marketers can easily get valuable data that can enhance their marketing strategies.

Harness Customer Data Responsibly:

Customers willingly share personal information with companies, providing valuable insights into their preferences, behaviours, and sentiments. Marketers must mine this data responsibly and use it to deliver personalized experiences and targeted offers.

By leveraging predictive analytics and machine learning, marketers can analyze data faster and make informed decisions to enhance omnichannel marketing efforts.

Utilize Content Repurposing Tools:

Authentic content remains paramount in marketing, but creating content for various channels and platforms can be challenging. Content repurposing tools like Optimizely and Interaction Studio help marketers adapt long-form content into social media posts, videos, and other formats.

Expanding your content footprint not only enhances brand visibility but also allows for faster learning and adaptation to changing market dynamics.

Invest in Upskilling Your Team:

While AI-based tools offer significant automation potential, managing and mastering these technologies require skilled professionals. Marketers must invest in continuous learning and cross-functional collaboration to stay ahead.

Effective leadership and teamwork are essential for navigating the complexities of modern marketing. Encouraging knowledge sharing and collaboration across teams fosters a culture of innovation and growth.

Embrace Transformational Opportunities:

As AI continues to reshape the marketing landscape, traditional metrics of success are being redefined. Marketers must embrace the transformative potential of AI and other emerging technologies to serve their customers better.

When evaluating new ideas and technologies, marketers should prioritize customer value and align them with their brand and company values. By focusing on solutions that genuinely benefit customers, marketers can drive meaningful impact and success.

In conclusion, navigating the ever-evolving domain of AI-driven marketing requires a blend of innovative strategies and steadfast principles. By embracing more human-centric engagement technologies, responsibly harnessing customer data, utilizing content repurposing tools, investing in team upskilling, and embracing transformational opportunities, modern marketing teams can position themselves for success. The key lies in adapting to change while remaining true to customer-centric values, fostering collaboration, and prioritizing solutions that genuinely benefit the audience. With these practical tactics in hand, marketers can not only thrive but also lead the way in shaping the future of marketing.

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notthestarwar · 9 months

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Look what image to text did to my woooords

There is so much of this lol. Paragraphs and paragraphs

#i mean #writing something in one app #screenshotting it #and then image to text is clearly not efficient but like #it's never been this bad before #my words #my beautiful words about Jango #what have you done #cruel technology

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seoconsultantaustraliaa · 3 months

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85% of Australian e-commerce content found to be plagiarised

Optidan Published a Report Recently

OptiDan, an Australia-based specialist in AI-driven SEO strategies & Solutions, has recently published a report offering fresh insights into the Australian e-commerce sector. It reveals a striking statistic about content across more than 780 online retailers: 85% of it is plagiarised. This raises severe questions about authenticity and quality in the e-commerce world, with possibly grave implications for both consumers and retailers.

Coming from the founders of OptiDan, this report illuminates an issue that has largely fallen under the radar: content duplication. The report indicates that suppliers often supply identical product descriptions to several retailers, resulting in a sea of online stores harbouring the same content. This lack of uniqueness unfortunately leads to many sites being pushed down in search engine rankings, due to algorithms detecting the duplication. This results in retailers having to spend more on visibility through paid advertising to compensate.

Key Findings in Analysis

Key findings from OptiDan's research include a worrying lack of originality, with 86% of product pages not even meeting basic word count standards. Moreover, even among those that do feature sufficient word counts, Plagiarism is distressingly widespread. Notably, OptiDan's study presented clear evidence of the detrimental impacts of poor product content on consumer trust and return rates.

Founder and former retailer JP Tucker notes, "Online retailers anticipate high product ranking by Google and expect sales without investing in necessary, quality content — an essential for both criteria." Research from 2016 by Shotfarm corroborates these findings, suggesting that 40% of customers return online purchases due to poor product content.

Tucker's industry report reveals that Google usually accepts up to 10% of plagiarism to allow for the use of common terms. Nonetheless, OptiDan's study discovered that over 85% of audited product pages were above this limit. Further, over half of the product pages evidenced plagiarism levels of over 75%.

"Whilst I knew the problem was there, the high levels produced in the Industry report surprised me," said Tucker, expressing the depth of the issue. He's also noted the manufactured absence of the product title in the product description, a crucial aspect of SEO, in 85% of their audited pages. "Just because it reads well, doesn't mean it indexes well."

OptiDan has committed itself to transforming content performance for the online retail sector, aiming to make each brand's content work for them, instead of against them. Tucker guarantees the effectiveness of OptiDan's revolutionary approach: "We specialise in transforming E-commerce SEO content within the first month, paving the way for ongoing optimisation and reindexing performance."

OptiDan has even put a money-back guarantee on its Full Content Optimisation Service for Shopify & Shopify Plus partners. This offer is expected to extend to non-Shopify customers soon. For now, all retailers can utilise a free website audit of their content through OptiDan.

Optidan – Top AI SEO Agency

Optidan is a Trusted AI SEO services Provider Company from Sydney, Australia. Our Services like - Bulk Content Creation SEO, Plagiarism Detection SEO, AI-based SEO, Machine Learning AI, Robotic SEO Automation, and Semantic SEO

We’re not just a service provider; we’re a partner, a collaborator, and a fellow traveller on this exciting digital journey. Together, let’s explore the limitless possibilities and redefine digital success.

Intrigued to learn more? Let’s connect! Schedule a demo call with us and discover how OptiDan can transform your digital performance.

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