Daric Gill used an Arduino UNO R3 to create his “The Translation Machine” sound art installation for an exhibition at the Dunn Museum. Except he didn’t do it alone, because bees helped with its construction.

The Translation Machine is a motion-triggered interactive art piece that plays sounds that Gill collected during his world travels. He recorded those using binaural microphones, which approximate human ears (including the distance between them) to produce spatial audio like we hear in the real world. It plays those sounds when someone comes within view of its passive infrared (PIR) sensor. And it monitors their distance with an ultrasonic sensor, pumping up the volume as they get closer.

The enclosure that contains the Arduino and other components, plus the amplification horns for the speakers, are made of sassafras wood. That isn’t very common for woodworking these days, but Gill reclaimed the wood from an old barn.

The best part of this project, however, is the incorporation of honeycombs built by bees. While he was traveling and capturing those binaural recordings, Gill left the sassafras wood speakers horns at The Bee Collective. They seeded those horns with starter wax, which encouraged their bee colonies to construct honeycombs within the horns. Now, at the exhibition, anyone approaching “The Translation Machine” will hear the sound filtered through honeycomb. 

The post Bees built it, Arduino brought it to life appeared first on Arduino Blog.

Read more here: https://blog.arduino.cc/2025/11/25/bees-built-it-arduino-brought-it-to-life/

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Some members of the maker community are distraught about Arduino’s new terms of service (ToS), saying that the added rules put the company’s open source DNA at risk.

Arduino updated its ToS and privacy policy this month, which is about a month after Qualcomm announced that it’s acquiring the open source hardware and software company. Among the most controversial changes is this addition:

User shall not:

• translate, decompile or reverse-engineer the Platform, or engage in any other activity designed to identify the algorithms and logic of the Platform’s operation, unless expressly allowed by Arduino or by applicable license agreements …

In response to concerns from some members of the maker community, including from open source hardware distributor and manufacturer Adafruit, Arduino posted a blog on Friday. Regarding the new reverse-engineering rule, Arduino’s blog said:

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Read more here: https://arstechnica.com/gadgets/2025/11/arduinos-new-terms-of-service-worries-hobbyists-ahead-of-qualcomm-acquisition/

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On the surface, the Superbox media streaming devices for sale at retailers like BestBuy and Walmart may seem like a steal: They offer unlimited access to more than 2,200 pay-per-view and streaming services like Netflix, ESPN and Hulu, all for a one-time fee of around $400. But security experts warn these TV boxes require intrusive software that forces the user’s network to relay Internet traffic for others, traffic that is often tied to cybercrime activity such as advertising fraud and account takeovers.

Superbox media streaming boxes for sale on Walmart.com.

Superbox bills itself as an affordable way for households to stream all of the television and movie content they could possibly want, without the hassle of monthly subscription fees — for a one-time payment of nearly $400.

“Tired of confusing cable bills and hidden fees?,” Superbox’s website asks in a recent blog post titled, “Cheap Cable TV for Low Income: Watch TV, No Monthly Bills.”

“Real cheap cable TV for low income solutions does exist,” the blog continues. “This guide breaks down the best alternatives to stop overpaying, from free over-the-air options to one-time purchase devices that eliminate monthly bills.”

Superbox claims that watching a stream of movies, TV shows, and sporting events won’t violate U.S. copyright law.

“SuperBox is just like any other Android TV box on the market, we can not control what software customers will use,” the company’s website maintains. “And you won’t encounter a law issue unless uploading, downloading, or broadcasting content to a large group.”

A blog post from the Superbox website.

There is nothing illegal about the sale or use of the Superbox itself, which can be used strictly as a way to stream content at providers where users already have a paid subscription. But that is not why people are shelling out $400 for these machines. The only way to watch those 2,200+ channels for free with a Superbox is to install several apps made for the device that enable them to stream this content.

Superbox’s homepage includes a prominent message stating the company does “not sell access to or preinstall any apps that bypass paywalls or provide access to unauthorized content.” The company explains that they merely provide the hardware, while customers choose which apps to install.

“We only sell the hardware device,” the notice states. “Customers must use official apps and licensed services; unauthorized use may violate copyright law.”

Superbox is technically correct here, except for maybe the part about how customers must use official apps and licensed services: Before the Superbox can stream those thousands of channels, users must configure the device to update itself, and the first step involves ripping out Google’s official Play store and replacing it with something called the “App Store” or “Blue TV Store.”

Superbox does this because the device does not use the official Google-certified Android TV system, and its apps will not load otherwise. Only after the Google Play store has been supplanted by this unofficial App Store do the various movie and video streaming apps that are built specifically for the Superbox appear available for download (again, outside of Google’s app ecosystem).

Experts say while these Android streaming boxes generally do what they advertise — enabling buyers to stream video content that would normally require a paid subscription — the apps that enable the streaming also ensnare the user’s Internet connection in a distributed residential proxy network that uses the devices to relay traffic from others.

Ashley is a senior solutions engineer at Censys, a cyber intelligence company that indexes Internet-connected devices, services and hosts. Ashley requested that only her first name be used in this story.

In a recent video interview, Ashley showed off several Superbox models that the Censys research team was studying in the malware lab — including one purchased off the shelf at BestBuy.

“I’m sure a lot of people are thinking, ‘Hey, how bad could it be if it’s for sale at the big box stores?’” she said. “But the more I looked, things got weirder and weirder.”

Ashley said she found the Superbox devices immediately contacted a server at the Chinese instant messaging service Tencent QQ, as well as a residential proxy service called Grass IO.

GET GRASSED

Also known as getgrass[.]io, Grass says it is “a decentralized network that allows users to earn rewards by sharing their unused Internet bandwidth with AI labs and other companies.”

“Buyers seek unused internet bandwidth to access a more diverse range of IP addresses, which enables them to see certain websites from a retail perspective,” the Grass website explains. “By utilizing your unused internet bandwidth, they can conduct market research, or perform tasks like web scraping to train AI.” 

Reached via Twitter/X, Grass founder Andrej Radonjic told KrebsOnSecurity he’d never of a Superbox, and that Grass has no affiliation with the device maker.

“It looks like these boxes are distributing an unethical proxy network which people are using to try to take advantage of Grass,” Radonjic said. “The point of grass is to be an opt-in network. You download the grass app to monetize your unused bandwidth. There are tons of sketchy SDKs out there that hijack people’s bandwidth to help webscraping companies.”

Radonjic said Grass has implemented “a robust system to identify network abusers,” and that if it discovers anyone trying to misuse or circumvent its terms of service, the company takes steps to stop it and prevent those users from earning points or rewards.

Superbox’s parent company, Super Media Technology Company Ltd., lists its street address as a UPS store in Fountain Valley, Calif. The company did not respond to multiple inquiries.

According to this teardown by behindmlm.com, a blog that covers multi-level marketing (MLM) schemes, Grass’s compensation plan is built around “grass points,” which are earned through the use of the Grass app and through app usage by recruited affiliates. Affiliates can earn 5,000 grass points for clocking 100 hours usage of Grass’s app, but they must progress through ten affiliate tiers or ranks before they can redeem their grass points (presumably for some type of cryptocurrency). The 10th or “Titan” tier requires affiliates to accumulate a whopping 50 million grass points, or recruit at least 221 more affiliates.

Radonjic said Grass’s system has changed in recent months, and confirmed the company has a referral program where users can earn Grass Uptime Points by contributing their own bandwidth and/or by inviting other users to participate.

“Users are not required to participate in the referral program to earn Grass Uptime Points or to receive Grass Tokens,” Radonjic said. “Grass is in the process of phasing out the referral program and has introduced an updated Grass Points model.”

A review of the Terms and Conditions page for getgrass[.]io at the Wayback Machine shows Grass’s parent company has changed names at least five times in the course of its two-year existence. Searching the Wayback Machine on getgrass[.]io shows that in June 2023 Grass was owned by a company called Wynd Network. By March 2024, the owner was listed as Lower Tribeca Corp. in the Bahamas. By August 2024, Grass was controlled by a Half Space Labs Limited, and in November 2024 the company was owned by Grass OpCo (BVI) Ltd. Currently, the Grass website says its parent is just Grass OpCo Ltd (no BVI in the name).

Radonjic acknowledged that Grass has undergone “a handful of corporate clean-ups over the last couple of years,” but described them as administrative changes that had no operational impact. “These reflect normal early-stage restructuring as the project moved from initial development…into the current structure under the Grass Foundation,” he said.

UNBOXING

Censys’s Ashley said the phone home to China’s Tencent QQ instant messaging service was the first red flag with the Superbox devices she examined. She also discovered the streaming boxes included powerful network analysis and remote access tools, such as Tcpdump and Netcat.

“This thing DNS hijacked my router, did ARP poisoning to the point where things fall off the network so they can assume that IP, and attempted to bypass controls,” she said. “I have root on all of them now, and they actually have a folder called ‘secondstage.’ These devices also have Netcat and Tcpdump on them, and yet they are supposed to be streaming devices.”

A quick online search shows various Superbox models and many similar Android streaming devices for sale at a wide range of top retail destinations, including Amazon, BestBuy, Newegg, and Walmart. Newegg.com, for example, currently lists more than three dozen Superbox models. In all cases, the products are sold by third-party merchants on these platforms, but in many instances the fulfillment comes from the e-commerce platform itself.

“Newegg is pretty bad now with these devices,” Ashley said. “Ebay is the funniest, because they have Superbox in Spanish — the SuperCaja — which is very popular.”

Superbox devices for sale via Newegg.com.

Ashley said Amazon recently cracked down on Android streaming devices branded as Superbox, but that those listings can still be found under the more generic title “modem and router combo” (which may be slightly closer to the truth about the device’s behavior).

Superbox doesn’t advertise its products in the conventional sense. Rather, it seems to rely on lesser-known influencers on places like Youtube and TikTok to promote the devices. Meanwhile, Ashley said, Superbox pays those influencers 50 percent of the value of each device they sell.

“It’s weird to me because influencer marketing usually caps compensation at 15 percent, and it means they don’t care about the money,” she said. “This is about building their network.”

A TikTok influencer casually mentions and promotes Superbox while chatting with her followers over a glass of wine.

BADBOX

As plentiful as the Superbox is on e-commerce sites, it is just one brand in an ocean of no-name Android-based TV boxes available to consumers. While these devices generally do provide buyers with “free” streaming content, they also tend to include factory-installed malware or require the installation of third-party apps that engage the user’s Internet address in advertising fraud.

In July 2025, Google filed a “John Doe” lawsuit (PDF) against 25 unidentified defendants dubbed the “BadBox 2.0 Enterprise,” which Google described as a botnet of over ten million Android streaming devices that engaged in advertising fraud. Google said the BADBOX 2.0 botnet, in addition to compromising multiple types of devices prior to purchase, can also infect devices by requiring the download of malicious apps from unofficial marketplaces.

Some of the unofficial Android devices flagged by Google as part of the Badbox 2.0 botnet are still widely for sale at major e-commerce vendors. Image: Google.

Several of the Android streaming devices flagged in Google’s lawsuit are still for sale on top U.S. retail sites. For example, searching for the “X88Pro 10” and the “T95” Android streaming boxes finds both continue to be peddled by Amazon sellers.

Google’s lawsuit came on the heels of a June 2025 advisory from the Federal Bureau of Investigation (FBI), which warned that cyber criminals were gaining unauthorized access to home networks by either configuring the products with malicious software prior to the user’s purchase, or infecting the device as it downloads required applications that contain backdoors, usually during the set-up process.

“Once these compromised IoT devices are connected to home networks, the infected devices are susceptible to becoming part of the BADBOX 2.0 botnet and residential proxy services known to be used for malicious activity,” the FBI said.

The FBI said BADBOX 2.0 was discovered after the original BADBOX campaign was disrupted in 2024. The original BADBOX was identified in 2023, and primarily consisted of Android operating system devices that were compromised with backdoor malware prior to purchase.

Riley Kilmer is founder of Spur, a company that tracks residential proxy networks. Kilmer said Badbox 2.0 was used as a distribution platform for IPidea, a China-based entity that is now the world’s largest residential proxy network.

Kilmer and others say IPidea is merely a rebrand of 911S5 Proxy, a China-based proxy provider sanctioned last year by the U.S. Department of the Treasury for operating a botnet that helped criminals steal billions of dollars from financial institutions, credit card issuers, and federal lending programs (the U.S. Department of Justice also arrested the alleged owner of 911S5).

How are most IPidea customers using the proxy service? According to the proxy detection service Synthient, six of the top ten destinations for IPidea proxies involved traffic that has been linked to either ad fraud or credential stuffing (account takeover attempts).

Kilmer said companies like Grass are probably being truthful when they say that some of their customers are companies performing web scraping to train artificial intelligence efforts, because a great deal of content scraping which ultimately benefits AI companies is now leveraging these proxy networks to further obfuscate their aggressive data-slurping activity. By routing this unwelcome traffic through residential IP addresses, Kilmer said, content scraping firms can make it far trickier to filter out.

“Web crawling and scraping has always been a thing, but AI made it like a commodity, data that had to be collected,” Kilmer told KrebsOnSecurity. “Everybody wanted to monetize their own data pots, and how they monetize that is different across the board.”

SOME FRIENDLY ADVICE

Products like Superbox are drawing increased interest from consumers as more popular network television shows and sportscasts migrate to subscription streaming services, and as people begin to realize they’re spending as much or more on streaming services than they previously paid for cable or satellite TV.

These streaming devices from no-name technology vendors are another example of the maxim, “If something is free, you are the product,” meaning the company is making money by selling access to and/or information about its users and their data.

Superbox owners might counter, “Free? I paid $400 for that device!” But remember: Just because you paid a lot for something doesn’t mean you are done paying for it, or that somehow you are the only one who might be worse off from the transaction.

It may be that many Superbox customers don’t care if someone uses their Internet connection to tunnel traffic for ad fraud and account takeovers; for them, it beats paying for multiple streaming services each month. My guess, however, is that quite a few people who buy (or are gifted) these products have little understanding of the bargain they’re making when they plug them into an Internet router.

Superbox performs some serious linguistic gymnastics to claim its products don’t violate copyright laws, and that its customers alone are responsible for understanding and observing any local laws on the matter. However, buyer beware: If you’re a resident of the United States, you should know that using these devices for unauthorized streaming violates the Digital Millennium Copyright Act (DMCA), and can incur legal action, fines, and potential warnings and/or suspension of service by your Internet service provider.

According to the FBI, there are several signs to look for that may indicate a streaming device you own is malicious, including:

-The presence of suspicious marketplaces where apps are downloaded.
-Requiring Google Play Protect settings to be disabled.
-Generic TV streaming devices advertised as unlocked or capable of accessing free content.
-IoT devices advertised from unrecognizable brands.
-Android devices that are not Play Protect certified.
-Unexplained or suspicious Internet traffic.

This explainer from the Electronic Frontier Foundation delves a bit deeper into each of the potential symptoms listed above.

Read more here: https://krebsonsecurity.com/2025/11/is-your-android-tv-streaming-box-part-of-a-botnet/

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Every click, swipe, location ping, or late-night search you make is quietly turning into the world’s newest economic super-asset. Digital footprints now power AI engines, shape political campaigns, drive $1T ad markets, and influence global competition. But who controls this invisible wealth?

For most of human history, economic power was tied to land, labour, capital, or natural resources. Today, a new form of wealth is quietly eclipsing them: the digital footprints we leave behind every time we search, click, chat, shop, stream, or share. 

According to a recent report, the global data-monetisation market (i.e., enterprises selling data or monetising internal data assets) was valued at around US $3.47 billion in 2024, projected to reach US $12.62 billion by 2032.

These trails of behavioural, transactional, and identity-linked data, once considered mere digital exhaust, have now become the world’s most valuable economic asset, fuelling AI models, driving trillion-dollar companies, shaping election strategies, influencing consumer behaviour, and underpinning the next phase of global economic competition.

A United Nations analysis estimated the global “data economy”, meaning the combined market value of data, analytics and related flows, at nearly US $4 trillion in 2018. 

If data was the “new oil” of the 2010s, then digital footprints are the refined fuel of the 2020s and beyond. They are richer, more contextual, highly personal, constantly replenished, and infinitely monetisable. In an AI-powered world, digital footprints are no longer a by-product; they are the product. 

The rise of the digital footprint economy

Digital footprints were once simply metadata: logs that enabled websites and devices to function. Over time, organisations realised that these tiny crumbs of information, location histories, search queries, purchase behaviour, and content preferences held extraordinary predictive power. What began as a technical artefact is now a behavioural map of human society, a forecasting dataset for markets, a training pool for AI models, a tool for hyper-personalised persuasion, and a source of competitive advantage for every modern enterprise.

In effect, digital footprints have transitioned from invisible residue to the centrepiece of the modern data economy. Early adopters, such as search engines in the late 1990s, used basic logs to improve relevance, but today’s systems aggregate billions of points daily, creating profiles that reveal socioeconomic trends with startling precision. This evolution mirrors the industrial revolution, where raw materials became processed goods; here, passive traces transform into active capital that generates ongoing value.

The process involves layering data from multiple sources, including social media, apps, and IoT devices. For instance, a single smartphone can produce up to 1.5 megabytes of data per minute, turning routine activities into economic inputs that businesses refine for profit.

The shift from data collection to behavioural prediction

The first wave of the internet economy was about collecting as much data as possible. The second wave focuses on predicting actions, what we will buy, believe, or desire next. AI systems thrive on digital footprints because they provide real-time behavioural context, unlike structured datasets that lack nuance on habits, emotions, motivations, and impulses.

This is why digital footprints now underpin online advertising, credit scoring, fraud detection, personalised education, real-time insurance risk scoring, AI recommendation engines, health diagnostics and lifestyle tracking, and national surveillance systems. Footprints offer a deeper level of behavioural insight than any traditional economic resource, allowing firms to anticipate needs before they surface.

In practice, machine learning algorithms analyse these patterns to forecast outcomes. For example, streaming services use viewing histories to predict content hits, reducing production risks and boosting subscriber retention by up to 75%. This predictive power extends to public policy, where governments model citizen responses to initiatives based on aggregated footprints.

Why digital footprints have become the new global currency

Oil runs out. Minerals deplete. Land is finite. But digital footprints regenerate every moment of every day. The more humans interact with digital environments, the richer and more granular their footprints become, with every phone unlock, voice command, map search, wearable movement, and online purchase adding another data point to the global behavioural database. This infinite supply makes digital footprints uniquely scalable, supporting exponential growth in data-dependent industries.

Projections indicate that by 2030, daily data generation could triple, driven by 5G networks and edge computing, ensuring a perpetual flow of economic value. Unlike finite resources, footprints improve with volume, as larger datasets enhance AI accuracy through better pattern recognition.

They can be extracted without physical labour

Traditional resources require labour, machinery, or extraction processes. Digital footprints require none of that; they can be collected passively, continuously, and at negligible marginal cost. In effect, individuals produce value every time they interact online, even while they sleep, without being compensated for it.

This frictionless extraction powers platforms where user engagement directly translates to revenue. Social networks, for instance, harvest interactions via embedded trackers, converting free user time into targeted ad sales worth billions annually. The model’s efficiency challenges labour-based economics, positioning footprints as a borderless, cost-free asset.

They have immediate economic utility

Digital footprints are not raw materials waiting to be refined—they are instantly useful to AI systems, advertisers, financial institutions, governments, and technology companies. They can be used to refine algorithms, improve product design, target consumers, optimise logistics, detect anomalies and fraud, personalise services, and forecast economic behaviour. Their utility is instant and universal, enabling rapid deployment across sectors.

In finance, for example, real-time footprints from mobile banking apps adjust loan offers dynamically, expanding access while minimising defaults. This immediacy accelerates innovation cycles, outpacing slower traditional assets.

They are hard to replicate and impossible to counterfeit

Unlike digital files, human footprints are unique, they reflect lived behaviour that cannot be fabricated at scale. This scarcity and authenticity make footprints economically priceless, as synthetic alternatives lack the depth of real-world variability. Authenticity stems from biometric and contextual elements, like irregular typing patterns or location idiosyncrasies, which defy imitation.

This uniqueness fortifies their value in verification-heavy fields, such as identity management, where footprints underpin secure transactions worth trillions globally.

The industries built on digital footprints

Advertising and media

The global advertising industry—now valued at over US$1 trillion—runs almost entirely on digital footprints. Every targeted ad is powered by behavioural data: what we browse, how long we linger, what we like, share, or ignore. The advertising giants of today, Google, Meta, ByteDance, did not grow because of content; they grew because they mastered the art of monetising footprints.

Targeted campaigns yield conversion rates five times higher than broad ones, driving the sector’s dominance in digital revenue streams. Media outlets leverage footprints for content curation, ensuring relevance that sustains viewer engagement.

Artificial Intelligence

AI models are now trained on vast amounts of behavioural data to understand human language, preferences, and decision-making patterns. Large Language Models (LLMs) and multimodal AI systems depend heavily on human digital footprints, including search queries, forum conversations, customer reviews, social posts, user interactions, speech, and video behaviour. AI’s accuracy and intelligence rise exponentially as digital footprints increase, enabling breakthroughs in generative technologies.

Footprints provide the contextual richness needed for nuanced outputs, from chatbots to autonomous systems, powering a market projected to exceed $500 billion by 2025.

Financial services and fintech

Banks and fintech firms use footprints to detect fraud, assess creditworthiness, forecast spending, personalise financial products, and evaluate business risk. In some emerging markets, alternative data credit scoring allows millions without formal financial histories to access loans based purely on their digital behaviour. This democratises finance, with platforms like Upstart using footprints to approve 27% more loans at lower rates.

Footprint-driven analytics reduce default rates by 20-30%, stabilising global financial flows.

Retail and e-commerce

E-commerce platforms use footprints to predict demand, recommend products, set dynamic prices, and optimise supply chains. Amazon’s “anticipatory shipping,” for instance, predicts what a customer is likely to buy before they buy it—powered entirely by digital footprints. Such systems cut delivery times and boost sales by 25%, transforming retail logistics.

Personalisation via footprints also minimises returns, saving retailers billions in operational costs annually.

Healthcare and wellness

Wearables and digital health platforms capture real-time footprints of the human body: heart rate, sleep cycles, physical activity, stress levels, and dietary habits. This data fuels predictive healthcare, early diagnostics, and personalised treatment. Companies like Fitbit analyse these to offer insights that prevent conditions, potentially adding years to life expectancies.

The sector’s data market alone could reach $70 billion by 2025, driven by footprint-enabled telemedicine.

Government and national policy

Governments use digital footprints for national security, urban planning, epidemic forecasting, tax compliance, digital identity systems, and public service optimisation. Countries like India, Singapore, the UAE, and China have national data frameworks that treat citizen footprints as strategic assets. During the COVID-19 pandemic, footprint tracking aided contact tracing, saving countless lives while informing policy.

The economic power of digital footprints

Digital footprints contribute to GDP through data monetisation revenue, productivity gains from AI, new digital services and markets, cost savings for businesses, and new forms of personal and organisational wealth. Whole economies are now modelling growth forecasts on data flows rather than physical goods. The World Economic Forum estimates that data-driven economies could add $15.7 trillion to global GDP by 2030, with footprints as a key driver.

In the UK, the data sector already accounts for 6% of GDP, underscoring footprints’ tangible impact.

Footprints create a competitive advantage

The success of modern companies correlates directly with their ability to capture and use digital footprints. For example, Netflix predicts viewing habits with 80–90% accuracy using footprint-based algorithms, while retailers increase margins by 20–30% with footprint-driven customer insights. AI companies with rich training data outperform rivals by wide margins. The competitive moat of the future is not product quality, it is data depth.

This advantage manifests in market share; data-rich firms like Alibaba dominate e-commerce in Asia through superior footprint utilisation.

Digital Footprints Reduce Risk

They allow organisations to detect patterns that humans alone would miss: early-stage fraud, cybersecurity threats, market shifts, supply chain weaknesses, and customer churn. This predictive capacity has immense economic value, potentially averting losses in the trillions. Insurers, for instance, use driving footprints from apps to adjust premiums, reducing claims by 15%.

The rise of data sovereignty and digital power politics

As digital footprints become economic assets, governments are competing to regulate, capture, or monetise them. 

But why are governments stepping in?

Nations are building digital identity systems, health data exchanges, cross-border data frameworks, AI governance structures, data-sharing rules, national clouds, and sovereign AI models. The battle for digital dominance is now a geopolitical priority, with policies like the EU’s GDPR setting global standards.

In the US, executive orders on data security highlight footprints’ role in national interests.

The new global divide

Countries with large, digitally active populations have a massive advantage in training AI and building digital economies. Digital population size now matters as much as natural resources. This dynamic helps explain why regions like India, China, Southeast Asia, and Africa are becoming major engines of the next digital economy—they generate billions of daily digital footprints.

Data-poor nations risk dependency, importing AI models trained elsewhere, which could widen economic gaps.

Corporate power vs national power

Tech giants now hold more behavioural data on citizens than many governments. This creates complex questions: Who owns digital footprints? Who profits from them? Who protects them? Who decides how they are used in AI? These tensions will define the next decade of policy and economic development. Conflicts, such as US-China tech restrictions, illustrate the stakes.

Balancing corporate innovation with national control remains a core challenge.

The individual: Owner, contributor, or product?

Individuals produce digital footprints, but they rarely see or control the value derived from them. The modern economy treats individuals as producers of data, consumers of digital services, but not beneficiaries of the economic value created. This raises deep ethical questions around fairness and compensation, as users fuel profits without shares.

Surveys show 80% of people feel uneasy about data use, yet continue contributing due to service dependencies.

The next evolution of the data economy may enable individuals to control their footprints, decide who uses them, monetise them, and transport them across platforms. Digital identity wallets, decentralised data storage, and user-controlled data licences are early steps in this direction. Platforms like Ocean Protocol allow data sales on blockchain, empowering users.

These models could redistribute value, with projections of a $100 billion personal data market by 2030.

Future citizens may have systems that show what data is collected, how much economic value it has produced, what revenue companies have earned using it, and the ability to revoke access at any time. This could fundamentally rebalance the digital economy, fostering transparency and agency. Initiatives in the EU already mandate such disclosures, paving the way.

Empowered users might negotiate better terms, akin to content creators today.

AI and the future of digital footprints

AI models are only as powerful as the data they ingest. Digital footprints supply the raw behavioural complexity that enables AI to understand human context, anticipate needs, generate personalised output, and operate autonomously. The AI race is, in many ways, a race for digital footprints, with investments surging to secure datasets.

Without footprints, AI remains generic; with them, it achieves human-like intuition.

While synthetic data is expanding rapidly, it cannot replicate real human unpredictability. Digital footprints remain the gold standard for training high-quality models, providing authentic variability essential for robust AI. Hybrids may emerge, but real footprints ensure reliability in critical applications.

Experts predict that synthetic data will augment, not supplant, by 2030.

Future AI systems will use footprints from voice, video, biometrics, movement, interactions, ambient computing, augmented reality (AR), and brain-computer interfaces (BCIs). These will create a multi-layered behavioural map of human life, enabling unprecedented levels of predictive intelligence. Multimodal AI could revolutionise fields like autonomous vehicles, using integrated footprints for safer navigation.

This integration promises efficiency gains across economies.

The Ethical and Societal Risks

Surveillance Capitalism: Companies that secretly harvest footprints can manipulate behaviour, influence elections, and distort social realities. This model prioritises profit over consent, eroding democratic processes through micro-targeted misinformation. Regulators worldwide are addressing it, but enforcement lags behind tech evolution.

Algorithmic Bias: Footprints often reflect historical inequalities. AI trained on such footprints may reinforce systemic biases, perpetuating discrimination in hiring, lending, and policing. Diverse datasets are crucial to mitigate this, yet collection biases persist. Efforts like bias audits are gaining traction.

Privacy Erosion and Psychological Profiling: Digital footprints can reveal intimate personal details: mental health, political beliefs, sexual orientation, religious inclinations, and future intentions. This level of insight, if misused, threatens individual autonomy. Constant profiling fosters self-censorship, altering societal norms. Privacy tools like VPNs offer partial shields.

Economic Inequality: As companies grow wealthier by monetising footprints they did not pay for, inequality may widen between data-rich corporations and data-producing citizens. Low-income users generate value without benefits, exacerbating divides. Policy interventions could enforce revenue sharing.

The future of digital footprints as a formal economic asset class

We are moving towards a world where digital footprints will be recognised as economic assets, governed by national frameworks, priced in international markets, and integrated into GDP calculations. This formalisation could standardise valuation, treating footprints like intellectual property.

Central banks may track data flows as key indicators.

Emerging models foresee marketplaces where individuals can license their data, cooperatives where communities pool data and share revenue, and decentralised systems where users retain cryptographic control. These exchanges could empower billions, creating new wealth tiers.

Blockchain-based platforms are prototyping this vision.

Future wealth may partly depend on the quality of a person’s digital identity, the value of their behavioural patterns, their influence footprint, and their AI-training contribution. Just as creators monetise content today, individuals may monetise their digital behaviour tomorrow. This shift could redefine prosperity metrics.

Influencers already exemplify early footprint monetisation.

The post How Digital Footprints Are Becoming the World’s Most Powerful Economic Asset appeared first on IntelligentHQ.

Read more here: https://www.intelligenthq.com/digital-footprints-becoming-most-powerful-economic-asset/

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The way we talk to computers is changing fast. It used to be all commands and specific phrases, but now we have AI that can actually chat. This article looks at ai chachat, how it got here, and where it’s going. It’s more than just a tool; it’s changing how we connect with technology and each other.

Key Takeaways

• Ai chachat started with basic programs and has grown into systems that understand us much better.
• These tools are breaking down language barriers and changing how businesses help customers.
• Ai chachat is being used in many areas, from making work easier to helping us learn and have fun.
• The future involves humans and ai chachat working together more closely, almost like partners.
• We need to think about privacy and fairness as ai chachat becomes a bigger part of our lives.

Understanding The Evolution Of Ai Chachat

Artificial intelligence, particularly in the realm of conversational agents, has seen a remarkable transformation. What started as simple rule-based systems has evolved into sophisticated models capable of nuanced and context-aware interactions. This journey reflects a deep commitment to creating AI that can genuinely communicate and assist.

The Genesis Of Advanced Conversational AI

Early conversational AI was quite basic. Think of chatbots that could only respond to very specific commands or keywords. They lacked the ability to understand the intent behind a user’s words or to carry on a natural back-and-forth. The real leap forward came with advancements in machine learning and natural language processing (NLP). These fields allowed AI to start learning from vast amounts of text data, recognizing patterns, and predicting likely responses. This shift from rigid programming to data-driven learning was the foundation for more human-like interaction.

Key Milestones In Ai Chachat Development

The path to today’s advanced AI chat systems is marked by several significant achievements. Each milestone built upon the last, bringing us closer to AI that feels less like a tool and more like a collaborator. Some of these key developments include:

• The advent of recurrent neural networks (RNNs): These allowed AI to process sequential data, like sentences, remembering previous parts of the conversation.
• The development of transformer architectures: This was a game-changer, enabling AI to weigh the importance of different words in a sentence, leading to a much better grasp of context.
• The scaling of models: Training AI on ever-larger datasets and with more computational power has directly correlated with improved performance and capabilities.

These advancements have paved the way for systems that can handle a wide range of conversational tasks, from answering simple questions to generating creative text formats. The progress is ongoing, with new models and techniques emerging regularly, pushing the boundaries of what AI can achieve in communication.

From Algorithms To Human-Like Interaction

The transition from purely algorithmic responses to something resembling human conversation is fascinating. Initially, AI relied on predefined scripts and decision trees. If you deviated from the expected path, the AI would likely falter. However, with the integration of deep learning techniques, AI models began to develop an emergent understanding of language. They learned grammar, context, and even subtle nuances like tone and sentiment, not by being explicitly programmed for each, but by identifying patterns in the data they were trained on. This allows for more flexible and natural exchanges, making interactions feel less like talking to a machine and more like conversing with an intelligent entity. This evolution is critical for applications ranging from customer service to creative writing assistance, as seen in the fashion value chain.

The continuous refinement of AI models, driven by massive datasets and innovative algorithms, has moved conversational AI from a novelty to a powerful utility. The goal is to create systems that are not only informative but also intuitive and adaptable to individual user needs and conversational styles.

Transforming Communication With Ai Chachat

Breaking Down Language Barriers Globally

Communication has always been the bedrock of human connection and progress. For centuries, the diversity of languages has presented a significant hurdle, limiting collaboration and understanding across different cultures. AI Chachat is changing this landscape dramatically. Imagine a world where speaking with someone from the other side of the globe is as simple as talking to a neighbor. AI Chachat models can now translate conversations in real-time, making complex multilingual interactions fluid and natural. This isn’t just about convenience; it’s about opening doors to new partnerships, shared knowledge, and a more unified global community.

• Real-time Translation: AI Chachat can process spoken or written language and translate it instantly into another language, allowing for immediate understanding.
• Contextual Accuracy: Beyond simple word-for-word translation, advanced AI considers nuances, idioms, and cultural context to provide more accurate and meaningful communication.
• Accessibility: This technology makes information and dialogue accessible to a much wider audience, breaking down educational and professional barriers.

The ability of AI Chachat to bridge linguistic divides means that ideas and collaborations are no longer confined by geography or language. This opens up unprecedented opportunities for global problem-solving and cultural exchange.

Redefining Customer Service Interactions

Customer service has often been a source of frustration, characterized by long wait times, repetitive questions, and impersonal responses. AI Chachat is stepping in to revolutionize this experience. Instead of generic scripts, AI Chachat can understand the specific issue a customer is facing, access relevant information, and provide personalized, helpful solutions. This means faster resolutions, more satisfying interactions, and a significant improvement in overall customer satisfaction. Businesses can also use AI Chachat to analyze customer feedback at scale, identifying trends and areas for improvement that might otherwise go unnoticed.

• 24/7 Availability: AI Chachat agents are always on, providing support whenever a customer needs it.
• Personalized Support: AI can recall past interactions and customer preferences to tailor its responses.
• Efficient Problem Solving: By quickly accessing and processing information, AI Chachat can resolve common issues much faster than human agents.

Fostering Deeper Cross-Cultural Exchange

Beyond just practical communication, AI Chachat has the potential to enrich our understanding of different cultures. By facilitating easier communication, it allows individuals to engage more directly with people from diverse backgrounds. This direct interaction, supported by AI’s translation capabilities, can lead to a more authentic appreciation of different perspectives, traditions, and ways of life. This increased exposure and understanding can help reduce misunderstandings and build stronger, more empathetic relationships between people worldwide. It moves us closer to a global village where cultural differences are celebrated rather than seen as barriers.

Ai Chachat’s Impact Across Industries

Enhancing Business Efficiency And Insights

In today’s fast-moving business world, staying ahead means being smart and quick. AI Chachat is really changing how companies work. It helps analyze lots of data, predict what customers might want, and give businesses a clearer picture of market trends. This means companies can adjust faster to what’s happening.

Think about all those repetitive tasks like scheduling meetings or sorting through records. AI Chachat can take over a lot of that. This frees up people to focus on more important, creative work. It’s not just about saving money; it’s about making businesses more flexible and responsive.

• Automating routine tasks to free up human resources.
• Providing deep insights from complex datasets.
• Predicting market shifts and consumer behavior.

This technology is built on a mix of AI and machine learning, which means it gets better and smarter over time. It helps make decisions faster and more accurately. Companies that are using tools like this are finding new ways to compete and do well.

The ability of AI Chachat to process and interpret vast amounts of information quickly allows businesses to move beyond guesswork and make data-driven decisions with greater confidence.

Revolutionizing Education And Research Access

AI Chachat is also making big waves in how we learn and discover new things. It can help make educational materials more accessible to everyone, no matter where they are or what language they speak. For students, it can act like a personal tutor, explaining difficult concepts in different ways until they click. Researchers can use it to sift through mountains of studies and data much faster than before, speeding up the pace of discovery. This kind of help is especially useful for complex fields like understanding 3D models of objects and spaces, a technique known as photogrammetry.

• Personalized learning experiences for students of all ages.
• Accelerating scientific research through rapid data analysis.
• Breaking down language barriers in academic resources.

Innovations In Entertainment And Gaming

Beyond work and study, AI Chachat is adding a new layer of fun and engagement to entertainment and gaming. In video games, it can create more realistic non-player characters (NPCs) that react to players in surprising ways, making the game world feel more alive. It can also help game developers by automating parts of the creation process, like generating dialogue or even basic game levels. In other forms of entertainment, AI Chachat can help create personalized content recommendations or even assist in writing scripts and stories, opening up new creative avenues.

The Future Of Human-Ai Collaboration

As AI systems like Chachat become more advanced, they are moving beyond being simple tools to becoming partners. This shift means we need to think about how humans and AI can work together effectively and build trust. It’s not just about what AI can do for us, but how we can grow alongside it.

Building Trust Through Empathetic Ai

For AI to be a true collaborator, it needs to understand and respond to human emotions. This doesn’t mean AI will

Navigating The Ethical Landscape Of Ai Chachat

Prioritizing Data Privacy and Security

As AI chat systems like Chachat become more integrated into our lives, the information they handle grows. This includes personal conversations, sensitive business data, and even private thoughts shared in confidence. It’s really important that this information is kept safe. Think about it like a diary; you wouldn’t want just anyone reading it. Companies developing and using AI chat need to put strong protections in place. This means using advanced encryption to scramble data so only authorized people can read it, and having strict rules about who can access what. Regular security checks are also a good idea, like a digital security guard making sure no one is trying to break in. The goal is to build systems that users can trust with their most private information.

Ensuring Responsible Ai Usage

AI chat tools are powerful, and with that power comes responsibility. We need to think about how these tools are used and make sure they’re used for good. This involves setting clear guidelines for both the developers and the users. For developers, it means designing AI that is fair, doesn’t spread misinformation, and respects human dignity. For users, it means using AI chat in ways that are honest and constructive. For example, using AI to help with homework is one thing, but submitting AI-generated work as your own is another. It’s about using AI as a tool to help us, not as a way to cheat or deceive.

Here are some key points for responsible AI use:

• Transparency: Be clear when you are interacting with an AI.
• Fairness: AI should not discriminate against any group of people.
• Accountability: There should be a way to address issues if the AI makes a mistake or causes harm.
• Beneficence: AI should be used to benefit society and improve lives.

Addressing Potential Misuse And Bias

AI chat systems can sometimes reflect the biases present in the data they were trained on. This can lead to unfair or discriminatory outputs, which is a serious problem. Imagine an AI that gives different advice based on someone’s background – that’s not right. Developers must actively work to identify and reduce these biases. This can involve carefully selecting training data and testing the AI rigorously to spot any unfair patterns. Furthermore, there’s always a risk that AI could be used for harmful purposes, like creating fake news or impersonating people. We must be vigilant and develop safeguards to prevent such misuse. It requires ongoing effort and a commitment to ethical development to make sure AI chat remains a positive force.

Looking Ahead: The Next Frontier For Ai Chachat

As we look towards the horizon, the capabilities of AI Chachat are set to expand in ways that will further reshape our interactions with technology and each other. The focus is shifting from simply understanding commands to truly grasping the nuances of human communication and context. This evolution promises more intuitive and helpful AI assistants.

Advancements In Contextual Understanding

One of the most significant areas of development is how AI Chachat understands context. Current models are good, but they can still miss subtle cues or forget previous parts of a conversation. The next generation of AI Chachat will be much better at remembering past interactions and understanding the broader situation. This means fewer repetitive questions and more natural, flowing conversations.

• Improved Memory Retention: AI Chachat will retain information from longer conversations, allowing for more coherent and personalized exchanges.
• Situational Awareness: AI will better interpret the user’s current environment or task to provide more relevant assistance.
• Emotional Nuance Detection: Future AI will be more adept at recognizing tone and sentiment, leading to more appropriate and empathetic responses.

The drive towards deeper contextual understanding is not just about making AI smarter; it’s about making it more useful and less frustrating for everyday people.

Seamless Integration With Emerging Technologies

AI Chachat is not developing in a vacuum. It’s becoming a core component that connects various technologies. Think about how your smart home devices could work together more intelligently, or how AI could help manage complex workflows across different software applications. The goal is to make these integrations feel effortless.

• IoT Connectivity: AI Chachat will act as a central hub, coordinating actions between smart devices in homes and workplaces.
• Cross-Platform Functionality: Expect AI to assist you across different apps and services without needing to switch contexts manually.
• Augmented Reality Integration: AI Chachat could provide real-time information and assistance overlaid onto your view of the world through AR devices.

The Evolving Role Of Human Expertise

With AI Chachat becoming more capable, some might wonder about the role of human skills. However, the trend points towards collaboration, not replacement. AI will handle routine tasks and provide data, freeing up humans to focus on creativity, critical thinking, and complex problem-solving. Human judgment and creativity will become even more valuable as AI handles the more predictable aspects of work and life.

Looking Ahead: The Evolving Role of AI in Conversation

As we wrap up our exploration of AI chatbots like ChatGPT, it’s clear we’re witnessing a significant shift in how we communicate and interact with technology. These tools are becoming more capable, understanding context better and offering more personalized responses than ever before. They’re not just for simple questions anymore; they’re helping businesses improve customer service, aiding in education, and even assisting with daily tasks. While the possibilities are exciting, it’s also important to remember that AI is a tool. It works best when we use it thoughtfully, combining its abilities with our own judgment. The journey of AI in conversation is still unfolding, and it promises to bring even more interesting developments as it continues to grow and integrate into our lives.

Frequently Asked Questions

What exactly is AI Chachat?

Think of AI Chachat as a super-smart computer program that’s really good at talking. It’s like having a conversation with a very knowledgeable friend who can understand what you’re saying and respond in a way that makes sense. It’s built using advanced technology that helps it learn and communicate like humans do.

How has AI Chachat changed how we talk to each other?

AI Chachat is making it easier for people to talk, even if they speak different languages. It’s also making customer service much better because it can understand and help people quickly and clearly. It’s like building bridges so everyone can understand each other more easily.

Can AI Chachat help in different kinds of jobs?

Yes, absolutely! AI Chachat can help businesses work faster and understand their customers better. It’s also helping students learn and researchers find information more easily. Even in games and entertainment, it’s making things more exciting and interactive.

Will AI Chachat start working with people more closely?

The idea is for AI Chachat to become a helpful partner. It’s learning to understand feelings and offer support, almost like a companion. The goal is to make it a natural part of our everyday lives, helping us with tasks and even offering comfort.

Is it safe to use AI Chachat with my personal information?

Companies that make AI Chachat are working hard to keep your information safe. However, it’s always a good idea to be careful about what personal details you share online. It’s best not to share very private information.

What’s next for AI Chachat?

AI Chachat is always getting smarter. Future versions will understand conversations even better, connect with other new technologies, and become even more helpful. While AI will do more, people’s unique skills and knowledge will still be very important.

The post Exploring the Future of Conversation with AI Chachat appeared first on IntelligentHQ.

Read more here: https://www.intelligenthq.com/ai-chachat/

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We have written about various types of rounded IPS displays in the past, like the Elecrow CrowPanel 1.28-inch and 2.1-inch rotary displays, the Waveshare ESP32-P4-WIFI6-Touch rounded touchscreen displays, and the MaTouch ESP32-S3 2.1-inch touch display, but this is the first time we have seen a rounded display with a (mini) HDMI port built into it. The 2.8-inch Round IPS Display from Elcrow is a compact circular 480×480 display housed in a CNC-machined aluminum shell. It features an IPS panel with wide viewing angles, an ST7701S driver, a mini HDMI video input, and a USB-C port for power. Thanks to its HDMI input, the display supports common operating systems such as Raspberry Pi OS, Ubuntu, Kali, and Windows, making it suitable for creative displays, industrial control interfaces, dashboards, and compact UI applications. Elecrow 2.8-inch round IPS display specifications: Display – 2.8-inch circular IPS panel Resolution – 480 × 480 pixels Driver IC – […]

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Read more here: https://www.cnx-software.com/2025/11/24/2-8-inch-round-ips-display-features-mini-hdmi-input-cnc-aluminum-housing/

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We’ve heard some questions and concerns following our recent Terms of Service and Privacy Policy updates. We are thankful our community cares enough to engage with us and we believe transparency and open dialogue are foundational to Arduino.

Let us be absolutely clear: we have been open-source long before it was fashionable.  We’re not going to change now. The Qualcomm acquisition doesn’t modify how user data is handled or how we apply our open-source principles. 

We periodically update our legal documents to reflect new features, evolving regulations, and best practices.

What remains the same

• Open Source and reverse-engineering. Any hardware, software or services (e.g. Arduino IDE, hardware schematics, tooling and libraries) released with Open Source licenses remain available as before. Restrictions on reverse-engineering apply specifically to our Software-as-a-Service cloud applications. Anything that was open, stays open.
• Ownership of your creations. The Terms of Service clarifies that the content you choose to publish on the Arduino platform remains yours, and can be used to enable features you’ve requested, such as cloud services and collaboration tools.
• Minors’ data and privacy. Our privacy disclosures have been strengthened, including enhanced protections for minors’ data. We’ve updated our data retention policies and age limits to provide age-appropriate services. We limit data retention for inactive users by automatically deactivating their accounts after 24 months of inactivity, in which case usernames would still be preserved in the Arduino Forum to address an explicit request from the Forum community to maintain attribution for user-generated content; where user requests account deletion, the username would be promptly removed and related posts would become anonymous.

Why we updated our terms: clarity and compliance

These latest changes are about clarity, compliance, and supporting the innovative environment you expect.

Here’s what the updates actually cover:

• Enhanced transparency around data practices: We’ve made our privacy disclosures more precise and more detailed, including what data we retain, to protect your privacy.
• New product capabilities and AI: As we introduce optional AI-powered features, such as those in the Arduino UNO Q and Arduino App Lab, we needed to update our terms to reflect these new capabilities and encourage their safe, responsible, and ethical use.
• More precise commercial terms: For users of our Premium Services, we’ve clarified billing mechanics, recurring payments, and refund rights to make purchasing and returns easier.
• Legal compliance: We’ve updated language to address US-specific privacy laws, export controls, and other regulatory requirements, while ensuring compliance with global standards.

Our 20-year commitment to open-source is unwavering

We are very proud of the Arduino community, and we would like to reaffirm our fundamental, non-negotiable commitment to the principles that founded Arduino.

Please read the full Terms of Service and Privacy Policy, to appreciate how they support the innovative, collaborative environment you’ve come to expect.

If you have specific questions or concerns, please consult our detailed Q&A in our FAQ section or reach out to us at privacy@arduino.cc.

We are Arduino.  We are open. We’re not going anywhere.

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The sharing economy began as a promise, fairer prices, empowered individuals, and community-driven services. But a decade later, platforms like Uber and Airbnb have shifted from grassroots disruptors to corporate powerhouses. What was meant to democratise access has been overtaken by big money, rising housing costs, and exploitative gig work. 

The sharing economy, once hailed as a revolution in how we live, work, and interact, has taken a turn in recent years that many didn’t quite see coming. Remember the early days of companies like Uber and Airbnb? There was this hopeful feeling in the air. These platforms were supposed to change the game, offering more affordable, flexible, and less corporate-driven alternatives to traditional services. 

They were going to democratise access to resources, whether that meant a ride to the airport or a place to stay. These companies were seen as part of a broader social movement that promised to reduce the stranglehold of big business and empower individuals. But somewhere along the way, things changed.

Today, companies like Uber and Airbnb no longer stand as beacons of a new, egalitarian economic model. Instead, they’re viewed by many as symbols of how the sharing economy has been overtaken by big money, with local services getting crushed under the weight of massive investments and corporate greed.

The original Vision of the Sharing Economy

It all seemed so promising. Uber would give us a way to bypass taxi monopolies, offering a cheaper, more flexible option to get around. Airbnb promised to do the same for accommodation, allowing homeowners to rent out their space to travellers, thereby cutting out the middleman and the corporate hotel chains. The idea was that these platforms would create a more informal, community-driven way of sharing resources, allowing people to monetise things they weren’t fully utilising—like their spare room or their car—and helping others access services more affordably.

And it wasn’t just about saving money. These platforms tapped into a growing desire for more control over our lives and how we spend our time and money. As Airbnb founder Brian Chesky put it in 2013, “We believe that people should be able to share the things they have, whether it’s a spare room, a car, or even a moment in time.” The idea was that anyone could join this global network of sharers and renters, creating a peer-to-peer system that could shift the balance of power away from large corporations.

The Shift: Big Money Takes Over

But today, that idealistic vision seems like a distant memory. What we’re left with is something far more corporate and commercial. The Guardian even pointed out that the lack of government oversight and social movement involvement led to “big money seizing the sharing economy.”

What started as a form of grassroots, community-driven sharing has become a playground for investors and corporations, eager to capitalise on the growing demand for these services. Companies like Uber and Airbnb, once the darlings of the startup world, are now well-funded global giants that operate like any other corporation—chasing profits and market share at all costs. The problem is that the original intent was for small, local businesses to thrive on these platforms, not be outbid and pushed aside by wealthy investors with deep pockets.

This situation is similar to the way that the welfare state was developed in the 20th century, especially in the UK. The state stepped in to protect services like healthcare and education, ensuring that they were shielded from the market forces that could have turned them into profit-driven enterprises. While the welfare state is certainly not without its flaws, it still maintains certain democratic and localised protections, which the sharing economy, by and large, never had.

Instead, the digital platforms that once promised fairness and equal opportunity have been swallowed up by corporate greed. The model that was meant to empower individuals to share their resources has been hijacked by big business, and local communities are feeling the effects.

The Airbnb Dilemma: Local Housing Crisis

Take Airbnb, for example. What was once seen as an affordable alternative to hotels, offering travellers the chance to stay in homes rather than sterile hotel rooms, has now become a platform where large investors buy up multiple properties, turning them into Airbnb rentals. In some cities, entire blocks or neighbourhoods are now filled with empty properties that are only ever rented out on a short-term basis, creating a strain on the local housing market. This leaves residents with fewer affordable rental options and drives up property prices—making it harder for locals to find a place to live. In many cases, the sharing economy has become a force that further exacerbates the very problems it once promised to solve.

While consumers may enjoy the convenience and affordability of using Airbnb, the long-term impact on local communities is becoming harder to ignore. Entire areas are being transformed into tourist zones, where residents are pushed out in favour of higher-paying visitors. This isn’t what the platform was initially designed to do. The model that allowed people to share their homes with others in a meaningful way has been warped into a business model that prioritises profit over people.

Uber and the Gig Economy: Exploiting Drivers

Similarly, Uber’s promise of cheaper, more flexible transportation has been overshadowed by criticism of its treatment of drivers. What was once sold as a peer-to-peer service, where anyone with a car could be a driver, has now become a gig economy job with little to no benefits. Uber drivers often work long hours to make a reasonable wage, but with no job security, no health benefits, and no traditional worker protections. The company’s business model relies on drivers being treated as independent contractors, rather than full employees, which has been a point of contention for years.

Looking further down the road, it’s not hard to imagine a future where Uber does away with drivers altogether, replacing them with self-driving cars. From a business perspective, this makes complete sense. But it’s hard to ignore the fact that it would further reduce the number of jobs available for people who rely on driving for a living. What started as a way for drivers to earn extra income by offering rides to passengers has evolved into a business model that strips workers of their rights, all while reaping the rewards of billions of dollars in valuation.

The Dark Side of the “Sharing” Economy

As we see with Airbnb and Uber, the promise of a more collaborative, sharing-driven economy has often been co-opted by big business in the pursuit of profit. Rather than empowering individuals and communities, these platforms have become mechanisms for large corporations to extract value from everyday people.

In fact, some of the most pressing issues we face today—rising housing costs, job insecurity, and the erosion of worker rights—can be directly linked to the way that platforms like Airbnb and Uber have evolved. What was once seen as a way to share resources more efficiently has instead created new forms of inequality and exploitation.

The Promise of Technology: Will It Repeat the Mistakes?

The rise of new technologies like blockchain, artificial intelligence (AI), and smart cities brings with it the same promises that the sharing economy once did. These innovations are being sold to us as solutions to some of society’s biggest challenges, from urban overcrowding to energy inefficiency. But without the proper protections in place, there’s a real risk that these technologies could end up in the hands of big business in much the same way the sharing economy did. We need to be wary of being swept up in the hype and make sure that these technologies are used for the greater good, not just to line the pockets of a few powerful players.

Protecting the Future: Learning from the Past

If we’ve learned anything from the rise of the sharing economy, it’s that unchecked capitalism can have harmful effects on our communities. Without the proper oversight and protections, the sharing economy has morphed into something very different from what we envisioned. The only way to prevent this from happening again is to make sure that new technologies and innovations are approached with caution and a commitment to ensuring that the benefits are shared equitably.

We need to ask ourselves some tough questions. Is our society becoming too commercialised? Are we allowing big business to take over platforms that were designed to serve the people? And, most importantly, what steps are we willing to take to protect the democratic values that we hold dear?

The early days of the sharing economy may have seemed like the beginning of something revolutionary. But unless we learn from the past, we may find ourselves falling into the same traps of exploitation and inequality that have plagued the corporate world for centuries. We must be careful not to get caught up in the fantasy that technology will solve all our problems, and instead ensure that it works for everyone, not just the wealthy few.

The post How The Sharing Economy Has Been Taken Over By Big Business appeared first on IntelligentHQ.

Read more here: https://www.intelligenthq.com/how-the-sharing-economy-has-been-taken-over-by-big-business/

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PegorK’s f32 might be the world’s smallest ESP32-C3 board. It measures just 9.85 x 8.45 mm, or slightly larger than the area covered by a USB Type-C connector. A board of this size will have limited features, and besides the ESP32-C3FH4 RISC-V WiFi and Bluetooth microcontroller, it comes with a USB-C port, a ceramic antenna, and a single GPIO pin connected to an LED. f32 specifications: SoC – Espressif Systems ESP32-C3FH4 Single-core 32-bit RISC-V microcontroller @ up to 160 MHz Memory – 400 KB SRAM Storage – 4MB flash Wireless 2.4 GHz Wi-Fi 4 & Bluetooth 5.0 USB – 1x USB Type-C port for power and programming Misc Tiny LED connected to GPIO10 Ceramic antenna Crystal Power Supply – 5V via USB-C port; 3.3V LDO Dimensions – 9.85 x 8.45 mm (the height must be around 4-5 mm) The PCB was designed using DipTrace and manufactured with a board thickness […]

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Read more here: https://www.cnx-software.com/2025/11/21/ridiculously-tiny-esp32-c3-board-features-usb-c-one-led-and-a-ceramic-antenna/

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Bowling is a fun sport, but many of us see the complicated machinery running behind the scenes as just as engrossing. How do all of the mysterious contraptions actually work to pick up and reset pins? Now you can find out for yourself and also enjoy bowling at home by backing Danny Lum’s Mini Tabletop Bowling machine on Kickstarter.

This campaign is for an entirely digital product: the 3D models, bill of materials, code, wiring diagrams, and instructions to build the Mini Tabletop Bowling lane. And it has been wildly successful, raising nearly $70,000 from over 750 backers so far.

It is easy to see why: this is a marvel of engineering. It does everything you’d see at a real bowling alley, just in miniature. It picks up and resets pins, it returns balls, it keeps score, and it even has optional bumpers for beginners. Aside from electronic components and some off-the-shelf materials, such as the wood lane and the fasteners, the entire six-foot-long machine is 3D-printable.

We don’t know much about the electronics under the hood (that information is part of the product being sold), but we do know that an Arduino handles the logic. Kickstarter backers will receive an Arduino sketch that is ready to flash onto the board — a sketch that they can tweak to modify the behavior and features.

This looks like a really fun project, so be sure to back the Kickstarter campaign before December 4th to get the best deal if you’re interested.

The post A tabletop bowling lane machine you can 3D print at home appeared first on Arduino Blog.

Read more here: https://blog.arduino.cc/2025/11/20/a-tabletop-bowling-lane-machine-you-can-3d-print-at-home/

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