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AI Art Model Primo Showcases New Frontiers in Generative Art – Business Applications and Trends | AI News Detail

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Artificial Intelligence continues to revolutionize various industries, with AI-generated art emerging as a significant trend in the creative sector. One notable example is the recent showcase by PicLumen AI, which shared a stunning piece titled ‘Watching Earth from a Safe Distance’ on July 10, 2025, using their Primo model. This artwork, blending surreal imagery with cutting-edge technology, highlights the growing capabilities of AI in producing visually captivating content that resonates with audiences globally. According to PicLumen AI’s social media post, this piece exemplifies how AI art is not just a novelty but a transformative tool for artists and creators. The AI art community has seen exponential growth, with platforms like PicLumen leading the charge by providing accessible tools for generating high-quality digital art. This development is part of a broader trend where AI technologies, particularly generative models, are democratizing creativity, allowing individuals without traditional artistic skills to express themselves. The impact of such tools extends beyond individual creators to industries like advertising, gaming, and entertainment, where unique visual content is in constant demand. As of 2025, the global AI art market is projected to grow at a compound annual growth rate of over 35%, driven by advancements in generative adversarial networks (GANs) and diffusion models, as reported by industry analysts in recent studies.

From a business perspective, AI-generated art presents lucrative opportunities for monetization and market expansion. Companies like PicLumen are capitalizing on this trend by offering subscription-based models and licensing deals for AI-generated content, catering to businesses needing custom visuals for marketing campaigns or product designs. The direct impact on industries such as advertising is profound, as firms can now produce tailored artwork at a fraction of the cost and time compared to traditional methods. For instance, a 2024 report by a leading market research firm indicated that businesses adopting AI art tools reduced content creation costs by up to 40%. Market opportunities also lie in integrating AI art into non-fungible tokens (NFTs), where unique digital assets can be sold on blockchain platforms, creating new revenue streams for creators and companies alike. However, challenges remain, including intellectual property disputes and the need for robust platforms to ensure fair compensation for artists. PicLumen and similar players must navigate these issues to maintain trust and competitiveness in a rapidly evolving market. Key competitors include MidJourney and DALL-E, which also dominate the generative AI art space as of mid-2025, pushing innovation through frequent model updates and user-friendly interfaces.

On the technical side, the Primo model used by PicLumen likely leverages advanced diffusion techniques or GANs to create high-resolution, emotionally evocative images, as seen in their July 2025 artwork release. Implementation of such models requires significant computational resources, posing a barrier for smaller creators or businesses without access to cloud-based GPU services. Solutions like scalable AI platforms and partnerships with cloud providers can mitigate these challenges, making AI art tools more accessible. Looking to the future, the implications of AI art are vast, with potential applications in virtual reality and augmented reality spaces by 2027, as predicted by tech trend reports from early 2025. Regulatory considerations are also critical, as governments worldwide begin to draft policies on AI-generated content ownership and usage rights, with the European Union leading discussions as of mid-2025. Ethically, ensuring that AI does not replicate copyrighted works without permission remains a priority, and best practices include transparent attribution and user education. The competitive landscape will likely intensify, with ongoing innovation driving down costs and increasing quality, ultimately benefiting end-users. As AI art continues to evolve, businesses and creators must stay agile, adapting to both technological advancements and emerging legal frameworks to fully harness its potential.

In terms of industry impact, AI art tools like those from PicLumen are reshaping creative workflows, enabling faster prototyping in game design and film production. The business opportunities are evident, with companies able to license AI-generated art for branding or create exclusive digital collectibles. As this technology matures, its integration into everyday business operations will likely become seamless, further solidifying AI’s role in the creative economy by the end of the decade.

FAQ:
What are the main benefits of AI-generated art for businesses?
AI-generated art offers businesses significant cost savings, faster content creation, and access to unique visuals for marketing and branding. As of 2024, studies show cost reductions of up to 40% in content production.

How can creators monetize AI art effectively?
Creators can monetize AI art through NFT marketplaces, licensing agreements, and subscription platforms, tapping into the growing digital asset market as of 2025.

What challenges do companies face in adopting AI art tools?
Challenges include high computational costs, intellectual property concerns, and the need for regulatory compliance, which are critical issues as of mid-2025.



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‘Autofocus’ specs promise sharp vision, near or far

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Chris Baraniuk

Technology Reporter

IXI Niko Eiden, smiling and wearing IXI's autofocus specs.IXI

“People don’t want to look like cyborgs,” says Niko Eiden

They look like an ordinary pair of glasses – but these are tech-packed specs.

On a Zoom call, Niko Eiden, chief executive and co-founder of Finnish eyewear firm IXI, holds up the frames with lenses containing liquid crystals, meaning their vision-correcting properties can change on the fly.

This one pair could correct the vision of someone who normally uses totally different pairs of glasses for seeing near or far.

“These liquid crystals… we can rotate them with an electrical field,” explains Mr Eiden.

“It’s totally, freely tuneable.” The position of those crystals affects the passage of light through the lenses. A built-in eye-tracker allows the glasses to respond to whatever correction the wearer needs at a given moment.

However, tech-laden eyewear has a troubled history – take Google’s ill-fated “Glass” smart glasses.

Consumer acceptability is key, acknowledges Mr Eiden. Most people don’t want to look like cyborgs: “We need to make our products actually look like existing eyewear.”

IXI A pair of IXI glases. On one side you can see through to the electronicsIXI

IXI glasses have lenses that can be manipulated with an electric field

The market for eyewear tech is likely to grow.

Presbyopia, an age-related condition that makes it harder to focus on things close to you, is projected to become more common over time as the world’s population ages. And myopia, or short-sightedness, is also on the rise.

Spectacles have remained largely the same for decades. Bifocal lenses – in which a lens is split into two regions, usually for either near- or far-sightedness – require the wearer to direct their vision through the relevant region, depending on what they want to look at, in order to see clearly.

Varifocals do a similar job but the transitions are much smoother.

In contrast, auto-focus lenses promise to adjust part or all of the lens spontaneously, and even accommodate the wearer’s changing eyesight over time.

“The first lenses that we produced were horrible,” admits Mr Eiden, candidly.

Those early prototypes were “hazy”, he says, and with the lens quality noticeably poor at its edges.

But newer versions have proved promising in tests, says Mr Eiden. Participants in the company’s trials have been asked, for example, to read something on a page, then look at an object in the distance, to see whether the glasses respond smoothly to the transition.

Mr Eiden says that the eye tracking device within the spectacles cannot determine exactly what a wearer is looking at, though certain activities such as reading are in principle detectable because of the nature of eye movements associated with them.

Since such glasses respond so closely to the wearer’s eye behaviour, it’s important the frames fit well, says Emilia Helin, product director.

IXI’s frames are adjustable but not to a great degree, given the delicate electronics inside, she explains: “We have some flexibility but not full flexibility.” That’s why IXI hopes to ensure that the small range of frames it has designed would suit a wide variety of faces.

The small battery secreted inside IXI’s autofocus frames should last for two days, says Mr Eiden, adding that it’s possible to recharge the specs overnight while the wearer is asleep.

But he won’t be drawn on a launch date, which he intends to reveal later this year. As for cost, I ask whether £1,000 might be the sort of price tag he has in mind. He merely says, “I’m smiling when you say it but I won’t confirm.”

Getty Images A mother tries on glasses in a store with her young daughterGetty Images

Autofocus lenses could help people who struggle with varifocals or bifocals

Autofocus lenses could help people who struggle with varifocals or bifocals, says Paramdeep Bilkhu, clinical adviser at the College of Optometrists.

However, he adds, “There is insufficient evidence to state whether they perform as well as traditional options and whether they can be used for safety critical tasks such as driving.”

Chi-Ho To, an optometry researcher, at the Hong Kong Polytechnic University has a similar concern – what if the vision correction went wrong or was delayed slightly while he was, say, performing surgery on someone?

“But I think in terms of general use having something that allows autofocusing is a good idea,” he adds.

Mr Eiden notes that the first version of his company’s lenses will not alter the entire lens area. “One can always glance over the dynamic area,” he says. If wholly self-adjusting lenses emerge then safety will become “a much more serious business”, he adds.

In 2013, UK firm Adlens released glasses that allowed wearers to manually change the optical power of the lenses via a small dial on the frames. These lenses contained a fluid-filled membrane, which when compressed in response to dial adjustments would alter its curvature.

Adlens’ current chief executive Rob Stevens says the specs sold for $1,250 (£920) in the US and were “well received by consumers” but not so much by opticians, which he says “strangled sales”.

Since then, technology has moved on and the concept of lenses that refocus themselves automatically, without manual interventions, has emerged.

Like IXI and other companies, Adlens is working on glasses that do this. However, Mr Stevens declines to confirm a launch date.

Joshua Silver, an Oxford University physicist, founded Adlens but no longer works for the company.

He came up with the idea of fluid-filled adjustable lenses back in 1985 and developed glasses that could be tuned to the wearer’s needs and then permanently set to that prescription.

Such lenses have enabled roughly 100,000 people in 20 countries to access vision correcting technology. Prof Silver is currently seeking investment for a venture called Vision, which would further rollout these glasses.

As for more expensive, electronics-filled auto-focus specs, he questions whether they will have broad appeal: “Wouldn’t [people] just go and buy reading glasses, which would more or less do the same thing for them?”

Hong Kong Polytechnic University Prof Chi-Ho To holding up a lens.Hong Kong Polytechnic University

Prof Chi-Ho To has developed a lens which slows short-sightedness

Other specs tech is even slowing down the progression of eye conditions such as myopia, beyond just correcting for them.

Prof To has developed glasses lenses that have a honeycomb-like ring in them. Light passing through the centre of the ring, focused as normal, reaches the wearer’s retina and allows them to see clearly.

However, light passing through the ring itself is defocused slightly meaning that the peripheral retina gets a slightly blurred image.

This appears to slow improper eyeball growth in children, which Prof To says cuts the rate of short-sightedness progression by 60%. Glasses with this technology are now in use in more than 30 countries, he adds.

British firm SightGlass has a slightly different approach – glasses that gently reduce the contrast of someone’s vision to similarly affect eye growth and myopia progression.

While autofocus glasses and other high-tech solutions may have promise, Prof To has an even bigger goal: glasses that don’t just slow down myopia but actually reverse it slightly – a tantalising prospect that could improve the vision of potentially billions of people.

“There is growing evidence that you can do it,” teases Prof To.

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Does AI actually boost productivity? The evidence is murky

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There’s been much talk recently – especially among politicians – about productivity. And for good reason: Australia’s labour productivity growth sits at a 60-year low.

To address this, Prime Minister Anthony Albanese has convened a productivity round table next month. This will coincide with the release of an interim report from the Productivity Commission, which is looking at five pillars of reform. One of these is the role of data and digital technologies, including artificial intelligence (AI).

This will be music to the ears of the tech and business sectors, which have been enthusiastically promoting the productivity benefits of AI. In fact, the Business Council of Australia also said last month that AI is the single greatest opportunity in a generation to lift productivity.

But what do we really know about how AI impacts productivity?

What is productivity?

Put simply, productivity is how much output (goods and services) we can produce from a given amount of inputs (such as labour and raw materials). It matters because higher productivity typically translates to a higher standard of living. Productivity growth has accounted for 80% of Australia’s income growth over the past three decades.

Productivity can be thought of as individual, organisational or national.

Your individual productivity is how efficiently you manage your time and resources to complete tasks. How many emails can you respond to in an hour? How many products can you check for defects in a day?

Organisational productivity is how well an organisation achieves its goals. For example, in a research organisation, how many top-quality research papers are produced?

National productivity is the economic efficiency of a nation, often measured as gross domestic product per hour worked. It is effectively an aggregate of the other forms. But it’s notoriously difficult to track how changes in individual or organisational productivity translate into national GDP per hour worked.

AI and individual productivity

The nascent research examining the relationship between AI and individual productivity shows mixed results.

A 2025 real-world study of AI and productivity involved 776 experienced product professionals at US multinational company Procter & Gamble. The study showed that individuals randomly assigned to use AI performed as well as a team of two without. A similar study in 2023 with 750 consultants from Boston Consulting Group found tasks were 18% faster with generative AI.

A 2023 paper reported on an early generative AI system in a Fortune 500 software company used by 5,200 customer support agents. The system showed a 14% increase in the number of issues resolved per hour. For less experienced agents, productivity increased by 35%.

But AI doesn’t always increase individual productivity.

A survey of 2,500 professionals found generative AI actually increased workload for 77% of workers. Some 47% said they didn’t know how to unlock productivity benefits. The study points to barriers such as the need to verify and/or correct AI outputs, the need for AI upskilling, and unreasonable expectations about what AI can do.

A recent CSIRO study examined the daily use of Microsoft 365 Copilot by 300 employees of a government organisation. While the majority self-reported productivity benefits, a sizeable minority (30%) did not. Even those workers who reported productivity improvements expected greater productivity benefits than were delivered.

Prime Minister Anthony Albanese has convened a productivity round table in August.
Lukas Coch/AAP

AI and organisational productivity

It’s difficult, if not impossible, to attribute changes in an organisation’s productivity to the introduction of AI. Businesses are sensitive to many social and organisational factors, any one of which could be the reason for a change in productivity.

Nevertheless, the Organisation for Economic Co-operation and Development (OECD) has estimated the productivity benefits of traditional AI – that is, machine learning applied for an industry-specific task – to be zero to 11% at the organisational level.

A 2024 summary paper cites independent studies showing increases in organisational productivity from AI in Germany, Italy and Taiwan.

In contrast, a 2022 analysis of 300,000 US firms didn’t find a significant correlation between AI adoption and productivity, but did for other technologies such as robotics and cloud computing. Likely explanations are that AI hasn’t yet had an effect on many firms, or simply that it’s too hard to disentangle the impact of AI given it’s never applied in isolation.

AI productivity increases can also sometimes be masked by additional human labour needed to train or operate AI systems. Take Amazon’s Just Walk Out technology for shops.

Publicly launched in 2018, it was intended to reduce labour as customer purchases would be fully automated. But it reportedly relied on hiring around 1,000 workers in India for quality control. Amazon has labelled these reports “erroneous”.

More generally, think about the unknown number (but likely millions) of people paid to label data for AI models.

A shopfront on a city street.

Amazon’s Just Walk Out technology intended to reduce labour as customer purchases would be fully automated.
John G. Mabanglo/EPA

AI and national productivity

The picture at a national level is even murkier.

Clearly, AI hasn’t yet impacted national productivity. It can be argued that technology developments take time to affect national productivity, as companies need to figure out how to use the technology and put the necessary infrastructure and skills in place.

However, this is not guaranteed. For example, while there is consensus that the internet led to productivity improvements, the effects of mobile phones and social media are more contested, and their impacts are more apparent in some industries (such as entertainment) than others.

Productivity isn’t just doing things faster

The common narrative around AI and productivity is that AI automates mundane tasks, making us faster at doing things and giving us more time for creative pursuits. This, however, is a naive view of how work happens.

Just because you can deal with your inbox more quickly doesn’t mean you’ll spend your afternoon on the beach. The more emails you fire off, the more you’ll receive back, and the never-ending cycle continues.

Faster isn’t always better. Sometimes, we need to slow down to be more productive. That’s when great ideas happen.

Imagine a world in which AI isn’t simply about speeding up tasks but proactively slows us down, to give us space to be more innovative, and more productive. That’s the real untapped opportunity with AI.



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‘I can’t drink the water’

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Michelle Fleury & Nathalie Jimenez

North America business correspondent & Business reporter

Watch: Beverley Morris flushes her toilet using a bucket because of low water pressure

When Beverly Morris retired in 2016, she thought she had found her dream home – a peaceful stretch of rural Georgia, surrounded by trees and quiet.

Today, it’s anything but.

Just 400 yards (366m) from her front porch in Mansfield, Georgia, sits a large, windowless building filled with servers, cables, and blinking lights.

It’s a data centre – one of many popping up across small-town America, and around the globe, to power everything from online banking to artificial intelligence tools like ChatGPT.

“I can’t live in my home with half of my home functioning and no water,” Ms Morris says. “I can’t drink the water.”

She believes the construction of the centre, which is owned by Meta (the parent company of Facebook), disrupted her private well, causing an excessive build-up of sediment. Ms Morris now hauls water in buckets to flush her toilet.

She says she had to fix the plumbing in her kitchen to restore water pressure. But the water that comes of the tap still has residue in it.

“I’m afraid to drink the water, but I still cook with it, and brush my teeth with it,” says Morris. “Am I worried about it? Yes.”

Meta, however, says the two aren’t connected.

In a statement to the BBC, Meta said that “being a good neighbour is a priority”.

The company commissioned an independent groundwater study to investigate Morris’s concerns. According to the report, its data centre operation did “not adversely affect groundwater conditions in the area”.

While Meta disputes that it has caused the problems with Ms Morris’ water, there’s no doubt, in her estimation, that the company has worn out its welcome as her neighbour.

“This was my perfect spot,” she says. “But it isn’t anymore.”

A data centre in Georgia being built in a forest clearing with the flat land going off into the distance

Huge data centres are being built across the state of Georgia

We tend to think of the cloud as something invisible – floating above us in the digital ether. But the reality is very physical.

The cloud lives in over 10,000 data centres around the world, most of them located in the US, followed by the UK and Germany.

With AI now driving a surge in online activity, that number is growing fast. And with them, more complaints from nearby residents.

The US boom is being challenged by a rise in local activism – with $64bn (£47bn) in projects delayed or blocked nationwide, according to a report from pressure group Data Center Watch.

And the concerns aren’t just about construction. It’s also about water usage. Keeping those servers cool requires a lot of water.

“These are very hot processors,” Mark Mills of the National Center for Energy Analytics testified before Congress back in April. “It takes a lot of water to cool them down.”

Many centres use evaporative cooling systems, where water absorbs heat and evaporates – similar to how sweat wicks away heat from our bodies. On hot days, a single facility can use millions of gallons.

One study estimates that AI-driven data centres could consume 1.7 trillion gallons of water globally by 2027.

Few places illustrate this tension more clearly than Georgia – one of the fastest-growing data centre markets in the US.

Its humid climate provides a natural and more cost-effective source of water for cooling data centres, making it attractive to developers. But that abundance may come at a cost.

Gordon Rogers is the executive director of Flint Riverkeeper, a non-profit advocacy group that monitors the health of Georgia’s Flint River. He takes us to a creek downhill from a new construction site for a data centre being built by US firm Quality Technology Services (QTS).

George Dietz, a local volunteer, scoops up a sample of the water into a clear plastic bag. It’s cloudy and brown.

“It shouldn’t be that colour,” he says. To him, this suggests sediment runoff – and possibly flocculants. These are chemicals used in construction to bind soil and prevent erosion, but if they escape into the water system, they can create sludge.

QTS says its data centres meet high environmental standards and bring millions in local tax revenue.

While construction is often carried out by third-party contractors, local residents are the ones left to deal with the consequences.

“They shouldn’t be doing it,” Mr Rogers says. “A larger wealthier property owner does not have more property rights than a smaller, less wealthy property owner.”

Tech giants say they are aware of the issues and are taking action.

“Our goal is that by 2030, we’ll be putting more water back into the watersheds and communities where we’re operating data centres, than we’re taking out,” says Will Hewes, global water stewardship lead at Amazon Web Services (AWS), which runs more data centres than any other company globally.

He says AWS is investing in projects like leak repairs, rainwater harvesting, and using treated wastewater for cooling. In Virginia, the company is working with farmers to reduce nutrient pollution in Chesapeake Bay, the largest estuary in the US.

In South Africa and India – where AWS doesn’t use water for cooling – the company is still investing in water access and quality initiatives.

In the Americas, Mr Hewes says, water is only used on about 10% of the hottest days each year.

Still, the numbers add up. A single AI query – for example, a request to ChatGPT – can use about as much water as a small bottle you’d buy from the corner shop. Multiply that by billions of queries a day, and the scale becomes clear.

Gordon Rogers showing a water sample to the BBC's Michelle Fleury

Gordon Rogers takes regular water samples to monitor the health of Georgia’s Flint River

Prof Rajiv Garg teaches cloud computing at Emory University in Atlanta. He says these data centres aren’t going away – if anything, they’re becoming the backbone of modern life.

“There’s no turning back,” Prof Garg says.

But there is a path forward. The key, he argues, is long-term thinking: smarter cooling systems, rainwater harvesting, and more efficient infrastructure.

In the short term, data centres will create “a huge strain”, he admits. But the industry is starting to shift toward sustainability.

And yet, that’s little consolation to homeowners like Beverly Morris – stuck between yesterday’s dream and tomorrow’s infrastructure.

Data centres have become more than just an industry trend – they’re now part of national policy. President Donald Trump recently vowed to build the largest AI infrastructure project in history, calling it “a future powered by American data”.

Back in Georgia, the sun beats down through thick humidity – a reminder of why the state is so attractive to data centre developers.

For locals, the future of tech is already here. And it’s loud, thirsty, and sometimes hard to live next to.

As AI grows, the challenge is clear: how to power tomorrow’s digital world without draining the most basic resource of all – water.

Correction: This article originally said that Beverly Morris lives in Fayette County, Georgia, and has been amended to explain that she lives in Mansfield, Georgia.

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