Tech

Is AI-generated art really art? Here’s what the history says.

Published

3 hours ago

3 June 2026

As AI continues to encroach on every aspect of our lives, there is a persistent fear or hope, depending on your angle: AI will someday take over art. The internet is full of quizzes showing that most lay people cannot tell the difference between AI-generated art (digital pictures of paintings, prose) and the real thing. Multiple studies have shown that when people are shown AI-generated art and human-made art, but are not told which is which, they tend to prefer the AI-generated art, whether it be images, poetry, or prose.

Yet what’s striking is that despite this disparity, people still consistently say that human-made art is what they want.

In one study published in 2023, participants were shown a series of images, each randomly labeled “AI-made” or “human-made.” Participants rated the images they thought were machine made as worse than the images they thought had been created by a human artist — even when those were actually human-made.

A natural experiment in how difficult it can be for people to tell the difference between AI-generated art and human-made art occurred last month, when the prestigious Commonwealth Foundation awarded its short story prize to “The Serpent in the Grove,” which a bears some of the hallmarks of AI-generated prose. In a statement to New York magazine, the Commonwealth Foundation said that the prize committee does not use AI checkers, but that “all shortlisted writers have personally stated that no AI was used.”

The big “tell” for “Serpent in the Grove” was that it is riddled with metaphors that are rhythmic and evocative at first glance but fall apart when you try to figure out what they mean: “The girl smiled like sunrise over a sink”; “She had the kind of walking that made benches become men.” If art is about connecting with another human mind, we might say that “Serpent” fails if, when you read it, you find it almost impossible to tell what the mind behind that story is trying to say.

One conclusion you might draw here is that the widespread disdain for AI-generated art is empty snobbery. If human-made art were so much better, the argument goes, then people would be able to see a real difference.

This line of thinking relies on the belief that “good” art is something that many people find appealing, at least in a vacuum. At this point, AI has automated that generation fairly successfully. At some point, it may get even better at it.

But I don’t think those study participants were lying when they said they wanted human-made art, even if they couldn’t tell the difference. Even if we get to a future in which AI’s persistent glitches are ironed out, so that there are no more missing fingers and garbled sentences, and AI-generated images and music and poetry and prose and film are completely indistinguishable from the best a human can produce, even to highly trained experts — even then, I think people would still keep saying they would rather experience art made by humans. And even in such a world, I don’t think they would be lying.

The pleasure of art is specifically related to the human mind on the other side of the product. When we’re told that the mind on the other side is a machine, many of us don’t want to engage anymore.

That loss of interest matters. It is consistent. It has happened before in the history of art.

Two hundred years ago, another new technology emerged that was capable of automating the technical skills many people at the time would have considered one of art’s fundamental functions: the camera. It could capture a likeness perfectly and very quickly, in a moment when almost all of visual arts were organized around capturing a likeness.

The camera changed the way paintings were produced and ultimately valued, but it did not replace the medium entirely — and the reasons why can help explain why AI-generated art won’t replace human-made art, either.

“Art’s most mortal enemy”

Three soldiers stand before a red-robed man who is holding their swords, stretching out their arms towards him in a ritual oath. Behind them, three women swoon over two children.

Looking at the 1785 painting “The Oath of the Horatii” by Jacques-Louis David can feel like watching a movie.

Wikimedia Commons

In 19th-century Europe, one of the major ways people decided whether a painting was good was by asking the question, “How closely does this match what I can see with my eyes?” It was important for painters to be able to create something that we would now describe as photorealistic.

What people wanted from art at the time, says Richard Meyer, a professor of art history and director of American studies at Stanford University, was what people expect from a good Hollywood movie now: “You suspend your disbelief that you’re looking at a flat surface with pigment built up on it, and you fall into the fiction of, here are these beautiful bodies before you, or here is this landscape, or here’s this bowl of fruit.”

An artist’s skill was in large part defined by how faithfully they were able to recreate reality. Many artists were able to make a living painting relatively affordable portraits, which allowed people who weren’t aristocrats or nobility to commission a permanent record of their appearance, says Anju Lukose-Scott, a curator and master’s student at the University of Chicago.

As inventors began to develop early versions of photography in the middle of the 19th century, it started to seem like artists might become redundant. A camera can create an exact record of the way the world looks far faster and more easily than any painter can, no matter how skilled they are with their brush. The new technology, French poet Charles Baudelaire wrote darkly in 1859, was “art’s most mortal enemy.” By the 20th century, as it became possible to reproduce an old masterpiece on a postcard, philosopher Walter Benjamin feared that original works of art had lost their unique aura.

The immediate implications for a large class of skilled craftspeople were catastrophic. “Portraiture was a huge commercial business,” Lukose-Scott says. The camera made such work nearly obsolete. Some artists went out of business; others pivoted to making daguerreotypes for their clients instead of paintings.

But the effect on painting as a fine art form was different, Meyer says. Painters began to focus on what they could accomplish with their brushes that a camera could not. Instead of trying to capture reality, they began to use colors and textures to convey emotions.

Artists in the new impressionist movement would deliberately show their brushstrokes in their paintings, making the texture of the paint and canvas part of the artistic effect they were developing. Since photography was still a black-and-white medium, the impressionists made vivid colors more and more central to their work. They moved away from trying to duplicate the shapes and lines that cameras could record so well, and instead began to explore the way unnatural shapes and lines could provoke a visceral response from a viewer.

To the modern eye, it’s these discrepancies between paintings and reality that make these impressionist paintings so exciting and pleasurable to look at. They show us a way of perceiving the world that photography cannot.

An oil painting depicts a red sun rising over a blue-gray sea. In the foreground, two fishing boats make their way over the water. Ships loom in the background.

Claude Monet’s 1872 painting “Impressionism, Sunrise,” with its expressive brushstrokes and impossible physics, gave the impressionists their name.

Wikimedia Commons

As painting evolved, photography took over where trade portraiture left off: It was considered a craft, not an art. When people began to take photography seriously as its own medium in the 20th century, it wasn’t because of photography’s exceptional ability to capture a likeness, Meyer says. The ability to do that could now be taken for granted. Instead, the art of photography was about the choices made by the human using the camera: what to shoot, how to frame the subject, how to light it, how to edit it.

Today, almost all of us carry cameras around in our pockets. But most of us would not describe the quick, functional photographs we take with our smartphones as art, no matter how accurately they capture the world around us. People can and do make art with their phones, but doing so requires a human mind working with intention and craft behind the machine of the camera.

We no longer consider the ability to create a perfect replica of reality to be the main prerequisite to making a piece of visual art. Technology has made it easy enough to do that the skill has lost value. People still care about visual art, but we use different criteria to evaluate it than we did in 1800.

AI’s arrival may very well devalue the ability to create smoothly readable text and pleasant visual compositions, and that could mean bad things for a lot of industries, including journalism. But that doesn’t mean we’ll stop caring about whether or not a human being made a piece of art.

“Art offers us a way of looking”

I keep thinking about something Meyer told me about what happened to the 19th-century portrait painters who lost their jobs to daguerreotypists. Meyer argues that there was something about the nature of middle-class portraiture that made people willing to cede it to cameras, in a way that they didn’t feel happy to do with the types of paintings that live on in museums.

In portraiture, Meyer says, “you’re going not so much for the individual expressive perspective of the artist but for a likeness. It’s really about oneself, the person portrayed, rather than the person portraying.” In contrast, Meyer says, fine art is about the artist, and the way that the artist sees the world.

It’s worth spending a bit of time on the distinction Meyer is drawing. One thing that people who love playing with AI sometimes say is that the pleasure of prompting comes from watching a stray thought become concrete in the blink of an eye: It is a piece of your mind made external, so that you can look at it. An AI prompt is about the person prompting, in much the same way that the average hired portrait was about the person being painted.

If I consider an image or a piece of text to be a reflection of myself, I might not mind using soulless technology to create it — it’s already interesting to me, because it’s about me and for me. But when an image or a piece of text is about something else, I feel differently. I want to connect with another person, not something mechanical.

That seems to be the thing that most humans crave from art: an encounter with another human mind. Someone expresses how it feels to be alive in a human body, with a human soul, and another one sees it, reads it, hears it, and grasps at it. That is the experience that moves us.

“It’s about wanting to understand how an individual sees the world differently from how we can see it on our own,” Meyer says. “Art offers us a way of looking.”

So when we think about whether AI-generated content has the potential to be art, to replace art, the question that matters is not whether it can create entertaining or realistic images and text out of nothing. The question is whether the machine allows us to experience the way a different person lives in the world.

For Lukose-Scott, the possibility is unlikely, because today’s LLMs are trained on a corpus of existing art. ”What’s retained in the invention of photography is a kind of artistic identity. People are using the technology through their own artistic voice, which from my perspective is lacking in AI,” Lukose-Scott says. “My perception of AI art is that it’s just a self-gratifying loop, because it’s taking from what we already know, and it’s putting it back in the world.”

When a person uses ChatGPT to spit out a Studio Gibliflied replication of their family snapshots, they are not showing us a new form of subjectivity. They are mimicking the subjectivity of Hayao Miyazaki, without bringing Miyazaki’s intention or skill to bear on the finished product — and they’re able to do so because OpenAI trained its model on Miyazaki’s work without his permission. Unlike the camera, AI is built on a foundation of what is arguably intellectual theft.

This is not to say that it would be impossible for an artist to use AI as a tool to produce new artistic ideas, just as it is not impossible for an artist to use an iPhone camera as a tool to make art. But it would look different from slapping a prompt into Midjourney, for the same reason that most people’s iPhone selfies are not very artistically interesting: Because they are about and for you, not about sharing your embodied experience with the world.

The context matters enormously. The context is what tells me that when I reach out to art with my human mind — my human soul — another mind is on the other side, reaching back.

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Microsoft Plans Linux Tools, RTX Spark Desktop For Windows Devs

Published

6 minutes ago

3 June 2026

NewsAdmin

An anonymous reader quotes a report from Ars Technica: Microsoft’s Build developer conference kicked off today, and as with almost everything the company has done in the last few years, Microsoft’s opening keynote focused overwhelmingly on AI and other closely related technologies. […] On the hardware front, we didn’t get any updates for existing Surface devices (not counting yesterday’s Surface Laptop Ultra announcement), but we did get something new: the Surface RTX Spark Dev Box is “a compact developer PC” built around Nvidia’s new RTX Spark chip with up to 128GB of built-in memory. The Dev Box looks a little like a cartoon anvil or piano fell onto an Xbox Series X and flattened it. Its aluminum casing was designed “to double as a heatsink,” and its preloaded version of Windows 11 Pro will include a “purposeful” set of developer-centric default settings and preinstalled tools.

This is a follow-up of sorts to the Windows Dev Kit 2023, also known as “Project Volterra.” This Qualcomm Snapdragon 8cx Gen 3-powered PC was essentially the system board from a Surface Pro tablet stuffed into a plastic box, and it was introduced alongside Arm-native versions of several Microsoft developer tools. It helped to set the stage for the Arm-based flagship Surface devices that launched the next year, which benefitted from a better and faster x86-to-Arm code translation technology called Prism and a greater number of Arm-native third-party apps that didn’t need to be translated in the first place. Microsoft didn’t announce pricing or specific specs for the RTX Spark Dev Box, but you can probably expect it to cost quite a bit more than the $600 that Project Volterra did. Hopefully, Microsoft can keep the price at least somewhat lower than the $4,699 asking price for Nvidia’s similarly specced DGX Spark box.

On the software side, several developer-centric changes are coming to Windows 11, particularly for users of the Windows Subsystem for Linux (WSL). Microsoft is introducing a Windows-native version of the coreutils command line tools, so that commands or scripts made for Linux work within Windows and the other way around; the ability to run WSL inside of containers, said to be arriving in “the coming months”; and something called Windows Developer Configurations that uses the WinGet tool to quickly set up “a distraction-free dev environment with VS Code, GitHub Copilot, WSL, PowerShell 7 and developer-optimized settings with one command on any Windows 11 device.” Microsoft also introduced Microsoft Execution Containers (MXC), as “enterprise-grade sandboxed environments” that let AI agents like OpenClaw operate on Windows without getting unrestricted access to the whole system. In theory, MXC could let organizations enforce agent-specific limits, such as blocking access to personal accounts, separating work and personal data, or requiring permission before deleting files.

The MXC GitHub repo also notes support for “multiple containment backends,” meaning the same sandboxing concept could apply beyond AI agents to other plugins, tools, and workloads.

Further reading: Microsoft Unveils Scout, an Autonomous AI Agent Built On OpenClaw

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Best Resume Builders for Designers, Developers, and Digital Creators in 2026

Published

20 minutes ago

3 June 2026

NewsAdmin

For certain professions, like designers, developers, and digital creators, the portfolio-first idea keeps coming back. As the argument goes, if your work speaks for itself, why would you ever need a resume? However, anyone who has recently applied for a contract or full-time role knows the reality of the situation.

Hiring still very much happens through structured filters, applicant tracking systems (ATS), and busy recruiters. Yes, you need a decent portfolio to be memorable but having a compelling resume is what gets you screened in.

Here’s the good news: resume builders in 2026 have caught up. The best ones are AI-integrated, ATS-intelligent, and allow you to balance personal branding with structured information.

If you’re a freelancer, a designer, a developer, or a digital creator, then using one of these resume builders is the perfect way to compliment your personal website.

What makes a resume builder worth using in 2026

You need to understand that the category for this type of software has evolved. A few years ago, most resume builders were nothing more than template libraries. The bar is much higher now.

Ideally, a resume builder that’s worth your time and money has these four major facets:

AI that understands resumes, not just text. General AI tools rewrite bullets without knowing what a recruiter is actually looking for. Tools trained on resume best practices focus on the specifics, like action verbs, quantified results, and missing keywords from the job description.
ATS intelligence without hacks. The ideal resume builder employs clear layouts and logical keyword placement, ensuring that your resume is easily readable by both machine algorithms and people.
Real-time feedback. The builders that offer you real value can tell you exactly which bullet is vague, which section is light, and what you need to fix.
Design that compliments a portfolio. For designers and developers, a resume that looks like it was made in the previous decade contradicts the work it’s attached to. Layout, typography, and visual hierarchy still matter.

Now let’s go over the tools that meet most of the criteria.

Side-by-side resume builder comparison

Tool	Best for	AI features	ATS-friendly	Free plan
Enhancv	Best overall for personal branding	ATS intelligence, AI content tailoring, real-time feedback	Yes	Limited
Canva	Full creative control	Basic AI writing	Mixed	Generous
Novoresume	Structured, polished layouts	Content suggestions	Yes	Limited
Resume.io	Speed and simplicity	Pre-written bullets	Yes	No
Kickresume	AI-assisted writing	GPT-based generator	Yes	Limited
FlowCV	Minimalist resumes	Light AI assistance	Yes	Generous

Now let’s take a closer look at each tool.

Enhancv: best overall resume builder for personal branding

Enhancv is the strongest all-rounder resume builder. It’s the most consistent pick for developers and digital creators who want their resume to do more than list jobs. It combines AI assistance with real-time feedback. That’s what separates it from tools that only generate text.

You can use the AI resume tailoring feature to analyze a job description and adjust your resume to match it. It will rework your keywords, skills, accomplishments, and phrasing. The Resume Checker runs 27 distinct checks across content, layout, formatting, and style, and explains the why behind every recommendation. The content checker is trained on hiring patterns, rewording weak bullets into active, quantified ones.

The template library is ATS-tested. And the drag-and-drop editor gives high degrees of customization. For digital creators who want personality and recruiter-readiness in one document, Enhancv’s resume templates are the safest default.

However, Enhancv isn’t a design tool. Despite the high levels of personalization you can achieve with it, you’d need a dedicated design tool for complete visual control. This brings us to the next best option.

Canva: best for full creative control

Canva gives you a lot of freedom to make your design look the way you want it to. Drag, drop, recolor, add an icon, swap a font. The flexibility is genuine, and for portfolio-related positions where the resume serves as a design example, Canva is effective.

But the trade-off is also real. ATS parsability on heavily designed Canva documents can be a hit or miss. Multi-column layouts, embedded graphics, and non-standard visuals can confuse older parsers.

Canva’s AI writing tools have advanced, yet they still seem more general-purpose compared to the specialized ones designed for resumes. The optimal approach is to utilize Canva when the focus is on the design itself. Nonetheless, combine it with a simpler version for the ATS systems.

Novoresume: best for structured, polished layouts

Novoresume leans more into clean, structured layouts. The sections of the resume are clearly defined, the spacing is uniform, and the final product appears refined immediately. This is an excellent option for those who desire their resume to appear traditional and professional without investing much time in making adjustments.

AI assistance is lesser here than at Enhancv. It provides you with content ideas, but the feedback loop is much narrower. The main idea is that Novoresume is perfect for those who have their content ready and just need help with the design.

Resume.io: best for speed and simplicity

Resume.io optimizes for the quickest path between a blank page and finished ATS-ready PDF. The interface is straightforward, the prompts are simple to comprehend, and the suggested pre-written bullet points help you with the most tedious aspect of resume writing.

However, what this tool lacks is depth. Customization is limited, design variation is modest, and the AI is limited to filling in blanks rather than diagnosing what’s weak. Still, if you need a resume real quick, then Resume.io will suffice.

Kickresume: best for AI-assisted resume writing

As a product, Kickresume bets heavily on AI-generated content. It can create a complete initial draft from a job title and some prompts. This is useful if you’re unable to get beyond looking at an empty document. The template library is robust, and ATS compatibility is typically effective.

But keep in mind that drafts generated by AI still require editing and personal contributions. Kickresume produces a polished output, but recruiters can easily identify a generic application from afar. Utilize it to start, then rephrase the bullet points in your unique style.Your portfolio and your resume should look like they were made by the person so make sure your resume sounds like you and shows your character.

FlowCV: best minimalist resume builder

FlowCV is known for minimal, ATS-friendly resumes. There’s little friction and the free plan is unusually generous. The interface is calm, and the output is pretty much what you’d expect for a developer who wants a straightforward document.

The AI features are light, design options are intentionally narrow to minimize choice fatigue, and the tool assumes you know exactly what to say in your document. If you’re a developer or a freelance engineer, and you prefer a visually quiet resume, then FlowCV is a reliable option.

Resume builder vs. personal website: what should you use?

As we established, the two formats serve different parts of the same job search.

When a resume builder is enough

Modern resume builders cover what most hiring pipelines actually require:

Applying through traditional channels (job boards, company career pages, recruiter inboxes).
structured document that an ATS can read in under a second.
The role values consistency and credentials over visual differentiation.

Corporate design teams, in-house developer roles, and full-time positions routed through HR usually expect a resume. A polished personal site you have to ask the recruiter to bookmark won’t suffice.

When you should build a personal website instead

A personal website is the better investment when the work is the pitch:

You’re a freelancer, contractor, or creator selling services directly.
Your portfolio needs to breathe (case studies, process write-ups, video, interactive demos).
You want clients finding you via search, not just applying through a job board.
You care about branding (domain, design system, voice, all within your control).

For independent designers and developers, a well-put WordPress website is often the difference between getting referrals and chasing them.

The hybrid approach (recommended)

For most digital creators, it’s best to have both.

Use a resume builder that suits you for your applications. When a recruiter asks for a PDF, you’ll have one ready.

Meanwhile, use your WordPress site for presence and credibility. That’s the long tail of work that wins trust before the interview. Besides, you can link to your site from your resume header.

Final thoughts

The portfolio-first mindset is partially correct. Portfolios continue to serve as evidence. The thing is, recruiters usually look at your resume first to decide if they want to consider you for a job. Portfolios are evidence of your work and skills and resumes help recruiters screen people from a sea of candidates.

In 2026, the top resume creators connect the two. They offer AI that comprehends recruitment, feedback that enhances the resume, and formats that succeed in ATS.

If you choose to invest in just one tool, Enhancv is the safest overall choice. It is particularly effective for developers and creators seeking to establish personal branding while ensuring recruiter appeal in one document.

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China’s DeepSeek close to $7.4bn raise at up to $59bn valuation

Published

34 minutes ago

3 June 2026

NewsAdmin

The company is expected to complete the round in the next couple of weeks.

Chinese AI leader DeepSeek is close to finalising a $7.4bn funding round led by Tencent and Contemporary Amperex (CATL), with participation from the $8bn state-backed National Artificial Intelligence Industry Investment Fund, multiple publications have reported.

The round is expected to value the GenAI darling between $52bn and $59bn, sources added, placing it leagues ahead of rival Moonshot, which raised $2bn last month at a valuation of $20bn.

External participants are expected to invest around $4.4bn, with Tencent pitching in $1.5bn and battery giant CATL around $735m, while company founder Liang Wenfeng has personally invested around $2.94bn, reports suggested.

Alibaba was also reported to be taking part in this round, while Tencent was reported to have proposed taking a 20pc stake in the company, which is expected to complete the round in the next couple of weeks.

DeepSeek’s latest funding round comes as AI contemporaries across the world are raising capital to compete in the fast-advancing race for enterprise adoption.

Claude parent Anthropic announced that it filed to go public earlier this week, with reports estimating the company’s valuation could soar above $1trn. The AI leader raised $65bn at a $965bn valuation in its last private round.

OpenAI, recently valued at $852bn, is also planning to go public. CNBC reported that the company was preparing to confidentially file for an IPO late last month.

DeepSeek’s popularity surged last year after the company launched its model R1, whose cost effectiveness and performance sent Silicon Valley leaders into uproar, igniting accusations of theft. R1 was trained using lower-capacity Nvidia chips.

The company took more than a year after R1 to release its long-awaited V4 large language model, which, it claimed at the time, “redefine[d] the state-of-the-art for open models”. V4 was hyped to be the company’s most important launch since R1, and V3 in late 2024.

Other AI rivals in China made a flurry of launches ahead of V4 to avoid competition, including Alibaba with Qwen3.5; ByteDance’s Seedance 2.0; Zhipu’s GLM-5, trained entirely using Chinese chips; MiniMax, which released M2.5; and the Alibaba-backed Moonshot AI, which came out with Kimi K2.5.

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AI changing jobs faster than companies can keep up with, finds report

Published

49 minutes ago

3 June 2026

NewsAdmin

The BCG report found that many organisations are struggling to turn AI into a resource that shows genuine company-wide value.

New research from Boston Consulting Group (BCG), has found that for some organisations, artificial intelligence is fundamentally reshaping the nature of work, leadership and how employees experience the workplace. However, whether the change is positive or negative is up for debate.

To collect data for BCG’s fourth annual AI at Work report, the organisation gathered information from 11,749 globally dispersed employees across 14 markets in a broad range of industries. What was discovered is that 72pc of respondents believe AI has already considerably changed skills expectations in their roles. Almost half report spending more time managing and directing AI than doing the work itself.

More than two-thirds of people who regularly use AI say it has improved their job satisfaction. However, four out of every 10 contributors to the research find that it has increased cognitive load, creating a ‘joy paradox’ where AI is making work better and harder at the same time.

Despite widespread usage, many companies are finding that they are not necessarily converting supposed AI-driven efficiency gains into something that is of measurable value.

For example, while 42pc of regular frontline users report saving at least a full workday through AI per week, 66pc also reported that they get limited or no guidance on what to do with that time. More than half don’t redirect it into strategic work, meaning any time saved leaks out of the organisation.

“The first wave of AI focused on individual productivity. The coming wave will need to transform collective work,” said Vinciane Beauchene, a managing director and partner at BCG, who is also a co-author of the report.

“Everyone is talking about AI replacing work, but it is in fact really about rethinking the human value-add inside. This is the role of leaders. Our survey reveals a true managerial revolution in the age of AI. 65pc of managers and leaders now believe agents will take over at least half of their job in the next three years and frontline workers see their jobs evolving towards more managing and directing AI.”

Strategic clarity

Since last year’s report, more than double the number of respondents said that AI agents are already integrated into workflows, however, there are clear issues around clarity and efficacy. 61pc of contributors agreed that agents could do at least half their job within three years, yet more than half (52pc) still have a limited understanding of what agents are and governance still lags far behind the technology.

The report finds that strategic clarity emerges from the survey as “the most crucial differentiator in sustaining AI’s impact over time as organisations are moving past simply implementing AI tools in use-case deployment initiatives”. This has resulted in what the report authors called the ‘reshape/invent dividend’, which “leads to more value captured and a better employee experience”.

Sylvain Duranton, another co-author and the global leader of BCG X said: “The joy equation rewrites itself within a year of using AI. Early on, AI’s novelty and cognitive stretch fuel enjoyment, but that ‘AI honeymoon’ fades without strategic clarity.

“Employees don’t push back on AI intensity, they thrive when the strategy is clear, the direction is real and the message reaches them. Business value and employee enjoyment aren’t trade-offs. The organisations capturing the greatest business value are the same ones where employees enjoy work the most.”

In mid-May, International Data Corporation (IDC), in partnership with Dell Technologies, published a global study exploring how European governments and public sector organisations are approaching sovereign and agentic AI and what it will take to deploy the technology at scale.

What was discovered is that leaders in Europe’s public sector are showing strong drive in accelerating modernisation through agentic AI, although they also face a critical gap in the skills that are needed to operate advanced technologies. This is creating a significant divide between ambition and operational capacity, according to the report.

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Meta Workers Can Opt Out of Workplace Tracking for Up to 30 Minutes

Published

1 hour ago

3 June 2026

NewsAdmin

Meta is scaling back parts of its employee tracking initiative after staff objected to software that collected mouse movements, clicks, keystrokes, and other actions for AI training data. According to Reuters, the company will now let workers pause collection for up to 30 minutes and request exemptions. Reuters reports: [Stephane Kasriel, a vice president in Meta’s AI model-building Superintelligence Labs unit] said the team behind the software had also introduced “several optimizations” to reduce its impact on computer battery life, after employees complained it was consuming so much data it was causing their home internet usage to spike. “While we remain confident in the privacy protections we put in place at launch, which went through several layers of risk review, we have heard your concerns about personal data on work devices, battery life, and wanting more control over when capturing happens,” Kasriel said in the memo.

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Linux Fu: Fake Webcams, GUI Edition

Published

1 hour ago

3 June 2026

NewsAdmin

Previously, I looked at using the Linux video loopback system from the command line. The basic trick was simple enough: capture video from a real camera, process it with something like ffmpeg, and write the result to a fake camera device via the v4l2loopback device. Then a browser, or any camera-enabled software, sees the fake camera as if it were real. This allows you to manipulate video before sending it to the rest of the world.

That works, and for those of us who like command lines, it’s easy enough to execute. But not everyone loves the command line. In the comments, there was another obvious answer: use OBS Studio.

While OBS is excellent, it is also a bit like using a laser to chop a carrot. If you already use OBS, fine. If you only want to crop a webcam, add an effect, mirror an image, or feed a virtual camera, it can feel like a lot. If you must have a GUI, you can try Webcamoid, which sits somewhere between a simple webcam viewer and a full video production system.

Webcamoid gives you a GUI for selecting a camera, applying effects, and sending the result to a virtual camera. Conceptually, it is much closer to the command-line loopback setup from the previous post than to OBS. You are still building a pipeline from input camera to output camera, but now you can do much of it with buttons and menus instead of shell commands.

That’s in theory, of course. Implementing Webcamoid turned out to be quite the exercise. Granted, this probably varies depending on where you install software. If your distro has a clean working copy of Webcamoid and its dependencies, good for you. For everyone else, keep reading.

The Moving Parts

There are two pieces to understand. Webcamoid is the GUI application. It captures video, previews it, applies effects, and can write to a virtual camera. You also need a driver to produce the fake or virtual camera. AkVCam is one of the virtual camera drivers that Webcamoid can use on Linux. It can also use v4l2loopback, as we discussed last time. Both approaches create fake /dev/videoX devices, but their configuration models are different.

With v4l2loopback, the typical setup is command-line oriented:

sudo modprobe v4l2loopback video_nr=10 card_label="Virtual Camera" exclusive_caps=1

Then some program writes frames to /dev/video10. For example, ffmpeg can read from a real webcam and write to the virtual one. Of course, if you want a permanent virtual camera, you can make an entry in /etc/modprobe.d.

AkVCam is more structured. Instead of simply creating a generic loopback device, it uses a configuration file that defines one or more virtual cameras, their input/output relationship, and the formats they support. That sounds like more work, and in a way it is. But it also gives you tighter control over what formats the virtual camera advertises. This sometimes matters more than you might expect.

Install, Remove, Install…

The hard part of Linux webcam work is often not getting video — it’s getting every piece of the chain to agree on width, height, frame rate, and pixel format, along with matching each other’s API expectations.

I tried three different ways to install Webcamoid. First, I used the normal OpenSUSE Tumbleweed repos to install the program. It couldn’t find any cameras. My next stop was a Flatpak version. That worked well, but it is deliberately crippled and won’t even try to drive a virtual camera, directing you to install the regular version instead. Then I tried an AppImage. This seemed to work OK, but the virtual camera would never display anything but a black screen.

Note that the version on AppImageHub is old, and the source project requires payment for prebuilt binaries. I didn’t try either of those options.

I tried a lot of things to make it work. My final answer was to use the AppImage, but I had to build my own version of AkvCam from GitHub.

Even then, at first, the video output was highly pixelated. The culprit was AkVCam using the 640×480 RGB format. Upscaling created a blocky mess.

You can see what a device is doing with:

v4l2-ctl -d /dev/video3 --all

In my case, the virtual output reported:

Width/Height : 640/480
Pixel Format : 'RGB3'
scaling_mode : Fast
aspect_ratio_mode : Ignore

That explains it. “Fast” scaling usually means “not pretty,” and 640×480 is not a great starting point for modern video calls.

The fix was to simplify the AkVCam configuration. Instead of giving the virtual camera a long list of supported formats, I configured it with essentially one useful format. For example, if the pipeline is meant to be 1280×720 at 30 fps, make that the format. Do not give every program in the chain an opportunity to negotiate itself down to postage-stamp resolution.

A minimal AkVCam setup generally defines a capture device, an output device, a connection between them, and formats. In the generated config I was using, the output camera had several formats:

cameras\2\type=output
cameras\2\videonr=3
cameras\2\formats=19, 20, 21, 22, 23, 24

The problem was that format 19 was 640×480. The high-resolution formats were present, but not preferred. Reordering the list might help, but for reliability, using only the desired format is even better.

Webcamoid As A GUI Pipeline

Once the virtual camera driver is sane, Webcamoid works well. You select the real camera as the source, apply whatever effects you want, and select the AkVCam virtual camera as the output. The receiving application then sees the virtual camera.

Compared to the command-line approach, Webcamoid makes experimentation easier. Want to flip the image, adjust color, crop, blur, or test silly filters? That is all much easier in a GUI than in an ffmpeg or gstreamer filter chain, although I still don’t mind the command line. There’s not much difference between using Webcamoid as a friendly front end or manipulating the image as we did last time.

However, I would not oversell it. Webcamoid is not OBS. It is not really a scene compositor. If you want multiple live sources — say, a screen capture as the main image and your webcam as picture-in-picture — OBS is the obvious GUI tool. With the command line, you can easily do things like this by calling ffmpeg directly.

That’s a Wrap!

If you want a full production environment, OBS is still the right answer. It handles scenes, multiple sources, transitions, screen capture, overlays, and virtual camera output in a single application. But if you liked the command-line loopback idea and wished it had a friendlier face, Webcamoid plus AkVCam is worth a look. It gives you a GUI for the common case: one camera in, effects applied, one virtual camera out. You just need to fight through the installation and configuration with your specific setup. Hopefully, yours will be easier than mine.

As usual, Linux rewards knowing what is happening under the hood. Webcamoid can make the workflow friendlier, but v4l2-ctl is still your friend, and, at least for some people, you’ll need some Linux Fu to get it all working in harmony.

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Is gaming better value than movies? New study shows US gamers think it’s a better use of their cash

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2 hours ago

3 June 2026

NewsAdmin

A new Entertainment Software Association study found that most Americans think video games provide the most entertainment value for their money compared to other forms of entertainment
75% of parents are actively play video games each week, while 81% enjoy playing with their children
The majority of players across all age groups are also spending money on in-game content

A new Entertainment Software Association (ESA) study has found that the majority of gamers in the United States prefer to spend their money on video games because they think they provide more entertainment value than other forms of media.

As detailed in its annual Essential Facts About the U.S. Video Game Industry report conducted in partnership with YouGov, video games are more popular than ever among most age groups.

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Daily Deal: LabsDigest | Techdirt

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2 hours ago

3 June 2026

NewsAdmin

from the good-deals-on-cool-stuff dept

LabsDigest is built for those who learn best by doing. Whether you’re preparing for a CompTIA certification or diving into Python development, our platform offers interactive labs that simulate real-world tasks—no passive watching or reading, just real experience. Work through performance-based exercises for CompTIA A+, Network+, Security+, and more, or sharpen your coding skills with hands-on Python projects. Learn by solving problems, fixing bugs, and applying your knowledge in practical scenarios that prepare you for the real world. It’s on sale for $30.

Note: The Techdirt Deals Store is powered and curated by StackSocial. A portion of all sales from Techdirt Deals helps support Techdirt. The products featured do not reflect endorsements by our editorial team.

Filed Under: daily deal

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Lovable makes Google Cloud a primary partner to win over corporate buyers

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2 hours ago

3 June 2026

NewsAdmin

The Swedish app-builder, processing a million new projects a week, is making Google Cloud a primary partner, with Gemini models and a security layer aimed at corporate buyers.

The pitch behind Lovable has always been that anyone can build software by chatting with an AI. The harder pitch, the one that turns a viral tool into a durable business, is that a large company can trust what gets built.

On 3 June, at Google Cloud’s Nordics summit in Stockholm, Lovable set out to make that second case, announcing an expanded multi-year collaboration with Google Cloud aimed squarely at enterprise buyers.

The deal makes Google Cloud one of Lovable’s primary technology partners, anchoring its platform on Google’s AI infrastructure and Gemini models. Lovable says its users are now processing more than one million new projects every week, a volume that has outgrown the scrappy infrastructure a consumer tool can run on and needs the secure, enterprise-grade backing a hyperscaler provides.

Lovable is one of the more remarkable growth stories in recent software. Founded in Sweden and built around what the industry has taken to calling “vibe coding,” turning natural-language prompts into full-stack applications, it raised a $200M Series A in mid-2025 at a $1.8bn valuation and was reported to be valued at around $6.6bn by the end of the year. The company says builders created more than 25 million projects in its first year, and that Lovable-built applications now draw 600 million visits a month.

The collaboration is built on three pillars, and they read as a checklist of what enterprises demand before they let an AI tool near production. The first is a verified agent: Lovable has launched its Lovable Agent in Google Cloud’s Gemini Enterprise Agent Gallery, a vetted catalogue of third-party agents that corporate customers can adopt with some assurance about what they are running.

The second is security, reinforced by a new integration with Wiz, the cloud-security company Google is acquiring, to identify and remediate vulnerabilities in AI-generated code in real time, alongside continuous scanning, dependency checks, permissioning and audit trails.

The third pillar is the least glamorous and arguably the most telling: simplified procurement and billing through Google Cloud Marketplace and Gemini Enterprise.

Enterprises buy software through approved channels with predictable invoicing, and being available where a corporate buyer already has a billing relationship removes a quiet but real barrier to adoption. The pillar exists because procurement, not capability, is often what stalls enterprise deals.

The security emphasis is the substantive part of the announcement, because it speaks to the central anxiety about AI-generated code. Tools that let non-engineers ship applications also let them ship vulnerabilities they cannot see, and for a regulated enterprise that risk is disqualifying.

Wrapping Lovable’s output in continuous scanning and remediation is the company conceding that “anyone can build” needs “and it will be checked” attached before a serious buyer signs on.

There is a competitive subtext worth noting. Lovable sits in a crowded vibe-coding field alongside Cursor, Replit and Bolt, and the AI model providers themselves are building rival app-creation tools.

Tying tightly to Google Cloud, and to Gemini, gives Lovable a hyperscaler’s distribution and infrastructure at a moment when its rivals are racing for the same enterprise budgets. It also slots into Google’s broader campaign to win the “agentic enterprise,” the same push behind its $750M partner fund for agentic AI.

As a Google Cloud announcement, the framing is naturally Google’s, and the deeper commercial terms, what each side pays and commits, are not disclosed. What the partnership establishes is direction.

Lovable has decided its next phase runs through the enterprise, and that getting there means less talk of how easy building is and more proof that what gets built is secure, governed and accountable. The million projects a week are the easy part. Convincing a Fortune 500 compliance team is the part this deal is for.

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Hydraulic Drive For Your Lawn Tractor

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2 hours ago

3 June 2026

NewsAdmin

Most larger ride-around landscaping machinery has a similar transmission, a transaxle containing a gearbox, or in some cases, a continuously variable drive. [Made In Garage] has a Toro lawn tractor with just such a setup, and when the transaxle failed he replaced it with a hydraulic drive.

The video below is a classic bit of workshop porn, as he fabricates both the hubs and the rear frame to fit a pair of hydraulic motors. The throttle pedal is a hydraulic valve with the lever swapped for a pedal, and the hydraulic reservoir, in a nice touch, is an old fire extinguisher.

We’re not so sure about the pipework in such an exposed position under the machine as we think it would inevitably be damaged, but you can’t argue with the results. Having used a rough service mower with a hydraulic drive in the past, we appreciate always being exactly at the right ratio for the engine.

We think perhaps he should complement it with a loader.