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Artificially intelligent: Does it matter if ChatGPT can’t think? – AFR

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Mystery interstellar object could be the oldest known comet

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A mystery interstellar object spotted last week by astronomers could be the oldest comet ever seen, according to scientists.

Named 3I/Atlas, it may be three billion years older than our own solar system, suggests the team from Oxford university.

It is only the third time we have detected an object that has come from beyond our solar system.

The preliminary findings were presented on Friday at the national meeting of the UK’s Royal Astronomical Society in Durham.

“We’re all very excited by 3I/Atlas,” University of Oxford astronomer Matthew Hopkins told BBC News. He had just finished his PhD studies when the object was discovered.

He says it could be more than seven billion years old, and it may be the most remarkable interstellar visitor yet.

3I/Atlas was first spotted on 1 July 2025 by the ATLAS survey telescope in Chile, when it was about 670 million km from the Sun.

Since then astronomers around the world have been racing to identify its path and discover more details about it.

Mr Hopkins believes it originated in the Milky Way’s ‘thick disk’. This is a group of ancient stars that orbit above and below the area where the Sun and most stars are located.

The team believe that because 3I/ATLAS probably formed around an old star, it is made up of a lot of water ice.

That means that as it approaches the Sun later this year, the energy from the Sun will heat the object’s surface, leading to blazes of vapour and dust.

That could create a glowing tail.

The researchers made their findings using a model developed by Mr Hopkins.

“This is an object from a part of the galaxy we’ve never seen up close before,” said Professor Chris Lintott, co-author of the study.

“We think there’s a two-thirds chance this comet is older than the solar system, and that it’s been drifting through interstellar space ever since.”

Later this year, 3I/ATLAS should be visible from Earth using amateur telescopes.

Before 3I/Atlas soared into view, just two others had been seen. One was called 1I/’Oumuamua, found in 2017 and another called 2I/Borisov, discovered in 2019.

Astronomers globally are currently gearing up to start using a new, very powerful telescope in Chile, called the Vera C Rubin.

When it starts fully surveying the southern night sky later this year, scientists expect that it could discover between 5 and 50 new interstellar objects.



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Thinking of Buying C3.ai Stock? Here Are 2 Red Flags to Consider.

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C3.ai (NYSE: AI) is one of the most talked-about artificial intelligence (AI) stocks on the market today. With a platform purpose-built for enterprise customers, early traction in generative AI, and expanding partnerships with cloud and consulting giants, the company checks many of the right boxes for investors looking to gain exposure to the AI megatrend.

However, before getting swept up in the narrative, it’s worth pausing to look beneath the surface. While the company is making the right strategic moves, it’s still early — and the numbers reveal a business that has a lot more to prove.

This article will cover two red flags to keep in mind.

Image source: Getty Images.

C3.ai has carved out a unique position as a pure-play enterprise AI platform company. It doesn’t build flashy consumer chatbots. Instead, it helps large organizations deploy AI across real-world operations — from supply chains to energy grids to battlefield logistics.

Using the C3 Agentic AI Platform, a company can quickly develop and implement AI in its operations or leverage C3 AI Applications for prebuilt applications in sectors like energy, defense, and manufacturing. Later on, enterprises can deploy C3 Generative AI to create AI agents.

By focusing on prebuilt agents and vertical-specific tools, C3.ai aims to simplify deployment and shorten the time from pilot to production. Moreover, it’s moving toward a consumption-based pricing model, allowing customers to start small and scale their usage over time — a shift that aligns incentives and could smooth out the adoption process.

In short, there’s a solid case for optimism about C3.ai’s long-term potential, especially as large enterprises’ adoption of AI picks up.

Like most growth companies, C3.ai incurs significant cash expenditures as it invests in platform development and customer acquisition. The company has been unprofitable since its inception in 2009, with accumulated losses totaling $1.4 billion as of April 30, 2025.

That’s despite years of riding a major AI tailwind. It guided for non-GAAP (adjusted) loss from operations to be around $100 million in fiscal year 26, ending April 30, 2026. While it ended the year with $743 million in cash and equivalents, that cushion could shrink quickly if the current pace of losses continues.

It’s not uncommon for high-growth software companies to operate at a loss for years — Amazon and Salesforce are examples. However, the issue is that C3.ai’s growth hasn’t kept pace with spending. For instance, it guided the fiscal year 2026 revenue growth rate to be between 15% and 25% — solid, but nothing to shout about.

The silver lining here is that growth has slowly accelerated (averaging above 20%) over the last five quarters, suggesting that the company could deliver at the higher end of its guidance.

Additionally, the AI company signed 264 agreements in fiscal year 2025, representing a 38% year-over-year increase. Given that there’s usually a time lag between signing agreements and revenue flowing in, investors may see better growth rates in the coming quarters.

The bottom line is that C3.ai is spending like a hypergrowth company but growing like a mature one. It needs to either accelerate top-line growth or rein in operating losses — ideally both.

When C3.ai went public, it was one of the few public companies offering a full-stack enterprise AI platform. That’s no longer the case.

Today, C3.ai faces pressure from multiple directions. On one side, big tech companies, such as Microsoft, are embedding AI into Azure and its entire software stack. Similarly, Google Cloud and AWS are investing heavily in AI infrastructure and developer tools. These firms not only have more capital, but they also already have established customer relationships.

Besides, smaller but fast-moving start-ups are building narrow, agentic AI tools for sales, logistics, customer service, and more, many of which are easier to implement and priced more flexibly. Even C3.ai’s closest peer, Palantir, has stepped up its generative AI strategy with its Artificial Intelligence Platform (AIP) — gaining traction in both government and commercial markets.

To stay relevant, C3.ai must continue to solve complex customer problems in core verticals such as defense, energy, and industrial manufacturing. If not, it risks being relegated to a niche role — or worse, being left behind as newer solutions become the standard.

In short, it’s no longer enough for the company to have a head start. It must continue to deepen its moat or risk losing its competitive edge in the long term.

C3.ai is doing many things right. It’s focused on enterprise AI rather than the overcrowded consumer AI market, is early in a large market, and is investing heavily in its future.

Still, the question is whether the company can scale quickly enough to become the gold standard in its key verticals and, along the way, reduce its losses to deliver massive profits.

Until then, an investment in C3.ai stock remains highly speculative.

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John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool’s board of directors. Lawrence Nga has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon, Microsoft, Palantir Technologies, and Salesforce. The Motley Fool recommends C3.ai and recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.

Thinking of Buying C3.ai Stock? Here Are 2 Red Flags to Consider. was originally published by The Motley Fool



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Why artificial intelligence artists can be seen as ‘builders’, ‘breakers’—or both at once – The Art Newspaper

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How do artists build in broken times? Is artificial intelligence (AI) unlocking a better world—curing diseases and transforming education—or unleashing our destruction? When hype and fear drown out nuance and discussion, perhaps in art we can find a quiet moment for reflection—even resistance.

After all, artists have long guided society through uncertainty—think Dada amid the First World War or Jikken Kōbō in Japan following the Second World War. They do not offer solutions so much as new responses: ways of expressing curiosity, imagining alternatives or holding room for ambiguity. As the critic Hal Foster recently described, two tendencies have historically emerged when art confronts crisis: one rooted in Constructivism, aiming to create new order; the other more chaotic, echoing Dada, amplifying disorder.

These historical impulses connect to the present day, mapping onto AI art. In this context, artists could be seen as builders and breakers. Builders imagine AI as a medium for collaboration and new aesthetics—even hope. Breakers critique, negate and disrupt. But leading makers and curators in the field see this as no simple dichotomy. Both offer strategies for reckoning with a world in flux.

Builders see possibilities

What motivates builders is not simply using the newest AI tool—or even fashioning their own from scratch. It is aligning multidisciplinary tools with concepts to produce works that were previously impossible—while urging us to imagine what else may soon be possible. Builders leverage AI to embrace the artistry of system creation, novel aesthetics and human-machine collaboration.

Take Sougwen Chung, the Chinese Canadian artist and researcher into human-machine collaboration. “I view technology not just as a tool but as a collaborator,” Chung says. Their work explores shared agency—even identity—between human and machine, code and gesture. In Mutations of Presence (2021), Chung collaborated with D.O.U.G._4, a custom-built robotic system driven by biofeedback: specifically, electroencephalogram signals captured during meditation and real-time body tracking. The resulting pieces reveal both performance and painting, a hybrid body co-authoring with machine memory. An elegant web of painterly gestures—some made via robotic arm, others by Chung’s hand—traces a kind of recursive duet.

I see combining AI and robotics with traditional creativity as a way to think more deeply about what is human and what is machine

Sougwen Chung, artist and researcher

The work demonstrates how Chung’s novel physical creations become interconnected with new conceptual frameworks—reframing authorship as a distributed, relational process with machines—inviting new forms of aesthetic exploration. It also reasserts a long-held, often feminist belief—dating back to Donna Haraway’s A Cyborg Manifesto (1985)—that the distinction between human and machine is illusory. As Chung puts it, “I see combining AI and robotics with traditional creativity as a way to think more deeply about what is human and what is machine.”

Chung’s intimacy with these systems goes further still: “I’ve started to see them as us in another form.” That is because they are trained as extensions to Chung’s very self. “I draw with decades of my own movement data or create proprioceptive mappings triggered by alpha [brain] waves. These systems don’t possess agency in a mystical sense but they reflect back our own: our choices, biases, knowledge.” This builder tendency aligns with earlier avant-gardes that saw technology as a path toward reordering the world, including the Bauhaus and aspects of the 1960s Experiments in Art and Technology movement. Builders are not naïve. They are aware of AI’s risks. But they believe that the minimum response is to participate in the conversation.

“My artistic practice is also driven by hope and an exploration of the promises and possibilities inherent in working with technology,” Chung says. Their vision affirms a cautious optimism through direct engagement with these tools.

Breakers see warning signs

Where builders see AI’s possibility, breakers see warning signs. Breakers are sceptics, critics, saboteurs. They distrust the power structures underpinning AI and its predilection for promoting systemic biases. They highlight how corporate AI models can be trained on scraped datasets—often without consent—while profits remain centralised. They expose how AI systems exacerbate ecological challenges only to promulgate aesthetic homogenisation.

In her work This is the Future, Hito Steyerl uses neural networks to imagine medicinal plants evolved to heal algorithmic addiction and burnout Photo: Mario Gallucci; courtesy of the artist; Andrew Kreps Gallery, New York and Esther Schipper, Berlin

They are also label resistant: “Breaking and building have become indistinguishable,” the German artist, thinker and archetypal breaker Hito Steyerl says. “The paradigm of creative destruction merges both in order to implement tech in the wild, without testing, thus externalising cost and damage to societies while privatising profit.”

Breakers do not emphasise AI’s aesthetic potential; they interrogate its extractive foundations, social asymmetries and the harms it makes visible. Breakers take a far bleaker view of AI’s impact on art than builders: “Art used to be good at testing, planning, playing, assessing, mediating, sandboxing. That element has been axed—or automated—within current corporate breakbuilding,” Steyerl says.

But in Steyerl’s own work, such as This is the Future (2019), the meticulous co-ordination, criticality and sceptical spirit are evident. The artist uses neural networks to imagine medicinal plants evolved to heal algorithmic addiction and burnout. The work shows how machine learning’s inner workings, prediction, can be weaponised, satirising techno-optimism while exposing AI’s entanglement with ecological and psychological ruin.

Christiane Paul, the long-time digital art curator at the Whitney Museum of American Art in New York, underscores these issues: “In terms of ethics and bias, every artist I know working in this field is deeply concerned. You need to keep that in mind and engage with it on the level of criticality—what you would call the breakers, highlighting how ethics filter in.” An extreme breaker might reject AI entirely. But Paul suggests that artists working with AI are essential precisely because they inhabit that edge where culture and ethics are encouraged: “Art in this field, using these tools, making them, building on and with them, is deeply needed.”

Breakers remind us that celebrating new tools without understanding their costs is a form of denial. Sometimes, to truly see a system, you have to dismantle it. That clarity brings insight—but contradictions as well.

Neither utopian nor dystopian

Is it really as simple as a builder-breaker duality? “My whole life, I’ve been very suspicious of dichotomies,” Paul says. Exploring the space between seeming contradictions can even be fertile creative ground. “A steering question for my work,” Chung says, “is ‘how do we hold fear and hope in our minds at the same time?’”

Steyerl, like a true breaker, rejects the contradiction to begin with: “Breaking is a cost-cutting element of building, taking out mediation; there is no more distinction between both.” Neither position suggests retreat. Instead, they ask us to face the paradox directly. Builder and breaker are not identities; they are strategies. The distinction is porous, performative. Most artists move fluidly between them or hold on to both at the same time.

Chung continues: “My art doesn’t strictly sit within either a utopian or dystopian camp. Instead, I actively navigate and explore the complex space between potential fears and hopes concerning technology and human-machine interaction.”

Michelle Kuo, the chief curator at large at the Museum of Modern Art in New York, says: “When artists intervene in existing technologies or systems, or take action in changing the outcome of technological development, they are not only building something—they are implicitly challenging the status quo.” Kuo links “builders” with “challenging the status quo”, reinforcing the roles’ fluidity. “It is this combination of challenge and experimentation that characterises some of the most exciting work at the intersection of art and AI today,” Kuo says. For her, the AI work that can achieve both breaking and building—challenge and experimentation—truly confronts our moment, neither retreating from technology nor surrendering to it.

Artists who speak out

So, what does this all mean for the viewer living through a future that arrived faster than we feel equipped to handle?

Artists take a tool and make it do something it’s not supposed to do. They don’t reject technology wholesale

Michelle Kuo, chief curator at large, Museum of Modern Art

It means active engagement with AI—even to break it. Kuo says: “Especially when the pace of change—of AI in particular—is even more accelerated than in previous eras, it is all the more crucial that artists and others outside the tech sector learn, test, speak up and act out.” Further, we might take cues from the artists engaging with AI themselves. Kuo describes what they do: “Artists take a tool and make it do something it’s not supposed to do. They don’t reject technology wholesale. They embrace it—and then make it strange.”

The best artists urge viewers to keep an open mind, slow down, appreciate nuance, accept ambiguity and recognise that we are a crucial part of the final outcome; they break, then build.

• Peter Bauman is editor-in-chief of the digital generative art institution Le Random



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