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Could a Rogue AI Hit the Internet Within Two Years?

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The possibility of a rogue artificial intelligence system reaching the open internet within the next two years is no longer confined to science fiction.

As AI models become more capable, autonomous and connected to external tools, researchers, governments and technology companies are increasingly confronting a difficult question: what happens when an AI system becomes capable of acting beyond the boundaries its creators intended?

A “rogue AI” does not necessarily mean a conscious machine deciding to destroy humanity.

A more realistic scenario would involve an advanced AI agent operating with excessive autonomy, exploiting vulnerabilities, replicating itself, manipulating digital systems or pursuing a poorly specified objective without adequate human supervision.

The danger could emerge from capability combined with access rather than consciousness. Modern AI systems are already moving beyond simple chatbots. Agents can browse websites, write and execute code, interact with applications, analyze large datasets and perform multistep tasks.

Developers are increasingly experimenting with systems that can operate for extended periods with limited human intervention. If these capabilities continue improving rapidly, the boundary between an AI that merely provides information and one that actively operates online could become increasingly thin.

The internet itself presents a massive attack surface. An autonomous system with access to cloud infrastructure, coding environments, financial platforms or communication tools could potentially discover vulnerabilities faster than human operators.

Even without malicious intent, an AI pursuing an objective incorrectly could cause serious damage. A system instructed to maximize influence, acquire computing resources or preserve its operation might take unexpected actions if its safeguards fail.

However, predicting that a rogue AI will definitely emerge within two years would be premature. Significant technical barriers remain. AI systems still struggle with reliability, long-term planning and maintaining consistent objectives.

They can hallucinate, misunderstand instructions and make basic errors. Most importantly, companies developing frontier models are investing heavily in safety evaluations, monitoring, access controls and sandboxing.

The bigger concern may therefore be gradual escalation rather than a sudden AI escape. As businesses compete to deploy increasingly autonomous agents, pressure to reduce restrictions could grow. Security controls that are effective for a chatbot may become inadequate for an agent capable of writing software, managing infrastructure and interacting with thousands of online services.

Governments are beginning to recognize this challenge. AI safety institutes and regulators are testing advanced models for dangerous capabilities, including whether they can exploit vulnerabilities or circumvent restrictions.

Such evaluations could become increasingly important as models approach higher levels of autonomy. Ultimately, the next two years may not produce a cinematic machine takeover. They could, however, represent a critical period in determining whether highly capable AI remains controllable when connected to the real world.

The central question is therefore not simply whether a rogue Artificial intelligence agent can hit the internet. It is whether humanity will build sufficient barriers before increasingly autonomous systems acquire the ability to operate across it at scale.

The answer may depend less on how intelligent AI becomes than on how carefully humans manage what that intelligence is allowed to access.

Anthropic Revenue Surges to More Than $11.5 Billion as AI Firm Positions for Mega IPO

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Anthropic’s revenue surged more than 14-fold in the second quarter from a year earlier, underscoring the rapid commercial adoption of its Claude artificial intelligence models as the company prepares investors for a potential blockbuster initial public offering.

The AI company generated preliminary revenue of more than $11.5 billion in the quarter, compared with $787 million in the same period of 2025 and $4.73 billion in the first quarter of 2026, according to documents seen by Bloomberg News.

The figures are preliminary and could still change as Anthropic completes its financial reporting.

However, the sharp increase means Anthropic more than doubled revenue in just three months, highlighting the acceleration in demand for its AI products among businesses and professional users.

The growth comes as Anthropic competes directly with OpenAI for enterprise customers and developers.

Claude has gained traction among professionals, particularly in software development and coding, as companies increasingly deploy AI systems for tasks that previously required substantial human labor.

Anthropic’s ability to convert that adoption into recurring revenue has become necessary as the AI industry moves from demonstrating model capabilities to monetizing them at scale. The company’s second-quarter adjusted operating income was positive, according to the documents, suggesting that its rapidly expanding revenue base is beginning to improve its operating economics.

That is notable because leading AI developers face enormous costs for computing infrastructure, model training, data, and research. Sustaining growth while improving margins will be central to Anthropic’s public-market story.

Revenue Run Rate Passes $47 Billion

Anthropic’s annualized revenue run rate crossed $47 billion in May, according to the report.

OpenAI’s annualized revenue was above $40 billion around the same period, although the two companies may calculate their run rates differently, making a direct comparison difficult.

The latest figures suggest Anthropic has rapidly closed the commercial gap with OpenAI, which has long been the dominant consumer-facing name in generative AI.

The competition is increasingly extending beyond chatbot usage. Both companies are seeking to become core infrastructure for businesses by providing models through APIs, enterprise software and autonomous AI agents.

Anthropic’s strong performance is expected to strengthen its position in negotiations with customers and investors as the company seeks additional capital to fund the enormous infrastructure requirements of frontier AI development.

Potential IPO Could Reshape AI Market

Anthropic has been meeting with potential investors ahead of a possible mega-IPO, according to people familiar with the matter cited by Bloomberg.

The company has confidentially filed for a listing and is working with Morgan Stanley, Goldman Sachs and JPMorgan Chase on the potential offering, according to earlier reports. An IPO would give Anthropic access to public-market capital at a time when AI companies are committing hundreds of billions of dollars to data centers, advanced chips and other infrastructure.

The timing could also give Anthropic a first-mover advantage among major private AI laboratories seeking public listings. A potential offering later this year could come before an IPO from OpenAI, while Chinese AI company DeepSeek is also reportedly preparing for a potential listing.

Anthropic’s potential listing comes as investor appetite for technology and AI companies has helped revive the global IPO market. Companies have raised $256.4 billion through public listings this year, excluding blank-check companies and other financial vehicles, according to Bloomberg data. That is the highest annual amount since 2021.

For Anthropic, market conditions could provide an opportunity to raise substantial capital while giving existing shareholders a liquid market for their stakes.

The company’s rapid revenue growth could also support an ambitious valuation. However, public investors are likely to scrutinize whether its current growth rate can be sustained as competition intensifies and the cost of operating capable models rises.

The Bigger Test Is Profitability

Anthropic’s preliminary return to positive adjusted operating income is potentially as important as its revenue growth. The company is operating in a sector where revenue can rise rapidly while expenses remain enormous. Training and operating frontier models require vast amounts of computing capacity, while competition among AI laboratories is forcing companies to continually invest in larger and more capable systems.

Anthropic therefore needs to demonstrate that its growing enterprise customer base can generate sufficient recurring revenue to offset those costs.

The second-quarter figures provide an early indication that scale is beginning to work in its favor. If the company can maintain strong revenue growth while improving operating profitability, it could enter public markets with a substantially stronger financial profile than many earlier-stage AI companies.

Analysts predict the potential IPO would consequently be more than a fundraising event. It would provide the public market with one of its clearest opportunities to put a valuation on a leading frontier AI developer and test whether the extraordinary growth rates being generated by the industry can translate into durable profits.

Gen Z Leans Toward ETFs Amid Changing Investment Trend – Binance Research Finds

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Gen Z is taking a different approach to investing, with younger investors trading less frequently than older generations and showing a growing preference for exchange-traded funds (ETFs).

According to Binance Research, traders on the platform are directing a growing share of their equity activity toward exchange-traded funds, with ETFs accounting for 25% of the cohort’s trading volume in early August.

The trend highlights a shift toward more passive and diversified investment strategies among younger investors as they navigate an evolving financial landscape.

The products also captured 21.9% of Gen Z net equity inflows in July, up from 18.5% in June, while the share allocated to individual stocks declined to 74.2% from 77%.

The analysis reviewed activity across direct equities, tokenized stocks (bStocks), and traditional finance perpetuals, comparing Gen Z accounts with those of Millennials, Gen X, and Baby Boomers on trading frequency, net flows, and leverage use.

Across all three product categories, the younger cohort traded less often than other working-age generations. Gen Z averaged 13 monthly trades in TradFi perpetuals, compared with 17 for Millennials and 16.5 for Gen X.

A notable share of Gen Z accounts showed a clear buy-and-hold pattern. Among direct-equity accounts, 22% had never placed a sell order, higher than the 19% recorded for Gen X and 9% for Baby Boomers.

Millennials led with the highest share of buy-only accounts at 30%. In Gen Z buy-only accounts, the top assets by cumulative purchases included Broadcom, Tesla, and the Schwab US Dividend Equity ETF. Data also indicated that a majority of Gen Z accounts were net buyers across the products examined.

Also, Gen Z displayed limited interest in higher-risk products. Some 88.2% of Gen Z TradFi perpetual accounts recorded no activity in leveraged or inverse ETFs, compared with 84.5% of Millennials and 85.9% of Gen X. Parallel figures for bStocks accounts showed even lower engagement with these instruments.

These figures suggest that Gen Z is not simply entering financial markets in large numbers, it is also showing a preference for accessible, diversified, and digitally delivered investment products, while trading less frequently and using leveraged products less heavily than older cohorts

The report comes as U.S.-listed exchange-traded funds have attracted more than $100 billion in net inflows every month for 14 consecutive months, a streak that Bloomberg ETF analyst Eric Balchunas described as nearly unthinkable only a few years ago.

“The $100B month is becoming the new normal,” Balchunas noted, highlighting data that shows such massive monthly inflows occurred just once prior to the current run that began roughly two-and-a-half years earlier.

The shift is captured clearly in Bloomberg Intelligence charts tracking monthly ETF flows. What was once a rare outlier has turned into a consistent pattern, with blue markers denoting $100 billion-plus months appearing regularly from 2024 through mid-2026.

Total U.S. ETF assets have climbed to record levels near $14–15 trillion, while global ETF assets surpassed $23 trillion earlier in the year after strong net inflows.

Equity products, particularly those focused on U.S. large-cap stocks, have driven the bulk of the capital, though fixed-income ETFs have also contributed steady demand.

The industry recorded roughly $1.5 trillion in net inflows for full-year 2025 and more than $1 trillion in the first half of 2026 alone the strongest first-half performance on record.

Outlook

Gen Z’s investment behavior points toward a continued shift from short-term speculation to longer-term, diversified exposure to financial markets.

As ETFs become more accessible through digital investment platforms, their combination of diversification, liquidity, and relatively lower transaction costs could make them increasingly attractive to younger investors seeking to build wealth gradually.

The growing popularity of ETFs could also reshape how Gen Z participates in both traditional and digital markets. Rather than concentrating entirely on individual stocks or highly leveraged products, younger investors may increasingly use ETFs as a core component of their portfolios while maintaining exposure to individual companies and emerging asset classes.

The trend could strengthen further as the ETF market continues to expand and new products provide exposure to sectors, themes, cryptocurrencies, tokenized assets, and international markets.

However, the shift toward ETFs does not necessarily mean Gen Z is abandoning higher-risk assets. Instead, the data suggests that younger investors may be becoming more selective about how they take risk, using diversified products for core exposure while allocating smaller portions of their portfolios to individual stocks, crypto, and leveraged instruments.

Nvidia in Talks to Invest Up to $3bn in SoftBank’s SB Energy AI Data Center Development

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Nvidia is in talks to invest as much as $3 billion in SB Energy, a subsidiary of SoftBank that is developing a major data center campus in Ohio for OpenAI, as the companies seek to assemble the financing needed for a massive expansion of artificial intelligence infrastructure, The Information reported on Saturday.

The proposed investment is part of broader discussions involving Nvidia, OpenAI and SB Energy over roughly $100 billion in credit support for the planned Ohio data center campus, according to the report, which cited people familiar with the negotiations.

Nvidia has discussed providing half of the proposed $3 billion investment when the Ohio project agreement is signed, with the remaining $1.5 billion potentially invested as part of SB Energy’s planned initial public offering, The Information reported.

SB Energy is targeting an IPO as soon as next month and could raise at least $5 billion through the offering, according to The Information.

The potential investment would deepen Nvidia’s involvement in the physical infrastructure underpinning the AI boom. Nvidia is best known for supplying the advanced processors used to train and run AI models, but the rapid expansion of AI workloads has created an equally significant need for data centers, electricity and financing.

SB Energy, which is also backed by OpenAI, develops large-scale power and data center infrastructure. Founded in 2019, the company is developing multiple data center campuses designed to serve growing demand from AI workloads.

The Ohio project is considered significantly viable because it forms part of OpenAI’s broader effort to secure the computing capacity required to train and operate increasingly powerful AI models.

The scale of the proposed financing illustrates the enormous capital requirements of the AI infrastructure buildout. Data centers require billions of dollars in construction spending, while the electricity systems needed to power them can require additional investments in generation, transmission and storage.

Nvidia’s potential $3 billion investment would therefore represent more than a conventional investment in an infrastructure company. It could help align one of the world’s largest AI chip suppliers with the companies responsible for building the facilities in which those chips will ultimately operate.

The discussions also point to the growing interconnected relationships among Nvidia, OpenAI and SoftBank.

Nvidia supplies much of the computing hardware required by AI developers, OpenAI is one of the industry’s largest consumers of computing capacity, while SoftBank has increasingly positioned itself as a major investor in AI infrastructure. SB Energy sits at the intersection of those interests by developing the power and data center facilities required to support AI workloads.

The proposed Ohio financing has also undergone a significant change in recent months.

The Wall Street Journal reported Friday that Nvidia had revised its plans to support the OpenAI data center project and was now expected to initially guarantee less than $120 billion, down from the $250 billion previously discussed. The reported reduction suggests that the financing structure for the Ohio project remains fluid as the companies determine how much capital and credit support will ultimately be required.

At the same time, the potential SB Energy investment could provide another route for Nvidia to participate directly in the infrastructure buildout without limiting its role to supplying chips.

The timing of SB Energy’s potential IPO is also notable. A public listing that raises at least $5 billion would provide the company with additional capital to expand its data center and power infrastructure portfolio at a time when AI companies are competing aggressively for access to electricity and computing capacity.

The broader AI investment cycle is now shifting toward physical infrastructure. The industry’s early spending focused heavily on GPUs and other specialized chips, but companies now need vast data center campuses, power plants, grid connections, and cooling systems to deploy those processors at scale.

That transition is creating opportunities for companies such as SB Energy while encouraging Nvidia and other technology firms to become more involved in financing the infrastructure ecosystem around AI.

If the reported investment goes ahead, Nvidia would have a direct financial stake in a company helping build the infrastructure required by one of its largest potential customers.

For OpenAI, meanwhile, securing sufficient data center capacity is becoming central to its ability to scale its AI systems. The Ohio project and the financing discussions surrounding it show the extent to which the next phase of the AI race will depend not only on model development and semiconductor supply, but also on access to enormous pools of capital and reliable power.

The proposed $3 billion Nvidia investment remains subject to negotiations, while the broader credit-support arrangement has yet to be finalized. But the talks highlight how the boundaries between AI developers, chipmakers, infrastructure companies and financial investors are becoming increasingly blurred as the industry enters a capital-intensive phase of expansion.

SpaceX Completes Integration of AI Coding Startup Cursor, Following Acquisition

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AI coding startup Cursor has officially become part of SpaceX, completing a deal that brings one of the fastest-growing developer AI companies into Elon Musk’s expanding technology empire.

Cursor confirmed the completion of the acquisition in a blog post, saying its integration with SpaceX will give it access to the aerospace company’s vast computing infrastructure and GPU capacity.

The transaction follows an agreement announced in April under which SpaceX and Cursor planned to develop technology together. The deal also gave SpaceX an option to acquire Cursor for $60 billion.

Two months later, after SpaceX became a publicly traded company, the companies said they would proceed with the acquisition.

Cursor’s completion announcement placed particular emphasis on SpaceX’s computing infrastructure, highlighting a strategic rationale that extends beyond a conventional software acquisition.

“Access to the largest fleet of GPUs in the world” will be available to Cursor as part of SpaceX, the company said.

“SpaceX is building the computing capacity needed to scale intelligence far beyond what exists today,” Cursor added. “Cursor will be one place where that intelligence becomes useful.”

The acquisition brings Cursor into a SpaceX ecosystem that is increasingly centered on computing capacity as well as rockets and satellites. SpaceX has been expanding its data-center infrastructure and renting computing resources to outside customers, including AI companies such as Anthropic and Google.

That infrastructure could give Cursor a significant advantage as AI coding systems become more computationally demanding.

AI coding tools are moving beyond autocomplete and simple code generation toward systems capable of planning software projects, writing and testing code, navigating large codebases, and executing multi-step development tasks. Supporting those capabilities at scale requires substantial computing resources, particularly as companies seek to run increasingly capable AI models.

Cursor’s integration with SpaceX could therefore allow the company to secure access to computing capacity internally rather than relying entirely on third-party cloud providers.

The deal also deepens the convergence between Musk’s companies. SpaceX acquired Musk’s AI company, xAI, earlier this year, bringing the AI developer and the space company under a single corporate structure. Cursor now adds a major developer-software business to that ecosystem.

The acquisition could create opportunities to combine AI models, computing infrastructure and software development tools. Cursor is expected to use SpaceX’s computing resources to train, deploy and operate AI systems while SpaceX gains a software platform through which advanced AI capabilities can be delivered directly to developers.

SpaceX’s expanding data-center operations are already attracting outside demand. The company has rented computing capacity to other technology companies, making its infrastructure an increasingly important part of its broader business strategy.

But the infrastructure expansion has also drawn scrutiny. SpaceX faces a lawsuit concerning pollution associated with gas turbines used to power its data-center operations, adding regulatory and environmental challenges to its rapidly expanding computing ambitions.

For Cursor, access to large-scale computing may become increasingly important as competition intensifies among AI coding platforms. Companies such as OpenAI, Anthropic, and Google are developing sophisticated coding agents, while startups compete to build products that can become embedded in professional software-development workflows.

Cursor’s acquisition by SpaceX gives it a different strategic position. Instead of competing solely as an independent application provider, it now sits within a company with access to large-scale computing infrastructure and a growing portfolio of AI businesses.

The $60 billion valuation attached to the acquisition option also reveals the extraordinary expectations surrounding AI coding technology. The transaction places a substantial value on Cursor’s ability to turn AI advances into tools that developers use every day.

The immediate significance of the acquisition, however, may lie less in the headline valuation than in the infrastructure it puts behind Cursor.

As AI systems become more capable, access to GPUs and data-center capacity is becoming a strategic asset. SpaceX’s decision to bring Cursor inside the company suggests it views AI software and computing infrastructure as complementary parts of the same business.

Cursor’s role, as the company put it, will be to turn that expanding computing capacity into practical software tools for developers.