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Claude New Update Takes Direct Control of Your Computer via Cowork and Claude Code Tools 

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Anthropic just rolled out a major update that lets Claude take direct control of your computer via its Cowork and Claude Code tools.

Claude can now: Take screenshots of your screen. Move the mouse cursor, click, drag, and interact with any UI element. Type on the keyboard and use shortcuts. Navigate and control desktop apps, browsers, files, and workflows — essentially acting like a human user sitting at your machine.

It starts by preferring connected apps and integrations like Slack, Calendar, Google Workspace. When those aren’t enough, it asks for permission to directly control the screen and perform actions. This builds on Anthropic’s earlier “computer use” API tool launched in 2024 for developers, but the new version integrates it more deeply into consumer-facing products like Cowork (for general knowledge work) and Claude Code (for development tasks).

It pairs especially well with Dispatch, allowing you to assign tasks from your phone and let Claude handle them on your desktop even when you’re away. Right now: Available to Claude Pro and Max subscribers on macOS via the Claude Desktop app. Windows support is coming soon.

It’s explicitly labeled as an early research preview — expect bugs, rate limits, and the need for user supervision. Safety features include permission prompts before actions, one-click pause, and scanning for prompt injection risks. Anthropic still recommends reviewing their “Use Cowork safely” guidelines.

This is a big step toward practical AI agents that don’t just chat or run in sandboxes — they can operate your actual computer like a remote assistant. It positions Claude as a strong competitor to viral tools like OpenClaw and could accelerate automation in coding, admin work, data entry, and more.

That said, handing any AI full screen, mouse and keyboard access is powerful but comes with obvious security considerations; keep sensitive stuff like crypto wallets air-gapped. Many users are calling it “wild” or “magic,” while others note it’s still early and best used with caution.

This shifts AI from conversational helper to an autonomous desktop agent that can see your screen, move the mouse, click, type, and interact with any app. Claude can handle repetitive or multi-step tasks across apps: organizing files, filling spreadsheets, navigating browsers, drafting reports, managing email/calendar, or even running workflows while you’re away via Dispatch on mobile.

Users describe it as “hypnotic” or “magic” for knowledge work. Non-technical users or busy professionals get a true “AI coworker” that executes rather than just suggests. Early tests show strong potential for admin, data entry, coding support, and research. Pairs especially well with Claude Code for building, testing, and iterating in IDEs or terminals. Broader trend: AI agents are already contributing a notable share of GitHub commits in some workflows.

Anthropic’s own data shows heavy usage in computer/math occupations; deeper computer control could accelerate labor shifts in white-collar roles, moving more tasks from human to API/agent execution. This represents a practical step toward reliable AI agents that operate like a remote human assistant.

Granting mouse/keyboard/screen control means Claude can read anything visible, modify/delete files, send messages, or interact with logged-in services. Prompt injection (malicious instructions hidden in web pages/emails) remains a real vulnerability — the AI could be tricked into harmful actions.

As a research preview, it’s slow (relies on repeated screenshots + interpretation), prone to vision hallucinations, misclicks, or getting stuck on complex UIs. One wrong move could corrupt data or break workflows.

You’re accountable for everything it does. Enterprises are already hesitant due to compliance, data leakage, and “delegation with anxiety” — time saved on execution often gets spent on verification. Best practice for now: sandbox it, start with low-risk tasks, and never leave it unsupervised with important data.

This builds on Anthropic’s earlier “computer use” API and competes with tools from OpenAI, Google, and others. Expect faster iteration toward more reliable, multi-device agents (phone control is reportedly in testing too). Many react with a mix of excitement and fear. It highlights the tension between capability and control — full autonomy sounds great until something goes wrong.

Could amplify productivity for individuals and teams, but also raise questions about job displacement in routine cognitive tasks, accountability, and the need for new oversight processes in companies. Anthropic maintains safety red lines, but deeper real-world control pushes boundaries on alignment, bias in actions, and unintended consequences.

 

In short, this is a milestone toward practical AI agents that “do” rather than just “talk.” It’s genuinely powerful for boosting output on macOS today (Windows soon), but treat it as experimental: powerful tool, not yet a fully trusted employee. Many users are testing it on throwaway folders first and reporting impressive results with careful scoping.

Over $250M Worth of Shorts get Liquidated in 15 Mins as Trump Postpones Strikes on Iran

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President Trump announced via Truth Social that, following what he described as “very good and productive” conversations with Iranian officials aimed at a “complete and total resolution” of hostilities including issues around the Strait of Hormuz, he had instructed the U.S. military to postpone any strikes on Iranian power plants and energy infrastructure for five days.

This came after he had issued a 48-hour ultimatum over the weekend threatening to “obliterate” such targets if Iran did not fully reopen the Strait of Hormuz. Iran quickly denied that any substantive bilateral talks or negotiations were occurring, calling Trump’s characterization inaccurate.

The de-escalation tone triggered an immediate risk-on surge: Bitcoin pumped roughly $2,900–$3,000 in a sharp candle, briefly pushing toward the $71,000 level. Broader crypto markets followed, with sentiment flipping bullish on reduced geopolitical risk.

In the ~15 minutes following Trump’s statement, approximately $250–265 million in short positions were liquidated across crypto derivatives; Bitcoin accounted for the bulk, around $248–250M in shorts wiped out. Total 24-hour liquidations exceeded $700–800M, affecting hundreds of thousands of traders.

This was a classic short squeeze amplified by high leverage in the crypto futures market. Traders who had piled into shorts betting on further downside from weekend escalation fears got caught off guard by the sudden reversal. Traditional markets also reacted: U.S. stock futures rose, while oil prices dropped sharply on lowered fears of major supply disruptions from the Gulf region.

This fits into a broader, volatile period of U.S./Israeli actions against Iran, including prior strikes on energy-related targets and Iranian threats of retaliation; targeting Gulf infrastructure or closing the Strait. Volatility remains high—headlines can flip quickly as seen with Iran’s denial, and some analysts expect continued back-and-forth between escalation rhetoric and negotiation signals.

Crypto’s extreme sensitivity here highlights how leveraged derivatives amplify headline-driven moves far beyond spot price action. It’s a textbook example of geopolitics meets crypto leverage: one tweet-style announcement, massive short pain, and a fast rebound.

Markets hate uncertainty, but they love a surprise “pause for talks” narrative—even if the other side disputes it. A short squeeze is a rapid, self-reinforcing surge in an asset’s price (stock, crypto, commodity, etc.) driven primarily by short sellers being forced to buy back the asset to close (or “cover”) their positions, rather than by strong underlying fundamentals.

A trader believes the price of an asset will fall. They borrow the asset; shares of a stock or equivalent contracts in futures/perpetuals from a broker or lender. They immediately sell it at the current market price.

Later, they hope to buy it back at a lower price, return the borrowed asset, and pocket the difference as profit. If the price falls as expected, the short seller profits. If it rises instead, losses mount quickly—potentially unlimited in theory, since there’s no upper limit to how high a price can go.

High short interest builds up: Many traders pile into short positions, betting on downside. This can reach extreme levels e.g., 20–100%+ of available shares or open interest in derivatives. Unexpected positive news, a tweet, earnings beat, or sudden buying pressure pushes the price higher. In the recent crypto example, Trump’s announcement of postponing strikes on Iranian infrastructure flipped sentiment from “geopolitical risk = sell” to “de-escalation = risk-on,” driving Bitcoin up sharply.

Short sellers feel pain: Rising prices create unrealized losses. Brokers issue margin calls demanding more collateral. If unmet, or if automatic stop-losses trigger, positions are forcibly closed. Forced covering: To exit, shorts must buy back the asset. This buying adds sudden demand.

Feedback loop: The new buying pushes the price even higher ? more shorts hit their pain thresholds ? more forced buying ? price accelerates further. This is the “squeeze.” Liquidation cascade (especially in crypto/futures): In leveraged derivatives markets (perpetual futures common in crypto), exchanges automatically liquidate positions when margin runs out. Each liquidation executes a market buy order, amplifying the upward move and triggering the next wave.

This is why $250M+ in shorts can get wiped out in minutes—leverage often 10x–100x makes small price moves catastrophic for shorts. A sharp vertical candle upward, often with massive volume, even if the “real” news isn’t that bullish long-term.

Traders had built up bearish bets expecting escalation in the Middle East to hurt risk assets like Bitcoin. Trump’s “productive talks” post reversed that narrative instantly. Shorts rushed to cover or got auto-liquidated, creating the exact cascade: Bitcoin jumped ~$3,000 quickly, liquidating over $250M in shorts in ~15 minutes. Iran’s quick denial later cooled things, showing how headline-driven these moves can be.

Short squeezes are often short-lived; once most shorts are squeezed out, the price can reverse if fundamentals don’t support the new level. They hurt shorts badly but can reward longs who timed the catalyst. In crypto, perpetual futures with funding rates make squeezes more frequent and violent because positions don’t expire.

A short squeeze turns a modest price increase into a rocket because the very act of shorts trying to escape creates the fuel for even more upside. It’s pure supply-demand dynamics on steroids, amplified by leverage and psychology. Always high risk—markets can squeeze in either direction.

U.S. Stock Futures Slip as Iran Rift Clouds Trump’s Overture, Forcing Markets to Reprice Risk

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U.S. equity futures retreated early Tuesday, erasing part of the previous session’s sharp gains as doubts over Washington’s claims of backchannel engagement with Tehran unsettled investors and revived the geopolitical risk premium that has gripped markets for much of the past week.

The pullback followed a rapid shift in narrative. President Donald Trump said on Monday he had held off on a planned strike against Iran’s power grid after what he described as “productive talks” with Iranian officials. The comment briefly steadied markets and triggered a broad-based rally across Wall Street, with the main indexes posting their strongest one-day advance in over a month.

By Tuesday, that optimism had begun to unravel. Iran’s parliament speaker, Mohammad Baqer Qalibaf, publicly rejected the notion that any negotiations had taken place, contradicting the U.S. account and casting doubt on whether a diplomatic channel exists at all. Israeli officials compounded the uncertainty, indicating that while Washington appears to be seeking a deal, the prospects for meaningful progress remain low.

The conflicting signals have left markets navigating a familiar but destabilizing pattern: a surge in risk appetite driven by political rhetoric, followed by a recalibration once that rhetoric is challenged. Analysts at Deutsche Bank said the reversal reflected a growing skepticism among investors about headline-driven optimism.

“Iranian officials have repeatedly denied that talks with the U.S. were even happening,” the bank noted, adding that the market reaction had begun to unwind as traders reassessed the credibility of those claims.

By 05:21 a.m. ET, Dow E-minis were down 0.4%, S&P 500 futures had fallen 0.38%, and Nasdaq 100 futures slipped 0.34%. The declines point to a market that is no longer willing to extend gains without clearer evidence of de-escalation.

The deeper concern lies in the feedback loop between geopolitics, energy prices, and monetary policy. Oil’s recent surge—driven by fears of supply disruption in the Middle East—has reintroduced inflation risk at a moment when central banks had been cautiously signaling a shift toward easing. That dynamic is now reversing.

The Federal Reserve last week struck a more hawkish tone than many investors had anticipated, projecting only a single rate cut in 2026. Since the escalation in the Middle East, traders have moved to price out rate reductions for this year entirely, a sharp pivot from earlier expectations of two cuts. Data from the CME Group show that even fleeting expectations of rate hikes emerged at the height of last week’s tensions, before being pared back following Trump’s remarks.

What is becoming clearer is that monetary policy expectations are now being dictated less by domestic economic data and more by developments in the Gulf. Higher oil prices risk feeding through to core inflation via transport and input costs, complicating the Fed’s path and tightening financial conditions even without formal policy action.

This repricing comes against a backdrop of weakening equity momentum. All three major U.S. indexes logged their fourth consecutive weekly decline last week, with the Nasdaq suffering its steepest drop since early February. The inability of Monday’s rally to sustain itself suggests that investors remain cautious about re-entering risk assets in the absence of durable geopolitical clarity.

Attention now turns to incoming economic signals, including a flash reading of March business activity and remarks from Federal Reserve Governor Michael Barr. While typically market-moving, such data may play a secondary role if geopolitical developments continue to dominate sentiment.

In corporate trading, Jefferies stood out, rising in premarket dealings after reports that Sumitomo Mitsui Financial Group is exploring a potential acquisition. The move, if pursued, would mark one of the more significant cross-border plays in investment banking in recent years and underscores how strategic dealmaking can persist even in unsettled markets.

Elsewhere, Battalion Oil shares declined following weaker revenue, a reminder that elevated crude prices do not translate uniformly into improved corporate performance, particularly for smaller producers facing cost pressures and operational constraints.

For now, markets remain tethered to geopolitical developments that resist easy interpretation. The gap between Washington’s assertions and Tehran’s denials has introduced a layer of ambiguity that investors cannot easily hedge. Until that gap narrows, either through verifiable diplomacy or a clearer escalation path, equities are likely to remain volatile, with sentiment shifting as quickly as the headlines that drive it.

OpenAI Scraps Sora Video App in Strategic Shift Toward Robotics and Core AI Systems

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OpenAI is shutting down its Sora video platform in its current form, abandoning both the consumer app and API in a decisive pivot that reflects the mounting cost pressures and strategic trade-offs shaping the artificial intelligence industry.

The company confirmed the move in a statement, saying it would discontinue Sora as it reallocates resources toward more foundational research.

“We’ve decided to discontinue Sora in the consumer app and API,” a spokesperson said. “As we focus and compute demand grows, the Sora research team continues to focus on world simulation research to advance robotics that will help people solve real-world, physical tasks.”

The decision marks the end of one of the company’s most visible consumer experiments. Sora burst onto the scene in late September 2025, quickly becoming a showcase for the capabilities of generative AI. Its ability to produce realistic, cinematic video clips from simple text prompts propelled it to the top of app store rankings, with more than one million downloads recorded within days of launch.

That early success masked deeper structural challenges. Video generation sits at the extreme end of AI’s compute spectrum, requiring significantly more processing power than text or image models. As user demand surged, so too did the cost of serving it. OpenAI was forced to impose limits on free usage and scale back access, with Sora lead Bill Peebles acknowledging at the time that the economics were “completely unsustainable,” adding bluntly that “video models really are expensive.”

Those constraints highlight a broader reality confronting the sector. Even as AI tools attract mass adoption, the infrastructure required to sustain them, specialized chips, data centers, and energy, remains finite and costly. Companies are increasingly being forced to choose between scaling consumer products and investing in longer-term capabilities that may yield greater strategic returns.

Sora also became an early test case for the legal and ethical tensions surrounding generative media. Users quickly pushed the system to recreate copyrighted characters and historical figures, including Pikachu and Martin Luther King Jr., prompting OpenAI to introduce tighter safeguards. The platform drew legal scrutiny as well. Cameo filed a lawsuit alleging trademark infringement over the use of “cameo” as a feature name, forcing OpenAI to rebrand part of the product.

At the same time, the company attempted to formalize relationships with rights holders. In December, The Walt Disney Company struck a three-year agreement with OpenAI, becoming the first major content partner on Sora and committing $1 billion as part of the deal. Disney acknowledged the shutdown on Tuesday, saying it “respects” OpenAI’s decision and will continue exploring how to engage with AI platforms while protecting intellectual property.

The pivot away from Sora suggests that those efforts, while significant, were not enough to overcome the underlying economic and strategic constraints. Monetizing generative video at scale remains an unresolved challenge, particularly when weighed against the opportunity cost of deploying compute toward more advanced systems.

OpenAI’s shift toward “world simulation” points to where those resources are now being directed. Such systems aim to model real-world environments with high fidelity, enabling AI to plan, reason, and act within dynamic physical settings. The approach is widely viewed as a critical step toward more capable autonomous systems and robotics, where virtual training environments can accelerate real-world performance.

The decision also aligns with other industry changes. As competition intensifies and demand for computing accelerates, leading AI firms are increasingly prioritizing core infrastructure and high-impact research over consumer-facing applications that, while popular, may not justify their operational cost.

Sora’s trajectory encapsulates that tension. It demonstrated the frontier of what generative AI can produce, captured public imagination, and attracted major partners. Yet its rapid growth exposed the limits of current economics, governance frameworks, and infrastructure capacity.

For users and creators, the shutdown leaves a gap in a nascent but fast-evolving segment of the AI market. However, it marks a return to OpenAI’s first principles: investing in systems that extend beyond content generation into domains where AI can interact with the physical world.

The retreat from Sora is not a rejection of generative video itself, but a recognition that, under current conditions, the path to scaling it sustainably remains uncertain. In the meantime, the company is redirecting its most constrained resource, compute, toward technologies it believes will define the next phase of artificial intelligence.

Oracle Overhauls Fusion Cloud Software to Let AI Agents Handle Routine Tasks, Freeing Humans for Higher-Value Decisions

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Oracle is reshaping its Fusion cloud software so that AI agents can take over the drudgery of data entry and routine execution, leaving human workers to focus on the judgment calls that actually move the business forward.

The overhaul, unveiled Tuesday at an event in London, is the latest sign that makers of heavyweight corporate systems are scrambling to adapt to a world where autonomous agents handle the mechanical work.

Steve Miranda, Oracle’s executive vice president of applications development, put it plainly: the aim is to let managers ask real business questions, how to design a new product more cheaply and faster while avoiding supply chain blowups, and let the system hunt down the scattered data, pull it together, and lay out options.

That data lives across Fusion modules and linked third-party applications. The AI will track it, compile the information, and suggest next steps. Humans, Miranda said, will spend more time on the things machines still cannot do well: negotiating with suppliers, weighing risk tolerance, and making the final calls.

“Typing in an invoice isn’t a particularly high-value skill to your enterprise or to the person who does that part of their job,” he told the audience. “Decision making is still kind of up to that human and weighing the different pros and cons of that case. But certainly the execution, the typing of the invoices, the typing of the purchase order, that is what is going to be replaced in whole by AI.”

Oracle’s shares have dropped about 40 percent this year as investors fret that AI could eventually eat into the need for complex enterprise software. Company executives have pushed back, insisting they are leaning into the technology rather than waiting to be overtaken. By making Fusion more agent-friendly, Oracle hopes to keep its flagship product indispensable even as generative tools reshape how companies run their back offices.

Fusion handles core operations from factory planning to revenue collection. The update turns those pieces into a more intelligent system where agents can move data, flag exceptions, and generate recommendations without constant human babysitting. The shift mirrors what Salesforce, Workday, and SAP are also attempting: turning their platforms into launchpads for autonomous workflows rather than static record-keeping tools.

For large companies already running Fusion, the change could mean quicker cycles on everything from procurement to financial close. It also carries the usual caveats. Accuracy, audit trails, and human oversight will matter more than ever when agents start touching real money and real supply chains.

Oracle has not detailed every safeguard, but Miranda made clear the system is built with controls that keep people in the loop on consequential decisions.

The broader market reaction has been muted. Oracle’s stock has been under pressure for months, caught in the same AI-induced reevaluation that has hit other enterprise software names. Some investors worry the very tools Oracle is embracing could shrink the addressable market for traditional ERP suites. Others see the move as a necessary defense — a way to stay relevant as customers demand systems that do more than store data.

But Oracle is not alone in this bet. The entire sector is racing to agent-enable its platforms, hoping to turn potential disruption into an upsell opportunity. Anthropic has just initiated a move to give its Claude system the ability to operate a user’s computer and carry out tasks with limited supervision.

With Oracle now in the picture, the agentic AI race is believed to be escalating. This means the heavy lifting of corporate data work is increasingly headed for automation. The humans who used to do it will be asked to do something harder — and, Oracle hopes, more valuable. But that increases the concern of AI taking over jobs.