Friday, 11 September 2026

Dogecoin’s Rough Ride: ETF Closure and Macro Headwinds Trigger Sharp Sell-Off

Dogecoin took a beating on Thursday. The meme coin dropped more than 5% in afternoon trading, underperforming the broader market as Bitcoin held steady near $78,000. But the reasons run deeper than a bad day. They point to limited institutional appetite, crowded trades unwinding fast, and shifting economic signals that hit risk assets hardest.

Traders noticed the move early. By late afternoon Eastern time, DOGE had shed nearly 5%. Some reports pegged the decline closer to 7% at its worst, taking the price down toward $0.083. Short sentences capture it best. Quick. Brutal. And not entirely surprising given what was unfolding behind the scenes.

The most direct blow came from Bitwise Investment Advisors. The firm announced it would close and liquidate its spot Dogecoin ETF. Trading ends Oct. 13. Liquidation follows on Oct. 22. Shareholders receive cash through their brokers. The Motley Fool highlighted how this decision stood out on a day already filled with negative momentum. Fewer Dogecoin ETFs exist compared with those tracking Bitcoin or Ether. Their shutdown signals thinner demand from everyday investors.

But the ETF news didn’t arrive in isolation. Bond yields climbed. Oil prices pushed toward $102 a barrel amid tensions with Iran. The producer price index came in roughly as expected, yet it reinforced worries about sticky inflation. When safer fixed-income assets offer better returns, appetite for speculative bets like cryptocurrencies fades. CoinDesk reported Dogecoin led losses among major coins. BNB fell about 4%. XRP dropped 3%. Ether and Solana gave back 1% to 3% each.

Leverage made things worse. Data from CoinGlass showed $8.91 million in Dogecoin positions liquidated over 24 hours. Longs accounted for $8.59 million of that total. The imbalance reached 2,691%. Bulls who bet on a breakout got caught. U.Today detailed how the price failed to clear the 200-day moving average near $0.088 to $0.096. Four straight days of declines followed a weekend surge that topped out at $0.095.

Support levels now sit between $0.082 and $0.084. A break lower could test $0.08, a level where more than 30 billion DOGE tokens have changed hands historically. Technical rejection at key averages amplified the move. Yet many analysts describe this as a positioning reset rather than a fundamental breakdown.

Whale activity tells a mixed story. Large holders accumulated. One wallet associated with SANGRIX sold 3 million DOGE on Sept. 7 for roughly $267,665 to fund working capital and AI infrastructure. Still, overall whale holdings hit a record 108.5 billion DOGE. Futures open interest climbed to 16.38 billion tokens, worth about $1.5 billion. These figures suggest conviction among big players even as retail sentiment sours.

Positive developments exist too. Dogecoin went live on Solana this week through the Sunrise Protocol. Trading volume on the new bridge exceeded $19 million on day one. The DOGE-1 lunar mission, backed by Dogecoin, prepares for a SpaceX launch on Sept. 14. Such news would normally spark buying. This time it barely registered against the macro tide.

Bitcoin printed a golden cross. Its 50-day average moved above the 200-day average, a pattern that preceded a 90% rally in 2019. The largest cryptocurrency stayed relatively firm near $78,000, down only 1%. That resilience highlighted Dogecoin’s higher beta. When risk appetite shrinks, meme coins feel it first. And right now, the Federal Reserve’s next moves loom large. Markets price in a possible quarter-point rate hike after months on hold. Friday’s consumer price index report could sharpen those expectations.

Institutional interest in dedicated Dogecoin products remains modest. The 21Shares Dogecoin ETF held just $2.66 million in assets as of Sept. 9. Other vehicles show slightly larger figures but still pale next to Bitcoin or Ethereum funds. KuCoin News noted this lack of support from ETFs contributed to the vulnerability.

Yet Dogecoin refuses to fade entirely. Its community stays active. Cultural relevance persists years after its 2013 launch as a joke. Elon Musk’s occasional mentions still move markets. Some treasury firms disclosed plans to add DOGE to compliant portfolios. These undercurrents suggest the sell-off may prove temporary.

The Technical Picture and Support Tests

Price action reveals clear levels. Rejection from the 200-day EMA created the initial catalyst. Leveraged longs then unwound in a cascade. Bollinger Bands have tightened across timeframes, hinting at an imminent volatility expansion. Traders watch whether $0.08 holds. A bounce from there could retest $0.09 or higher. Failure opens the door to further weakness.

Broader market structure matters too. Bitcoin dominance rose to nearly 59% as altcoins bled. Total crypto market capitalization fell more than 4% in 24 hours. This rotation away from higher-risk names explains much of the disparity.

Looking Past the Immediate Pressure

The current decline doesn’t erase longer-term developments. Record whale balances. Growing futures interest. New distribution channels on Solana. Upcoming mission milestones. All point to sustained, if volatile, interest.

Macro conditions can shift. Cooler inflation readings or a softer Fed stance would ease pressure on risk assets. Until then, Dogecoin trades in a tight range with clear downside risks. Investors who entered with leverage learned the cost once again. The rest watch support levels and wait for the next catalyst. One thing remains clear. This asset never moves quietly.



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OpenAI’s GPT-Live-1 API Hands Developers a Voice Model That Never Stops Listening

OpenAI just opened the doors wider on voice AI. The company released GPT-Live-1 to its API on September 10. This model listens and speaks simultaneously. No more rigid turn-taking. Conversations flow with interruptions, acknowledgments and background reasoning all happening at once.

The new offering builds directly on technology first shown in ChatGPT earlier this year. Developers can now integrate it into their own applications. They pair the voice layer with backend models of their choice. One handles fluid dialogue. Another tackles complex tasks. The split keeps responses quick while delivering smarter answers.

From ChatGPT Experiment to Developer Platform

GPT-Live-1 first appeared inside ChatGPT in July. It replaced the older Advanced Voice Mode for many users. The model used a full-duplex architecture from the start. It processes incoming audio and generates output in a continuous stream. Decisions happen many times per second. Speak. Listen. Pause. Interrupt. Call a tool. All without breaking the audio loop.

That design solved persistent problems. Previous systems chained speech-to-text, a large language model and text-to-speech. Each handoff added latency. Interruptions often failed. Context got lost. GPT-Live-1 collapses those steps into one model for the voice layer. It sends harder questions to a separate reasoning engine in the background. The conversation continues uninterrupted.

OpenAI detailed the improvements in its announcement. On the Full Duplex Bench, GPT-Live-1 scores 30 percentage points higher than GPT-Realtime-2.1. Turn-taking latency falls to 0.8 seconds from 1.4 seconds. Tool-calling accuracy rises to 87 percent from 60 percent. In a banking voice support test, the pass rate jumps to 32 percent from 12.4 percent. These numbers come from OpenAI’s own evaluations. They paint a picture of measurable progress. (OpenAI)

Yelp already put the technology to work. Its Host service manages restaurant reservations over the phone. CTO Alex Levy reported better call handling. The system manages interruptions more gracefully. It keeps callers engaged even while looking up availability or confirming details. Real customer deployments like this one test the model under pressure. They reveal where the gains matter most.

The API version gives developers fresh controls. They decide how the voice agent speaks and acts. Twelve new voices arrived with the release. Accents, dialects and languages vary. Automatic speech recognition transcripts and response text come standard. Pricing sits at $0.05 per minute for the front-end voice layer. Not cheap. Yet the cost stays separate from the backend model. Teams can choose GPT-6 Astra for deep reasoning or cheaper options for simple exchanges. (The Decoder)

But the real story runs deeper than benchmarks. Voice agents have struggled with one fundamental flaw. They feel robotic because they wait. Users pause. The system stays silent. Or worse, it talks over them. GPT-Live-1 changes the rhythm. It offers verbal nods like “mhmm” when appropriate. It stays quiet during thoughtful pauses. It adjusts instantly to corrections mid-sentence. The result sounds closer to talking with a person. Not a machine waiting for its cue.

Industry watchers noted the shift months ago. Early leaks in June pointed to a bidirectional model then called GPT-Bidi-1. It promised exactly this capability. OpenAI refined the approach through summer testing in ChatGPT. The July launch of GPT-Live set the stage. Now the API release invites builders to experiment at scale. (The Register)

Competition looms. Google offers Gemini Live. Other providers push their own real-time voice tools. Yet OpenAI’s move carries weight. The company leads in developer mindshare. Its benchmarks position GPT-Live-1 at the top of the Tau3 voice-agent intelligence ranking when paired with GPT-6 Astra at medium effort. That combination handles end-to-end customer service tasks better than prior setups. Airlines, retailers and telecom operators stand to benefit first.

Developers face trade-offs. The $0.05 per minute adds up in high-volume call centers. Backend reasoning costs extra. Integration requires careful design. Still, the simplification appeals. One voice model. Configurable intelligence. Native support for interruptions and parallel tool calls. The architecture reduces brittle handoffs that plagued earlier voice agents.

OpenAI plans to expand voice options and language support in coming months. More accents. Broader dialects. The roadmap hints at longer, more agentic interactions. For now, the focus stays on fluid conversation. Make the AI sound attentive. Keep the exchange moving. Let complex work happen offstage.

Early reactions on X reflect cautious optimism. Engineers experiment with the new endpoint. Some note the price. Others highlight the jump in natural behavior. One developer called it a solid step for voice infrastructure. Another predicted faster adoption in reservation and support apps. The conversation around voice AI just got more interesting. And more practical.

This release marks another incremental gain in a series of voice updates. Each version closes the gap between scripted assistants and genuine dialogue. GPT-Live-1 doesn’t solve every challenge. Hallucinations can still occur. Context windows have limits. Costs require monitoring. Yet it gives developers a stronger foundation. One that listens while it talks. One that reasons without going silent. The kind of tool that could finally make voice the default interface for many tasks.



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Thursday, 10 September 2026

Meta Launches Muse: Personal AI Agent for Email, Calendar and Smart Devices

Meta has officially introduced Muse, a personal AI agent designed to handle everyday digital tasks by connecting directly with a user’s email, calendar, payment services, health data, and smart home devices. The announcement, made available through both the main Meta app and WhatsApp, positions the tool as an always-available assistant that operates across multiple areas of a person’s life. Pricing starts with a free tier that offers basic functionality, while paid options at twenty dollars and one hundred dollars per month unlock advanced capabilities such as higher usage limits and priority processing.

The system runs inside a dedicated virtual machine equipped with its own browser instance, an approach intended to isolate the agent’s activities from the user’s primary devices. This setup allows Muse to visit websites, fill out forms, and interact with online services without requiring users to share their login credentials directly. Instead, the agent uses secure token exchanges and permission-based access that users must approve through a straightforward interface. According to the official announcement from Meta at about.fb.com, the virtual machine environment also includes safeguards that prevent the agent from storing sensitive information beyond the duration of a specific task.

Early coverage from Reuters highlights both the promise and the practical challenges that emerged during internal testing. The news outlet reported at reuters.com that engineers observed occasional stalls when the agent attempted to coordinate actions across several connected services at once. In one documented case, a request to schedule a medical appointment while checking available funds and updating a fitness tracker resulted in a delay of nearly forty seconds before completion. These performance hiccups appeared more frequently when the agent managed complex sequences involving health records and financial transfers.

Data exposure concerns also surfaced during those same tests. Reuters noted that in rare instances, fragments of calendar entries appeared in temporary log files that were accessible to Meta support staff. Although the company quickly patched the logging mechanism, the incident underscored the tension between functionality and privacy that accompanies any agent granted broad system access. Meta responded by implementing stricter compartmentalization rules and adding user-controlled audit logs that record every action the agent performs.

The free version of Muse limits users to thirty interactions per day and restricts the number of simultaneous connections to three services. The twenty-dollar tier raises those limits substantially, allowing two hundred interactions daily and support for up to ten connected accounts. At the top pricing level of one hundred dollars monthly, the agent gains access to specialized reasoning modules that can handle multi-day planning tasks, such as organizing an entire business trip including flights, hotel reservations, ground transportation, and follow-up calendar entries. This highest tier also includes dedicated support from human reviewers who can step in when the agent encounters ambiguous situations.

Integration with WhatsApp gives the agent a conversational entry point that feels familiar to billions of users. People can message the agent directly within the chat app to request actions such as sending a polite decline to an unwanted meeting invitation or transferring money to a family member. The system converts those natural language instructions into a series of discrete steps that it then executes inside the protected virtual machine. Voice input is supported through the Meta app on mobile devices, allowing users to speak commands while driving or exercising.

Health data connections represent one of the more sensitive aspects of the rollout. Muse can link with popular fitness trackers and electronic medical record portals to pull information like recent lab results or daily step counts. Users must explicitly authorize each connection, and the agent is barred from modifying any medical data, only reading what is necessary to complete a requested task. For example, it can check a user’s vaccination status before booking an international flight but cannot add new entries to a health record.

Home automation compatibility extends to major smart device platforms, enabling the agent to adjust thermostats, lock doors, or dim lights based on a user’s schedule. During testing, participants asked Muse to prepare their house for an evening dinner party by setting the temperature, turning on specific lights, and ordering groceries through an integrated shopping service. The agent completed the sequence without human intervention, though reviewers noted that the grocery order occasionally included items that were close but not exact matches to the spoken request.

Security remains a central theme in Meta’s communications about Muse. The dedicated virtual machine resets after each major task, clearing temporary memory and browser cookies to reduce the risk of accumulated data leaks. All external connections travel through encrypted tunnels that Meta controls, and the company has committed to annual third-party audits of the entire system. Despite these measures, privacy advocates have raised questions about whether an AI granted such wide-ranging permissions can ever be considered fully trustworthy.

The product concept builds on years of incremental advances in large language models and automation tools. Rather than positioning Muse as an entirely new invention, Meta describes it as a practical assembly of existing technologies refined for everyday reliability. The agent relies on a mixture of optical character recognition for reading web pages, natural language understanding for interpreting user intent, and rule-based engines for handling financial transactions that require absolute accuracy.

Early user feedback collected through closed beta programs revealed a split in reactions. Many appreciated the ability to offload routine administrative work such as expense reporting or appointment coordination. Others expressed discomfort with the idea of an AI reading their email inbox or accessing banking information, even when the system provided detailed logs of its activities. Meta has attempted to address these concerns by offering granular permission controls that let users specify exactly which folders or accounts the agent may touch.

Technical architecture details released in the announcement show that Muse contains several specialized modules working in concert. A planning module breaks down complex requests into ordered steps. An execution module carries out those steps inside the virtual machine. A verification module double-checks results against user-defined rules before reporting completion. When the agent encounters uncertainty, it pauses and sends a clarification question back to the user rather than guessing.

The one-hundred-dollar tier introduces what Meta calls extended reasoning, which allows the agent to maintain context across multiple days. A user could ask Muse on Monday to plan a conference trip for the following month, and the agent would continue gathering options, comparing prices, and seeking the user’s preferences over the course of several interactions. This persistent memory is stored in an encrypted database that only the specific user’s instance of Muse can access.

Industry observers point to the launch as a significant test of consumer willingness to trust AI with personal affairs. Previous attempts by other companies to introduce similar agents met with mixed success, often because users grew concerned about accuracy or data handling practices. Meta appears to have learned from those experiences by emphasizing transparency and control. Every action taken by Muse generates a plain-language summary that users can review and revoke if necessary.

Performance improvements are expected in the coming months as the company collects data from the initial wave of users. The internal tests mentioned by Reuters exposed bottlenecks in the browser automation layer that engineers are now optimizing. Future updates may also expand compatibility with additional services, including government portals for filing taxes or renewing licenses, areas where accuracy and security requirements are especially high.

The pricing structure reflects different levels of commitment from users. Casual users can experiment with the free version to see whether the agent saves meaningful time. Professionals who spend hours each week on administrative tasks may find the twenty-dollar plan worthwhile. Power users, such as executives or small business owners managing complicated schedules, might justify the one-hundred-dollar investment for the extended planning features and higher reliability guarantees.

Meta has also published a detailed transparency report outlining how training data for Muse was collected and filtered. The company states that no individual user messages were used to train the underlying models. Instead, synthetic task sequences generated by other AI systems formed the bulk of the training material. This approach aims to reduce privacy risks while still providing the agent with realistic examples of common digital workflows.

As adoption begins, questions about liability remain unresolved. If Muse makes an error that costs a user money or causes a missed opportunity, who bears responsibility? Meta’s current terms place the risk on the user, though the company promises to refund certain types of documented financial losses during the first year. Legal experts suggest that clearer regulations around AI agents will likely emerge as these tools become more common in daily life.

The launch arrives at a moment when many people feel overwhelmed by the volume of digital tasks competing for their attention. Email inboxes overflow, calendar conflicts multiply, and payment reminders arrive at inconvenient times. Muse offers to absorb some of that cognitive load by monitoring all these channels and surfacing only the decisions that genuinely require human judgment. Whether users will feel comfortable handing over that responsibility is the central question the coming months will answer.

Engineers at Meta continue to refine the agent’s ability to recover gracefully from failures. If a website changes its layout or a connected service updates its authentication method, Muse now includes self-diagnostic routines that alert developers and temporarily disable affected functions rather than producing incorrect results. This resilience testing formed a major part of the internal evaluation process that Reuters referenced in its reporting.

For families, the agent offers shared modes where multiple people can grant limited access to joint calendars or household accounts. Parents might allow Muse to coordinate children’s after-school activities while keeping financial details hidden. Couples could use the tool to manage shared budgets and bill payments without either partner needing to review every transaction manually.

Education and support materials released alongside the launch include video tutorials, interactive walkthroughs, and a comprehensive help center. Meta has also created a community forum where users can share successful automation patterns and troubleshoot unexpected behavior. The company plans to host monthly webinars featuring product managers and engineers who will demonstrate advanced techniques for getting the most from the higher-priced tiers.

Longer-term ambitions for Muse include deeper integration with augmented reality devices that Meta continues to develop. Future versions could potentially observe a user’s physical environment through smart glasses and suggest context-aware actions, such as reminding them to order more printer ink when the agent sees low supplies during a video call. Those possibilities remain speculative, but the current release establishes the foundational trust and technical infrastructure needed for such expansions.

The introduction of Muse marks a concrete step toward AI systems that actively manage aspects of daily life rather than simply answering questions. By combining careful engineering, transparent data practices, and multiple pricing levels, Meta hopes to build confidence among users who have grown wary of previous automation promises. The coming year will reveal whether the agent’s practical benefits outweigh the very real concerns about privacy, reliability, and the gradual transfer of personal responsibility to artificial systems. Early indications from beta testers suggest that many people already see enough value to give the free version a serious try, with a significant portion expressing willingness to upgrade once they experience time savings in their own routines.



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Wednesday, 9 September 2026

Australia Hands Users the Off Switch: Inside Albanese’s Bid to Tame Social Media Algorithms

Prime Minister Anthony Albanese stood before reporters in Canberra on Tuesday and delivered a message that cut through years of complaints about addictive feeds and harmful content. This is not about giving government control, he said. It is about giving people control.

The Albanese government released draft legislation for a Digital Duty of Care on September 8, 2026. At its center sits an Australian first called “My Feed, My Way.” Social media platforms must notify new and existing users over 16 and offer a clear choice for their default feed. They can opt in to personalized algorithmic recommendations. Or they can opt out and see only posts from friends and creators they deliberately follow.

The proposal builds directly on Australia’s world-leading ban on social media for those under 16, which took effect late last year. That measure led to more than five million accounts being deactivated or removed within a month, though enforcement challenges remain. Now the government wants to extend its reach. Digital services including online games, apps, AI chatbots and search engines would face new obligations to protect users, especially minors, from addictive design features and specific categories of harmful material.

Penalties for noncompliance could hit A$109.2 million. The independent eSafety Commissioner gains expanded powers to enforce the rules, issue content removal notices and demand that platforms document their risk management efforts. Platforms must conduct annual risk assessments, address foreseeable harms and prove those measures stay effective over time. Failure brings real financial pain.

And the timing matters. Albanese plans to highlight the initiative at the United Nations General Assembly later this month. Communications Minister Anika Wells described the package as the start of a global reckoning for big tech. The approach, she said, puts the onus on companies to create safer environments rather than leaving users to fend for themselves against opaque recommendation systems.

Users who choose the non-algorithmic feed won’t have their experience dictated by past behavior or inferred interests. The pop-up notification makes the choice explicit and repeatable. Wells noted that many people will still select the algorithmic option. That remains their decision. The law simply ensures the choice exists and persists.

Critics have already begun to weigh in. Some free speech advocates worry the broad definitions of harm and the regulator’s discretion could slide toward overreach or censorship. Opposition figures called parts of the draft an absolute threat to free speech, arguing Parliament should set harm categories rather than leave them to ministerial rules. Others point to a deeper flaw. Consent campaigner Chanel Contos has spent months warning that algorithms often hook users on problematic content long before any opt-out appears. A test profile for a teenage boy encountered misogynistic material on TikTok in minutes, according to reporting in The Sydney Morning Herald. Opting out later may not undo the initial damage.

Yet the government insists the measure restores agency. “We have an opportunity to shape technology for the better, rather than let it shape us,” Albanese told reporters. The draft requires platforms to disable algorithmic recommendations and certain addictive features for users under 16. It targets content promoting eating disorders, misogyny, pornography, crime glorification, self-harm and material that causes serious mental health distress.

The policy arrives amid growing international pressure on technology giants. The European Union has imposed its own algorithmic transparency requirements. Australia’s version stands out for its explicit user choice mechanism and heavy penalties. It also expands eSafety’s authority to tackle “nudify” apps that generate non-consensual intimate images and to demand swift removal of illegal or harmful material.

Industry reaction remains guarded so far. The consultation period seeks input from digital platforms, industry bodies, civil society groups and advocates. Legislation is slated for introduction to Parliament before the end of 2026. A public inquiry and negotiations seem certain. Tech companies have long argued that prescriptive design mandates could stifle innovation and raise compliance costs that ultimately hit users.

But parents and safety campaigners have driven much of the momentum. Emma Mason, whose 15-year-old daughter Tilly Rosewarne died by suicide in 2022 after online bullying, joined Albanese at the announcement. Her presence underscored the human stakes. For years platforms have run what Wells called real-time, unregulated product testing on Australians. The draft laws aim to end that experiment.

Implementation details will matter enormously. How exactly must the notification appear? How easy should switching back and forth be? What counts as genuine and enduring choice? The government has left some of these questions open for feedback. Yet the core principle is set. Default feeds should not automatically optimize for engagement at the expense of user well-being.

Supporters see this as pragmatic reform. Albanese called it sensible, pragmatic and practical. It does not ban algorithms. It does not dictate content. It simply forces companies to let users decide whether they want the machine curating their experience or prefer to follow their own network.

Skeptics counter that the algorithm has already won by the time the choice appears. Decades of behavioral data shape what users see first. Even a chronological feed of followed accounts may still reflect prior algorithmic influence on who those users chose to follow. The Sydney Morning Herald analysis highlighted this limitation. A boy saturated in manosphere content who then opts out will still confront a feed full of those same accounts.

The government acknowledges the concern but maintains that giving adults ongoing control represents progress. For minors the rules go further, with mandatory protections built into product design from the start. Platforms must proactively prevent exposure rather than respond after complaints.

This marks a significant shift in regulatory philosophy. Previous Australian efforts, including the 2021 News Media Bargaining Code, focused on economic power between platforms and publishers. The Digital Duty of Care targets the heart of the user experience itself. It treats social media not merely as a communications tool but as a product with design features that carry measurable behavioral risks.

Whether the approach succeeds depends on enforcement and adaptation. The eSafety Commissioner will need resources and technical expertise to audit complex recommendation systems. Platforms may design compliance in minimal ways that satisfy the letter but not the spirit of the law. Users themselves may grow weary of repeated pop-ups or simply accept the algorithmic default out of convenience.

Still, the move positions Australia as an aggressive regulator willing to impose design mandates where others have relied on transparency or self-regulation. The draft legislation reflects lessons from the under-16 ban. Pure age restrictions proved difficult to enforce without broader changes to platform architecture. Giving users tools to control their feeds attempts to address the problem at the level of daily interaction.

Albanese will carry this message to New York. Other nations watch closely. If the model withstands legal challenges and industry pushback, it could influence similar efforts in Europe, the United Kingdom and beyond. For now the consultation begins. Feedback will shape the final bill. But the direction is clear. Australian users may soon gain a real off switch for the algorithms that have quietly shaped their online worlds for more than a decade.

The government’s original announcement appears at the Prime Minister’s website. Reuters provided early reporting on the user-choice rules and penalties in its September 8 article. The Guardian detailed the global reckoning framing and eSafety’s expanded role. Additional context on potential flaws in the opt-out model came from The Sydney Morning Herald’s same-day coverage. The Financial Times examined the legislation’s place in Australia’s broader effort to rein in Big Tech. These accounts, published within hours of the announcement, capture the immediate reactions and technical specifics that will define the debate in coming months.



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Apple to Unveil First Foldable iPhone Ultra on September 9 Alongside iPhone 18 Pro and Watch Series 11

Apple’s first major product showcase under new chief executive John Ternus arrives on September 9, and the lineup promises more than the usual annual refresh. According to a report from Bloomberg published on September 4, the company will introduce its initial foldable handset, referred to internally as the iPhone Ultra, alongside the iPhone 18 Pro models and an updated Apple Watch. The absence of a standard iPhone 18 at the event signals a deliberate shift in how Apple times its hardware releases, placing the spotlight on premium devices that carry fresh industrial designs and software capabilities tailored to their new physical formats.

The foldable device represents Apple’s most significant departure from its rectangular slab formula in more than a decade. Sources familiar with the project describe a book-style fold that opens into a tablet-like display roughly matching the screen area of an iPad mini. When closed, the phone resembles a thicker traditional iPhone but with a secondary external screen that allows quick glances without unfolding. This dual-screen arrangement forces changes across the user interface that extend far beyond a simple hinge mechanism. Apple engineers have spent years refining the folding display’s crease visibility and hinge durability, aiming for a product that feels solid enough to carry daily without special care.

Software adjustments form the core of the new experience. The home screen, notification center, and control center all adapt to the device’s orientation. When opened flat, users can run two apps side by side with a drag-and-drop gesture that mirrors iPadOS but includes tighter integration with iPhone-specific features such as Continuity Camera and Apple Intelligence. Developers must submit additional screenshots to the App Store showing how their applications behave in both folded and unfolded states. This requirement already appears in updated App Store Connect documentation, suggesting the review process will begin accepting foldable-optimized binaries well before the hardware ships.

Multitasking receives particular attention. A new Stage Manager variant allows three or four overlapping windows on the larger internal display, complete with resizable panes and a persistent dock that slides away when not needed. Apple has also created a split-view keyboard option that places half the keys on each side of the hinge, reducing thumb travel during two-handed typing. These additions arrive alongside iOS 19, which will ship on all new devices announced at the event. The operating system update includes system-wide enhancements to window management, focus modes that react to device posture, and improved Stage Manager animations that make the foldable feel like a natural extension of existing iPhone behaviors rather than an entirely foreign platform.

On the hardware side, the iPhone 18 Pro and iPhone 18 Pro Max receive their expected yearly upgrades with a stronger emphasis on camera hardware and thermal management. The Pro models will feature a new 48-megapixel ultra-wide lens that matches the resolution of the main sensor, allowing consistent detail across all three rear cameras. Apple has also increased the telephoto zoom range to 6x optical on the larger Pro Max variant, achieved through a folded lens design that maintains a slim body profile. These camera improvements pair with a faster neural processing unit inside the A19 Pro chip, which accelerates on-device Apple Intelligence tasks such as real-time language translation during video calls and more sophisticated photo editing suggestions.

Thermal performance receives a quiet but meaningful upgrade. The iPhone 18 Pro models adopt a larger vapor chamber cooling system that sits closer to the main logic board. Early testing shared with supply chain partners indicates the new design can sustain peak GPU performance for nearly twice as long as the previous generation during intensive tasks like 4K video export or sustained augmented reality sessions. This matters particularly for the foldable model, which will likely share many internal components with the Pro lineup but must manage heat across a larger surface area when opened.

The Apple Watch update focuses on health sensing and battery life. Bloomberg’s reporting points to a new temperature sensor array capable of more precise cycle tracking for female users and improved heat stroke warnings for athletes. The Series 11 Watch, expected to appear alongside the phones, will also include a brighter always-on display that reaches 3000 nits outdoors, matching the latest iPhone screens. Battery capacity grows modestly through a more efficient power management chip, pushing average usage to nearly two days on a single charge for most users.

Design language across the new devices adopts softer edges and thinner bezels. The foldable’s hinge uses a multi-link mechanism that allows the two halves to sit completely flat when open, eliminating the slight tenting seen on many competing Android foldables. Materials remain premium, with titanium frames on the Pro and Ultra models and a new color palette that includes a deep navy and a warm titanium gold. The iPhone 18 Pro models retain the squared-off edges that have defined the Pro line since 2020 but reduce overall thickness by almost a millimeter through tighter component stacking.

Apple’s decision to skip a base iPhone 18 at this September event aligns with a broader strategy to stagger releases throughout the calendar year. Industry analysts expect a more affordable iPhone 18 model, possibly with a different display technology, to arrive in spring 2027. By separating the foldable launch from the volume-selling standard model, Apple can focus its marketing message on the new form factor without diluting attention across too many products. This approach mirrors the company’s handling of the original iPhone SE and the first Apple Watch Edition, where premium or experimental devices received dedicated spotlight events.

Supply chain preparations suggest the foldable will enter production later than the Pro models. Initial units may reach customers in limited quantities during the fourth quarter, with broader availability scheduled for early 2027. Apple has reportedly secured exclusive supply of ultra-thin glass from multiple vendors to reduce the risk of screen damage during repeated folding. Durability testing reportedly includes 400,000 open-close cycles, a figure that would support more than ten years of average daily use.

Software developers have already begun adapting popular applications to the new screen ratios. Major productivity apps such as Microsoft Office, Notion, and Adobe Lightroom have preview builds that automatically adjust toolbars and palettes when the device changes orientation. Gaming titles face interesting challenges and opportunities; some developers are experimenting with separate control schemes for folded and unfolded modes, effectively turning the closed device into a portable controller for the larger screen.

The health and fitness features on the new Watch tie directly into the iPhone’s expanded capabilities. When paired with the foldable, the Watch can display detailed workout metrics across the larger internal screen during indoor cycling or treadmill sessions, allowing users to follow guided classes without needing a separate tablet. Sleep tracking gains additional context from the phone’s new microphone array, which can detect snoring patterns and suggest positional changes to improve breathing quality.

Pricing remains a key question. Early indications place the iPhone Ultra starting near the current Pro Max tier, with the foldable premium adding roughly $300 to $400 over a comparable Pro model. Apple appears committed to offering the device with the same trade-in programs and financing options as its other flagships, lowering the barrier for users upgrading from older foldables or high-end Android phones.

The September 9 event will also likely include software announcements beyond iOS 19. WatchOS 12 will ship with the new Apple Watch and introduce customizable complications that react to the user’s current activity level. iPadOS 19 gains several of the multitasking features developed for the foldable, allowing existing iPad owners to benefit from the engineering work without purchasing new hardware.

As the John Ternus era begins, the company’s product decisions reflect a measured approach to innovation. Rather than flooding the market with incremental updates, Apple is concentrating resources on devices that introduce genuinely new interaction methods while maintaining the reliability customers expect. The foldable iPhone, the enhanced Pro camera system, and the longer-lasting Watch together form a cohesive vision for personal computing that stretches across form factors without forcing users to abandon familiar gestures or workflows.

The coming weeks will bring hands-on impressions, developer sessions at the fall WWDC follow-up, and detailed teardowns that reveal exactly how Apple solved the engineering problems inherent in folding glass and miniature cooling systems. For now, the September 9 stage will serve as the first official look at hardware that has been in development for more than five years, representing one of the most closely guarded projects in the company’s recent history. Attendees and viewers alike can anticipate a presentation that balances technical achievement with practical demonstrations of how these new devices fit into everyday routines, from morning briefings spread across two screens to evening workouts tracked by a smarter wrist companion. The combination of fresh industrial design, thoughtful software adaptation, and targeted hardware improvements suggests Apple intends to set a new standard for what a modern smartphone and its supporting wearables can accomplish together.



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Tuesday, 8 September 2026

GM’s Stubborn Bet Against CarPlay Faces Its First Crack in the Cadillac Lyriq

General Motors once seemed dead set on breaking up with Apple CarPlay and Android Auto. The decision drew sharp criticism from drivers who rely on familiar smartphone interfaces for navigation, music and calls. Yet the 2027 Cadillac Lyriq stands apart. It will keep both systems, wired and wireless. This single exception hints at deeper tensions inside the automaker’s software strategy.

Three years ago GM announced it would drop phone mirroring from future electric vehicles. Executives argued the move would reduce driver distraction. They claimed native systems deliver tighter integration with vehicle data, especially battery range and charging. Reuters first reported the shift in 2023, noting GM’s partnership with Google to build in-house infotainment.

CEO Mary Barra doubled down last year. In an interview on The Verge’s Decoder podcast she described switching between the car’s interface and CarPlay as “very clunky.” Barra signaled the change would extend beyond EVs to gas-powered models with the arrival of a new centralized computing platform around 2028. The company sees software subscriptions as a major profit driver, aiming for tens of billions in annual recurring revenue.

But reality has proven messier. Models like the 2026 GMC Hummer EV and base Chevrolet Silverado EV lost CarPlay and Android Auto during updates. Newer EVs such as the Cadillac Optiq and Vistiq never offered them. Production of the 2027 Lyriq begins soon in Tennessee. According to sources it will remain the last GM electric vehicle sold in North America with the features. GM Authority reported the exception in May.

Consumer pushback explains part of the hesitation. Surveys repeatedly show a majority of buyers view smartphone projection as a must-have. One study found 55 percent of drivers would walk away from a purchase without Apple CarPlay. And in August, Cadillac’s online configurator for 2027 models still listed both systems as standard. The brand responded carefully. “Cadillac is continuing to evolve its infotainment strategy across the EV portfolio, based on customer feedback, while also prioritizing the native, in-vehicle experience,” a representative told Carscoops.

That language marks a shift from earlier hard-line statements. No outright reversal. No promise the Lyriq will keep the features forever. Still, the delay raises questions about GM’s confidence in its own platform. The company has rolled out updated infotainment software with improved usability. It now offers native Apple Music through over-the-air updates on many models. Yet drivers complain the built-in experience feels slower and less intuitive than familiar phone mirroring.

GM isn’t alone in this tension. Other automakers have resisted full reliance on CarPlay or Android Auto to retain control over data and user relationships. Tesla and Rivian never adopted them. Mercedes has limited support in some markets. The financial incentive is clear. When an automaker owns the infotainment stack it captures far more of the software dollar than through vehicle sales alone. GM has said it keeps roughly 70 cents of every subscription dollar compared with pennies from hardware margins.

The Lyriq’s exception comes with other updates. The 2027 model adopts the North American Charging Standard port, gaining direct access to Tesla’s Supercharger network. Base pricing rises by $200. Range for the rear-wheel-drive version reaches 326 miles. These changes position the luxury crossover as a competitive offering in a segment where buyers expect polished technology. Cadillac needs the Lyriq to succeed as it expands its electric lineup with vehicles like the Escalade IQ.

Third-party workarounds have emerged for owners of newer GM EVs without native support. One $199 device called EV Play LT plugs into a USB port and restores CarPlay and Android Auto, at least for now. Its makers acknowledge GM could disable the functionality in future updates. The company previously instructed dealers to stop installing an earlier retrofit kit, citing safety and warranty concerns. The Verge covered that crackdown last year.

Meanwhile GM pushes forward with artificial intelligence. It plans to replace the current Google Assistant with Gemini across vehicles equipped with OnStar, starting with an over-the-air update. The goal is a conversational interface fine-tuned on vehicle-specific data for route planning, entertainment and more. Company statements describe an experience that anticipates driver needs without constant menu switching. Whether this proves compelling enough to overcome attachment to CarPlay remains untested at scale.

Recent coverage shows the story continues to evolve. In early August Autoblog noted the Lyriq exception could signal cracks in GM’s gamble. Customer feedback appears to be forcing a slower transition than first announced. The automaker still insists its direction aligns with an industry shift toward software-defined vehicles. Partnerships with Google and now deeper ties to Apple for native apps suggest a hybrid approach.

Industry watchers point to safety as one stated rationale. Executives once argued that phone mirroring creates inconsistency between interfaces and may distract drivers. Data from vehicle systems flows better when everything stays inside the native environment. Yet many owners simply want the system they already know and trust from their phones. They don’t want to learn a new interface or pay for subscription features that duplicate what their devices offer for free.

So the Lyriq becomes both outlier and test case. If sales remain strong with CarPlay included, pressure may grow to extend the option to other models. If GM successfully migrates most users to its native system and AI assistant, the exception could quietly disappear with the next refresh. For now the luxury brand is listening. The rest of the portfolio follows a stricter path.

Buyers in the market for a premium electric SUV will notice the difference. Those who prioritize familiar smartphone integration have one clear choice inside the GM family. Everyone else faces a future where the carmaker controls more of the digital experience inside the cabin. The bet is substantial. Success depends on whether drivers ultimately prefer the promise of deeper integration over the convenience they already hold in their pockets.



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The Robotics Readiness Gap: Why Leaders Expect Robot Fleets but Lack Plans to Manage Them

Business leaders see robots as teammates. They just aren’t ready for them yet.

A new Intel-commissioned study lays bare the contradiction. Six in 10 senior executives expect their organizations to run fleets of robots within five years. Only four in 10 have drawn up any formal strategy for a mixed human-robot workforce. The gap stands at 26 percentage points in manufacturing alone. And it widens in sectors such as defense.

The report, titled The Robotics Readiness Gap, surveyed 800 leaders from companies with more than $500 million in annual revenue across the US, UK, Germany, Japan, China and South Korea. Its conclusions feel urgent. Leaders believe full-scale robot deployment could double operational output. They also predict that, on average, buying and running a robot will prove cheaper than hiring a human in their industry inside three years. Yet preparation lags confidence.

The Five Barriers Slowing Scaled Adoption

Intel identifies five areas where readiness falls short: strategy, skills, safety, shape and scale. Strategy shows the widest disconnect. Sixty-seven percent of leaders feel confident their organizations will handle mixed workforces by 2030. Only 40 percent have plans on paper today. Skills follow close behind. Two-thirds think robots will make human employees more capable. At the same time, 40 percent say talent shortages already block them from moving past pilot projects.

Safety concerns have delayed deployments for 55 percent of respondents. Thirty-one percent point to safety as the area where robotics has delivered the most value so far. Sixty-eight percent say clearer global standards would speed things up. The shape of the machines matters less than performance. Seventy-seven percent of leaders care more about what robots can do than what they look like. Humanoids accounted for just 8 percent of interest in the survey. Yet the conversation around them dominates headlines.

John Healy, vice president and general manager of Intel’s Industrial and Robotics Division, put it plainly. “The next phase of robotics adoption won’t be defined by whether organisations can deploy robots, it will be defined by whether they’re ready to scale them.” The TechRadar analysis of the report captured the tension well. Robots won’t replace people. They will create new forms of collaboration. Or so the official line goes.

But history offers caution. Past waves of automation promised partnership and often delivered displacement. This time feels different because the machines are different. Advances in sensors, AI models and edge computing now let robots perceive, decide and act in unstructured environments. Physical AI has moved from lab demos to factory trials faster than many expected.

The International Federation of Robotics released its World Robotics 2025 report on the same day as Intel’s findings. Professional service robots grew 9 percent in 2024 to nearly 200,000 units sold. Transportation and logistics robots led the way with 102,900 units, up 14 percent. Robot-as-a-service models expanded 42 percent. Staff shortages drive much of this demand. An aging population pushes medical applications higher. The data shows steady if unspectacular growth in conventional automation.

Humanoids tell a more volatile story. Funding for general-purpose robotics jumped fivefold between 2022 and 2024, exceeding $1 billion annually, according to a McKinsey analysis from mid-2025. Patent filings rose at a 40 percent compound annual growth rate. China made embodied AI a national priority with a $138 billion fund. Startups such as Figure AI, Agility Robotics and 1X raised hundreds of millions. Production ramps remain modest. Agility aims to move from 1,200 Digit robots in 2025 to 7,500 by 2027. Chinese firms talk of thousands per year. Volumes still sit far below the millions needed to reshape labor markets.

Gartner struck a skeptical note in January 2026. Fewer than 20 companies will scale humanoid robots into production for manufacturing and supply chain by 2028, the firm predicted. Most deployments will stay in tightly controlled settings. Current models lack the dexterity, intelligence and cost-effectiveness required for dynamic warehouses. Abdil Tunca, senior principal analyst at Gartner, warned that the promise sounds compelling but the technology remains immature.

Yet ambition keeps rising. Amazon has openly discussed avoiding the need to hire more than 160,000 additional U.S. workers by 2027 through automation. Internal documents reviewed by The New York Times show executives targeting 75 percent automation of operations over time. The company already deploys more than one million robots globally. Its latest machines — Sparrow, Cardinal, Proteus — handle picking, packing, stacking and transport with growing sophistication.

Smaller factories have taken a different route. Instead of buying expensive systems outright, they rent robots. Formic offers units for about $23 an hour, comparable to human wages for tough shifts. The approach lets managers test automation on the dirtiest, most dangerous tasks without committing capital. Turnover drops when workers no longer spend entire shifts lifting heavy boxes. The model spreads faster than outright purchases ever could.

Labor reactions vary. Hyundai Motor workers in South Korea staged a partial strike after the company demonstrated its Atlas humanoid. The union insisted the robot would not reach the production line without agreement. In India, thousands of workers now wear cameras on their heads to record manual tasks. The footage trains AI models that may one day replace the very jobs being filmed. Bloomberg detailed the uncomfortable irony in an August 2026 feature.

Public sentiment splits along task lines. A Hexagon study released in June 2026 found adults most comfortable with robots in warehouses and factories. Sixty-three percent approve. Hospitals and schools score far lower. People want machines for heavy lifting, hazard monitoring and repetitive work. They draw firm lines around caregiving and teaching. Clear rules matter. Eighty-six percent say governance must define what robots can and cannot do.

Japan offers a preview. One in three firms already use or consider AI-powered robots, a Reuters poll showed in May 2026. Transportation equipment makers lead at 80 percent adoption intent. The government sees robotics as essential to offset chronic labor shortages. Japan built its industrial robot leadership on repeatable tasks inside safety fences. The new generation must operate alongside people in open spaces. That shift demands better perception, faster decision-making and tighter integration with human workflows.

STMicroelectronics announced plans in March 2026 to deploy more than 100 humanoids in its older European fabs. The move aims to avoid plant closures and layoffs. Humanoids would handle repetitive shifts, freeing workers for higher-skilled roles. One executive claimed a single humanoid could replace three out of four shifts in some cases. Retraining programs run in parallel. The strategy bets that productivity gains will protect jobs rather than eliminate them.

But will they? The Intel report insists this wave differs. “This isn’t about replacing people but creating new forms of human-machine collaboration, with robots working alongside employees as productive teammates.” The words echo every previous automation pitch. Outcomes have rarely matched the rhetoric. Real wages stagnated for many while capital owners captured gains. This time, the machines learn. They adapt. They multiply faster.

Scale remains the decisive hurdle. Five thousand units mark the line between laboratory curiosity and genuine factory output, one recent industry discussion noted. Most humanoid makers still operate well below that threshold. Supply chains for actuators, sensors and specialized chips have yet to mature. Energy demands grow with every added capability. Safety certification for collaborative robots in unstructured settings takes time.

Even so, the direction looks clear. Operational output could double at full deployment, leaders say. Cost curves bend downward. Performance improves monthly. The critical threshold Intel describes feels close. Organizations that close the readiness gap first will set the pace. Those that treat robots as simple labor substitutes may find the technology bites back in unexpected ways.

Skills will decide much of the outcome. Forty-one percent of surveyed leaders doubt their HR teams can plan for robot-inclusive workforces. Two-thirds expect robots to raise human skill levels. The contradiction sits at the heart of the debate. Collaboration requires new training, new metrics, new organizational designs. Functions that never spoke to each other must now align. Operating models built for human-only teams need redesign.

And the clock ticks. Three years until robots become cheaper than humans in many sectors, according to the executives polled. Five years until most expect robot fleets on site. The gap between expectation and preparation yawns wide. Closing it demands more than pilot projects. It requires strategy, investment in people, agreement on safety standards and honest reckoning with what the machines can actually do today.

Robot coworkers aren’t science fiction. They already appear in warehouses, chip fabs and test lines. Their numbers will grow. The question isn’t whether they arrive. It’s whether companies, workers and societies prepare for the mixed workplace they will create. The Intel report suggests many talk a good game. Fewer have started the real work. That gap may prove the most expensive mistake of the next decade.



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