Tag: mint – technology

  • X revamps creator revenue sharing to prioritize original posts and reduce engagement farming

    This article was generated by AI and cites original sources.

    Elon Musk-led social platform X is changing how it pays creators, aiming to reduce incentives for engagement farming and to direct revenue sharing toward original, high-quality content that adds value to the Timeline. According to X Product Head Nikita Bier, the update for the creator payout cycle will experiment with tools to identify original authors and will derank low-quality content—an approach that targets the mechanics of monetization rather than the content itself. The move follows months of criticism that X’s earlier payout rules rewarded accounts posting low-quality viral videos or clickbait to maximize impressions.

    What X is changing in its monetization mechanics

    X Product Head Nikita Bier outlined the rationale and mechanics of the revamp in a post on X. Bier stated that for the current payout cycle, X is “experimenting with new tools to identify original authors of content and allocating a portion of revenue to them.” The update also includes deranking low-quality content alongside incentivizing original, high-quality content that brings new value to the Timeline.

    Bier framed the policy shift in terms of how X’s revenue sharing should work. He wrote that reposts and commentary would “always be a core pillar of X,” but that the Revenue Sharing programme should not simply reward the accounts that “helped [content] travel furthest.” Instead, the programme should “reward[] the effort it takes to produce something,” with the stated goal of building “a richer Timeline.” Bier also said that the Revenue Sharing programme “will continue to evolve” to encourage creators to post “their best content” to X.

    Technically, the key change is the introduction of tools designed to identify original authors. While the source does not describe the specific technical method—such as how X determines originality or how it handles reposts, remixes, or commentary—the emphasis on “tools to identify original authors” indicates a shift toward attribution mechanisms within the payout pipeline.

    Why engagement farming became a focus

    The revamp arrives after months of criticism of X for promoting engagement farming. In this practice, accounts post low-quality viral videos or clickbait content to improve the number of impressions on their posts, which was a key factor in the X creator payout. In other words, the incentive structure rewarded distribution volume over content quality.

    Engagement farming becomes a systems problem when monetization relies on signals that can be gamed. X’s creator payout tied to impressions created incentives for the spread of low-quality content. By changing what counts and how revenue is allocated, X is attempting to modify the feedback loop between content performance metrics and payout outcomes.

    The updates could reduce the volume of clickbait-style posts while preserving legitimate reposting and discussion. Bier’s language that reposts and commentary remain a “core pillar” suggests X is attempting to preserve conversational distribution while adjusting monetization incentives.

    Prior payout changes: reply spam and impression counting

    This update is not X’s first adjustment to payout criteria. Earlier in the year, Bier announced another change: X stopped counting impressions on replies toward monetization payout in order to reduce “reply spam.” The platform now counts only organic views on the main homepage timeline toward payout.

    From a product perspective, these changes indicate that X’s creator payout system is sensitive to how different surfaces contribute to impressions. Moving from “replies” to “main homepage timeline” reduces the ability to manufacture payouts through low-effort reply activity. The new revamp extends that pattern by shifting revenue attribution from whoever “helped [content] travel furthest” toward the original author, using tools to identify who created the content in the first place.

    The sequence indicates that X is iterating on both (1) the signal sources that feed payout (organic views on the main homepage timeline) and (2) the attribution logic that determines who receives revenue for performance.

    Regional weighting proposal and leadership intervention

    The source also highlights an internal policy decision. Bier had proposed a change to the revenue sharing programme where X would give weight to impressions from the poster’s home region, intended to encourage content that resonates with people in that country. That proposal was vetoed by Elon Musk. Following criticism, Musk stated the policy was on “pause moving forward with this until further consideration.”

    This detail shows how creator monetization rules can intersect with questions of audience targeting, fairness, and localization. The veto indicates that X’s monetization strategy is actively being shaped, with leadership intervention when proposed changes trigger backlash.

    For industry observers, this suggests that payout programs can become a high-stakes policy surface: small changes to how impressions are weighted or counted can have significant effects on creator behavior. The combination of deranking low-quality content, experimenting with original-author identification, and revising impression sources reflects a broader trend in platform monetization—moving from simple performance metrics toward more complex ranking and attribution systems.

    What comes next

    The source notes that eligibility for X creator payout depends on meeting X’s monetization criteria, though specific criteria are not detailed in the available information. The described direction is specific: X will experiment with tools to identify original authors, allocate a portion of revenue to them, and derank low-quality content—while keeping reposts and commentary central to the platform.

    Given that X has already adjusted payout counting to reduce “reply spam,” the current update represents another iteration in the same design loop: modify the signals that drive payouts, observe creator behavior, then refine. Whether these changes measurably reduce engagement farming will likely depend on how well X’s originality tools and deranking mechanisms align with what users and creators consider “original” and “high-quality.” The source does not provide performance results or timelines beyond the announcement of the new payout-cycle experiment.

    Source: mint – technology

  • Pixel phones experiencing bootloop issues after March 2026 update; Google acknowledges problem and directs users to support

    This article was generated by AI and cites original sources.

    Google has acknowledged reports that some Pixel phones are becoming unusable after the March 2026 Pixel update. According to user reports collected on forums such as Reddit and Google’s official Issue Tracker, affected devices can get stuck in a bootloop—often halting on the “G” logo during startup—or repeatedly rebooting, entering Recovery mode, or showing messages that device data or the “Android system” might be corrupted. Google stated it is actively working to identify a fix and recommends contacting Pixel support for assistance.

    What users are reporting after the March 2026 Pixel update

    Following the March 2026 rollout, the issue appears to impact multiple Pixel models, including the Pixel 10, Pixel 8 Pro, Pixel 7a, Pixel 7 Pro, Pixel 10 Pro XL, and Pixel 6. Users describe startup failures with three recurring patterns:

    1) Bootloop on the “G” logo or initial boot screen: Several reports indicate the device is stuck on the initial startup display with the “G” logo, leaving the phone unusable.

    2) Repeated reboots or refusal to turn on: Some users report the device may not fully turn on, while others report it constantly reboots.

    3) Recovery mode and corruption-related errors: Some users report the device is forced into Recovery mode and displays errors indicating device data or the “Android system” might be corrupted.

    User reports illustrate how the failure can appear at different points in the boot process. One Pixel 6 user wrote: “When I boot my phone and was asked to enter my password, the phone turns to black screen, freezes and reboots itself after having entered the correct passcode. When I enter a wrong passcode it can identify that it’s wrong though.” Another user stated: “I am experiencing the same issue on a Pixel 6 and have tried sideloading March update multiple times with no luck. I am stuck in a bootloop.” A third comment noted: “The march OTA caused a lot of Pixel Phones to bootloop. They basically wont turn on and are completely unusable. Currently there is no real solution apart from factory reset which according to reports online is at least unreliable. So far Google hasnt addressed the issue properly.

    Google’s response and technical implications

    Google acknowledged the issue in a comment on its Issue Tracker, stating it has shared the problem with its engineering team and is “actively working to identify a fix.” The company also responded to various Reddit threads regarding the March update.

    Bootloops indicate a failure occurring early in the startup sequence, typically involving system components that must initialize correctly before the device reaches a stable state. The fact that users report being forced into Recovery mode and seeing corruption-related messages suggests the update may be triggering a condition where the device cannot reliably complete its normal boot sequence. However, the source does not provide technical details on the root cause.

    Google’s acknowledgment and statement that it is “actively working” on a fix indicates the issue has been escalated to engineering teams and is being tracked publicly via the Issue Tracker. For affected users, the immediate path forward is through support channels rather than self-service solutions, at least until Google releases a fix.

    What Google recommends and reported workarounds

    Google recommends reaching out to Pixel support immediately for assistance. Some users on Reddit have reported that starting the Pixel in Safe Mode while keeping it plugged in may help, though this is user-reported rather than an official solution.

    The distinction between official support guidance and community workarounds is important for users evaluating options. User reports indicate that factory reset may be the only available solution in some cases, though reports suggest this approach is unreliable. Because the source does not independently verify the reliability of factory reset in this situation, it should be understood as user testimony rather than confirmed guidance.

    Implications for Pixel users and the update ecosystem

    This incident highlights the operational risk that update pipelines can introduce when changes affect components required for boot. The problem is tied specifically to the March 2026 Pixel update and affects multiple models, including older devices such as the Pixel 6. While the report does not quantify how widespread the problem is, it demonstrates that multiple device models can be impacted.

    For the broader industry, the key implication concerns software lifecycle management: when an OTA update breaks startup behavior, the technical challenge involves both diagnosing the specific failure mode and restoring devices without causing further data loss. Google’s decision to publicly acknowledge the issue on the Issue Tracker and involve engineering suggests a structured process for isolating and resolving the problem, though the source does not provide a timeline for a fix.

    Until Google releases an update that prevents the bootloop, the practical guidance for affected users remains: contact Pixel support and, for emergencies, consider attempting Safe Mode while the device is plugged in.

    Source: mint – technology

  • OpenAI’s $100 ChatGPT Pro tier boosts Codex to match Anthropic’s Claude Code push

    This article was generated by AI and cites original sources.

    OpenAI has launched a new $100 per month ChatGPT subscription tier designed to compete with Anthropic’s Claude Code offering. The change centers on how much Codex usage subscribers can access, along with continued access to OpenAI’s “exclusive Pro model” and unlimited access to Instant and Thinking models—features OpenAI says are still part of the new Pro tier.

    According to OpenAI’s announcement on X, the new Pro plan provides “5x more Codex usage than Plus” and is positioned as best for “longer, high-effort Codex sessions.” OpenAI is also running a time-limited promotion that increases Codex usage for eligible users until May 31, while it adjusts how Codex usage is allocated for Plus subscribers going forward. (See mint – technology for the full details, including the stated pricing and the promotion window.)

    What OpenAI changed in ChatGPT Pro

    The headline change is a new subscription price point: $100/month. OpenAI says this new Pro tier still includes access to all Pro features, including the exclusive Pro model. OpenAI also states that the tier provides unlimited access to Instant and Thinking models.

    Where the tier differentiates is Codex usage. OpenAI says the new plan offers “5x more Codex usage than Plus.” In the same announcement, OpenAI frames the tier as suitable for “longer, high-effort Codex sessions.” That language suggests the company is shaping the experience around sustained coding workflows rather than short bursts, using usage limits as the mechanism to steer how people allocate time and compute for coding tasks.

    OpenAI is also offering a launch promotion. In its post, the company says it is “increasing Codex usage for a limited time through May 31st”. The promotion is targeted at Pro subscribers: “Pro $100 subscribers get up to 10x usage of ChatGPT Plus on Codex” to help users “build your most ambitious ideas,” as OpenAI put it.

    The promotion is time-bounded, and OpenAI says the Codex promotion for existing Plus members “will end today.” In addition, OpenAI says it is rebalancing Codex usage for Plus users to “support more sessions throughout the week, rather than longer sessions in a single day.” OpenAI’s stated framing indicates the company is not only changing total allowance tiers but also the distribution pattern of usage within a week.

    Pricing and the rest of OpenAI’s ChatGPT tiers

    OpenAI is not replacing its other plans. The company says it will continue to offer $200/month Pro alongside the $20/month Plus plan. It also continues to list an $8 “Go” plan and a free tier.

    OpenAI explicitly characterizes the Plus plan at $20 as the “best offer” for “steady, day-to-day usage of Codex,” while describing the $100 Pro tier as a “more accessible upgrade path for heavier daily use.” These statements matter because they show OpenAI is drawing a ladder between tiers based on expected user behavior—daily usage patterns for Plus versus heavier daily use for the new Pro tier, with longer sessions supported by increased Codex allowance.

    OpenAI CEO Sam Altman is also referenced in the same source. Altman had earlier announced that Codex had reached three million users, and that the company would reset usage for its users every million users. The mint – technology report links this context to the new subscription changes, placing them within an ongoing effort to manage Codex demand and usage accounting as the user base grows.

    Why usage limits are becoming the battleground

    This announcement reflects how AI coding tools are increasingly packaged as usage-based experiences. Instead of only differentiating models by capability, OpenAI is differentiating by how much Codex usage a subscriber can consume and how that usage is structured over time.

    OpenAI’s own language shows two levers:

    1) Total allowance by tier: The new Pro plan offers “5x more Codex usage than Plus.”

    2) Temporal allocation: OpenAI says it is rebalancing Plus Codex usage to support more sessions throughout the week rather than longer sessions in a single day.

    From a technology and product operations standpoint, these levers can affect compute scheduling, session planning, and how users design their coding workflow. The promotion—up to 10x usage for Pro $100 subscribers through May 31st—also indicates OpenAI can temporarily expand capacity or relax limits for a subset of users, then tighten back to the standard tier after the window closes.

    OpenAI’s approach also ties the subscription directly to Codex usage rather than only to access to models. While OpenAI highlights unlimited access to Instant and Thinking models in the Pro tier, the primary “upgrade” metric presented in the report is Codex usage. That suggests Codex is the product component most sensitive to demand and thus most likely to be metered through subscriptions.

    Competition with Anthropic: tier design echoes Claude Code

    The mint – technology report notes that OpenAI’s subscription structure now looks similar to Anthropic’s. Specifically, it states that OpenAI’s plan “look[s] eerily similar to Anthropic,” describing Anthropic’s tiers as Max 5x for its $100/month users and Max 20x for its $200/month tier users.

    OpenAI’s new tier provides 5x more Codex usage than Plus at $100/month, and the report frames this as part of OpenAI’s effort to rival Anthropic’s Claude Code popularity. The comparison matters because it shows how competitive pressure may push companies toward similar product packaging strategies—particularly when a key differentiator is the amount of coding-tool compute or usage a subscriber receives.

    The report also links OpenAI’s subscription revamp to broader competitive context, including references to OpenAI executing a “code red” to counter Anthropic’s dominance in the coding market, and a shift toward more professional tool work. It further notes that OpenAI has put other plans on hold or shut them down, such as the recent Sora video generator (as described in the source material). While those points extend beyond subscriptions, they provide context for why OpenAI is focusing on coding-related tooling and on tier mechanics that map to developer usage.

    As an industry signal, observers may watch whether usage-based tiering becomes a standard pattern for AI coding assistants—where the main product differentiation is how much “coding work” the subscription allows, and how that allowance is timed and reset as demand grows.

    Source: mint – technology

  • WhatsApp Encryption Disputed: Musk Questions Trust as Lawsuit Alleges Message Interception

    This article was generated by AI and cites original sources.

    Elon Musk renewed a public dispute with Meta on Thursday by questioning whether WhatsApp’s end-to-end encryption can be trusted. His comments came after a new class action lawsuit alleged that the app intercepted messages despite WhatsApp’s claims of end-to-end encryption protection. Meta’s response directly challenged the allegations and reiterated that WhatsApp uses end-to-end encryption based on the Signal protocol.

    The exchange centers on a technical claim: whether the cryptographic design behind end-to-end messaging is actually implemented in a way that prevents third-party access. In a market where messaging platforms compete on privacy properties, the dispute highlights how encryption architecture, legal claims, and third-party integrations intersect in public trust debates.

    Musk’s Challenge and the Lawsuit

    Responding to a post on X about the lawsuit, Musk wrote, “Can’t trust WhatsApp”. The class action lawsuit alleges that WhatsApp intercepted private messages of users despite the app’s claims of end-to-end encryption and shared those messages with third parties, including Accenture.

    In the same thread, Musk encouraged users to switch to X Chat for an encrypted chat experience, stating that it “comes with this great benefit of actual privacy.”

    From a technology standpoint, Musk’s argument challenges the end-to-end encryption trust boundary—specifically, who can access plaintext content and under what conditions. The lawsuit’s allegations center on the gap between encryption claims and alleged message handling in practice.

    WhatsApp’s Response: Signal Protocol Encryption

    WhatsApp responded to Musk’s claims, stating that the lawsuit allegations are “categorically false and absurd.” The company argued that WhatsApp has been end-to-end encrypted using the Signal protocol for a decade, and therefore “your messages cannot be read by anyone other than the sender and recipient.”

    According to WhatsApp’s FAQ, end-to-end encryption is used when users chat with another person using WhatsApp Messenger. The company states that “No one outside of the chat, not even WhatsApp, can read, listen to, or share them.” The FAQ describes messages as secured with a “lock,” with only the recipient and sender having the “special key needed to unlock and read them.”

    These statements describe a threat model in which the platform operator cannot decrypt message contents. The specific reference to the Signal protocol points to the cryptographic framework WhatsApp says it relies on for end-to-end guarantees.

    However, the underlying controversy remains centered on the lawsuit’s allegations. The dispute currently presents a clash between the platform’s stated encryption properties and the lawsuit’s claims about message interception and sharing with third parties.

    The Technical Dimensions of the Dispute

    End-to-end encryption is not merely a feature label; it represents a set of engineering decisions that determine what data is encrypted, where keys reside, and which components can access plaintext. Musk’s assertion that WhatsApp “can’t be trusted” and WhatsApp’s response that its encryption “cannot” be read by anyone other than sender and recipient map directly onto those engineering questions.

    The mention of third-party involvement (Accenture) points to a common real-world consideration for messaging systems: the boundary between cryptographic processing and operational workflows. If a platform’s end-to-end design truly prevents decryption by the service provider, then any claim that intercepted messages were shared with third parties would suggest either an implementation failure, a misunderstanding of what was intercepted, or a scenario outside the claimed end-to-end scope.

    The precision of WhatsApp’s FAQ language reflects the technical stakes. It claims that even WhatsApp itself cannot read, listen to, or share messages, and that only the “recipient and you” have the keys needed to unlock content. That specificity typically defines measurable behavior: if a platform can be shown to access content, the operational reality would conflict with the stated cryptographic model.

    Regulatory Scrutiny and Prior Complaints

    WhatsApp has faced scrutiny tied to end-to-end encryption claims previously. A report by Bloomberg earlier this year stated that US law agencies were investigating allegations raised by a former Meta contractor that the company can access WhatsApp messages despite end-to-end encryption claims. The investigation was said to be led by special agents with the US Department of Commerce.

    Additionally, Meta received a whistleblower complaint filed with the US Securities and Exchange Commission in 2024 raising similar concerns. This pattern suggests that encryption claims have drawn attention from both the legal system (via class action) and regulatory investigations.

    For the industry, this indicates that “end-to-end encryption” is increasingly treated as a compliance and trust topic, not only a product feature. Observers may watch whether public disputes and lawsuits lead to technical disclosures, audit results, or court findings that clarify what “intercepted” means in the context of WhatsApp’s claimed Signal-protocol-based encryption.

    In the meantime, Musk’s promotion of X Chat is positioned as a direct alternative for encrypted messaging and calls. The technical details of X Chat’s encryption are not provided in available sources, so the comparison remains at the level of user-facing claims rather than a technical comparison.

    What Comes Next

    The immediate timeline is clear: Musk questioned WhatsApp’s encryption trustworthiness on X, WhatsApp responded by citing the Signal protocol and detailed FAQ language, and the backdrop includes a new class action lawsuit plus earlier reporting about US investigations and a 2024 SEC complaint. The next meaningful developments would be how the lawsuit’s allegations are substantiated and how WhatsApp supports its end-to-end encryption claims in response.

    For technologists and privacy-focused users, the controversy underscores an operational reality: cryptographic assurances are only as credible as the implementation details and evidence presented when those assurances are challenged. The dispute between public claims and legal allegations will likely remain a focal point for how messaging platforms communicate encryption guarantees and how those guarantees are tested in practice.

    Source: mint – technology

  • India’s 5G scale-up targets: more than a billion 5G users by 2030 and the infrastructure stack behind it

    This article was generated by AI and cites original sources.

    India’s Union Minister of Communications, Jyotiraditya M Scindia, said the country is on track to reach over a billion 5G users by 2030, citing what he described as rapid network buildout and earlier growth milestones. Speaking at AIMA’s 11th National Leadership Conclave (as reported by mint), Scindia tied the 5G growth target to specific deployment figures—500,000 towers and ₹450,000 crore in capex—along with a broader infrastructure narrative that includes 6G, DPI infrastructure, and the United Payments Interface (UPI).

    The statement matters for technology watchers because it frames India’s telecom progress not only as consumer adoption, but as a stack of network and digital infrastructure projects—some oriented toward connectivity (5G, fibre) and others toward application-layer systems (UPI). While the remarks are policy- and program-oriented, they also point to engineering and deployment choices that determine how quickly networks can scale and how services can run on top of them.

    5G rollout metrics and the adoption curve

    Scindia’s remarks anchored the 5G target in deployment and adoption numbers. He said India had the fastest 5G rollout in the world and cited 500,000 towers alongside ₹450,000 crore worth of capex. He also described a short adoption window: in four years, 400 million consumers reached 5G.

    From there, he projected a growth trajectory: 5G consumers will go from 400 million to over a billion by 2030. In other words, the minister’s thesis is that early scale in tower deployment and capital investment can translate into a rapid expansion of end-user adoption—provided the network capacity and coverage keep pace with demand.

    For technologists, the key takeaway is that the target is tied to measurable infrastructure indicators (tower counts and capex) and a measurable user milestone (400 million within four years). Even without additional engineering details in the source, this framing suggests that India’s 5G program is being managed as a capacity-and-coverage buildout problem, not just as a service launch.

    From 4G execution to 5G scale—and a stated 6G direction

    Scindia said India “followed the world on 4G” and “marched with the world on 5G,” then added that India “will lead the world in 6G.” The source also reports that he positioned India’s digital infrastructure efforts as parallel tracks: he referenced DPI infrastructure and UPI as examples of systems that scale through both infrastructure and operational throughput.

    In telecom terms, the move from 4G to 5G is often described as a transition in radio technology and network architecture. The source does not provide technical specifications about India’s 6G plan, so any interpretation of what “lead” would mean technically would be speculative. However, his comments do indicate a narrative continuity: 5G rollout is presented as a platform for subsequent generations, with 6G framed as a future leadership objective.

    That matters because next-generation cellular rollouts depend on coordinated work across spectrum strategy, device ecosystem readiness, and network software evolution. Even without those details here, the way Scindia linked 5G to 6G implies that the industry may be expected to maintain momentum in research, standards engagement, and deployment planning while 5G adoption continues.

    The “DPI + UPI” analogy: infrastructure that scales transactions

    Beyond cellular networks, Scindia cited India’s “DPI infrastructure” and UPI as examples of infrastructure systems that can scale in operational terms. He said: “Think about it, 20 billion transactions a month. USD 3.4 trillion dollars exchanged over our UPI infrastructure.”

    These figures provide a different measurement lens than tower counts or subscriber numbers: they emphasize application-layer throughput and transaction volume. In the minister’s analogy, 5G rollout speed and 6G leadership ambition are paired with digital infrastructure capability, suggesting that connectivity and digital services are being treated as mutually reinforcing.

    For observers, the implied technology question is how these systems interact. The source does not describe technical dependencies between 5G and UPI, so it’s not possible to assert that one directly enables the other. Still, the inclusion of UPI transaction scale in the same remarks as telecom rollout metrics suggests that policymakers and industry leaders may be looking at end-to-end digital capacity: network availability, performance, and the ability of digital platforms to handle large volumes.

    Fibre connectivity, BharatNet, and the broader infrastructure framework

    Scindia also discussed connectivity infrastructure through the BharatNet program. He cited ₹1.39 lakh crore as the program’s value and said 55 per cent of the funds went toward operational expenses to maintain fibre connectivity across every village for ten years.

    This detail is technically relevant because fibre networks are not only about deployment; they require ongoing maintenance and operations to preserve performance. By highlighting operational expenses and a ten-year maintenance horizon, the source indicates an emphasis on lifecycle management rather than one-time construction.

    He also described India reaching an “inflection point” and pointed to a “3S” framework consisting of Stability, Scalability, and Strategic Autonomy. The source does not define how this framework is implemented in technical terms, but it provides a policy framing that may guide how telecom and digital infrastructure programs are prioritized.

    Separately, the minister projected a transformation for India Post into a logistics powerhouse. He said India Post recorded revenues of ₹13,280 crore in the 2024-25 fiscal and aimed for double-digit growth in the latest fiscal, with a goal to transition from a “government cost centre to a profit center by the year 2029-30.” While this is not telecom technology per se, it extends the infrastructure theme into logistics operations—areas that increasingly depend on digital systems for routing, tracking, and service delivery. The source does not provide specific technology plans for India Post, so any deeper linkage would be conjecture.

    Why the billion-user target matters for the tech ecosystem

    If India’s stated trajectory holds, the engineering challenge shifts from early rollout to sustained capacity scaling. Scindia’s cited numbers—400 million 5G consumers in four years, with a plan to reach over a billion by 2030—suggest that the network must support a growing base of users over time, not just deploy towers. The source also ties the rollout to large-scale investment (₹450,000 crore capex), which may reflect the cost profile of densification, backhaul, and spectrum-related deployment.

    At the same time, the inclusion of DPI infrastructure and UPI transaction scale in the same remarks suggests that the broader digital stack is part of the same strategic storyline. For the technology industry, this could mean that connectivity targets and digital service performance targets are being discussed together, potentially influencing how companies plan for network readiness, application performance, and operational scaling.

    Finally, the “lead the world in 6G” statement indicates that the industry may continue to monitor how quickly near-term deployment goals transition into longer-term standards and research efforts. The source does not provide a 6G roadmap, so readers should treat that as a direction rather than a detailed plan. Still, it positions 5G rollout as a step in a longer generational strategy.

    Source: mint – technology

  • Meta Unveils Muse Spark, First AI Model From Superintelligence Team

    This article was generated by AI and cites original sources.

    Meta Platforms unveiled Muse Spark on Wednesday, the first artificial intelligence model from a team it assembled last year to advance its AI capabilities. The launch comes as U.S. tech companies face pressure to demonstrate that substantial AI investments will translate into usable products and measurable competitive advantage.

    Meta’s Investment in AI Talent and Infrastructure

    Meta’s move reflects significant commitments to AI development. The company hired Scale AI CEO Alex Wang last year under a $14.3 billion deal and offered some engineers pay packages of hundreds of millions of dollars to staff a new superintelligence team. Muse Spark is the first model to emerge from that group, which is pursuing machines that can outthink humans.

    Muse Spark: Design and Deployment

    Meta initially plans to make Muse Spark available only on the Meta AI app and website. In the coming weeks, the model will replace the existing Llama models that currently power chatbots on WhatsApp, Instagram, Facebook, and Meta’s collection of smart glasses.

    According to Meta’s blog post, Muse Spark is “small and fast by design,” while capable enough to “reason through complex questions in science, math, and health.” The company did not disclose the model’s size, a key metric typically used to compare an AI system’s computing power. Internally, Muse Spark is part of a family of models known as Avocado.

    Extended Reasoning Capabilities

    Meta also released Contemplating mode, which runs multiple AI agents in parallel to boost reasoning power. This approach is comparable to extended thinking modes offered by Google’s Gemini Deep Think and OpenAI’s GPT Pro.

    User-facing examples for Muse Spark include estimating calories in a meal from a photo and superimposing an image of a mug on a shelf to preview how it looks—capabilities that some competitors already offer.

    Strategic Implications

    Meta’s approach combines model deployment across its platforms with reasoning features designed to enhance user interactions. By rolling out Muse Spark first on Meta AI and then replacing Llama-powered chatbots across multiple properties, the company appears to be operationalizing its superintelligence team’s work at scale. The company is betting that applying these AI capabilities to everyday personal tasks will help it leverage its more than 3.5 billion users across its social media platforms, potentially providing an advantage over rivals with smaller user bases.

    Source: mint – technology

  • WhatsApp Introduces Usernames: A New Way to Connect Without Sharing Phone Numbers

    This article was generated by AI and cites original sources.

    WhatsApp has started rolling out a new feature that allows users to communicate through usernames, eliminating the need to share phone numbers, reports WABetainfo. The feature is currently accessible to a select group and will gradually expand to more users in the upcoming weeks.

    The usernames feature is designed to enhance privacy and security on the messaging platform. Users can select a unique username, enabling them to connect with others without divulging their phone numbers. This functionality ensures a secure communication environment and simplifies contact discovery.

    To check if you have access to this feature, navigate to your profile settings on WhatsApp. Eligible users will find an option to create a username, with specific character criteria set by WhatsApp. Usernames must be 3 to 35 characters long, containing at least one letter and allowing lowercase letters, numbers, periods, and underscores.

    Furthermore, to prevent confusion with official websites, usernames cannot start with ‘www.’ or end with domain extensions like ‘.com’ or ‘.net.’ Additionally, usernames must be unique across the Meta ecosystem, meaning that if a username is claimed on Facebook or Instagram, it cannot be used on WhatsApp.

    With this new feature, WhatsApp aims to offer a more personalized and secure messaging experience to its users, allowing for seamless communication while maintaining privacy. As the rollout progresses, more individuals will benefit from this new way of connecting online.

    Source: mint – technology

  • X Launches AI-Powered Photo Editor for iOS Users

    This article was generated by AI and cites original sources.

    X has introduced a new AI-powered photo editing feature for iOS users. The in-app editor allows users to edit images using natural language commands, leveraging Grok AI technology. X Product Head Nikita Bier announced the rollout, noting that Android support is planned.

    The image editing feature enables users to interact with Grok AI within the X app, instructing the AI assistant to perform tasks like adding blur effects or making specific changes to images. The rollout has been cautious, likely in response to previous concerns about Grok AI generating inappropriate content based on user requests.

    This move aligns with X’s efforts to enhance user experience while addressing past issues. The integration of AI technology into the platform offers users more creative and intuitive ways to engage with visual content.

    Source: mint – technology

  • Vivo T5 Pro 5G Announced with Snapdragon 7s Gen 4 and 9,020mAh Battery

    This article was generated by AI and cites original sources.

    Vivo has announced the launch date of the Vivo T5 Pro 5G in India, scheduled for April 15th at 12 PM. The mid-range smartphone will feature the Snapdragon 7s Gen 4 processor, similar to the chip in Redmi Note 15 Pro+ and Motorola Edge 70 Fusion. Key features include a 9,020mAh battery and a 1.5K AMOLED display running on OriginOS 6 based on Android 16.

    Leaked details suggest a 6.8-inch AMOLED panel with a 144Hz refresh rate and a 50MP Sony IMX882 primary camera capable of 4K video recording. The device is expected to support 90W wired fast charging, but wireless charging may not be included. Additionally, the Vivo T5 Pro 5G could offer IP68/IP69 water and dust resistance.

    The phone is anticipated to come in Glacier Blue and Cosmic Black color options, with a speculated starting price slightly above ₹30,000 in India. Stay tuned for the official launch event to learn more about Vivo’s latest mid-range offering.

    Source: mint – technology

  • X Platform Experiences Third Outage, Impacting Users’ News Feeds

    This article was generated by AI and cites original sources.

    Elon Musk’s microblogging platform X is currently experiencing its third outage, affecting thousands of users in the US. Reports indicate users are encountering difficulties such as feed loading failures, login issues, session timeouts, and app crashes. This recent disruption follows previous outages that impacted global users, with complaints ranging from feed refresh problems to posting errors.

    According to outage monitoring site Downdetector, users in cities like Chicago, Los Angeles, and New York have flagged issues with X, with over 2000 reports logged. Despite the widespread problems, X has not issued any official statement addressing the outage.

    Previous incidents on X have highlighted the platform’s vulnerability to technical disruptions, with prior outages prompting thousands of user complaints. The recurring nature of these issues raises concerns about X’s stability and reliability as a communication tool.

    While users express frustration over the current outage, the lack of communication from X adds to the uncertainty surrounding the platform’s performance and user experience.

    Source: mint – technology