Apple AI now runs on Google, Nvidia tech: What happens to privacy promise

Apple AI now runs on Google, Nvidia tech: What happens to privacy promise


At the Worldwide Developers Conference (WWDC) 2026, Apple unveiled its biggest expansion of Apple Intelligence since the platform was first introduced in 2024. The company also announced Siri AI, a completely rebuilt version of Siri that can understand personal context, search across emails, messages and photos, answer questions using web information, and perform actions across apps. Apple noted that the latest generation of Apple Intelligence relies on technology developed in collaboration with Google and cloud infrastructure powered by Nvidia GPUs.

 


The disclosure marks a significant evolution from the original Apple Intelligence vision unveiled in 2024, when Apple emphasised that its AI strategy would rely heavily on on-device processing and an in-house privacy-focused cloud system known as Private Cloud Compute. Despite the shift, Apple insists its approach to privacy has not changed.

 
 


The question now is whether Apple is maintaining that promise while increasingly relying on infrastructure and technology beyond its own walls.


Apple’s privacy-first AI strategy began in 2024


When Apple Intelligence debuted at WWDC 2024, Apple sought to distinguish itself from rivals by positioning privacy as a core feature rather than an afterthought. The company argued that many AI tasks should run directly on users’ devices whenever possible. For more computationally demanding requests, Apple introduced Private Cloud Compute (PCC), a cloud-based architecture designed to extend Apple’s privacy protections beyond the device.

 


Apple described Private Cloud Compute as a system where user data would only be processed for the duration of a request, would not be stored, and would remain inaccessible even to Apple itself. The company also said security researchers would be able to independently inspect and verify the architecture.

 


At the time, Apple’s message was clear: users could access advanced AI capabilities without handing over their personal information to cloud providers. That privacy-centric approach became one of the defining pillars of Apple Intelligence.


What changed in 2026


The biggest change is not in Apple’s privacy messaging. It is in the technology stack powering Apple Intelligence. In January 2026, Apple and Google announced a multi-year collaboration under which the next generation of Apple Foundation Models would be based on Google’s Gemini models and cloud technology. The companies further stated that Apple Intelligence would continue to run on Apple devices and Private Cloud Compute while maintaining Apple’s privacy standards.

 


That partnership became more visible at WWDC 2026. Apple’s Security Research documentation states that the latest family of Apple Foundation Models was built in collaboration with Google. Apple also revealed that its cloud-based AI infrastructure now extends to Nvidia GPUs operating within Google’s cloud infrastructure.

 


Amar Subramanya, Apple’s vice president responsible for AI technologies, said the company works with both Google and Nvidia to extend Private Cloud Compute to Nvidia GPUs running in Google’s cloud while maintaining Apple’s privacy guarantees. In practical terms, this means some of the most advanced Apple Intelligence workloads no longer rely exclusively on Apple’s own server infrastructure. Instead, they can be processed using Nvidia hardware operating within Google Cloud environments. That represents one of the most significant architectural shifts since Apple Intelligence was introduced.


Why did Apple turn to Google and Nvidia


The answer largely comes down to capability and scale. At WWDC 2026, Apple introduced a significantly more capable version of Siri than the one it first showcased in 2024.

 


Siri AI can understand personal context, search across messages and emails, retrieve information from photos, understand on-screen content, answer questions using information from the web, perform actions across apps, and maintain conversations across devices. These capabilities are far more demanding than traditional voice assistant tasks. But what could have led to the shift?

 


An earlier report by The Information suggested that the increasing computational requirements of advanced AI models may have influenced Apple’s decision to partner with Google and Nvidia. Further, Nvidia’s role addresses another challenge: compute. Large AI models require specialised processors capable of handling massive inference workloads, and Nvidia’s GPUs have become the industry standard for running advanced AI systems at scale.

 


Then comes the point of scale. According to Counterpoint Research, Apple had cumulatively shipped more than 450 million Apple Intelligence-capable iPhones by the first quarter of 2026. As per the report, Apple currently has the largest installed base of GenAI-capable smartphones among all smartphone brands.

 


That figure only accounts for iPhones. Apple Intelligence features are also accessible on iPads, Macs, Apple Watches, and Vision Pro devices, significantly increasing the number of users who could potentially use these features.

 


Supporting AI services for such a large installed base requires enormous computing resources. In that context, Google’s cloud infrastructure and Nvidia’s GPUs provide Apple with capabilities that would be difficult and expensive to replicate quickly using only its own infrastructure.

 


However, if the integrations between the companies run this deep, then how will Apple maintain the privacy guarantees that have been central to its AI strategy since 2024? Part of the answer lies in a technology Apple is now using alongside Private Cloud Compute: Nvidia’s Confidential Computing.


What is Nvidia’s Confidential Computing


A key component of Apple’s updated architecture is Nvidia’s Confidential Computing technology. To understand why it matters, it helps to understand how data is typically protected.

 


Most digital systems encrypt data while it is stored and while it travels across networks. However, during computation, data becomes exposed during processing. Confidential Computing aims to close that gap.

 


The technology creates a protected execution environment that helps keep data secure even while it is actively being processed. Nvidia says its Confidential Computing technology uses hardware-based Trusted Execution Environments (TEEs) to protect data while it is being processed and help prevent unauthorised access.

 


The technology has become increasingly important as AI models grow larger and require powerful cloud-based GPUs to perform inference and reasoning tasks. Nvidia has positioned Confidential Computing as a way for enterprises and governments to run sensitive AI workloads while maintaining strong security protections. Apple is now using that same technology as part of its broader AI infrastructure.


How Private Cloud Compute and Confidential Computing work together


Although Apple and Nvidia are both talking about privacy and security, they are solving different problems.

 


Private Cloud Compute is Apple’s privacy architecture. Apple’s Private Cloud Compute architecture governs how requests are processed, limits what data can be accessed for a task, prevents retention of personal information after processing, and allows independent researchers to verify the software running on its servers.

 


Nvidia’s Confidential Computing technology focuses on the hardware environment used for computation. It secures the hardware environment where AI processing occurs, including protecting memory, encrypting active workloads, and safeguarding computations from unauthorised access.

 


In simple terms, Apple defines the privacy rules, while Nvidia helps secure the hardware running those rules. The two systems are complementary rather than interchangeable. Put simply, Apple’s Private Cloud Compute governs the privacy model for AI requests, while Nvidia’s Confidential Computing technology helps secure the infrastructure on which those workloads run.


Has Apple really changed its privacy approach?


This is where the debate becomes more nuanced. Apple’s public position is that its privacy guarantees remain unchanged. The company says user requests processed through Private Cloud Compute are still protected, data is not stored after processing, and personal information remains inaccessible to Apple, Google, or other third parties.

 


However, there is a meaningful difference between Apple’s 2024 and 2026 architectures. In 2024, Apple controlled nearly every layer involved in cloud-based AI processing. The company designed the hardware, operated the infrastructure, controlled the software stack, and defined the privacy architecture.

 


In 2026, Apple still controls the privacy architecture and the rules governing how data is handled. But some of the underlying infrastructure is now supplied by Google and Nvidia. That distinction matters because it shifts the discussion away from privacy alone and towards ownership. The real shift is not necessarily privacy, but control.

 


Apple no longer owns every layer of the stack supporting Apple Intelligence. Instead, it is extending its privacy architecture onto infrastructure supplied by external partners. That is a different proposition from the one Apple presented when Apple Intelligence first launched.

 


At the same time, it does not automatically mean Apple has abandoned its privacy commitments. The company’s argument is that the privacy protections users receive are determined by the architecture governing the system, not by who owns the physical servers or chips.


The bigger question


The broader challenge for Apple is no longer building AI features. It is convincing users that those features can scale without compromising the trust that has differentiated Apple from many of its rivals.

 


As Apple Intelligence expands across hundreds of millions of iPhones, iPads, Macs, and other devices, the company will increasingly rely on partnerships that were largely absent from its original AI strategy. Google provides key models and cloud technologies, while Nvidia supplies the hardware that powers some of the underlying AI workloads.

 


For users, the ultimate test will not be who provides the infrastructure, but whether Apple’s privacy safeguards continue to work as advertised. If Private Cloud Compute delivers the same protections regardless of whether workloads run on Apple-designed systems or on infrastructure supplied by partners, most users are unlikely to object.

 


WWDC 2026, therefore, marks an important evolution in Apple’s AI strategy. The company is no longer attempting to build every layer of the stack on its own. Instead, it is combining its privacy architecture with technologies from some of the biggest players in AI. Whether that approach strengthens Apple Intelligence without weakening trust is a question that will only be answered as these features roll out to users over time.


What Apple announced at WWDC 2026


The infrastructure discussion matters because it underpins a major expansion of Apple Intelligence.

 


The centrepiece of WWDC 2026 was Siri AI, a rebuilt assistant capable of understanding personal context, maintaining conversations, searching across apps, understanding on-screen content, and retrieving information from the web.

 


Apple also announced:


  • Spatial Reframing, Extend, and upgraded Clean Up tools in Photos

  • AI-powered tab organisation, page monitoring, and extension generation in Safari

  • Photorealistic image generation through Image Playground

  • Intelligent suggestions in Messages and Mail

  • Call Context, which surfaces relevant information during phone calls

  • Natural language event creation in Calendar

  • Describe a Shortcut for generating automations using natural language

  • AI-powered search and summaries in the Home app

  • Expanded accessibility features powered by Apple Intelligence



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INR surges amid sharp pull back in oil prices;  Sensex and Nifty jump by around 2%

INR surges amid sharp pull back in oil prices; Sensex and Nifty jump by around 2%


The Indian rupee surged 67 paise to close at 95.18 (provisional) against the greenback on Friday as global oil prices fell sharply after US President Donald Trump indicated an imminent deal with Iran. A firm trend in domestic equity markets and a weaker American currency also supported the rupee during the day. Indian shares closed Friday’s session on a buoyant note in a broad-based rally, with both frontline and broader market indexes posting sharp gains. The BSE Sensex settled at 75,527.95, surging 1,695.40 points (2.30%), and the NSE Nifty50 ended at 23,622.90, climbing 461.30 points (1.99%). Trump has reportedly said a deal to end the war with Iran is nearly complete, and is expected to be signed over the weekend in Europe, as he called off military strikes on the Islamic Republic hours after threatening to take control of its oil industry.

 

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Disclaimer: No Business Standard Journalist was involved in creation of this content

First Published: Jun 12 2026 | 5:04 PM IST



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Sensex, Nifty up 2%, Bank Nifty tops 56,800 amid softer crude and hopes of easing West Asia tensions

Sensex, Nifty up 2%, Bank Nifty tops 56,800 amid softer crude and hopes of easing West Asia tensions


Equity benchmarks rallied sharply on Friday as easing geopolitical tensions in West Asia, optimism surrounding a potential US-Iran peace deal, and a significant decline in crude oil prices boosted investor sentiment.

The BSE Sensex ended 1,695.40 points or 2.30 per cent higher at 75,527.95, while the Nifty 50 climbed 461.30 points or 1.99 per cent to close at 23,622.90.

Over the week, Sensex rose 1.7 per cent, and Nifty 50 was up 1 per cent.

Bank Nifty outperformed the broader market with a gain of nearly 3 per cent, ending at 56,814.80. The index rose 4.2 per cent this week.

The rupee strengthened during the session, supported by lower crude prices and improved global sentiment. Precious metals also moved higher.

According to Hariprasad K, SEBI-registered Research Analyst and Founder of Livelong Wealth, market sentiment was further supported by softer-than-expected US inflation data, which revived expectations of a more supportive global interest rate environment.

Banking, financials and realty lead gains

Broader markets outperformed, with the Midcap 100 and Smallcap 100 indices advancing 2.4 per cent and 2.8 per cent, respectively.

On the sectoral front, banking, financial and realty have witnessed strong buying due to improving liquidity management measures and macro stability.

Banking stocks led the gainers following RBI’s latest liquidity management measures aimed at stabilising foreign currency inflows and supporting institutions accessing overseas funds. Kotak Mahindra Bank, ICICI Bank, and HDFC Bank were among ⁠the top weekly gainers

IT extends losing streak

Nifty IT remained the only exception to the broader market rally and declined for the eighth consecutive session.

Continued concerns around global technology spending, AI disruption and uncertainty regarding US demand kept investors cautious towards export-oriented technology stocks.

Top Nifty 50 movers today: Shriram Finance, Bajaj Finance top gainers

Among the Nifty 50 constituents, Shriram Finance, Bajaj Finance, L&T, IndiGo and TMPV were the top gainers, while Nestle India, ONGC, Tech Mahindra and Tata Consumer Products were among the major laggards.

Market breadth remained firmly positive. Of the 4,422 stocks traded on the BSE, 3,222 advanced, 1,046 declined and 154 remained unchanged. A total of 102 stocks touched their 52-week highs, while 79 slipped to their 52-week lows. Additionally, eight stocks were locked in the upper circuit and six hit the lower circuit.

Midcap & smallcap movers

In the midcap segment, Ashok Leyland, LTF, Motilal OFS and HPCL surged 7-10 per cent. Oil India, Premier Energies, Coforge, Persistent Systems and Lenskart declined up to 2 per cent.

Among smallcaps, IFCI, Netweb, Inox Wind and Cholamandalam Holdings rallied 9-20 per cent, while Gland Pharma fell 2 per cent.

On the BSE, IFCI, Authum Investments and MTAR Tech were among the top movers. Cemindia Projects, Nestle India, Oil India, ONGC and Inox India declined 2-4 per cent.

Market outlook

Pravesh Gour, Senior Technical Analyst at Swastika Investmart, said the signs of progress in negotiations between the US and Iran have reduced geopolitical risk, improved global risk appetite and encouraged investors to move back into equities. “The resulting decline in crude oil prices is especially beneficial for India, as it helps ease inflationary pressures and improves the country’s macroeconomic outlook,” he said.

Vinod Nair, Head of Research at Geojit Investments, said India has faced challenges from US tariffs and the energy-driven shock, although conditions on both fronts have improved.

“The upcoming US Fed meeting is drawing heightened attention as markets assess the balance between growth and persistent inflation pressures. Strong domestic liquidity continues to provide an important buffer against recurring global macro shocks, helping absorb foreign outflows and stabilize market sentiment,” he said.

According to Nair, any moderation in FII selling or greater clarity on the US Federal Reserve’s policy trajectory could act as a catalyst for domestic capital and trigger a broad-based breakout in equities.

Dr Ravi Singh, Chief Research Officer at Master Capital Services, said markets may remain volatile due to global developments and economic data releases, but the overall undertone remains positive.

“Markets may continue to remain volatile because of global developments and economic data, but the overall undertone still looks positive as long as crude prices stay under control and institutional buying continues,” he said.

On the domestic front, the key monitorables will be India’s Consumer Price Index inflation data today and Wholesale Price Index inflation data next week, according to Siddhartha Khemka – Head of Research, Wealth Management, Motilal Oswal Financial Services.

Asian markets ended higher on Friday, tracking overnight gains on Wall Street, supported by enthusiasm surrounding SpaceX’s IPO debut. European markets traded higher as well.

Overnight, US markets rebounded sharply, with the Dow Jones, S&P 500 and Nasdaq rising 1.9 per cent, 1.8 per cent and 2.5 per cent, respectively, amid easing geopolitical concerns and optimism around SpaceX’s market debut.

FIIs offloaded equities worth ₹1,987.09 crore on Thursday, according to exchange data.

In previous session, Sensex closed 150.63 points lower at 73,832.55, and Nifty 50 edged lower by 53.35 points to 23,161.60.

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Published on June 12, 2026



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From Reels to risks: How scammers are turning videos into malware traps

From Reels to risks: How scammers are turning videos into malware traps



You are scrolling through Instagram when a video appears showing how to unlock Spotify Premium for free. The clip has a polished voiceover, simple step-by-step instructions, and more than 100,000 views. It looks no different from the countless tutorials users save and revisit every day. You follow the steps. Days later, your passwords, financial information, and stored credentials are in someone else’s hands.

 

That scenario is no longer hypothetical. Researchers at ReversingLabs recently uncovered two separate cybercrime campaigns operating through TikTok and Instagram Reels, using tutorial-style short videos to trick users into downloading malware or handing over sensitive information through malicious websites. The attacks succeed not because they are highly sophisticated, but because they feel familiar, carefully designed to blend into platforms users already trust.

 
 


At the centre of these campaigns is VidarStealer, a malware-as-a-service infostealer built to harvest passwords, browser data, cryptocurrency wallet information, and other credentials. With subscriptions reportedly starting at around $300, the tool has dramatically lowered the barrier to entry for cybercriminals, making large-scale social media scams easier and cheaper to launch than ever before.


How social media became a malware playground


Researchers at cybersecurity firm ReversingLabs (RL) have documented two social engineering attack techniques that target users through short-form videos, primarily on TikTok and Instagram Reels. The campaigns, which promise free access to paid software like Spotify Premium and Microsoft Word, represent a significant evolution in how phishing operates. Instead of phishing emails, cybercriminals are now hiding in plain sight on social media, blending their schemes into the creator content users trust and engage with daily.

 


People are already looking for scams in their email inboxes and text messages, but not as much on their social media feeds, especially when posts are framed as being helpful rather than carrying the urgency or sob stories associated with stereotypical phishing attempts.

 


That shift in framing is precisely what makes these campaigns effective. A tutorial about unlocking Spotify Premium looks, in every respect, like the thousands of legitimate life-hack videos that populate a user’s feed. There is no misspelled domain name in a subject line, no unfamiliar sender. There is just a video, and it looks like every other video.

 


Using social media is free and rewards frequent uploads. By using multiple platforms, accounts, and posts, attackers are able to access many users. The economics are attractive: no bulk email infrastructure, no cost per send, and a built-in recommendation engine willing to do the distribution work.


The growing role of social media as a search and discovery platform


Social media platforms are no longer just spaces for entertainment; they have quietly become the internet’s new search layer. Google itself has confirmed that over 40 percent of Gen Z prefer Instagram or TikTok over Google for search, while Google usage among Gen Z has dropped by nearly 25 percent compared to Gen X. According to GRIN’s report, The Power of Influence, Instagram now leads product discovery among Gen Z at 30.4 percent, followed by TikTok at 23.2 percent, with Google trailing at 18.8 percent. Users are not just passively scrolling; they are actively searching for software guides, tech fixes, and product recommendations through the feed.

 


This behavioural shift has created a significant opening for attackers. On TikTok, people do not just scroll for inspiration, but actively look for answers, whether finding a restaurant, a solution to a problem, or an honest product review, increasingly going straight to TikTok instead of Google.

 


The malicious campaigns documented by ReversingLabs are built precisely for this environment, using descriptions and tags to make content appear as legitimate customer support pages, positioning themselves directly in the path of users who are already looking for help. When the feed doubles as a search engine, a malicious tutorial is only one recommendation away.


Two campaigns, two playbooks


RL’s researchers identified two distinct approaches, each designed to game social media differently.

 


The first involves fake tutorial accounts built to impersonate legitimate tech support. The malicious accounts use usernames like “windows.tips” or “windows.insights” and the same blue and white profile picture, mirroring the colour palette of the official Windows social media account to establish credibility. The videos themselves are clean and professional, featuring what appear to be AI-generated voiceovers walking viewers through step-by-step instructions, for instance, how to access Windows PowerShell and run a command to supposedly unlock Spotify Premium for free.

 


A non-technical user would not know any better and may assume the tutorial is legitimate. Attackers rely on this lack of understanding. The command used will download scripts from a specified address, and some users may believe the domain is Microsoft-affiliated or otherwise trustworthy. What is actually downloaded is something else entirely.

 


The file delivered through the command is identified as VidarStealer, a popular infostealer malware-as-a-service (MaaS) offering that steals credentials, financial information, and tokens from victims. With an affordable $300 lifetime licence, it is a widely used tool by malicious actors, with usage documented across fake game cheats, malvertising campaigns, and more.

 


The second campaign takes a different approach. It relies on short videos set to trending music, showing off features of premium software with on-screen text claiming the user has unlocked them for free. The accounts behind these videos appear like regular users at first glance, but their profiles are typically filled with repetitive, near-identical clips promoting free access to services like Spotify Premium and similar tools.

 


These vague videos prompt users to ask questions in the comments, wondering how the poster managed to get free access. This curiosity plays directly into what the attacker wants. Some videos actively encourage viewers to comment with certain phrases, a strategy borrowed from non-malicious creators like recipe writers who use it to build engagement and foster an audience relationship. Once engagement builds, the attacker replies with directions pointing toward malicious download sites.


Why social media video is trusted more


The success of both campaigns is not accidental. It is rooted in how users relate to video content. What makes these videos dangerous is how clean and professional they are, creating a false sense of authority. Tutorials are frequently liked and saved, as users want to return to them. Saving is a valuable interaction for posts, causing the platform algorithm to push content to more users.

 


Users may also share tutorials, creating more engagement that content-serving algorithms favour. In one documented example, a video with over 100,000 views had nearly 200 more saves than likes, demonstrating how attackers are specifically targeting the more algorithmically valuable forms of engagement. Each save is a vote of confidence in the algorithm’s eyes and a further amplification of reach.

 

This is a deliberate strategy, not incidental. Attackers understand how platform recommendation systems work and produce content calibrated to exploit them. 


The role of AI in scaling attacks


Running a social media account is a very low-time-investment endeavour, and with AI voice and video generation, videos are becoming easier to mass-produce. Social media provides ample opportunities for attackers to access victims, and there will likely be increasing numbers of these accounts and videos in the coming years.

 


The ReversingLabs analysis found that at least some of these tutorial videos already use AI-generated voiceovers, giving them a polished quality that signals legitimacy to casual viewers. As AI generation tools become more accessible and cheaper, the barrier to producing convincing, high-volume campaigns drops further. What once required a professional setup — like clean graphics, a confident voice, and a plausible script — can now be assembled in minutes.

 


Tools such as ChatGPT, Gemini, Midjourney, Adobe Firefly, Runway, and ElevenLabs have dramatically lowered the barrier to content creation. What once required design skills, video-editing software, or professional voiceover equipment can now be produced in minutes using AI-generated images, videos, and audio. This accessibility is not only helping creators but also making it easier for cybercriminals to produce convincing scam content at scale.


Why platforms are struggling to respond


These techniques are difficult to defend against, like any social engineering method. Users who identify the malicious intent may try to warn others in the comments, but most platforms allow creators to delete comments and block commenters, so diligent attackers can suppress this resistance.

 


Reporting suspicious videos does not always lead to quick action. In their investigation, ReversingLabs researchers reported several scam-related posts on Instagram, but the platform rejected those reports. This highlights a broader challenge for social media companies: harmful content can remain online even after users flag it.

 


Part of the problem is that moderation systems do not always recognise these videos as dangerous. Even when a report is reviewed by a person, they may not have the cybersecurity expertise needed to understand how a seemingly harmless tutorial could be directing users to malware or phishing websites. As a result, scam videos can continue to spread and attract victims before they are eventually removed, if they are removed at all.

 


Even when a social media video or account is taken down, it is likely only after it has amassed a large number of views, and threat actors can easily start anew.

 


The structural mismatch between how fast bad content spreads and how slowly platforms respond creates a window that attackers are actively exploiting.

 


Removing a scam video or banning an account does not necessarily solve the problem. By the time platforms take action, the content may have already reached thousands or even millions of users. In many cases, attackers have already achieved their goal of spreading malware or collecting personal information.

 


What makes the issue even harder to tackle is how quickly cybercriminals can create new accounts and upload fresh content. While harmful videos can spread within hours, platform moderation and review processes often take much longer. This gap between the speed of attackers and the speed of enforcement allows cybercriminals to continue targeting users and expanding their reach.


What platforms and users can do to stay protected


Social media scams are becoming harder to spot because they often look like ordinary tutorials or product recommendations. As attackers adapt their tactics, both users and organisations need to broaden their approach to online safety.

 


Recommended precautions


  • Audit software installation permissions

  • Update phishing awareness training

  • Treat social media as a phishing vector

  • Report suspicious videos and accounts

  • Be cautious of “free premium software” claims


One of the key defences against this kind of attack is to regularly audit permissions, ensuring people with installation privileges understand what they are installing. Most examples described in the analysis involve leisure software, but some promise access to professional software, which employees may deem useful enough to attempt to install on work devices.

 


Phishing training also needs to be maintained and kept up to date so people are aware of the evolving threat landscape. Organisations must broaden their awareness of a variety of vectors and focus on more than just the typical avenues of phishing.

 


Users are encouraged to report suspicious social media advice even when using personal social media on personal devices. The more reports filed, the more likely it is that accounts are taken down, which does slow down the momentum of attackers.


The unfortunate reality is that these techniques work. Videos are reaching hundreds of thousands of views, thousands of saves, likes, and shares, and hundreds of comments. These are hugely influential on how well content performs, and these techniques leverage that priority. The threat, in other words, is not theoretical. It is already reaching a very large audience — one scroll at a time.



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Australian Open 2026: PV Sindhu overcomes Chen Su-yu, sets up semi-final clash with Akane Yamaguchi

Australian Open 2026: PV Sindhu overcomes Chen Su-yu, sets up semi-final clash with Akane Yamaguchi


World No. 10 PV Sindhu booked her place in the semifinals of the Australian Open 2026 with a dominant victory over Chinese Taipei’s Chen Su Yu in the quarter-finals at the Quaycentre in Sydney on Friday, May 12.

In a match lasting just 27 minutes, the third-seeded Indian controlled both games from the beginning to seal a 21-6, 21-9 victory. The result marks Sindhu’s second semifinal appearance of the season, having previously reached the last four at the Malaysia Open 2026, the BWF Super 500 tournament.

ALSO READ: FIFA World Cup 2026 Golden Ball contenders: Lamine Yamal, Harry Kane, Kylian Mbappe and more; check all top names

 


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Stage Set For Another PV Sindhu vs Akane Yamaguchi Battle

An interesting semifinal awaits Sindhu as the two-time Olympic medallist takes on top seed and three-time world champion Akane Yamaguchi, who advanced to the last four with a 21-14, 21-14 victory over India’s Tanvi Sharma in 32 minutes.

The upcoming clash will be the 29th meeting between the two, with Sindhu holding a 15-13 advantage over Yamaguchi in their head-to-head record. However, the Japanese has won four of their last five encounters.

Their most recent meeting came at the Thailand Open last month, where Sindhu came agonisingly close to victory. The Indian shuttler took the opening game and led by four points at the second mid-game interval in the second game, but Yamaguchi staged a strong comeback to prevail 19-21, 21-18, 21-15.

Notably, one of Sindhu’s most iconic wins against Yamaguchi came in the Tokyo 2020 quarter-finals, paving the way for her to clinch a second consecutive Olympic medal.

Sindhu is chasing her first BWF World Tour title since lifting the Syed Modi International crown in Lucknow in 2024.

ALSO READ: Explained: Why England’s Djed Spence will wear protective mask at FIFA World Cup 2026

 

India’s Challenge Ends In Men’s Doubles

Meanwhile, India’s challenge in the men’s doubles events came to an end on Friday after MR Arjun and Hariharan Amsakarunan retired from their quarter-final against Chinese Taipei’s Chen Cheng Kuan and Liu Kuang-Heng.

The Indians had narrowly lost the opening game 21-19 and were trailing 16-9 in the second when they withdrew. 



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