OPPO Reno15 Series Price In India: Chinese smartphone brand OPPO has recently launched the OPPO Reno15 series in India. The lineup includes the OPPO Reno 15 5G, Reno 15 Pro 5G, and Reno 15 Pro Mini 5G. All three smartphones are now available for sale in the country. The OPPO Reno15 series focuses on advanced AI-powered photography, a rugged build, and long-lasting batteries. Alongside the Reno15 series, OPPO India’s new ecosystem products, the OPPO Pad 5 and OPPO Enco Buds 3 Pro+, are also available for sale starting today. These products are designed to support everyday productivity, entertainment, and on-the-go lifestyles. The OPPO Reno15 series runs on ColorOS 16, featuring the all-new Trinity Engine and Luminous Rendering Engine for smoother performance and improved visual responsiveness. OPPO has also confirmed long-term software support, with the devices set to receive five major ColorOS version updates along with six years of security updates. Add Zee News as a Preferred Source OPPO Reno15 Series: Display The OPPO Reno15 Pro 5G features a 6.78-inch AMOLED display with LTPO technology and a 120Hz dynamic refresh rate. The OPPO Reno15 Pro Mini 5G comes with a 6.32-inch AMOLED LTPS display that also supports a 120Hz dynamic refresh rate. Meanwhile, the OPPO Reno15 5G sports a 6.59-inch AMOLED LTPS display with a 120Hz dynamic refresh rate, delivering smooth visuals across the lineup. (Also Read: Realme Pad 3 Launched In India With MediaTek Dimensity 7300 Chipset; Check Display, Camera, Battery, Price And Other Specs) OPPO Reno15 Series: Processor The OPPO Reno15 Pro 5G and OPPO Reno15 Pro Mini 5G are powered by the MediaTek Dimensity 8450 chipset built on a 4nm process. The processor features an octa-core CPU clocked at up to 3.25GHz, a Mali-G720 MC7 GPU, and an NPU 880 for enhanced AI performance. Both devices support LPDDR5X RAM and UFS 3.1 storage. Meanwhile, the OPPO Reno15 5G is equipped with the Qualcomm Snapdragon 7 Gen 4 Mobile Platform, featuring an octa-core tri-cluster 64-bit architecture for balanced performance and efficiency. OPPO Reno15 Series: Battery The OPPO Reno15 Pro 5G packs a 6,500mAh battery and supports 80W SUPERVOOC fast charging, along with 50W AirVOOC wireless charging. The OPPO Reno15 Pro Mini 5G is equipped with a 6,200mAh battery and also supports 80W SUPERVOOC fast charging. Meanwhile, the OPPO Reno15 5G comes with a 6,500mAh battery and supports 80W SUPERVOOC fast charging for quick top-ups. OPPO Reno15 Series: Camera The OPPO Reno15 Pro 5G and OPPO Reno15 Pro Mini 5G feature a 200MP HP5 primary rear camera with OIS. They are paired with a 50MP ultra-wide camera with autofocus and a 116-degree field of view, along with a 50MP telephoto lens. The OPPO Reno15 5G comes with a 50MP primary camera with OIS, supported by an 8MP ultra-wide camera and a 50MP telephoto lens with 3.5x optical zoom. (Also Read: Xiaomi’s Redmi Note 15 5G Launched In India With 4K Video Recording; Check Display, Camera, Battery, Price, Sale Date And Other Specs) For quality selfies and video chats, the Reno15 Pro 5G and Reno15 Pro Mini 5G house a 50MP selfie camera with autofocus, while the OPPO Reno15 5G features a 50MP front camera with a 100-degree field of view and autofocus. OPPO Reno15 Series Price In India And Availability The OPPO Reno15 Pro is available in two variants, with the 12GB RAM and 256GB storage model priced at Rs 67,999, while the 12GB RAM and 512GB storage variant costs Rs 72,999. The OPPO Reno15 Pro Mini is offered in 12GB + 256GB and 12GB + 512GB configurations, priced at Rs 59,999 and INR 64,999, respectively. Meanwhile, the OPPO Reno15 is available in three storage options, including 8GB + 256GB priced at Rs 45,999, 12GB + 256GB at Rs 48,999, and 12GB + 512GB at Rs 53,999. The series is available for purchase with exciting offers across Amazon, Flipkart, Mainline Retail Outlets and OPPO E-store. OPPO Pad 5 And OPPO Enco Buds3 Pro+ Price And Availability The OPPO Pad 5 is offered in two storage options, with the 8GB + 128GB variant priced at Rs 26,999 and the 8GB + 256GB 5G model priced at Rs 32,999. Alongside it, the OPPO Enco Buds 3 Pro+ is priced at Rs 2,499 and is available through the OPPO e-store, Flipkart, Amazon, and leading offline retail stores. OPPO Reno15 Series: Bank Offers Customers purchasing the OPPO Reno15 series can avail multiple launch offers, including up to 10% instant cashback on credit card payments with select bank partners and on UPI transactions. The brand is also offering zero down payment options for up to 15 months through leading financiers, along with an exchange bonus of up to INR 2,000 via select trade-in partners. Buyers will also receive 180 days of screen damage protection at no additional cost and a one-year extended warranty. Adding further, OPPO is providing a 50% discount on the OPPO Enco Buds 3 Pro+ with every Reno15 series purchase. 

AI Voice Scam: What began as an ordinary day for an Indore school teacher quickly turned into a nightmare she never anticipated. A phone call with a familiar, anxious voice and an urgent plea for help caught her off guard. Trusting the moment and acting on instinct, she followed the instructions without verification. Within minutes, Rs 1,00,000 was gone. The voice she believed was real was actually generated using artificial intelligence, exposing a disturbing new form of cyber fraud that is increasingly targeting unsuspecting victims. After this incident, one question arises in the mind: what are AI voice scams, and how can people stay safe from them? What Is AI Voice Scam Add Zee News as a Preferred Source AI voice scams are a type of cyber fraud in which scammers use artificial intelligence to clone or mimic a person’s voice to deceive victims. By using short audio clips, often taken from phone calls, social media, or videos, criminals create realistic voice replicas of family members, friends, or officials. These fake voices are then used to make urgent phone calls, pressuring victims to transfer money or share sensitive information. Because the voice sounds familiar and convincing, many people fall for the scam without verifying the caller’s identity. (Also Read: Did You Know How Much Money You Earn For 1,000,000 Views On Instagram Reels? How To Earn More From Meta-Owned Platform: Check Eligibility And Tips) AI Voice Scams: How To Avoid Use Family Code Word Create a secret code word or phrase with your family members and close relatives. In any emergency call asking for money or urgent help, ask the caller to share this code word to confirm their identity before taking any action. Verify Through Video Call If you receive an urgent or emotional phone call, disconnect and call back using a saved contact number. Ask the person to switch to a video call, as scammers usually avoid showing their face and cannot replicate real-time visuals. Enable Caller ID And Alerts Install trusted caller ID applications and enable bank transaction alerts on your phone. These tools help identify suspicious or spoofed numbers quickly and notify you instantly if any unauthorised transaction attempt takes place. Limit Sharing Voice Clips Publicly Avoid posting voice notes, interviews, reels, or videos on social media platforms. Scammers require only a few seconds of audio to clone a voice using AI, making public audio content a potential security risk. Never Share OTPs Or Make Urgent Payments Do not share OTPs, PINs, or banking details under pressure. Refuse urgent payment requests through UPI, QR codes, wire transfers, or gift cards, and immediately report suspicious calls to the national cybercrime helpline 1930. Facebook, Instagram And WhatsApp Top Online Scam Platforms Misuse of social media has emerged as the biggest source of digital crime in recent years, making up 37 to 53 percent of reported cases. Hundreds of incidents involve impersonation, sextortion and online blackmail, with scammers actively targeting users on popular platforms such as Facebook, Instagram and WhatsApp. 

New Smartphone Security Rules: The government has denied a report by an international news outlet that claimed it wants to force smartphone companies to share their source code and make major software changes for security reasons. As per reports, this plan had upset big tech giants like Apple and Samsung. However, the IT Ministry said these claims are misleading, noting that the report did not include any statements from the smartphone makers or the industry groups that represent them. This move comes after India proposes requiring smartphone makers to share source code with the government and make several software changes as part of a raft of security measures, prompting behind-the-scenes opposition from giants like Apple and Samsung. Notably, smartphone makers closely guard their source code. To recall, the Apple declined China’s request for source code between 2014 and 2016, and US law enforcement has also tried and failed to get it. PIB Fact-Checks Add Zee News as a Preferred Source The Centre’s PIB has fact-checked the Reuters report and said that the Government of India has not proposed any move to force smartphone makers to share their source code. It also added that the Ministry of Electronics and Information Technology (MeitY) has started discussions with stakeholders to create the most suitable rules for mobile security. A news report by @Reuters claims that India proposes forcing smartphone manufacturers to share their source code as part of a security overhaul. #PIBFactCheck  This claim is #FAKE  The Government of India has NOT proposed any measure to force smartphone manufacturers to… pic.twitter.com/0bnw0KQL9Q — PIB Fact Check (@PIBFactCheck) January 11, 2026 What Is Smartphone Source Code A smartphone’s source code is the set of instructions written by developers that tells the phone’s software how to work. It includes the code behind the operating system (like Android or iOS), system apps, and core features such as calling, messaging, security, and app permissions. This code controls how data is processed, how apps run, and how the phone protects user information. For users, source code is usually hidden and managed only by the company that built the software. For governments or developers, accessing source code can help check for security flaws, but it can also raise concerns about privacy, intellectual property, and misuse. (Also Read: Can Public Wi-Fi At Railway Stations Expose Your Online Search? Here’s How To Protect Your Sensitive Data) MeitY In Talks With Smartphone Industry The Ministry of Electronics and Information Technology (MeitY) has been talking with industry representatives to understand technical challenges, compliance issues, and global best practices followed by smartphone makers. The India Cellular and Electronics Association (ICEA) said these discussions have been going on for several years and should not be seen as a sudden policy change. The IT Ministry said these consultations are part of its regular talks with the industry on safety and security standards. It added that the government is continuously working to protect user data in a fast-changing digital world. The ministry also said it is engaging with industry stakeholders in a constructive way and will review all genuine concerns with an open mind, keeping the interests of both the country and the industry in focus. (Also Read: What Is AI Voice Scam? Indore School Teacher Duped Of Rs 1,00,000; Here’s How To Avoid) World’s Second-Largest Smartphone Market Tech companies have pushed back against a proposed set of 83 security rules, saying there is no global example for such measures. According to people familiar with the talks and a Reuters review of confidential documents, the rules would also require companies to inform the government about major software updates. The firms warn that this could expose sensitive and proprietary information. The proposal is part of Prime Minister Narendra Modi’s broader push to strengthen user data security as online fraud and data breaches continue to rise in India, the world’s second-largest smartphone market with nearly 750 million devices.

Ray-Ban Meta Gen 2 AI Smart Glasses Price In India: After a global launch, Meta has finally brought the Ray-Ban Meta Gen 2 smart glasses to India, marking the company’s expansion of wearable devices in the country. The AI-powered glasses will soon be available on Amazon India, making them accessible to a wider audience. Until now, buyers could only purchase the smart glasses from Ray-Ban’s official website. Amazon has set up a dedicated microsite for the Ray-Ban Meta Gen 2 glasses. While the page does not mention a launch date, it does highlight the main features of the product. The wearable device is build on the previous generation of Meta smart glasses, bringing a more capable camera system, upgraded Meta AI integration and revised designs. The Ray-Ban Meta Gen 2 smart glasses are available in Wayfarer, Skyler, and Headliner styles. It is offered in colour options such as Shiny Cosmic Blue and Shiny Mystic Violet. Add Zee News as a Preferred Source Ray-Ban Meta Gen 2 AI Smart Glasses Features The Ray-Ban Meta Gen 2 smart glasses come with an upgraded 3K Ultra HD camera that offers improved stabilisation and better low-light performance. It is powered by the Meta AI. The smart glasses can answer questions based on what the user is seeing. They support 3K video recording through a five-microphone system and allow hands-free photo and video capture. Users also get open-ear speakers with built-in microphones and voice access to Meta AI using the “Hey Meta” command. The product offers a regular fit and delivers up to 48 hours of total battery life when used with the charging case. To widen its appeal in India, the smart glasses support Hindi voice interaction and also come with AI voice options. Adding further, Meta plans to enable UPI Lite payments, allowing users to scan QR codes and make payments using voice commands linked to their WhatsApp-connected bank account. Ray-Ban Meta Gen 2 Smart Glasses Price In India The Ray-Ban Meta Gen 2 smart glasses are priced starting at Rs 39,900. The Amazon listing is expected to follow the same pricing announced earlier by Ray-Ban India. However, the company has not yet confirmed the official sale date. 

New Delhi: For the first time since domestic production began in 2021, US tech giant Apple Inc’s iPhone exports from India crossed Rs 2 lakh crore in 2025, as per industry data. Exports of the tech company in January–December 2025 reached a record $23 billion or Rs 2.03 lakh crore, up nearly 85 per cent over 2024 exports. Around three months remain before Apple’s five‑year PLI window ends. Under the production-linked incentive scheme (PLI), Apple’s focus in India had been expansion of the iPhones exports. In the first nine months of FY26, iPhone exports stood at nearly $16 billion, pushing cumulative shipments during the PLI period beyond the $50‑billion mark. By comparison, Samsung exported devices worth around $17 billion during its five‑year eligibility period under the scheme from FY21 to FY25. Apple’s manufacturing footprint in the country includes five iPhone assembly plants—three operated by Tata Group entities and two by Foxconn—supported by a supply chain of around 45 companies, including many MSMEs supplying components for domestic and global operations. Add Zee News as a Preferred Source Driven largely by iPhone shipments which contributed about 75 per cent of total smartphone exports, smartphones rose to India’s single largest export category in FY25, up from their rank of 167 among export items in 2015. India became the world’s second-largest mobile phone producer, with more than 99% of phones sold domestically now Made in India moves up the manufacturing value chain. The smartphone PLI scheme is scheduled to conclude in March 2026, though the government is reportedly exploring ways to extend support. Under revised rules, companies were allowed to claim incentives for any five consecutive years within a six‑year period. Apple also sold about 6.5 million iPhone 16 units in the first 11 months of 2025, making it the country’s highest selling smartphone.

In this article, you will learn how quantization shrinks large language models and how to convert an FP16 checkpoint into an efficient GGUF file you can share and run locally. Topics we will cover include: What precision types (FP32, FP16, 8-bit, 4-bit) mean for model size and speed How to use huggingface_hub to fetch a model and authenticate How to convert to GGUF with llama.cpp and upload the result to Hugging Face And away we go. Quantizing LLMs Step-by-Step: Converting FP16 Models to GGUFImage by Author Introduction Large language models like LLaMA, Mistral, and Qwen have billions of parameters that demand a lot of memory and compute power. For example, running LLaMA 7B in full precision can require over 12 GB of VRAM, making it impractical for many users. You can check the details in this Hugging Face discussion. Don’t worry about what “full precision” means yet; we’ll break it down soon. The main idea is this: these models are too big to run on standard hardware without help. Quantization is that help. Quantization allows independent researchers and hobbyists to run large models on personal computers by shrinking the size of the model without severely impacting performance. In this guide, we’ll explore how quantization works, what different precision formats mean, and then walk through quantizing a sample FP16 model into a GGUF format and uploading it to Hugging Face. What Is Quantization? At a very basic level, quantization is about making a model smaller without breaking it. Large language models are made up of billions of numerical values called weights. These numbers control how strongly different parts of the network influence each other when producing an output. By default, these weights are stored using high-precision formats such as FP32 or FP16, which means every number takes up a lot of memory, and when you have billions of them, things get out of hand very quickly. Take a single number like 2.31384. In FP32, that one number alone uses 32 bits of memory. Now imagine storing billions of numbers like that. This is why a 7B model can easily take around 28 GB in FP32 and about 14 GB even in FP16. For most laptops and GPUs, that’s already too much. Quantization fixes this by saying: we don’t actually need that much precision anymore. Instead of storing 2.31384 exactly, we store something close to it using fewer bits. Maybe it becomes 2.3 or a nearby integer value under the hood. The number is slightly less accurate, but the model still behaves the same in practice. Neural networks can tolerate these small errors because the final output depends on billions of calculations, not a single number. Small differences average out, much like image compression reduces file size without ruining how the image looks. But the payoff is huge. A model that needs 14 GB in FP16 can often run in about 7 GB with 8-bit quantization, or even around 4 GB with 4-bit quantization. This is what makes it possible to run large language models locally instead of relying on expensive servers. After quantizing, we often store the model in a unified file format. One popular format is GGUF, created by Georgi Gerganov (author of llama.cpp). GGUF is a single-file format that includes both the quantized weights and useful metadata. It’s optimized for quick loading and inference on CPUs or other lightweight runtimes. GGUF also supports multiple quantization types (like Q4_0, Q8_0) and works well on CPUs and low-end GPUs. Hopefully, this clarifies both the concept and the motivation behind quantization. Now let’s move on to writing some code. Step-by-Step: Quantizing a Model to GGUF 1. Installing Dependencies and Logging to Hugging Face Before downloading or converting any model, we need to install the required Python packages and authenticate with Hugging Face. We’ll use huggingface_hub, Transformers, and SentencePiece. This ensures we can access public or gated models without errors: !pip install -U huggingface_hub transformers sentencepiece -q from huggingface_hub import login login() !pip install –U huggingface_hub transformers sentencepiece –q   from huggingface_hub import login login() 2. Downloading a Pre-trained Model We will pick a small FP16 model from Hugging Face. Here we use TinyLlama 1.1B, which is small enough to run in Colab but still gives a good demonstration. Using Python, we can download it with huggingface_hub: from huggingface_hub import snapshot_download model_id = “TinyLlama/TinyLlama-1.1B-Chat-v1.0″ snapshot_download( repo_id=model_id, local_dir=”model_folder”, local_dir_use_symlinks=False ) from huggingface_hub import snapshot_download   model_id = “TinyLlama/TinyLlama-1.1B-Chat-v1.0” snapshot_download(     repo_id=model_id,     local_dir=“model_folder”,     local_dir_use_symlinks=False ) This command saves the model files into the model_folder directory. You can replace model_id with any Hugging Face model ID that you want to quantize. (If needed, you can also use AutoModel.from_pretrained with torch.float16 to load it first, but snapshot_download is straightforward for grabbing the files.) 3. Setting Up the Conversion Tools Next, we clone the llama.cpp repository, which contains the conversion scripts. In Colab: !git clone https://github.com/ggml-org/llama.cpp !pip install -r llama.cpp/requirements.txt -q !git clone https://github.com/ggml-org/llama.cpp !pip install –r llama.cpp/requirements.txt –q This gives you access to convert_hf_to_gguf.py. The Python requirements ensure you have all needed libraries to run the script. 4. Converting the Model to GGUF with Quantization Now, run the conversion script, specifying the input folder, output filename, and quantization type. We will use q8_0 (8-bit quantization). This will roughly halve the memory footprint of the model: !python3 llama.cpp/convert_hf_to_gguf.py /content/model_folder \ –outfile /content/tinyllama-1.1b-chat.Q8_0.gguf \ –outtype q8_0 !python3 llama.cpp/convert_hf_to_gguf.py /content/model_folder \     —outfile /content/tinyllama–1.1b–chat.Q8_0.gguf \     —outtype q8_0 Here /content/model_folder is where we downloaded the model, /content/tinyllama-1.1b-chat.Q8_0.gguf is the output GGUF file, and the –outtype q8_0 flag means “quantize to 8-bit.” The script loads the FP16 weights, converts them into 8-bit values, and writes a single GGUF file. This file is now much smaller and ready for inference with GGUF-compatible tools. Output: INFO:gguf.gguf_writer:Writing the following files: INFO:gguf.gguf_writer:/content/tinyllama-1.1b-chat.Q8_0.gguf: n_tensors = 201, total_size = 1.2G Writing: 100% 1.17G/1.17G [00:26<00:00, 44.5Mbyte/s] INFO:hf-to-gguf:Model successfully exported to /content/tinyllama-1.1b-chat.Q8_0.gguf Output: INFO:gguf.gguf_writer:Writing the following files: INFO:gguf.gguf_writer:/content/tinyllama–1.1b–chat.Q8_0.gguf: n_tensors = 201, total_size = 1.2G Writing: 100% 1.17G/1.17G [00:26<00:00, 44.5Mbyte/s] INFO:hf–to–gguf:Model successfully exported to /content/tinyllama–1.1b–chat.Q8_0.gguf You can verify the output:

Public Wi-Fi Safety: You’re at your favourite cafe, sipping coffee, at a railway station, and logging onto the free public Wi-Fi. It feels convenient, fast, and easy. But have you ever wondered who might be watching your online activity? Every click, search, and login could leave a digital trail. Public Wi-Fi networks are like open windows into your online life, and while they promise connection, they might also invite unseen eyes. Can the owner of that café or any public Wi-Fi provider actually see what you are doing online? In this article, we will uncover the truth behind these invisible spectators. Public Wi-Fi Networks: ISPs Monitor All Unencrypted Traffic  Public Wi-Fi is everywhere and crucial these days, from metro stations to airports, because our devices always need an internet connection, but internet service providers (ISPs) can see all unencrypted activity on their networks, meaning every click, search, and login can be logged. This does not mean they are constantly watching, but the possibility is real, which is why browsing personal content on company Wi-Fi can be risky. Where you connect also matters, as airports and railway stations may have extra security to detect unusual activity, yet their high traffic can make these networks less safe than smaller public Wi-Fi spots. Add Zee News as a Preferred Source Are Public Wi-Fi Connections Safe? Public Wi-Fi is not as safe as private networks because it often has no password and weak encryption. This makes it an easy target for “man-in-the-middle” attacks, where hackers can intercept your internet data. They might capture sensitive information like credit card numbers, passwords, and the websites you visit, even though they cannot see exactly what you do on those sites. On top of that, some cybercriminals create “fake hotspots” that look real. If you connect to them, they can quietly monitor your activity and steal your data without you even realizing it. (Also Read: What Is AI Voice Scam? Indore School Teacher Duped Of Rs 1,00,000; Here’s How To Avoid) Public Wi-Fi Safety: How To Protect Your Sensitive Data You should always use a trusted VPN like Norton or Surfshark on public Wi-Fi to keep your data encrypted and safe from snoopers. Turn off auto-connect and file or printer sharing to avoid unauthorized access. Always confirm the network name with staff to avoid fake hotspots. Keep your device firewall on and enable two-factor authentication for extra protection. Avoid sensitive activities like online banking or shopping, log out after use, and clear your browser cache to remove any traces of your activity. These steps help you stay secure on open networks.  

Fast Charging Tips: In today’s tech world, many smartphone users believe that turning on airplane mode charges a phone faster. This tip is often recommended and shared online by tech advisors for situations when people are in a hurry. But does airplane mode actually make a difference, or is it just a common myth? Here’s what experts and smartphone manufacturers say. When airplane mode is enabled, the phone disconnects from all wireless networks. This includes mobile data, calls, Wi-Fi, Bluetooth, and background syncing. As a result, the phone stops searching for network signals and pauses many background activities that usually consume power. With fewer functions running, the phone uses less energy while charging. Does It Really Help? Add Zee News as a Preferred Source Yes, but only slightly. Turning on airplane mode can help a phone charge faster because the battery is not being drained by network connections and background tasks. Since less power is being used during charging, more of the incoming power goes directly into charging the battery. However, the speed increase is not dramatic. Studies and battery experts say the difference may range from a few minutes to around 10-15% faster charging, depending on the phone model, battery health, and charger used. Other Factors While turning on airplane mode can help your phone charge faster, other factors play a bigger role in charging speed. Using a fast charger, a high-quality cable, and a wall socket instead of a laptop USB port makes a noticeable difference. Modern smartphones also support fast charging technologies that automatically adjust power flow. Using the phone while charging, especially for gaming, video streaming, or navigation, slows down charging far more than keeping airplane mode off. (Also Read: How To Use UPI Payments Without Internet? This Mind-Blowing Service Could Help You In Emergency Situations) Battery Safety Airplane mode can also reduce heat generation. Less heat helps the battery charge more efficiently and protects long-term battery health. Overheating is one of the main reasons phones slow down charging. Myth or Fact? The idea that airplane mode charges your phone faster is a fact, but with limits. It does help by reducing power usage, but it is not the only or magic solution. For significantly faster charging, using proper chargers, avoiding phone use during charging, and keeping the device cool are far more effective. Airplane mode could be seen as a helpful tip but not a guaranteed fast-charging trick.

You must have faced situations where you could not make UPI payments due to reasons such as poor mobile network or technical issues. Everyone finds this annoying as it tests patience levels. Most people try to reconnect the network by switching airplane mode on and off or using other methods. To address this problem, India has an offline UPI payment facility that allows users to send money even without an internet connection. What Is Offline UPI Payment? Offline UPI payments work through a service called *99#, which uses Unstructured Supplementary Service Data (USSD) technology. Unlike regular UPI apps that depend on mobile data or Wi-Fi, USSD works on basic GSM signals. This makes it useful in areas with weak or no internet connectivity. Add Zee News as a Preferred Source The service is supported by the National Payments Corporation of India (NPCI) and works on all feature phones and smartphones. How *99# Works? To make a payment without internet, users need to dial *99# from their registered mobile number. Once dialed, a menu appears on the screen with options such as sending money, checking balance, or viewing recent transactions. Users can send money by entering the receiver’s UPI ID, bank account number with IFSC code, or mobile number. After entering the amount, the user confirms the transaction by entering their UPI PIN. The payment is then processed using GSM signals instead of internet data. (Also Read: Did You Know How Much Money You Earn For 1,000,000 Views On Instagram Reels? How To Earn More From Meta-Owned Platform: Check Eligibility And Tips) Who Can Use Offline UPI? Any user with a bank account linked to their mobile number and UPI can use the *99# service. It is especially helpful for people using feature phones and users in rural or remote areas where internet connectivity is unreliable. However, the service usually supports smaller transaction values, with a daily limit generally capped at Rs 5,000. Benefits During Emergencies Offline UPI is particularly useful during emergencies such as floods, cyclones, or power outages, when internet services may be disrupted. Through this service, essential payments like buying groceries, medicines, or transport fares can still be made digitally. Limitations to Keep in Mind While useful, offline UPI has limitations. The interface is text-based and slower compared to app-based UPI. Also, not all banks offer the same level of support, and transaction success depends on basic mobile network availability. As India pushes towards cashless transactions, offline UPI acts as a reliable backup option. It ensures that digital payments are accessible even without internet connectivity, helping users make payments during emergency situations.

New Delhi: India must accelerate AI-led innovation, industrial automation, and the adoption of frontier technologies to fully realise its manufacturing ambitions, according to The Make-in-India Upgrade: Advanced Manufacturing Trends, a December 2025 chartbook by Ionic Wealth. India stands at a critical juncture in its industrial journey, with advanced manufacturing emerging as a decisive lever for long-term economic competitiveness. The report noted that failure to unlock advanced manufacturing could leave India with a manufacturing GDP gap by the 2047 Viksit Bharat vision. Under a business-as-usual scenario, manufacturing GDP would reach only USD 2.3 trillion, far below the USD 7.4 trillion potential, highlighting what the report calls a “significant gap” if decisive action is not taken. At the core of the recommended strategy is AI-led innovation and productivity gains, combined with automation, digitisation, and product and process innovation. The report stated that AI-led innovation and productivity gains, along with industrial automation and the adoption of frontier technologies, are key enablers of India’s manufacturing progress. These technologies can help Indian firms move up global value chains, reduce costs, and compete with manufacturing powerhouses. Add Zee News as a Preferred Source India has already made progress on foundational reforms. The report noted advances in labour code implementation, GST rationalisation, easing of FDI norms, land reforms, and infrastructure modernisation, including single-window digital clearances under PM Gati Shakti and the rollout of the National Logistics Policy. Large investments such as Micron’s USD 2.75 billion semiconductor assembly plant and Google’s combined USD 25 billion commitment to digitisation and AI-led data centres are cited as early indicators of momentum. Looking ahead, the report highlighted that emerging and PLI-linked sectors are expected to contribute 27 per cent of industrial capital expenditure over the next decade, with average annual capex projected to rise from Rs 4.3 lakh crore in FY21–FY25 to Rs 7.1 lakh crore in FY26–FY30. Sectors such as advanced electronics, clean energy, next-generation automotive technologies, aerospace, and AI-cloud-cyber stacks could collectively drive USD 1.4–1.9 trillion in GDP growth by 2035. Additionally, the adoption of frontier technologies—including AI/ML, robotics, digital twins, 3D printing, advanced materials, and smart grids—could boost India’s manufacturing GDP by USD 1.1 trillion, the report estimated. The Ionic Wealth report also cited NITI Aayog, which had earlier stated that advanced manufacturing is no longer optional—it is the foundation of India’s global competitiveness in the next decade.