It's official: WhatsApp now available for download on iPad
WhatsApp has officially introduced its long-awaited app for iPad.
"As one of our biggest requests, we're excited to announce that WhatsApp is now available on iPad," the company said in an announcement on its blog.
WhatsApp Messenger for iPad supports multitasking features including Split View, Slide Over, and Stage Manager (available on compatible iPad models), which allows users to organise and switch between multiple app windows.
Users can also make group video or audio calls with up to 32 people. It added that WhatsApp also works with Apple accessories Magic Keyboard and Apple Pencil.
WhatsApp Messenger for iPad is available for download on the App Store.
WhatsApp had earlier hinted at the release of the app for iPad in a cryptic post on X yesterday (May 27). Users expressed both excitement and scepticism.
Hours later, the company's latest announcement about WhatsApp for iPad has received more than 1.2 million views.
Users are now asking that parent company Meta make WhatsApp available for Apple Watch and release an Instagram app for iPad as well.
Telegram responded to the WhatsApp's announcement with a GIF asking: "What year is it?", implying that perhaps, WhatsApp for iPad has just taken too long.
One user replied: "Only 15 years later, you're doing great Mark (Zuckerberg)."
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
The Star
a day ago
- The Star
Meta unveils wristband for controlling computers with hand gestures
SAN FRANCISCO: The prototype looks like a giant rectangular wristwatch. But it doesn't tell the time: It lets you control a computer from across the room simply by moving your hand. With a gentle turn of the wrist, you can push a cursor across your laptop screen. If you tap your thumb against your forefinger, you can open an app on your desktop computer. And when you write your name in the air, as if you were holding a pencil, the letters will appear on your smartphone. Designed by researchers at Meta, the tech giant that owns Facebook, Instagram and WhatsApp, this experimental technology reads the electrical signals that pulse through your muscles when you move your fingers. These signals, generated by commands sent from your brain, can reveal what you are about to do even before you do it, as the company detailed in a research paper published Wednesday in the journal Nature . With a little practice, you can even move your laptop cursor simply by producing the right thought. 'You don't have to actually move,' Thomas Reardon, the Meta vice president of research who leads the project, said in an interview. 'You just have to intend the move.' Meta's wristband is part of a sweeping effort to develop technologies that let wearers control their personal devices without touching them. The aim is to provide simpler, quicker and less awkward ways of interacting with everything from laptops to smartphones – and maybe even to develop new digital devices that replace what we all use today. Most of these technologies are years away from widespread use. They typically involve tiny devices surgically implanted in the body, which is a complicated and risky endeavor. These implants are tested solely with disabled people who cannot move their arms and hands, and need new ways of using computers or smartphones. Neuralink, a Silicon Valley startup founded by Elon Musk, aims to implant chips under the skull, beside the brain. Synchron, run by an Australian neurologist, hopes to implant devices inside blood vessels in the neck. These efforts, like those of many other startups, aim to read brain activity directly – an enormously complex process that must be tailored to the individual. Meta is taking a simpler approach. Its technology does not require surgery. Anyone can strap on the device and start using it. Using artificial intelligence techniques, Reardon and his team have identified common electrical signals that appear when a person moves a finger, wrist or thumb. 'This idea – this kind of technology – is not new, it is decades old,' said Dario Farina, a professor of bioengineering at Imperial College, London, who has tested the technology but was not involved in the research. 'The breakthrough here is that Meta has used artificial intelligence to analyse very large amounts of data, from thousands of individuals, and make this technology robust. It now performs at a level it has never reached before.' Meta's wristband uses a technique called electromyography, or EMG, to gather electrical signals from muscles in the forearm. These signals are produced by neurons in the spinal cord – called alpha motor neurons – that connect to individual muscle fibers. Because these neurons connect directly to the muscle fibers, the electrical signals are particularly strong – so strong that they can be read from outside the skin. The signal also moves much faster than the muscles. If a device like Meta's wristband can read the signals, it can type much faster than your fingers. 'We can see the electrical signal before you finger even moves,' Reardon said. EMG has long provided a way for amputees to control prosthetic hands. But technologies that use the technique as a computer interface are only beginning to mature. In 2012, three Canadian entrepreneurs founded a company called Thalmic Labs, which built an armband called Myo that sent simple computer commands using hand gestures. With the swipe of a hand, for instance, you could switch to a new slide in a PowerPoint presentation. But the company discontinued the product several years later. Reardon started similar research after founding a company called Ctrl Labs with two other neuroscientists he had met in a Ph.D. program at Columbia University. In 2019, the startup was acquired by Meta, where it now operates within a research operation called Reality Labs. Although Reardon and his colleagues have been privately demonstrating their technology for years, they are only now beginning to publicly share their work because it is now mature enough for the marketplace. The key development is the use of AI techniques to analyse the EMG signals. After collecting these signals from 10,000 people who agreed to test the prototype, Reardon used a machine learning system called a neural network – the same breed of AI that drives ChatGPT – to identify common patterns in this data. Now, it can look for these same patterns even when a different person is using the device. 'Out of the box, it can work with a new user it has never seen data for,' said Patrick Kaifosh, director of research science at Reality Labs and one of the neuroscientists that founded Ctrl Labs. According to Reardon, who is also known as the founding father of the Internet Explorer web browser at Microsoft, Meta plans to fold the technology into products over the next few years. Last fall, the company demonstrated how its wristband could be used to control an experimental version of its smart glasses, which can take photos, record videos, play music and verbally describe the world around you. Like technologies from Neuralink and Synchron, Meta's wristband could also provide new options for disabled people. Researchers at Carnegie Mellon are testing the wristband with people who have spinal cord injuries, allowing them to use smartphones and computers even though they do not have full use of their arms or hands. Most people with these types of injuries retain the ability to activate at least some of their muscle fibers. This allows the device to read what their brain is trying to do, even though their bodies can't actually make it happen. 'We can see their intention to type,' said Douglas Weber, a professor of mechanical engineering and neuroscience at Carnegie Mellon. In a similar way, Meta's wristband lets you control a computer with the appropriate thought. Merely thinking about a movement is not enough. But if you intend to make a movement, the wristband can pick up on what you aim to do – even if you do not physically move. 'It feels like the device is reading your mind, but it is not,' Reardon said. 'It is just translating your intention. It sees what you are about to do.' When you move your arm or hand or finger, the number of muscle fibers you activate varies depending on how big or how small the movement is. If you practice using the wristband long enough, you can learn to activate a tiny number of fibers without actually moving your fingers. 'We can listen to a single neuron. We are working at the atomic level of the nervous system.' – ©2025 The New York Times Company This article originally appeared in The New York Times.
Barnama
2 days ago
- Barnama
FACIA Achieves 100 Pct Accuracy On Deepfake Detection Benchmark
BUSINESS KUALA LUMPUR, July 23 (Bernama) -- FACIA, a global leader in facial biometric technology, has announced that its deepfake detection system achieved 100 per cent accuracy on Meta's Deepfake Detection Challenge Dataset (DFDC), reinforcing its position in combatting synthetic media threats. In a statement, the company said its proprietary algorithm was tested on over 100,000 images and videos across multiple datasets, with an overall detection accuracy of 99.6 per cent. 'This is not just about setting a benchmark. Deepfakes are proliferating rapidly, and scalable detection systems are now critical for public agencies, social platforms, and financial services,' said FACIA Chief Technology Officer, Daniyal Assad Chughtai. Deepfake content tripled in 2023, with manipulated media widely used in fraud, disinformation, and non-consensual content, prompting increased concern and regulatory action globally. The DFDC dataset, considered a benchmark for deepfake testing, includes 2,100 altered videos using eight facial modification techniques. FACIA also tested its algorithm on an internal dataset of 3,430 artificial intelligence-generated images from tools such as Midjourney, Artbreeder, and achieving 89.01 per cent accuracy. Combined testing across four additional open-source datasets contributed to the system's total detection score, which FACIA said was relevant to industries such as finance, defence, and immigration. Unlike conventional frame-by-frame methods, FACIA's detection uses a multi-layered pipeline tailored for today's advanced deepfake techniques, with consistently low false acceptance and rejection rates. The technology's reliability is suited to high-assurance identity verification, offering real-time, scalable implementation for deepfake-vulnerable environments. FACIA plans to further enhance its system with multilingual spoof detection, broader dataset training, and improved application programming interface (API) support to facilitate integration with third-party platforms. The announcement comes amid growing scrutiny of synthetic media on major platforms such as Meta, TikTok, and X (formerly Twitter), which are under pressure to counter misinformation and manipulated content.
Barnama
2 days ago
- Barnama
FACIA Reports 100% Accuracy in Deepfake Detection Across Industry Datasets
LONDON, July 23 (Bernama) -- FACIA, a global leader in facial biometric technology, announced that its deepfake detection system has achieved 100% accuracy on multiple industry datasets, including Meta's Deepfake Detection Challenge Dataset (DFDC). FACIA's proprietary algorithm was tested across more than 100,000 images and videos, reporting an overall detection accuracy of 99.6%. The announcement comes amid growing global concern over synthetic media. In 2023 alone, the number of deepfake videos tripled, with total deepfake content increasing eightfold. These manipulated assets are now widely used in fraud schemes, misinformation campaigns, and non-consensual content creation, prompting regulatory responses worldwide.
