Closeup of the Ray-Ban logo and the built-in ultra-wide 12 MP camera on a pair of new Ray-Ban Meta Wayfarer smart glasses. PHOTO: ADOBE STOCK
At under US$1,000, Hypernova isn’t just eyewear—it’s Meta’s push to make AR feel ordinary.
Updated
November 27, 2025 3:26 PM
Closeup of the Ray-Ban logo and the built-in ultra-wide 12 MP camera on a pair of new Ray-Ban Meta Wayfarer smart glasses. PHOTO: ADOBE STOCK
Meta is preparing to launch its next big wearable: the Hypernova smart glasses. Unlike earlier experiments like the Ray-Ban Stories, these new glasses promise more advanced features at a price point under US$1,000. With a launch set for September 17 at Meta’s annual Connect conference, the Hypernova is already drawing attention for blending design, technology and accessibility.
In this article, let’s take a closer look at Hypernova’s design, features, pricing and the challenges Meta faces as it tries to bring smart glasses into everyday life.
Meta’s earlier Ray-Ban glasses offered cameras and audio but no display. Hypernova changes that: The glasses will ship with a built-in micro-display, giving wearers quick access to maps, messages, notifications and even Meta’s AI assistant. It’s a step toward everyday AR that feels useful and natural, not experimental.
Perhaps most importantly, the price makes them attainable. While early estimates placed the cost above US$1,000, Meta has committed to a launch price of around US$800. That’s still premium, but it moves AR smart glasses into reach for more consumers.
Hypernova weighs about 70 grams, roughly 20 grams heavier than the Ray-Ban Meta models. The added weight likely comes from added components like the new display and extra sensors.
To keep the glasses stylish, Meta continues its partnership with EssilorLuxottica, the company behind Ray-Ban and Prada eyewear. Thicker frames—especially Prada’s designs—help hide the hardware like chips, microphones and batteries without making the glasses look oversized.
The glasses stick close to the classic Ray-Ban silhouette but feature slightly bulkier arms. On the left side, a touch-sensitive bar lets users control functions with taps and swipes. For example, a two-finger tap can trigger a photo or start video recording.
Hypernova introduces something the earlier Ray-Ban glasses never had: a display built right into the lens. In the bottom-right corner of the right lens, a small micro-screen uses waveguide optics to project a digital overlay with about a 20° field of view. This means you can glance at turn-by-turn directions, check a notification or quickly consult Meta’s AI assistant without pulling out your phone. It’s discreet, practical and a major step up from the older models, which were limited to capturing photos and videos, handling calls and playing music via speakers.
Alongside the glasses comes the Ceres wristband, a companion device powered by electromyography (EMG). The band picks up the tiny electrical signals in your wrist and fingers, translating them into commands. A pinch might let you select something, a wrist flick could scroll a page, and a swipe could move between screens. The idea is to avoid clunky buttons or having to talk to your glasses in public. Meta has also been experimenting with handwriting recognition through the band, though it’s not clear if that feature will be ready in time for launch.
Meta doesn’t just want Hypernova to be useful—it wants it to be fun. Code found in leaked firmware revealed a small game called Hypertrail. It looks to borrow ideas from the 1981 arcade shooter Galaga, letting wearers play a simple, retro-inspired game right through their glasses. It’s not the main attraction, but it shows Meta is trying to make Hypernova feel more like a playful everyday gadget rather than just a piece of serious tech.
Hypernova runs on a customized version of Android and pairs with smartphones through the Meta View app. Out of the box, it should support the basics: calls, music and message notifications. Leaks suggest several apps will come preinstalled, including Camera, Gallery, Maps, WhatsApp, Messenger and Meta AI. A Qualcomm processor powers the whole setup, helping it run smoothly while keeping energy demands reasonable.
Meta is also trying to bring in outside developers. In August 2025, CNBC reported that the company invited third-party developers—especially in generative AI—to build experimental apps for Hypernova and the Ceres wristband. The Meta Connect 2025 agenda even highlights sessions on a new smart glasses SDK and toolkit. The push shows Meta’s interest in making Hypernova more than just a device; it wants a broader platform with apps that go beyond its own first-party software.
During development, Hypernova was rumored to cost as much as US$1,400. By pricing it around US$800, Meta signals that it wants adoption more than profit. The company is keeping production limited (around 150,000 units), showing it sees this as a market test rather than a mass rollout. Still, the sub-US$1,000 price tag makes advanced AR far more accessible than before.
Despite its promise, Hypernova may still face hurdles. The Ceres wristband can struggle if worn loosely, and some testers have reported issues based on which arm it’s worn on or even when wearing long sleeves. In short, getting EMG input right for everyone will be critical.
Privacy is another major concern. In past experiments, researchers hacked Ray-Ban Meta glasses to run facial recognition, instantly identifying strangers and pulling personal info. Meta has added guidelines, like a recording indicator light, but critics argue these measures are too easy to ignore. Moreover, data captured by smart glasses can feed into AI training, raising questions about consent and surveillance.
The Meta Hypernova smart glasses mark a turning point in wearable tech. They’re lighter and more stylish than bulky AR headsets, while offering real-world features like navigation, messaging and hands-free control. At under US$1,000, they aim to make AR glasses more than a luxury gadget—they’re a step toward everyday use.
Whether Hypernova succeeds will depend on how well it balances style, usability and privacy. But one thing is clear: Meta is betting that always-on, glanceable AR can move from science fiction to daily life.
Keep Reading
From information gaps to global access — how AI is reshaping the pursuit of knowledge.
Updated
November 28, 2025 4:18 PM
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Paper cut-outs of robots sitting on a pile of books. PHOTO: FREEPIK
Encyclopaedias have always been mirrors of their time — from heavy leather-bound volumes in the 19th century to Wikipedia’s community-edited pages online. But as the world’s information multiplies faster than humans can catalogue it, even open platforms struggle to keep pace. Enter Botipedia, a new project from INSEAD, The Business School for the World, that reimagines how knowledge can be created, verified and shared using artificial intelligence.
At its core, Botipedia is powered by proprietary AI that automates the process of writing encyclopaedia entries. Instead of relying on volunteers or editors, it uses a system called Dynamic Multi-method Generation (DMG) — a method that combines hundreds of algorithms and curated datasets to produce high-quality, verifiable content. This AI doesn’t just summarise what already exists; it synthesises information from archives, satellite feeds and data libraries to generate original text grounded in facts.
What makes this innovation significant is the gap it fills in global access to knowledge. While Wikipedia hosts roughly 64 million English-language entries, languages like Swahili have fewer than 40,000 articles — leaving most of the world’s population outside the circle of easily available online information. Botipedia aims to close that gap by generating over 400 billion entries across 100 languages, ensuring that no subject, event or region is overlooked.
"We are creating Botipedia to provide everyone with equal access to information, with no language left behind", says Phil Parker, INSEAD Chaired Professor of Management Science, creator of Botipedia and holder of one of the pioneering patents in the field of generative AI. "We focus on content grounded in data and sources with full provenance, allowing the user to see as many perspectives as possible, as opposed to one potentially biased source".
Unlike many generative AI tools that depend on large language models (LLMs), Botipedia adapts its methods based on the type of content. For instance, weather data is generated using geo-spatial techniques to cover every possible coordinate on Earth. This targeted, multi-method approach helps boost both the accuracy and reliability of what it produces — key challenges in today’s AI-driven content landscape.
Additionally, the innovation is also energy-efficient. Its DMG system operates at a fraction of the processing power required by GPU-heavy models like ChatGPT, making it a sustainable alternative for large-scale content generation.
By combining AI precision, linguistic inclusivity and academic credibility, Botipedia positions itself as more than a digital library — it’s a step toward universal, unbiased access to verified knowledge.
"Botipedia is one of many initiatives of the Human and Machine Intelligence Institute (HUMII) that we are establishing at INSEAD", says Lily Fang, Dean of Research and Innovation at INSEAD. "It is a practical application that builds on INSEAD-linked IP to help people make better decisions with knowledge powered by technology. We want technologies that enhance the quality and meaning of our work and life, to retain human agency and value in the age of intelligence".
By harnessing AI to bridge gaps of language, geography and credibility, Botipedia points to a future where access to knowledge is no longer a privilege, but a shared global resource.