What Happened To Google Glass? How Google Glass Set The Stage For The AR Revolution

  • Google Glass is a brand of smart glasses with an optical, head-mounted display. Just two years after they were launched, Google announced they would no longer be producing a consumer version of the glasses. 
  • Google Glass failed primarily because of a poor product-market fit. The developers believed the glasses would sell on hype and not on how they would solve user problems.
  • Google Glass competed against more successful smart devices such as watches, speakers, and televisions. They also attracted criticism for their ability to film others covertly and didn’t perform any function especially well.

Origin Story

Google Glass is a brand of smart glasses with an optical, head-mounted display.

Google developed the glasses with the intent to produce a ubiquitous computer allowing the wearer to communicate with the internet via voice commands.

Prototype Google Glass smart glasses were launched in April 2013 for the princely sum of $1,500. Almost immediately, they attracted criticism from consumers concerned about their privacy, safety, and cost. 

Just two years later, Google announced it would be ceasing production of the consumer version of the glasses.

The company then pivoted to the business sector and launched Glass Enterprise Edition for certain workplaces such as factories and surgeries. 

Why did the consumer version fail so spectacularly? Read on to find out.

Product-market fit

Marc Andreessen defined Product/market fit as “being in a good market with a product that can satisfy that market.” According to Andreessen, that is a moment when a product or service has its place in the market, thus enabling traction for the company offering that product or service.

Google Glass failed as a product because its inventors did not conduct proper research on its potential users and the market.

Instead of developing a product that would solve user problems, they believed the glasses would sell on hype and revolutionary technology alone.

The early adopters were exposed to poor product development and could not identify any meaningful benefits to wearing the glasses.

Moreover, the glasses were not technologically advanced enough to warrant regular use, and Google had not determined whether they were comfortable to wear for long periods.


Google had lofty ambitions to augment reality with a touchpad, camera, and LCD or LED display.

In truth, however, all the company did was supplement reality.

Ultimately, the sunglasses had a limited battery life of between three to five hours.

They were also competing with smart televisions, watches, and speakers with faster processors, larger capacities, and better cameras. 

Stigma and negative publicity

Google Glass attracted significant criticism after discovering wearers could film others covertly. 

Some bars and restaurants banned wearers from entry, with the term “Glasshole” coined around the same time.

Google then released a statement instructing users to respect the privacy of others and not be creepy or rude, but the damage had been done. 

The timing of the negative publicity was also unfortunate since there was also rising distrust around the power of big tech companies at the time.


Even the prototype version of the glasses retailed for $1,500 – equivalent to the price of a well-equipped desktop computer.

The high cost of the glasses was exacerbated by the fact that they didn’t perform any function, especially well.

As a result, those who could afford them were content purchasing a more affordable smartphone without the associated stigma of owning it.

Google released the latest version of its AR headset in February 2020. Known as Glass Enterprise Edition 2 and retailing for a more agreeable $999, the “faster and more helpful” release enables employees to perform their jobs more efficiently. 

The product is most effective in manufacturing, logistics, construction, healthcare, and other industries that don’t require a dedicated mixed-reality device such as Microsoft HoloLens.

Project Iris

In September 2021, it was revealed that Google was working to develop an augmented reality OS for a new and innovative AR device. The initiative, known as Project Iris, involves a headset that will augment video from outward-facing cameras with various graphics.

Referencing those close to the project, American tech news website The Verge claimed the product would more closely resemble ski goggles than typical glasses. It would also be run on an unspecified processor most likely based on Tensor with hardware chief Rick Osterloh noting it was the “perfect foundation for making big improvements in AR.

The search giant is reticent to share details about Project Iris, with work undertaken in a separate building that requires a special keycard to access. There are over 300 employees working on the project with all signing non-disclosure agreements. 

Google splits its AR division

In February 2023, various articles reported that Google had split its AR division in response to competitors like Oculus Quest and Microsoft HoloLenses increasing their market share.

The reports coincided with the news that Google AR head Clay Bavor – at the helm for 18 years – would be leaving the company in March. All AR efforts previously under the purview of Bavor (such as Project Iris) will be moved into two separate divisions.

The first, Devices & Services, is headed by Osterloh and encompasses the Pixel Tablet, Fitbit, Pixel Watch, Chromecast, and Nest speakers, cameras, and displays. The second division, Platforms & Ecosystems, is led by Hiroshi Lockheimer and will incorporate Google’s AR efforts. 

Samsung collaboration

Google’s decision to incorporate AR into Platforms & Ecosystems is perhaps a nod to its recent collaboration with Samsung on Android-based extended reality (XR) headsets. Samsung president and mobile leader TM Roh hinted that the product was still in development but potentially close to a debut in the near future.

As part of the collaboration, Google is providing the software and a special version of Android tailored for wearable headsets and displays. The partnership and indeed restructuring of the AR division shows that Google is placing more of an emphasis on monetization. It also has the intention to adapt more of its services to XR environments.

Whether the company’s renewed focus on AR can overcome more advanced competitors and the negative experience it had with Google Glass remains to be seen.


While as a company, you can innovate and create new markets.

Often, technologies proceed with the development of complementary innovations.

AR might have been too early to be accepted at the time, given the strong transition from desktop to mobile.

In that phase, though, mobile won.

Setting the stage for the AR revolution

Augmented reality and virtual reality are taking center stage in what has been defined as the “Metaverse.”

Just like Virtual Reality (VR) develops an entirely new environment for the user using the technology and replaces the existing real environment, AR uses the current and real environment. Still, the objects inside are enhanced to stimulate user perception. It alters one or multiple aspects of the environment for interaction and enriches the experience. Whereas VR would have replaced the entire room and shown you an entirely manipulated environment, AR enables users to use the same environment and observe different objects.

Today these technologies and products might become the next frontier. As companies like Apple dominated the mobile industry.

Who’ll be able to tame the next wave will also ride a very large market.


Key Highlights

  • Google Glass was a brand of smart glasses with a head-mounted display and augmented reality capabilities.
  • It was launched as a consumer product in 2013 but failed to gain traction due to a poor product-market fit.
  • The developers focused on hype and technology rather than solving user problems, leading to a lack of meaningful benefits for early adopters.
  • Google Glass faced competition from other successful smart devices like watches, speakers, and televisions.
  • The product received negative publicity and criticism for potential privacy violations, leading to the coining of the term “Glasshole.”
  • The high cost of Google Glass, retailing at $1,500, made it less appealing to consumers compared to more functional and affordable alternatives like smartphones.
  • Google pivoted to the business sector with Glass Enterprise Edition, targeting specific workplaces like factories and surgeries.
  • Google continued its AR efforts with “Project Iris,” developing an augmented reality OS and innovative AR headset.
  • In 2023, Google split its AR division and collaborated with Samsung on Android-based extended reality (XR) headsets to focus on monetization and adapting services to XR environments.
  • AR and VR technologies are becoming central to the concept of the “Metaverse,” and companies are positioning themselves to dominate this emerging market.

Related To Google

Google Business Model

Google is an attention merchant that – in 2022 – generated over $224 billion (almost 80% of revenues) from ads (Google Search, YouTube Ads, and Network sites), followed by Google Play, Pixel phones, YouTube Premium (a $29 billion segment), and Google Cloud ($26.2 billion).

Google Other Bets

Of Google’s (Alphabet) over $282 billion revenue for 2022, Google also generated over a billion dollars from a group of startup bets, which Google considers potential moonshots (companies that might open up new industries). Those Google’s bets also generated a loss for the company of over $6 billion in the same year. In short, Google is using the money generated by search and betting it on other innovative industries. Of Google’s (Alphabet) over $282 billion revenue for 2022, Google also generated over a billion dollars from a group of startup bets, which Google considers potential moonshots (companies that might open up new industries). Those Google’s bets also generated a loss for the company of over $6 billion in the same year. In short, Google is using the money generated by search and betting it on other innovative industries. 

Google Cloud Business


How Big Is Google?

Google is an attention merchant that – in 2022 – generated $224 billion (almost 80% of its total revenues) from ads (Google Search, YouTube Ads, and Network sites), followed by Google Play, Pixel phones, YouTube Premium (a $29 billion segment), and Google Cloud ($26.3 billion).

Google Traffic Acquisition Costs

The traffic acquisition cost represents the expenses incurred by an internet company, like Google, to gain qualified traffic – on its pages – for monetization. Over the years, Google has been able to reduce its traffic acquisition costs and, in any case, to keep it stable. In 2022 Google spent 21.75% of its total advertising revenues (over $48 billion) to guarantee its traffic on several desktop and mobile devices across the web.

How Does Google Make Money

Alphabet generated over $282B from Google search and others, $32.78 billion from the Network members (Adsense and AdMob), $29.2 billion from YouTube Ads, $26.28B from the Cloud, and $29 billion from other sources (Google Play, Hardware devices, and other services).

YouTube Business Model

YouTube was acquired for almost $1.7 billion in 2006 by Google. It makes money through advertising and subscription revenues. YouTube advertising network is part of Google Ads, and it reported more than $29B in revenues by 2022. YouTube also makes money with its paid memberships and premium content.

Google vs. Bing


Google Profits


Google Revenue Breakdown

In 2022, Google generated over $282 billion in revenues, of which over $162 billion from Google Search, over $29 billion from YouTube Ads, and almost $33 billion from Network Members’ properties. In addition, Google generated over $29 billion in other revenue, over $26 billion from Google Cloud, and over a billion dollars from other bets.

Google Advertising Revenue


Apple vs. Google


Google Employees Number


Google Ad vs. Facebook Ad


YouTube Ad Revenue

YouTube, by 2022, generated over $29 billion in advertising revenues.

AI Paradigm




Large Language Models

Large language models (LLMs) are AI tools that can read, summarize, and translate text. This enables them to predict words and craft sentences that reflect how humans write and speak.

Generative Models


Prompt Engineering

Prompt engineering is a natural language processing (NLP) concept that involves discovering inputs that yield desirable or useful results. Like most processes, the quality of the inputs determines the quality of the outputs in prompt engineering. Designing effective prompts increases the likelihood that the model will return a response that is both favorable and contextual. Developed by OpenAI, the CLIP (Contrastive Language-Image Pre-training) model is an example of a model that utilizes prompts to classify images and captions from over 400 million image-caption pairs.

OpenAI Business Model

OpenAI has built the foundational layer of the AI industry. With large generative models like GPT-3 and DALL-E, OpenAI offers API access to businesses that want to develop applications on top of its foundational models while being able to plug these models into their products and customize these models with proprietary data and additional AI features. On the other hand, OpenAI also released ChatGPT, developing around a freemium model. Microsoft also commercializes opener products through its commercial partnership.


OpenAI and Microsoft partnered up from a commercial standpoint. The history of the partnership started in 2016 and consolidated in 2019, with Microsoft investing a billion dollars into the partnership. It’s now taking a leap forward, with Microsoft in talks to put $10 billion into this partnership. Microsoft, through OpenAI, is developing its Azure AI Supercomputer while enhancing its Azure Enterprise Platform and integrating OpenAI’s models into its business and consumer products (GitHub, Office, Bing).

Stability AI Business Model

Stability AI is the entity behind Stable Diffusion. Stability makes money from our AI products and from providing AI consulting services to businesses. Stability AI monetizes Stable Diffusion via DreamStudio’s APIs. While it also releases it open-source for anyone to download and use. Stability AI also makes money via enterprise services, where its core development team offers the chance to enterprise customers to service, scale, and customize Stable Diffusion or other large generative models to their needs.

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