What Version of Google Chrome Do I Have? – Online Tech Tips

Make sure it’s up to date

Google ships minor updates to the “Stable” version of Chrome every 2-3 weeks, while major updates happen every 4-6 weeks. The minor updates or point releases typically offer security updates and bug fixes. On the other hand, major releases often ship with new features.Google Chrome automatically installs both minor and major updates in the background on all devices. However, there are instances when Google Chrome malfunctions and the browser fails to auto-update. If you have reasons to believe the browser isn’t up-to-date, we’ll show you how to check what Chrome version you have.Open Google Chrome on your Windows, macOS, or Linux computer and enter chrome://version in the address bar. Check the “Google Chrome” row at the top of the page for the browser version.This technique also works on the mobile builds of the Google Chrome browser. Open Chrome on your Android or iOS device and enter chrome://version in the address bar. Check the Google Chrome row for the browser’s version or build number.You can also go through Chrome’s settings menu to find your browser’s version.If you’re using Chrome on a Mac computer, here’s how to check the browser version from its settings menu.You’ll see a “Chrome is up to date” message on the screen if you have the latest version of Chrome. Sometimes, you may need to relaunch Chrome to install pending updates. Refer to their tutorial on updating web browsers for more information on updating Chrome and other web browsers—Mozilla Firefox, Apple Safari, etc.Open the Chrome web browser on your computer and follow the steps below.Alternatively, paste chrome://settings/help in Chrome’s address bar and press Enter on your keyboard.Follow the steps below to check the Google Chrome browser version installed on your iPhone or iPad.Follow the steps below to verify the current version of Google Chrome installed on your Android device.Chromebooks are based on the Chrome operating system. If you use a Chromebook, you can verify the device’s Chrome version from the Settings menu.Open your Chromebook’s Settings app and expand the “Advanced” drop-down section on the sidebar. Select About ChromeOS to check what version of Chrome’s operating system is powering your Chromebook.Google releases all versions of the Chrome browser in trickles, depending on the stage of development. Chrome has four release channels: Canary, Dev, Beta, and Stable.This channel is at the forefront of Google Chrome’s development phase. Google calls it the “bleeding edge” build of Chrome. Canary builds are in development, and new versions are released daily.The Canary channel is the first testing ground for new features still in development. If Google were to introduce a new feature in Chrome, the company first pushes the feature to the Canary build for testing and observation.Chrome’s Canary channel is the most unstable build of the browser. You can run Chrome’s Canary build alongside the stable version on your device. However, they don’t recommend installing Chrome Canary unless you’re asked to—especially on your primary computer.Google updates the Dev channel once or twice weekly. Developers often use this build to get a 9-12 weeks preview of new features coming to Chrome.The Dev channel often crashes and malfunctions, but it’s a lot more stable than the Canary channel. Google resolves issues with features in the Dev channel before marking them as “stable.”Chrome’s Beta build lets you test-run new features 4-6 weeks before they’re introduced to the Stable version of Chrome. Google updates the Beta channel roughly every week, fixing issues or bugs reported by Beta users/testers.Chrome’s Stable build is what you’ll find on the Chrome website, Google Play Store, and Apple App Store. The Stable channel is also called the “Official Build” The Chrome team has thoroughly tested this channel, and you should have little to no issue using the browser.You may see “32-bit” or “64-bit” next to your Chrome version number. The 64-bit version has more RAM than the 32-bit version and performs best on 64-bit computers.When downloading Chrome from Google Chrome’s website on a Linux or macOS computer, you get the 64-bit version by default. In Windows, Chrome automatically detects your PC’s processor architecture and provides the version that’s best for your device.You’ll get the 64-bit obtain link on a 64-bit PC and the 32-bit obtain link on 32-bit devices. Don’t know your PC’s processor architecture? Here are 4 ways to check if you have a 32-bit or 64-bit computer.Google also gives users the liberty to obtain either the 32-bit or 64-bit version of the browser. Scroll to the bottom of the Chrome obtain page and select Other Platforms.Select your preferred version (32-bit or 64-bit) on the “Get Chrome” pop-up page.You now know how to check Chrome’s version. The next step is verifying if you have the latest browser version on your device. WhatIsMyBrowser.com keeps an updated summary of the latest Google Chrome web browser versions and their release dates.If your device’s browser version differs from what’s on WhatIsMyBrowser’s report, update Google Chrome immediately.Sodiq has written thousands of tutorials, guides, and explainers over the past 4 years to help people solve problems with Android, iOS, Mac, and Windows devices. He also enjoys reviewing consumer tech products (smartphones, smart home devices, accessories, etc.) and binge-watching comedy series in his spare time. Read Sodiq’s Full Bio

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What to Expect from Google’s Gemini?

Google DeepMind’s most awaited foundational model, Gemini, is expected to be launched sometime next month. Demis Hassabis recently claimed that engineers at DeepMind are using techniques from AlphaGo for Gemini—which will be its challenger in the AI race and was teased during Google’s I/O event. Hassabis claims that Gemini will be more capable than OpenAI’s GPT-4.

“At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models,” Hassabis said. “We also have some new innovations that are going to be pretty interesting,” he added.

In April, Google brought Google Brain and DeepMind teams together into a single unit—Google DeepMind. Pichai’s unexpected merger aimed to boost efficiency, using Google’s seemingly unending computational resources and DeepMind’s meticulous research to build more capable systems which would be the next frontier in this AI arms race.

Before that, both entities developed individual responses against ChatGPT. While DeepMind initiated Project Goodall, using an undisclosed model called Chipmunk, Google launched Bard based on Google Brain models. Despite a rivalry between the teams, DeepMind abandoned Goodall to collaborate on Gemini.

However, people forget that PaLM and PaLM 2 were not created by Deepmind. Gemini will be deepminds potentially first popular commercialised model that won’t be stuck in research like Gato and it’s other interesting models.  

Despite being in the early stages of development, Google reports significant advancements in Gemini’s multimodal capabilities, surpassing preceding models. Its notable that Gemini was conceived from the ground up with a multifaceted design approach. This design not only prioritises being multimodal, allowing it to process and understand various forms of data, but also emphasises high efficiency in terms of tools and API integrations. Gemini’s architecture is furthermore poised to facilitate future innovations, specifically memory and planning.

The implications of this progress are substantial, as it hints at enhanced comprehension and interaction with diverse types of data. While GPT-4 is adept at understanding and generating conversational text, Gemini will transcend this by being proficient in processing various inputs, including text, images, and videos. Gemini will also be capable of generating outputs in the form of text, videos, audio, music, and images. Additionally, it will possess reasoning capabilities and the ability to facilitate translations across diverse languages and input formats.

In addition, discussions among Google employees have revolved around using Gemini for various functionalities. This includes tasks such as analysing charts, producing graphics accompanied by text descriptions, and operating software through text or voice commands.

Boosting Enterprise Services 

Google is pinning its hopes on Gemini to fuel a range of services. These applications span from the Bard chatbot, which competes with OpenAI’s ChatGPT, to enterprise-oriented platforms like Google Docs and Slides. In pursuit of this goal, Google envisions charging app developers for access to Gemini via its Google Cloud server-rental division. At present, Google Cloud provides access to less advanced Google-designed AI models through Vertex AI. By incorporating these new attributes, Google aims to narrow the gap with Microsoft, which has surged ahead in integrating new AI features into its Office 365 suite. Microsoft has also been offering OpenAI’s models to its application users.

Unleashing New Medical Use-cases 

Google has been high on integrating its AI models to develop medical use cases. It has been testing an AI tool called Med-PaLM 2, which would answer medical questions. The product is being tested at renowned healthcare institutions like the Mayo Clinic research hospital. 

These efforts could be magnified with Gemini and could be used in medical chatbots or robotics to help with surgeries or assistance in medical procedures.

Building Super Cool Robots 

In addition, Google might also look to integrate their insights from building DeepMind’s Gato, a “general-purpose” system, which was trained to complete 604 tasks through multi-modal, multi-task training, including image captioning, dialogue, robot-arm block stacking, playing games, and navigating 3D environments. 

Gato’s unique aspect is its task diversity and training approach which employed a transformer neural network and various data modalities like text, images, and actions. During deployment, Gato tokenises prompts and observations to generate actions sequentially. 

Similarly, with the recent launch of RT-2, which is based on Transformer architecture and trained on web text and images, empowering it to directly generate robotic actions. 

Similar to language models, it learns from web data to guide robot behaviour. This innovation builds on vision-language models (VLMs) like PaLI-X and PaLM-E, using action tokens in its output to control robots’ behaviour effectively.

With the recent launch of its RT-2 a successor to its Robotics Transformer model, Google DeepMind has taken a leap forward in robotics as well. RT-2 is based on Transformer architecture and trained on web text and images, which empowers it to directly generate robotic actions. 

This innovation builds on vision-language models (VLMs) like PaLI-X and PaLM-E, using action tokens in its output to control robots’ behaviour effectively. Similar to language models, it learns from web data to guide robot behaviour. 

While DeepMind’s Gato was seen as a stride toward artificial general intelligence (AGI), because of its capability of diverse tasks—Gemini could accelerate its AGI push.

Might Kill OpenAI’s GPT-4 

The fact that Google Brain and DeepMind are working on this together possibly means trouble for OpenAI and other competitors. Additionally, others like former Google president Sergey Brin have joined forces to strengthen its AI capabilities.

OpenAI Chief Sam Altman believes video training is the next frontier, however, Google has got an edge and is sitting on top of the world’s biggest video library—Youtube.

Gemini is being trained on YouTube videos and would be the first multi-modal model being trained on video rather than just text (or in GPT-4’s case text plus images). This might equip Gemini with capabilities well beyond GPT-4. Don’t forget that it has access to nearly all of the web, to which Google claimed a stake recently by changing its privacy policy.

Not just that, there are reports indicating that Gemini is being trained on twice the number of tokens as GPT-4 was, and 10x that of PaLM 2. manifold compute making it significantly smarter and less prone to hallucinations. Not just that, with friction between OpenAI and Microsoft lately, Google could be the tortoise to beat OpenAI to the punch and become the first to arrive at AGI or AGI-like model.

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