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An enterprise version of the Chrome web browser designed to protect and power business clients

An enterprise version of the Chrome web browser designed to protect and power business clients

Vote: (132 votes)

Program license: Free

Developer: Google

Version: 89.0.4389.114

Works under: Windows

Vote:

Program license

(132 votes)

Free

Developer

Version

Google

89.0.4389.114

Works under:

Windows

Pros

  • 24/7 access to cloud services without having to sign-in for every use.
  • Automatic updates.
  • Security features following Google's industry-leading standards.

Cons

  • Memory management issues. Memory leaks when some cloud plug-ins run for days, so you may need to close and open Chrome.
  • Inconsistent Java support.
  • Your activity can be used by Google analytics unless you specifically secure your actions.

What is Google Chrome for Work?

Google Chrome for Work--also known as Google Chrome Enterprise--is a workforce-friendly version of the Chrome web browser that delivers cloud-based power and other benefits.

Like many enterprise solutions, the real power is in the services. You're basically signing up for a Service-Level Agreement (SLA) that keeps your workforce connected to the cloud.

What Are Google's Cloud Services?

Compute Engine

Google's answer to Virtual Machine (VM) technology is the Compute Engine service. It can be used for virtual computers, running virtual servers, or cloud apps.

Virtual machines are the backbone office efficiency. Virtual desktop computers were the first major use case, allowing businesses to make, edit, destroy, and rebuild workstations in virtual space rather than buying multiple, physical computers.

Cloud Storage

Virtual storage lockers have been around for decades, and were one of the first pre-existing technologies to change their name to cloud services.

You can store lots of information on Google's cloud storage, but simple storage is just the basic use. Every other cloud service can work from the cloud storage feature, allowing collaboration and enhancement in many directions.

Private and business users can subscribe to higher tiers of cloud storage for bigger storage, faster transfers, and service support. Bigger storage is necessary to have backups and data peace of mind.

Cloud SQL

MySQL, PostgreSQL, and many other databases are the core of business data. Everything is stored in a database these days to make research, analysis, and especially automation and artificial intelligence (AI) easier.

With Google Chrome for Work, users can stay connected with their databases for seamless queries. Database administrators and managers can handle database creation and management without using too many additional tools.

Many third-party tools used for personal preference can interface with Google cloud services. This is important when working with databases, as well as most development tasks.

Anthos

Google entered the enterprise data center space when they introduced Anthos in early 2019.

It's a system that modernizes your existing digital presence, meaning that you you can update the way older apps, code, and other legacy systems work with your updated Google services.

This is important because while you can run almost any programs in most modern cloud services, they don't always work efficiently and the output often requires a bit of hacking to work efficiently.

Vision AI

Google offers two AI products for images: AutoML and Vision AI.

AutoML offers a way to upload images, then send them to your AI training system in the cloud. It's basically an upload and interfacing suite, with tools for automation.

Uploading information and sending them into a system are a series of basic tasks that should be automated in modern tech situations. It's just a series of clicks, or automating moving one file to another area.

Vision AI is a way to train using Google's preexisting data sets. While AutoML allows custom or manual training, you're using Google's data as a frame of reference.

Knowing your data set's source is important. Data sets are basically the details that create your AI's understanding; all assumptions, theories, and ways of digitally thinking are based on that data.

Any data set can be inherently flawed. That said, just because you want to do it on your own doesn't mean you're capable of making a "flawless" data set; there are many theories on data set integrity, and specialists can deliver more information.

That's why the two choices in Vision AI are important. One option allows you to use your own data sets in your own system, while another offers pre-built data sets.

AI and Machine Learning tools

Once an experimental concept with no major names in the game, multiple major tech businesses have their own AI systems that they lease to others.

With Google's AI and machine learning tools, you can use cloud services to research, build, and develop your own AI progress. While the core of your AI work will be based on Google's system, there's still massive room for growth.

More importantly, the resources needed to manage AI development without someone else's framework is a huge and expensive undertaking for the time being. When that changes, it's still easy to move from a Google-based understanding to your own.

What are AI and machine learning tools? AI is all about making decisions, and systems need to be taught how to learn from others and develop its own way of learning.

From speech to text to recognizing patterns to everything about data sets, Google's AI tools operate at the center of AI. Specialized AI is there as well, with cloud-based GPUs (graphics processing units) available to handle images and video.

Pros and Cons

Pros

  • 24/7 access to cloud services without having to sign-in for every use.
  • Automatic updates.
  • Security features following Google's industry-leading standards.

Cons

  • Memory management issues. Memory leaks when some cloud plug-ins run for days, so you may need to close and open Chrome.
  • Inconsistent Java support.
  • Your activity can be used by Google analytics unless you specifically secure your actions.