Silver BlogTop Google AI, Machine Learning Tools for Everyone

Google is much more than a search company. Learn about all the tools they are developing to help turn your ideas into reality through Google AI.

By Claire D. Costa, Content Writer and Strategist at Digitalogy, LLC.

Google AI bringing the benefits of AI to everyone (source).

“We want to use AI to augment the abilities of people, to enable us to accomplish more and to allow us to spend more time on our creative endeavors.” -- Jeff Dean, Google Senior Fellow

Calling Google just a search giant would be an understatement with how quickly it grew from a mere search engine to a driving force behind innovations in several key IT sectors. Over the past couple of years, Google has planted its roots into almost everything digital, be it consumer electronics such as smartphones, tablets, laptops, its underlying software such as Android and Chrome OS or the smart software backed by Google’s AI.

Google has been actively innovating in the smart software industry. Backed by its expertise in search and analytical data acquired over the years have helped Google create various tools like TensorFlowML KitCloud AI, and many more for enthusiasts and beginners alike who are trying to understand the capabilities of AI.

Google AI is focused on bringing the benefits of AI to everyone.

The following sections will shed more light on how Google has targeted its suite of tools to specific groups of users, such as Developers, Researchers and Organizations and how they can benefit from the AI tools by Google.


For Developers


With more developers diving into the world of AI seeing its potential, Google is catering to their dynamic needs by providing several powerful tools such as:


The revolution is here! Welcome to TensorFlow 2.0.

TensorFlow is Google’s offering to the world as an end-to-end open-source deep-learning library utilizing machine learning to improve the services provided by various of its products. Using TensorFlow’s suite of tools and libraries, developers can build highly precise and well-defined Machine Learning models.

Offering smooth model building and flexible deployment on a variety of devices, TensorFlow can make creating and deploying complex AI models a breeze. With strong community support, there are plenty of ideas to get you started, whether you’re a novice or an experienced individual.

Let’s see some samples here.

ML Kit

ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package (source).

ML Kit is a mobile-only SDK, currently available to Android & iOS to leverage the benefits of Google’s Machine Learning onto your mobile apps and prepare them to solve real-world problems. ML Kit can help you achieve success in tasks driven by the underlying Machine Learning techniques such as:

  • Language Identification

Pass text to ML Kit -> Get detected language in the text

This supports over 100 languages, including Hindi, Arabic, Chinese and many more! Find the entire list of supported languages here.

Click a pic -> Get the text in the pic

ML Kit extracts any text that is present in that picture (source).

  • Image Scanning and Labelling

Click a pic -> Get a list of objects in the pic

  • Face Recognition

Click a pic -> Get all faces in the pic

  • Smart Replies

Pass messages to ML Kit -> Get 3 smart replies

ML Kit provides you 3 smart replies.

  • Barcode Scanning

Click a pic -> Get info from the scanned barcode/QR code

ML Kit supports the scanning and extraction of information from barcode (source).

  • Custom Model Integration with TensorFlow Lite

With ready-to-use APIs for on-device or cloud implementation for a variety of use-cases, you can easily apply your ML model to your data and track the performance of your app with an option for custom integration with TensorFlow Lite.

This option lets you add TensorFlow Lite models to ML Kit and use them (source).


Google Open Source


Google Open Source bringing all the value of open source to Google and all the resources of Google to open source (source).

As newer and better software get developed every day, there is a constant need to take it to the next level. Once developers start creating code that is open-source only then the community can actively participate and help improve and expand upon it. With freely available code, developers can modify and scale the code by accessing its repository, often solving complex problems in the process.

Google has pledged to bring the developers together by encouraging them to make their code openly available to anyone interested in the idea behind it. Google has offered loads of free and open-source projects such as:

  • ClusterFuzz, that has uncovered more than 11000 bugs within the last two years in several projects.
  • AutoFlip, that intelligently reframes videos to fit modern devices.
  • Blockly, that offers easy coding via drag-and-drop code blocks which can even be used to create business logic.

Fairness Indicators

Google, in its Open Source initiative, offers Fairness Indicators. It is a tool that provides metrics to quantify fairness in a machine learning system. Powered by TensorFlow, the intent is to eliminate any bias from a machine learning system while improving its fairness and decreasing unfair biases from impacting systems and organizations. With the ability to scale-up as the need grows, Google designed this with all kinds of businesses in mind.

Using Fairness Indicators to visualize metrics for fairness evaluation (source).


Start Writing Python with Google Colaboratory (source).

Colaboratory or Colab, in short, is an online code editor and compiler for Python. Think of it as Google Docs but for Python, backed by the storage capabilities provided by the likes of Google Drive. It is relatively easy to use and eliminates the hassle of sharing configurations across multiple users, simplifying the collaboration process. It also offers the ability to work remotely on your code with the option to create markdowns for detailed explanations with code snippets.

Get started with Google Colaboratory (source).


For Researchers


While diving into a new field of study, extensive research is an absolute must. With comprehensive and rich datasets generated by the existing models which are openly available to the users, Google has simplified the process to get your hands on them by offering the following tools:

Google Datasets

With every machine learning model, the fundamental problem is to train it with correct data. Google Datasets caters to that problem by offering datasets.

Google Datasets is a collection of datasets curated by Google that is periodically refreshed by analyzing the broad range of interests of the researchers.

Google offers quite a broad range of dataset categories covering images, transcribed audios, videos, and text. Targeted towards a wide variety of users with varying use-cases, each category features a detailed run-down of the dataset with download links for easy access.

Once users download the datasets and train their model on the datasets, they can prepare their models for real-world scenarios. Search for more datasets can be done via the Google Dataset Search.

Google Dataset Search

With each model on the internet generating its dataset, Google has helped ease the process of sharing the datasets with other users on the internet by providing a search feature. Much like its search service that searches anything on the web, Google’s Dataset Search narrows down your search for the dataset you’re looking for. From there on, you can know more about the dataset and get your hands on it.

Data is King and Google Knows it


Another initiative by Google increases the accuracy of its datasets by presenting users with fun challenges, asking them to recognize various categories of images such as drawings, letters, newspapers, illustrations, and many more.

From these categories, contributors can identify and label the pictures from provided choices to improve Google’s services. You will be awarded a fun badge and given milestones to achieve once you start contributing if you have that competitive spirit.

Improve your products by Google Crowdsource (source).

Google Crowdsource works not just on images but a variety of other sections like:

  • Handwriting Recognition
  • Facial Expressions
  • Translations
  • Translation Validation
  • Image Captions
  • Image Label Verification


For Organizations


By closely monitoring the market, Google can identify how its services can turn an enterprises’ potential milestone into an achieved target. Google offers businesses with tools that can streamline their workflow and reach new heights by adopting the expertise of AI and ML. From precise datasets, custom models, high-performance cloud services and much more, Google has a lot to offer to enterprises of all scales.

Several organizations have benefitted from Google’s AI tools such as LyftMax KelseneBay, and Two Sigma, to name a few. Organizations can benefit off the following Google AI tools.

Cloud TPU

TPU V2 (Source: Google Cloud Platform Blog).

With all the number crunching, Machine Learning requires a high-performance system. And just for that, Google built its TPU, short for Tensor Processing Unit that serves just that. By equipping businesses with the firepower they want, without any on-premises setup, Cloud TPU enables enterprises to offer their best services to customers by reducing hardware costs.

Enterprises can settle on their preferred choice of cloud TPU, ranging from less demanding tasks to the most demanding ones and pick one from below offered options:

  • Cloud TPU v2
  • Cloud TPU v3
  • Cloud TPU v2 Pod
  • Cloud TPU v3 Pod

Cloud AI

Cloud AI enables you to implement machine learning capabilities into your business so that it is always ready to take on new challenges. Using Cloud AI, businesses can use the already available models provided by Google or go ahead and customize one to their liking.

Cloud AI is broken down into three components. Cloud AI consists of —

  • AI Hub: Provides a collection of ready to use AI components with options to share and experiment on the models.
  • AI Building Blocks: Allows the developers to add conversation, sight, language, structured data and Cloud AutoML capabilities to their application.
  • AI Platform: AI Platform empowers data scientists, engineers and developers to quickly turn their ideas to deployment with several services such as AI Platform Notebooks, Deep Learning Containers, Data Labelling Services, Continuous Evaluation, AI Platform Training and more.

Cloud AutoML

Being used by popular brands such as Disney, Imagia, Meredith and more, Cloud AutoML enables effortless training of custom machine learning models to generate high-quality training data. Being fully integrated with a host of other Google services paired with a seamless transfer process from one service to another, your business can achieve its full potential by maximizing your output.

Get started with AutoML (source).




AI has been around for a relatively short period, but the advancements and applications that we have discovered over time are staggering. Looking at the benefits of AI, enterprises can gain the upper edge by adopting Artificial Intelligence and Machine Learning early-on and experimenting with it.

Google has been consistently innovating in the category, with several tools such as ML KitTensorFlowFire Indicators and many more for a variety of its users, including developers, researchers, and businesses. By encouraging the use of its Cloud AI tools, Google is trying to boost the presence of AI and ML in the real-world.

The purpose is to empower users with precise means of evaluating, collaborating, improving and deploying their tailored machine learning models for increased productivity and improved services.

Original. Reposted with permission.


Bio: Claire D. Costa is a Content Crafter and Marketer at Digitalogy, a tech sourcing and custom matchmaking marketplace.