What if we have to traverse and inscribe hard and uncertain enigmas?
What if people need to prophesy a natural disaster before it happens?
If an individual wants to imperil species or trace affliction when it spreads or to oust it earlier.
All such unanswered problems must be essential to address, must be sustained for improving people’s lives. But how? Well, perhaps the answer will be Artificial Intelligence.
Put simply, AI is the creation of software that practices computers and algorithms in order to decipher data and function on its own account. Artificial intelligence is the fastest-growing industry, it lists range from education, investments, business, trends, to news and politics. (Must read: AI in politics)
This simple blog throw lights on how AI will change the world and making peoples’ lives easier, especially when employs and connects hands with Google, bestowing a voyage to Google AI.
Google AI, which is heretofore known as Google Research also, is presently Google’s Artificial Intelligence R&D division for numbers of fundamental applications of AI. Even, Google has revealed its rebrand of Google AI at Google I/O in 2018.
Google is continuously augmenting its division of AI in all its accompanying fields that include Google Auto ML vision (for image recognition), Google Assistant (for android devices), TensorFlow(for ML and deep learning), DeepMind( for developing deep learning and artificial general intelligence technology)
Google Research undertakes numerous challenging issues in Computer Science and allied fields, Google believes that AI can give distinct methods of cornering problems and enrich the lives of people pointedly. (Click here to know how AI changes our lives)
According to the definition of Google,
The theory and research-development of computer systems that are worthy to execute functions usually compelling human intelligence like visible discernment, speech recognition, decision-making, and interpretation amid languages.
Google is shaping tools and resources that are available to everyone so that everybody can implement technology to solve problems. Some tools are described below;
Machine Learning tools Kit delivers ML expertise of Google to mobile developers in terms of a compelling and convenient package. By this, you can shape your iOS and Android apps extra appealing, personalized, and effective alongside optimized solutions to be executed on the device. It helps in;
Fairness Indicators, an elementary computation of ordinarily recognized fairness array of metrics for binary and multi-class classifiers. Priorly, in order to evaluate the fairness watchfulness by utilizing enormous tools on huge datasets and models are not suitable. In regard to this at Google, it facilitates such tools that can operate on billions of user-systems.
Therefore, by fairness indicators, Google can evaluate fairness metrics over any size of data, or used-cases. It incorporates the empower to;
Assess the dissemination of datasets
Figure out the performance of models and classify over across defined groups of users
Decipher all individual parts for discovering motive causes and possibilities for advancement
Don’t you want to learn how fairness indicators can be applied to any product for evaluating fairness interests over a duration of time, Do you?
List of Google AI tools
Colaboratory, or you would say “Colab” for short, enables you for writing and running Python your web browser, especially with;
Zero arrangement necessitated
Free and open access to GPUs
"Colab makes work much easier for students, data scientists, and AI researchers"
It is a Jupyter notebook environment that is available for free, it doesn’t need setup and executes wholly i.e, writing, functioning, and sharing code on the cloud.
This is the official video from Google Colab Research where Jake Vanderplas told what exactly you necessitate to get originated with Colab.
Google understands that open-source is best for everyone. After being available freely and openly, Google approves and stimulates collaboration that also addresses in solving real-world problems through the development of technologies.
“It draws open-source’s values to Google and complete resources of Google to an open-source.”
(As discussing open source, go to the link to learn other open-sources applications)
More or less, it implements numerous open-source projects to establish high-scale and authentic products. Also, Google has published millions-lines of code beneath the licenses of open-source for others to use.
“Google's embrace of open source has been important to me as an engineer in ways I can't express. It's fantastic!”- Rob Pike, Distinguished Engineer
This is the link where you get some tutorials on how to use TensorFlow.js with excellent examples, commonly used case models and live demos and examples through TensorFlow.js.
For its working;
Retrain existing models: You can retrain pre-existing ML models by managing your individual data.
(Learn how ML models help Uber to optimize its services)
Google's machine learning and artificial intelligence (or machine intelligence, as the company likes to call it) influences many of its signature products. -John Chae
Google has been inaugurating its platform at the world-level that furnishes equal opportunities for us and observes how an individual company assumes for establishing machine learning systems. Moreover, Google puts enormous efforts into building a massive platform for Artificial Intelligence, and at this time, Google has released it worldwide.
You’ve gone through the understanding of Google AI, its perceptions, and various tools of Google Ai that are available freely and openly for everyone.
6 Major Branches of Artificial Intelligence (AI)READ MORE
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
Top 10 Big Data TechnologiesREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE
7 Types of Activation Functions in Neural NetworkREAD MORE
What Are Recommendation Systems in Machine Learning?READ MORE
7 types of regression techniques you should know in Machine LearningREAD MORE
Introduction to Time Series Analysis in Machine learningREAD MORE
How Does Linear And Logistic Regression Work In Machine Learning?READ MORE