In this Blog Post, we are going to explore the Top machine learning tools and technology developed by Google.
Artificial intelligence is crucial for any architecture decision or development. There are lots of great open-source AI frameworks that can be incorporated into your system.
Many businesses and organizations use AI technologies to improve their IT environment without much hassle.
One such organization is google and its interest in the field of artificial intelligence (AI). It provides many services based on this technology in its everyday operations.
With the massive resources that it has access to, Google has been able to build a strong ecosystem around AI.
Top Machine Learning Technology by Google
Tool Build with AI
1. Vertex AI
Vertex AI is a new unified machine learning platform by Google. It’s a combination of AutoML Vision, AutoML Translation, and structured data toolkits built on TensorFlow Lite (at under 5MB).
Vertex AI aims to democratize artificial intelligence, enabling every business to use Google-level technology with minimal effort.
Training a machine learning model often takes weeks or months, even with the most experienced data scientists.
With Vertex AI, thousands of data scientists can train their models in days and deploy them at scale.
2. AI Building Blocks
Building your app using AI building blocks helps you to connect, compute and understand the world.
It makes it easier for you to focus on your core product and business, because it takes care of the hassle of integrating large amounts of data, like customer reviews and social media comments, which goes into the underlying neural network.
Google AutoML is a set of cloud-based machine learning services that simplify and automate many of the most time-consuming and complex aspects of building machine learning systems.
Google has been pushing AutoML in recent months. AutoML is an application of ML that makes it easier and faster to generate strong ML models and manage them so you can focus on strategy, not infrastructure.
Google has developed the AutoML based products including AutoML Image, AutoML Video, AutoML,Text, AutoML translation, AutoML tabular etc.
Machine Learning (ML) and deep learning are transforming the way we live and do business.
It’s time to free yourself from spending time and resources on training machine learning models and focus on results that matter.
The Google AutoML portfolio makes it easy for business users and developers to build their own high-quality custom models with minimal effort and expertise required from machine learning experts.
Building a business-ready machine learning model is no longer a pursuit only for data scientists, but can be done with just the help of an AutoML product; AutoML for vision, AutoML for translation, AutoML for structured data, and others.
Related Article: What is Q learning? | Deep Q-learning
4. AI Infrastructure
Google Cloud is helping organizations accelerate their artificial intelligence (AI) initiatives with a full suite of infrastructure, platforms, and services.
Whether you want to iterate faster or train more complex models, use GPUs or TPUs.
It’s easy to get started with simple web requests and quick setup options for clusters. And now we’re introducing industry-leading security built from the ground up with AI in mind.
Today we’re announcing a set of infrastructure services from the Google Cloud AI Platform.
The Google Cloud AI Platform helps companies across industries build and scale applications using artificial intelligence.
With this platform, we enable customers to build and train models at cloud scale, deploy models at cloud speed, and run customer insights at a human scale.
The Google Speech API uses the latest in machine learning technology to power speech recognition and natural language understanding.
These trained models minimize the need for hand-tuning, making the API suitable for speech recognition tasks such as Speech-to-Text convert speech to text Automatic Speech Recognition (ASR).
It is used to interpret what was said using autotuned acoustic models Natural Language Understanding (NLU) understand what was said and what needs to be done
Speech-To-Text by google speech recognition service is here to help you convert your audio into text.
With the help of a cloud-based NLP engine, this service can convert more than 120 languages, including dialects, accents, and noisy recordings with accuracy.
This offers fast and reliable solutions for 3 main use cases: Speech Synthesis for hands-free voice commands Spoken language understanding to drive intelligent products Improve customer experience thru accessibility features.
Text-to-speech technology is a type of automatic speech recognition that converts written words into natural-sounding speech.
The Google Text-to-Speech API uses cutting-edge TTS technology to convert text into synthesized speech by applying powerful neural network models.
With the help of the API, organizations can engage their customers in new ways with lifelike responses and personalize communication based on customer preferences for voice/accent, language, and speed of reading.
7. Virtual Agents by Google
Google has been making a big effort to achieve human-like interactions with their products, and virtual agents are a step further down that road.
With the launch of Google’s Conversational AI platform called Dialogflow, they are hoping to streamline the process of building virtual agents and make the whole experience more intuitive.
8. Dialogflow by Google
Dialogflow is an AI platform to build conversational interfaces for messaging, voice and video chat, web, and IoT apps.
You can develop for Google Assistant, Facebook Messenger, Slack, Cortana, etc. with a single API.
You also get access to comprehensive language understanding so you can create a truly intelligent assistant for your users
Dialogflow, by Google, is an easy way to design a conversational interface for your product.
With pre-built integrations for hundreds of products such as Slack, WhatsApp & Google Home, you can deploy within minutes and be on your way to designing the next great customer experience.
9. Contact Center AI
Over the past decade, Google has pioneered call analytics, call recording, and contact center technology.
Today we’re taking yet another step forward in artificial intelligence (AI) research to increase customer satisfaction and improve agent utilization.
The Contact Center AI team is building a long-term research agenda to build intelligent automated virtual agents.
Our goal is to develop an end-to-end automated agent that can converse naturally with real people in order to provide assistance when needed or requested.
Google’s Contact Centers AI is an intelligent framework, which simplifies and advances the art of developing intelligent multi-agent systems.
It provides a common platform to quickly build, test, deploy and iterate solutions across contact center agents and specialties such as bilingual agents, supervisory control, and task automation.
AI for documents
10. Natural Language AI
The Natural Language API enables you to programmatically analyze text at scale.
It supports common NLP tasks, including part-of-speech tagging, named entity extraction, sentiment analysis, and syntactic chunking.
It also provides a comprehensive set of language identification capabilities that can be used to identify the language of the text.
Google’s Natural Language API uses machine learning to understand the text.
The API supports several language-processing features, including text analysis, entity recognition, sentiment analysis, and syntax analysis.
11. Translation AI
At Google I/O 2018, Google added support for six new languages in their translation services.
Their Language API supports 53 languages and 95 language pairs then earlier this year with the addition of support for nine more languages and a few more language combinations.
We’ve been hard at work to support these new languages on the Cloud Translation API so that developers can more easily use translation technology to create multilingual content and apps.
Here are a few of the most common questions we received since our release of this new functionality.
This FAQ will help you get started using Google’s Translation API in your application or website.
12. Vision OCR (Vision AI)
Vision AI is an end-to-end platform capable of recognizing the content of images using neural networks.
Available as a service or as open-source software, Vision AI enables you to understand the contents of your images with remarkable accuracy and speed.
The Google Cloud Vision machine learning platform is a collection of APIs that enables you to understand the content of images, including labels and locations, using a computer vision model.
You can use the vision to help build, run and manage your applications that need visual understanding.
Google’s Vision recognition technology is faster and more accurate than ever before. It runs on the cloud or at any of Google’s edge locations in order to deliver low latency, highly accurate insights right into your app.
13. Document AI Platform
Google’s Document AI is a set of machine-learning APIs that help you create intelligent apps that can process documents, extract useful information and make analyses.
Google’s vision of an intelligent, information-rich workplace is here. Document AI by Google allows you to extract a high volume of documents while keeping costs in check.
It fundamentally changes how you can access and use data. With Google Cloud Machine Learning’s recent release of Document AI, we are happy to announce that customers can now automate data capture at scale to reduce document processing costs.
Through the GCP Marketplace, you will be able to leverage our world-scale infrastructure, security model, and machine learning capabilities to make better decisions with enterprise-grade workloads.
Our goal is simple: we want to use machine learning and artificial intelligence to help you work smarter and free yourself from the countless hours spent on mundane, repetitive tasks.
AI for Industries
14. Media Translation
At Google, we believe that the best way to get your message across is by speaking the same language.
That is why we created the Media Translation API. Whether you are trying to reach a large audience through traditional media or extend an existing website into a new language, the API has you covered.
The API allows you to quickly and easily process pre-recorded audio or capture live streaming audio and automatically translate it into any number of languages.
This means that your international users can enjoy the same content in their native language as native speakers.
15. Recommendations AI
Recommendations AI by Google is a solution for e-commerce sites to deliver personalized product recommendations at scale.
Recommendations AI analyzes a customer’s interaction with your online store and recommends products based on the likelihood of them being of interest to customers.
This creates an environment where a customer can more easily find the products that fulfill their needs and lead them to complete a sale.
By making each customer the focal point of your online business, you can earn their trust and create loyalty.
Related Article: Why Artificial Intelligence is Highly Used in Google?
16. Healthcare Natural Language
Google is used in many different ways by healthcare professionals. From searching patients’ symptoms and treatments using Google search to managing their jobs across applications like Gmail or Google Calendar, or even accessing patient data via the enterprise suite Google Apps.
But there’s more than doctors and nurses can do with Google. And that’s why we’re excited to announce Healthcare Natural Language AI: a product designed to help them convert text into actionable insights using machine learning, all within an enterprise setting.
To find out more about Natural Language AI and how it could transform the way your healthcare organization works with text, read our other AI blog post.
17. Lending DocAI
Google’s Lending DocAI, a mortgage loan automation tool, is designed to improve the home loan experience for both borrowers and lenders.
It automates mortgage document processing and supports regulatory and compliance requirements, reducing processing time.
We are excited to share that Lending DocAI by Google, a service for automating mortgage document processing, is now generally available.
The service can be used by any player in the mortgage value chain: from originators to lenders and mortgage servicers of all sizes and mortgage investors who manage their own data.
Lending DocAI by Google is a highly automated system that helps lenders quickly process mortgage documents.
By using machine learning to improve over time, it speeds up the processing of mortgage applications while maintaining the accuracy of your loan portfolio.
18. Procurement DocAI
Organizations around the world manage billions of purchase orders each year. As your business grows, it’s more important than ever to build and scale an efficient, holistic procurement system.
But managing such a high volume of documents can be time-consuming and difficult. That’s where machine learning comes in our latest Google product.
Procurement DocAI, a product by Google, is an intelligent platform that allows companies to automate the process of turning unstructured data into structured data.
Procurement DocAI uses machine learning to read invoices and receipts, extract useful information, match against existing data, and create a unified, compliant data set.
Google has released a new set of tools for the Google Cloud Platform to help developers build better AI and Machine Learning tools. These APIs are available via Google Cloud’s new Core ML tool.
It’s like a Lego set for machine learning, allowing developers to mix and match what modules they need for their particular application.
Related Article: Top 10 Practical Applications of AI in the World?
Nitin is a professional data Engineer, Who has a Post Graduation in Data Science and Analytics and working in the healthcare sector. Experts in Data analysis, Machine learning, AI, blockchain, Data related tools, and technologies. He is the Co-founder and editor of analyticslearn.com