Artificial Intelligence and AWS
Tags: aws, ai, machinelearning
Published: 2021-12-29 15:19:00

                   
Artificial Intelligence (AI) and Machine Learning and are slowly becoming a part of every tech domain. In fact, no tech company can better support its infrastructure without these two mandatory components. This article will discuss how artificial intelligence and machine learning integrate with amazon web services. 
Artificial intelligence is a science of making machines do the things which would otherwise require intelligence if it is done by man.
Machine-learning machine learning is an essential aspect of artificial intelligence. It is the process in which we make a machine respond to a situation without being explicitly programmed.
The difference between both is that artificial intelligence is the habit of a machine to react as a person responds to a situation intelligently; on the other hand, machine learning is when we make that machine learn how to respond to that particular situation. Nowadays, companies widely use machine learning to excel in their businesses.
The machine learning process goes on as it learns the patterns from past data and then implements that to make unpredictable impressive analyses, decisions, and predictions for the new data.
Following are some aspects of AI used widely nowadays;
•	NLP
•	Robotics 
•	Expert Systems
•	AI vision
•	Speech Analytics

An important aspect of AI is  NLP. Natural Language Processing or NLP is the application of artificial intelligence. All the machines based on AI can process human languages and then interpret them, which is actually the essential requirement of AI. A daily life example of NLP is a chatbot. When you type in something, the chatbot answers that question eliminating the need for a human to answer that question on the other side, and it’s been widely used for enhancing eCommerce services. For example, if you type in the chatbot, “I want shoes of XYZ brand, “it will quickly ask you, “Which color and size do you want. “

Then comes robotics. It brings the intelligent behavior to the robot to be able to provide these services to humans in unpredictable
and changing environments or just homes, hospitals, the marketplace, and other surroundings.
Then we have another impressive AI-based application called the expert systems. These expert systems are designed to solve complex problems by reasoning with knowledge using artificial intelligence. A machine can give advice like an expert lawyer or a doctor.

If we talk about vision(another AI advancement), a machine can see the objects around it like humans like a car. Now, this technology makes it easy to predict what is there in the background to do the automatic inspection
control the complete process and the way the guidance or board is actually recognizing or e-mail or
video or something like that.
Then comes speech analytics, an outstanding feature of AI.
It can process the speech or convert the written information to the speech.
It amazingly simplifies the interaction between the machines are. The best example of this is Google Maps.

There are several steps involved in successfully implementing AI and Ml in the business. You have to make teams first to whom you will allocate the tasks. You will need a Front-end team, analysts and data scientists, and DevOps experts. Firstly, you have to identify the problem and the right related prediction that would benefit your business; this is mainly done by your front-end team members. Then you need the related data based on past needs like your previous transactions, sales operations, prices, etc., that could benefit your business. The data science team will then process this data to analyze it according to the given problem. Once that data is processed and aggregated, a machine learning model is built based on that analysis. Then that machine learning model is run, and the prediction output of the model is applied back to the system to make more informed and intelligent decisions that will provide long-term benefits to your business. So this is how we implement AI and Ml in business growth. 


Now we will see how Amazon web services provide services using AI and ML.AWS provides machine-learning-based tools and services tailored to meet your needs and level of expertise. Developers can easily add these intelligent services to any application with various pertained services like computer vision, language analytics, speech, and chatbot functionality. For that, they don’t even need to make these services on their own. Instead, these are the services in which you just have to put your data, and this unique system will provide you these services of vision, chatbot functionality, etc. So most of your work will be done by the AWS cloud.

AWS supports all the machine learning frameworks like Tensorflow, Caffe2, and ApacheMXNet so that you can bring or develop any model you want.
AWS provides you loads of options in categories of GPU, FPGAs instance types.FPGAs are alternative prototypes for processors or ASICs (chips) designing, which are constantly reprogrammed until the required circuit or processor is bug-free.

Another service from AWS is that you don’t have to pay for the infrastructure or hardware. Rather , you only have to pay for the amount of time you are using these services on the AWS platform.




AI is implemented on Amazon using these three services :
•	Amazon Polly 
•	Amazon Lex
•	Amazon Rekognition