Artificial intelligence as a Service

Quick Guide to AI as a Service

With the development of advanced technology, it has become easier to manage the business on a global scale.

Automation has added a lot of benefits and almost replaced manual work in organizations. Some companies, as a third-party, offer AI outsourcing. This service is known as Artificial Intelligence as a Service.

This article contains a quick guide about artificial intelligence definition, AI as a service, companies providing these services, pros, and cons, etc.


What is artificial intelligence definition ?

The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

The English Oxford Living Dictionary

Artificial intelligence is a branch of computer science that aims to create machines performing intellectual tasks.

It represents the creation of intelligent machines that react and work like humans.

Been a big hype topic for a long time, many pieces of research, innovation, and development are been carries out in this field.

artificial intelligence definition
Architecture

Some of the top AI trends for 2020 are –

  1. Virtual Agents
  2. Speech Recognition
  3. Natural Language Creation
  4. AI-Optimized Hardware
  5. Content Creation

These AI trends are shaping our today and tomorrow. The latest technology for 2020 will be beneficial for modern culture using an outlook of an improved world.

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Everything-as-a-Service (X-a-a-S)

Everything as a service (XaaS) is a term from cloud computing. It describes a broad category of services and applications related to remote access to technologies.

There are now a large number of ‘as a service’ abbreviations present. Some of them are Software As A Service (SAAS), Platform As A Service(PAAS), Infrastructure As A Service(IAAS), Algorithm as a service(AAAS).

Software as a service (SaaS) is a software distribution model where a third-party provider hosts applications and makes them available to customers over the Internet.

It is among the three main categories of cloud computing, alongside infrastructure as a service (IaaS) and platform as a service (PaaS). Acronym overload?

artificial intelligence definition

What is AI as a service?

Just as we have services like SAAS, PAAS, IAAS by cloud. AI provides a service called AIaaS.

Artificial Intelligence as a Service (AIaaS) is a third-party offering of AI outsourcing.

Cloud AI service provides specialized hardware required for a few AI tasks. For eg. GPU based processing for intensive workloads, etc.

No big investments in hardware and software are required to use AI.

AIaaS improves Time-to-Value significantly. Fast testing of new approaches to your problems.


High level and Low-level AI as a Service

Low-level AIaaS –

Low-level AI or weak AI or narrow AI is that intelligence that focuses on one narrow task. They implement a limited part of the mind and seem to be very intelligent at it.

They consist of Classic Machine Learning algorithms like Classification, Regression, Clustering – Bayesian Networks – Reinforcement Learning, Representation Learning – Genetic Algorithms.

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Low-Level AIaaS requires expert knowledge to implement. The benefit is that it allows the creation of innovative solutions for unsolved, non-standardized problems.

They also consist of processing pipelines. It includes data collection and pre-processing, training, parameter optimization, testing, etc.

High-level AIaaS

High level or strong AI which is defined as a machine having the ability to apply intelligence to any problem.

It doesn’t only focus on one problem. It sometimes considered requiring consciousness mind.

Strong AI is capable of all and any cognitive functions that a human may have. In essence, it’s similar to the real human mind. They consist of Deep Learning with Artificial Neural Networks (ANNs) – Convolutional neural network (CNN) – Autoencoder – Recurrent neural network (RNN) – Long/Short Term Memory (LSTM) – problem-oriented solutions/algorithms i.e. face recognition, text-to-speech – Solve a standardized problem.

High-level AIaaS has a simple interface and is easy to handle by non-AI experts.

Microsoft Azure, AWS, Google Cloud provides low level and high-level AI services up to a great extent. Detailed information is given below.


Market overview of AIaaS

AI is one of the fastest-growing technologies in past years. The global artificial intelligence market size is expected to reach $169,411.8 million in 2025, from $4,065.0 million in 2016.

My blind bird

Following companies provides AI as a service-

AWS DataRobot Algothmia
Data ikuBigml Google Cloud Platform

According to Amazon:
In the cloud, 81% of Deep learning projects run on AWS
85% of Tensor Flow projects in the cloud run on AWS

Below are some of the services provided by these companies.

AI ServicesLow LevelHigh Level
MS AzureML Studio :
1. Anomaly Detection
2. Clustering
3. Statistical Functions
4. Text Analytics
Cognitive Services :
1. Language
2. Speech
3. Search
4. Vision

Google CloudLarge Scale Machine Learning
Service –
Custom models from regression
models to image classification based on deep learning
Google Cloud Job Discovery –
Google Cloud Video Intelligence –
Google Cloud Vision- Google Natural Language.
AWS AWS Machine Learning –
Algorithms: Regression, classification (binary/multi-class)
Amazon Lex: – natural language understanding
(NLU) automatic speech recognition
(ASR) Amazon Recognition: – visual search and image recognition

Pros and Cons of AIaaS

Ai as a Service

PROS- of AIaaS

  1. Access and work with all data from a central location.
  2. Your organization has fewer responsibilities as data center infrastructure and environment are handled for you.
  3. Quick scale infrastructure up and down as needed is possible, allowing you to quickly test new products and achieve a faster time to market.
  4. Increased data security by the provider.
  5. And much more !!!

CONS- of AIaaS

  1. Mostly not open source.
  2. Not clear what algorithm is implemented, what parameters are used.
  3. Like any other software: implementations can be buggy.
  4. Systematic tests recommended.
  5. AIaaS aspects hinder the comparability of services between providers.

The Market of AI as a Service

As mentioned above, globally AI market size is expected to reach $169,412 million in 2025, from $4,065 million in 2016.
you can refer to this site for complete STATS.

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EndNote

AI as a service helps organizations to scale in less time improving the overall performance of the business.

The AI Layer abstract your models from infrastructure so that you can do more of what matters to scale.

It can enhance the customer experience in a contact center, forecast demand more accurately, improve healthcare analytics, and much more.

Depending upon your need and usage of this technology you can prefer any of the above companies. Some of them do provide a free trial.

Comment down your views about this technology.

Feel free to contact us!

Thank you!

2 thoughts on “Quick Guide to AI as a Service”

  1. “Nice article.
    Artificial intelligence for startups and businesses is an essential thing in this competitive business environment.
    The author shared interesting facts regarding how can we use artificial intelligence and its necessity.
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