What is Artificial Intelligence?

Artificial Intelligence(AI) is a kind of a blanket that covers different things today. In most of our minds, it is as parallel to “cooking”, we know what is it, but we speak only about end products.

Artificial Intelligence is more like that, we could speaking more like machine learning, deep learning or anything.

The base differences of each are essential, it’s not to the data scientists, also to the professional who can buy or use AI for their business.

The best part is that you needn’t have to know about advanced math or any algorithms, you should just know the differences and should be knowing how and where to effectively apply. Don’t have to be a master in it, Being a jack will lead a long way.

What is Machine Learning?

What is Machine Learning?

AI in business terms is known as Machine Learning(ML), it is the system that learns over a period of time. It learns from the pattern on how you have input the data. To perform different models to do the different task you use ML tools. Some of the most commonly used models are:

  1. Decision Tree.
  2. Random Forest.
  3. Hidden Markov.
  4. Naïve Bayes
  5. Support Vector Machines. 

These models work differently, but they can be used in combination with one another.

Decisions Tree

It works in the process, like answering a ranking of yes or no questions to fetch the result.

For example:

  1. Is there a difference in income this year vs the last year? (yes or no)
  2. Are the expenses higher than last year? (Yes or no)
  3. So on..

It is highly powerful and intuitive which is used in rules-based businesses like Credit risk assessments or any data applications. It is something like we do everyday decisions. Do I need to play music (yes), should I play blues (no).

artificial intelligence examples

Hidden Markov Models (HMM)

They are used in places like predicting Weather. HMM uses hidden state analyzing to observable state predictions. Example observable stated like rainy or sunny weather, another is like the hidden state can be emotions – it observers by eyebrow movement or by your voice.

By using the observing state we can even identify specific words or sounds. Many other models of ML work to give different solutions, these are some tools people use mostly in company contents and back-office process jobs, and customer experience area to give solutions.

How Does AI Take Decision?

How Does AI Take Decision?

The ML-based on the quality of data you input, it is highly efficient and highly accurate. All the tedious, manual and slow works can be transformed. Many technologies are there in the market which can mimic human intelligence.  This is the point we get into deep learning and neural networks.

Big discussions are happening like these technologies which are so advanced can mimic human smartness, at least they can surface like mirroring human thinking. Neural networks, like the human brain, can communicate one another depending on the task in hand. This is how we input in ML and neural networks are trained themselves. Highly complex concepts can learn.

Example:  Neural networks can spot a particular face or anything in a picture or even in a video.

Buyer and user should understand there are different tools for solving different issues, other kinds of approaches, and different models for AI & ML. Besides empowering you to expand and start its services to your company. If your planning for one it mostly comes with the packaged application of AI.

Example: Alfresco Intelligence Services, it gives AI services is a third party which is pre-integrated, like Comprehend (Amazon’s web services), Recognition (Image Analyser), and Textract ( data and text extractor). These services store AI output and you can use it when required in the business.

Decision-Making Technologies

applications of artificial intelligence

AI covers different kinds of technologies, which learns and takes decisions. Many systems are easy to understand. By setting the parameter it can take decisions based on our previous actions. Besides, neural networks can continue to develop by itself, it would be hard for us to know by its decision-making skills.

By knowing the approaches, models, and tools you should make sure that it is the right fit according to your requirements. You should decide its transparency the system has to be or not.  Human supervision required for some system. Depending on the system it would require more data or less data. 

Therefore, some system is more costly to manage and run, some require a lot of computing than others. You should take the right decision on the system which works better for you and to your requirements.

Try using pre-integrated applications, which processed specifically requirements.  You can get help from experts on handing the system. Do homework to make sure the right questions are asked and engage in the attachment of Artificial Intelligence in your company.

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