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Buddha vs Child Paradigm

“Artificial Intelligence (AI) is like a child, who needs time to learn and adapt, whereas a typical IT system is like Buddha who knows everything about the problem it was supposed to solve.”   
          - Devesh Rajadhyax, Founder, Cere Labs.

Images: By Purshi - Own work, CC BY-SA 3.0,
By Shaun MItchem - Diggy starts to learn to walk, CC BY 2.0, 

Let us in this post try to elaborate on this Buddha vs Child Paradigm which Devesh coined for 
differentiating between conventional IT systems and AI. It is essential to know the difference because it 
helps in building the right kind of attitude towards implementing AI systems. A typical IT system such as 
ERP does the job for what it was implemented. It is assumed that it will solve the problem for what it was 
made. Take for example an accounting system like Tally. It will help you to manage your accounts in highly
accurate manner. This system is like a Buddha, who is enlightened from the start. We can’t expect it to do
any mistakes (except the initial software bugs that are rectified). Or take for example a calculator. 
A calculator will always give you 1+2 = 3, no matter you do this operation million times assuming that 
the calculator is in a working condition. Thus we expect an IT system to work perfectly, and it does indeed.

But take an AI system. A typical AI system learns from data. Initially it is like a child, finding it difficult to 
even crawl, but slowly and steadily it learns how to walk as it is exposed to more situations which in the 
case of AI is more data. Maturity of an AI system comes with more and more exposure to data. 
In the example of calculator, an AI system will get many examples such as  1+2 = 3, and over a period 
of time it will learn how to perform addition. Initially it might fail to predict 3, but it will come closer and 
closer to 3.

As you have noticed there is a paradigm shift in understanding and using an AI system compared to an 
IT system. Let us summarize few differences…

IT System
AI System
Matured to solve the problem right from 
the start it was supposed to.
Keeps getting matured as it is exposed to 
more data.
Results are expected to be accurate.
Results keep improving.
Patience by IT executives is only required 
till implementation.
Patience is required throughout the lifetime 
of the system.
Mistakes in output can’t be tolerated.
Mistakes in output can be tolerated.
100% accuracy.
Accuracy tries to reach 100%, but is 
mostly probabilistic.

AI systems are the only option to solve problems which are not well defined, such as prediction or
anomaly. That’s why people tolerate its childish behavior.

Thus it is essential to understand this difference between an IT system and an AI system. It will help an 
executive to assist AI researchers and engineers in achieving great results over a period of time.

Siddhesh Wagle,
Head of Research,
Cere Labs


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