We all know there are two critical questions that are associated with every project that we get:
Cloud-Native evokes different responses from every engineer on any team. As a part of this visual presentation, we would like to get a common understanding of what is cloud native, talk about its pillars and which applications are a good candidate for the same.
AI has traditionally been deployed in the cloud. AI algorithms crunch massive amounts of data and consume massive computing resources. But AI doesn’t only live in the cloud. In many situations, AI-based data crunching and decisions need to…
In our previous post we have talked about different types of agents that can be built for business. Any type of agent (model-based, goal-based, utility-based, etc.) can be built as a learning agent (or not). Learning allows the agent to…
In the previous post, we discussed the environment in which the agent operates and the characteristics of those environments. In this post let us talk about the types of agents and challenges of data set for the agents.
There is a lot of interest in Machine Learning and AI. Ofcourse, a lot of it is still the level 1 of AI …
In the previous posts, we looked at the Rational Agent and the operating environment. In this post we would try to study the nature of the environment.
The environment is the Task Environment (problem) for which the Rational Agent is the solution. Any…
In our previous blog on understanding the basic AI concepts, we touched upon the creation of Rational Agents. Concept of rationality can be applied to wide variety of agents under any environments. In…
Well, a one working with spark is very much familiar with the ways of reading the file from…