"Clarifying questions and Assumptions
ChatGPT search means the search function inside the chat app? OR ChatGPT search Chrome extension? Assumption: Search inside the chat app.
Is there any location restriction in this analysis? Assumption: USA only.
Is there any user segment restriction in this analysis? Assumption: All user segments.
Are we assuming the ChatGPT search already exists or going back in time before the ChatGPT search existed? Assumption: Go back in time"
Darpan D. - "Clarifying questions and Assumptions
ChatGPT search means the search function inside the chat app? OR ChatGPT search Chrome extension? Assumption: Search inside the chat app.
Is there any location restriction in this analysis? Assumption: USA only.
Is there any user segment restriction in this analysis? Assumption: All user segments.
Are we assuming the ChatGPT search already exists or going back in time before the ChatGPT search existed? Assumption: Go back in time"See full answer
"Reinforcement Learning is a type of machine learning where an agent learns to make decisions by trying out different actions and receiving rewards or penalties in return. The goal is to learn, over time, which actions yield the highest rewards.
There are three core components in RL:
The agent — the learner or decision-maker (e.g., an algorithm or robot),
The environment — everything the agent interacts with,
Actions and rewards — the agent takes actions, and the environmen"
Constantin P. - "Reinforcement Learning is a type of machine learning where an agent learns to make decisions by trying out different actions and receiving rewards or penalties in return. The goal is to learn, over time, which actions yield the highest rewards.
There are three core components in RL:
The agent — the learner or decision-maker (e.g., an algorithm or robot),
The environment — everything the agent interacts with,
Actions and rewards — the agent takes actions, and the environmen"See full answer
"Clarifying
When we say cloud gaming, we refer to a video gaming experience using cloud computing, right? Assumption: Yes.
Understanding of cloud computing first. I'll use some analogies:
Imagine you are looking to do heavy computing but don't have a powerful CPU and GPU.
CPU and GPU are like your big calculators.
You can buy a powerful CPU and GPU, but problems:
It costs a lot to buy.
It costs a lot to run.
You don't need it 24-7.
You are not a un"
Darpan D. - "Clarifying
When we say cloud gaming, we refer to a video gaming experience using cloud computing, right? Assumption: Yes.
Understanding of cloud computing first. I'll use some analogies:
Imagine you are looking to do heavy computing but don't have a powerful CPU and GPU.
CPU and GPU are like your big calculators.
You can buy a powerful CPU and GPU, but problems:
It costs a lot to buy.
It costs a lot to run.
You don't need it 24-7.
You are not a un"See full answer
"Tell me about a time you were with someone on your team who was struggling to meet objectives.
How did you address the situation?
What kind of feedback did you give the individual?
What was the outcome?"
Jawahir Y. - "Tell me about a time you were with someone on your team who was struggling to meet objectives.
How did you address the situation?
What kind of feedback did you give the individual?
What was the outcome?"See full answer
"Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"
Joshua R. - "Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"See full answer