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NEW QUESTION: 1
You are designing an AI solution in Azure that will perform image classification.
You need to identify which processing platform will provide you with the ability to update the logic over time.
The solution must have the lowest latency for inferencing without having to batch.
Which compute target should you identify?
A. graphics processing units (GPUs)
B. field-programmable gate arrays (FPGAs)
C. central processing units (CPUs)
D. application-specific integrated circuits (ASICs)
Answer: B
Explanation:
FPGAs, such as those available on Azure, provide performance close to ASICs. They are also flexible and reconfigurable over time, to implement new logic.
Incorrect Answers:
D: ASICs are custom circuits, such as Google's TensorFlow Processor Units (TPU), provide the highest efficiency. They can't be reconfigured as your needs change.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-accelerate-with-fpgas
NEW QUESTION: 2
CORRECT TEXT
What are the drawbacks of quick create?
Answer:
Explanation:
The
fields which are displayed in the quick create page layout (e.g.while creating a new contact, if we use quick create to create a new account on the fly) cannot be modified/selected/chosen by us & validation rules don't fire (for the account which is created quickly using quick create) which is a limitation of Salesforce.
NEW QUESTION: 3
DRAG DROP
Answer:
Explanation:
Explanation:
References:
http://msdn.microsoft.com/en-us/library/ms141003.aspx
http://msdn.microsoft.com/en-us/library/ms141261.aspx
http://msdn.microsoft.com/en-us/library/ms141722.aspx
http://msdn.microsoft.com/en-us/library/ms139895.aspx