CT-AI · Question #4
Which ONE of the following hardware is MOST suitable for implementing Al when using ML?
The correct answer is B. Hardware supporting fast matrix multiplication. Matrix multiplication is a fundamental operation in many machine learning algorithms, especially in neural networks and deep learning. Hardware optimized for fast matrix multiplication, such as GPUs (Graphics Processing Units), is most suitable for implementing AI and ML…
Question
Which ONE of the following hardware is MOST suitable for implementing Al when using ML?
Options
- A64-bit CPUs.
- BHardware supporting fast matrix multiplication.
- CHigh powered CPUs.
- DHardware supporting high precision floating point operations.
How the community answered
(27 responses)- A11% (3)
- B78% (21)
- C4% (1)
- D7% (2)
Explanation
Matrix multiplication is a fundamental operation in many machine learning algorithms, especially in neural networks and deep learning. Hardware optimized for fast matrix multiplication, such as GPUs (Graphics Processing Units), is most suitable for implementing AI and ML because it can handle the parallel processing required for these operations efficiently.
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