Consider the following statements :
I. It is expected that Majorana 1 chip will enable quantum computing.|
II.Majorana 1 chip has been introduced by Amazon Web Services (AWS).
III.Deep learning is a subset of machine learning.
Which of the statements given above are correct?
(a) I and II only
(b) II and III only
(c) I and III only
(d) I, II and III
The correct answer is (c) I and III only.
Explanation
- I. It is expected that Majorana 1 chip will enable quantum computing.
- This is correct. The “Majorana 1 chip” refers to a breakthrough by Microsoft in its long-running effort to create a new type of quantum bit (qubit) based on Majorana zero modes. These are theoretical quasiparticles. The goal of this research is to build a “topological qubit,” which is expected to be much more stable and resistant to environmental “noise” than current qubits, thereby enabling more reliable and scalable quantum computing.
- II. Majorana 1 chip has been introduced by Amazon Web Services (AWS).
- This is incorrect. This line of research and the associated hardware breakthroughs have been announced by Microsoft, not Amazon Web Services.
- III. Deep learning is a subset of machine learning.
- This is correct. This is a fundamental concept in computer science.
- Artificial Intelligence (AI) is the broad field.
- Machine Learning (ML) is a subset of AI where systems “learn” from data.
- Deep Learning (DL) is a subset of ML that uses multi-layered “deep” artificial neural networks to solve complex problems.
- This is correct. This is a fundamental concept in computer science.
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Quantum Computing and Majorana Fermions
The central challenge in quantum computing is the stability of its basic unit, the qubit. Unlike a classical bit (which is a 0 or a 1), a qubit can exist in a “superposition” of both 0 and 1 at the same time. This property gives quantum computers their potential power.
However, qubits are incredibly fragile. The slightest noise, vibration, or temperature change can cause them to lose their quantum state and “decohere,” leading to errors in calculation.
Microsoft’s research into Majorana fermions is a novel approach to solve this.
- Topological Quantum Computing: This is a theoretical type of quantum computer that would encode information in the “braiding” of quasiparticles called anyons or Majorana fermions.
- Majorana-based Qubit: The information is stored not in a single, fragile particle but in the shared, “topological” properties of a pair of Majorana particles. This makes the qubit inherently stable and immune to local noise.
- Significance: If successful, this would be a major leap toward a fault-tolerant quantum computer, which is the ultimate goal of the field.
The AI Hierarchy
It is helpful to visualize the relationship between AI, ML, and DL as a set of nested dolls.
- Artificial Intelligence (AI): This is the outermost, broadest field. It refers to any system or machine that mimics human intelligence to perform tasks, such as problem-solving or decision-making.
- Machine Learning (ML): This is a subset of AI. Instead of being explicitly programmed with rules for every task, an ML system is “trained” on large amounts of data. It learns to recognize patterns and make predictions or classifications on its own.
- Deep Learning (DL): This is a specialized subset of ML. It uses a specific type of algorithm called an artificial neural network (ANN). The “deep” in its name refers to the fact that these networks have many layers, much like the neurons in a human brain. This depth allows them to learn and identify extremely complex patterns from vast datasets, powering everything from advanced image recognition to large language models (like the one you are interacting with).
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