Which of the following statements best describes big data and its relationship to AI?

Question

BlackTom AI · Accepted Answer

Large, diverse datasets improve model learning by exposing algorithms to many examples and variability, but quantity alone does not guarantee accurate or fair AI.

1. Relevant knowledge points and concepts
- Big data is commonly characterized by volume, variety, velocity, and veracity: very large amounts of data, multiple data types (structured and unstructured), high generation speed, and variable quality. 
- AI (machine learning) uses data to learn patterns; model performance depends on representativeness, label quality, and appropriate model architecture and training, not just raw size.
- Issues such as noise, bias, missing values, and overfitting show why quality and relevance matter. Techniques like transfer learning, data augmentation, and careful feature engineering can reduce dependence on sheer volume.

2. Step-by-step reasoning
- Compare each option against the definitions and practical experience of AI development.
- Determine whether the option accurately describes big data (includes unstructured and structured types, importance of quality, and not strictly necessary in extreme volume for every task).

3. (No numeric calculations required) Intermediate logical steps are: define big data → examine role in AI → evaluate claims about structure, exclusivity, and necessity → conclude which statement is balanced and accurate.

4. Why the correct answer is correct
- The chosen option acknowledges that large, diverse datasets help models identify patterns (true — more examples and diversity typically improve generalization) while also noting that data quality, relevance, and model design affect accuracy (true — poor data or wrong model undermines results). This balanced claim aligns with the four Vs and ML best practices.

5. Why the other options are incorrect
- Option 1: Incorrect — social media and sensors often produce unstructured data (text, images, audio), not only structured data.
- Option 2: Incorrect — big data includes traditional structured sources as well as unstructured types; it is not exclusive.
- Option 4: Incorrect — big data is not “mostly structured”; it frequently includes large amounts of unstructured data.
- Option 5: Incorrect — while large datasets help, AI can perform well with smaller or synthetic datasets using transfer learning, domain knowledge, or careful modeling; extreme volume is not always necessary.

6. Conclusion
The balanced statement that big data is valuable for AI because large, diverse datasets can help models identify patterns, but data quality, relevance, and model design also affect accuracy is correct and matches the provided answer.

Which of the following statements best describes big data and its relationship to AI?单项选择题

类似问题

Which best describes the relationship between AI and Big Data?

Is the following statement true or false? In the products of methylation-hydrolysis, every -OH group corresponds to the position of a glycosidic bond in the starting polysaccharide.

Which of the follwoing structures represents amylopectin?

Which of the following is true about an aldopentose?I. It is a monosaccharide.II. It contains a CHO groupIII. It is a disaccharide.IV. It is an oligosaccharide.

For stock A, we have 𝛽 𝑖 = 0.70. Suppose the expected market risk premium next year is 9% and the risk-free rate is 3%. What is the expected return of this stock based on the CAPM? (Please answer in % and round to 2 decimal places. If the answer is 8.057%, then in the box, write 8.06)

更多留学生实用工具

智能学习助手

风格化写作助手

论文查重助手

文献引用助手

课堂转译助手

课堂笔记助手

Quiz搜索助手

学校历年真题

智能刷题助手

智能匹配练习

希望你的学习变得更简单