Which of the following statements about the evolution of AI is not true?

Question

BlackTom AI · Accepted Answer

Hardware scaling — GPUs and specialized accelerators — has been a primary, not secondary, driver of modern AI progress. Below is a structured explanation that demonstrates why the statement "The growth in the power of processors has been a secondary driver in the rapid evolution of AI." is not true.

1) Relevant knowledge points and concepts
- Primary drivers of recent AI progress: compute (hardware), large datasets, and algorithmic/architectural advances (e.g., deep learning, transformers).
- Key hardware: GPUs (for parallel matrix ops), TPUs and other accelerators, and cloud-scale clusters enabling training of very large models.
- Empirical evidence: scaling laws for neural networks show model performance improves predictably with increased compute; landmark models (BERT, GPT-series) required vast compute to train.

2) Step-by-step reasoning
- The statement labels processor growth as “secondary.” Evaluate whether hardware improvements were central or marginal.
- Modern deep learning workloads depend on parallel matrix multiplications; GPUs offered orders-of-magnitude speedups vs. CPUs for these tasks.
- Specialized chips (TPUs) and massive distributed clusters enabled training models with billions/trillions of parameters that were previously infeasible.
- Research (e.g., scaling law papers) empirically ties improvements to increases in compute; many breakthroughs were only practical once hardware scaled.

3) Intermediate steps / evidence (no numeric calculations required)
- GPUs (mid-2000s onward) enabled training deep nets at practical timeframes.
- 2012 ImageNet success and subsequent language-model scaling depended on abundant compute.
- Transformer-based large-scale models (2018 onward) required cloud compute and accelerators.

4) Why the correct answer is correct
- Because processor power growth was foundational and often a primary enabler of rapid advances, calling it “secondary” misstates its role. Hardware advances and large-scale compute are central to recent AI evolution.

5) Why other options are incorrect (brief)
- “Advances…made possible personal assistants like Siri.” True — speech recognition and NLP advances enabled assistants.
- “Growth relied on refinement of algorithms…and investments.” True — broad research, engineering, and funding have driven progress.
- “In the last decade, there have been numerous fundamental conceptual breakthroughs.” Reasonable to call out several (deep learning architectures, attention/transformer, GANs, RL progress), so this option is presented as true.
- “In the last decade, significant progress has been made…” True — overall progress has been substantial.

6) Conclusion
The false statement is the one claiming processor growth was a secondary driver. This matches the provided correct answer: "The growth in the power of processors has been a secondary driver in the rapid evolution of AI."

Which of the following statements about the evolution of AI is not true? 单项选择题

类似问题

在哪个时期，人们对人工智能的未来感到悲观？ In what time period are people pessimistic about the future of artificial intelligence?

The implementation and loading phase of the Database Life Cycle (DBLC) involves _____.

Which of the following parameters is used to determine the concentration of protein in a spectrophotometer?

What are the units of absorbance?

What is the concentration of protein in the stock solution of BSA used for the standard curve?

When dissolved in water, hydrogen bromide (HBr) forms hydrobromic acid. Determine the hydroxide ion concentration in a 4,500 mL solution containing 3.78 g hydrogen bromide; K = 1.00 x 10¯14.

UVA radiation has a wavelength of approximately 390. nm. What is the energy of a photon of this light? (Planck's constant is 6.626 x 10 − 34 J s)

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