What is the main architectural innovation in ChatGPT that allows it to handle complex language tasks?

Question

BlackTom AI · Accepted Answer

The question asks for the main architectural innovation in ChatGPT that enables handling complex language tasks.
Option 1: Decision trees. While decision trees are a simple and interpretable model, they lack the capacity to model long-range dependencies in natural language and do not scale to the complexities ChatGPT handles. This makes them inadequate as the core architecture for large language models.
Option 2: Convolutional neural networks. CNNs are powerful for grid-structured data like images and have been adapted for some text tasks, but they are not the primary architecture that enables scalable, context-aware language generation at the scale of ChatGPT. They typically process local neighborhoods and struggle with long-range dependencies without substantial modifications.
Option 3: Transformer architecture with attention mechanisms. This option identifies the key design that enables models like ChatGPT to process and generate coherent text. The transformer uses self-attention to weigh relationships between all tokens in a sequence, capturing long-range dependencies, parallelizing training, and scaling to large datasets. This approach is central to modeling complex language structure and semantics, and it underpins the capabilities of ChatGPT.
Option 4: Rule-based expert systems. Rule-based systems rely on hand-crafted rules and explicit if-then logic, which do not possess the statistical learning and generalization necessary for open-ended language understanding and generation. They cannot match the flexibility and scale of neural transformer architectures for ChatGPT tasks.
In summary, options 1 and 2 describe older or less suitable architectures for modern large-language modeling, option 4 describes a non-learning, rule-based approach, whereas option 3 captures the transformative architectural innovation—the Transformer with attention—that enables handling complex language tasks at scale.

What is the main architectural innovation in ChatGPT that allows it to handle complex language tasks?

查看解析

登录即可查看完整答案

类似问题

A team of data scientists is experiencing poor performance with their Transformer model. After inspecting their implementation, you find several suspicious design choices. Which one would you identify as the MOST problematic based on the architectural principles discussed in the lecture?

What operations are part of a standard Transformer block? (Select all that apply.)

In a consumer society, many adults channel creativity into buying things

Economic stress and unpredictable times have resulted in a booming industry for self-help products

People born without creativity never can develop it

A product has a selling price of $20, a contribution margin ratio of 40% and fixed cost of $120,000. To make a profit of $30,000. The number of units that must be sold is: Type the number without $ and a comma. Eg: 20000

Which of the following statement regarding cost is correct:

Under the assumptions used in cost-volume-profit analysis, as the activity increases:

更多留学生实用工具

考试浏览器助手

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