1. What are some of the applications of LLMs? LLM의 응용 분야에는 어떤 것들이 있습니까?
(1) LLMs can be used for many tasks, including:1) Writing2) Translating3) Coding4) Answering questions5) Summarizing text6) Generating non-creative discrete probabilities, classes, and predictions.
LLM은 다음을 포함하는 많은 작업에 사용될 수 있다:1) 쓰기 2) 번역 3) 코딩 4) 질문에 대한 답 5) 텍스트 요약 6) 비창조 이산 확률, 클래스 및 예측 생성
(2) LLMs can be used for many tasks, including:1) Writing2) Translating3) Coding4) Answering questions5) Summarizing text6) Generating non-creative discrete probabilities
LLM은 다음을 포함하는 많은 작업에 사용될 수 있다:1) 쓰기 2) 번역 3) 코딩 4) 질문에 대한 답 5) 텍스트 요약 6) 비창조 이산 확률 생성
(3) LLMs can be used for many tasks, including:1) Writing2) Translating3) Coding4) Answering questions5) Summarizing text6) Generating non-creative discrete classes
LLM은 다음을 포함하는 많은 작업에 사용될 수 있다:1) 쓰기 2) 번역 3) 코딩 4) 질문에 대한 답 5) 텍스트 요약 6) 비창조 불연속 클래스 생성
(4) LLMs can be used for many tasks, including: 1) Writing2) Translating3) Coding4) Answering questions5) Summarizing text6) Generating non-creative discrete predictions
LLM은 다음을 포함하는 많은 작업에 사용될 수 있다:1) 쓰기 2) 번역 3) 코딩 4) 질문에 대한 답 5) 텍스트 요약 6) 비창조 불연속 예측 생성
(5) LLMs can be used for many tasks, including:1) Writing2) Translating3) Coding4) Answering questions5) Summarizing text6) Generating creativecontent
LLM은 다음을 포함하는 많은 작업에 사용될 수 있다:1) 쓰기 2) 번역 3) 코딩 4) 질문에 대한 답 5) 텍스트 요약 6) 창의적 콘텐츠 생성
정답은 (5)번
2. What are some of the challenges of using LLMs? Select three options.
LLM을 사용할 때 어떤 어려움이 있습니까? 세 가지 옵션을 고르시오.
(1)After being developed, they only change when they are fed new data.
개발된 후, 그들은 새로운 데이터를 공급받을 때만 변화한다.
(2)They can be biased.
그들은 편향적일 수 있다.
(3)They can be used to generate harmful content.
그들은 해로운 내용을 생성하는 데 사용될 수 있다.
(4)They can be expensive to train.
그들은 훈련하는 데 많은 돈이 들 수 있다.
정답은 (2),(3),(4)번
3. What are some of the benefits of using large language models (LLMs)?
(1) LLMs have a number of benefits, including:1) They can generate human-quality text.2) They can be used for many tasks, such as text summarization and code generation.3) They can be trained on massive datasets of text, images, and code.4) They are constantly improving.
LLM은 다음과 같은 여러 가지 이점이 있습니다: 1) 그들은 사람 수준의 텍스트를 생성할 수 있습니다. 2) 텍스트 요약 및 코드 생성과 같은 많은 작업에 사용될 수 있습니다. 3) 그들은 텍스트, 이미지, 코드의 대규모 데이터 세트에서 훈련될 수 있습니다. 4) 그들은 계속해서 개선되고 있습니다.
(2) LLMs have a number of benefits, including:1) They can generate non-probabilities and human-quality text.2) They can be used for many tasks, such as text summarization and code generation.3) They can be trained on massive datasets of text, image, and code.4) They are constantly improving.
(3) LLMs have many benefits, including: 1) They can generate probabilities and human-quality text.2) They can be used for many tasks, such as text summarization and code generation.3) They can be trained on massive datasets of text and code.4) They are constantly beingimproved.
(4) LLMs have many benefits, including: 1) They can generate discrete classes and human-quality text.2) They can be used for many tasks, such as text summarization and code generation.3) They can be trained on massive datasets of text and code.4) They are constantly improving.
(5) LLMs have many benefits, including: 1) They can generate human-quality text. 2) They can be used for a variety of tasks.3) They can be trained on massive datasets of text and code. 4) They are constantlyimproved.
정답은 (4)번
4. What are large language models (LLMs)?:
(1) Generative AI is a type of artificial intelligence (AI) that can create new content, such as discrete numbers, classes, and probabilities. It does this by learning from existing data and then using that knowledge to generate new and unique outputs.
(2)An LLM is a type of artificial intelligence (AI) that can generate human-quality text. LLMs are trained on massive datasets of text and code, and they can be used for many tasks, such as writing, translating, and coding.
LLM은 사람 수준의 텍스트를 생성할 수 있는 인공지능(AI) 유형입니다. LLM은 텍스트와 코드의 대규모 데이터 세트에서 학습하며, 쓰기, 번역, 코딩 등 많은 작업에 사용될 수 있습니다.
(3)Generative AI is a type of artificial intelligence (AI) that only can create new content, such as text, images, audio, and video by learning from new data and then using that knowledge to predict a discrete, supervised learning output.
(4) Generative AI is a type of artificial intelligence (AI) that only can create new content, such as text, images, audio, and video by learning from new data and then using that knowledge to predict a classification output.
정답은 (2)번