Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 65 discussion

A. Diminua o valor da temperatura. ✅ Explicação:O parâmetro temperatura controla o nível de aleatoriedade nas respostas geradas por um modelo de linguagem. Temperatura baixa (ex: 0.2) → respostas mais determinísticas e consistentes. Temperatura alta (ex: 0.8 ou 1.0) → respostas mais variadas e criativas. Aplicação ao caso: Para que o LLM produza respostas mais consistentes ao mesmo prompt (como é desejado na análise de sentimentos, onde a estabilidade na resposta é essencial), a empresa deve diminuir a temperatura.

A. Decrease the temperature value: The temperature parameter controls the randomness of the model’s output. Lower temperatures make the model more deterministic and lead to more consistent and focused responses, while higher temperatures introduce more randomness and variety. For sentiment analysis, where you want consistent outputs for the same input, decreasing the temperature will help achieve more predictable and reliable results.

Lowering the temperature value in an LLM controls the randomness of the model's output. A lower temperature (close to 0) makes the model's predictions more deterministic and consistent, leading to similar outputs for identical prompts. This is particularly beneficial in tasks like sentiment analysis, where consistency and reliability in responses are crucial.

A. Decrease the temperature value. Lowering the temperature value reduces the randomness of predictions from a large language model (LLM) and makes the output more deterministic and consistent. This is ideal for producing consistent responses to the same input prompt during sentiment analysis.