Large Language Models (LLMs) refer to large general-purpose language models that can be pre-trained and then fine-tuned for specific purposes. They are trained to solve common language problems, such as text classification, question answering, document summarization, and text generation. The models can then be adapted to solve specific problems in different fields using a relatively small size of field datasets via fine-tuning.
The ability of LLMs taking the knowledge learnt from one task and applying it to another task is enabled by transfer learning. Pre-training is the dominant approach to transfer learning in deep learning.
LLMs predict the probabilities of next word (token), given an input string of text, based on the statistical properties of the language in the training data. Typical training corpora for LLMs include natural language (e.g. web data). But LLMs can also be trained on other types of languages (e.g. programming languages).
LLMs are large, not only because of their large size of training data, but also their large number of parameters. They display different behaviors from smaller models and have important implications for those who develop and use A.I. systems. First, the ability to solve complex tasks with minimal training data through in-context learning. Second, LLMs are accessed primarily through a prompting interface, which necessitates human comprehension of how LLMs function and the ability to format tasks in a way that LLMs can comprehend. Third, the development of LLMs no longer distinguishes between research and engineering. The training of LLMs requires extensive hands-on experience in processing large amounts of data and training in distributed parallel training. To develop effective LLMs, researchers must address complex engineering issues and work alongside engineers or have engineering expertise themselves.
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To prompt ChatGPT effectively, it is important to be specific about what you are looking for, and provide context and examples to help ChatGPT generate accurate and relevant responses. Asking follow-up questions and giving feedback to ChatGPT’s responses can also help it learn and improve over time. Besides, it is also recommended to experiment with different prompts.
What does effective prompting look like? Here’s an example:
User: I want you to act as a personal trainer. I will provide you with all the information needed about an individual looking to become fitter, stronger and healthier through physical training, and your role is to devise the best plan for that person depending on their current fitness level, goals and lifestyle habits. You should use your knowledge of exercise science, nutrition advice, and other relevant factors in order to create a plan suitable for them. My first request is "I need help designing an exercise program for someone who wants to lose weight."
ChatGPT: Sure, I can help design an exercise program for someone who wants to lose weight. Here are some general guidelines and considerations for creating an effective exercise plan:
1. Identify goals: Before starting any exercise program, it's important to clearly define your goals. In this case, the primary goal is weight loss. It's also important to consider other goals such as improving cardiovascular health, building strength, and increasing endurance.
2. Assess current fitness level: ...
3. Choose appropriate exercises: ...
4. Determine frequency and duration: ...
5. Consider nutrition: ...
Here's an example of a weekly workout plan for someone who wants to lose weight:
Monday: 30 minutes of brisk walking, followed by a full-body strength training workout
Tuesday: Rest day
Wednesday: 30 minutes of jogging, followed by a core-focused strength training workout
Thursday: Rest day
Friday: 30 minutes of cycling, followed by a lower-body strength training workout
Saturday: 30 minutes of brisk walking, followed by an upper-body strength training workout
Sunday: Rest day
... Remember to listen to your body, start slowly and gradually increase the intensity and duration of your workouts. Consistency is key, and remember that weight loss is a journey, not a destination. Good luck with your fitness journey!
User: I don't have time for training on Mondays. I am also not a fan of cycling. Give me a more interesting workout plan.
ChatGPT: Sure, I can revise the workout plan to better suit your preferences and schedule. Here's an updated plan:
Monday: Rest day
Tuesday: 30 minutes of brisk walking, followed by a full-body strength training workout
Wednesday: Rest day
Thursday: 30 minutes of jogging, followed by a core-focused strength training workout
Friday: 30 minutes of swimming, followed by a lower-body strength training workout
Saturday: 30 minutes of hiking or outdoor activities, followed by an upper-body strength training workout
Sunday: Rest day
This updated plan includes more outdoor activities like hiking, which can be a fun and challenging way to get cardio exercise. Swimming is also a great low-impact cardio exercise that can be easier on your joints compared to jogging or cycling. Strength training is still a key component of the plan, as it helps build lean muscle mass and boost metabolism. ...
User: How can I make sure I'm not overdoing it with strength training?
ChatGPT: It's important to listen to your body and not push yourself too hard with strength training, as overdoing it can lead to injury or muscle soreness that can hinder your progress. Here are some tips to make sure you're not overdoing it with strength training:
1. Start with lighter weights: ...
2. Gradually increase weight and reps: ...
3. Take rest days: ...
4. Listen to your body: ...
5. Work with a trainer or coach: ...
Remember that strength training should be challenging, but it should also be enjoyable and sustainable. By listening to your body and gradually progressing your workouts, you can avoid overdoing it and achieve your fitness goals safely and effectively.
Reference: Act as a Personal Trainer
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