COURSE Congratulations you've made it to the last chapter! Now it's time to put it all together and learn how to create unique and complex prompts. In the following, you'll use our recommended structure for leading complex prompts. In the second half of the chapter, we'll show some industry-specific prompts and explain what these mention...
Lesson Some bad news: Claude sometimes "hallucinates" and makes untrue or unreasonable statements. The good news is that there are techniques that can help you minimize the occurrence of hallucinations. In the following, we will discuss a few of these techniques, which include: Giving Claude the opportunity to answer questions he doesn't know the answers to...
Enable Builder Smart Programming Mode, unlimited use of DeepSeek-R1 and DeepSeek-V3, smoother experience than the overseas version. Just enter the Chinese commands, even a novice programmer can write his own apps with zero threshold.
Lesson Giving Claude examples of how you want it to behave (or not behave) is very effective for: Getting the right answer Getting the answer in the right format This type of hinting is also known as "sample less hinting". You may also encounter "zero samples", "n samples", or "same book"...
Lesson How would you fare if someone suddenly woke you up and immediately asked you several complex questions that you had to answer right away? Probably not as well as if you had time to think before answering. And guess what, the same goes for Claude. Giving Claude time to think gradually can sometimes make the difference in his answers...
Course Claude can format its output in many ways. All you need to do is ask it to do so! One way is to use XML tags to separate responses from other extraneous text. You've learned that you can use XML tags to make prompts clearer and easier for Claude to parse...
Lesson Often, instead of writing complete prompts, we want prompt templates that can be modified later based on additional input data and then submitted to Claude.This is useful if you want Claude to perform the same task each time, but the data Claude uses may be different each time...
Lesson Continuing on the theme of Claude having no context other than the information you provide, it is sometimes important to have Claude play a specific role (with all the necessary context), which is called a role cue. The more detailed the role context, the better. Having Claude preset a character...
Lesson **Claude responds best to clear and direct instructions. Think of Claude as any new employee who has just started a new job. ** Claude has no background information about what to do other than what you literally tell it. Just as when you first explain a task to a human, the more you...
Lesson This lesson needs to be executed in a code environment and is an exercise in constructing the correct message interface format, which can be skipped. The Claude for Sheets extension provides several functions that you can use to call Claude. one of these functions is CLAUDEMESSAGES(), which is constructed...
Welcome to Anthropic's Hints for Engineering Interactive Tutorial Note: This tutorial does not provide code samples to follow to interact with Claude, for the full tutorial with code samples please visit: https://github.com/anthropics/courses/blob/master/prompt_ engin...
Promoting cost-effective inference technology. We have launched OpenAI o1-mini, a cost-effective inference model. o1-mini excels in STEM, especially in math and programming, with performance nearly as good as OpenAI o1 on review benchmarks such as AIME and Codeforces...
We launched OpenAI o1, a new large language model trained through reinforcement learning to perform complex reasoning tasks. o1 is characterized by "thinking twice" - thinking long chains of internal thoughts before answering a user's question. In multiple tests, OpenAI o1 demonstrated excellent...
OpenAI introduces a new series of inference models built to solve tough problems. It will officially launch on September 12th. We've developed a new series of AI models that take extra time to think before giving an answer. They are capable of handling complex tasks, and have been developed in science, programming, and mathematical...
Retrieval-augmented generation (RAG) has become an important framework in AI, greatly improving the accuracy and relevance of large language models (LLMs) when generating responses using external knowledge sources. According to Databricks, 60% of LLMs in the enterprise should...
Original: https://ai.meta.com/blog/adapting-large-language-models-llms/ https://ai.meta.com/blog/when-to-fine-tune-llms-vs-other- techniques/ https://ai.meta.com/blog/how-to-fine-tune-llms-peft-dataset...
The introduction of ChatGPT ushered in an important moment in enabling organizations to envision new application scenarios and accelerating the adoption of AI by these companies. A typical application in the enterprise space is to enable users to talk to chatbots and get answers to their questions based on a company's internal knowledge base. However, ChatG...
It's 2024, and generative AI writing tools are no longer science fiction fantasies, but real, viable tools with many applications in the workplace that can make our jobs easier. Marketers and content creators, perhaps more than any other industry, rely on AI writing...
AKA: Chain-of-Thought Definition and Principles of Chain-of-Thought 'Chain-of-Thought' (CoT for short) is a method of thinking based on the principle of creating a chain of thoughts consisting of a series of linked thinking steps. The method helps people to be more systematic by breaking down the thinking process into a series of ordered steps...
There was a time when conversing with AI was an adventure. Now, by mastering key terms and commands, you'll easily navigate AI and make conversations lively and productive. 1. Learning terminology is the first step in mastering AI capabilities and is as important as learning the basic vocabulary of a new language, especially ChatGPT. 2...
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