What They Told You About Prompt Engineering is WRONG!
TLDRThe video debunks the myth that prompt engineering is merely about crafting effective prompts for AI like Chat GPT, and that it's a lucrative career. It explains that while prompt engineering can enhance productivity, it's not a high-paying job as portrayed. The speaker, from atck Technologies, reveals that prompt engineers either assist companies using AI models or work in AI development. They must understand linguistics, have strong communication skills, domain knowledge, and programming abilities. The video concludes that as of April 2024, the job market for prompt engineers is limited, advising viewers to be cautious of misleading courses promising high earnings.
Takeaways
- 😀 Prompt engineering is often misunderstood as simply writing effective prompts for AI, similar to writing effective queries for Google.
- 🤔 The speaker argues that the idea of being paid hundreds of dollars for prompt engineering is a myth, based on their own company's experience.
- 🔍 The formal definition of prompt engineering is to write prompts that guide an AI to produce a desired output.
- 💼 Prompt engineering can be done as a user for personal productivity or as a professional role within companies that use or develop AI models.
- 🏥 In professional settings, prompt engineers work with companies on tasks like healthcare data extraction, where they guide AI models to produce specific outputs.
- 🛠️ Prompt engineers may need to provide detailed examples and context to guide AI models, requiring a deep understanding of the domain and strong communication skills.
- 📈 They also play a role in testing new AI models, writing test cases, and evaluating the model's responses using metrics like cosine similarity.
- 💻 Skills required for a prompt engineer include linguistic understanding, domain expertise, programming skills, and knowledge of AI evaluation metrics.
- 📉 As of April 2024, the demand for prompt engineers is low, with only a limited number of jobs available in India, according to the speaker's research.
- ⚠️ The speaker advises caution against enrolling in courses that promise high earnings from prompt engineering, urging individuals to conduct thorough research.
Q & A
What is the main argument against prompt engineering being a lucrative career as presented in the video?
-The main argument is that prompt engineering, as portrayed by many online videos, is oversold as a high-paying career. The speaker argues that in reality, prompt engineering is not a specialized job that commands high salaries, and in his own company, there is no need to hire dedicated prompt engineers.
What is the formal definition of prompt engineering given in the video?
-The formal definition of prompt engineering is writing prompts in such a way that you can guide a large language model (LLM) to produce a desired output.
How does the video differentiate between using prompt engineering as a casual user and as a professional?
-As a casual user, prompt engineering involves writing effective prompts for personal use in tools like ChatGPT, for which there is no monetary compensation. As a professional, it involves a career role where one might get paid for creating prompts that guide LLMs in specific applications, such as data extraction or testing new LLMs.
What are the two types of companies where prompt engineers might be employed according to the video?
-Prompt engineers might be employed by companies that use LLMs for specific applications, like Walmart or Reliance, and by companies that build or customize LLMs, such as OpenAI or Google.
What is the role of a prompt engineer in a healthcare data extraction company as described in the video?
-In a healthcare data extraction company, a prompt engineer would write prompts that guide the LLM to extract meaningful information from healthcare documents in a format that can be easily consumed by downstream processing systems.
What is 'few-shot learning' as it relates to prompt engineering?
-Few-shot learning in the context of prompt engineering refers to providing detailed examples that guide the large language model to understand the task and produce the desired output more effectively.
What skills are required for a prompt engineer according to the video?
-The skills required for a prompt engineer include understanding of linguistics, psychology, strong communication and problem-solving skills, domain understanding, programming skills, knowledge of LLM evaluation metrics, and some statistical skills.
Why does the speaker advise caution when considering prompt engineering courses that promise high earnings?
-The speaker advises caution because, as of April 2024, the demand for prompt engineers is not high, and he has not found it necessary to hire prompt engineers in his own company. He suggests that the job role may evolve or change in the future, and recommends doing thorough research before investing in such courses.
How does the video suggest using effective prompts with ChatGPT in day-to-day tasks?
-The video suggests using effective prompts with ChatGPT to boost productivity in day-to-day tasks by providing explicit instructions and context to get more customized and useful responses.
What is the importance of cosine similarity in the context of testing LLMs as mentioned in the video?
-Cosine similarity is important for testing LLMs because it allows for the comparison of the semantic meaning of the expected and actual outputs, ensuring that the LLM's responses are meaningful and relevant, even if they are not word-for-word matches.
Outlines
🤖 The Truth About Prompt Engineering
The speaker begins by debunking the myth that prompt engineering is a lucrative job that involves simply writing effective prompts for AI like ChatGPT. They argue that the concept of being paid hundreds of dollars for such a task is false. The speaker shares their own experience from their company, ATCK Technologies, where they have never felt the need to hire a prompt engineer. They then delve into what prompt engineering truly entails, which is guiding a large language model (LLM) to produce a desired output through effective prompts. The speaker differentiates between using prompts for personal productivity and the professional role of a prompt engineer, which may involve more complex tasks such as customizing outputs for specific formats or contexts. They also touch on the idea of 'few-shot learning,' where detailed examples guide the LLM, and the importance of domain understanding, communication skills, and English proficiency for a prompt engineer.
🔍 The Role of Prompt Engineering in AI Development
The second paragraph delves into the specific roles and requirements of a prompt engineer within two types of companies: those that utilize LLMs like Walmart and Reliance, and those that build or customize LLMs like OpenAI and Google. For companies using LLMs, prompt engineers may work on automating data extraction processes, where they need to write prompts that guide the LLM to produce outputs in specific formats, such as JSON, for downstream processing. For companies developing LLMs, prompt engineers are involved in testing new models, writing comprehensive and adversarial test cases, and evaluating the model's responses, often using metrics like cosine similarity to measure the semantic similarity between expected and actual outputs. The speaker outlines the skills required for a prompt engineer, including linguistic understanding, psychology, communication, problem-solving, domain expertise, programming skills, and knowledge of LLM evaluation metrics and statistics. They conclude by discussing the current job market for prompt engineers, noting the limited demand as of April 2024, and caution against enrolling in courses that overpromise financial rewards without proper research.
Mindmap
Keywords
💡Prompt Engineering
💡ChatGPT
💡Persona
💡Task
💡Context
💡LLM (Large Language Model)
💡Few-shot Learning
💡Domain Understanding
💡API (Application Programming Interface)
💡Cosine Similarity
💡Prompt Evaluation
Highlights
Prompt engineering is often misrepresented as simply writing effective prompts for AI, akin to writing good Google queries.
The speaker claims that many online sources are misleading about the value and necessity of prompt engineering.
At the speaker's company, Atck Technologies, they have never felt the need to hire a prompt engineer for their AI projects.
The formal definition of prompt engineering is to write prompts that guide an LLM to produce a desired output.
Prompt engineering can be done as a user to improve productivity or as a professional role that may earn a salary.
Using effective prompts with AI like ChatGPT can boost daily productivity but is not considered engineering work.
Prompt engineers work in companies that use LLMs for tasks like data extraction or in companies building custom LLMs.
In data extraction, prompt engineers might write prompts to guide an LLM to produce output in a specific format like JSON.
Few-shot learning is a technique where detailed examples guide the LLM, requiring domain understanding and good English writing skills.
Large companies may hire dedicated prompt engineers to handle extensive prompt engineering tasks separately from AI engineering.
Prompt engineers in companies building LLMs are involved in testing the model through comprehensive and adversarial testing.
Cosine similarity is used to measure the semantic similarity between expected and actual LLM outputs.
Prompt engineers need skills in linguistics, psychology, communication, problem-solving, domain expertise, programming, and statistical analysis.
As of April 2024, the demand for prompt engineer jobs in India is low, with only 20 jobs found on LinkedIn.
The speaker advises caution against enrolling in courses promising high earnings from prompt engineering, urging research before making decisions.
The speaker concludes by encouraging viewers to do their research and be critical of misleading information about prompt engineering.