Discover Prompt Engineering | Google AI Essentials
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- เผยแพร่เมื่อ 19 มิ.ย. 2024
- This video is a preview of Module 3 in Google AI Essentials, available on Coursera. In this module, you'll write effective prompts to get the output you want. You'll learn how to incorporate prompting techniques, such as few-shot prompting, into your work, and you'll understand how LLMs produce output and the importance of evaluating output before using it. By the end of this module, you will be able to write clear and specific prompts and produce outputs that help accomplish workplace tasks. You'll learn from experts at Google and get essential AI skills to boost your productivity with Google AI Essentials, zero experience required.
In this self-paced course, you’ll gain hands-on experience using generative AI tools to help develop ideas and content, make more informed decisions, and speed up daily work tasks. After you complete the course through Coursera, you’ll earn a certificate from Google to share with your network and potential employers.
Take the course HERE to access all videos, readings, and activities: goo.gle/49yq5h5
00:00 Module 3 introduction: Discover the art of prompt engineering
3:05 Understand large language models
8:13 Write clear and specific prompts
12:28 Leverage an LLM's capabilities at work
18:10 Improve AI output through iteration
24:03 Discover few-shot prompting
28:26 Wrap-up
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Discover Prompt Engineering | Google AI Essentials
• Discover Prompt Engine... - วิทยาศาสตร์และเทคโนโลยี
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Crystal clear presentation. Good job!
Thank you for your teaching ☺️
Good i description & details on how LLlM can be.. Thank You...
amazing 🎉 thanks buddy
I love his voice…❤ Thanks for your presentation!
Seems like an AI
Thank you
thanks for this type of knowledge pls update us with type of videos in future
Subscribe to our channel for updates and future videos!
This guy is a great presenter
Thank!
I am against using the word engineering in “prompt engineering”.
I understand that coding is undergoing significant changes with the introduction of LLMs such as GPT, however, in my opinion we need to be more precise in choosing words that match the actual task being done by the software developer.
Engineering design has a very precise meaning and it incorporates a lot of stages starting from setting quantitative measurable specifications, proposing multiple design alternatives, evaluating them against the specifications, iterative analysis and design usually involving mathematics and physics, selecting a design after examining trade offs among conflicting metrics, implementing the selected design, evaluating the implementation on different platforms (if feasible), module testing, integration testing, and more. Those engineering design stages constitute a cycle that can be revisited with each iteration including even the specifications stage which can be modified if necessary, but with caution and after agreement with the project stakeholders.
In that context, software engineering for example might not satisfy all the above while being considered engineering nevertheless, but with some reservation in my opinion.
However, prompt engineering barely includes a very small fraction of engineering design stages, and thus in my opinion should be given another name.
I agree I am also against data "scientists" term in data science.
I always refer to it as prompt writing instead. It's not a job for a coder, but for a skilled writer.
Engineering is meant to solve problems with technology, since prompt engineering do it, it’s ok to say engineering
"Prompt pooping"
What do you do when you don't know what the output should be? How will you use critical reasoning to evaluate the output then?
i love this this video but why are you crouching? the furniture looks small
I created a prompt for a tiny chair
I created the prompt for the table to the left.
@@untitled001tm 😂😂😂😂
@@coolfrisbee 😂😂😂
😂😂😂😂 so true
Can Gemini and ChatGPT help in writing research paper which can minimise Palagrism?
I did exactly that
my understanding of plagiarism is carbon copy of the exact combination of a collection of words from a publication made by an author. and what chatGPT capable of doing is to re-orienting the placement of the words. It directly challenges the very meaning of plagiarism as we know. it’s interesting to reflect on the fact how we define plagiarism, perhaps we have to move it’s goalpost in a post AI era 🤔 … or maybe it becomes the a concept of the past
❤
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👍
There is some glitch in the Google map can you guys fix that?
😊
0:29
Sanitation Engineer - Garbageman
Prompt Engineer - Googler
Prompting Engineering is very offensive to the what is engineering.
bro talkin about biases when gemini ai itself is extremely biased due to the woke data fed to it by its devs