Actually Useful AI
Welcome! 🤖
Our community focuses on programming-oriented, hype-free discussion of Artificial Intelligence (AI) topics. We aim to curate content that truly contributes to the understanding and practical application of AI, making it, as the name suggests, "actually useful" for developers and enthusiasts alike.
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We highly value participation in our community. Whether it's asking questions, sharing insights, or sparking new discussions, your engagement helps us all grow.
What can I post? 📝
In general, anything related to AI is acceptable. However, we encourage you to strive for high-quality content.
What is not allowed? 🚫
- 🔊 Sensationalism: "How I made $1000 in 30 minutes using ChatGPT - the answer will surprise you!"
- ♻️ Recycled Content: "Ultimate ChatGPT Prompting Guide" that is the 10,000th variation on "As a (role), explain (thing) in (style)"
- 🚮 Blogspam: Anything the mods consider crypto/AI bro success porn sigma grindset blogspam
General Rules 📜
Members are expected to engage in on-topic discussions, and exhibit mature, respectful behavior. Those who fail to uphold these standards may find their posts or comments removed, with repeat offenders potentially facing a permanent ban.
While we appreciate focus, a little humor and off-topic banter, when tasteful and relevant, can also add flavor to our discussions.
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TL;DR: (AI-generated 🤖)
The author of the text argues that the field of AI engineering is emerging and will become a new subdiscipline within software engineering. They propose that an AI engineering curriculum should focus on foundational concepts, such as large language models (LLMs), embeddings, RLHF (reinforcement learning from human feedback), and prompt engineering. They also suggest exploring specific models like GPT-4, Claude, Bard, LLaMa, LangChain, and Guidance, as well as tools like LlamaIndex and Pinecone/Weaviate. The author proposes several AI engineering projects, including building a document chatbot, a ChatGPT plugin, a basic agent, a smart assistant, and fine-tuning a language model. They emphasize the importance of building on existing models rather than training new ones, and recommend using closed-source products first and open-source as necessary. The author also encourages staying nimble and agile in working with evolving AI technologies. They seek feedback on their ideas and ask whether this concept could be turned into an actual course.
Under the Hood
gpt-3.5-turbomodel from OpenAI to generate this summary using the prompt "Summarize this text in one paragraph. Include all important points."How to Use AutoTLDR