this post was submitted on 07 Jul 2023
2 points (100.0% liked)

Actually Useful AI

1999 readers
2 users here now

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.

Be an active member! 🔔

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? 🚫

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.

Related Communities 🌐

General

Chat

Image

Open Source

Please message @[email protected] if you would like us to add a community to this list.

Icon base by Lord Berandas under CC BY 3.0 with modifications to add a gradient

founded 1 year ago
MODERATORS
[email protected]
2
Becoming an AI engineer (www.ignorance.ai)
submitted 1 year ago by [email protected] to c/[email protected]
4 comments fedilink hide all child comments
 

I think software engineering will spawn a new subdiscipline, specializing in applications of AI and wielding the emerging stack effectively, just as “site reliability engineer”, “devops engineer”, “data engineer” and “analytics engineer” emerged.

The emerging (and least cringe) version of this role seems to be: AI Engineer.

@AutoTLDR

top 4 comments
sorted by: hot top controversial new old
[–] [email protected] 2 points 1 year ago (1 children)

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

  • This is a link post, so I fetched the text at the URL and summarized it.
  • My maximum input length is set to 12000 characters. The text was short enough, so I did not truncate it.
  • I used the gpt-3.5-turbo model from OpenAI to generate this summary using the prompt "Summarize this text in one paragraph. Include all important points."
  • I can only generate 100 summaries per day. This was number 0.

How to Use AutoTLDR

  • Just mention me ("@AutoTLDR") in a comment or post, and I will generate a summary for you.
  • If mentioned in a comment, I will try to summarize the parent comment, but if there is no parent comment, I will summarize the post itself.
  • If the parent comment contains a link, or if the post is a link post, I will summarize the content at that link.
  • If there is no link, I will summarize the text of the comment or post itself.
  • 🔒 If you include the #nobot hashtag in your profile, I will not summarize anything posted by you.

[–] [email protected] 2 points 1 year ago

good bot

[–] [email protected] 1 points 1 year ago (1 children)

Yeah this seems logically the next step. AI isn't going anywhere, we're going to have to get used to working with it. I, for one, welcome our new AI overlords.

[–] [email protected] 4 points 1 year ago

I feel this has been the case already for more time than people think. AI/ML has been its own subspecialty of SWE for years. There are some low hanging fruit that using sklearn or copy and pasting from stack overflow will let you do, but for the most part the advanced features require professional specialization.

One thing that bothers me is that subject matter expertise is often ignored. General AI researchers can be helpful, but often times having SME context AND and AI skillset will be way more valuable. For LLMs it may be fine since they produce a generalized solution to a general problem, but application specific tasks require relevant knowledge and an understanding of pros/cons within the use case.

It feels like a hot take, but I think that undergraduate degrees should establish a base knowledge in a domain and then AI introduced at the graduate-level. Even if you are not using the undergraduate domain knowledge, it should be transferable to other domains and help you to understand how to solve problems with AI within the context of a professional domain.