Actually Useful AI
Welcome! ๐ค
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! ๐
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? ๐
In general, anything related to AI is acceptable. However, we encourage you to strive for high-quality content.
What is not allowed? ๐ซ
- ๐ Sensationalism: "How I made $1000 in 30 minutes using ChatGPT - the answer will surprise you!"
- โป๏ธ Recycled Content: "Ultimate ChatGPT Prompting Guide" that is the 10,000th variation on "As a (role), explain (thing) in (style)"
- ๐ฎ Blogspam: Anything the mods consider crypto/AI bro success porn sigma grindset blogspam
General Rules ๐
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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This long, image-heavy article will pose a challenge to @AutoTLDR. Letโs see how it fares.
TL;DR: (AI-generated ๐ค)
This text discusses the concept of magical systems, which are black box systems that provide indeterministic results. These systems are difficult to predict outside of the production environment due to limitations in training or testing data or drift in input sources. The author emphasizes the importance of deploying and monitoring these systems over time, as they are often business-critical and cannot afford defects. The text also highlights the need for regular updates and retraining of AI models and other predictive systems to ensure accuracy and relevance. Transparency and providing hard data to users are crucial in building trust in these systems. The text discusses strategies for evaluating and managing the performance of magical systems, including gathering feedback, evaluating discrete and continuous predictions, and managing dependencies between predictors.
NOTE: This summary may not be accurate. The text was longer than my maximum input length, so I had to truncate it.
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