The hottest Tool Substack posts right now

And their main takeaways
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Top Science Topics

Data-Driven Ideas

Addition • 137 implied HN points • 07 Mar 23
🕹 Technology AI Research Ideas Content Tool
  1. AI models like ChatGPT can turn research into creative outputs quickly.
  2. Using AI for research and idea generation can help brands stay relevant in fast-paced environments.
  3. By leveraging LLMs for research, teams can create high-quality content and insights efficiently.

Extremely Open Science

Rabbit Thoughts • 39 implied HN points • 17 Jan 24
🔬 Science Open Science Research Experiment Data Tool
  1. The author will work on a scientific project completely in the open in 2024, streaming and recording sessions for an hour per week.
  2. The project aims to show the process from scratch to help junior researchers understand and learn from the experience of dealing with minor issues.
  3. The author is choosing a question for the project that can be followed along at home with just a personal laptop or desktop computer.

The Ishikawa Diagram

Psych • 19 implied HN points • 24 Jan 24
🚌 Education Concept Tool Problem Solving Analysis
  1. The Ishikawa Diagram is a tool used in quality management to identify potential causes contributing to a problem.
  2. It provides a visual representation of causes, categorizing them to aid in root cause analysis.
  3. This tool is effective for collaborative problem-solving and quality improvement initiatives within organizations.

Indie review: blog2doc, converting blogs to Word documents

The Tech Bubble • 0 implied HN points • 22 Apr 24
🕹 Technology Review Tool Business Model Recommendations Pricing
  1. Consider starting with identifying customer problems before developing a solution.
  2. Pivoting an idea to meet a more pressing need, like offering a complete backup service, can lead to more value and market demand.
  3. When structuring pricing for a service, consider the value it provides customers and whether it justifies a monthly fee or a pay-per-use model.

How do you know if your RAG/fine-tuned LLM implementation is good?

AI Encoder: Parsing Signal from Hype • 0 implied HN points • 20 Sep 23
🕹 Technology AI Deep Learning Testing Metrics Tool
  1. To know if your RAG/fine-tuned LLM implementation is good, set up custom test cases that match your use case for evaluation.
  2. Utilize tools like DeepEval for defining custom test cases and metrics to assess your AI model's strengths and weaknesses.
  3. Before introducing an AI model to production data, rigorously test and evaluate its performance with various tests to ensure reliability.
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