EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Aug 4·5 min read
Dataset: Dead mental health startups, 2000-2026, coded on 18 fields
TL;DR
A dataset cataloging 542 defunct mental health startups from 2000 to 2026 has been released, providing insights into their failures. It includes detailed classifications and reasoning behind each company's demise.
✦ Why It Matters
Analyze the dataset to identify common failure patterns in mental health startups and inform your next project.
Key Takeaways
- Examine who pays for services to predict startup survival.
- Utilize the dataset to explore reasons behind company failures.
- Consider the implications of funding sources on business models.
- Review the classification rationale to validate LLM-assisted labels.
How It Works
The dataset employs LLMs to classify companies based on their descriptions, assigning labels across four axes: product type, entity type, care mode, and clinician involvement. This automated classification is supplemented by a rationale document that allows users to verify the accuracy of the labels.