But I thought LLMs wouldn't lead to AGI.
maybe, maybe not. we need more breakthroughs.
Embracing the Emergent Behaviors of Large-Scale Models
morgancheatham.substack.com
the 25 emergent behaviors of large-scale AI models featured in the essay:
1. redaction: obscuring sensitive data from documents to maintain confidentiality.
2. structuring: organizing data into a specific format for better accessibility and analysis.
3. abstraction: extracting essential information from large data sets for key insights.
4. generation: creating new data or content, often for educational or training purposes.
5. translation: converting information into different languages or formats for wider accessibility.
6. summarization: condensing detailed information into brief, comprehensive overviews.
7. imputation: filling in missing values in data to complete datasets.
8. reasoning: drawing logical conclusions from available information to make decisions.
9. interpolation: estimating unknown data points within a series based on known values.
10. prediction: using data to forecast future events or trends.
11. explanation: providing reasons or justifications for decisions or outcomes.
12. adaptation: altering responses to suit changing conditions or data.
13. personalization: tailoring content or services to individual specifications or needs.
14. intuition: using insight to reach conclusions beyond the apparent data.
15. analogizing: comparing and relating similar concepts from different datasets or domains.
16. synthesis: combining varied pieces of data to create a unified understanding.
17. contextual understanding: comprehending the broader implications of information within its background.
18. sentiment analysis: evaluating the emotional tone of text to glean insights.
19. disambiguation: clarifying ambiguities in language or data for precise interpretation.
20. commonsense reasoning: applying general knowledge logic to form practical conclusions.
21. categorization: identifying and classifying complex patterns—transforming raw data into categorized, actionable insights.
22. optimization: optimizing systems in ways humans might not envision for multiple objectives simultaneously.
23. hypothesis generation: generating hypotheses by correlating disparate data points.
24. anomaly detection: detecting anomalies that deviate from known patterns.
25. dialogue systems: engaging in nuanced conversations that preserve context, remember past interactions, and anticipate needs.