EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Lobsters·Aug 30·5 min read
On Taste
TL;DR
The discussion around AI's impact on white-collar work highlights its mechanical capabilities but underscores its lack of 'taste'—a nuanced sense of aesthetics and judgment. This has led to a shift in roles, where professionals now focus more on evaluating AI-generated outputs rather than creating them.
✦ Why It Matters
Focus on developing your aesthetic judgment to enhance your role in evaluating AI-generated outputs.
Key Takeaways
- Emphasize learning fundamentals to enhance your taste.
- Explore the parallels between software and music production.
- Consider the implications of AI on your professional identity.
- Cultivate your aesthetic judgment to maintain relevance.
Full Summary
As AI technologies advance, many white-collar jobs involving mechanical tasks like programming and legal research are becoming obsolete. However, a key distinction remains: AI lacks 'taste,' which is defined as an intuitive sense of aesthetics and judgment shaped by experience.
Richard Hamming, a notable figure in digital signal processing, emphasized that taste cannot be easily taught but can be illustrated through examples. This concept has gained renewed attention with terms like 'vibe coding' emerging in tech discussions, reflecting a shift where software engineers feel their coding skills are diminishing.
The article explores whether humans will be relegated to mere judges of taste as AI continues to generate solutions rapidly, questioning the future of human creativity and decision-making in the face of advancing AI capabilities.