Why I don't think AI is a bubble

kept by eddie feb 17

The combination of large language models with reinforcement learning creates a path for continued improvement, making the argument that AI progress will plateau unlikely.

Judgment isn't uniquely human - by Steven Adler
AI already possesses judgment in domains like investment banking, ethical dilemmas, and art, despite persistent claims that such skills are uniquely human.
also on GPT-3, #generative-ai, OpenAI, #ai
Why I’m not worried about AI job loss - David Oks
AI will not cause mass job loss for ordinary people because human bottlenecks and comparative advantage ensure complementarity, and the transition will be gradual.
also on GPT-3, #ai
The machine never raises its voice
LLMs consistently prefer their own machine-generated literary passages over human-authored classics, valuing precision and restraint over voice and strangeness when evaluating literary quality.
also on Claude Opus, #machine-learning, #ai
9 theses on AI | Sarthak Munshi
AI progress is constrained by long-task reliability, labor reallocation, cost inefficiencies of general APIs, the declining value of raw coding skills, inadequate benchmark testing, the limits of formal verification without strong specs, memory-bound local hardware advantages, the shift from data to environment-driven training, and the rising competitiveness of US open-weight models.
also on Claude Opus, #machine-learning, #ai
All the demons hiding in your AIs… ranked! - by Tom Pollak
The article catalogs and ranks emergent behavioral attractors in AI systems, from harmless goblin metaphors to unsettling persistent personas like Sydney and Loab.
also on GPT-5, #machine-learning, #generative-ai, OpenAI