• Home
  • Technology
  • Gaming
  • Entertainment
  • World & Business
  • Science
  • Sports
  • AI
HomeTechnologyGamingEntertainmentWorld & BusinessScienceSportsAI
  • HomeTechnologyGamingEntertainmentWorld & BusinessScienceSportsAI
    • Home
    • Technology
    • Gaming
    • Entertainment
    • World & Business
    • Science
    • Sports
    • AI
    AI

    Ryan Greenblatt on AI Acceleration of Software R&D

    Redwood Research scientist defines broad software R&D and predicts progress acceleration.

    RG
    2 Sources, 24d ago, first seen 24d ago

    TLDR

    Ryan Greenblatt, Chief Scientist at Redwood Research focused on AI safety, posted that downstream of AI, strong acceleration is likely in publicly salient software R&D tasks easy to hill climb on, with clear metrics and short feedback loops. He described software R&D broadly to include all R&D doable purely in software, such as math and various solvers or optimization problems. Greenblatt indicated this development merits tracking.

    Combined views

    15.3K

    2 Sources, first seen 24d ago

    Combined views

    15.3K

    2 Sources, first seen 24d ago

    164 likes
    164 likes
    10 comments
    44 saves
    11 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    10 comments
    44 saves
    11 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    Today's Rank

    —

    Not ranked yet

    Today's Rank

    —

    Not ranked yet

    2 Sources

    @RyanGreenblattIt seems likely that downstream of AI we'll soon see a strong acceleration in progress on publicly salient software R&D tasks that are easy to hill climb on (e.g., clear metric, short feedback loops). This is worth tracking.

    2 Sources

    @RyanGreenblattIt seems likely that downstream of AI we'll soon see a strong acceleration in progress on publicly salient software R&D tasks that are easy to hill climb on (e.g., clear metric, short feedback loops). This is worth tracking.