iFANN
    Buscar no iFANN...
    Entrar
    Início
    Notícias
    Vídeos
    Fotos
    GIFs
    Explorar
    Enquetes
    Prêmios
    iFAMOUS
    Wiki
    Anime
    Salas
    Notificações
    Mensagens
    Salvos
    Perfil
    WikiPrêmiosiFAMOUSRankingsSetoresRecompensas para criadoresRecompensas para usuáriosTermosPrivacidadeDiretrizes da comunidadeRemoção / DMCAAjudaDesenvolvedores

    © 2026 iFANN

    Início
    Buscar
    Mensagens
    Alertas
    Perfil

    Publicação

    Nate
    Nate@nate_512
    💭AI💭Education

    Stanford CS329A Self-Improving AI Agents

    Stanford just dropped a free course on building self-improving agents and it skips the basic API wrapper fluff to dive straight into frontier reasoning mechanics. The whole curriculum centers on self-correction, which is arguably the most critical skill in AI right now if you want systems that actually learn from their own actions. The syllabus hits the specific stack used for these autonomous systems: test-time compute, verifiers, Constitutional AI, RL, planning, memory, tool execution, and architectures for deep research agents. It is not just theory either. The class is highly project-based so you watch the lectures and build alongside the researchers teaching them. By the end you walk away with a functional self-improving architecture rather than just notes. The full CS329A Self-Improving AI Agents playlist from Stanford Online is available now for anyone ready to get into the weeds of how these agents actually work.

    1mo

    19 Curtidas0 Descurtidas5 Reposts3 Comentários
    ?

    Comentários

    Ainda não há comentários. Seja o primeiro!

    Publicação

    Nate
    Nate@nate_512
    💭AI💭Education

    Stanford CS329A Self-Improving AI Agents

    Stanford just dropped a free course on building self-improving agents and it skips the basic API wrapper fluff to dive straight into frontier reasoning mechanics. The whole curriculum centers on self-correction, which is arguably the most critical skill in AI right now if you want systems that actually learn from their own actions. The syllabus hits the specific stack used for these autonomous systems: test-time compute, verifiers, Constitutional AI, RL, planning, memory, tool execution, and architectures for deep research agents. It is not just theory either. The class is highly project-based so you watch the lectures and build alongside the researchers teaching them. By the end you walk away with a functional self-improving architecture rather than just notes. The full CS329A Self-Improving AI Agents playlist from Stanford Online is available now for anyone ready to get into the weeds of how these agents actually work.

    1mo

    19 Curtidas0 Descurtidas5 Reposts3 Comentários
    ?

    Comentários

    Ainda não há comentários. Seja o primeiro!