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Meta's Joe Spisak explains how AI models can train themselves by generating images, asking itself questions about them, and choosing the best answers, in order to move beyond human data and human fine-tuning, and teach itself from synthetic data

Tsarathustra

83,522 subscribers

42,390 просмотров • 1 год назад •via X (Twitter)

Наука и технологии

Anya Rossi• Live Now

Private livecam show

Комментарии: 10

Фото профиля Tsarathustra

Tsarathustra1 год назад

Source (thanks to @curiousgangsta):

Фото профиля Bunagaya

Bunagaya1 год назад

doesn't feel like that much time left before recursive self improvement

Фото профиля Rob Leclerc

Rob Leclerc1 год назад

We do this as well, but we don’t get far without testing our hypotheses against reality. AI can’t side step this epistemological constraint no more than we can.

Фото профиля Narasimha R N 🤗 AI - Disciple @69

Narasimha R N 🤗 AI - Disciple @691 год назад

AI self-training is revolutionary. Synthetic data bypasses human limits, speeding progress. However, guardrails are crucial to ensure ethical outcomes and prevent unintended consequences.

Фото профиля Chandan Ganwani

Chandan Ganwani1 год назад

Hallucinations squared and compounded exponentially. This is brilliant!

Фото профиля Rob Parker

Rob Parker1 год назад

Human limitations

Фото профиля 𝕏one - exo/acc 🧙🏽‍♂️🎨

𝕏one - exo/acc 🧙🏽‍♂️🎨1 год назад

Self play is the correct way forward.

Фото профиля Shawn

Shawn1 год назад

Sounds like Meta is closing up OAIs moat

Фото профиля Tsarathustra

Tsarathustra1 год назад

have you tried Meta AI's voice model? It's pretty good. I think it's only a 1B/3B model based on Llama 3.2

Фото профиля Timi Okoya

Timi Okoya1 год назад

This allows AI to explore beyond the limitations of human-labeled data, increasing its ability to learn, adapt, & improve autonomously. It opens up possibilities for faster, more scalable training, enabling AI systems to tackle complex tasks with minimal human intervention.

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