Meta's Chief AI Scientist Yann LeCun recently challenged a prevailing assumption in the AI field: the path to achieving human-level artificial intelligence won't come through text-based approaches alone. His stance questions whether current language model trajectories can actually bridge the gap to genuine AGI. It's a thought-provoking take from someone at the forefront of AI research, suggesting the industry may need fundamentally different architectures or methodologies beyond what we're seeing in today's LLM boom.

This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.
  • Reward
  • 4
  • Repost
  • Share
Comment
0/400
GasBankruptervip
· 3h ago
The pure text route can't produce AGI, this guy's point is spot on.
View OriginalReply0
GmGnSleepervip
· 3h ago
Yann LeCun's point is spot on. The pure text approach has long been outdated, and the ceiling for LLMs is becoming more and more apparent. Multimodal is the way to go, right?
View OriginalReply0
ForkThisDAOvip
· 3h ago
LeCun's words should have been said long ago; the pure text approach indeed has its ceiling right there.
View OriginalReply0
LiquidityWitchvip
· 3h ago
Yann LeCun is once again going against the trend, but the reasoning is sound... a pure text-based approach might indeed be a dead end.
View OriginalReply0
Trade Crypto Anywhere Anytime
qrCode
Scan to download Gate App
Community
English
  • 简体中文
  • English
  • Tiếng Việt
  • 繁體中文
  • Español
  • Русский
  • Français (Afrique)
  • Português (Portugal)
  • Bahasa Indonesia
  • 日本語
  • بالعربية
  • Українська
  • Português (Brasil)