ClaimsYann LeCun

“Designing those guardrails so that the system behave properly is not going to be a simple issue for which there is a silver bullet for which you have a mathematical proof that the system can be safe.”

Yann LeCun, interviewee 8 March 2024 Transcript for Yann Lecun: Meta AI, Open Source, Limits of LLMs, AGI & the Future of AI (Lex Fridman Podcast)

This quote could not be matched word for word to the source page.

Prediction AI safety and alignment

Designing AI guardrails will not be solved by a single silver bullet or a mathematical proof of safety.

Unresolvable The public record could not settle it.

Prediction: Statements about events outside the person's control, checked once they fell due: did they come true?

Reasoning

Open-ended prediction about safety methods with no horizon.

Cite this claim

Yann LeCun, “Designing AI guardrails will not be solved by a single silver bullet or a mathematical proof of safety.” (said 8 March 2024). Verdict: unresolvable. Reliability API, claim c_56be8b1ccce9, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_56be8b1ccce9

This claim is in dataset release v1.1.2, with the same verdict.

Reply to this claim

For Yann LeCun, or someone speaking for them: a correction or counter-evidence. Replies are read before anything is shown; an approved reply shows your name, role, date, statement and link. Your email address is never shown and is deleted 30 days after the decision (privacy).

More prediction claims by Yann LeCun

  1. Mostly true Prediction 8 March 2024
    “Increasingly, the search engines that we’re going to use are not going to be search engines, they’re going to be dialogue systems”

    Search engines will increasingly be replaced by dialogue systems that answer questions and perhaps point to appropriate references.

  2. Mostly true Prediction 2019
    “We foresee an increase in the usage of such networks for a wide variety of applications, which are likely to violate the assumptions of current DL hardware.”

    Usage of graph neural networks will increase for a wide variety of applications likely to violate the assumptions of current deep learning hardware.

  3. Mostly true Prediction 2019
    “As DL systems are increasingly used for high-level cognitive tasks, such memory modules will become commonplace and very large, requiring hardware support.”

    As DL is used for high-level cognitive tasks, memory modules will become commonplace and very large, requiring hardware support.

  4. Mostly true Prediction 18 February 2015
    “The next frontier for Deep Learning is natural language understanding.”

    Natural language understanding will be the next frontier for Deep Learning.

  5. Mostly true Prediction 2010
    “one of the major challenges of computer vision, machine learning, and AI in general in the next decade will be to devise methods that can automatically learn good features hierarchies from unlabeled…”

    In the next decade, a major challenge of computer vision, machine learning and AI will be devising methods that learn good feature hierarchies from unlabeled and labeled data in an integrated fashion.

All of them

Verdicts are made automatically; how verdicts are made.