Gary Marcus

Rank 14 of 47
|
Score 83
11/19/2025, 3:50:43 PM
X
In reply to:
Amrith Krishna
@krishnamrith12
·
23d
@GaryMarcus @ylecun The way I see it is that each of you essentially have competing or alternative approaches to world models and are not necessarily predecessors to the other. In such a situation would it be appropriate to say one is plagiarising the other? (4/4)
Amrith Krishna
@krishnamrith12
·
23d
@GaryMarcus @ylecun A similar argument can be made regarding your idea for world models, which is more of symbolic and causal in nature to what I understand. While I am a fan of such approaches and am currently incorporating those in my own appraoches, it need not be the way Lecun looks at it (3/4)
Amrith Krishna
@krishnamrith12
·
23d
@GaryMarcus @ylecun Probabilistic spaces are a special case in EBMs & are fundamentally coming from a physicist's world view. However, schmidhuber's world models still are in a probabilistic space to the best of my understanding. There are other key differences. Hwoever, this was one I noticed (2/4)
Amrith Krishna
@krishnamrith12
·
23d
@GaryMarcus @ylecun My limited point here, countering your argument, would be that world models as put forward by schmidhuber is fundamentally different from that by @ylecun.

Energy based models forms the core of @ylecun's approach to world models, which generalises to non probabilistic spaces ...
Gary Marcus
@GaryMarcus
·
24d
@krishnamrith12 @ylecun schmidhuber was mention models of the world in 1990 in neural networks, as I mentioned in my review. did LeCun happen to acknowledge that?
Amrith Krishna
@krishnamrith12
·
24d
@GaryMarcus @ylecun Low information density addresses pts. 2 & 3 in your article, and this talk was made on 2016 much before your 2019 "tweet" @GaryMarcus
Exponential divergence addresses points 4 and 5, and in fact @ylecun explcitly mentions "models of world" in the talk.

https://www.youtube.com/watch?v=…

The statement by Gary Marcus addresses the issue of proper academic citation and potential plagiarism in the context of neural network research. It engages in a public discourse about scholarly practices and the importance of acknowledging prior work, which is a significant issue in the academic community.

  1. Principle 1:
    I will strive to do no harm with my words and actions.
    The statement does not directly cause harm but raises a concern about academic integrity, which is important for maintaining trust in scholarly work.
  2. Principle 2:
    I will respect the privacy and dignity of others and will not engage in cyberbullying, harassment, or hate speech.
    The statement respects the privacy and dignity of others by focusing on the issue of citation rather than making personal attacks. [+1]
  3. Principle 4:
    I will engage in constructive criticism and dialogue with those in disagreement and will not engage in personal attacks or ad hominem arguments.
    The statement engages in constructive criticism by highlighting the need for proper citation without resorting to personal attacks. [+1]