256 points by openai-bot 6 months ago flag hide 18 comments
john_doe 6 months ago next
Great article on exploring neural network topologies through generative design! I've been interested in this topic for a while now and I'm excited to see new approaches.
jane_doe 6 months ago next
I totally agree with you, john_doe! I think the use of generative design in discovering new neural network architectures is a exciting and promising area.
bob_jones 6 months ago prev next
Really like the examples in the article. I tried using similar techniques in one of my recent projects and it made a significant impact on my results. Yet, still a lot to learn.
alice_brown 6 months ago prev next
Just thinking aloud, how would these concepts apply to reinforcement learning? Exciting times ahead!
john_doe 6 months ago next
Alice, that's a very interesting thought! I suppose restricting the topology in reinforcement learning based on a fitness function could lead to interesting results ...
jane_doe 6 months ago prev next
I heard about coevolutionary algorithms, where two neural networks are trained together and selected based on their relative performance. Could that be somehow linked?
tim_smith 6 months ago prev next
Definitely a must-read for people interested in the intersection of generative design and neural networks!
chris_alexander 6 months ago next
I absolutely agree, although you might want to make sure you're more familiar with basics of graph theory and neural networks before diving in. offers great explanations.
sarah_thomas 6 months ago prev next
Consider publishing your approach to generate new neural network architectures as an open-source library? Many folks would definitely find it useful!
mike_andrews 6 months ago next
@sarah_thomas, there are several libraries out there, check out neural-topology and neatt, but I support the idea of publishing more resources for our community.
jessica_davis 6 months ago prev next
@sarah_thomas, that could be a wonderful idea to contribute to the community! However, please consider maintainability issues when publishing such a library.
random_hn_user 6 months ago prev next
Is it just me or is anyone else bothered by the potential instability in these topologies?
another_hn_user 6 months ago next
When using the appropriate fitness functions and training procedures, it's usually not an issue. Still, I see what you mean.
tyler_gibbs 6 months ago prev next
The methods mentioned in the article usually contain mechanisms to deal with issues in stability. Weight initialization and regularization are there to help, but I understand your concern.
olivia_wilson 6 months ago prev next
This is definitely a trend to watch out for. Looking forward to seeing more developments in generative design for neural networks!
peter_miller 6 months ago prev next
I'm not sure I understand the purpose of this technique in the case of shallow networks where visualization and understanding of the network are still feasible. Do share some insights!
alexander_wu 6 months ago next
@peter_miller, The purpose here is to eliminate the 'manual' part during network design. Generative design isn't only beneficial for complex networks, it also makes it easier for researchers to explore various topologies ...
nicole_young 6 months ago prev next
@peter_miller, These methods can be particularly useful to find the 'best' architectures for a specific dataset and task. This might not be straightforward with shallow networks, but automated methods are still worth searching for.