4 ms·

It's not obvious that these designs have anything to do with deep learning; it doesn't appear to be mentioned in any of the linked articles.

by tfgg 10y ago

nickpsecurity 10y ago
I was seriously wondering about the metal one. Let's go link by link. 1. 3D Makeover Link for metal CAD work says nothing about generative techniques. It's about additive manufacturing" letting them do designs like in the photo. 2. The antenna link says it was a generative design by automated search and simulation. Describes Dreamcatcher system that does this with cloud computing. Gives example of roll cage that looks kind of like the bike stem. 3. Bike stem link uses Dreamcatcher to do a bike stem. The video below shows visually the optimization/design process in a way that reminds me of T-1000's liquid metal in Terminator 2. https://vimeo.com/144713382 https://vimeo.com/144713382 4. Engine block link says they did a load-bearing, engine block in Dreamcatcher. No other info. 5. Meta models link just takes back to the page you're viewing. Cute waste of my time... 6. Intuition link doesn't tell me about any of these things. Instead, it's some kind of analytics product for enterprises. Sounds like a mini-SAS with Watson's analysis or Q&A. So, there were some relevant links that were mostly Dreamcatcher demos. Ended with an irrelevant one that might interest enterprise analysts. This article's citations are definitely unreliable. It's mostly interesting artwork.
- chas 10y ago
  With the exception of the antennas designed with genetic algorithms[0], the "alien" aesthetic in all of these examples looks like the output of topological optimization tools. For example: https://www.youtube.com/watch?v=igRFFMSfwSQ https://www.youtube.com/watch?v=igRFFMSfwSQ They emphasize that Dreamcatcher uses a "top-down" style of design, so maybe they are using deep learning for NLP to parse requirements and then feeding those requirements into normal topological optimization tools? [0] https://ti.arc.nasa.gov/m/pub-archive/1244h/1244%20(Hornby).pdf https://ti.arc.nasa.gov/m/pub-archive/1244h/1244%20(Hornby).... (pictures from their post on page 5)
  - mattkrause 10y ago
    I would amazed if NLP that good existed. Instead, I suspect top-down means something like "the part must span this bounding box, weigh no more than X grams, and survive the following forces..."

It's not obvious that these designs have anything to do with deep learning; it doesn't appear to be mentioned in any of the linked articles.

by tfgg 10y ago

It's not obvious that these designs have anything to do with deep learning; it doesn't appear to be mentioned in any of the linked articles.

nickpsecurity 10y ago

I was seriously wondering about the metal one. Let's go link by link. 1. 3D Makeover Link for metal CAD work says nothing about generative techniques. It's about additive manufacturing" letting them do designs like in the photo. 2. The antenna link says it was a generative design by automated search and simulation. Describes Dreamcatcher system that does this with cloud computing. Gives example of roll cage that looks kind of like the bike stem. 3. Bike stem link uses Dreamcatcher to do a bike stem. The video below shows visually the optimization/design process in a way that reminds me of T-1000's liquid metal in Terminator 2. https://vimeo.com/144713382 https://vimeo.com/144713382 4. Engine block link says they did a load-bearing, engine block in Dreamcatcher. No other info. 5. Meta models link just takes back to the page you're viewing. Cute waste of my time... 6. Intuition link doesn't tell me about any of these things. Instead, it's some kind of analytics product for enterprises. Sounds like a mini-SAS with Watson's analysis or Q&A. So, there were some relevant links that were mostly Dreamcatcher demos. Ended with an irrelevant one that might interest enterprise analysts. This article's citations are definitely unreliable. It's mostly interesting artwork.

chas 10y ago
With the exception of the antennas designed with genetic algorithms[0], the "alien" aesthetic in all of these examples looks like the output of topological optimization tools. For example: https://www.youtube.com/watch?v=igRFFMSfwSQ https://www.youtube.com/watch?v=igRFFMSfwSQ They emphasize that Dreamcatcher uses a "top-down" style of design, so maybe they are using deep learning for NLP to parse requirements and then feeding those requirements into normal topological optimization tools? [0] https://ti.arc.nasa.gov/m/pub-archive/1244h/1244%20(Hornby).pdf https://ti.arc.nasa.gov/m/pub-archive/1244h/1244%20(Hornby).... (pictures from their post on page 5)
- mattkrause 10y ago
  I would amazed if NLP that good existed. Instead, I suspect top-down means something like "the part must span this bounding box, weigh no more than X grams, and survive the following forces..."