Recent submissions

Comment · 4 years ago
I’m just so grateful that they started with the actual picture. So many articles today talk about something visual and never show it.
Comment · 4 years ago
I can confirm that this works great on the M1 Max. It has been taking less than a minute to run the model and generate the images. So far I have been really satisfied with the output. Let's please make one-click installers the norm for future technology. I love nerding out, but wading through dependency hell is not worth it most of the time.
Comment · 6 years ago
Thanks, I wonder if that gives any insight to what the core issue is
Comment · 6 years ago
Comment · 6 years ago
Is there any aggregated source to see how Angel Investors and other startup financial investments are tracking? I wonder if there is going to be a financial crisis on a smaller scale for startups running out of runway.
Comment · 8 years ago
He was in software sales FYI
Comment · 8 years ago
I think one of the interesting things is the lack of reason why. There are plenty of theories and many people yelling for the end of crypto, but it seems despite of what people say or predict the crypto market has a mind of it's own. There has been speculation of market manipulation, but it seems odd for there to be a crash now.
Comment · 8 years ago
So the optical component is only the end result model of the NN? It isn't learning using the optics?
Comment · 8 years ago
Can someone help me Grok how the 3D printed Neural Networks back propagate? As I am trying to go through the paper they describe it as a pure optical approach, but what adjusts the refraction elements during the learning process?
Comment · 8 years ago
It's an interesting and fairly well written writeup. It makes me wonder at what point understanding how "blockchains work" becomes a moot point. Much like Machine Learning it seems like we are rapidly approaching where you can create your own smart contracts and "dapps" with no understanding of the inner workings of blockchains. Then the focus goes onto security and smart development.

To go back to the ML metaphor I think ML is going to have a growing field of "auditing" algorithms to look for biases towards certain races / social classes / etc. Right now for dapps the focus is on security auditing. Perhaps in this early stage we should be looking at how utilizing blockchain could marginalize people.

Comment · 8 years ago
I am curious if this will end with a "bubble-burst" or a slow burn like twitter has experienced. Surely the money has to dry up sometime? It is too bad that none of these companies create any kind of net good for society like a startup that pays you over minimum wage to clean up a park or sort recycling.
Comment · 8 years ago
Except I literally cannot read it
Comment · 8 years ago
I am sure this is controversial, but how many people have actually read these books? It's unfortunate because they are held in high regard, but the impact seems reduced for what it could be. I definitely could be wrong. I would love to at least peruse through them, but they seems to be hard to find as a full set at a decent price.
Comment · 9 years ago
Some interesting limitations here, but overall great work. The output is only 256x256, which doesn't seem useful in the short run. It would be interesting to see if there was another deep learning network that could fill in the pixels and net a higher resolution. It also looks like it uses models specifically trained for that given category (i.e. birds, flowers). I wonder how it would fair trying to visualize a distinct animal / flower that we only have a written description of.
Comment · 9 years ago
Thank you for summing the up in a way that is accurate and not overdramatic. I think the hardest thing about describing today's work environment is that it's easy to dismiss as "millennials" or "spoiled tech workers". The mental aspects are crushing in a way that is hard to describe to someone that is in a more easily understood challenging position like retail or food service.

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