aaggarwal

I see these articles every now and then over last 5-10 years, but as someone who has followed/worked around this industry in the past, I can tell you that there is enough demand, supply and capital for this industry and it is not going anywhere.

All of these companies are EBDITA profitable with decent margins and the net loss is them reinvesting in marketing, product and M&A (from their earnings reports). As the effects of covid wanes, their profits are going to go up very quickly which will be seen over the next year.

City and state governments can offer temporary tax breaks for building new housing in certain zones to attract capital. This is already done in a way when government is trying to attract capital for new industries via SEZs.

One problem with high tax based on capital gains at sale is that it needs the sale to happen and you start running into issues where people never sell and houses will get inherited. This still doesn’t tackle the problem head on.

Most housing discussions seems to avoid one of the main reason driving the prices up, their treatment as an investment vehicle.

Residential housing should not be used as an investment vehicle. Period. Its primary purpose is to allow families to own and live in the house. Mandating that can eliminate the rich landlords/foreign investors buying houses just for investment, stabilize the demand and drive down the prices.

One way to mandate that could be progressive property tax based on how many properties you already own with a max cap on number of allowed residential properties one can own. This might decrease incentive to build new housing for developers, but can be solved by temporary tax breaks for building new housing.

Am I missing some second order effects?

The author originally released the book here (http://codeforces.com/blog/entry/50728).

Hi James, this is pretty neat. I think this website could be a big hit among all the graduate applicants since they all are looking for creating a personal academic website at the time of applications.

Is there an option to import a latex resume to create the website? That would be handy.

I just want to thank you for ShareLatex, I use it for all my academic documents, it's pretty awesome.

Yes, I used Freeboard (https://github.com/Freeboard/freeboard) couple of years ago for an IoT store. It's highly customizable and has fantastic UI. It can be used with minimal effort. Highly recommended.

The OP's project is also pretty cool.

For the people interested in reading about different template configuration and their results, this is a great resource:

[1] http://cnn-technology.itk.ppke.hu/Template_library_v3.1.pdf

[2] http://cnn-technology.itk.ppke.hu/Template_library_v4.0alpha...

Nice catch! It is indeed closely related to cellular automata. CNN processors could be thought of as a hybrid between ANN (artificial neural networks) and CA (continuous/cellular automata) [1]. Like neural networks, they are large-scale nonlinear analog circuits that process signals in real time. Like cellular automata, they consist of a massive aggregate of regularly spaced circuit clones, called cells, which communicate with each other directly only through their nearest neighbors [2].

The topology and dynamics of CNN processors closely resembles that of CA. Like most CNN processors, CA consists of a fixed-number of identical processors that are spatially discrete and topologically uniform. The difference is that most CNN processors are continuous-valued whereas CA have discrete-values [1].

You can also read this: http://www.nims.go.jp/nanophys6/Anirban%20Bandyopadhyay/site...

[1] https://en.wikipedia.org/wiki/Cellular_neural_network#Relate...

[2] http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7600

Yes, this is one of the applications of these networks.

Actually, it's more related to the original naming term that was adopted for cellular neural networks (CNN). Convolutional neural networks were originally referred to as ConvNets (CNN term is also used for them as well).

IMHO, I don't think this naming is misleading since CNN has been originally used to refer cellular neural networks.

Please take a look at the image processing specific applications [1] and advantages of the cellular neural networks.

[1] https://en.wikipedia.org/wiki/Cellular_neural_network#Applic...

Hi, author here. Even though I was on HN, I didn't realize that this is posted over here :) I'm glad about all the feedback. Thank you.

> I'm reading up on Cellular Neural Networks and it seems like they are simple convolutions, of which you can specify the kernel.

Actually its more than that, simply put, cellular neural networks are a parallel computing paradigm similar to neural networks, with the difference that communication is allowed between neighboring units only [1].

> In fact, this library is just calling scipy.signal.convolve2d() with different kernels.

The part you're referring to performs the convolution between the kernel function and the feedback template to get the result of the feedback loop. Please note the kernel function is sigmoidal or its approximation and remains unchanged.

It will be easier to understand if you'll visualize it as a control system as shown in [2] with a feedback template and a control template. These templates (coefficients) are configurable and produce different results for different configurations.

One of the applications of these networks is image processing as stated in [3] "CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors needed for applications like particle detection in jet engine fluids and spark-plug detection.".

[1] https://en.wikipedia.org/wiki/Cellular_neural_network

[2] http://www.isiweb.ee.ethz.ch/haenggi/CNN_web/CNN_figures/blo...

[3] https://en.wikipedia.org/wiki/Cellular_neural_network#Applic...

Originally CNN was used for Cellular Neural Networks and ConvNet was used for Convolutional Neural Networks. However, lately, CNN and ConvNet are both used interchangeably for Convolutional Neural Networks.

I'm using mobile and the adding website flow is smooth and concise. I connected my blog hosted on GitHub. The only caveat is that this requires permission to access everything on your GitHub account, public and private repositories, and permission to do anything with them.

However, after adding the website repository, I'm not able to see any posts, is this only for pages? There are some UI issues with page editor on mobile that can be sorted out in beta. Nice product!

Update: I can access posts after changing the URL, but a direct link is missing in the UI.

I was using wit.ai for adding an NLP interface on an IoT product at a startup a few years ago. This was before wit.ai was acquired by Facebook.

They have an impressive product and a great team. It was very smooth to work with their api, and with reasonable accuracy.

I had been using such platforms (coursera, edX) since their inception, and they were delightfully helpful to me. They were free of cost at that time and I really appreciated that as a student.

I feel a more apt pricing strategy would be to provide free/low-cost yearly access to students and a free basic course + paid advanced courses to non-students.

As far as I remember, edX used to follow this 'pay-what-you-like' strategy for honor-code certificate, along with fixed pricing for verified certificate.

I'm positive about your idea and it's potential use in the future. Moreover, since you have already moved onto 4th prototype, this looks promising. May I suggest you to think about integration with other vendors (e.g. SolarCity) for a sustainable home or place. All the best! [Voted]

Now the MOOCs are all popular, there are a lot of interesting courses out there, but I feel the best one is still the first online course I took in 2012, the pilot from edX (MITx at that time) - 6.002x Circuits and Electronics (https://6002x.mitx.mit.edu) by Dr. Anant Agarwal and Dr. Gerald Sussman.

It's an awesome course that introduces one to the electronics that goes behind modern day computers and smartphones. It really helped me understand how things work and what questions to ask.