kaveh_h

Nice! could be useful base for a tool to make code more DRY or higher quality.

One way would be an IDE extension that suggests a reference implementation of an algortihm if it finds code in your code base resembling it with high prediction score. Or if it sees code duplication it will suggest a refactoring to factorize the common function.

Gene technology has potential to develop truly targeted weapons. What's worse is that it could spread through anyone but only attacking it's intended target(s).

What is China doing to Africa? And how is that any different than what US does to any other region in the world. Even though America is a democracy it has not really promoted democracy overseas. Apart from earlier itself being involved in wars now instead many bad foreign leaders are supported by US politicians and leaders. Allies which have been behaving badly for long time.

US greatest talent is (perhaps was) it’s ability to attract the talent of the world and creating great value out of it. This happened primarily during and after the world wars was as many nations were becoming more hostile places and American open culture and values became a refuge for many. US will only truly lose it’s leadership position when it gives up on moral leadership.

It’s not merely military organizations. The US president and congress use military force on any target in the world even when there’s no or very little benifit for security of US citizens, even under influence of lobbyists. Think of Vietnam or Iraq 2003, and others.

Interesting, so how does the winch system work is it actually pulled and released from each pole base? Are they going to be modularized so they can pass tools along multiple such systems? Have you thought about harvesting and collecting?

Robots with legs are probably not an option, they are both costly in production and energy usage. Something more akin to https://farm.bot but on a larger scale would probably work better. Maybe a hybrid solution like a CNC bot built on top a frame with wheels that could simply drive around a field and work on different quadrants would be a way forward.

There’s an important distinction here. This is an efficiency which decrease power consumption of idle an itself useless ”activity” which is a side effect everybody is trying to avoid, compare that to coal burners that really care about generating energy cheap.

Yes, borders aren’t what they used to be.

There’s not really a problem of Vitamin D deficiancy for women in Iran, and that is much more likely if they would move to and live in northern countries that get little sunlight during long winters.

Spreadsheets are pretty good for using when exploring the execution of an algorithm or computation graph. You can basically book keep every step of an execution.

Efficiencies or lack of it is visible in the spreadsheet in a very concrete way. How many used cells are there, how many “steps” or rows is required to finish a computation and how many times are cells addressed clearly relates to time and space complexity of an algorithm.

This doesn’t hurt ticket buyers as much as it hurts artists and producers. It’s they who get payed less from Ticketmaster, the consumer would have to pay market value anyway.

What they should really do to get market value ethically is simple, have an auction for the tickets. The going price would be transparent to buyers, artists/producers and Ticketmaster wouldn’t have the ability to doubly collect fees without paying the artists/producers their real cut in the end. Of course you could argue Ticketmaster would have the ability to benefits from resellers anyway, but in reality the price difference the second time would not be big enough to be benificial for scalpers and Ticketmaster.

If the band/artist want to give more to dedicated fans, just set a side a set of tickets for their fan club and let them buy for a flat fee or from a private auction.

Actually the LSTM model doesn't asume anything about ordering itself, but it could probably overfit because of ordering depending on how much training data is available, and in this case we know that the order of input and output is not directly related. One way to make the LSTM model more robust and less prone to over-fitting would simply be by making a number of copies of each training examples where each copy is then mutated by changing order of the images and tags.

Glad to inspire and go ahead and use this idea. By the way my full name is Kaveh Hadjari.

Yes you would still would need a good image classifier like ResNet 34 to actually extract usuable features which could then be used as input to a RNN model.

An important point if you would try to actually implement such a model, don't train the image classifier together with the RNN as that would probably make the training unnecessarily slow with the end result of either not making a dent in the weights of the ResNet or simply overfitting the relatively small and inappropriate training set that is provided by Yelp for this competition. Instead use the ResNet classifier in a preprocessing step to transform the images to the activations of a later layer in the ResNet and use those as the input for the RNN model, note when training the RNN you should persist these activations as you would otherwise would unnecessarily need to run forward prop multiple times through the ResNet for each image. In this manner you get the benefit of the ResNet which is great at extracting features from images and the ability to train the RNN model much more quickly.

Nick (the author) reflects on this: "The data needs to be merged into a format which can be used to train a neural network. Solving this leads to the second, much bigger issue: many of the resulting label to image mappings are inappropriate...".

If one instead use a RNN (recurrent neural network) particularly with LSTM, then it can take as input the sequence of all photos from a business and the output of the model would then be the sequence of labels, similar to how translation models work. Of course then another problem could perhaps be the ordering of labels is unrelated to order of photos for a business, but there is probably some way to handle this by either data synthesis (multiple permutations of the training data to ignore ordering of labels) or by sorting the labels in a certain fashion that the model can learn.

That would exclude "no go zones" as they are inhabitated by the poorest AKA immigrants, and very few Swedes.

Lots of factors contribute to change in criminal activity, urbanization, rise of income inequality but also more people in segregated areas will probably not work out very well either.

That you believe a majority are religious fundementalist is bias

"Things are also confounded by the fact.."

Which facts? What do you base this belief on? Any sources to any studies?

Swedens tiny population of 10 million can't handle immigration of tens of thousands? That's laughabale, it's been doing exactly that for decades now. Iraq, Iran, Bosnia, Kosovo, Somalia, Eritrea, Ethiopia, Afghanistan, Iraq again, Ukraine, Syria. Only recently has a resistance to these policies been seriously challenged...

Upwards mobility will happen, even during the worst conditions, like the slavery in US, did they manage to break free. This is not about when but how, true solidarity or true civil war and tragedy..

If that's the long term goal, then the US government is going to have a problem things such as the internet, bitcoin and more technologies open up even more possibilities for foreign workers and freelancers to work from abroad and avoid US taxes all together.

As I've come to understand it when implementing deep learning machine learning the hardware requirement for running a trained neural network model efficiently is much lower than the one required to train it. I've also read somewhere that if an instance of AlphaGo run on a modern powerful desktop machine would compete with the cluster used in Lee See-dol match which consisted of something close to 2000 of CPUs and more than 100 gpus then the ratio in wins would be only be 3:1 in favor of the cluster. Much less than if you would compare it to the ratio of computational power so that gives you hint of how much of the intelligence in it is about previous knowledge gained vs brute computing power. To me that also implies that a lot of the innovation done at DeepMind is more about improving the speed of which a neural net learns and aquires knowledge and less about the running time of applying the model. And that's probably an important distinction in the discussion of this technology.