# Tag Info

### Can a neural network be used to predict the next pseudo random number?

If we are talking about a perfect RNG, the answer is a clear no. It is impossible to predict a truly random number, otherwise it wouldn't be truly random. When we talk about pseudo RNG, things change ...
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### Could a neural network detect primes?

Early success on prime number testing via artificial networks is presented in A Compositional Neural-network Solution to Prime-number Testing, László Egri, Thomas R. Shultz, 2006. The knowledge-based ...
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### When will the number of neurons in AI systems equal the human brain?

Some back of the envelope calculations : number of neurons in AI systems The number of neurons in AI systems is a little tricky to calculate, Neural Networks and Deep Learning are 2 current AI ...
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### How can I predict the next number in a non-obvious sequence?

This is a question of time series forecasting, since your numbers form a sequence. You may want to take a look at the "forecasting" tag at CrossValidated. If you have only 700 data points, ...
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### How can I predict the next number in a non-obvious sequence?

As all you have is a series of numbers, you should try using a sequence model. I suggest you look into RNNs and in particular LSTMs. Of course this is assuming despite the lack of "obvious ...
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### What makes neural networks so good at predictions?

Neural networks are good at classifying. In some situations that comes down to prediction, but not necessarily. The mathematical reason for the neural networks prowess at classifying is the ...
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### Is there any research on the application of AI for drug design?

Yes, many people have worked on this sort of thing, due to its obvious industrial applications (most of the ones I'm familiar with are in the pharmaceutical industry). Here's a paper from 2013 that ...
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### When will the number of neurons in AI systems equal the human brain?

Soon enough but that doesn't mean anything at all. In machine learning the word neuron represents a calculation whereas in brain the word neuron represent a specific type of cell which is a ...
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### Do I need classification or regression to predict the availability of a user given some features?

Yes. For instance, the popular softmax regression gives you probability distribution for each class. Yes. Softmax is a regression over a set of discrete classes. We can use regression for ...
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### How can I predict the next number in a non-obvious sequence?

I guess the most "suitable" approach is to look up research papers on ML/AI/Stats based methods on bipolar disorder mood swings prediction/regression etc. Focus on the abstract, intro/...
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### Can a neural network be used to predict the next pseudo random number?

Old question, but I thought it's worth one practical answer. I happened to stumble upon it right after looking at a guide of how to build such neural network, demonstrating echo of python's randint as ...
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### How to design a neural network when the number of inputs is variable?

The best option in your case would probably be zero-padding or padding up. This is simply zeroing out inputs for cases in which there is no data. It's done a lot on the borders of images for CNNs. ...
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### Could a neural network detect primes?

I'm an undergraduate researcher at Prairie View A&M university. I just spent a few weeks tweaking an MLPRegressor model to predict the $n$th prime number. It recently stumbled into a super low ...
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### What could possibly replace artificial intelligence?

By definition, artificial intelligence includes all forms of computer systems capable of completing tasks that would ordinarily warrant human intelligence. A superintelligent AI would have ...
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### How can I predict the next number in a non-obvious sequence?

Since you only have only 700 observations, I would not try a deep learning approach. I think it is very unlikely that any Deep Learning approach will learn a non-obvious relationship with that little ...
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### Is there any research on the application of AI for drug design?

Yes, there were successful attempts at predicting the interaction between molecules and biological proteins which have been used to identify potential treatments by using convolutional neural networks....
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### When will the number of neurons in AI systems equal the human brain?

The answers so far haven't answered the question numerically, so here is my attempt to steer them in the direction I was seeking: The freely available Deep Learning Book has the following figure on ...
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### When will the number of neurons in AI systems equal the human brain?

While interesting, this is all rendered somewhat moot if you think about what will happen once we understand how the brain works. After all, once we understood flight, we didn't start making birds. ...

### Could a neural network detect primes?

In theory, a neural network can approximate any given function. This result is known as the universal approximation theorem. However, if you train a network with the numbers $0$ to $N$, you cannot ...
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### Can a neural network be used to predict the next pseudo random number?

Being a complete newbie in machine learning, I did this experiment (using Scikit-learn ): Generated a large number (N) of pseudo-random extractions, using python random.choices function to select N ...
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### Selecting the right algorithm to predict disease from questions

There is no defined rules for choosing a machine learning algorithm to learn some type of pattern. However, there are some guidelines to help you better select an algorithm which will yield a higher ...
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### Can one use an Artificial Neural Network to determine the size of an object in a photograph?

Can one use an Artificial Neural Network to determine the size of an object in a photograph? Yes: Learning Depth from Single Monocular Images In the end, depth is just one special form of size. Of ...
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### Can one use an Artificial Neural Network to determine the size of an object in a photograph?

In my thesis I actually solve the problem of depth estimation with a CNN based on a single monocular image so I can share my experiences for understanding that problem. As you already stated in ...
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### Why is it harder to achieve good results using neural network based algorithms for multi step time series forecasting?

ANNs & RNNs can be used to create some great models in many different domains, including time-series forecasting. However, across all of these domains, they suffer from the problem of hyper-...
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### How do I predict the occurrence of rare events?

It might be more informative to: Label each combination of location, type, and time of crime with a crime rate. For example, theft, in Crystal City, at 11pm at night, occurs 20 times per year, or 0.4 ...
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### Can a neural network be used to predict a sequence of integers based on dataset of previously produced random numbers?

The post you linked to clearly states that pseudo random number cannot be predicted. Their randomness is made to be nearly perfect, and if you ever found a way to even predict a pseudo random number ...
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### How to perform prediction when some features have missing values?

You should look into "missing values". This is an entire research field in itself. First, you need to identify the type of missing values: They can be missing purely at random. Whether they ...

### What makes neural networks so good at predictions?

With Neural Networks you simply classify datas. If you classify correctly, so you can do future classifications. How It Works? Simple neural networks like Perceptron can draw one decision boundary ...
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Additional features can also cause overfitting if they have low or misleading information. Consider the following problem: $X = [1, 3, 3, 4, 5]$, $Y = [1, 3, 4, 4, 5]$. Suppose that the real ...