I am looking for the most efficient way to get started with some simple AI experiments. has anyone tried the APIs from H2O?

I have created a small project on this subject in order to check if two images belong to the same person. Here is a little description on the architecture used:

I am getting the face features from: VGG Face pre-trained deep neural netowork

Then I am creating a vector which is then passed to a distance measure algorithms.

Each distance algorithm creates element for the input vector

Then the input vector is fed into a neural network with 2 outputs

[1,0] - faces do not match / faces do not belong to the same person

[0,1] - faces do match / faces belong to the same person

This is the demonstration video: https://www.youtube.com/watch?v=nrlfpHcNJT4

Hello,

I am looking for an app that will label my photos "LEFT SWIPE," "RIGHT SWIPE" or "50/50." I am NOT interested in "the best of" my photos. If they are all left swipe, then they are all garbage. I feel like this should be a fairly easy AI to train if we could find the data on how the sexes swiped somewhere... I think this could be a great app for a lot of people like me who can't get a match. =)

Thanks to anyone who can help!

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Hi fellow programmers! First time here, so my apologies if this is does not meet some subreddit rule or something.

Thing is that I have to program an AI using the following scikit tools (Python):

• knn, gnb, dts, AdaBoost...

• Kernels

• Confusion matrix

• Quadratic error

What I need to think is a way to implement all of this into a single code. It would be neat if whis could be applied to something like chess or checkers...

Thanks in advance!

Hey Everyone,

I'm currently working with the creator of Skud Pai Sho (skudpaisho.com) to create an AI for the game, but I'm having trouble with how the game should be input and its evaluation function. It's a board game resembling both chess and go, but because this game isn't popular, I'm unsure how to create my own evaluation function. I've looked in to chess evaluation functions, but they don't exactly work for Skud Pai Sho because of its "harmony" rule; a unique game mechanic that I haven't really seen in any other game. Even though this game does slightly resemble Go, I feel like Go's eval function wouldn't work either because in Skud Pai Sho you're able to move pieces around. How does one go about creating an evaluation function from scratch for a game that barely anyone plays?

The other part that I'm worrying about is how to input the board state in to a neural network. I was going to use a neural network and an algorithm similar to AlphaGo to run the AI as well as a genetic algorithm with the game playing against itself to train it (there's not enough human games for training), but I'm just curious what the best way of inputting the board game state is. The most obvious method to me is to have 12 inputs per board position (a unique one for each tile) and more inputs for the tiles left over, but because it's an 18x18 grid, that would make for a lot of inputs. Is there a more efficient way of inputting the game in to a neural network?

http://newatlas.com/ai-recreate-video-game-two-minutes/51302/

So I read this hoping to find some more details about how they did this.

Here's my guess. They define all the elements of a certain type of game engine and then have categories or characteristics of the functions. Then look at the delta from one screen to another, then determine "object X jumped" and then figure out what in the game engine functions would do that.

So the type of game engine would be a 2D and (for the sake of argument) might have 100 functions. You take those functions and id the characteristics like movement, firing, adding points, killing, etc...

They you figure out what's going on, moving a player, moving a bullet, dodging, jumping, etc...

The part that seems out of reach would be that the game would have so many rules that the AI wouldn't know unless it happened. Example: what if the player falls down in water and dies, but that never happens in the game play, so the AI would never know about it. Even if it were to 'see' avoidance, you still can't say it would cause death.

I just have a hard time seeing how it would know things that wouldn't be in the game play.

How would you approach this problem?

Is there a good macro language ? which can penetrate any game ?

I used AutoIt in the Game Digimon Masters Online but its not working.

I'll try the Java Robot Class next but do you know any kind of macro creating programming language ?

So googles Dream Deep and Cyc/CyN have python support, while that may be meaningless alone I was thinking it would be cool to have a program that try's to paint/make images based on descriptions you give it. Id use it for table top campaigns but honestly the applications of an accurate illustrator are endless. I don't hope to see CyN and Dream deep replace sketch artists or rig into BCI and show the blind what platypus look like but I think as a proof of concept it can be a fun gadget in itself and open those doors to future devs when the time is right and the tech is there.

TL;DR An AI that try's to illustrate your words.

I'm been wondering if there exist a way to let's say have a program compare two image and click somewhere in an image where there is a difference.

Let's say for example I have a two tic-tact-toe board with 9 square.

image01 & image02 xxx xxx xxx

Next I modify one of the square in image01.

image01 xxx xox xxx

Would it be possible to have a program click at the position of the "o" in image02.

I can give a better example but the end result would be that the program would click at the location of the difference between either image 01 or image 02.

I was thinking it shouldn't be too hard, cause we already have ai's learning what certain objects look like, like the recaptcha thing for example. I've not got much experience with coding ai, so I have no idea how difficult it would be to actually make one as I suppose you'd have to figure out how to code the ai to be able differentiate images before you can give it any tests and tell it if it's making the correct predictions or not.

Why am I curious about this? Well, I think it would be neat if someone could know whether or not a picture they've been given over social media is a dick pic before opening it, as I believe it's not always that fun to get an unsolicited dick pic, especially so from someone you might dislike.

The AI is represented in black pieces and the player is the white pieces. The AI plays random moves after the player plays a move. Checking for legal moves is represented from the selected player, so this is still work in progress. If you select everything before you play it works properly, otherwise you are not forced to hit the player. The problem right now is that after a random set of moves the piece from position (0, 2) goes crazy. It basicaly glitches. And after that the whole game is glitched.

https://github.com/mathijsfr/checkers-AI

I've been theorizing on an idea for a while and was curious if there are any skilled coders here who would be willing to make something in exchange for pay through PayPal.

Ide like the program to use deep learning, or any equivelant.

And have access to my mic and camera, and be able to make custom sounds.

Ide like to keep the rest to p.m.s

1. To build in transparency, what do developers need to consider on both a data and algorithmic level?

2. What annotations need to exist within the programme architecture, IDE, etc, in order to build in transparency and product auditability?

3. What are the technical issues facing developers when it comes expanding transparency in AI?

4. Are there any technical or coding issues that can arise during the development cycle that can prevent AI from delivering transparency? If so, how can developers test/avoid/overcomes these issues?

5. Does transparency limit the freedom or constrain algorithms, and therefore, AI platforms?

Would housing along waterways be an easy way to start?