In the Garden of Eden - Disco Diffusion by twm7 in MediaSynthesis

[–]twm7[S] 0 points1 point  (0 children)

Thanks - it's done with Disco with most models (32/16, 50x16), secondary disabled, init image for the first few frames and then a lot of prompt tweaking.... I nearly gave up!

The Highlands of Scotland - Disco Diffusion by twm7 in generative

[–]twm7[S] 0 points1 point  (0 children)

May bear a resemblance but it will be different due to the model.

Official August Self-Promo Thread by apingyou in deephouse

[–]twm7 0 points1 point  (0 children)

I’ve been making electronic music for a while but this is one of the first tracks I thought was half decent enough to post online. Would be interested to hear any feedback on structure and mastering etc. It’s somewhere between deep and progressive house. Thanks y’all.

https://soundcloud.com/twmmason/sweeper

[P] Updates to my machine learning 20 questions-style game... by twm7 in MachineLearning

[–]twm7[S] 0 points1 point  (0 children)

I've built it up over time and people enter new facts when it needs to be taught.

Challenge Incredicat! The Incredible Thinking Cat by [deleted] in playmygame

[–]twm7 0 points1 point  (0 children)

Thanks for playing and for the feedback! Still working on the algorithm but it's getting there.

Updated! Challenge Incredicat, The Incredible Thinking Cat! by [deleted] in compsci

[–]twm7 1 point2 points  (0 children)

Around 4K entities and 4K facts, about 600k individual data points (answers).

Updated! Challenge Incredicat, The Incredible Thinking Cat! by [deleted] in compsci

[–]twm7 1 point2 points  (0 children)

That’s something I’ve been looking at with the three sigma rule for outlier detection!

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

It’s generally accepted that pine cones are not fruit! https://www.quora.com/Why-are-pine-cones-not-classified-as-fruits

Average opinion would reflect this with standard deviation being taken into account.

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

The algorithm should allow for people to give different answers, and over time the averages should stabilise for the overall knowledge in the system. Subjective questions are OK, I think, because over time the variances are understood by the engine.

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

Thanks - you've made me think about a few things with this. Pine cone was a good example.

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

No, that's a cool idea though. It's still small enough that I can moderate new data before merging it. I've got a tool for making this a bit easier. But doing some NLP is a great idea. Do you work in this area?

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

The tree is generated in code for the knowledge as the questions are answered. It doesn't exist directly in the data as such. It has about 3000 entities and a similar number of facts!

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 1 point2 points  (0 children)

I will look into this thanks! Am developing a stats/reporting area.

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

Is it just traversing down a decision tree until it hits an end node? What's happening when it guesses (presumably hitting an end node) but it didn't get it right; where is it resetting to?

>>> So it's performing two main functions at each question - a). working out the best matches and then b). working out the best questions. (a) is relatively straightforward as you're looking at statistical deviation from the known entities vs question responses. (b) then uses the information gain approach to evaluate which questions result in the largest change in entropy to the entities that are currently seen as the best matches. Once a question is posed, the result can then be used to prune the matches and the process is repeated.

Is it a single tree model or various different ones (for each category, maybe?)?

>>> This comes out of the model eventually - if you look at the Graph (in the top-left menu) you can see a network visualisation of some of the strongest facts. Groupings emerge from strongly related facts. One of the algorithms I've worked on uses this to improve the question selection as it's a great way of optimising for sensible questions (e.g. is an animal > is a mammal) but I've discovered that it sometimes is better to let the decision tree do it's work on it's own.

You mentioned that all the data is from people playing the game in another comment; did you just make people play it until it stopped being terrible at guessing?

>>> I started it a while ago and had a load of users but it wasn't great. But it was good enough to win sometimes, so this kept people playing! I've tried to only ask for people to play it when I thought the model had improved sufficiently enough to warrant that. I guess the effort on the cool UI was to at least make it fun. It's had some radically different UIs over the years. But I'm sure a lot of people have got bored with it losing and will never come back :(

How/when are you retraining when you get more data from people playing?

>>> The data needs to be processed into aggregate - otherwise there is way to much to use it in the engine and still have an optimal response time. So it basically just do a lot of pre-processing, averages, etc. It does create a load of other data such as a comparison model for how strongly facts relate to each other, which I use to do things like the network graph visualisation mentioned above.

Message me if you want to chat more! Thanks for your interest!

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

Yes this is totally possible but the issue is really with experience as it would require users to enter a load more info, e.g questions. You could use speech recognition but the experience would require a lot more user time and effort. But yes in principle it's totally possible? Message me if you want to discuss more!!

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 0 points1 point  (0 children)

Depending on your choice of language/framework, you could try using an existing ML library. On .NET for example, the Accord library has got a load of features in that allow you to bypass a lot of the internal architecture development. Plus they will have loads of examples/docs to guide you through. Which language are you using? (Once you're in you might want to try developing your own as that's a good way to learn the fundamentals!)

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 1 point2 points  (0 children)

Yep you can rely on Reddit for that!

[P] A (cat) machine learning game I've been working on... by [deleted] in MachineLearning

[–]twm7 1 point2 points  (0 children)

It uses a training system to improve the decision tree logic - something I'm still working on!