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Improve AI – Optimize Your App Easily with AI

improve.ai

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Re: Improve AI – Optimize Your App Easily with AI

#11
post #2

Hi there, Justin here, the creator of Improve AI. I would love any feedback and feel free to ask me anything. Thanks!

This looks awesome! Is there anyway to pay you for the license but self host it instead of aws?

I'd love to learn more about what you're envisioning, you can e-mail me at justin@improve.ai or hit me up on Discord at https://discord.com/invite/mxtdJxfyRk

Re: Improve AI – Optimize Your App Easily with AI

#12
post #9
post #8

Earlier quoted context omitted.

Going to sound cynical/snarky below, promise I'm not. Also disclaimer, I know almost nothing about ML: - The homepage makes a vague statement about "AI". This is a personal thing, but to me "AI" sets off warning bells. It feels like a vague term, compared to "ML". - I couldn't find any FAQ or references on the site to technical architecture. What underlying framework/library is used for the models, and what kind of N…

I hear you on the AI vs ML thing. I doubt the debate will ever be resolved, but the domain name is .ai so I went with that. The reason to use a full machine learning model instead of a simple statistical model is three-fold: 1) The framework supports any arbitrary JSON encodable data structure as a variant, this includes nested dictionaries, lists, etc. A full ML model allows capturing the entire complexity of the da…

Those are really good answers, especially the points about nested JSON structures and generalization.

Not sure I understand point #3 -- not familiar with global vs contextual optimum. The idea is that a global optimum is the aggregate optimum across all users, versus a contextual optimum which is the optimum for just the current user/device?

Couldn't you do this by doing regressions on a per-user-id basis or similar if that was the case? (I really don't know)

Re: Improve AI – Optimize Your App Easily with AI

#14
post #13

This is a really good example of putting ML Models into real world product engineering, nice use us adding the functions like 'which' etc in code. May I ask where did you get inspiration to do this and build this solution?

Wow, thank you so much. What a nice thing to say!

The inspiration comes from way back in the early 2000s. My team invented HTTP Live Streaming and there were a lot of performance sensitive places in the code where I was essentially making guesses on the values of buffer sizes, initial bitrates, etc and I wished that the variables could just auto-tune themselves in production.

I started working on this in earnest 7 years ago and this release is the result of countless hours of iteration and refinement. It means a lot that you feel like the API is good.

Re: Improve AI – Optimize Your App Easily with AI

#17
post #16
post #2

Hi there, Justin here, the creator of Improve AI. I would love any feedback and feel free to ask me anything. Thanks!

Any technical reason why there's no Typescript SDK?

For our initial launch we decided to go with Python and Java. For the time being for other backend frameworks we figure people can fairly easily spin up a Python microservice. We are listening to the requests for other SDKs so thanks for mentioning it.

Re: Improve AI – Optimize Your App Easily with AI

#18
post #15

Wonderful! Can you please provide some easy examples? Can this be a pip3 package?

It is now up on pypi:

https://pypi.org/project/improveai/

We’ll be updating the docs with examples over the coming weeks. Are there any specific use cases you’re interested in?

Re: Improve AI – Optimize Your App Easily with AI

#20
post #7
post #6

This looks awesome, I'm excited to try it out. It'd be cool to be able to dynamically deploy new configuration options without deploying new device code, or remove bad configurations. Looks like that could be possible but it would depend on your app to supply the configuration. Is there any support for continuous variables (e.g. find me the best price between $10 and $20)?

Thanks! For updating variants remotely you can query them from a database or use something like Firebase Remote Config. We've intentionally separated updating variants from the decision of which variant to choose so that decisions don't block on network requests. The machine learning models actually perform wonderfully on continuous variables, but for this initial launch we're having developers specify the increments…

I'm not in the market right now, so don't do it for me :)

That makes sense, I think it's the right call.

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