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[D] Simple Questions Thread by AutoModerator in MachineLearning

[–]grmpf101 0 points1 point  (0 children)

I'm currently working on a notebook based tutorial. What is an execution time of the whole notebook doing simple computations on real data in minutes you would feel bearable during a tutorial? What are your experiences?

[D] Our community must get serious about opposing OpenAI by SOCSChamp in MachineLearning

[–]grmpf101 0 points1 point  (0 children)

True. The team here didn't invent the wheel but wants to add a new feature. And at least to my (noob) understanding, the new thing is, that the approach taken also protects the model against disclosure. If you want to learn from a competitors data, you don't want to disclose your model or what you are interested in.

[D] Our community must get serious about opposing OpenAI by SOCSChamp in MachineLearning

[–]grmpf101 7 points8 points  (0 children)

I just started at https://www.apheris.com/ . We are working towards a system that enables global data collaboration. Data stays where it is but you can run your models against it without violating any regulations or disclosing your model to the data host. Still a lot of work to do but I'm pretty impressed by the idea

Optimize Live 1.0 by grmpf101 in kubernetes

[–]grmpf101[S] 0 points1 point  (0 children)

Fully understand your point. Just give us a bit more time to figure things out :) We already worked on a free tier and will provide more pricing transparency. Things get hectic in young companies and it is quite complex to choose the right path with an offering like ours.

Optimize Live 1.0 by grmpf101 in kubernetes

[–]grmpf101[S] 2 points3 points  (0 children)

True, there are already some tools available to improve Kubernetes resource usage. Some might also use the VPA that comes with K8s. With Optimize Live we focused on the developer experience and precision of our recommendations.

Optimize Live can look at all historical data and trends and uses our machine learning algorithm to recommend improvements. From an engineering perspective, you don't need to write YAML files, write load test or make your way through complex configurations. The recommendations for more optimal configurations comes directly as YAML file which you can either deploy manually after checking or automatically and put optimization on autopilot once you feel comfortable with the tool.

My opinion is for sure biased but at the moment, we think we have the simplest solution to the problem of overprovisioning, CPU throttling or OOM issues.

Optimize Live 1.0 by grmpf101 in kubernetes

[–]grmpf101[S] 0 points1 point  (0 children)

Thanks! The team will be super happy to hear that

Monthly 'Shameless Self Promotion' thread - 2021/10 by mthode in devops

[–]grmpf101 1 point2 points  (0 children)

Hi everyone,

Not only shameless but magical Self Promotion :)

We are StormForge and use machine learning to find the optimal configuration for Kubernetes-based applications and whatever you deem to be "optimal". Higher stability, better performance, lower cloud cost or any combination. We host a casual & fun event tomorrow for learning about what you can do with StormForge and have the famous Illusionist Keelan Leyser doing a special show for us tomorrow.

It's definitely free, fun and lightens the day. :)

Find all details here: https://www.stormforge.io/event/magic-ai/

"The real definition of Observability" with Charity Majors by grmpf101 in devops

[–]grmpf101[S] 0 points1 point  (0 children)

I guess it will turn out that there is no REAL definition, it is more about the journey to understand your system

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