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Democratizing Access to AI with K3ai (keɪ3ai)

December 14, 2020 by systems

Make it easier for everyone to start and learn AI — 927 words (< 5 mins read)

K3ai (kei3ai) is a lightweight infrastructure-in-a-box specifically built to install and configure AI tools and platforms to quickly experiment and/or run in production over edge devices.

K3ai Channel

“Artificial Intelligence platforms are complex”.

Photo by tian kuan on Unsplash

They combine a multitude of tools and frameworks that help Data Scientist and Data Engineers to solve the problem of building end-to-end pipelines.

But those AI platforms, by inheritance, have a degree of complexity.

Let take at the use case of some of them:

The end goal of every organization that utilizes machine learning (ML) is to have their ML models successfully run in production and generate value to the business. But what does it take to reach that point?

Before a model ends up in production, there are potentially many steps required to build and deploy an ML model: data loading, verification, splitting, processing, feature engineering, model training and verification, hyperparameter tuning, and model serving.

In addition, ML models can require more observation than traditional applications, because your data inputs can drift over time. Manually rebuilding models and data sets is time consuming and error prone.

Kubeflow project — https://www.kubeflow.org/docs/about/use-cases/

See the elephant in the room?

We all have to struggle with the complexity of a process that has no clear solutions.

Click on the image to zoom in/out

So here the first problem we identified (yes I said first):

Remove the complexity and give you a straight solution.

Now there are plenty of alternatives when it comes to the infrastructure (aka get a local infrastructure to play with) and some of them even allow you to install some platforms like Kubeflow but.. could you cherry-picking AI tools and/or solutions and running them on top of an infrastructure that does not suck up your entire laptop RAM?

Let say you start from learning the basics of training a model on different platforms and later move to learn serving models. You won’t have everything running but move from one configuration to the other quickly and to do so there is not an easy way to accomplish your goals and make your life easier.

Words are important but we are visual animals so we love to see things more than read them. Here’s a short video that shows how it is easy to deploy a full Kubernetes cluster and add on top of it any AI tool I like.

Filed Under: Artificial Intelligence

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