|||

Open Source

Dear Friend,

I’ve been think a lot about open source lately. I’ve also been thinking of closed source and open core too.

All those words. What do they mean? Why does it sound so important and confusing at the same time?

Selling AI

I’m back in sales now and you can say that I sell AI. What a strange thing to say, sell AI. I help sell support and Driverless AI.

Support for what?

I sell support for the open source offering called H2O-3.

Wait, it’s open source right? Why isn’t it free?

It is free.

We all love free.

Free, free, free, I can do whatever I want and use it wherever I want!

That’s right. You can use it for free. All over the place.

The community develops it. They make the fixes and H2O.ai keeps developing it too.

So many other Data Science platforms use H2O-3 in their backends and make money from it. H2O-3 has enabled companies to make BILLIONS of dollars from free.

Bad Business Strategy

Is open source a bad business strategy. It can be. Is this the case here? No.

Good open source products are ok. Awesome open source products level the field. They destroy competition before it begins.

So many open source’ companies just build one open source product and then quickly build closed source products to make money.

I get it, you have investors. You want to keep the lights on. You build one lone tree and try to call it forest.

Raise a Forest

H2O-3 is free. So is Flow. So is Sparkling Water and H2O4GPU.

So many companies use this with Scala, Python, and R. Thousands upon thousands of companies use these tools in production and make tons of money from it.

Years ago H2O planted seedlings that have now grown into a strong and vibrant forest. Every once in a while a forester needs to come and trim a few branches. That’s the support we sell, and we sell it well. We’ve built the ecosystem and we lovingly tend to it.

Sometimes a tree dies and returns to the earth from whence it came. It makes room for a new seedling. This one is called Driverless AI.

Driverless AI

It’s closed source, it’s product. It has all the power of the open source stuff but with more.

MORE.

Yes, more.

It’s cutting edge.

Machine learning interpretability.

Feature generation.

Much, much more.

You could build your own Driverless AI if you want. The free tools are out there.

But do you understand the ecosystem? Do you know where to trim the branches and on what tree?

Do you know the seldom traveled forest path to get to where you want to go?

Maybe.

Maybe not.

This blog is open source

All my tutorials on RapidMiner helped me become who I am today. The giving of my time and myself to answer questions and create tutorials have help countless of organizations adopt RapidMiner and use it to make money.

I benefited from it by working for RapidMiner for 3 years. I transformed my career into something wonderful. Thank you all. I really mean that.

I’ve met so many awesome people. Inspired.

I’ve made so many incredible friends.

Don’t be confused

Don’t be confused. Open source is altruistic giving. It’s for something greater than yourself.

It’s a mission. It’s for the hearts and minds of people. For you.

Take your idea. What you love.

Throw it out to the universe and it will come back to you a thousand fold.

One tree makes thousands of seeds.

All you need to do is spread them.

Up next H2O.ai This week (10/3/18) I traveled to Mountain View, the ground zero of this awesome AI startup. I’m in sales engineering training and learning all the H2O World London 2018 - Record Signups! We now return to our regularly scheduled machine learning and sales engineering posts, already in progress… I’m off to London later tonight to go to
Latest posts The Ye Old Blog List Motorola: Then and Now EWM Redux Testing for mean reversion with Python & developing simple VIX system - Talaikis unsorted - Tadas Talaikis Blog Steps to calculate centroids in cluster using K-means clustering algorithm - Data Science Central Basics of Statistical Mean Reversion Testing - QuantStart Algorithmic trading in less than 100 lines of Python code - O’Reilly Media Interpreting Machine Learning Models Microsoft the AI Powerhouse Investing in the S&P500 still beats AI Trading Microsoft makes a push to simplify machine learning | TechCrunch 10 Great Articles On Python Development — Hacker Noon Introduction to Keras Democratising Machine learning with H2O — Towards Data Science Getting started with Python datatable | Kaggle Phone Addiction Version 12 Launches Today! Machine Learning Making Pesto Tastier 5 Dangerous Things You Should Let Your Kids Do The Pyschology of Writing Investing in 2019 and beyond TensorFlow and High Level APIs Driving Marketing Performance with H2O Driverless AI Machine Learning and Data Munging in H2O Driverless AI with datatable Making AI Happen Without Getting Fired Latest Musings from a Traveling Sales Engineer The Night before H2O World 2019 Why Forex Trading is Frustrating Functional Programming in Python Automatic Feature Engineering with Driverless AI Ray Dalio's Pure Alpha Fund