How AI Bots can beat Humans at Starcraft using Machine Learning (Use Case)

For #transformationtuesdays I’m sharing one of the most common use cases for Machine Learning that a lot of people who are young or young at heart can relate to – computer games.

For today’s example, it’s how AI Bots can be better than humans at playing Starcraft.

Why Starcraft? Because its complexity and the multitude of factors to consider that affect gameplay is closer to the number of factors a human brain considers in real life when making decisions, as compared to other games like Chess for example, where players take turns.

Why is this important? Because implementing Machine Learning Algorithms on games like Starcraft will allow us to learn more about how we can build better Bots that will be applicable to the real world.

Read on for more details and to see the actual use case.

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Chat Bots Making Phone Calls on Your Behalf using NLP AI (Use Case)

For today’s #transformationtuesdays we’ll talk about an innovation in AI (Artificial Intelligence), particularly Natural Language Processing.

You know when there are big corporate bosses or entrepreneurs who get to delegate tasks to their Assistants such as booking dinner reservations, hair stylist appointments, and other tasks that would require the Assistant to contact other people to complete the task?

What if you had the power to do all that, without having the need to hire a living breathing Assistant, and all you have to do is command your mobile phone to do those kinds if tasks for you. Wouldn’t that be awesome?

Well that’s exactly what I’ll be showing you today.

You see, Google has been busy developing the next generation Google Assistant, where they have injected it with Google Duplex technology to give it the power to make Phone Calls on your behalf.

Some of you may already know this, but for those who aren’t aware of the existence this technology yet, I’ll share with you (1) The Demo when it was launched, so you know how it works, and (2) Where it is being applied now, and where it will be used next.

And for those who want to know what goes on inside these kinds of Chat Bots, and where Natural Language Processing and AI comes into play, then I’ll break down the bits and pieces for you so you’ll get a better understanding.

Let’s go!

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How Eduardo reduced Software Bug Fix Lead Time from 25 to 15 days (LSS Green Belt Use Case)

It’s #transformationtuesdays and today we’ll talk about a Use Case of Lean Six Sigma being implemented successfully in the Technology industry.

Usually, Tech firms would default to the Agile approach and talk about how they can make further improvements during their Scrum rituals.

And non-Technology companies take best practices from Tech firms implementing Agile and Scrum, to see how they can work in a non-Technology setting.

But here you’ll see the opposite happening.

Lean Six Sigma, a methodology widely used in non-Technology settings, being implemented in the Software and Technology industry.

Today I’ll be showing you the entire Lean Six Sigma Green Belt Project Storyboard by Eduardo Torres, where he was able to reduce Software Bug Fix Lead Time from 25 to 15 days.

This not only improved Customer Perception in a good way, this has also increased Team Member Morale as they were able to free up some of their capacity for them to work on features, moving them in the right direction to become Best in Class.

Continue on to see the full project storyboard.

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You Won’t Believe what Dale and Tracey said about the Online Green Belt Course at GoLeanSixSigma

Yesterday, I shared how I learned my core skillset – Lean Six Sigma.

This is the skill that allowed me to broaden my mindset and branch out to learn and gain experience in various other Continuous Process Improvement related skills, including automation, and even Artificial Intelligence, which I’ve been posting a lot about lately.

I truly believe that this skillset is foundational for you to be able to look at business processes in a way that no one else in your company has seen before.

And this will definitely open up so many doors in your career, as it has for me, and you will be known as the one who can make things done.

Without this skillset, I don’t think I could have achieved the same level of success as I have now.

And for today’s #transformationtuesdays, apart from what I have just shared with you regarding how this has transformed my life and my career, I’d like to share with you 2 more from people just like you – Tracey and Dale.

Like you, they’ve researched about how they can get themselves Lean Six Sigma Green Belt Certified for them to take their career to the next level.

They’ve also looked at several other options and providers, both in-classroom and online, and have weighed the pros and cons of each. And have even experienced some of these trainings, only to end up either more confused, overwhelmed, or constrained by time.

But in the end, you won’t believe what they had to say about GoLeanSixSigma.com’s Online Green Belt Training and Certification course.

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Sorting Lego Bricks using Computer Vision AI (Use Case)

For #transformationtuesdays I’m sharing another use case for Artificial Intelligence using Computer Vision.

This is the world’s first universal Lego sorting machine by Daniel West, and here you’ll see a demonstration of it in action, as well as the details as to how it works.

What makes this interesting is that the typical image classifiers you’ll see work on 2D images. But this sorter works on 3D real-life Lego bricks, which makes it more challenging.

Moreover, it has the ability to classify even Lego pieces that it has not seen before!

In fact, that’s what makes it AI, as otherwise, perhaps you could just simply hardcode every Lego brick piece into the program as if it were just a rules-based task.

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How Artificial Intelligence allows the Blind to “See”

Last Friday we talked about some Artificial Intelligence Basics, specifically Computer Vision.

So for today’s #transformationtuesdays I’ll share with you a specific use case where Computer Vision is being used, together with Natural Language Processing to describe to a blind person what is in their surroundings.

It can read text, answer certain questions, and even identify sentiment and emotion on the faces of the people in front of them.

If you haven’t seen this yet, then now is the time to check it out.

If not, you’re missing half of your life.

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How Jamen went from Zero Experience to becoming a Data Scientist (Success Story)

It’s #transformationtuesdays where I share use cases and success stories that you can learn from, and replicate too!

If your dream is to become a Data Scientist, and you’re wondering what you need to do, and what it would take to break into one of the most sought-after jobs of the future, then this article is for you.

Today, I’m sharing the success story of Jamen Long, and how he broke into his career as a Data Scientist.

And like you, he started with zero experience.

If you’re interested to find out exactly what Jamen did, then read on.

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How Facebook uses Data Science for Social Analytics (Use Case)

It’s #transformationtuesdays and our topic of the day is Data Science, and how Facebook uses it to do the following:

  1. Facial Recognition
  2. Textual Analysis
  3. Targeted Advertising

No, they didn’t use some magic beans then all of a sudden they became an internet giant.

They uses Data Science extensively to make these things possible.

If you want to find out how, then read on.

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How Design Thinking saved the struggling Oil of Olay brand (Use Case)

For today’s #transformationtuesdays I will be sharing with you a case study of how Design Thinking saved the struggling Oil of Olay brand.

In the early 1990s, Proctor & Gamble’s Oil of Olay brand reached a point where it was seen by the public as a brand meant for “older” women.

They have lost their competitive edge as a top skin care brand.

In short, they were in trouble.

At that point they had 3 choices:

  1. Scrap Oil of Olay and just launch a new brand
  2. Buy out a competitor
  3. Innovate and reinvent the Oil of Olay brand

The use case below talks about how they applied Design Thinking to put themselves in the user’s shoes, empathize with them and find out what their pain points are.

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