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Virtual Reality and its Impact to the Future of Businesses

For today’s edition of #futurefridays let’s talk about Virtual Reality, and how it will change the Future of how Businesses operate today.

Have you ever been in a situation where you were trying to choose a resort to go to for your vacation, and you made your decision based on the pictures you saw?

What if there was a way to “try before you buy” by way of virtually immersing you into the resort, so you can experience what it’s like being there first-hand. Would that make your decision-making faster?

That’s what Virtual Reality can do for you. And it has many more use cases other than that.

Join me as we explore what Virtual Reality is and how it can be helpful in changing the way we do things within and around your business.

Let’s start with a video that defines what Immersive Technology like Virtual Reality is, and some examples of how it applies in the world today.

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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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Artificial Intelligence Basics: What is Machine Learning?

It’s #futurefridays and today we’ll be talking about the basics of Artificial Intelligence.

Previously, I talked about Natural Language Processing, and before that, Computer Vision.

But today we’ll tackle another field of Artificial Intelligence called Machine Learning.

Wikipedia defines Machine Learning as:

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task.

Let me show you some examples of how Machine Learning is being used in real-world scenarios.

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Why AI (Artificial Intelligence) is still considered “Primitive”

For #wisdomwendesdays I’ll be helping shed some light on the fears that have been brought about by the coming of Artificial Intelligence.

Though I’ve mentioned in one of my previous articles that:

“Though we all know that technology is continuously improving. But we shouldn’t put all our trust in it just yet. Yes, Google’s AI has nearly twice the IQ of Siri, but a 6-year-old child is still smarter than both. And even if it does improve further, 75% if customers, like you, still say that they would want to interact with a real person more as technology improves. child.”

I’d still like to talk about this a bit more, especially on why AI is still considered “Primitive.”

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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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What will happen to RPA (Robotic Process Automation) in 2020?

For #futurefridays let’s talk about RPA (Robotic Process Automation) and what will happen to it in 2020.

With all the rage about AI (Artificial Intelligence) and the Future of Work, people have been saying that RPA seems to have taken a back seat from all the action.

To the uninitiated, I’ll talk about the difference between RPA and AI.

So back to what will happen to RPA, in the recent past, people have been so afraid about RPA and that people would lose jobs because of it.

That was only for RPA. What more for AI? I guess people are, and were, just afraid of what they don’t know.

But now that people have become accustomed to having a “Digital Workforce” or software robots working alongside them, people’s thoughts have changed from fearing about job security, to scrutinizing where RPA falls short!

In my opinion, that’s a good thing, because we can now start doing innovations!

Here are some of the things I’ve heard people say about RPA lately:

  • It’s becoming a band aid solution
  • It can only do so much
  • With AI coming in, let’s just set our sights on that

With that, I’d like to talk about each of those bullet points in detail.

I will share my thoughts based on my own experience, as well as where I think RPA will be going to next.

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DEMYSTIFIED: What’s the difference between Classification and Regression?

For today’s #futurefridays I’m going to answer a question that confuses a lot of people trying to learn Data Science and Machine Learning.

The question is “What’s the difference between Classification and Regression?”

Let me give a shot at this with a simple explanation and example.

Think about the output that you want to achieve.

If you have a dataset, and the output you want to get are labels or categories, then it’s classification.

However if the output you want to get is a numerical value based on computations done on the dataset, then it’s regression.

Let me give you a specific example.

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Artificial Intelligence Basics: What is Natural Language Processing?

It’s #futurefridays and today we’ll be talking about the basics of Artificial Intelligence.

Previously, I talked about Computer Vision. But today we’ll tackle another field of Artificial Intelligence called Natural Language Processing.

Wikipedia defines Natural Language Processing as:

Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.

Let me show you some examples of how Natural Language Processing is being used in real-world scenarios.

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RPA vs AI: What’s the Difference?

For today’s #wisdomwednesdays I’ll talk about the difference between Robotic Process Automation (RPA) and Artificial Intelligence (AI).

In a sense, they can both be categorized as forms of software automation. But the major difference is their purpose.

The short explanation is that RPA is used to automate repetitive rules-based tasks, such as repetitive clicks and keystrokes, copying and pasting, if-then types of processes.

On the other hand, AI is used to automate tasks that require judgment, such as reading unstructured documents, identifying patterns, making decisions based on what you see in photos, or getting context based on what you hear in conversations.

Read on to find out the long explanation as well as some examples. This will also touch on Machine Learning.

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