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Creating Intelligence with Data Science

In this article I will show how Data Science enable us to create intelligence through AI.

What is intelligence?

Not an easy question to answer. I struggled a while ago trying to define what was it, but I found a simple phrase in one of Lex Friedman‘s courses that I liked.

So let’s define intelligence as:

The ability to accomplish complex goals.

But what is complex here? How are we defining something complex? If you look in the internet you will find several different definitions, but I think the "main" one is close to what I think the definition of intelligence is talking about.

If we think that something complex as something having many parts related to each other in ways that may be difficult to understand, we can say then that something complex is a mix of things or parts, that together form a bigger thing, and the way those parts are related is not very easy to understand.

For example, something complex that has many parts that works together in a way that are not that easy to understand is a car.

But! If we take a look, the individual parts are not that hard to understand. I’m not saying that they are easy to build or see exactly what they do, but it is easier to grasp what they do.

So we can say now that intelligence is:

The ability to accomplish difficult goals by understanding the parts that form the main goal.

These goals will be defined in the context we want, but now we want to focus on the field of Artificial Intelligence (AI). So as AI wants to build intelligence using machines and computation trying to mimic the ways we as human see, hear, learn and more, these goals will be seeing, learning, hearing, moving, understanding and more.

What is understanding?

Other important concept that we will took from Lex’s classes is understanding. We have used that word several times by now, so lets define it:

Understanding is the ability to turn complex information into simple, useful information.

We need this, and we talked about it when we saw the parts of the car. When we are understanding we are decoding the parts that forms this complex thing, and transforming the raw data we got in the beginning to something useful and simple to see.

We do this by modeling. This is the process of understanding the "reality", the world around us, but creating a higher level prototype that will describe the things we are seeing, hearing and feeling, but it’s a representative thing, not the "actual" or "real" thing.

So how do us human create intelligence? By modeling the world around us, understanding its parts, transforming the raw data we got into useful and simple information to then see how these parts form more complex things, accomplishing in the end goals, "difficult" goals.

How long for us to be intelligent?

This took something like 3.800.000 million years. And we want this to happen in the next five years:

Even though it will not take us that long to accomplish complex goals with AI, it won’t be as fast as we think. We are a field that is maturing, and improving every day. But AI along will not solve all the problems.

What do we need to create intelligence with AI?

I think the recipe to create intelligence is not that hard in a high level. This is what I propose we need to do it:

Big Data + AI + Data Science = Artificial General Intelligence

I’m talking about Artificial General Intelligence (AGI) as the main goal of this revolution. AGI are general-purpose systems with intelligence comparable to that of the human mind (or maybe beyond humans).

We need Big Data as a Catalyst to get to AGI, because with more data, plus new ways of analyzing data, plus better software and hardware, we can create better models and better understanding. We need the current state of AI, very close to Deep Learning, Deep Reinforcement Learning and its surroundings (more about Deep Learning here), and then we need Data Science as the controller and science behind this revolution.

What is Data Science?

This definition may cause controversy for some people, but this is something I think is very close to what the leaders (both theoretical and in the business) side are saying right now. So,

Data Science is the resolution to Business / Organizations problems through mathematics, programming and the scientific method that involves the creation of hypotheses, experiments and tests through the analysis of data and the generation of predictive models. It is responsible for transforming these problems into well-posed questions that can also respond to the initial hypothesis in a creative way. It must also include the effective communication of the results obtained and how the solution adds value to the Business / Organization.

And with this definition we can define whom is a Data Scientist:

A Data Scientist is a person (or system?) in charge of analyzing business/organizations problems and give a structured solution starting by converting this problem into a valid and complete question, then using programming and computational tools develop codes that prepare, clean and analyze the data to create models and answer the initial question.

What I’m saying here is that Data Science is very much linked to the business, but it is a science in the end, or in the process of becoming one, or maybe not. I think it could be very useful that Data Science is a Science because if that’s the case, every project in Data Science should be at least:

**- Reproducible

  • Falible
  • Collaborative
  • Creative
  • Compliant to regulations**

You can read more about why is this important in the amazing book by Henri Poincaré, "Science and Method" free here:

Science and method : Poincaré, Henri, 1854-1912 : Free Download & Streaming : Internet Archive


The main point of this article (there might be more in the future about this), is showing you that these are really serious areas of research and development, we need all of them to get to AGI, and Data Science is crucial to this endevour.

You might think, why do we need AGI? or why do we need AI in the first place?

I think we can change the world for the better, improve our lives, the way we work, think and solve problems, and if we channel all the resources we have right now to make these area of knowledge to work together for a greater good, we can make a tremendous positive impact in the world and out lives.

We need more people interested, more courses, more specializations, more enthusiasm. We need you 🙂


If you have questions just add me on LinkedIn and we’ll chat there:

Favio Vázquez – Data Scientist / Tools Manager MX – BBVA Data & Analytics | LinkedIn


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