DON’T argue with Donkeys

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Fable: DON’T ARGUE WITH DONKEYS

The donkey said to the tiger:

  • “The grass is blue”.

The tiger replied:

  • “No, the grass is green.”

The discussion heated up, and the two decided to submit ohim to arbitration, and for this they went before the lion, the King of the Jungle.

Already before reaching the forest clearing, where the lion was sitting on his throne, the donkey began to shout:

  • “His Highness, is it true that the grass is blue?”.

The lion replied:

  • “True, the grass is blue.”

The donkey hurried and continued:

  • “The tiger disagrees with me and contradicts and annoys me, please punish him.”

The king then declared:

  • “The tiger will be punished with 5 years of silence.”

The donkey jumped cheerfully and went on his way, content and repeating:

  • “The Grass Is Blue”…

The tiger accepted his punishment, but before he asked the lion:

  • “Your Majesty, why have you punished me?, after all, the grass is green.”

The lion replied:

  • “In fact, the grass is green.”

The tiger asked:

  • “So why are you punishing me?”.

The lion replied:

  • “That has nothing to do with the question of whether the grass is blue or green.

The punishment is because it is not possible for a brave and intelligent creature like you to waste time arguing with a donkey, and on top of that come and bother me with that question.”

The worst waste of time is arguing with the fool and fanatic who does not care about truth or reality, but only the victory of his beliefs and illusions. Never waste time on arguments that don’t make sense…

There are people who, no matter how much evidence and evidence we present to them, are not in the capacity to understand, and others are blinded by ego, hatred and resentment, and all they want is to be right even if they are not.

When ignorance screams, intelligence is silent. Your peace and quietness are worth more. 🤎

AI – your business already has projects underway for the most important part and aspect of AI and it’s not technology

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With increased knowledge, frankly, you can, reuse, and leverage, train AI with data you already have however, the most important essay is was and will be Quality, fact. And you don’t need to purchase special proprietary, IP or vendor programs to take advantage. Do you need it to be untangled explain in the mystify it’s not marketing crap it’s the real world

You have the foundation for AI already in your ability, you may not know broadly that is AI is solely based on data, standardization, profiling, quality in essence, statistics because that’s what makes information , we already have it and more importantly, it can be accomplished by your own developers or regular consultant, contractors, contractors.

It’s only the AI algorithm and algorithms that you may need some guidance and use open source. More importantly, even if you decide to buy a proprietary AI model, there are numerous open source models that you can build or prototype making sure you have the correct information, data assumptions and Hokies bill to make a meaningful model.

“You get what you inspect, not what you expect” There are many skilled people and resources that can build and validate the foundation for your Company without knowing much about in the beginning stages, the emphasis should be on business requirements and data quality before anything else weather Data Governance or AI.

It’s the same it’s start with understanding your own information or data. AI the Data quality principles that we used are still the same and they hold.

I will be posting and scheduling a free brief webinar to hopefully demystify this going forward. AI is a evolution is not revolution there’s no magic. although I will add that one major impact of AI is it can used in and reducing the cost and time for data governance and data stewardship

3 Minute AI School Bytes Episode 2 Correlation versus Causation

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3 Minute AI School Bytes Episode 2 Minute AI School Bytes Episode 2Hi
Artificial intelligence , define correlation or causation , a very important difference
Artificial intelligence stems from a concept invented by Alan Turing during his work with The Bomb , an early computer , in World War II. Needless to say, there are many aspects of today’s AI. However, most of them are driven by various features and math formulas.
Ultimately, I mean data fields ,are the primary drivers of AI and the concept of correlation or causation . In essence, they are represented in the graph by a line pointing upward or down a trend , if you involve two features , let’s say, in the same general direction of the other arrow, and, there is another arrow adjacent to it in the same general direction up or down that can be interpreted either as correlation or causation, This is important in all fields , meaning that just because two things are happening and going in the same direction , or trend , they are correlated, but it’s does not mean one is causing the other , this is critical to understand , as a sidenote we have made this mistake in history and science many times.


Of course this is another reason to base your science on standardized verified , human curated, information not just raw data ,or data, manipulated by algorithms to make them, conform to a model usable by AI. As you see from the diagram , including melting ice cream, it’s not the cause of a sunburn it is simply correlated.




Ira

AI Splainer for regular people or clarity

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I’m going to give you my perspective of understanding how AI works

I would like to offer my understanding of how AI works with my experience in BI and a lot of researchi.

First, in my opinion this AI consist of these important areas of the logical real world areas

Statistics

Algorithms

Patterns

Data.

Predictions

Semantics

First, this is meant to be at the normal person level. Of course they’re my opinions. I will go into technical detail later.

It is important to understand the difference between our intelligence and artificial intelligence, mainly artificial intelligence consist of memorization, patterns in huge amounts of data and calculations. The result, it is important to remember that you as a human have a ability to override your thoughts or predictions, it’s good sometimes that.also, as a human, sometimes you have that intuition? Many times this would be in conflict of what artificial intelligence would tell you. i’m not making a judgment I’m just observing

Artificial intelligence, I will point out is no better than human intelligence . In fact, AI is modeled on human intellgence

AI is faster, it can consume, vastly more data quickly, and you can correlate, that does not make it better. It’s just different. It is useful and faster

I would like to help compare and contrast for many of you, what we have done over the years and where we are now I believe there’s to many synonyms saying the same information and rather then a simple comparison and relationship, as well as many mathematical concepts, and even that many of these have existed for a while and that are being called by different names. It’s not new or different. Mathematics is still the center and it’s always been there., this is to clear things up, you may know more about how this things work then you realize

Oneiof the basic parallels or similarities is in BI, we focused on Files, tables, dimensions and of course fields pand metric and KPI’s. Surprisingly, it is very similar in artificial intelligence, and the focus on on algorithms,, and features which many derived from fields and dimensions which many are also derived from data fields, statistics or other things again, I’d like to point out that there is a correlation and a relationship of featured

It is important to realize previously because of technology constraints. , we would focus on these correlations and relationships to be hard wired any coded in physical files in artificial intelligence. Currently, we can perform this kind of relationship discovery, and correlations and memory encoding differently, but it’s still the same conceptionally., obviously, this can be done on a greater scale and quicker

This is just one of many correlations I will be pointing out. Thank you.

AI Beneath the covers!

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Artificial intelligence as has four basic subject areas. They are as follows:

Statistics or, features

Linear algebra

Calculus

Probability

I would like to focus on statistics or AI eatures.

Information including statistics are derived from data ,data is real potential. It’s not calculated or surprised that will come later. And it most probably reflects some type of transaction

Information which is derived from data, can be standardized by reference data, or calculated of cours,e

Features can also be transformed, standardized and, consist of calculated information and be in many cases, change from its raw form

Then, of course we have to consider the algorithm you may choose to predict or especially recently todays generative content

It is also worth considering that in the early AI days much data concerns came from structured , sources, tables, or dimensions and columns, or as a attributes this data, what is the model and kept in and RDBMS recently we are able to process mature what we would call a structured data. This presents both great opportunity, and a greater chance for not understanding the context of the data.

My main conclusion is that you have to be careful that you consume data or feed it to your AI with a forensically traceable and verifiable source. In other words, he a chain of custody as you would in the real world. You cannot just take a prediction and not understand how it was. Arrived at. Like in the real world, there’s a difference between a guess and a well thought out prediction

Something you may want to know before you go that way , We have yet learned how our judgment works. Apparently, it’s a mixture of learned knowledge, experiences in human intelligence