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Aquí vamos de nuevo (1980–1987)

En la década de 1980, las corporaciones de todo el mundo adoptaron con éxito una forma de programa de IA llamada “sistemas expertos”. Para 1986, un sistema experto estaba ahorrando a una compañía $ 40 millones al año estimadamente. …


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Introducción

La inteligencia artificial (IA) necesita principalmente dos cosas para hacer su magia: los datos y la potencia informática. Desde principios del siglo XXI hemos estado acumulando una cantidad asombrosa de datos y definitivamente no estamos desacelerando el ritmo. Según un informe de DOMO, “se crean más de 2.5 quintillones de bytes de datos todos los días, y solo crecerá a partir de ahí. Para 2020, se estima que se crearán 1,7 MB de datos por segundo para cada persona en la tierra ”. Eso es difícil de comprender.

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Con respecto a la potencia informática, la ley de Moore sigue vigente y hemos estado viendo ordenadores más rápidos año tras año. Si agregamos además mejoras algorítmicas, no es de extrañar que la IA haya comenzado a producir excelentes resultados. Un hito importante en el desarrollo de la IA es el triunfo de AlphaGo (un programa de ordenador que juega el juego de mesa Go) que compitió en 2017 contra Ke Jie (que en ese momento ocupó continuamente el ranking mundial №1 durante dos años). …


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La génesis de la inteligencia artificial (1943–1955):

Warren McCulloch y Walter Pitts generalmente reconocen que las primeras semillas de IA se hicieron en 1943. Se les ocurrió un modelo de neuronas artificiales donde cada neurona tiene un estado “encendido” o “apagado” con un cambio a “encendido” en respuesta a la estimulación por un número suficiente de neuronas vecinas.

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Mostraron que cualquier función computable podría ser calculada por alguna red de neuronas conectadas y que todos los conectivos lógicos (y, o, no, etc.) podrían implementarse mediante estructuras de red simples. McCulloch y Pitts también sugirieron que las redes podrían aprender.

En 1949, Donald Hebb demostró una regla de actualización simple para modificar las fuerzas de conexión entre las neuronas. Su regla, ahora llamada aprendizaje hebbiano, sigue siendo un modelo influyente hasta nuestros días. …


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Este artículo fue publicado originalmente en mi blog.

Primero, tomemos cada palabra del término individualmente e intentemos explicarlo. Artificial se refiere a algo hecho por humanos (en contraste con cosas hechas por la naturaleza) y generalmente es una copia de algo natural. Entonces, artificial se trata de humanos tratando de replicar a la Madre Naturaleza.

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¿Qué pasa con el significado de la inteligencia? Bueno, ahí es cuando comienza la diversión. Nos llamamos “Homo Sapiens”, que en latín significa “hombre sabio” y nos enorgullece ser tan inteligentes en comparación con nuestros compañeros del reino animal. Pero, ¿qué significa realmente inteligente? …


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Here we go again (1980–1987)

In the 1980s a form of AI program called “expert systems” was successfully adopted by corporations around the world. …


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The genesis of artificial intelligence (1943–1955):

The first seeds of AI is generally recognized to be done by Warren McCulloch and Walter Pitts in 1943. They came up with a model of artificial neurons where each neuron has an “on” or “off” state with a switch to “on” occurring in response to stimulation by a sufficient number of neighboring neurons.

They showed that any computable function could be computed by some network of connected neurons and that all the logical connectives (and, or, not, etc.) …


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This article was originally published on my blog

First, let’s take each word of the term individually and try to explain it. Artificial refers to something made by humans (in contrast to nature made stuff) and usually is a copy of something natural. So, artificial is about humans trying to replicate Mother Nature.

What about the meaning of intelligence? Well, that’s when the fun begins. We call ourselves “Homo Sapiens”, which in Latin means “wise man” and we like to take pride in being so intelligent in comparison to our fellow peers from the animal kingdom. …


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Last year I’ve decided to get past the artificial intelligence buzzwords from the media articles and really have a clue about the subject.

The more research I made the more I got intrigued and interested in AI. It baffled me how much AI will impact our lives and I realised this is the field I want to be in.

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So, I began searching for learning resources and immersed myself into all kinds of AI related material. …


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Intro

Artificial intelligence (AI) needs mostly two things to work its magic: data and computing power. Since the beginning of the 21st century we’ve been amassing an astonishing amount of data and we definitely we are not slowing down the pace. According to a report from DOMO “over 2.5 quintillion bytes of data are created every single day, and it’s only going to grow from there. By 2020, it’s estimated that 1.7MB of data will be created every second for every person on earth.” That’s really hard to fathom.

Regarding computing power, Moore’s law is still standing and we’ve been seeing faster computers every year. If you add on top of that algorithmic improvements then is no wonder that AI started to yield great results. A significant milestone in the development of AI is the triumph of AlphaGo (a computer program that plays the board game Go) in 2017 against Ke Jie (who at the time continuously held the world №1 ranking for two years). …


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I have wanted to start a business for as long as I can remember. I even learned how to code in order to be able to create an online product because I thought I have more chances of success with an online business rather than an offline one.

Anyway, I had no clue how to start a business, but I knew I wanted to. As the years went by I started to find out how not to do it rather than how to do it as I read more books on the subject, talking to people on forums and listening to lots of podcast on my way home from work. …

About

Alin Rauta

Self-taught web developer.

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