Thoughts on Artificial Intelligence

The computer science field of Artificial Intelligence has sparked a lot of interest yet hasn't really turned up many visible products. There are a lot of projects out there and I don't want to even attempt to minimize the amount of effort that has been spent on AI research, but by and large there aren't many visible "AI" companies or tools that we use regularly.

A large part of that has to do with the confusion of what AI is? What does artificial "intelligence" mean? I know about programming language research. The goal there is to create expressive, productive programming languages. Systems research centers around operating systems, distributed systems, fault tolerance and other similar areas. But AI could mean different things to different people.

Change the Vocabulary


My suggestion is to do away with the term AI all together. It is not useful, even at a high-level. Modern software is pretty "intelligent". That is the goal of most software. We humans need a way to communicate with software in order to tell the software to do something. The software will respond with a set of terminology or actions that we understand. A lot of software is good at that. If I tell google to give me information on cars Google will return a set of listings on cars. I don't know the internal details, how it came up with the information. All I do know, I am normally happy with the results. The back and forth conversation with google was a positive one. Google is an AI. Microsoft windows/Ubuntu Linux are forms of AI? The seem pretty intelligent to me.

So the term AI doesn't mean a whole lot. Or at the very least, it is a misnomer. I am not totally set of this term, but it seems to fit for the time-being. "evolved, adaptive artificial systems". That is what we are looking for. Systems that have evolved past the "dumb" systems that we are normally used to. Outside of google, most applications are built with every action, feature is known. If a piece of software does something that we don't expect, we call that a bug. An evolved system is one that is adaptive to its inputs. You may not get the same output if given a known input. The term evolved is less meaningful than adaptive. In 100 years, the software will have evolved past what it is today. I want to use the term because of the connection with typical usage of evolution. A dumb amoeba is the basis of all life. Man is the result of millions of years of evolution. The software of tomorrow will evolve past the software of today.

The question is, what determines that evolution? What will google look like in 100-200 years. What processes will encourage evolution. Does open source encourage? Does the addition of AI technology encourage it. Will the future evolved software thrive on autonomous, fault tolerant operations?

Comments

Post a Comment

Popular posts from this blog

Is Java the new COBOL? Yes. What does that mean, exactly? (Part 1)

Image
"If you want to know the past, look at your present. If you want to know the future, look at your present." -- Gautama Buddha Java is the new COBOL, whaaaat?     If you are software developer that mainly writes applications for the web; even if you aren't a Java/J2EE developer, you have probably heard the new meme circulating the web and blogosphere. "Java is the new COBOL" . Most blogs and technical writers regurgitate that statement and follow-up by saying that EJBs suck, and some companies are considering Ruby on Rails. I didn't really think much of these posts. I get the impression that a lot of these "managers" don't write any Java or COBOL code. They are really not highlighting the seriousness of the problem. COBOL development has remained stagnant for decades. Java may see the same problem in the future. The Pentagon/DOD has a trillion dollar COBOL problem because it is so difficult to change their ancient infrastructure. Anyon
Read more

On Unit Testing, Java TDD for developers to write

It has been a while, let's kick off 2017 with a blog entry. I have read and I am reading about four or five posts a day about unit testing. It really has been a long time obsession for me. I have moved past the technical and practical considerations on unit testing frameworks and done with the debates with "should you use Junit or Mockito or Karma?" I am more interested in the psychology of unit testing, who does it, likes it, hates it? It really is one of those easy to learn, hard to master concepts. For example, many many may play chess when they are young and can end up being horribly chess players most of their life, I am part of that majority. Unfortunately, I have never played chess and sat down for hours and tried to master it. I never see the common patterns or have a developed end game. I mostly just play with a knowledge of the basic rules. Following good unit testing practices within your software development shop is a lot like playing chess. It is easy to le
Read more

JVM Notebook: Basic Clojure, Java and JVM Language performance

Image
"Measure, don't guess. The primary goal of all performance tuning exercises should be maximize the end user experience given the resource constraints." [1] "It isn't so much a "farewell to the J" as an expansion of the platform opportunities Java provides. Sun's investment to power ongoing development of JRuby and Jython broadens the range and reach of Java, as a whole." -- Rick Ross Overview and JVM Languages    One of the exciting trends to recently emerge from the Java community is the concept of the JVM language. These technologies are all that you would expect them to be. They are implementations of languages that run on the Java Virtual Machine. Some are newly created and some are based on existing, more mature languages. JRuby, Jython are two JVM languages based on CRuby and CPython. Groovy, Scala, Clojure are three completely new JVM languages that were created to add new language features that weren't supported by the core Ja
Read more