Everything is made from scratch. From the ground-up. I could have used AIML (the AI version of XML), or anything I wanted. But instead, to make it unique and customizable to the demand of this project, I created my own markup language entitled ACUMANSCRIPT. Even the sentiment analysis algorithms are made from scratch by using Naive Bayens algorithms. The only APIs in use are those for some aspects of the knowledge base, which is a must in any machine learning or artificial intelligence project, as not leveraging the massive amount of data available on the internet would be a waste.
I sincerely doubt that we are anywhere near a flawless piece of artificial intelligence software, but this is not a result of people's lack of diligence in the field, but rather a testimony to it's complexities.
Google has made a short documentary explaining why natural language processing and machine learning are some of the hardest fields due to their surprisingly complex nature:
... doubt that we are anywhere near a flawless piece
of artificial intelligence software, but this is not
a result of people's lack of diligence in the field,
but rather a testimony to its complexities.
... a quick glance at the "read more" page on the
technologies ...
Here is the URL: http://acuman.us/readmore.php
I decided that AIML was not useful to me because it was too rigid in syntax and was too static. This is particularly in the manner in which most AIML interpreters parse the syntax, making a rigid "if hello is in string, then say nice meeting you" syllogism (basically a beefed-up conditional statement) that essential has no room or place in actual artificial intelligence. I could have adjusted it to match my needs by creating my own interpreter, but I thought if I was going to accomplish that, why not create my own syntax that matches my needs better and has syntax that is even less convoluted and more focused on pattern-matching and machine learning?
I thought of releasing an API where you can code using the syntax of ACUMANSCRIPT- but I am unfortunately not prepared for open-sourcing ACUMAN's main architecture code due to it still competing in contests and fairs.
My ideas are definitely half-baked and may be completely wrong/useless/inappropriate, or it may even be that you prefer to continue to work largely independently. That's not a bad thing, as getting input from other people may stifle your own creativity and ideas.
Regardless, thanks for the responses and for the interesting project.
Since you wrote the entire thing, you could AGPL it for now and then pick a less restrictive license later.
(could, is, of course, not should, but it's an option people don't always consider)
I do not care about speech recognition when we are talking about AGI.
I care about AGI being able to understand written text - the most natural form of communication between humans and AGI.
The problem is that AGI is not able to understand written text well, cannot build good mental models and cannot make meaningful decisions based on them.
I'd love to see more about how much this is gluing together existing components, and how much is original to the project. Back when I was doing this everything had to be written by hand, from scratch. So much time was spent/wasted in basic, underlying stuff. It's fantastic that people now have so many resources that they don't have to start from so far back, and the inventiveness can shine through.
I'd love to see the inventiveness in this and other projects, but it's hard to see what's really new.