My Blog 08-December 2018
This blog will change over time and hold
I am currently not working that
much with picture recognition, I have been spending my time writing software
that analyses information.
What is interesting is that I have
been using Artificial Technology to achieve this to date. What is
interesting unlike these huge systems that Google and others are using to
create such systems on huge networks my software runs on a simple laptop
1) What does it do?
Quite a lot actually but just to
name one thing I found interesting is the identification of nouns, verbs,
pronouns, adjectives , adverbs, etc. What the software does is given
any text it just works out what parts are nouns, adjectives or verbs etc.
It continues to create lists of nouns, verbs, adjectives, pronouns. adverbs
etc. Some would call this thinking, actually what I find interesting myself
is that it does this much better than I can do it. Its accuracy levels seems
to be about 100% and if for any reason it is uncertain which is not that
often it will ask me what category that word belongs to. Most of the
time I check against a dictionary or Google just to check that what I think
I have now linked this to others who have POS big
systems, to confirm my results. This is even more interesting because
I am networking different systems together. Two narrow POS system, I
have found give 100% confirmed accuracy. This is with two POS systems.
Average humans would I guess get about 40 to 60 percent accuracy. I
say 100% because all the words I have checked using Google search or
dictionaries have been correct it maybe that it is only say 99 percent
accuracy with two competing POS systems put just say you add a third or
fourth then I would think it would get it right 100% without any
argument or doubt. But unless I find some words in the wrong category,
I have to conclude its currently about 100% accurate.
2) Is this
system more intelligent that a human
Yes again its artificial
intelligence therefore like a calculator does math better than humans now
A.I can identify nouns, verbs adjectives, definitions etc. much better
than a human.
3) Do you need big neural networks to achieve
Actually surprisingly NO, you can do this all on a laptop with
the software I have developed.
4) Is your software in the public
No, its not for sale or in the public domain and I have no
intension of putting it in the public domain currently.
5) Why not
put it in the public domain
The software is very powerful indeed,
mainly because it does not need large networks of GPUs or CPUs . I am
amazed at what the software can do. The truth is I do not know what I
will end up doing with the software.
6) Why does it not need
large amounts of GPUs or CPUs to run the software
Its because its
been designed to work more like a human being, its does not need huge
amounts of training data that needs huge amounts of processing power.
It uses traditional computing techniques to create a system that works using
information that a human would hold.
7) Does it use a neural network?
No, it does not use a neural network, let me say neural networks are
great for things like picture recognition, not I think so good for this type
of application, its needs a more human approach, which I have called the
Yes, No network.
8) So how does it work?
It works like humans
work if you think of a Car, you think about associated things. It is
that simple it just thinks like a normal human thinks.
it difficult to program?
Yes, I think of it as an Artificial
Intelligent Engine. Its taken a very long time to program the engine
and I would be the first to admit that its been quite a challenge.
Most difficult was performance improvements. It can still get better
parallel streams maybe help improve speed on new multi core laptops. I
am currently using a old laptop that is not very fast.
language was it programmed in?
I used Java for one simple reason I
wanted the code to be portable and if necessary scalable. I
wanted to be able to run it on Windows, Linux or any other platform that
Java can run on using virtual machine technology.
11) What do I
currently us it for
I use it for legal research purposes mainly
because my two main interests are law and computing.
12) What is it
good at doing?
Its good at finding information given a abstract
question. It uses two approaches one is key word search that seems
very traditional but within A.I it find best results. For example if you
have million pages of data with the word car in it you want it to find the
appropriate car not just list a thousand links to the word car. But
also it goes further it actually uses inference like a human can do. So it
will also return information relating to the initial search you gave it with
no key words but that maybe still appropriate for your search.
13) Why does it need to use inference?
It uses inference
because in law and other things you may not know the correct question or key
words to give the system. Therefore over time the Artificial
Intelligence within the system I have written uses inference to help get the
14) Is inference hard without big data?
The amount of data I use to create inference is very small, humans do not
use billions of lines of information to create inference what they do is use
targeted small amounts of linked data to create inference. This is
what my system is attempting do achieve.
15) What do you
like about your A.I Engine or System?
I like just watching it learn,
its just amazing how it works out things and how it produces results.
I just love that its like a human learning a little bit about the English
language every day.
16) Why are such systems
Its important because for example there is just two much
law out there. I am astonished that it finds new law that I have never
heard about before or did not know that it even existed. It helped me
find related law going back to the 1800's I did not know related to current
law and cases that I would have never known existed. It also points me
in legal directions I would not have ever considered or thought could be
relevant to a legal position. It reminds me of the latest Chess
computers that seem to give insight into new ways of playing chess.
Its a little like this in my view when thinking about law, it enhances your
knowledge base and makes you aware of different arguments.
The idea that someone playing chess on his own is
always going to be beaten by someone who plays chess and uses a good chess
computer. Therefore my knowledge is Ok but given my knowledge and a
good A.I System combined is going to produce better results just about
every time, even if my thoughts and the AI's thoughts are different or the
same. This can often lead to new outcomes. AI helping humans,
intellectually or otherwise should always produce better results and that
has been my experience at first hand programming an A.I. Engine.
For those who are interested in its ability to learn I watched the increase
Zero means no data taken.
line is left to right but no time taken
This is a snap shot in a
relatively short time frame
Notice that there are more then less then
more this is down to that it is learning and if it realizes that for example
a noun is not a noun but an adjective it gets removed.
words, only when words are confirmed by the system that they are an actual
category they are then considered perminant.
Permanent words with memory
dislodge will be allowed in the future with a type of negative data
re-enforcement to be implemented in the future.
Lets take Nouns we
had less accurate data at 4213 about 70% but this turned to 99.99% or 100
example accuracy at 4104 with none wrong to date found. If found could
reduce to 99%.
Importantly very little mathematical modeling is required
for the Yes No system to work well. We humans do not use calculation
to recall memory or put another way we to say pos 3 * pos 4 * layer 8 I
store the thought there. We just store it, we do not have to calculate
where. Also limits to any architecture are limits to the low
level materials used.
Nouns = 4176 = 4213 =
4214 = 4220 = 4222 = 4208 = 4241 = 3914 = 3995 = 4104
Verbs = 0
= 1273 = 1282 = 1285 = 1287 = 1289 = 1299 = 1021 = 0 = 1159
Adjective = 0
= 695 = 771 = 721 = 724 = 727 = 766 = 954 = 0 = 992
Adverb = 0
= 0 = 693 = 667 = 668 = 673 = 706 = 676 = 0 = 685
Conjunction = 0
= 111 = 114 = 115 = 115 = 115 = 118 = 138 = 0 = 149
Pronouns = 0
= 36 = 36 = 36 = 36 = 36 = 38 = 40 = 0 = 50
Definition = 0
= 21 = 23 = 23 = 23 = 23 = 23 = 22 = 0 =
Names = 407
= 509 = 509 = 514 = 537 = 537 = 52 = 0 = 590
Interjection = 0
= 0 = 78 = 78 = 93 = 89 = 91 = 0 = 99