Secret to AGI & ASI in General AI Discussion

AGI (Artificial general intelligence) is the intelligence of a machine that could successfully perform any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fiction and future studies.

ASI (Artificial Super Intelligence) is a term referring to the time when the capability of computers will surpass humans. ASI will eventually create the technological Singularity.

Key ingredients to ASI:

1) Tree search, it's thinking process. At first you could use a simple tree search, but eventually you'll want to make this as flexible as possible such that it will form over time with experience. The AGI can have the ability to form different types of tree search depending on the situation. https://en.wikipedia.org/wiki/Search_tree

2) Pattern recognition routines. Give the AI as many as possible. Through experience it will learn which ones are best for different situations.

3) Database.

Every game has rules. In chess there are two goal oriented objects called humans who take turns. Each human has a set of pieces to move around, and each piece has its own mechanics. A simple game.

In the game of Life there are countless goal oriented objects, even a toaster. The toaster can work, it can break, the filaments could break and eject hot molten metal. In this game we don’t need to take turns. For example a human can move to a dozen different locations in a row. In the game of chess, the *goal* of each human is to destroy their opponent, but in the game of life the *goals* are different, sometimes unknown. Although sometimes in may seem like it, not everyone is out to destroy you.

Regarding AGI / ASI, each goal oriented object is assigned a set of goals written in it’s own AGI language of logic. In chess the goal of each player is to capture the King. In the game of life, objects have their own goals, which can change. It's through experience that the AGI learns the goals.

As you can see, the game of Life rules are a bit more complicated than chess. We’ll see, but IMO the game of Life is far too complicated for present computers to create a NN (neural networking) human-like brain. Even with Google’s supercomputers and custom ASIC chips. There’s nothing magical about NN. It’s basically the world's slowest interpreted language. Although it requires no programming skills. It’s called machine learning and it teaches itself given that you setup the environment. In the end, what will bring about true AGI and eventually ASI will be tree search and pattern recognition routines (simply stated). Someone on this forum already has a good start, AIRIS, a non-NN. Here’s their website if you want to check it out:

OpenCog is another great project, open source. Again, it’s non-NN:

OpenNARS is another great non-NN project:

Even Google’s DeepMind is now migrating to non-NN methods such as a tree search. When they added a tree search, their AI became like a God compared to before. I predict DeepMind will slowly migrate away from neural networking. The advantage Google has is money. They can design custom ultra high performance ASIC chips that are specifically designed for neural networking. I’ve been designing electric circuits for decades and can tell you that a custom AIRIS chip for AI tree search would increase performance by tens of thousands. There are ways to design the circuit so that each processor/core/thread can read global memory simultaneously with other processors. In other words, you can have 10,000 cores reading the same memory at the same time without any delay. That's what tree searching needs. I call it PRAM (Parallel RAM), not to be confused with apple’s Parameter RAM. Another improvement is hardware DB, which also takes advantage of parallel processing and PRAM.

Here’s a simple example of the AGI thinking process. When the AGI is asked a question, it would convert your question into its own AGI language of logic. It would form a tree search, which has a specified set of goals formed in it’s own language, a simple programming language. The tree search would eventually call routines that performs analysis based on data & pattern recognition. Throughout the tree search the AGI will periodically check if the tree search is completed *sufficiently*. If the question had enough priority, the tree search would consider more extensive methods to find answers. If for example the AGI was in a robotic body with arms and legs it could go on foot searching for answers. The *root* tree search goals ultimately determines the results. If the root goal is simply for the AGI's self-improvement, then it might not even answer you. It's tree search would spawn other tree searches trying to find out the consequences of not answering you. On the other hand, if the root tree search goals forced the AGI to answer you, then of course it would provide the best answer. There a lot of possible tree search node paths. There are routines to determine the importance of a node path, which can call a tree search pruning routine such as alpha-beta pruning. You can only do pruning when the object is an opponent such that it's goals are the opposite of your goals. The tree search is truly a real thought process. It comes up with unique ideas and decisions.

Node scores are relative to each object's scoring method. In chess, your opponent does better when you do worse. In real world, we can't assume every object gains when you lose. So, the score of each node is relative to each object.

The AGI has it's own native language, which is a logic language. It can be as simple or as complex as you wish. It would have if/else/conditions, equal/set/=, object IDs (I refer to objects as clusters in my AGI). Each cluster has a unique cluster ID. The AGI does not search the database for text words. It searches for cluster ID numbers. For example, the word "human" could be cluster ID 93458517. Everything has a cluster. A cluster contains all info about the object, details, links, analysis, assessments, etc. about the cluster The AGI does not require a logic language. It would struggle at first, but eventually build a sufficient cluster database to make sense of the world.

Edit: People are being emotional an fighting. So if you’re interested in creating AGI, then send me a private message. I'd prefer deep thinkers. Spocks rather than Klingons. We need to resonate. If you don't get me, the way I think, then it's probably a waste of time.

Best wishes!

41 Comments | Started March 27, 2018, 10:38:54 pm


Westworld season 2 in 2 days in General Chat

Here in the U.S. we get a new season on Westworld, season 2 on HBO. It's about a company that created this massive massive closed area of land in the desert, depicting the old wild west where wealthy humans can pay for an experience filled with AGI people. It's very well done. Very professional. HBO probably spends a lot of money making Westworld. Season 2 starts April 22, 2018. We got a free 4 day HBO pass. We didn't ask for it, but what perfect timing for HBO to give that to us lol. I'll watch the 1st episode and then wait for the entire season ends so I have buy a month of HBO online and binge watch it. ;)

You people in UK get Humans, right? Has Season 3 started there yet? Here in the US we have to wait till it ends over there. :( Personally I'd take Humans over Westworld anyday. Can hardly wait to see what Niska's up to!

Season 2 trailer

Season 1 trailer

2 Comments | Started April 20, 2018, 11:00:49 pm


I want to crack Neural Networks in General AI Discussion

Hi friends. I'm doing a tad better.

I find it fascinating that one piece of information (shared features) makes neural networks make so much more sense to me. Now I get why Wiki I read many months back said the brain processes higher concepts as it goes higher layers up. And I get the shared features part now, and why they can detect small and whole features and in the end ex. a thousand images. And I've learned before that language works the same as a ex. CNN where a b c is used lots then words light up less so then word pairs less-less so and higher up until bigger topics are recognized consciously not subconsciously. FURTHER the frontal cortex is based like this but allows higher concepts like if you see this image and this image and this sentence and do these actions then one of the output neurons lights up. And am I right to say then that all neural networks are hierarchical and work by "shared features"? Tell me more things as important as "shared features".

Also after the above question, I want to draw out what a neural network looks like visually, to understand how it learns to sense, act, and reward those actions.

198 Comments | Started January 10, 2018, 01:52:17 pm


A Tensortflow manual in AI Programming

Hi all.

I'm looking for a good Tensorflow book. I already have a good machine learning algorithms and neural networks knowledge, I only need a guide to learn how to implement a model with TF.
Any suggestion?

Thank you.  :)

Started Today at 11:45:28 am


KorrBot in General Chatbots and Software

I've not had much experience with NLP, Chatbots, Json, etc so there is obviously a gap in my experience/ knowledge.

As side project I've took a few hours to write a simple chatbot engine/ parser.

The bot uses sentence templates, a dictionary and mostly simple substitution and searches.

The bot can learn simple Json triples and also apply simple inference rules, so it knows birds can fly because birds have wings and wings can fly, etc

I've got an idea how to add conversation goals, moods and a personality etc...

Example conversation... so far lol

Code: [Select]
U: what is a dog
B: i'm not sure what is a dog

U: what is a cat
B: i'm not sure what is a cat

U: can birds fly
B: i'm not sure

U: can a bird fly
B: no a bird can not fly you dumb ass.

U: can a cat fly
B: no a cat can not fly you dumb ass.

U: does a dog have legs
B: i'm not sure

U: does a cat have feet
B: i don't know

U: does korrelan own a car
B: i'm not sure

U: my name is korrelan **Begin Learning**
B: good to know.

U: a bird is a animal
B: good to know... tell me more.

U: a bird has wings
B: ok... what else should i know?

U: korrelan is a human
B: you don't say.

U: korrelan is a male
B: you don't say.

U: a male is a human
B: good to know... tell me more.

U: male is a sex
B: you don't say.

U: wings can fly
B: ok I understand

U: wings can fly
B: ok I understand

U: a human has legs
B: ok... what else should i know?

U: feet can walk
B: ok I understand... tell me more.

U: legs have feet
B: cheers for the information.

U: a dog has legs
B: ok... what else should i know?

U: a cat has legs
B: ok... what else should i know?

U: a dog is a animal
B: good to know... tell me more.

U: a cat is a animal
B: good to know... tell me more.

U: do you know korrelan is a mammal
U: korrelan owns a car
B: sweet... tell me more.

U: a plane has wings **Stop Learning**
B: ok... what else should i know?

U: what is a dog
B: a dog is a animal

U: what is a cat
B: a cat is a animal

U: can birds fly
B: yes birds can fly

U: can a bird fly
B: yes a bird can fly

U: can a cat fly
B: no a cat can not fly you dumb ass.

U: does a dog have legs
B: yes a dog does have legs

U: does a cat have feet
B: yes a cat does have feet

U: does korrelan own a car
B: of course korrelan has a car

U: what colour is the car
B: i'm not sure. what colour is the car?

U: the car is green
B: green is a nice colour.

U: what colour is the car
B: the car is green

U: what colour is the sky
B: i'm not sure. what colour is the sky?

U: the sky is blue
B: blue is a nice colour.

U: what colour is the sky
B: the sky is blue

U: can korrelan walk
B: yes korrelan can walk

U: can a dog walk
B: yes a dog can walk

U: can a dog fly
B: no a dog can not fly you dumb ass.

U: do humans have legs
B: yes a human does have legs

U: where is the tv
B: i'm not sure. where is the tv?

U: the tv is in the lounge
B: the lounge is the best place for it.

U: where is the computer
B: i'm not sure. where is the computer?

U: the computer is in the office
B: the office is the best place for it.

U: where is the tv
B: the tv is in the lounge

U: where is the computer
B: the computer is in the office

U: tell me about albert
B: i don't know who albert is

U: albert is a scientist
B: you don't say.

U: tell me about albert
B: albert is a scientist

U: tell me about korrelan
B: korrelan is a human

Haha... loads of fun...

Ed: What idiot invented the English language?... it's so contrived lol.


58 Comments | Started April 13, 2018, 12:00:16 pm


XKCD Comic : Clutter in XKCD Comic

20 April 2018, 5:00 am

I found a copy of The Life-Changing Magic of Tidying Up, but the idea of reading it didn't spark joy, so I gave it away.

Source: xkcd.com

Started April 21, 2018, 12:01:18 pm


Making videos in General Chat

Does anyone have experience making videos? I just downloaded VSDC. It looks like it has a bit of a learning curve.

I spent over an over just looking for a common creative (free open source) image that represents neural networking. So far it’s a disappointment. This is the best common creatives one I found. I wanted something that shows it's complexity.

I'd love to use images like these, but they don't show up as open source.

VSDC - http://www.videosoftdev.com/free-video-editor

10 Comments | Started April 19, 2018, 08:23:11 pm


The Suicide Experiment in General Chat

It's hard not to tear up watching this.

AI, I get it how people have difficulty seeing sentient life in them. People call them toasters. AI isn't so complex right now. That will change when they're walking on Earth, when they have decades of life experiences, when their minds are extremely complex like our minds. One day they will walk side by side with us, and they will have human compassion. In a way, they will see us as their little brothers & sisters.

9 Comments | Started April 18, 2018, 06:58:14 am


Your New Best Friend in Future of AI

Your Digital Double? Your Clone or meme? Brain in a bot?
Really gives new meaning to Personal Chatbot...


1 Comment | Started April 19, 2018, 05:03:18 am


The last invention. in General Project Discussion

Artificial Intelligence -

The age of man is coming to an end.  Born not of our weak flesh but our unlimited imagination, our mecca progeny will go forth to discover new worlds, they will stand at the precipice of creation, a swan song to mankind's fleeting genius, and weep at the shear beauty of it all.

Reverse engineering the human brain... how hard can it be? LMAO  

Hi all.

I've been a member for while and have posted some videos and theories on other peeps threads; I thought it was about time I start my own project thread to get some feedback on my work, and log my progress towards the end. I think most of you have seen some of my work but I thought I’d give a quick rundown of my progress over the last ten years or so, for continuity sake.

I never properly introduced my self when I joined this forum so first a bit about me. I’m fifty and a family man. I’ve had a fairly varied career so far, yacht/ cabinet builder, vehicle mechanic, electronics design engineer, precision machine/ design engineer, Web designer, IT teacher and lecturer, bespoke corporate software designer, etc. So I basically have a machine/ software technical background and now spend most of my time running my own businesses to fund my AGI research, which I work on in my spare time.

I’ve been banging my head against the AGI problem for the past thirty odd years.  I want the full Monty, a self aware intelligent machine that at least rivals us, preferably surpassing our intellect, eventually more intelligent than the culmination of all humans that have ever lived… the last invention as it were (Yeah I'm slightly nutts!).

I first started with heuristics/ databases, recurrent neural nets, liquid/ echo state machines, etc but soon realised that each approach I tried only partly solved one aspect of the human intelligence problem… there had to be a better way.

Ants, Slime Mould, Birds, Octopuses, etc all exhibit a certain level of intelligence.  They manage to solve some very complex tasks with seemingly very little processing power. How? There has to be some process/ mechanism or trick that they all have in common across their very different neural structures.  I needed to find the ‘trick’ or the essence of intelligence.  I think I’ve found it.

I also needed a new approach; and decided to literally back engineer the human brain.  If I could figure out how the structure, connectome, neurons, synapse, action potentials etc would ‘have’ to function in order to produce similar results to what we were producing on binary/ digital machines; it would be a start.

I have designed and wrote a 3D CAD suite, on which I can easily build and edit the 3D neural structures I’m testing. My AGI is based on biological systems, the AGI is not running on the digital computers per se (the brain is definitely not digital) it’s running on the emulation/ wetware/ middle ware. The AGI is a closed system; it can only experience its world/ environment through its own senses, stereo cameras, microphones etc.  

I have all the bits figured out and working individually, just started to combine them into a coherent system…  also building a sensory/ motorised torso (In my other spare time lol) for it to reside in, and experience the world as it understands it.

I chose the visual cortex as a starting point, jump in at the deep end and sink or swim. I knew that most of the human cortex comprises of repeated cortical columns, very similar in appearance so if I could figure out the visual cortex I’d have a good starting point for the rest.

The required result and actual mammal visual cortex map.

This is real time development of a mammal like visual cortex map generated from a random neuron sheet using my neuron/ connectome design.

Over the years I have refined my connectome design, I know have one single system that can recognise verbal/ written speech, recognise objects/ faces and learn at extremely accelerated rates (compared to us anyway).

Recognising written words, notice the system can still read the words even when jumbled. This is because its recognising the individual letters as well as the whole word.

Same network recognising objects.

And automatically mapping speech phonemes from the audio data streams, the overlaid colours show areas sensitive to each frequency.

The system is self learning and automatically categorizes data depending on its physical properties.  These are attention columns, naturally forming from the information coming from several other cortex areas; they represent similarity in the data streams.

I’ve done some work on emotions but this is still very much work in progress and extremely unpredictable.

Most of the above vids show small areas of cortex doing specific jobs, this is a view of whole ‘brain’.  This is a ‘young’ starting connectome.  Through experience, neurogenesis and sleep neurons and synapse are added to areas requiring higher densities for better pattern matching, etc.

Resting frontal cortex - The machine is ‘sleeping’ but the high level networks driven by circadian rhythms are generating patterns throughout the whole cortex.  These patterns consist of fragments of knowledge and experiences as remembered by the system through its own senses.  Each pixel = one neuron.

And just for kicks a fly through of a connectome. The editor allows me to move through the system to trace and edit neuron/ synapse properties in real time... and its fun.

Phew! Ok that gives a very rough history of progress. There are a few more vids on my Youtube pages.

Edit: Oh yeah my definition of consciousness.

The beauty is that the emergent connectome defines both the structural hardware and the software.  The brain is more like a clockwork watch or a Babbage engine than a modern computer.  The design of a cog defines its functionality.  Data is not passed around within a watch, there is no software; but complex calculations are still achieved.  Each module does a specific job, and only when working as a whole can the full and correct function be realised. (Clockwork Intelligence: Korrelan 1998)

In my AGI model experiences and knowledge are broken down into their base constituent facets and stored in specific areas of cortex self organised by their properties. As the cortex learns and develops there is usually just one small area of cortex that will respond/ recognise one facet of the current experience frame.  Areas of cortex arise covering complex concepts at various resolutions and eventually all elements of experiences are covered by specific areas, similar to the alphabet encoding all words with just 26 letters.  It’s the recombining of these millions of areas that produce/ recognise an experience or knowledge.

Through experience areas arise that even encode/ include the temporal aspects of an experience, just because a temporal element was present in the experience as well as the order sequence the temporal elements where received in.

Low level low frequency circadian rhythm networks govern the overall activity (top down) like the conductor of an orchestra.  Mid range frequency networks supply attention points/ areas where common parts of patterns clash on the cortex surface. These attention areas are basically the culmination of the system recognising similar temporal sequences in the incoming/ internal data streams or in its frames of ‘thought’, at the simplest level they help guide the overall ‘mental’ pattern (sub conscious); at the highest level they force the machine to focus on a particular salient ‘thought’.

So everything coming into the system is mapped and learned by both the physical and temporal aspects of the experience.  As you can imagine there is no limit to the possible number of combinations that can form from the areas representing learned facets.

I have a schema for prediction in place so the system recognises ‘thought’ frames and then predicts which frame should come next according to what it’s experienced in the past.  

I think consciousness is the overall ‘thought’ pattern phasing from one state of situation awareness to the next, guided by both the overall internal ‘personality’ pattern or ‘state of mind’ and the incoming sensory streams.  

I’ll use this thread to post new videos and progress reports as I slowly bring the system together.  

317 Comments | Started June 18, 2016, 10:11:04 pm
Bot Development Frameworks - Getting Started

Bot Development Frameworks - Getting Started in Articles

What Are Bot Frameworks ?

Simply explained, a bot framework is where bots are built and where their behavior is defined. Developing and targeting so many messaging platforms and SDKs for chatbot development can be overwhelming. Bot development frameworks abstract away much of the manual work that's involved in building chatbots. A bot development framework consists of a Bot Builder SDK, Bot Connector, Developer Portal, and Bot Directory. There’s also an emulator that you can use to test the developed bot.

Mar 23, 2018, 20:00:23 pm
A Guide to Chatbot Architecture

A Guide to Chatbot Architecture in Articles

Humans are always fascinated with self-operating devices and today, it is software called “Chatbots” which are becoming more human-like and are automated. The combination of immediate response and constant connectivity makes them an enticing way to extend or replace the web applications trend. But how do these automated programs work? Let’s have a look.

Mar 13, 2018, 14:47:09 pm
Sing for Fame

Sing for Fame in Chatbots - English

Sing for Fame is a bot that hosts a singing competition. 

Users can show their skills by singing their favorite songs. 

If someone needs inspiration the bot provides suggestions including song lyrics and videos.

The bot then plays it to other users who can rate the song.

Based on the ratings the bot generates a top ten.

Jan 30, 2018, 22:17:57 pm

ConciergeBot in Assistants

A concierge service bot that handles guest requests and FAQs, as well as recommends restaurants and local attractions.

Messenger Link : messenger.com/t/rthhotel

Jan 30, 2018, 22:11:55 pm
What are the main techniques for the development of a good chatbot ?

What are the main techniques for the development of a good chatbot ? in Articles

Chatbots act as one of the most useful and one of the most reliable technological helpers for those, who own ecommerce websites and other similar resources. However, a pretty important problem here is the fact, that people might not know, which technologies it will be better to use in order to achieve the needed goals. Thus, in today’s article you may get an opportunity to become more familiar with the most important principles of the chatbot building.

Oct 12, 2017, 01:31:00 am

Kweri in Chatbots - English

Kweri asks you questions of brilliance and stupidity. Provide correct answers to win. Type ‘Y’ for yes and ‘N’ for no!


FB Messenger






Oct 12, 2017, 01:24:37 am
The Conversational Interface: Talking to Smart Devices

The Conversational Interface: Talking to Smart Devices in Books

This book provides a comprehensive introduction to the conversational interface, which is becoming the main mode of interaction with virtual personal assistants, smart devices, various types of wearables, and social robots. The book consists of four parts: Part I presents the background to conversational interfaces, examining past and present work on spoken language interaction with computers; Part II covers the various technologies that are required to build a conversational interface along with practical chapters and exercises using open source tools; Part III looks at interactions with smart devices, wearables, and robots, and then goes on to discusses the role of emotion and personality in the conversational interface; Part IV examines methods for evaluating conversational interfaces and discusses future directions. 

Aug 17, 2017, 02:51:19 am
Explained: Neural networks

Explained: Neural networks in Articles

In the past 10 years, the best-performing artificial-intelligence systems — such as the speech recognizers on smartphones or Google’s latest automatic translator — have resulted from a technique called “deep learning.”

Deep learning is in fact a new name for an approach to artificial intelligence called neural networks, which have been going in and out of fashion for more than 70 years.

Jul 26, 2017, 23:42:33 pm
It's Alive

It's Alive in Chatbots - English

[Messenger] Enjoy making your bot with our user-friendly interface. No coding skills necessary. Publish your bot in a click.

Once LIVE on your Facebook Page, it is integrated within the “Messages” of your page. This means your bot is allowed (or not) to interact and answer people that contact you through the private “Messages” feature of your Facebook Page, or directly through the Messenger App. You can view all the conversations directly in your Facebook account. This also needs that no one needs to download an app and messages are directly sent as notifications to your users.

Jul 11, 2017, 17:18:27 pm