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Mapping the Drosophila Eye

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  T o emulate the Drosophila eye sensory system, I had to map what O mmatidia  to the optical sensory neurons. I used the Flywire.ai right eye map from this map:  Retina Grid . Taking each ommatidia, I first had to map the column id associated to the ommatidia. Here is that map by column id: I was able to create the eye map into a grid that has 28 columns and 28 rows, and put this grid into a MS SQL table: C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26 C27 C28 0 0 0 0 0 0 0 0 787 0 660 207 494 448 476 380 65 295 352 729 41 784 783 0 0 0 0 0 0 0 0 0 0 0 796 788 402 438 322 767 631 138 282 202 186 237 223 343 222 645 8 782 781 0 0 0 0 0 0 0 779 778 629 453 324 570 353 472 621 284 329 680 618 707 625 693 753 744 692 442 7...
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Making Dronesophila Part 1

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       E mulating the Drosophila nervous system was step one which I did successfully on a single laptop using functional groups. This works VERY well.   The functional groups I created were: Neuron Group    Synapse Count central                          1455116 optic_lobes                1217922 visual_projection      268547 AN                                    115292 Kenyon_Cell                92875 ALPN                          88302 CX                                    85831...
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Use Cases for the emulation of the Drosophila nervous system

 I am often asked, especially by VC types, what can you do with animal emulations? What they are really asking is how can this be applied and how can we make money? I will admit, emulating a nervous system is like telling people you are developing a new computer operating system. There are thousands of things you can run on an operating system so asking for the One thing, is analogous to asking what is the one thing you can run on your new OS that stands apart from all others? There is no One thing but thousands of things.  If I emulated a complete human level system, what is the One thing it can do that would exceed all others? The human brain is capable of thousands and thousands of things it can do. I think you get the picture.  The One thing that I have seen with all animal nervous system emulations is generalized intelligence. The one thing that current AI cannot accomplish which is being able to quickly adapt to any given situation and as we climb the evolutionary ...
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How do we use the Connectome for AGI?

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Using the connectome for AGI is the tricky part of the process. Tricky because it does take some thought behind how to associate sensory neurons to real world concepts and how to read the motor output in order to determine the results. To do this we break down the process simply as Sensory Input > Cortical Processing > Motor Output ( > Sensory Processing > Cortical Processing > ...). Sensory Processing Each connectome has a set of sensory neurons. When we create our AGI, we connect weights to the sensory neurons based on how we perceive the sensory input on a particular sensory neuron. As an example, if we want our AGI system to avoid particular situations, we connect that sensory input to sensory neurons that would cause the connectome to sense pain or unpleasant conditions. If we want our AGI system to want or like a particular input, we connect that sensory input to sensory neurons that would cause pleasant conditions in the connectome. Using Robotics makes this p...
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What is General Intelligence?

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There is a lot of confusion published about Artificial General Intelligence (AGI) so I felt I should weigh in on the subject since I am a serious AGI researcher and I have witnessed AGI first hand. A LOT of people equate the meaning of AGI to be equal to human level intelligence. Let me state emphatically that AGI is not about human intelligence although humans possess general intelligence. Also mice, birds, cats, dogs, and most of the animal kingdom possesses general intelligence. General intelligence is not unique to humans. One of the best ways to describe general intelligence is the tea (also known as the coffee) problem. I could fairly easily build a robot that could make me a cup of tea in my kitchen. It would do everything from get the items needed to dipping a tea bag into the cup after it poured in hot water. Then if I took this same robot over to your house and told it to make tea, using conventional AI, it would fail miserably due to the fact that the robot would have no ide...
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Obstacles and How to Overcome for Connectomic AI

Working with animal connectomes to emulate and create neurorobotic working systems has a number of issues that are surmountable but need to be considered. 1) Finding Connectomic data Data is still shy on the public domain. C elegans is the only full connectome available I am aware of. There are a number of other partial data sets and I would assume a number of data sets are in private hands. In addition, large data sets have a huge number of orphan and missing neuron and synaptic connections. How to overcome Going to conferences and making personal connections would most likely get access to the number of private data sets. In addition, having the backing of a major corporation could also assist in opening doors to private data sets. Providing funds to researchers could also create data sets specific to the data needs of emulations. I was part of a proposal that estimated roughly $30,000 USD would get us the ant connectome dataset so this would be in the neighborhood we would want to...
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