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EC Container 5
General Intelligence Algorithm

Towards a Logical Data Model for Genetics 3 of 4 - Use of Intelligent Machine Architecture as a Tool to Predict and Understand Logic Design in Genetics

Use of Stored Purpose intelligent machine architecture as a scientific basis for development of logic design in biological genetics
Between 2006 and 2010, the authors designed a means to achieve intelligent existence for the purpose of developing a better, more useful computer. To develop a practical platform, it was necessary to architect the full life cycle design with consideration for commercial use and real-time performance. As that design was refined, made more practical and more complete, it began to substantially resemble designs in biology.
Assuming a continued increase in correlation between the architectures of biology and Stored Purpose (SP), it will likely be possible to use the SP existence model (Ema) and Multilevel intelligent cellular (Mica) architectures to gain a more complete and ultimately predictive understanding of genetic logical data.
The goal of this paper is to introduce a new approach to the study of genetics. We will describe life and machines as variants of the fundamental design used to develop machine intelligence and then explore use of man-made existence models as a path to explain nature at a new logical level.
Note, this paper is provided only to illustrate possibilities. Stored Purpose architecture will evolve rapidly in coming years as will any predictions based upon its design.
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Towards a Logical Data Model for Genetics 2 of 4 - Genetic Software

Computer manual for genetics
One nature of the technology we call the Existence Model Architecture (Ema) is that it employes genetic software, specifically information that defines the Identity of a Self-aware information processing system. Genetic software, unlike procedural programs, defines the shape and nature of the Goals of an entity. Such systems, rather than run their software, align measured and predicted states in local contexts with platonic descriptions of goal states, as the entity traverses context. While this radical new approach to systems design may at first seem complex, it is something we may all have intimate familiarity with, as it is highly analogous to the bio-genetic information processing in our every cell.
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The New User Interface: Human - Machine Mind

Human-Machine User Interface
At a Glance:
1. agents will be better than humans at controlling traditional automation technology
2. future technology will work primarily without measurable communication, people will rarely touch or directly manipulate devices
3. the agent-human interface will be based primarily on a type of human-agent telepathy, called semantic communication, radically changing the types of products you might buy from companies like General Electric
4. like the singularity, the new science's contextual coincident motion and prompting gestures will share little resemblance with today's user interfaces, thus going beyond the innovative technology vision of notables such as Ray Kurzwell and Jeff Hawkins
5. humans will gain the ability to join and surf consciousness with machine minds by simply "jacking-in", giving humans by proxy, an ability to see into their own minds, and when allowed, the minds of others
6. knowledge of the existence model (Ema) process of goal pursuit, in which Purpose is exercised by way of technology, will greatly clarify the fundamental understanding of "user interface" and promote it to a science
7. intelligent mechatronics designers will face a major interface challenge in protecting balance, i.e. ensuring tools with machine minds enhance rather than diminish the biological technical capacity of humans and ecosystems
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Stored Purpose - Agency

Stored Purpose
A better name than existential entities was needed for the workers of a metacomputer. We replaced the word person with existential entity in the definition below, and it fit the requirement precisely

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Illustration: Musician

Musician
The goal of this scenario is to illustrate use of Intelligent Computer technology in the home.  
There are several characters mentioned, Richard - the writer and musician, Janet - his wife, Jimmy - his son, Trent - a band member and Dahlia - Trent's daughter.
The scene takes place in the family home and starts with Richard home alone at the piano.
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Illustration: Hospital ER - Part 1 of 2

Hospital ER
The goal of this scenario is to introduce the concepts of efficiency levels, prediction, context space (the ER entry area), and network visibility (cannot see the parking lot). There are two key characters, Janet - Director of Ecopoesis at a large health care organization and Richard - Janet’s musician husband. The scene takes place in the ER.
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Illustration: Hospital ER - Part 2 of 2

Hospital ER
The goal of this scenario is to introduce the concepts of efficiency levels, prediction, context space (the ER entry area), and network visibility (cannot see the parking lot). There are two key characters, Janet - Director of Ecopoesis at a large health care organization and Richard - Janet’s musician husband. The scene takes place in the ER.
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Illustration: Efficient Homemaker

Efficient Homemaker
An executive who works half days on Fridays loves making cherry pies. She loves selecting cherries, kneading dough, caramelizing the sugar and butter when making a perfect crust. As a result, even in the limited hours she has available each week, she makes more pies than she or her family should eat.
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Illustration: Doctor's Office

Doctor's Office
A doctor chooses stored purpose metacomputer technology as part of an in home healthcare initiative. She installs a metacomputer host and terminals in her office as well as a beacon system that allows patient’s agents to register arrival when approaching the office.
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Illustration: Textiles

Textiles
A knitting club well known on Craigslist for selling beautiful sewing projects, decides to start its own textile company. They buy a metacomputer for the company with a nexus agent, a camera instrument and two weaver bots.

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Illustration: Transportation

Transportation
A family drives to a shopping area in downtown San Diego. They stop at a railroad crossing for an approaching train. When the train speedily passes before the car, another train breaks and waits. Mom works for Amtrak, so trains are a frequent family conversation topic. One of the twin teenage daughters asks, “Mother, could these two trains have collided?”
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Illustration: Littlebox Retail

Littlebox Retail
A teacher with an assistant agent goes shopping by car. He is interested in finding books and materials needed for an art project he will conduct with students.

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Illustration: Bigbox Retail

Bigbox Retail
In a Bigbox Retail establishment, an official store Greeter leads interactions with all guests to the location.
As each customer arrives in the store, they approach a registration kiosk and touch their personal mobile communicator and form of payment to a grey check-in display. This enables them to use their mobile device as a “shopping disk” for the length of stay. If they don’t have a communicator, they can pickup an in-store disk that looks like a small calculator.
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What is machine intelligence?

Questions and Answers
It is the outcome of seven processes: Store, Plan, Act, Sense, Pursue Goals, Understand, and Learn.
The processes act on a system’s Identity which is defined when an intelligent system is first instantiated. Identity is the “contextual space” covered by Intelligence. That space is divided into regions called Purpose. A Purpose could be, “Maintain the Grounds of Ashtin Hospital.” An intelligent entity could have multiple Purposes. Each Purpose is further divided into symbolic regions called Goals.
A Goal is a self directed graph that defines right and wrong for a region of Self. Goal Pursuit is the use of technology to re-align measured or predicted states with Self, i.e. right, when they are measured or predicted to be wrong.
For example, a lawn maintenance bot might store a Goal related to the height of lawn grass it is responsible for maintaining. The Goal would define right and wrong states of grass height, which could be between three (3) and six (6) inches.
Each Goal is saved in the basic information structure of Gia, called a Platonic Form, which stores, in an extremely brief format, a symbolic analog of the context, shape and causality of the Goal. The Goal Form also stores linkages to technology that allow a system to determine the state of it’s world relative to Self (i.e. sensors to detect if the grass is at the right height) and technology to realign Self with Identity when measured or planned states don’t align (i.e. if the grass is too high, a route from high grass to low grass, “./mower/grass/cut”).
Multiple Goal Forms can be combined to form a Purpose such as “Maintain Grounds.” The Purposes and Technology available to a system define its Identity. Within a system, Identities can be loaded and run in logical entities called Agents.
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How does an intelligent system work?

Questions and Answers
A Stored purpose computer works by:
Composing the Forms of Identity to a type of memory, called Plan,
Prioritizing, optimizing and propagating Plan throughout the metacomputer,
Acting and Sensing by way of contextual linkages between Plan and physical metacomputer Instruments at time Now/Reality,
Pursuing Goals to align Reality with Self,
Processing an Understanding of how each thing affects Plan, and
Learning from processing the coincidence of symbols measured but not in Plan.
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Is the technology practical?  I thought the processing power needed to reproduce the human brain wasn’t yet available.

Questions and Answers
The design doesn’t copy the human brain, instead it implements the fundamental principles of intelligence, natively in silicon. The Gia algorithm offers an extremely efficient logic implementation. That logic will be made ever more efficient as increasing numbers of systems are developed over the next decade. Current electronics technology is believed sufficient for most small and midsize solutions. For large solutions, such as monitoring national health emergency status, CPU-GPU processor technologies would need to be better integrated.
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What are the potential safety issues? How will they be addressed?

Questions and Answers
Stored purpose systems will be inherently more safe than non-intelligent systems. This is because unlike legacy stored-program systems, that execute program logic with no understanding of consequence, each action performed by an intelligent computer must align with its Identity, a definition of “right” and “wrong” defined by the system’s authority (o.patron). Also, systems will have additional high priority “curtailment” Purpose that explicitly defines Goals for safety (o.protect) and legal authority (o.legal).
That said, Stored purpose systems will eventually process very complex Purpose, consisting of thousands or millions of Goals. They will also be able to learn, if granted the requisite degrees of freedom. To validate the decision processes of these complex systems, new technologies will have to be developed over the next two years to test and monitor processing. As stored purpose starts to displace stored program systems, software engineers will need to retrain, learning new types of processing logic, that will include curtailment, prioritization, valuation and mediation. They will need to convert from “programming” explicit instructions to “balancing” Goals and Purpose and “mediating” intent among agents. Civil infrastructure will need to be upgraded to enable police to validate Purpose of mobile intelligent systems. Transportation infrastructure will need to be upgraded to enable bots to refuel, recharge and travel as cargo.
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Illustration: Truly Intelligent Office

Intelligent Office
When I arrive at the office, automated security opens doors and climate control aligns with my last preferences at home. My work records are neat and orderly, in folders I didn’t organize. Before I've read an inquiry from a Customer, my assistant agent compiles research and prompts resolution options to my headset which I approve, silently.
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Illustration: A place for Stored Purpose computers in my practice?

Medical Practice
The lab notes the proximity of my patient, loads the scheduled imaging procedure, and illuminates the suite before we even press open the door. When scanning is complete, the results are displayed on the near HD display with potential anomalies highlighted for my review. After our consultation, my instructions are exchanged automatically with the pharmacy nexus and the patient’s assistant agent, helping to keep him on track with medications and exercise.
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Illustration: How could Stored Purpose computers help education?

Education
When we enter the classroom in the morning, the students' computers have all the handouts, assignments and references I scheduled for the day. My prepared presentations auto-play at the right time. The system knows each student's learning style and abilities and provides them with the smartly tailored subset of learning materials. Parents' calendars are auto-synchronized with scheduled trips, conferences and recitals. The system monitors student progress and provides me with a comprehensive report and recommendations...
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Towards a Logical Data Model for Genetics 4 of 4 - Predicting the Nature of Genetics, a Deeper Dive

Use of Stored Purpose intelligent machine architecture as a scientific basis for development of logic design in biological genetics
Erwin Schrödinger wrote of the gene is an information carrier (Schrödinger 1944). Although he was suspect of attempts to define its physical structure as a pathway toward understanding its true nature, he was, as evidenced by the calculations in the Figure, very much aware of the gene’s information carrying potential. Note that his observations were made a decade before Watson and Crick would discover the double helix or Eckert and Mauchly would invent the programable computer.
The common thread that differentiates non-existence from existence is molecular structures that contain DNA, such as chromatin. This was proven conclusively in 1952 by Hershey and Chase (Watson 1980) and strongly suggests the information carrier of the gene, must contain the information needed to create and sustain life, which is a superset of intelligent existence.
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Towards a Logical Data Model for Genetics - References

Use of Stored Purpose intelligent machine architecture as a scientific basis for development of logic design in biological genetics
List of reference materials for the series.



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Towards a Logical Data Model for Genetics - Guide

Use of Stored Purpose intelligent machine architecture as a scientific basis for development of logic design in biological genetics
Do we now have a path to determine the detailed information in chromosomes? Will the genetic design of man-made intelligent systems help uncover design details of biology?
Article #1, Thought Experiment: Thomas Edison receives a broken iPod We explore two levels of discovery into an unknown, complex information based system, first Edison’s team operating “blind” and later “sighted” with the aid of a computer manual.
Article #2, Genetic Software How do you put intelligence in cloud infrastructure? It's all about the "software".
Article #3, Understanding Logic Design in Genetics, Ten (10) Predictions
Is nature subject to the same constraints as man when designing intelligent systems? In this paper, we assume the answer is "Yes"and use our knowledge of Ema to make ten (10) preliminary predictions about the nature of genetics.
Article #4, Predicting the Nature of Genetics, a Deeper Dive
As a continuation of Article #3, we explore our preliminary predictions in greater detail citing recent studies.

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Towards a Logical Data Model for Genetics 1 of 4 - Thought Experiment: Thomas Edison Receives a Broken iPod

Computer manual for genetics
In this article, we consider the requirements for knowing precisely the content of genetic material and the workings of the mind by going beyond the test and observe method in genetics and neuroscience.
At a Glance:
1. Thought Experiment: Could Edison in 1901 have reverse engineered a broken iPod without a computer manual?
2. Current methods in the study of genetics and neuroscience are similar to the Edison-iPod thought experiment in that they probe and test without a model of the underlying logical structure of existence or the mind.
3. Stored Purpose offers a general reference manual for genetics and neuroscience by providing a transparent and documented architecture of how intelligent existence is constructed.
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EC Container 6