User:Darwin2049/ChatGPT-ScratchPad

Considerations. Context. Framing: Interface, Evolutionary, Political, Epistimological. Version .02

(2023.04.07@18:00 for next pass: add in references, links, imagery)

Interface Questions. This is presented as a multifaceted question. Its focus is on the risks associated with how target audiences access and use the system. The list of focal topics as currently understood but which may grow over time include:

• how this new technology will respond and interact with different communities;
• how will these different communities interact with this new technology;
• what if any limitations or “guard rails” are in evidence or should be considered depending upon the usage focus area;
• might one access modality inherit certain privileges and capabilities be considered safe for one group but risk for other groups; if so, how might the problem of “leakage” be addressed;
• in the event of an unintended “leakages” (i.e. “leaky interface”) what might be the implications of the insights, results, capabilities

In order to move this examination forward basic definitions are indicated. As a starting point we place focus on how we use the terms: communities, then we place focus on features. What we know is that this new ChatGPT4 (CG4) tool will be used by teams of individual with specific interests, means and goals. In no particular order of priority we start by defining terms and concepts. Following are some starting points for purposes of discussion:

• communities: what kinds of communities are they, are there some that are of interest to this discussion;
• common capabilities: the evolution of the World Wide Web has ushered in an era of software as a service (SAAS); for those of us who have been using the internet during the last twenty years or so we have come to take for granted such services as Google Search, Yahoo Finance or Morningstar Financial News; in each case we encounter choice trees that enable us to access specific functionalities; CG4 is directly comparable in terms of how we experience it;
• CG4: some questions about its capabilities;
• risks: some events that entailed risks;
• hypothetical risk scenarios: examples are hypothesized for each of the communities listed;

As a point of entry some if not many of these categories seem to be indicated; the intent is to establish a baseline for subsequent analysis; successive reviews can result in one or more categories being promoted or demoted; these may prompt the creation of more areas and questions; note that this is very much a work in progress; so to begin.

Communities. A scan of the topic of communities returns a wide swath of useful information regarding what kinds of communities there are and how they function; for purposes of this analysis we will limit our focus to just a few. According to Vuukle communities of: interest, action, place, practice, circumstance and hybrids;

The set of community types encompasses a fairly broad range of possibilities. Dozens to hundreds of pages could be written were an exhaustive effort to be made to examine each one. Therefore so as to move the discussion forward this analysis will focus on just a few. These will include communities of interest, action and practice. Using these as a baseline we might be able to extend our analysis to whichever other community type that may come to our focus.

In order to attempt to make an assessment of how CG4 might impact these communities we focus on and list what is new and interesting about CG4. With the items on this interest list we might then be able to identify what might be different and new.

A Community of Interest (COI). According to Wikipedia or interest-based community, is a community of people who share a common interest or passion. These people exchange ideas and thoughts about the given passion, but may know (or care) little about each other outside this area. Participation in a community of interest can be compelling, entertaining and create a community where people return frequently and remain for extended periods. Frequently, they cannot be easily defined by a particular geographical area.

In other words, "a community of interest is a gathering of people assembled around a topic of common interest. Its members take part in the community to exchange information, to obtain answers to personal questions or problems, to improve their understanding of a subject, to share common passions or to play." In contrast to a spatial community, "a 'community of interest' is defined not by space, but by some common bond (e.g. feeling of attachment) or entity (e.g. farming, church group)."

A Community of Action (COA) According to Wikipedia: unlike a community of practice (COP), they exist in a situation that is structurally more open, where actors have the possibility of bringing about change. These more open situations might, for example, correspond to collective design teams in professional environments.

COAs possess some of the characteristics of communities, such as the development of a common language and mutual learning in the course of action. However, they also possess some of the characteristics typical of more associative social relationships, such as the "voluntary" nature of association and the importance of "common goals" in directing collective activity. Some argue that this makes COAs more "rational" groups than COPs.

Community of Practice (COP). According to CommunityOfPractice (Canada): Community members have a shared domain of interest, competence and commitment that distinguishes them from others. This shared domain creates common ground, inspires members to participate, guides their learning, and gives meaning to their actions.

Community members are actual practitioners in this domain of interest, and build a shared repertoire of resources and ideas that they take back to their practice. While the domain provides the general area of interest for the community, the practice is the specific focus around which the community develops, shares and maintains its core of collective knowledge. There have been a number of communities that sprang up in the technology sector. They arose organically as a result of shared experiences. Some notable ones include some that identified common issues and formed in order to share experiences and propose solutions. Several early communities that became well known were active, held periodic open meetings and pursued objectives that were above board and legal. Others have formed in recent years that formed in reaction to perceived social, corporate or political issues. In various of their cases the legitimacy of their actions might be considered to remain in question.

Below is a summary list of possible features of interest. This is followed by a thumbnail sketch of communities. A quick Google Search scan will show that is a large library of material pertaining to communities. According to at least one entry there are at least twenty one different types. Some references suggest that there are seven types. Others five types and a further examination will suggest that there are three fundamental types. For purposes of simplicity this initial pass will focus on three community types, communities of: action, interest and those of practice. A later section will suggest one or more examples of each. In the examples provided several of the features discussed below will be addressed; the intention here is to illustrate how existing communities pursued their goals and objectives;

DECUS. During the late Seventies and on into the Eighties the Digital Equipment Corporation (DEC) was the go-to vendor of choice for affordable, powerful minicomputers; with increasing sales nationwide a community sprang up that called itself DECUS. This was the Digital Equipment Corporation Users Society; Its members held periodic meetings and established a means of communicating with each other; their activities typically included sharing and exchanging of patches, work-arounds to various issues found in the DEC operating systems such as RSX or RSTS.

Were one to send a blank tape (these were typically 2400 ft standard reel-to-reel tapes) and a self addressed return envelop then the DECUS steering committee would create a copy of current and up to date utilities, bug fixes, work-arounds and related documentation. As a result of technological advancement, mergers and acquisitions it eventually was subsumed along with several other user groups into what is now called Connect-Worldwide. It pursued legitimate, open, above-board activities that supported its membership. DEC maintained awareness of the issues brought up at various DECUS meetings and over time took steps to mitigate problems with its operating systems and its application software.

OTG. The Oracle Applications and Users Group developed as a result of the successes of the Oracle Corporation. Early on the company focused on managing a number of technological challenges with its flagship database management system (DBMS); Echoing the DECUS approach this group came together and consisted initially of database administrators (DBA’s); they held periodic meetings; typically a sales and marketing representative would participate. A common theme were resolution of various of the DBMS, new product announcements as well as related software issues. Oracle subsequently dramatically broadened its offering from just their DBMS but over time proceeded to offer industry specific solutions. Like DECUS, the OTG pursued legitimate supportive activities. Early on it Oracle Corporation representatives were present and demonstrated a willingness to be supportive of Oracle client concerns.

KnowBrainer. The Nuance Corporation advanced itself to become the supplier of choice for speech-to-text and text-to-speech voice activated interactive solutions. Nuance appears to have departed from the DECUS and OTG approach insofar as the activities of KnowBrainer are entirely virtual. It is not clear as to whether Nuance considers the issues raised by its members have a response or mitigation mechanism; this has been further complicated by the fact that Nuance was acquired by Microsoft recently.

IPSC-Group. During the early to mid Eighties the Intel Corporation began providing a category of computing system called Personal Supercomputers. Their flagship offering was the Intel Personal Scientific Computer; this was a cabinet housing 32 80386 processors. A Cube Manager processor running Xenix orchestrated the configuration of these processors into a range of connection topologies including: bus, ring, star, mesh and spanning B* Tree. As necessary a client could scale the processing ensemble from a D5 category machine (32 processing elements (PE’s)) on up to a D10 (1024 PE’s) For the time these were extraordinarily powerful machines. The users group followed in the path of prior special interest groups with the intent of supporting its membership. Intel has long since ceased producing the IPSC. COI/COA: As in the previously mentioned cases the community’s intentions and activities were legitimate, open and supportive. The actions of each of these groups argue for them to be categorized as Communities of Interest, but loosely share features found in Categories of Practice;

Anonymous.

WikiLeaks.

Pirate Bay.

Following these examples we will confabulate hypothetical cases where one or another of these types of communities might either a) be susceptible to the risks posed by ChatGPT4, or b) represent risks to one or another communities, or even in the larger context of all of society.

• Novelty: what does ChatGPT4 (CG4) offer that other information systems do not; what is different; have we seen anything like or similar to it before;
• Taxonomy: where can this capability be positioned in terms of systems with known capabilities;
• Benefits: what benefit or advantages can I expect by using this capability;
• Interaction Modality: how do I interact with it; what results do I receive;
• Learning Curve: will an hour’s investment be sufficient to learn its features or does it require days or weeks of training;
• Audience: who wants to use this; does team size influence utility; can individuals produce useful results;
• Reliability: is it available at any time like Gmail or Google Maps,
• Competence Map: is there a chart or means of profiling CG4’s relative strength by capability or topic;
• Confidence Map: is there an a priori source that enables assessments about CG4’s topical validity;
• Email or Blog: will others known or unknown to me be able to have access to my session;
• Competitive Advantage - Leverage: what advantage(s) do I get by using CG4 that non-users might not;
• User Skill: does continued usage enable qualitative leaps in utility rather than simple linear progress;
• Obsolescence: might a successor system obviate competence, insight gained in its usage;
• Impact: would using this system enable results more comparable to a skunk fighting with a dog, a gas line or toxic substance leak in a community or a tactical nuclear weapon detonation (or a strategic);
• Half Life: would using CG4 lead to consequences that are transitory or long term;
• Environmental Impact: might extensive usage of CG4 result in the creation of unforeseen composite capabilities; might it spark a Cambrian Explosion, a whole ecology;
• Ecology:can an ecology develop along the lines of the Apple iPhone, iPad, iWatch collection?
• Visibility: will my use be invisible to other users or will my actions create alerts that are recognizable to others; if so, what might be their range of responses;

Novelty. What does (CG4) offer that other information systems do not; what is different; have we seen anything like or similar to it before.

Summary:

• Known: we know that CG4 is a Large Language Model (LLM);
• SAAS: it uses the same SAAS model as other providers such as Yahoo, Morningstar or WSJ;
• More of the same: users of ChatGPT3.5 will know to interact view typed input and printed output;
• Pay = Faster, Smarter: access can be improved by using the fee based CG4;
• Anytime: it is always on and available;
• Leaps and bounds improvement: it is constantly growing and improving – with stunning speed;
• Semantic Coherence: salient session terms and topics are saved and can be referred back to;
• No one is home: CG4 is NOT a conscious entity, possesses no intentionality or sentience;
• Fast: its reaction times are almost instant:

Known. CG4 is the successor to the earlier ChatGPT3.5 system. As of this tract specifics about the number of parameters that were used to train it and other salient details have not been released by OpenAI. Current reports by users of the systems consistently report that it is dramatically more capable than its predecessor;

SAAS. CG4 has been made using the familiar software as a service (SAAS) format. Its usage, access and interaction model is very comparable to existing SAAS systems whose usage is either free or fee access basis such as Google Search, Google Disk each being free from the Google Corporation. In many cases such as Google, Yahoo or Morningstar there are at least two tiers of service that are provided. The firsts offers a free content area. A second fee based area provides subscribers with much more in depth insight and information.

User Model. A third party observer watching a user type in a query to a remote system, located somewhere in the world replies with a response and that an immediate reply comes back. They know that a gigantic server farm is sitting somewhere on the planet capable of fielding millions of queries per second. Free-Or-Fee. In this regard CG4 has enhanced its service quality by instituting a for-fee capability above and beyond still free CG3.5. format However there is a qualitative difference between CG3.5 AND CG4. Available. In the case of the CG4 subscription tier, responses are immediate. Any regular user of the more common SAAS systems will know that they can be accessed any time of the day or night, wherever on the planet they are. Queries posed to Google Search will consistently be met with an immediate response. The Search reaction time is so rapid that the system is already anticipating a range of possible directions that the user might going in even before the user has finished typing in their query.

Continual Growth. The system’s performance improves with time and usage. An obvious but poorly recognized fact about using Google is that the worldwide communities of users are constantly training it. When a user selects a specific item from the menu of choices that Google Search provides, each response gives the Google Search engine additional refinement and qualification on how to respond to each and every query issued to it.

Doctor. In certain respects, using CG4 is comparable to visiting your personal physician. Typically after a visit they will advise you to schedule another appointment in six or twelve months. A commonly recognized fact is that a patient rarely spends more than fifteen minutes in the presence of their physician. This means that on average a physician is seeing four patients per hour. Or leads us to conclude that a typical physician will see about 30 patients each day. Multiply that by 120 and by the time of the patient’s return visit six months later the physician has probably seen 3600 patients. The result must mean that the physician’s competence and grounding has to have advanced dramatically.

Warp Speed Improvement. Users are querying CG4 24/7/365. This must mean that its growth and competencies are growing exponentially with each passing day.

Therefore our usage of today’s instance of CG4 must be quantum leaps beyond its week ago instantiation. So this gives us reason to believe that CG4 is like a swimming pool whose deep end increases exponentially with each passing day. It will broaden, deepen and qualitatively improve its capabilities with each day of use. Semantically Coherent. CG4 has shown itself to be capable of abstracting and referencing prior points in a session. CG3.5 provided a text buffering capability of about 5000 words. CG4 now can retain about 25000 words. It limits its output to about 2500 words.

Key points or topics in a dialog can be referred to later in a dialog session. This is a quantum leap in terms of capability. A result of this is that the system can generate startlingly accurate references to prior activities or interactions during a given session. Concretely, were a user to engage in a dialog about Peter and the Wolf, one could ask about what Peter did when he saw the wolf. Or, what the wolf did when it saw Peter. Later in the session one could use the reference “he” or ‘it” instead of explicitly using Peter’s name or “the wolf”.

From the perspective of traditional rule or first order logic expert systems this is a huge leap. These systems were capable of demonstrating and responding to different levels of knowledge. These were known as: surface, shallow and deep:

• surface: this means that a person using a software system say for instance Microsoft Word for a day will have some superficial understanding of the system itself; that it will do nothing until prompted; i.e. it will not spontaneously do something unplanned or unexpected; is best used for textual composition and editing, that spelling and grammatical errors can be automatically corrected.

• shallow: in the case of shallow knowledge a user will have familiarity with the control interface and a range of its features; they will have some insight into how to best apply its features to the task at hand. If we go beyond shallow knowledge then we encounter deep knowledge.

• deep: this is insight sufficient to intelligently examine and modify its internal functioning; one might expect this level of knowledge to be found in a person with close familiarity with the tool itself, they might have been involved in its construction.

CG4 seems to be demonstrating deep knowledge and insight into the topics that a user provides. The range and depth of understanding is stunning. Many observers are now asserting that CG4 is passing the Turing Test. Subsequent sessions with CG4 have shown that it is capable of demonstrating sufficient competence to pass the Bar exam for lawyers, pass the SAT exam as well as perform as well as or better than humans in several academic categories. Thus, interacting with CG4 begins to resemble the experience of interacting with a person with deep knowledge. This quite is novel.

The lights are on. But the doors and windows are open and nobody’s home. CG4 is not conscious. It has no self referential capability. It does not possess sentience or more specifically it has no self consciousness. There are no actions that it takes that exhibit a prior intentionality. It has no means of making a qualitative assessment on how its responses will be accepted or what the reaction on the part of the human user might be. In short… this is not a person. It is at best an incredible mimic of human behavior.

Warp Speed. CG4 is obviously an information systems that is hosted on electronic devices. Therefore the obvious corollary is that it is operating at nanosecond, electronic speed. This must have many ramifications.

Taxonomy. CG4 capabilities show a qualitative leap in terms of capability and performance. We know that CG4 are based upon the ‘transformer models’. It has dramatically improved capabilities in part because of the vastly larger training data set made available to it; earlier LLM’s have provided metrics on how to improve performance without linearly scaling the hardware required to perform training;

Their advancement has tracked the explosive growth in the availability of high performance compute devices. The graphics card NVIDIA has heretofore featured in the advancement of the technology. Going forward other companies will come to the forefront in terms of compute power offered. Chief among them will be the company called: Cerebras. This Silicon Valley company is offering massively parallel ultra large ensembles of processing core devices. Their current offering is shipped with 850000 processing cores on a single substrate.

CG4 is a derivative of its root system which is known simply as GPT4. The GPT4 large language model is a follow in to the GPT3 and earlier GPT2 large language models. They makes use of “chain of thought” (CoT) models to solve problem; Interacting with them involves pre-trained prompt libraries;

Benefits.

Utility. Insight on how to use CG4 will impart to the user the ability to perform tasks that were complicated and due to their sophistication required extensive time and resources to complete; with the availability of CG4 the turnaround time from conception to response can be dramatically telescoped down; therefore a dramatic savings in terms of time can be realized. For the time being and looking forward the kinds of tasks that we can expect CG4 perform with increasing diligence and reliability will be those involving. With CG4 a user can issue a prompt to write a specific program and the result will be a detailed program that can be used to directly solve a problem. The output will also have documentation included as well as an explanation of what the code actually performs. The result of this capability is that going forward CG4 will become an ancillary productivity tool in reducing turnaround time from specification to working code. Fill In. the nature of the large language model is that it makes use of sentence patterns. It is able to recognize these sentence patterns as a result of being trained on a massive data set of text.

Recognize Sentence Patterns.

Interaction Modality. The CG4 offered by OpenAI accepts typed text instructions. Short essay length responses are returned. The amount of textual output and its style can be specified from terse to verbose. But this is only the side of the interaction that an end user sees.

Dr. Thompson’s website provides the impression that he is holding an ongoing verbal conversation with CG4. However in a prior Youtube video he explains how this “sleight of hand” is performed. his description reveals that his questions are produced at an earlier time. He then prompts his Synesthesia.IO avatar with the actual textual input prior to loading the finished video onto his channel. This thereby creates the illusion of a spontaneous conversation.

There is the other side of the equation. This is focused in the system administration location. Because of the nature of the system this system administration function can be geographically dispersed. But this is of secondary significance from the perspective of the user. However it is crucial to the successful functioning of the CG4 system. On the administration side there will also be a collection of staff charged with monitoring the “exception conditions”. These can be interpreted as being those cases where an individual or group has prompted CG4 to explore a hypothetical avenue. Which on examination could be used for unintended or undesirable purposes. This “Exception Staff” function will necessarily operate 24/7/365. This functional group will likely be allocated into teams whose tasks will be to identify prompt sequences that appear to approach or even breach the “guard rail” in terms of if these are being handled as prescribed or if they represent novel approaches. This in all likelihood will prove to be an unending task. This is because humans are endlessly creative. A read of the Lewis Carol novel “Alice in Wonderland” proves. In that novel the bulk of the characters and their actions are by turns highly allegorical or metaphorical. A casual reader unfamiliar with the political realities of Carol’s time might be totally oblivious to the actual import and intent of his efforts. A user can type in a free form sentence as input. The perception is created that the user is interacting with a system that quite possibly could be in the next room, or a broom closet rather than halfway around the planet. The responses come back as plain grammatical text.

Learning Curve. CG4 has gained a dramatically fast following and user population scaling. The reality of being able to interact with it using natural language is a huge plus. The ability of the system to almost instantly generate remarkably erudite responses regularly astonishes those who have interacted with it. However what has also come to the forefront and is gaining traction is the fact that key to effective use of CG4 is the ability to construct and refine prompting interrogatives. CG4 has shown that it can effectively respond to sophisticated and complex prompts with amazing effectiveness and accuracy. However there are still areas that need exploration. Responses to convoluted philosophical topics may still be a distance in time off. However because of the incredibly rapid pace of development the time to success remains an imponderable. It could happen in the very near term…. Possibly week or months or could be further out in time.

User Training. Anyone whose company has acquired a new software tool that possesses substantial sophistication will regularly find that the software provider will offer training in how to use that tool. This training might last a period of less than one week. For more advanced topics the training could extend beyond one week. In some cases such as the network router provider – Cisco whole curricula have been developed to train an individual to become a network engineer. CG4 will most likely prove to be no different.

Prompt Engineering. Based upon the sudden presence of book length offerings from individual on how to formulate prompts the race has already begun. The reality of this development is pointing in the direction that in order to capitalize on the full power of CG4 a user really must develop facility at a) understanding what its underlying capabilities are and b) how to most effectively present it with succinct and focused instructions on how to proceed.

Programming. CG4 responds to prompts. These are presented in simple or complex English language sentences. Those with familiarity with computer programming languages know that learning a sophisticated programming language requires both study and extensive experience. In the software development effort commands are combined into functions that perform specific tasks. Functions are combined into programs which when taken together achieve goals. Programs can be combined into libraries that allow for a user to mix and match various programs together to complete highly sophisticated and elaborate results. MidJourney. An examination of the efforts of peer MidJourney users is very likely to show the prompts that were used to generate an image. The more sophisticated users reveal prompts that demonstrate a high level of sophistication in terms of how to provide very precise and concise instructions to the image generator. These instructions might include camera angle, depth of field, resolution, camera aperture, time of day, scene contents as well as a number of other CG4 - Catalogs and Libraries. Going forward we should expect to see an ecology develop that is comparable to what we can find for MS-Excel users. A Google search will show that there is a large number of offerings from software providers. These offerings typically are targeted to perform specific functions. These range in focus from text manipulation, financial analysis, scientific calculations and a wide range of other solutions. We should expect to see the same thing happen with CG4 as well.

Markets – White, Gray, Black. A search on Google will reveal a very extensive universe of tools that are oriented toward users of Microsoft Office. These offerings are from legitimate, reputable sources and organizations. What we should expect to see however will be a reenactment of the Deep Web world wherein highly specific features are available that would never be found listed on a Google search. They will instead likely populate an already existing gray market and of course… there will be a black market of tools and capabilities. These will likely shadow the developments currently found in the so-called Black Hat hacker world. The only question that remains is how these non-mainstream markets will develop and how they they will be accessed.

User Skill – Novice to Power Users. In simple words… progressing in a linear sequential way with unexpected discontinuous competence leaps. This leap could result in qualitatively more sophisticated interaction with CG4. This category is intended to ask the question about competence. Suppose a user were to progressively cover one functional capability after another; in a sequential manner. Over time that person’s competence will near a plateau. However can it be the case that as that person increases their competence that they might experience an “ah ha!” moment; this could be accompanied by the recognition of some of the fundamental principles and concepts; subsequent usage might reflect a deep understanding in how to formulate profoundly more powerful prompts to the system and correspondingly get more powerful results as a result; Basically, if I continue to use CG4 then it is reasonable to expect that my level of skill and facility will improve. But is it possible to speculate that as my skill increases that a broader and deeper understanding of the underlying mechanisms of CG4 will increasingly reveal themselves; should this be the case then it is reasonable to speculate that as a user’s sophistication increases that they can experience a discontinuous leap forward in competence instead of a simple straight line improvement;

Credibility Profile (Competence, Confidence).

Competence. A confidence builder would be some kind of “terrain map” that illustrated the topical areas and competencies that CG4 offers; this may be unrealistic because CG4 is constantly evolving; with each passing day it will be improving quantitatively and qualitatively; this is because of the growth that they system undergoes on a daily basis; the CG4 instance that I interacted with last week is almost certainly far different than the instantiation that I interact with today; this is not to say however that such a feature is out of the question; were one to be possible then it might resemble a terrain map; possibly with subsurface features; these legend with which to interpret it might reveal competency areas in terms of their comprehensiveness and utility; a depth feature might reveal more underlying and profound realities about its capabilities that might go unsuspected;

Confidence. A possible way to provide a user with some level of results credibility might be a confidence map that provided some kind of indexing value; this index value might suggest to the user how sure CG4 was that it had grasped the thrust of the prompt set; a range of values could span from ‘very sure’ to ‘dreaming’; it too might resemble a terrain map with topics arrayed across; this map might be searchable along various scales;

Hypothetical Cases: In what follows this observer of how CG4 capabilities might become manifest in the real world. These are strictly leaps of imagination and should not be taken seriously, but rather as points of departure for further collective examination and rumination. They are intended to be used as a point of departure to return to the questions originally posed. Specifically, what might be some risks that this technology brings to different communities? How might one or another community view or interact with it? How might the activities of one community impact those of other communities? Social Engineering. In this area this observer suggests how CG4 can be used by one determined community to adversely impact the fortunes of another.

Novel Pharmaceuticals and Materials. CG4 has shown itself to be in possession of a remarkable range of highly specific and technical knowledge; this exploration postulates the actions of a small community gadfly or muckraker activists. It suggests how this group might be able to facilitate the creation of heretofore unforeseen or poorly recognized materials and molecular synthetics. It will go on to create a scenario on how these new artifacts might be introduced and what kinds of impacts they might have on an unsuspecting target community.

Advisors and Companions. Relatively recent movie productions have explicitly suggested that a sufficiently sophisticated system might acquire the traits and skills of a “best friend” and companion. The movie HER was an exploration of this topic back in 2015. CG4, or a derivative or refocused variant might well be capable of realizing this functionality. Narrative Creators. A casual user of CG4 will very quickly discover that it is fully capable of confabulating a series of hypothetical narrative structures. These narratives might be very suitable for works of fiction such as in the case of new screenplays or movie scripts; coupled with the realism available using tools such as MidJourney it is entirely possible that almost “whole cloth” narratives about current controversial topics can be manipulated.

Knowledge Ecosystems. Entirely new communities may soon emerge that consist of individual with highly specialized skills. These will be grounded with the quickly advancing knowledge intensive capabilities provided with the likes of CG4 and its peers. DeepMind is a case in point wherein they have become what might come to be considered a “Go-To” problem solver for exceptionally difficult to solve scientific or technological problems. Their recent AlphaFold2 system which produced a library of the 200 million proteins known to exist in human organism is a case in point. Other categories of competence are likely to arrive with headings such as:

Specialists. These will resemble already well known knowledge intensive individuals; these typically are experts in their field and are highly trained and competent; the more common description is that they possess an advanced academic certification – typically a PhD. We should expect to see a whole new gray area emerge that straddles the zone between a first graduate degree such as a BA or a BS and range of competencies in between; these may be subject to some form of review authority but may intersect or operate outside of the more formal traditional certification providers – what we see with in a PhD defense.

Moderators. These might be the “front end” for totally new types of highly advanced and sophisticated advice. Something along the lines of a “Board of Directors”. These types of arrangements already exist. They are currently known today as Actors and Actresses. If one were to scrutinize the activities of any of the most successful actors and actresses today then one will almost invariable discover that they are in fact privately held companies.

The point of contact will be the agent, there will be coaches – voice, accent, skills (horse riding, musical instrument competence and other specialized skills tutoring); obviously it is in the interest of the actor who wishes to become a greater success in their craft to be able to offer as many skills and talents as possible so as to provide versatility of role selection; in all cases they have their whole stake-holder community that are interested in furthering the ability of that actor or actress to escalate the value of new roles to higher levels.

In this setting we might see this model brought to a broader level of accessibility. A moderator would be (probably) a person who interfaces with a client (using mobile technology) and a team of specialist experts; this experts team might be ad hoc or might be contracted to be in an extended basis. An individual with this kind of advantage might be capable of moving ahead in a variety of in-the-moment directions at a brisk pace. They would accept queries, questions and musings from the client. they would then field the item out to the specific specialist with that particular skill for handling; the results would then be returned to the client for review, perusal and should they chose, execution. Possibly even in real time.

Something along the lines of the narrative found in the movie Limitless comes to mind. Though this augmentation mechanism was facilitated by psycho pharmaceutical modalities.

Map Makers. These might be individuals, or communities who focus on exploring at depth the capabilities of a CG4 (whether derivative and specialized or peer); their efforts might provide insight into what the responses that CG4 produces are solid or if they require “backing and filling”. Their activities might resemble those of the map-makers of the Seventeenth and Eighteenth Centuries. But in this case their efforts might be used to spotlight and identify areas that need attention, or, areas that CG4 is singularly excellent at.

Collectors. These might be individual or communities that focus on cataloging CG4’s particular strengths. They might offer access to libraries or catalogs of interaction functions or modules; they might provide offerings that resemble field programmable gate arrays (FPGA’s); in the electronic engineering world, FPGA’s are semi-finished ensembles of programmable logic devices; they are somewhat comparable to “the last mile” that the common carriers offer for land-line customers. Fiber optic offerings are typically already in the ground months to even years in advance before customers eventually figure out what to do with them;

Raters-Qualifiers. These might be comparable to the recent communities that provide credibility, bias and fact checking are dimensions that these activities would focus on; they might focus on specific topic categories and information sources. Bridge Builders. These might resemble communities of action such as are currently found with say, radiologists or other specialists.

An almost incandescent topic on almost any news or “news” channel will at some point discuss the issues associated with censorship. A bridge builder might be an individual or community capable of providing access to multiple pathways between “head end” and “audience”. This would resemble the head-end of an early cable company. The head end was the studio where program material was assembled and scheduled for replay down the company’s of coaxial cable network. In this case it could mean that there may be a number of intermediary “hops” where content is “loaded on” to a server network (much like NordVPN) and then shunted (after encryption) to a forwarding address. In terms of functioning it might closely resemble a torrent stream such as The Pirate Bay. But the content would be “chopped” into pieces and sent through different pathways… i.e… “bridge points”; a subscriber might register with a content provider; the content provider would then issue the “bridge pathway” to use to retrieve (whether live or prerecorded) content. Thereby circumventing the existing problems users of Youtube have encountered in recent years.

Portal Providers. These would be communities of practice comparable to Bridge Builders. This function might be to identify the growing population of VPN and P2P providers. They might act as intermediaries very similarly to how various ISP companies allow a client to “hotel” other website URL’s on their own account. In this context they could provide predefined or ad hoc collections of communications pathways for meetings or briefing sessions. These sessions might be of the type that certain government authorities disapprove of.

Other subspecialties might resemble those seen in prior times and other cultures. These might bear resemblance to:

• Masters of the Universe.
• Power Players.
• Liege Lords.
• Retinues and Retainers.
• Samuri.
• Artisans, Craftsmen and Storytellers.