User:Darwin2049/ChatGPT4-Sandbox

(2023.04.23@16:30; sharper, more focused, succinct; shorter, cut to the chase); (2023.04.24@13:30; keep focus on deep learning; what it is, can do; maintain short, preferably bullet point descriptions for discussion purposes; relegate observations, discussions to notes, references section); (2023.05.15@14:10; resume focusing efforts; sharpen risks discussion - theoretical, systemic, malicious; transfer in more recent text, imagery);

Overview. In the following we try to analyze and contextualize the current known facts surrounding the OpenAI ChatGPT4 (CG4) system.

• CG4: we offer a summary of how OpenAI describes it; put simply, what is CG4?
• Impressions: our focus then moves to examine what some voices of concern are saying;
• Impact: we then shift focus to what is being said about it; we note that in some cases people express astonishment and wonder; in other case they express fear and concern;
• Scenarios: here we focus on how CG4 might be used be used in expected and unexpected ways;

What is CG4? CG4 is a narrow artificial intelligence system, is rumored to have been trained on one hundred trillion parameters; if this is true then it is a substantial leap forward beyond the previous 175 billion parameters of ChatGPT3; thus far those who are knowledgeable about the size of the CG4 parameter count have not revealed the specific number. A peek at ResearchAIMultiple offers a comprehensive set of descriptions on how CG4 improves over CG3; to list just a few - it:

• has been developed using the generative predictive transformer (GPT) model;
• has been trained on a very large data set including textual material that can be found on the internet;
• is capable of sustaining conversational interaction using text based input provided by a user;
• can provide contextually relevant and consistent responses;
• can link topics in a chronologically consistent manner and refer back to them in current prompt requests;
• is a Large Language Models that uses prediction as the basis of its actions;
• uses deep learning neural networks and very large training data sets;
• uses a SAAS model; like Google Search, Youtube or Morningstar Financial;

Impressions (observations made by informed individuals)

• Some things that people have said about it:
  • possess no consciousness, sentience, intentionality, motivation, feelings or self reflectivity;
  • is a narrow artificial intelligence;
  • is available to a worldwide 24/7 audience;
  • can debug and write, correct and provide explanatory documentation to code;
  • explain its responses;
  • write music and poems;
  • summarize convoluted documents or stories;
  • score in the 90% level on the SAT, Bar and Medical Exams;
  • provide answers to homework;
  • self critiques and improves own responses;
  • provide explanations to difficult abstract questions;
  • calibrate its response style to resemble known news presenters or narrators;
  • provides convincingly accurate responses to Turing Test questions;

• Positive.
  • has demonstrated performance that suggests that it can pass the Turing Test;
  • CG4 derivative such as a CG5 could exhibit artificial general intelligence (AGI) capability;
  • emergent capabilities;
  • spatial, mathematical reasoning;
  • is capable of generating responses that are 25000 words in length compared to the 5000 of ChatGPT-3.5;
  • demonstrates better adherence to alignment imperatives;
  • is capable of engaging in a Socratic dialog;

• Concerns.
  • knowledge gaps: inability to provide meaningful or intelligent responses on certain topics;
  • deception: might be capable to evade human control, replicate and devise independent agenda to pursue;
  • intentionality: possibility of agenda actions being hazardous or inimical to human welfare;
  • economic disruption: places jobs at risk because it can now perform some tasks previously defined within a job description;
  • emergence: unforeseen, uncontrollable capabilities;
  • “hallucinations”: solution, answers not grounded in real world;
  • Elon Musk, Steve Wosniak, Emad Mostaque sign letter, along with one thousand other researchers to lead awareness effort of risks associated with unregulated artificial intelligence research;
  • Dr. Geoffrey Hinton, warns of risks associated with unregulated artificial intelligence research; resigns University of Toronto post;
  • Henry Kissinger, Derek Huttenocher and Eric Schmidt publish report highlighting risks, payoffs of pursuing artificial intelligence research;

Impact. There is an ongoing worldwide debate about the impact that CG4-type capabilities can have. Thus far there are voices that are cautioning against its further development. Geopolitical realities however may neutralize these concerns. Should a major nation-state demonstrate heretofore unexpected capabilities with this new technology then all other participants may find themselves in a catch-up mode.

In a recent statement, the president of Russia, Vladimir Putin noted that whoever is able to achieve the high ground in this technology race will possess a sustainable lead in affairs of state. Therefore some middle ground might need to be found to preclude a preemption on the part of one or another authoritarian regime and the risks associated with an unrestrained artificial intelligence system. That this is the case can be seen by the downside risks that have already occurred as a result of the accidental (or deliberate) release of the STUXNET intrusion tool.

An core feature of these deep learning systems is that they utilize large data sets for training purposes. Environments where large data sets are available will have an inherent advantage. At least one such case comes to mind and that is the PRC. It uses a system called WeChat for a remarkable variety of purposes. Individuals interact with each other as well as engage in commercial activities on a daily basis. A data set of this magnitude must offer a considerable advantage to any efforts that the CCP might have in mind.

Risks. CG4 is a technology whose full import is going to take time to understand and grapple with. Like any new technology it can be used for constructive as well as destructive purposes. Based upon the reporting so far we believe that CG4 will have impact across a wide variety of communities. Individuals who have till now been gainfully employed may find that their job definitions are being either redefined at best, or pruned, at worst they may find themselves sidelined.

• Theoretical Risks. Some knowledgeable observers have expressed the concern that a derivative of CG4 could achieve consciousness. How this might happen presupposes that some form of emergent properties crystallize from the complexity and architecture of the system. These concerns are not without merit. A real world example of emergence can be seen by examining how termite mounds can be constructed from the activities of tends of thousands of mindless termites; these structures reveal an astonishing degree of sophistication despite there being no central architect or team of engineers; However the path to consciousness is littered with pitfalls. Just to list a few: a conscious entity would possess sentience, intentionality, a self model as an agent in the world; effectors that can manipulate objects and elements in the real world; to be sure, there have been advances whereby a robotic or android device is driven wirelessly by an advanced artificial intelligence system; yet there remains the set of other features that a consciousness would be expected to have; these would also include motivation, goal orientation intrinsic to itself and independent from sourcing from an external (human) entity;

As of this writing some of these are possible, others remain to be demonstrated; Recent efforts by Stanford Univ and Google work in generative agents is suggestive of where more progress may develop. Based upon the approach that these teams used the work in this area bears close monitoring. This is because the team incorporated feedback loops in their system that can be used by the various agents to reflect upon and refine or otherwise improve their performance and behavior.

• Systemic Risks. A channel creator known as CP Gray posted a video some years ago titled Humans Need Not Apply. In this fifteen minute video he made the case that advancing artificial intelligence could result in as much as a 45% unemployment rate. He observed that during the Great Depression the unemployment rate was 25%. Moreover he concluded that large segments of recent college graduates would not only find themselves unemployed but unemployable. A review of the job categories that he mentioned in his video are already within the purview of CG4 to perform. Several recent news reports have shown that urban violence and looting seem to be on the rise in several American centers. There may be a variety of possible explanations for these events. Further analysis is suggested to separate out what the root causes are for these events.

• Malicious Risks. Malicious actors have become a common theme reported on in the 24/7 news cycle. We should expect that various nefarious actors will seize upon CG4's capabilities and use it to prompt further disruption. Because the range of capabilities that CG4 offers is so broad it is difficult to guess as to how individuals or groups of hackers might use this tool for creating trojan horse, backdoor or DOS as well as DDOS attacks.

As of November 2019 the OpenAI team had recognized that the tool will be used for malicious intent. Their paper identifies three categories of malicious actors; these include low skilled programmers with limited resources, moderate skill level programmers with resources adequate to build tools to leverage GPT-2 and highly skilled actors with considerable resources; this last group are categorized as advanced persistent threats (APT); they are typically state sponsored and pursue long term focused goals;

In each case a significant analysis has been offered as to how to address these risks.

Speculations. The range of possible areas that CG4 is very broad; in fact, society wide; therefore we will try to maintain focus by presenting a few possible scenarios of how its capabilities might be used;

• Influence, Persuasion. One can envision using CG4 to generate a narrative story. Business leaders, particularly at the executive level such as a CEO or members of a board of directors have as one of their required skills the ability to weave a narrative vision of the company's mission. This narrative is more successful when it is structured in such a way that the various stakeholders can see themselves and their roles articulated in these narratives. The skill of persuasion through storytelling is therefore vital. What CG4 has shown itself capable of is the creation of remarkable story narratives that can be endlessly honed and embellished upon. We should expect to see
  • new multi-media messaging that is totally realistic and lifelike with individuals with the likenesses of public individual;
  • narratives that will be described as disinformation or fake news;
  • entertainment media using story-book format; these will include narrative text as well as imagery;
  • libraries of instructions will become available that will allow a user to create or refine imagery of their choice;
• Novel capabilities. If one were to spend just a few minutes interacting with CG4 one can come away with the impression that this is a system capable of teaching at university level. We should expect that this trend will simply continue. Therefore it is hardly farfetched if we see new products emerge with unexpected qualities and capabilities. To make this supposition more concrete we might imagine work being performed using carbon nanotube fabrication.
  • Carbon Nanotubes. The 1968 John Brunner novel Stand on Zanzibar introduced what was then the possibility of a mono-filament thread; this thread required extremely careful handling because it had the inherent quality of having extremely powerful molecular bonding along its length; this enabled it to be used as a saw; the users of such as monofilament material was capable of slicing through any known material - including diamonds. In the novel so-called "partisans" were able to buy and sell lengths of this material as well as equipment required to handle it on a black market. Current carbon nanotube strands have shown strengths that exceed that of spider's silk by a factor of one hundred; Therefore it might not be out of the question that very novel materials of unique qualities might emerge as a result of intensive design sessions with a CG4 type capability that is optimized in the direction of materials science;
  • Psycho-Actives. In the same novel Brunner posited the availability of psych actives substances that when introduced to a willing subject enabled a highly refined ability to focus attention. One of the books main characters was subjected to this form of training called eptification; this was a highly intensive form of training that imparted very specialized skills in a dramatically shortened time frame; the person who had been eptified could flawlessly perform at the same level as the expert who had taught them. In the story line an individual with a very high level of education in genomics has spent years on inactive duty; he is unexpectedly summoned to active duty; within a matter of days he is trained to perform at the level of a master level kung-fu black belt; he is then directed to investigate a claim by a South Asian scientist who claims to have devised the ability to "optimize" any embryo and remove any hereditary defects such as Tay-Sachs or Cystic Fibrosis or other inherited problems. In the storyline of the novel, individuals with identifiable genetic defects were denied a license to procreate. The upshot therefore meant that there was an extremely high value placed upon proving that the scientist's claim was true or not - including if necessary kidnapping him to acquire his knowledge and insights.
  • Cambrian Explosion. As of April 2023 reports are indicating that CG4 is being used in a continually broadening range of activities and settings. Most recently Microsoft announced that it would be including CG4 in its Bing search tool; Khan Academy has announced that it will be incorporating CG4 as an integral element in its delivery of educational content. Bain and Company, a major business consulting firm is using CG4 to help manage work-flow at Coca-Cola. The pathway forward may result in an entirely new ecosystem of tools, add-ins and API components; the result will be that there will be an entirely new dimension for existing tools such as spread-sheet add-ins as well as hacker intrusion construction tools will presently materialize.
  • Agents.

Notes References Deep Learning Models. There are many variations on the deep learning network architecture models current today.

OpenAI released an earlier version of GPT4 in 2021 named GPT3. This transformer based model had been trained on 175 billion parameters. This made it one of the larger deep learning tools of the time. OpenAI released it for public usage and subsequently offered to the public the conversational ChatGPT3.5. GPT3 (OpenAI) The importance of this model was such that it gained one million users worldwide within four days. This very rapid uptake had not been seen in online systems such as Facebook or Youtube. Within several weeks its usage had leapt to 100 million users worldwide.

Several text-to-image systems have been released for public use such as Midjourney. This tool is capable of accepting a user input that verbally describes a scene or setting to be rendered. Midjourney is able to accept this input and produce a rendering of its interpretation of what the user described. The user can iteratively refine the image to the point that it is acceptable. Another major player in the text-to-image space is the Stable Diffusion tool. Like Midjourney it is able to accept a textual description of what the user wanted and attempt to render an image for it. Like Midjourney the user can iteratively refine the result. Recent (as of April 2023) news reports have indicated that individual who make their living using their artistic talents have filed class actions suits against these tools citing that it endangers their livelihood.

Generative Pre-Trained Transformers. A transformer is a deep learning model that adopts the mechanism of self-attention, differentially weighting the significance of each part of the input (which includes the recursive output) data. It is used primarily in the fields of natural language processing (NLP) and computer vision (CV).

The top ten types of deep learning models include:

• multilayer perceptrons (MLPs)
• radial basis function networks (RBFNs)
• convolutional neural networks (CNNs)
• recurrent neural networks (RNNs)
• long short-term memory networks (LSTMs)
• restricted boltzmann machines (RBMs)
• self organizing maps (SOMs)
• generative adversarial networks (GANs)
• autoencoders deep learning algorithm
• deep belief networks