ChatGPT4-Questions/User:Darwin2049/Overview

OpenAI - ChatGPT4.
In what follows we attempt to address several basic questions about the onrushing progress with the current focus of artificial intelligence. There are several competing actors in this space. These include OpenAI, DeepMind, Anthropic, and Cohere. A number of other competitors are active in the artificial intelligence market place. But for purposes of brevity and because of the overlap we will limit focus on ChatGPT4 (CG4). Further, we focus on several salient questions that that raise questions of safety, risk and prospects.
Specifically, risks that involve or are:

• Interfacing/Accessibility-Conformability - Synthesis. how will different groups interact with, respond to and be affected by it; might access modalities available to one group have positive or negative implications for other groups;
• Political/Competitive - Synthesis. how might different groups or actors gain or lose relative advantage; also, how might it be used as a tool of control;
• Evolutionary/Stratification - Synthesis. might new classifications of social categories emerge; were phenotypical bifurcations to emerge would or how would the manifest themselves;
  
• Epistemological/Ethical Relativism - Synthesis how to reconcile ethical issues within a society, between societies; more specifically, might it provide solutions or results that are acceptable to the one group but unacceptable to the other group;
  

Synthesis.
Responding to these questions calls for some baseline information and insights about the issues that this new technology entails. We propose to suggest we look

• Impressions that has been expressed by knowledgeable observers; a short sampling of impressions and perceptions include voices that are
  • in favor of rapid and forceful development
  • expressing caution
  • are urging extreme caution going forward;
  • pointing to extreme external risks and urging rapid further development;
• Caveats.
  After assessing the range of sentiment from very well informed observers and experts our conclusion is that a summary of caveats and qualifications might help in constraining and focusing the discussion going forward.
  

What does become evident is that even as the informed community is watching this new technology advance there are concerns and observations that suggest that our expectations be conditions to at least attempt to mitigate the surprises that are even as of this writing appearing on the horizon. The most recent developments and advances are suggesting further upsets to come. Advances in the underlying technology of computing in the guise of quantum computing point to the inevitability of a dramatic shift in the power of analysis and cognitive tools. Attempting to qualify, quantify or articulate these nascent developments is maximally challenging. Therefore siding with the camp that favors the most rapid all of national resources toward achieving the high ground is obvious.

• Terms, Theory of Operation of technology paradigm used to produce its results;
  • concepts are presented that contrast large language models with generative and generative adversarial models;
  • several other deep learning models are summarized as well for the purpose of further context;
  • LLM operation is sketched out in this section; several helpful video segments are presented that are intended to further facilitate why the LLM approach has become so successful; **novel and unexpected forms of emergent behavior are mentioned;
    
• Risks our approach has been to present a few commonly occurring risks,
  • that are inherent, organic and systemic with any new revolutionary science or technology
  • those that arise spontaneously as a result of malicious actors and
  • those that are theoretical;
• Intermediate Considerations. If we step back for a moment and summarize what some observers have had to say about this new capability then we might tentatively start with that:
  • is based upon and is a refinement of its predecessor, the Chat GPT 3.5 system;
  • 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; unconfirmed rumors suggest that it has been trained on 1 trillion parameters;
  • 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;

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