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 or are saying:
  • keep moving!
  • caution, risks ahead!
  • potential land mines ahead!;
  • damn the torpedoes, full speed ahead!;
• 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.
• An inflection point either has or momentarily will be or has been reached;
• mitigating surprise the concerned community would be well advised to regularly monitor the archive for papers so as to mitigate the gain early warning;
• Imaginative expectation is advised because novel combinations are emerging that will herald entirely new forms of CP capabilities; most of which can not be guessed at as of this writing (Fall 2023);
• Quantum Computing will upend all expectations. As of this report the major actors in this space have already reported advances. In the case of the IBM corporation their Quantum System Two may very well shatter all expectations. Current indications are that deep learning tools can be hosted on these new environments. At that point in time the ability of a deep learning CP based tool will take on qualities that can not now be estimated. Current training times have been reported to have required weeks to months to train as was the case of CG4. These times may now collapse to seconds or less.
• Pseudo-AGI (PAGI) might be a way to envision what to expect. This terminology is intended to suggest that the term AGI might be too simplistic and may require further analysis and refinement.
  • Quantum Based CP (QBCP)should be expected given that existing or soon-to-be commercialized systems will become the next logical environment in which to host CPs;
  • QBCP will show instant performance improvements; training data set or sets that have required weeks to months could be incorporated instantly;
  • Intelligent interfacing tools that can capitalize on a broad range of theory of mind could minimize the interval between end user motivation hypothesis and action plan to mere instants; such a capability might appear to even an expert user like interacting with an extremely well versed, empathetic and supportive colleague;
  • Autonomous QBCP/PAGI networking' might be a means whereby multiple QBCP's might form either ad hoc or permanent communications pathways between themselves in order to provide user groups or communities with responses; the quality of queries that a user community might pose will as always be limited to the quality and depth of knowledge of that community;
  • exponential growth - Cambrian explosion no capabilities such as this have yet been reported; yet there appear to be no obstacles to their development; the rise of
  • these kinds of composite CP's may not yet have been reported on; however the observant reader should not preclude their immanent arrival;
  • Darwinian evolution AGI may have yet to arrive; however close approximations may soon become evident; we could see an accelerated Moore's Law of evolution where problems that have heretofore taken months or years to solve might not only be solved in a morning but that highly sophisticated access and control tools might become commonly available mid-afternoon;
• High ground.The reality of a near-pear in the guise of a demonstrably hostile CCP urges caution;
  • knowledgeable observers have provided numerous reports of CCP hacking and related malicious efforts;
  • CCP literature and propaganda has made very clear that the West is an obstacle and that the US is the prime target;
  • demonstrated practices on the part of PRC companies to demand access to corporate IPR are numerous; therefore
  • anticipating that the PRC will attempt to neutralize the best efforts from the West can safely be assumed; otherwise we in the West risk seeing experiencing disruptive or devastatin pre-emptive actions against our corporate and defense capacities from means or techniques that our best and brightest find mysterious and unfathomable.
• 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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