Test Information Space
(Gemini Deep Research: review of Callard, 2025, from secondary sources. The conclusion sums up the terms. See the book's Table of Contents for more. Also, Gemini 2.5 Pro can look for uniqueness of the author's interpretation of the Socratic Method. Or the dialectical styles and tensions of the popular Chatbots, for that matter. Gemini Personalization model can talk about the user's, hinting at core beliefs/interests, based on their history. Related references might include Penn's Writing the Shadow, or Allen's Why Plato Wrote. On a rhetorical triangle of speaker/content/audience, this might be somewhere between Quora and POE. Rather than only a synthesis like Plato or Hegel, or aporia like Derrida, this might look for alternatives. Google AI Mode casts this framework as a contrast to Aristotle's eudaimonia based on endoxa.)
(How might image generators solve p;problems?
Elsewhere people used to read a lot, courses were gut or food for thought. Now social media is prevalent, so how is that used?
Robots are still unnerving.
In any case, Godel remains, and cybernetics. Where is the determinism? Can any element remotely know another without the direct prompt? Or would that have to become a function of long-term evolution. In which case, what are the competing or environmental factors?
Thiis may become interesting when robots like Optimus are sent on long-range missions such as Mars without humans around and occasionally on comms. How can that be tested more locally ahead of time? Other than by starving them of resources.
Who picks the missions? Scary version.
Perhaps a Tyrell origin story. Old Norse or French.
Who picks Tyrell?
What is the implicit goal?
Incidentally, early on, Minsky reportedly favored tele-presence. Others later looked at expert systems. Assuming they are not hallucinating, machines are also capable of augmented or mixed reality. How do they know the difference? How do people, in either sense? Other than biases.
Or Space Force interns go DOGE versus Delphi mode.
Backtracking through the plan, from results to analysis or methods, how do they pick better questions or problem sets?
Does self-reporting evidence subjectivity?
Are there Platonic or universal prompts or are they personalized or localized? Can those be made equivalent through a dictionary?
Is this another form of mimicry where the collaborating or training partner or source is then removed? Expecting Enlightenment. At least pattern affinity.
Why AI?)
Perplexity Summary given link to PDF: Here's a summary of the findings from the Conversica "2025 AI & Customer Experience Report":
Overall Focus: The report explores how conversational AI impacts customer behavior, satisfaction, and trust, aiming to guide companies in integrating AI into their marketing and sales processes. The research is based on a survey of 508 consumers and business buyers, 13 in-depth interviews, and a 12-person focus group.
Key Findings:
- Helpfulness:
- A majority (56.7%) of buyers find AI helpful.
- 67.7% believe AI accurately understands their needs at least half the time.
- Business buyers perceive AI as more helpful than non-business buyers.
- Convenience and speed are top reasons for interacting with AI.
- Accuracy is crucial; frustration arises when AI provides incorrect answers.
- When AI can't handle complex issues, users want to connect with a human.
- Timing and Topics:
- Customers prefer AI early in the purchasing process (exploration phase), valuing its 24/7 availability and low-pressure support.
- AI is favored by 21% more respondents than humans during the exploration phase.
- However, human representatives are still preferred for complex issues.
- AI's always-on availability is a significant advantage.
- Business buyers are most comfortable using AI for software purchases.
- Companies should balance AI and human interaction.
- Trust:
- Security risks (40%) and fear of inaccuracy (41%) are major deterrents to AI interaction.
- Users are hesitant to share sensitive data due to uncertainty about data usage.
- Distrust grows when AI struggles with complex issues.
- Transparency about interacting with AI (vs. a human) is important for building trust.
- Openness to AI in the Sales Process:
- Both B2B and B2C buyers increasingly prefer AI agents over humans in the early stages.
- Human involvement remains essential in the final "ready to buy" stage.
- Business buyers consistently prefer AI throughout the sales funnel more than non-business buyers. B2C buyers favor AI at a 3:1 ratio in the initial "exploration" phase.
Methodology: The study used a mixed-method approach, including surveys, in-depth interviews, and focus groups. Participants in the interviews and focus groups were college students in Provo, Utah. Survey respondents were US consumers aged 18 and over.