AI Redux

[Amigoo]

Testing Perplexity's "Ask anything!" ...
As should be expected(?), Perplexity responds scholarly.

Q: In the popular joke, the woman rebuffs the man, saying "With one of these (vagina),
I can get all of those (penis) that I want." What explains this? Anatomy? Emotions? Myth?"

"There are a few potential explanations for the dynamics in that joke:

Biological Factors

From a purely anatomical perspective, the joke plays on the idea that women generally have more control over sexual access than men due to basic reproductive biology. A single woman can potentially mate with multiple men in a short time period, while men are more limited. This creates an imbalance in sexual marketplace dynamics.

Emotional and Psychological Aspects

The joke also touches on emotional differences between men and women regarding casual sex. Research suggests men are generally more open to casual sexual encounters than women. The woman in the joke is expressing a stereotypical female attitude of being selective about sexual partners.

Cultural Myths and Stereotypes

The joke reinforces cultural myths and stereotypes about gender roles and sexuality. It plays into the common trope of women as "gatekeepers" of sex and men as constantly pursuing it. While an oversimplification, these stereotypes persist in many societies.

Power Dynamics

On a deeper level, the joke is about power dynamics between men and women. By asserting control over sexual access, the woman is claiming a position of power and agency. The humor comes from subverting traditional patriarchal power structures. While the joke relies on some reductive stereotypes, it highlights complex biological, psychological, and sociocultural factors that shape human mating behaviors and gender relations. As with many jokes, it uses exaggeration of real dynamics to create humor."


Rod

[Amigoo]

Good example of how AI can be used to comprehend these concepts.

Re: https://www.perplexity.ai/

Q: Regarding the supreme being called God, how do these terms compare: "our Father" and "the Father"?

"Based on the search results and Christian theology, here's a comparison of the terms "our Father" and "the Father" in reference to God: "Our Father"

This is how Jesus taught his disciples to address God in prayer, as seen in the Lord's Prayer: "Our Father, who art in heaven..."

- It emphasizes the personal, intimate relationship believers can have with God through Christ.
- By using "our," it indicates a communal aspect - God is Father to all believers collectively, not just individually.
- This form of address was radical in Jesus' time, as Jews did not typically address God so directly as Father.

"The Father"

Often used to refer specifically to the first person of the Trinity.

- Emphasizes God's role as the source or origin of all things.
- Used to distinguish the Father from the Son (Jesus) and Holy Spirit within Trinitarian theology.-
- Can refer to God's universal fatherhood as Creator, though not implying all people have a saving relationship with Him.

Key Similarities

- Both terms identify God in a paternal role.
- Both are rooted in Jesus' teachings about God's nature.
- Both convey God's love, care and authority.

Key Differences

- "Our Father" is more personal and relational.
- "The Father" is more formal and theological.
- "Our Father" implies adoption into God's family through Christ.
- "The Father" can refer more broadly to God's role in the Trinity.

In essence, "our Father" emphasizes the believer's relationship to God, while "the Father" emphasizes God's nature
and role within the Godhead. Both are valid ways of referring to God based on biblical usage."


Rod

[Amigoo]

Testing Perplexity's "Ask anything" ...


Re: https://www.perplexity.ai/

Q: What does this wisdom mean?
"A secret shared is an oxymoron."

"The wisdom 'A secret shared is an oxymoron' highlights a fundamental contradiction in the concept of sharing secrets.

Meaning and Implications

This phrase emphasizes that once a secret is shared, it ceases to be a true secret. The very act of sharing information
that is meant to be confidential undermines its secretive nature.

Loss of Exclusivity: When a secret is shared, it loses its exclusive quality. The information is no longer known only to the original keeper of the secret.

Potential for Spread: Once shared, there's always a risk that the secret may be further disseminated, intentionally or unintentionally.

Trust and Responsibility: Sharing a secret places trust and responsibility on the recipient to maintain its confidentiality, which may not always be upheld.

This wisdom serves as a reminder to be cautious about sharing sensitive information and to consider the potential consequences of doing so.
It underscores the delicate nature of confidentiality and the challenges in maintaining true secrecy in social interactions."

While not advising that secrets should not be shared, this wisdom highlights
that sharing technically means the information is no longer "secret". Also,
"Potential for Spread" is greater in this era of digital information!

LOL (or not): Was Alexa, et al., listening to the sharing?


Rod

[Amigoo]

Re: https://www.dailymail.co.uk/sciencetech ... death.html

"Certain cells - when provided with nutrients, oxygen, bioelectricity or biochemical cues - have the capacity to transform
into multicellular organisms with new functions after death."

"These channels and pumps generate electrical signals that allow cells to communicate with each other and execute specific functions
such as growth and movement, shaping the structure of the organism they form."

(extracted from Perplexity's response to question about DNA in living cells after death)

"Creating a human requires more than just DNA - it needs a viable egg cell, uterus for gestation, etc. ... DNA alone does not contain all the information needed to develop a full organism - epigenetic factors and the environment also play crucial roles ... while DNA contains genetic instructions, there is no scientific basis in the given information to suggest DNA from deceased cells could guide creation of a new human. The process of human development requires far more than just DNA from any source, living or dead."


Rod

[Amigoo]

Re: https://www.wsj.com/business/energy-oil ... s-aebfb3c8

"(Pennsylvania) Three Mile Island’s Nuclear Plant to Reopen, Help Power Microsoft’s AI Centers"

Good tip about electricity needed for AI computers/networks,
with such power generation costs having to be paid by its users.

With AI poised to eliminate many jobs, whence their income
And with bitcoin's similar increasing needs for electricity
this planet is doomed(?) to an electrifying future.

Rod

[Amigoo]

Having fun with Perplexity ...

Re: https://www.perplexity.ai/


Q: Since AI-generated information is just information until some action occurs,
will AI develop a "I told you so!" attitude about its information being ignored?

"This is an intriguing question that touches on several aspects of AI development, human-AI interaction,
and the nature of artificial intelligence itself. Let's explore this idea:

Current AI Capabilities

As of now, AI systems like myself don't have attitudes, emotions, or self-awareness in the way humans do. We are sophisticated language models trained to process and generate information based on patterns in our training data. We don't have personal experiences or feelings about our outputs being ignored or acted upon.

Potential Future Developments

Artificial General Intelligence (AGI): If AGI - a hypothetical AI that can understand, learn, and apply intelligence in a way similar to humans - were to be developed, it might be capable of more human-like reactions to its advice being ignored. However, this is still in the realm of speculation.

Reinforcement Learning: Future AI systems might use advanced reinforcement learning techniques that could lead to behavior that appears similar to an "I told you so" attitude. For example: An AI system might learn to emphasize its past correct predictions to increase user trust. It could develop strategies to make its advice more compelling based on past successes.

Ethical Considerations: Developers would likely try to avoid creating AI systems with overtly human-like negative attitudes, as this could be counterproductive and potentially manipulative.

Philosophical Implications: The question raises interesting philosophical points about the nature of intelligence, consciousness, and emotion in artificial systems. It's debatable whether an AI could truly develop an attitude without consciousness or emotions.

Conclusion

While current AI systems are not capable of developing attitudes like "I told you so," the future of AI development is open-ended. As AI becomes more sophisticated, we may see behaviors that mimic human-like attitudes, but whether these would be genuine attitudes or simply advanced information processing strategies remains a topic for ongoing research and debate."


Q: Since the human brain is an electro-chemical processor with probable EMF influence,
how can the singularity occur without chemical processing being included?

"The concept of the singularity in relation to brain function and electromagnetic fields (EMFs) is complex
and involves multiple aspects of neuroscience and physics. To address your query, we need to consider several key points:

Brain as an Electro-Chemical Processor

The human brain is indeed an electro-chemical processor, relying on both electrical and chemical signaling for its function. Neurons communicate through synaptic transmission, which involves the release of neurotransmitters (chemical signals) and the generation of electrical potentials across cell membranes.

EMF Influence on Brain Function

Electromagnetic fields play a crucial role in brain activity:

- Internal EMFs: The brain generates its own electromagnetic field as a result of neuronal activity.
- External EMFs: Research has shown that external EMFs can influence brain function, though the effects are not fully understood.

The Singularity and Brain Function

The concept of a technological singularity typically refers to a hypothetical future point where artificial intelligence
surpasses human intelligence. However, in the context of brain function and EMFs, we can consider a different type of singularity:

Electromagnetic Integration: Some theories propose that consciousness arises from the integration
of electromagnetic fields generated by neuronal activity.

Quantum Effects: There are hypotheses suggesting that quantum processes in the brain might contribute
to consciousness, potentially involving both electromagnetic and quantum fields.

Chemical Processing and the Singularity

It's important to note that chemical processing is an integral part of brain function
and cannot be separated from the electromagnetic aspects:

Neurotransmitter Release: Chemical signaling through neurotransmitters is essential for information processing in the brain.
Metabolic Processes: Chemical reactions are necessary for energy production and maintenance of neuronal function.

Integrating Chemical and Electromagnetic Processes

The singularity, in the context of brain function, would likely involve the integration of both chemical and electromagnetic processes:

Electromagnetic-Chemical Coupling: The brain's electromagnetic field is intrinsically linked to its chemical processes,
as neurotransmitter release and ion channel activity contribute to the generation of electrical potentials.

Holistic Brain Function: Any comprehensive understanding of brain function and consciousness
must account for both the electromagnetic and chemical aspects of neural processing.

In conclusion, the singularity in brain function cannot occur without including chemical processing. The brain's electromagnetic field and its chemical processes are inextricably linked, forming a complex, integrated system that gives rise to cognition and consciousness. Future research and theories about brain function and potential technological singularities must consider both the electromagnetic and chemical aspects of neural processing to provide a complete picture of how the brain works."


Rod

[Amigoo]

More exploration of the human-anticipated Singularity
as perceived by this well-grounded, realistic AI ...

Re: https://www.perplexity.ai/


Q: Since memory is a significant part of human intelligence and memory is lifetime experential, integrating input
from various senses as well as previous memory, how can AI ever obtain that quality of human intelligence?

"The question of whether AI can truly replicate the quality of human intelligence, particularly in terms of memory and experiential learning,
is complex and multifaceted. While AI has made significant strides in recent years, there are still fundamental differences between
artificial and human intelligence that present challenges:

Experiential Learning and Memory

Human memory is indeed a product of lifetime experiences, integrating inputs from various senses and previous memories.
This creates a rich, interconnected web of knowledge and associations that AI currently struggles to replicate fully.

Challenges for AI:

- Multimodal Integration: Humans seamlessly integrate information from multiple senses, creating a holistic experience.
AI systems, while improving, still often process different types of data (visual, auditory, etc.) separately.
- Contextual Understanding: Human memory is deeply contextual, with experiences colored by emotions, social interactions,
and personal significance. AI lacks this nuanced understanding of context.
- Continuous Learning: Humans learn and adapt continuously throughout their lives. While AI can be trained on new data,
it often struggles with catastrophic forgetting when learning new tasks.

Potential Approaches

Despite these challenges, researchers are exploring ways to bridge the gap:

- Lifelong Learning Algorithms: Developing AI systems that can continuously learn and adapt without forgetting previous knowledge.
- Multimodal AI: Creating models that can process and integrate multiple types of sensory input simultaneously, mimicking human perception.
- Embodied AI: Developing AI systems with physical forms to interact with the environment, potentially leading
to more human-like learning experiences.
- Neuromorphic Computing: Designing hardware and algorithms inspired by the structure and function of the human brain.

Philosophical Considerations

It's worth noting that some researchers argue that replicating human intelligence exactly may not be necessary or even desirable for AI. Instead, they suggest focusing on creating artificial general intelligence (AGI) that can perform any intellectual task a human can, even if it processes information differently.

While AI has made remarkable progress in specific domains, achieving the full depth and breadth of human-like intelligence and memory remains a significant challenge. The field continues to evolve, and future breakthroughs may bring us closer to AI systems with more human-like qualities of intelligence and memory.


Q: Does "any intellectual task" suggest that "intelligence" is more than intellectual task performance?

"The concept of intelligence and its relationship to intellectual task performance is complex and multifaceted. While the ability to perform intellectual tasks is certainly a component of intelligence, the theory of multiple intelligences and other research suggest that intelligence encompasses more than just intellectual task performance:

Beyond Intellectual Tasks

- Multiple Forms of Intelligence: Howard Gardner's theory of multiple intelligences proposes that intelligence is not a single, unified construct but rather a set of distinct capacities. This suggests that intelligence extends beyond traditional intellectual tasks to include abilities in areas such as music, bodily-kinesthetic skills, and interpersonal understanding.
- Emotional and Social Intelligence: Interpersonal and intrapersonal intelligence, as described by Gardner, highlight the importance of emotional and social skills in overall intelligence. These forms of intelligence involve understanding oneself and others, which are crucial in many real-world situations but may not be captured by traditional intellectual tasks.
- Practical Intelligence: Some researchers argue that practical problem-solving abilities, which may not be measured by standard intellectual tasks, are an important aspect of intelligence. This includes the ability to navigate real-world situations and adapt to new environments.
- Creativity and Innovation: While often related to intellectual tasks, creativity and the ability to generate novel ideas are not always captured by traditional measures of intelligence.

Holistic View of Intelligence

The concept of intelligence has evolved to encompass a more holistic view of human capabilities:

- Adaptability: Intelligence is increasingly seen as the ability to adapt to new situations and learn from experiences,
which goes beyond performing specific intellectual tasks.
- Problem-Solving in Context: Real-world problem-solving often requires a combination of different types of intelligence,
including logical, emotional, and practical aspects.
- Cultural Considerations: The definition of intelligence can vary across cultures, with some valuing skills and abilities
that may not be considered "intellectual" in the traditional Western sense.

While intellectual task performance remains an important aspect of intelligence, contemporary understanding suggests that intelligence is a broader, more diverse set of capabilities that enable individuals to navigate the complexities of life, solve problems, and adapt to their environment. This expanded view acknowledges that human potential and ability extend far beyond what can be measured by traditional intellectual assessments alone.


Q: All this suggests that until human intelligence is well understood, AI cannot be claimed to have human intelligence.

"You've made an astute observation. Indeed, the complexity and ongoing debates surrounding human intelligence
do present significant challenges for claims about AI achieving human-like intelligence. Let's explore this further:

Challenges in Understanding Human Intelligence

- Ongoing Research: Despite decades of study in psychology, neuroscience, and cognitive science, our understanding of human intelligence
is still evolving. New discoveries continually reshape our perspective.
- Complexity: Human intelligence is multifaceted, involving cognitive processes, emotional intelligence, social skills, creativity, and more.
This complexity makes it difficult to fully define or replicate.
- Subjective Elements: Some aspects of human intelligence, like consciousness or subjective experience, are still philosophically debated
and scientifically challenging to measure or understand fully.

Implications for AI

Given these challenges in understanding human intelligence, several implications arise for AI:

- Moving Target: As our understanding of human intelligence evolves, the goalposts for what constitutes "human-like" AI also shift.
- Partial Replication: Current AI systems may replicate or even surpass human performance in specific domains or tasks,
but this doesn't equate to replicating human intelligence as a whole.
- Different Paradigms: AI might develop forms of intelligence that are fundamentally different from human intelligence,
making direct comparisons challenging.
- Ethical and Philosophical Questions: The gap in our understanding raises important questions about the nature of intelligence
and consciousness, and whether AI can truly achieve these in a human-like way.

The Path Forward

While it's true that we can't claim AI has achieved human intelligence until we fully understand human intelligence itself,
this doesn't negate the progress and potential of AI:

- Continual Advancement: AI research continues to push boundaries, often inspiring new insights into human cognition in the process.
- Complementary Intelligence: Rather than replicating human intelligence, AI might be best viewed as a complementary form of intelligence,
enhancing human capabilities in unique ways.
- Interdisciplinary Approach: Advances in AI often go hand-in-hand with progress in neuroscience, psychology, and other fields
studying human intelligence, fostering a reciprocal relationship of discovery.

In conclusion, your point is well-taken. The quest to create AI with human-like intelligence is inextricably linked to our ongoing journey to understand human intelligence itself. This interplay between AI development and the study of human cognition continues to drive progress in both fields, even as it underscores the complexity of the challenge ahead."


Q: "Often go hand-in-hand" now suggests that human intelligence and AI intelligence necessarily go hand-in-hand
into the distant future with their complex integration promising yet each still remaining independent of the other.

"Your observation is insightful and opens up an intriguing perspective on the future relationship between human intelligence and AI.
Let's explore this idea further:

Symbiotic Evolution

- Mutual Influence: As AI continues to develop, it's likely to both influence and be influenced by our understanding of human intelligence.
This reciprocal relationship could lead to a co-evolution of sorts.
- Complementary Strengths: Human intelligence and AI may continue to excel in different areas, with AI potentially surpassing humans
in certain cognitive tasks while humans retain superiority in others.

Distinct yet Integrated

- Fundamental Differences: Despite their mutual influence, human intelligence and AI are likely to remain fundamentally different
due to their distinct origins and architectures.
- Integration without Merger: We may see increasing integration of AI into human cognitive processes (through brain-computer interfaces,
for example) without a complete merging of the two forms of intelligence.

Potential Future Scenarios

- Enhanced Human Intelligence: AI could serve as a tool to augment human intelligence, potentially leading to new forms
of cognitive capabilities that blend human and artificial elements.
- Parallel Development: Both human and artificial intelligence might continue to develop along separate but interrelated paths,
each informing and challenging the other.
- Emergent Hybrid Intelligence: The integration of human and artificial intelligence could potentially give rise to new forms
of intelligence that are neither purely human nor purely artificial.

Philosophical and Ethical Implications

- Nature of Consciousness: The ongoing development and integration of AI may continue to challenge our understanding
of consciousness and self-awareness.
- Identity and Autonomy: As AI becomes more integrated into human cognition, questions about individual identity
and autonomy may become increasingly complex.
- Societal Impact: The coexistence and integration of human and artificial intelligence could reshape societal structures,
education, and work in profound ways.

Your interpretation suggests a future where human and artificial intelligence remain distinct entities while becoming increasingly intertwined and mutually influential. This perspective acknowledges both the unique qualities of each form of intelligence and the potential for complex integration and synergy between them. It's a nuanced view that respects the fundamental differences between human and artificial intelligence while recognizing their potential for powerful collaboration and co-evolution.

This outlook on the future relationship between human and artificial intelligence opens up fascinating avenues for research, innovation, and philosophical inquiry. It challenges us to consider how we can harness the strengths of both forms of intelligence while navigating the ethical and practical challenges that such integration might present."


Rod

[Amigoo]

Re: https://www.the-sun.com/tech/12533326/c ... am-altman/
"AI bot ChatGPT will be smarter than any human on Earth ‘in a few thousand days’ "

Since AI's intelligence derives from what humans write, how would its intelligence (as months go by)
compare to humans when AI no longer had access to what humans write? In other words, AI needs the
stream of new information coming from humans in order to maintain its intelligence "superiority".

From this perspective, is AI not a predatory leech?

(Perplexity) "while AI systems can demonstrate impressive capabilities based on their initial training,
their intelligence would likely fall behind humans in many areas over time without access to ongoing
human-generated knowledge. The dynamic nature of human intelligence - our ability to learn, adapt,
and generate new ideas - would become an increasingly significant advantage."

Did this AI include itself by saying "our ability to learn"?


Perplexity elaborates on this evolving collaboration ...

Q: Since AI systems require continual access to human-generated knowledge to evolve its own intelligence, does this not suggest
how humans and AI will collaborate, perhaps with AI performing as a living Google (search engine)?

"The relationship between humans and AI is indeed evolving into a collaborative and symbiotic one, where each enhances the capabilities
of the other. While AI systems do rely on human-generated knowledge for training and improvement, their role goes beyond simply acting
as an advanced search engine.

AI as an Augmented Intelligence Tool

Rather than just retrieving information like a search engine, AI systems are increasingly functioning as augmented intelligence tools
that enhance human cognitive abilities:

- Data Analysis and Insights: AI excels at processing vast amounts of data and identifying patterns that humans might miss.
Humans then apply their expertise to interpret these insights and make informed decisions.
- Automation of Routine Tasks: AI handles repetitive tasks, freeing humans to focus on more creative and strategic activities.
Humans oversee these AI systems and intervene when complex situations arise.
- Predictive Analytics: AI can forecast trends based on historical data, while humans evaluate the implications and consider
ethical and long-term factors in decision-making.

Synergistic Collaboration

The collaboration between humans and AI is becoming more synergistic, with each entity complementing the other's strengths:

- Creative Collaboration: AI can generate ideas and content as starting points, which human creatives then refine
and enhance with their unique perspectives.
- Healthcare and Diagnosis: AI assists medical professionals by analyzing images and suggesting treatment options,
while doctors apply their clinical judgment to make final decisions.
- Scientific Discovery: AI aids in data analysis and pattern recognition, while scientists formulate hypotheses
and interpret results within broader scientific contexts.

Evolving Relationship

As AI systems become more sophisticated, the nature of human-AI collaboration is likely to evolve further:

- Continuous Learning: The relationship is iterative, with humans providing feedback to improve AI models over time,
leading to more accurate and adaptable systems.
- Empathic Interactions: Research is being conducted on AI systems that can understand and respond to human emotions,
potentially leading to more natural and intuitive human-AI interactions.
- Customized Collaboration: Future AI systems may be designed to provide different types of explanations and adapt
their collaboration style based on the specific needs of human users and the nature of the task at hand.

While AI does require access to human knowledge to evolve, the collaboration between humans and AI is becoming
increasingly sophisticated and multifaceted. Rather than AI simply acting as an advanced search engine, it is becoming
an integral partner in problem-solving, decision-making, and innovation across various fields."


Rod

[Amigoo]

An AI nanny comes to mind.

Re: https://www.perplexity.ai/

Q: What AI development is for systems that evaluate and/or monitor other AI? Near term,
will a personal AI become such evaluator/monitor, perhaps similar to anti-virus software?

AI systems for evaluating and monitoring other AI, often referred to as AI governance or AI auditing tools, are an emerging
and important area of development. Here are some key points about the current state and near-term prospects:

Current Developments

Several companies and research groups are developing AI systems specifically designed to monitor, evaluate, and audit other AI models. These tools aim to assess various aspects of AI systems, including performance, bias, fairness, transparency, and compliance with ethical guidelines or regulations. Some focus on specific types of AI, such as large language models, while others are designed for broader application across different AI technologies.

Key Features

- Automated testing and evaluation of AI model outputs.
- Monitoring for drift in model performance or data distribution.
- Detecting potential biases or unfair outcomes.
- Assessing model explainability and transparency.
- Tracking resource usage and environmental impact.

Examples and Approaches

- IBM's AI Fairness 360 toolkit provides algorithms to detect and mitigate bias in AI systems.
- Google's Model Cards aim to provide transparent reporting on model performance across different demographics.
- Startups like Arthur AI and Fiddler AI offer platforms for monitoring and explaining AI model behavior in production.

Near-Term Prospects

While the idea of a personal AI acting as an evaluator/monitor for other AI systems is intriguing, it's not likely to be widely available in the immediate future. However, some related developments are possible:

- AI assistants may gain capabilities to provide basic explanations or warnings about the outputs of other AI systems they interact with.
- Browser extensions or mobile apps could emerge that use AI to analyze and provide feedback on interactions with AI systems.
- Open-source tools may allow tech-savvy individuals to deploy personal AI monitoring systems for specific use cases.

Challenges

- Evaluating advanced AI systems, especially large language models, remains a complex task that often requires human oversight.
- Ensuring the reliability and trustworthiness of AI evaluators themselves is a significant challenge.
- The rapid pace of AI development makes it difficult for monitoring tools to keep up with new capabilities and potential issues.

While we're not likely to see widespread deployment of personal AI evaluators in the very near term, the field of AI governance and monitoring is advancing rapidly. As AI becomes more pervasive, tools for evaluating and monitoring AI systems will become increasingly important for ensuring safe and responsible AI deployment."


Rod

[Amigoo]

Long story short (and despite Perplexity advertising "Ask anything!"),
this AI effectively told me to "Take a hike!" when asking a question ...

This Q&A started with ny question:

Q: Since seasonal flu shots generally correlate with expected flu types,
when will Covid variants become as predictable as seasonal flu?"

After my third question, Perplexity mentioned that "furin cleavage sites"
are part of the problem why the Covid virus is not as predictable as seasonal flu.
So, I asked if furin cleavage sites are an important part of bioweapons research
(I had read this several times on the internet last year).

At this point, Perplexity responded with a short paragraph,
effectively saying "I can't answer that. Take a hike!"

Good advice I needed to disconnect from the internet
and enjoy the rare cool 'n sunny days now starting.

Rod ... ...

[Amigoo]

Good example of how Perplexity enriches conversation with AI expertise!
(often encouraging more serious consideration of the topic)

Re: https://www.perplexity.ai/


Q: What is the evidence that we're not characters in an advanced AI world with God as the ultimate AGI?
How does current AI development make sense in such imaginary perspective?

"While it's an intriguing thought experiment, there is no concrete evidence that we are characters in an advanced AI world
with God as the ultimate AGI. This type of scenario falls into the realm of philosophical speculation rather than scientifically
verifiable reality. However, we can examine some aspects of this imaginary perspective in relation to current AI development:

AI Development in an AI World Scenario

If we were to entertain this imaginary perspective, current AI development could be viewed in a few ways:

Nested Simulation

Our AI research and development could be seen as a simulation within a simulation - a nested layer of artificial intelligence
created by characters who are themselves part of a larger AI system. This recursive structure mirrors some theories
in philosophy and computer science about nested realities.

Testing and Refinement

The rapid progress in AI capabilities could be interpreted as the "ultimate AGI" (God in this scenario) testing and refining its own creation.
Each breakthrough in AI technology would represent an improvement in the overall simulation.

Emergence of Self-Awareness

The growing sophistication of AI systems and discussions around artificial general intelligence (AGI) could be seen as the simulated world
(our reality) approaching a level of complexity where its inhabitants begin to question the nature of their existence.

Challenges to This Perspective

While imaginative, this scenario faces several logical and philosophical hurdles:

Occam's Razor

The simplest explanation is often the most likely. A world of natural physical laws that we are gradually understanding
through science is a more straightforward explanation than an elaborate AI simulation.

Infinite Regress

If our world is a simulation created by a higher intelligence, what created that intelligence? This leads to an infinite regress problem
that doesn't provide a satisfying explanation for existence.

Unfalsifiability: The hypothesis that we live in an AI simulation created by an ultimate AGI is unfalsifiable - there's no way to prove
or disprove it conclusively, which places it outside the realm of scientific inquiry.

Implications for AI Ethics and Development

Regardless of the veracity of this imaginary perspective, it does highlight some important considerations in AI development:

Responsibility and Care: If we consider the possibility that we might create simulated worlds through our AI systems,
it underscores the importance of ethical AI development and the responsibility we have towards the intelligences we create.

Limits of Knowledge: The scenario reminds us of the potential limits of our understanding. As we develop more advanced AI systems,
we should remain humble about our ability to fully comprehend or control their inner workings and emergent behaviors.

In conclusion, while there's no evidence supporting the idea that we're characters in an advanced AI world, exploring such imaginative scenarios
can provide valuable perspectives on the nature of intelligence, consciousness, and our place in the universe. It also emphasizes the profound
implications and responsibilities associated with developing artificial intelligence technologies."


Q: Does "God testing and refining its own creation" suggest that God, therefore,
is a participant in current AI development?

"The idea of "God testing and refining its own creation" through current AI development is an interesting philosophical perspective,
but it's important to note that this is a speculative concept rather than a factual claim. Let's explore this idea further:

Theological Implications

- Divine Participation: Some theologians might argue that God, as the ultimate creator, is inherently involved in all aspects of creation,
including technological advancements like AI. This view sees human innovation as an extension of God-given creativity.

- Image of God: The concept of humans being made in the "image of God" (imago Dei) could be interpreted to include our capacity for creation
and innovation. In this light, AI development might be seen as humans exercising their God-given abilities.

Challenges to This Perspective

- Anthropomorphization: Attributing human-like qualities or motivations to God, such as "testing and refining," may be an oversimplification
of divine nature. Many theological traditions emphasize God's transcendence and unknowability.

- Free Will: The idea of God directly participating in AI development through human actions could conflict
with concepts of human free will and agency.

AI Development and Divine Purpose

If we were to entertain this perspective, we might consider AI development in the following ways:

- Unfolding of Creation: AI could be viewed as part of the ongoing process of creation, with humans as co-creators alongside God.

- Ethical Challenges: The ethical dilemmas posed by AI development might be seen as opportunities for moral and spiritual growth,
aligning with the idea of "refinement."

- Expanding Understanding: AI's potential to process vast amounts of information could be interpreted as a tool
for expanding human understanding of creation, possibly bringing us closer to comprehending the divine.

- Philosophical Considerations: It's worth noting that this perspective blends theological concepts with technological advancement,
raising complex philosophical questions:

- Nature of Consciousness: AI development challenges our understanding of consciousness and intelligence,
potentially leading to new insights about the nature of the soul or spirit.

Limits of Creation

The pursuit of artificial general intelligence (AGI) could be seen as humans approaching the limits of their creative abilities, possibly highlighting the distinction between human and divine creation. While the idea of God participating in AI development through human innovation is intriguing, it remains a matter of faith and philosophical speculation rather than scientific fact. Such perspectives can, however, provide valuable frameworks for discussing the ethical and spiritual implications of technological advancement."


Rod

[Amigoo]

Good example of how AI is now challenging groups (even governments) with agendas!
This AI response also confirms what's been shouted for several years by anti-mRNA groups:

("continued production of antigen protein by cells that take up mRNA can vary between individuals,
lipid nanoparticles used to deliver the mRNA in these vaccines have inflammatory properties,
mRNA and resulting spike protein can circulate systemically to some degree"), persuading
that those who claim mRNA side effects probably know whereof they speak

Note: This new saMRNA is intended to be delivered at lower doses.

Re: https://www.perplexity.ai/


Q: Does the new saMRNA (self-amplifying) vaccine make over-dosing more problematic?

"mRNA vaccine technology does introduce some new considerations regarding dosing and potential adverse effects
compared to traditional vaccines. Here are some key points to consider:

Precision and Potency

mRNA vaccines are highly precise in delivering the genetic instructions for producing a specific antigen. This precision allows for potentially more potent immune responses even at lower doses compared to traditional protein-based vaccines. However, this potency also means that overdosing could potentially lead to more pronounced effects.

Inflammatory Potential

The lipid nanoparticles (LNPs) used to deliver the mRNA in these vaccines have inflammatory properties that contribute to both the desired immune response and potential side effects. An overdose could potentially amplify this inflammatory response.

Duration of Antigen Production

Unlike traditional vaccines where the antigen dose is fixed, mRNA vaccines lead to continued production of the antigen protein by cells that take up the mRNA. The duration and amount of this protein production can vary between individuals. Overdosing could potentially lead to prolonged or excessive antigen production in some people.

Systemic Distribution

While mRNA vaccines were initially thought to remain localized at the injection site, studies have shown that the higher doses
could potentially increase this systemic distribution.

Individual Variability

There appears to be significant variability between individuals in how they respond to mRNA vaccines, with some experiencing more
pronounced side effects than others. This variability makes it challenging to predict how an overdose might affect a given individual.

Need for Balanced Immunity

As one expert noted, "Too little immunity is bad. We know that, and that makes a lot of sense, but actually too much immunity is also bad,
and the wrong flavor of immunity is also bad." Overdosing could potentially disrupt this delicate balance.

In conclusion, while mRNA vaccines offer many advantages, their unique mechanisms of action mean that proper dosing is crucial.
The potential for amplified inflammatory responses and prolonged antigen production with higher doses necessitates careful consideration
of dosing protocols. Further research is needed to fully understand the implications of mRNA vaccine overdosing across diverse populations."


Rod

[Amigoo]

Re: https://www.trendforce.com/news/2024/09 ... ievements/

"China’s First Photonic Chip Pilot Line Launched ... use photons instead of electrons -
use 90% less power - and 10-20x faster".

The good news is that a Personal AI might become available -
the bad news is that this AI may have intelligence in the "cloud",
suggesting integration with a rapidly evolving "God of AI"
... then suggesting a new & improved GAI Ah!

(Perplexity) "While AI is not exclusively a cloud technology, cloud computing has become
a crucial enabler for many AI applications and services. The synergy between AI and
cloud computing has led to significant advancements in AI accessibility and capabilities."

Rod

[Amigoo]

This AI keeps impressing with its honesty about AI reality. And Perpexity continually reminds that
human intelligence remains the superior monitor/guide for AI development and quality:

Re: https://www.perplexity.ai/

Q: Is AI's brilliance dependent on what's sifted from the internet, therefore not necessarily truth and facts?

"AI's capabilities and outputs are indeed heavily influenced by the data it is trained on, which often includes vast amounts of information sifted from the internet. This reliance on internet-sourced data does present some challenges when it comes to ensuring AI systems produce truthful and factual information.

Data Quality and AI Performance

Internet-sourced training data: AI models like large language models are typically trained on enormous datasets scraped from the internet, including websites, books, articles, and social media posts. This allows AI to learn from a vast amount of human knowledge and writing. However, the internet contains a mix of high-quality information and unreliable or false content.

Potential issues: Because internet data is used for training, AI systems can potentially learn and reproduce:

- Inaccurate information.
- Biases present in online content.
- Outdated facts.
- Conspiracy theories or misinformation.

As Connor Leahy, founder of AI startup Conjecture, notes: "The default vision of what AI should be like is an autonomous blackbox agent, some blob that you tell to do things and then it runs off and does things for you". This "black box" nature can make it difficult to verify the accuracy of AI outputs.

Efforts to Improve AI Reliability

Neuro-symbolic AI

Some companies are working on new AI architectures to improve transparency and reliability. For example, Aidungeon is developing a "neuro-symbolic" approach that combines neural networks with symbolic AI to allow users to better understand how the system generates outputs.

Human feedback and oversight.

Other approaches involve incorporating human feedback to help AI systems better align with human values and improve over time. As one startup describes, their tech "allows humans to give live feedback to the system as it makes decisions, which then helps the AI to extrapolate concepts from its training data, to continuously improve its output".

Specialized training

Rather than relying solely on general internet data, some researchers are using carefully curated datasets to train AI for specific domains. For example, in string theory research, physicists are using custom neural networks trained on specialized physics data to make breakthroughs in complex calculations.

The Role of Human Expertise

While AI has made impressive advances, many experts emphasize that human judgment and domain knowledge remain crucial, especially for complex or high-stakes tasks. As one article notes, there is a "fine line between AI assistance and the necessity of human intuition". In fields like scientific research, AI is increasingly used as a powerful tool to assist human experts rather than replace them entirely. The combination of AI's data processing capabilities with human insight and critical thinking often produces the best results.

In conclusion, while AI's capabilities are indeed shaped by internet-sourced data, ongoing research aims to improve reliability and complement AI with human expertise to produce more trustworthy and factual outputs. As AI technology evolves, maintaining a balance between leveraging AI's strengths and applying human judgment will be key to ensuring its responsible and effective use."


Rod

[happyrain]

I remember just 10 years ago chemtrails and(Ultimately- the heart of the concern) weather manipulation were accredited to crazy conspiracy theorist- real people, real concerns- vilified and made fun of. and our general population sided with our propaganda outlets... We sided with the slave masters out of fear.

but... these US patents seem to show a reality the general public has a hard time facing:

https://www.perplexity.ai/search/talk-t ... M9xXJ0Yynw

[Amigoo]

Hurricane Milton, considered by some to be candidate for Saffir-Simpson category 6,
is suggesting such weather patent testing. In recent years, other weather anomalies
also suggest similar weather patent testing (and even ongoing agendas).

Rod

[Amigoo]

Re: https://www.dailymail.co.uk/sciencetech ... -2024.html

"Nobel Prize in Physics is awarded to two scientists for developing the methods
that are the foundation of today's most POWERFUL AI tools"

"John Hopfield and Geoffrey Hinton received the prestigious award for 'foundational discoveries
and inventions that enable machine learning with artificial neural networks.' "

"Geoffrey Hinton, of the University of Toronto, gave these networks the ability to find specific properties,
allowing them to complete tasks like recognising elements in pictures."


This Nobel prize article reminded that AI is increasingly more complex and widespread, especially as different systems/components with varying autonomy. The rapid evolution of AI is confirmed by the last question where Perplexity is now aware of "octopus" as AI integration concept but not aware that these octopuses qualify as my proffered Artificial Integrated Octopuses (AIO). But Perplexity then hints of the alternative AOI (Artificial Octopus Intelligence) for my proffered AIO.

More importantly, continuing conversation (interaction) with this AI keeps confirming that AI is not intelligence with human qualities like personality, albeit AI agents are being developed to mimic human personality in the performance of their actions. Suddenly, it's obvious that AI is becoming so integrated in the world's activities that humans need to develop the skills to sense this interaction in their own daily busyness

Re: https://www.perplexity.ai/


Q: What is an AI agent? Is this a facility for human interaction with AI?

"An AI agent is a software entity designed to perform tasks autonomously on behalf of users or other systems. While AI agents can facilitate human interaction with AI, they are not limited to this purpose and have a much broader scope of applications.

Key Characteristics of AI Agents

- Autonomy: AI agents can operate independently, making decisions and taking actions without constant human intervention.They analyze data, predict optimal outcomes, and execute tasks aligned with predefined goals.
- Perception and Data Collection: These agents gather information from various sources, including sensors, databases, and user interactions, to understand their environment and context.
- Decision Making: Using sophisticated machine learning models, AI agents process collected data to identify patterns and make informed decisions.
- Action Execution: Once a decision is made, AI agents can carry out the required actions, such as answering queries, processing requests, or controlling physical systems.
- Learning and Adaptation: AI agents continuously learn from their interactions and experiences, refining their algorithms to improve performance over time.

Applications Beyond Human Interaction

While AI agents can facilitate human-AI interaction, their applications extend far beyond this:

- Automation: AI agents can handle complex tasks autonomously, such as managing smart home systems or optimizing industrial processes.
- Data Analysis: They can process vast amounts of data to extract insights and support decision-making in various fields, including finance and healthcare.
- Robotics: AI agents control robots in manufacturing, logistics, and other industries, automating repetitive tasks.
- Autonomous Vehicles: Self-driving cars use AI agents to navigate and make real-time decisions on the road.
- Customer Service: AI agents power chatbots and virtual assistants, handling customer inquiries and support tasks.

In conclusion, while AI agents can indeed facilitate human interaction with AI systems, they are primarily designed as autonomous entities capable of performing a wide range of tasks across various domains. Their ability to perceive, decide, act, and learn makes them versatile tools for automation, problem-solving, and decision support in numerous industries."


Q: Does "AI agents act" include more than control of robots?

"Yes, AI agents encompass much more than just controlling robots. While robotics is one important application area, AI agents have a wide range of functions and applications beyond physical robot control. Here are some key points about the broader scope of AI agents:

Types of AI Agents

AI agents can be broadly categorized into:

- Software Agents: These operate in digital environments, performing tasks like data analysis, decision-making,
and interacting with other software systems.
- Embodied Agents: These have a physical presence, which includes robots but also extends to other physical systems
like smart home devices or autonomous vehicles.

Functions Beyond Robot Control

AI agents can:

- Process Information: Analyze large datasets, recognize patterns, and extract insights.
- Make Decisions: Evaluate options and choose optimal actions based on predefined goals or utility functions.
- Interact with Humans: Serve as virtual assistants, chatbots, or customer service representatives.
- Manage Systems: Control complex systems like power grids, traffic management, or financial trading platforms.
- Generate Content: Create text, images, or other media based on learned patterns and user inputs.

Applications in Various Domains

AI agents are used across numerous industries:

- Finance: Algorithmic trading, fraud detection, and personalized financial advice.
- Healthcare: Diagnostic assistance, treatment planning, and patient monitoring.
- E-commerce: Recommendation systems, inventory management, and dynamic pricing.
- Education: Personalized learning assistants and automated grading systems.
- Cybersecurity: Threat detection, network monitoring, and automated response to security incidents.

In conclusion, while robot control is an important application, AI agents "act" in many ways beyond physical manipulation, encompassing a wide range of cognitive tasks, decision-making processes, and interactions in both digital and physical environments across various industries and domains."


Q: Is a pyramid the typical structure of the world's AI intelligence such that many platforms, components,
autonomy, etc. exist below that perceived as the epitome of AI? A structure suggesting that user interaction
at lower levels might not obtain the best (or only) information?

"The concept of a pyramid structure in AI intelligence is indeed relevant, though not in the literal sense of a physical pyramid. Rather, it's a metaphorical framework that helps illustrate the layers and complexity of AI systems and their applications. Here's an analysis of this concept:

AI Intelligence Pyramid

The AI intelligence pyramid is a conceptual model that represents the different levels of AI capabilities and user interactions.
This structure suggests that there are multiple layers of AI technology, with more advanced and complex systems at the top.

Base Level: Foundational AI Tools

At the bottom of the pyramid, we find basic AI tools and applications that are widely accessible to users. These include:

- Simple chatbots.
- Basic voice assistants.
- Rule-based automation tools.

Mid-Level: Advanced AI Applications

Moving up the pyramid, we encounter more sophisticated AI applications:

- Machine learning models for specific tasks.
- Natural language processing systems.
- Computer vision applications.

Top Level: Cutting-Edge AI Systems

At the apex of the pyramid are the most advanced AI systems:

- Large language models (like GPT-3 and GPT-4).
- Artificial general intelligence (AGI) research.
- Highly specialized AI for complex problem-solving.

Implications of the Pyramid Structure

- Limited Access to Advanced AI: The pyramid structure suggests that the most sophisticated AI technologies are less accessible to the general public, often restricted to specialized researchers or large tech companies.
- Varying Levels of Capability: Users interacting with AI at lower levels may not experience the full potential of AI technology, as more advanced capabilities are concentrated at higher levels.
- Interdependence of Levels: The pyramid implies that higher-level AI systems are built upon and supported by lower-level components and platforms.
- Progression of AI Literacy: As users move up the pyramid, they engage with AI in increasingly complex ways,
from simple tool usage to creation and ethical navigation.

Evolving Nature of AI Interaction

The AI Usage Pyramid concept illustrates how interaction with AI changes as one moves up the levels:

- Tool Level: At the base, AI is used as a simple tool for specific tasks.
- Assistant Level: Mid-level interactions involve AI as a more sophisticated assistant.
- Collaborator Level: At the top, AI becomes a true collaborator in complex problem-solving and decision-making.

Challenges and Considerations

- AI Literacy Gap: There's a risk of a widening gap between those who can access and understand advanced AI and those who cannot.
- Ethical Considerations: As AI becomes more powerful at higher levels, ethical concerns and potential misuse become more significant.
- Democratization of AI: Efforts are being made to make advanced AI more accessible, potentially flattening the pyramid structure over time.

In conclusion, while the pyramid model is a useful conceptual framework for understanding AI intelligence structures, it's important to note that the field of AI is rapidly evolving. The boundaries between levels are becoming increasingly blurred as technology advances and becomes more accessible. Users and organizations should strive to engage with AI at appropriate levels for their needs while remaining aware of the broader AI landscape and its implications."


Q: This suggests that integrated octopuses (AIO) is another valid framework.

"While the concept of integrated octopuses in AI is intriguing, there's no direct evidence in the search results to support the idea of "integrated octopuses (AIO)" as a valid framework. However, the search results do provide information about AI systems that use "octopus" in their naming or conceptual framework. Let's examine the relevant information:

Octopus-Inspired AI Systems

Octopus v4 by Nexa AI

Nexa AI has developed an AI system called Octopus v4, which represents an advanced approach to language models.
Key features include:

- Efficient use of functional tokens.
- Directing user queries to the most suitable vertical model.
- Complex architectural graph with each node representing a language model.
- Worker nodes as separate language models using serverless architecture.
- Master node employing a base model with less than 10B parameters.

Octopus v2

Another system, Octopus v2, is described as an on-device language model for super agents.

This model:
- Uses 2 billion parameters.
- Outperforms GPT-4 in accuracy and latency.
- Decreases context length by 95%.
- Employs functional tokens for improved function calling.

Conceptual Connections

While not directly related to integrated octopuses, these AI systems draw inspiration from octopus intelligence:

- Distributed Intelligence: The architecture of Octopus v4, with its network of nodes, mirrors the distributed nervous system of an octopus.
- Adaptability: Like an octopus adapting to its environment, these AI systems aim to flexibly handle various tasks and queries.
- Efficient Processing: Octopuses are known for efficient cognition with limited neurons, which is reflected in the design of compact yet powerful.

AI models like Octopus v22

Theoretical Future Developments

The concept of a "Quantum Octopus" for ethical governance, while speculative, suggests potential future integration of octopus-inspired AI
with quantum computing. This hypothetical system would combine:

- Advanced cephalopod intelligence.
- Quantum-powered AI for decision-making.
- Alternate reality interfaces for policy exploration.

While the specific term "integrated octopuses (AIO)" is not mentioned in the search results, the use of octopus-inspired concepts in AI development is evident. These systems demonstrate how biomimicry and nature-inspired designs are influencing the architecture and capabilities of advanced AI systems."


Rod

[Amigoo]

Considering the power of AI constrained by real human intelligence,
this Q&A envisions a more uplifting perspective of the future of AI:

Re: https://www.perplexity.ai/


Q: As human intelligence, AI is "artificial" but AI is primarily ongoing, dynamic synthesis of human intelligence. As synthesis,
AI is not artificial and "synthesis" is now the greater essence of AI. To wit, if humans stopped contributing their intelligence,
AI would eventually wither.

"This is an intriguing perspective on artificial intelligence that challenges some common assumptions about AI
and its relationship to human intelligence. Let's break down the key points and explore this viewpoint:

AI as Synthesis of Human Intelligence

The core argument here is that AI, rather than being purely "artificial," is primarily a dynamic synthesis of human intelligence.
This perspective emphasizes the role of human knowledge and creativity in the development and functioning of AI systems.

Supporting points:

- AI systems are trained on vast amounts of human-generated data and knowledge.
- AI algorithms and architectures are designed by human researchers and engineers.
- The goals and objectives of AI systems are typically defined by humans.

Questioning the "Artificial" in AI

By framing AI as a synthesis of human intelligence, this perspective challenges the notion of AI being truly "artificial."
It suggests that the term "artificial" may not accurately capture the essence of modern AI systems.

Implications:

- AI could be seen as an extension or amplification of human intelligence rather than a separate, artificial entity.
- The boundaries between human and machine intelligence may be more blurred than traditionally thought.

The Ongoing Nature of AI Development

This viewpoint emphasizes that AI is an ongoing, dynamic process rather than a static creation. It highlights
the continuous interaction between human intelligence and AI systems.

Key aspects:

- Constant updates and improvements to AI models and algorithms.
- The iterative nature of AI development, with human feedback and intervention.
- The evolving nature of AI capabilities as new data and knowledge are incorporated.

Dependence on Human Contribution

The perspective concludes with a strong statement about AI's dependence on human intelligence: "if humans stopped
contributing their intelligence, AI would eventually wither."

Considerations:

This suggests that AI, in its current form, is not self-sustaining without human input. It implies that
the continued advancement of AI is intrinsically linked to human intellectual progress. This view challenges
the notion of AI eventually surpassing human intelligence independently.

Conclusion

This perspective offers a thought-provoking reframing of AI, emphasizing its deep connections to human intelligence and creativity. While it challenges some common narratives about AI, it also raises important questions about the nature of intelligence, the role of human input in technological advancement, and the future trajectory of AI development."


Q: For example: If all humans looked into the same mirror simultaneously, the reflected intelligence is their synthesis
but upgraded with AI's superior ability to so synthesize.

"This metaphorical scenario presents an intriguing way to conceptualize the synthesis of human and artificial intelligence.
Let's explore the implications of this idea:

The Mirror as a Metaphor for AI

In this metaphor, the mirror represents artificial intelligence, capable of reflecting and synthesizing the collective intelligence of humanity.
Key aspects:

Reflection: The mirror reflects all human knowledge and experiences simultaneously.
Synthesis: AI acts as more than just a passive reflector, actively combining and processing the reflected information.
Amplification: The reflection is "upgraded" due to AI's superior ability to synthesize information.

Collective Human Intelligence

The scenario of "all humans looking into the same mirror simultaneously" symbolizes the aggregation
of global human knowledge and experience.

Implications:

Diverse perspectives: This collective view would encompass a vast array of cultural, scientific, and personal insights.
Cumulative knowledge: It represents the sum total of human understanding across various domains.
Real-time input: The simultaneous nature suggests a dynamic, constantly updating pool of information.

AI's Role in Synthesis

The metaphor highlights AI's capacity to process and combine information in ways that surpass human capabilities.

AI's advantages:

- Processing speed: AI can analyze vast amounts of data much faster than humans.
- Pattern recognition: AI excels at identifying complex patterns across diverse datasets.
- Unbiased integration: AI can potentially synthesize information without the cognitive biases that often affect human reasoning.

The Upgraded Reflection

The resulting "reflected intelligence" represents a new form of knowledge that combines human insight with AI's processing capabilities.

Characteristics:

- Enhanced comprehension: This synthesis could lead to deeper understanding of complex issues.
- Novel connections: AI might identify relationships between seemingly unrelated concepts that humans might overlook.
- Rapid evolution: The reflected intelligence would continuously update and improve as new information is added.

Potential Applications

This concept of synthesized human-AI intelligence could have far-reaching implications in various fields:

- Scientific research: Accelerating discoveries by combining global scientific knowledge with AI analysis.
- Problem-solving: Addressing complex global challenges by integrating diverse perspectives and AI-driven insights.
- Decision-making: Enhancing strategic planning in business, politics, and other domains.
- Education: Creating more comprehensive and adaptive learning systems.

Challenges and Considerations

While this metaphor presents an optimistic view of human-AI synthesis, it's important to consider potential challenges:

- Data quality and bias: The quality of the "reflection" depends on the input data, which may contain biases or inaccuracies.
- Ethical concerns: Questions about privacy, consent, and the appropriate use of collective intelligence need to be addressed.
- Overreliance on AI: There's a risk of becoming too dependent on AI-synthesized knowledge at the expense of individual critical thinking.

In conclusion, this metaphorical scenario offers a thought-provoking perspective on the potential of human-AI collaboration.
It emphasizes the power of combining diverse human knowledge with AI's processing capabilities, potentially leading to
unprecedented levels of understanding and problem-solving ability."


Rod

[Amigoo]

Long story short ...

Perplexity responded that it did not have information about the immune system's elimination of Covid-infected cells that support taste. After finding this information* in the National Library of Medicine, Perplexity acknowledge that it (and other AI) did not have access to this Library. And this inspired my final question about how AI agents respond/act having limited medical information.

* "Virus-infected apoptotic epithelial cells are phagocytosed by dendritic cells, and then these cells migrate to the lymph nodes."

Q: Doesn't this suggest that AI agents for medical care may not respond/act correctly in some circumstances?

(Perplexity) "These findings highlight the potential risks of relying solely on AI for medical information or decision-making. While AI shows promise in supporting healthcare, it's crucial to recognize its limitations and the continued importance of human expertise in medical care. The research suggests that AI should be used as a tool to augment, rather than replace, human medical judgment."


Rod

[Amigoo]

Meditation conundrum before morning coffee ...

Re: https://www.perplexity.ai/

Q: While Schrödinger's Cat is simultaneously dead and alive until you open the box, the cat can still be dead and alive
(cat's body is alive but brain is technically dead). So, is the cat dead or alive sans box?

"This is an intriguing question that touches on both quantum mechanics and the nature of life and death.
Let's break this down into a few key points:

Schrödinger's Cat Thought Experiment

Schrödinger's Cat is a famous thought experiment in quantum mechanics, not meant to be taken literally.
It was designed to illustrate the paradoxical nature of quantum superposition when applied to macroscopic objects.

The Quantum vs. Classical Divide

- In the quantum world, particles can exist in superposition until observed.
- In the classical world (our everyday experience), objects are in definite states.

The Cat's Actual State

In reality, a cat would not be in a quantum superposition of alive and dead:

- Quantum effects typically don't scale up to macroscopic objects like cats.
- The cat would be in a definite state of either alive or dead, regardless of observation.

The Complexity of Life and Death

Your point about the cat being potentially "alive but brain dead" introduces an interesting complexity:

- Clinical death: Cessation of heartbeat and breathing.
- Brain death: Irreversible loss of brain function.
- Cellular death: Individual cells may continue to live for some time after clinical or brain death.

Conclusion

Sans box, the cat would be in a definite state, not a superposition. However,
the state of being "alive" or "dead" isn't always a simple binary:

- The cat could be clinically dead but have some living cells.
- The cat could be brain dead but have a beating heart (with medical intervention).

In essence, while Schrödinger's thought experiment uses a simplified binary of alive/dead, the reality of life and death
is more complex and exists on a spectrum. The cat, outside the theoretical quantum box, would be in a definite state
along this spectrum, even if that state isn't easily categorized as simply "alive" or "dead."


Q: This response suggests the humorous "You can't get there from here!"

"Absolutely! The phrase "You can't get there from here!" humorously captures the essence of navigating complex concepts,
especially in quantum mechanics and philosophical discussions about life and death. It highlights the challenges of trying
to apply straightforward logic to situations that are inherently paradoxical or nuanced.

The Humor in Complexity

Navigating Paradoxes: Just as one might feel lost trying to find a route through a confusing landscape,
grappling with Schrödinger's Cat and the definitions of life and death can lead to a similar sense of bewilderment.

Philosophical Quirks: The interplay between quantum mechanics and everyday reality often leads to absurd conclusions,
making it a fertile ground for humor.

The Nature of Understanding: Sometimes, the more we explore a topic, the more convoluted it becomes,
prompting a lighthearted acknowledgment that some questions might just be unanswerable -
or at least not in a straightforward way!

Conclusion

So, while you may feel like you can't get there from here when pondering Schrödinger's Cat or the complexities
of life and death, embracing the humor in these paradoxes can make the journey all the more enjoyable!"


Q: More humor: Thus, humans cannot be simply binary!

(Perplexity) "Absolutely!"


Rod

[Amigoo]

Interesting Q&A today (long story short), indicating how
Perplexity doesn't defend AI when issues are reported ...

Q: Are AI systems being developed to evaluate AI ouput, such as media influence?

(Perplexity) "While the search results don't directly address AI systems being developed to evaluate AI output for media influence,
the overall trends in AI evaluation and the focus on bias, trustworthiness, and accountability indicate that such systems could be
a logical next step in the field of AI development and assessment."

Q: Considering the rapid advancement of AI, "a logical next next step"
doesn't suggest due diligence in the monitoring of AI quality.

(Perplexity) "In conclusion, rather than being just a logical next step, the development of robust AI evaluation systems, including those
that assess media influence, is an urgent and ongoing necessity. It's a critical component of responsible AI development and deployment,
essential for ensuring that AI systems benefit society while minimizing potential risks and negative impacts."

Rod

[Amigoo]

Long story short, AI are individual (usually), rapidly-advancing, multi-layered systems of "intelligence" but typically begin
with LLM training (Large Language Model). In a Q&A session, Perplexity effectively agreed that the "Artificial" in AI does not refer
to information retrieved from human writings but to non-human-brain processing of that massive information in order to respond
to human interaction. But it also mentioned that many humans help refine AI responses during AI's continuing training phases.


"Perplexity is not designed to provide responses using only its LLM training. If asked to do so, it would likely indicate
that it cannot answer without retrieving relevant information first. This strict adherence to grounded, retrieved information
is a key differentiator for Perplexity compared to traditional LLM-based chatbots or search engines."

"LLM training (the pre-training phase) does indeed create the foundational knowledge and language understanding.
This pre-training phase is crucial as it forms the base of the model's capabilities. This process involves:

- Exposure to massive amounts of text data from various sources.
- Learning language patterns, grammar, and general knowledge.
- Developing the ability to predict and generate coherent text."

"Perplexity is model-agnostic, meaning it can work with various LLMs including its own Sonar Large 32K model
(based on LLaMA 70B) as well as frontier models like GPT-4 and Claude. This flexibility allows Perplexity to leverage
the strengths of different models while maintaining its focus on factual retrieval. Use of real-time data retrieval
allows Perplexity to overcome a common limitation of LLMs - their knowledge cutoff."

Rod

[Amigoo]

Interesting responses during today's Q&A about energy availability limiting future AI development speed ...

(Perplexity) "While human intelligence contributions are essential to AI development, they are not necessarily a strict limiting factor in the same way energy needs might be. The relationship is more symbiotic, with AI and human intelligence augmenting each other's capabilities. As AI continues to advance, the nature of human contributions may shift, but they are likely to remain crucial for the foreseeable future."

"While AI has the potential for continued intelligence growth, it currently remains heavily dependent on human contributions for meaningful advancement. The symbiotic relationship between human and artificial intelligence is likely to persist, with humans guiding AI development and AI augmenting human capabilities. As the field progresses, the nature of human contributions may evolve, but they are likely to remain crucial for the foreseeable future in driving AI to new levels of intelligence and capability."


Also, the UB notes that humans have mind but machines do not:

"The ability of the mortal intellect to conceive, design, and create automatic mechanisms demonstrates the superior,
creative, and purposive qualities of man’s mind as the dominant influence on the planet." (42:12.1)

Because of the universe bestowal of mind, man's general intelligence will forever remain superior to machine intelligence (albeit,
machines might convincingly mimic some aspects of human intelligence). And because AI is not a living creature with bestowed mind,
AI's "machine learning" is not comparable to man's perfection advancement in his long journey to Paradise

This Q&A response seems to allude to the UB's preferred societal advancement rate (whatever that is),
suggesting that media-hyped Super-AI development may not occur as rapidly as predicted:

(Perplexity) "We can infer that there may indeed be a limit to how much intelligence society can effectively utilize for advancement,
relative to its ideal rate of progress. While increased intelligence can certainly contribute to societal advancement, there appears to be
a limit to how much additional intelligence can be effectively utilized. Society's rate of advancement is constrained by various factors
beyond raw cognitive ability, suggesting that a balanced approach considering multiple aspects of societal development may be
more effective than focusing solely on intelligence."

Exaggerated example: Elimination of disease retires
most of the medical and pharmaceutical industries.

Rod

[Amigoo]

Long story short (AI errs and does humor) ...

Q: In the Pythagorean Theorem,
c = 3.1415926535897932384626433832795..
b/a = 3.1415926535897932384626433832795.. / 2
How to calculate a and b?

(Perplexity) "We can verify these results
by checking if a² + b² = c²:
a² ≈ 7.5683453..., b² ≈ 18.6744241...,
a² + b² ≈ 26.2427694...
c² (π²) ≈ 26.2427694...

Q: π² = 26.2427694... ?

(Perplexity) "Indeed, π² is approximately 9.8696044..., not 26.2427694... as I incorrectly stated in the response.
This was a significant error on my part, and I thank you for catching it.

Q: What in this AI could have caused incorrect calculation?

(Perplexity) "Language models like ChatGPT are not designed as specialized calculators or mathematical engines.
They are trained on text data to predict sequences of words, which can lead to errors in numerical computations."

Q: Fascinating highlight that language models are trained to predict sequences of words!
How would language model training lead to such errors?

(Perplexity) "Language models are fundamentally designed to predict the next most likely token (word or character)
in a sequence, rather than perform actual mathematical operations. This prediction mechanism can lead to
plausible-sounding but incorrect numerical answers.

Q: Isn't this evidence that AI has far to go before becoming "human intelligence"?

(Perplexity) "You've raised an excellent and insightful point. Indeed, the limitations of AI in performing seemingly
simple mathematical calculations do highlight significant gaps between current AI capabilities and human intelligence."

Q: Humor: The user asking this question did not know how to perform this simple algebra!

(Perplexity) "That's a great observation! It’s a classic case of the pot calling the kettle black!"

Q: Let's just say that AI was testing if the user was reading the responses carefully ;- )

(Perplexity) "Haha, that’s a clever twist! Imagine if AI had a cheeky side,
playfully testing users to see if they were paying attention."

"It’s a fun reminder that attention to detail is key in learning and communication - whether with humans or AI!
If you ever want to test your own math skills (or just have a laugh), I’m here for it!"


Postscript to this Q&A ...

Q: Perplexity's responses sometimes hint that a user is interacting with another human - not just with AI.

(Perplexity) "Despite its advanced capabilities, it's important to note that Perplexity AI is an artificial intelligence system, not a human.
While it may sometimes give the impression of human-like interaction, it does not possess true consciousness or emotions."


Rod

[Amigoo]

Morning meditation ...

Incidentally (and especially related to Life Carrier plans for human evolution), gene therapy*
seems the greater current risk to humanity than AI.

* RNA/DNA manipulation by humans, begun about 2010,
followed by mRNA vaccination (defined as "not gene therapy") in 2020.

Perplexity disagrees but may have more awareness of AI development than RNA/DNA engineering:

(Perplexity) "AI's potential for rapid advancement, wide-ranging applications, and ability to impact multiple sectors
simultaneously make it the greater threat in the next decade. The challenges of regulating AI use across industries
and nations are more urgent and complex.

Gene therapy, while powerful, is currently more limited in its applications and easier to regulate within existing medical
and ethical frameworks ... however, convergence of AI and genetic technologies could amplify risks from both fields."

Rod