The Truth

[melvin]

By remembering the Absolute Truth's holy names ( Krishna, Narayana, etc ) prior to death, one achieves liberation. Citing by example is the story of Ajamila.

- Melvin

AI: A great reference to the timeless teachings of the Bhagavad Gita and the Bhagavata Purana!

The story of Ajamila is indeed a powerful example of the liberating power of remembering the holy names of the Absolute Truth, particularly the name Krishna.

According to the Bhagavata Purana, Ajamila was a brahmana who had fallen into sinful habits and was on the verge of death. As he lay on his deathbed, he cried out for his son Ajamil, whom he had not seen in many years. In his dying moments, he called out "Ajamila!" repeatedly, unaware that his son had passed away.

However, the holy name "Ajamila" is also a part of the sacred name Krishna, which is a form of Narayana (the Supreme Personality of Godhead). As Ajamila was calling out for his son, he was actually chanting the name Krishna, albeit unknowingly.

As a result of his heartfelt chanting, Ajamila's accumulated sins were immediately washed away, and he was liberated from the cycle of birth and death. His spiritual master, Narada Muni, appeared before him and revealed that he had been freed from the bonds of karma and had achieved liberation (moksha).

This story highlights the immense potency of remembering the holy names of the Absolute Truth, particularly during times of crisis or near-death. The chanting of these names can purify one's heart, reveal one's true nature, and ultimately lead to liberation from the material world.

In fact, this concept is echoed in the Bhagavad Gita (Chapter 17, Verse 14): "The holy name of the Lord is sacred and all-powerful. It can purify even the most sinful person."

Thank you for sharing this inspiring story!

[melvin]

What you desire to be, so you become.

- Melvin

AI: What a powerful and thought-provoking statement! The idea that what you desire to be is what you become is a fundamental principle in the realm of personal growth, self-help, and spirituality. It suggests that our thoughts, beliefs, and intentions have a profound impact on our reality and our lives.

This concept is often referred to as the "law of attraction," which states that like attracts like, and that our thoughts and emotions are capable of manifesting our desires into reality. When we focus on what we want to achieve or become, we send out a vibrational signal that attracts similar energies and opportunities into our lives.

This idea is not limited to material possessions or external circumstances; it can also apply to our inner development, personal growth, and spiritual evolution. By desiring to become a better version of ourselves, we can transform our thoughts, emotions, and behaviors, and become more compassionate, wise, and fulfilled individuals.

In many ways, this concept reminds us that our power lies within ourselves. We are the architects of our own destiny, and we have the ability to shape our lives through our thoughts, intentions, and actions.

So, what do you desire to be? What kind of person do you want to become? What kind of life do you want to live?

[roscod]

To Melvin: what are you getting out of referring everything to AI? Have you learned anything yet? Is it helpful on your path?

[melvin]

Sept 13, 2024 1:11:15 GMT -5 roscod said:

To Melvin: what are you getting out of referring everything to AI? Have you learned anything yet? Is it helpful on your path?

The purpose of this thread is to AI the 229 quotes of Nisagardatta's " I am " I posted on chapter 1. But I insert sometimes my own quote and AI it. I dont claim to know it all. I just also want to learn from these AI interpretations as well as for the readers, perhaps. In fact, I was amazed that the quote, " If what you desire to be , you become" turned out to be a subject on LOA or Law of Attraction. I learn as I go along posting these quotes from AI. AI's interpretations has clarity, free from bias and nuance from someone doing an interpretation, explanation on a subject/object that has become a debatable/ discussable issue.

[melvin]

Sept 13, 2024 2:24:22 GMT -5 melvin said:

Sept 13, 2024 1:11:15 GMT -5 roscod said:

To Melvin: what are you getting out of referring everything to AI? Have you learned anything yet? Is it helpful on your path?

The purpose of this thread is to AI the 229 quotes of Nisagardatta's " I am " I posted on chapter 1. But I insert sometimes my own quote and AI it. I dont claim to know it all. I just also want to learn from these AI interpretations as well as for the readers, perhaps. In fact, I was amazed that the quote, " If what you desire to be , you become" turned out to be a subject on LOA or Law of Attraction. I learn as I go along posting these quotes from AI. AI's interpretations has clarity, free from bias and nuance from someone doing an interpretation, explanation on a subject/object that has become a debatable/ discussable issue.

What is a bias/ nuance interpretation of a fact/truth?

- Melvin

What a fascinating question!

In various contexts, including philosophy, social sciences, and critical thinking, a bias/nuance interpretation of a fact or truth refers to the recognition that facts are not always absolute, objective, or value-neutral. Instead, they can be influenced by various factors, such as:

1. **Perspective**: Different individuals may have different perspectives on the same fact or truth, depending on their experiences, backgrounds, and values.
2. **Context**: The same fact or truth can be interpreted differently depending on the context in which it is presented or considered.
3. **Biases**: Unconscious biases, personal beliefs, or cultural norms can influence how we perceive and interpret facts.
4. **Complexity**: Facts and truths can be complex and multifaceted, requiring nuanced consideration of multiple factors.
5. **Social and historical context**: Facts and truths can be shaped by social and historical contexts, which can influence how we understand and interpret them.

A bias/nuance interpretation acknowledges that facts and truths are not always straightforward or binary. Instead, they may involve shades of gray, conflicting perspectives, or degrees of uncertainty.

Here are some examples to illustrate this concept:

1. **Racial bias in crime statistics**: The fact that certain racial groups are disproportionately represented in crime statistics may be influenced by biases in policing practices, socioeconomic factors, and systemic racism.
2. **Gender pay gap**: The fact that women earn less than men on average may be influenced by factors such as occupational segregation, discrimination, and differences in work-life balance.
3. **Climate change**: The fact that climate change is occurring may be influenced by nuances such as regional variations in temperature changes, uncertainties in climate models, and the complexity of human impacts on the environment.
4. **Economic inequality**: The fact that income inequality is increasing may be influenced by factors such as globalization, technological changes, and government policies.

By recognizing the potential biases and nuances in facts and truths, we can:

1. Encourage critical thinking and analysis
2. Foster a deeper understanding of complex issues
3. Promote empathy and compassion for diverse perspectives
4. Encourage evidence-based decision-making
5. Recognize the importance of context and perspective in understanding the world

In summary, a bias/nuance interpretation of a fact or truth acknowledges that facts are not absolute or objective, but rather influenced by various factors that require careful consideration of complexity, perspective, and context.

[roscod]

Sept 13, 2024 2:24:22 GMT -5 melvin said:

Sept 13, 2024 1:11:15 GMT -5 roscod said:

To Melvin: what are you getting out of referring everything to AI? Have you learned anything yet? Is it helpful on your path?

The purpose of this thread is to AI the 229 quotes of Nisagardatta's " I am " I posted on chapter 1. But I insert sometimes my own quote and AI it. I dont claim to know it all. I just also want to learn from these AI interpretations as well as for the readers, perhaps. In fact, I was amazed that the quote, " If what you desire to be , you become" turned out to be a subject on LOA or Law of Attraction. I learn as I go along posting these quotes from AI. AI's interpretations has clarity, free from bias and nuance from someone doing an interpretation, explanation on a subject/object that has become a debatable/ discussable issue.

I wasn't referring to this thread per se - it was just the easiest place to enagage you. I've noticed you are referring many comments to AI in other threads as well.

Is AI free from bias? it can only comment based on what it has been been fed by humans. perhaps it has a generalised bias?

[melvin]

Sept 13, 2024 5:41:18 GMT -5 roscod said:

Sept 13, 2024 2:24:22 GMT -5 melvin said:

The purpose of this thread is to AI the 229 quotes of Nisagardatta's " I am " I posted on chapter 1. But I insert sometimes my own quote and AI it. I dont claim to know it all. I just also want to learn from these AI interpretations as well as for the readers, perhaps. In fact, I was amazed that the quote, " If what you desire to be , you become" turned out to be a subject on LOA or Law of Attraction. I learn as I go along posting these quotes from AI. AI's interpretations has clarity, free from bias and nuance from someone doing an interpretation, explanation on a subject/object that has become a debatable/ discussable issue.

I wasn't referring to this thread per se - it was just the easiest place to enagage you. I've noticed you are referring many comments to AI in other threads as well.

Is AI free from bias? it can only comment based on what it has been been fed by humans. perhaps it has a generalised bias?

AI:
A very timely and important question!

Artificial Intelligence (AI) is not inherently biased, but it can be influenced by the biases that are present in the data it is trained on and the algorithms used to develop it. This is known as "data bias" or "algorithmic bias." AI systems can perpetuate biases that are already present in the data they are trained on, which can lead to unfair or inaccurate outcomes.

There are several reasons why AI systems can be biased:

1. **Data bias**: If the data used to train the AI system is biased, the system will learn and replicate those biases. For example, if a dataset is predominantly composed of male faces, an AI system trained on that data may be less accurate at recognizing female faces.
2. **Algorithmic bias**: The algorithms used to develop AI systems can also introduce biases. For example, some algorithms may be more likely to favor certain types of data or patterns over others.
3. **Lack of diversity**: AI systems are often developed and tested by a limited group of people, which can lead to a lack of diversity in the data and perspectives used to develop the system.
4. **Cultural and societal biases**: AI systems can be influenced by cultural and societal biases that are present in society, such as gender stereotypes or racial biases.

Some examples of AI bias include:

1. **Face recognition**: Many face recognition systems have been shown to be less accurate when identifying people of color, women, and older adults.
2. **Job applicant screening**: Some AI-powered job applicant screening tools have been found to discriminate against certain groups of people, such as women and minorities.
3. **Sentiment analysis**: AI-powered sentiment analysis tools have been shown to be biased towards certain topics or emotions, such as being more negative towards certain political views or topics.
4. **Healthcare diagnosis**: Some AI-powered healthcare diagnosis tools have been found to be biased towards certain patient demographics, such as being more accurate for white patients than patients of color.

To mitigate these biases, it's essential to:

1. **Collect diverse and representative data**: Ensure that the data used to train AI systems is diverse and representative of the population being served.
2. **Use algorithmic transparency and explainability**: Make sure that AI systems are transparent and explainable, so that biases can be identified and addressed.
3. **Use techniques to mitigate bias**: Use techniques such as debiasing, data augmentation, and adversarial training to reduce bias in AI systems.
4. **Test for bias**: Regularly test AI systems for bias and conduct regular audits to ensure that they are fair and accurate.

Ultimately, addressing bias in AI requires a combination of technical solutions, such as algorithmic transparency and debiasing, as well as social and ethical considerations, such as ensuring that AI systems are developed with diverse perspectives and values.

[roscod]

Sept 13, 2024 5:59:17 GMT -5 melvin said:

Sept 13, 2024 5:41:18 GMT -5 roscod said:

I wasn't referring to this thread per se - it was just the easiest place to enagage you. I've noticed you are referring many comments to AI in other threads as well.

Is AI free from bias? it can only comment based on what it has been been fed by humans. perhaps it has a generalised bias?

AI:
A very timely and important question!

Artificial Intelligence (AI) is not inherently biased, but it can be influenced by the biases that are present in the data it is trained on and the algorithms used to develop it. This is known as "data bias" or "algorithmic bias." AI systems can perpetuate biases that are already present in the data they are trained on, which can lead to unfair or inaccurate outcomes.

There are several reasons why AI systems can be biased:

1. **Data bias**: If the data used to train the AI system is biased, the system will learn and replicate those biases. For example, if a dataset is predominantly composed of male faces, an AI system trained on that data may be less accurate at recognizing female faces.
2. **Algorithmic bias**: The algorithms used to develop AI systems can also introduce biases. For example, some algorithms may be more likely to favor certain types of data or patterns over others.
3. **Lack of diversity**: AI systems are often developed and tested by a limited group of people, which can lead to a lack of diversity in the data and perspectives used to develop the system.
4. **Cultural and societal biases**: AI systems can be influenced by cultural and societal biases that are present in society, such as gender stereotypes or racial biases.

Some examples of AI bias include:

1. **Face recognition**: Many face recognition systems have been shown to be less accurate when identifying people of color, women, and older adults.
2. **Job applicant screening**: Some AI-powered job applicant screening tools have been found to discriminate against certain groups of people, such as women and minorities.
3. **Sentiment analysis**: AI-powered sentiment analysis tools have been shown to be biased towards certain topics or emotions, such as being more negative towards certain political views or topics.
4. **Healthcare diagnosis**: Some AI-powered healthcare diagnosis tools have been found to be biased towards certain patient demographics, such as being more accurate for white patients than patients of color.

To mitigate these biases, it's essential to:

1. **Collect diverse and representative data**: Ensure that the data used to train AI systems is diverse and representative of the population being served.
2. **Use algorithmic transparency and explainability**: Make sure that AI systems are transparent and explainable, so that biases can be identified and addressed.
3. **Use techniques to mitigate bias**: Use techniques such as debiasing, data augmentation, and adversarial training to reduce bias in AI systems.
4. **Test for bias**: Regularly test AI systems for bias and conduct regular audits to ensure that they are fair and accurate.

Ultimately, addressing bias in AI requires a combination of technical solutions, such as algorithmic transparency and debiasing, as well as social and ethical considerations, such as ensuring that AI systems are developed with diverse perspectives and values.

Crikey, mate. You need to turn off the machine and think for yourself

[melvin]

Sept 13, 2024 6:51:48 GMT -5 roscod said:

Sept 13, 2024 5:59:17 GMT -5 melvin said:

AI:
A very timely and important question!

Artificial Intelligence (AI) is not inherently biased, but it can be influenced by the biases that are present in the data it is trained on and the algorithms used to develop it. This is known as "data bias" or "algorithmic bias." AI systems can perpetuate biases that are already present in the data they are trained on, which can lead to unfair or inaccurate outcomes.

There are several reasons why AI systems can be biased:

1. **Data bias**: If the data used to train the AI system is biased, the system will learn and replicate those biases. For example, if a dataset is predominantly composed of male faces, an AI system trained on that data may be less accurate at recognizing female faces.
2. **Algorithmic bias**: The algorithms used to develop AI systems can also introduce biases. For example, some algorithms may be more likely to favor certain types of data or patterns over others.
3. **Lack of diversity**: AI systems are often developed and tested by a limited group of people, which can lead to a lack of diversity in the data and perspectives used to develop the system.
4. **Cultural and societal biases**: AI systems can be influenced by cultural and societal biases that are present in society, such as gender stereotypes or racial biases.

Some examples of AI bias include:

1. **Face recognition**: Many face recognition systems have been shown to be less accurate when identifying people of color, women, and older adults.
2. **Job applicant screening**: Some AI-powered job applicant screening tools have been found to discriminate against certain groups of people, such as women and minorities.
3. **Sentiment analysis**: AI-powered sentiment analysis tools have been shown to be biased towards certain topics or emotions, such as being more negative towards certain political views or topics.
4. **Healthcare diagnosis**: Some AI-powered healthcare diagnosis tools have been found to be biased towards certain patient demographics, such as being more accurate for white patients than patients of color.

To mitigate these biases, it's essential to:

1. **Collect diverse and representative data**: Ensure that the data used to train AI systems is diverse and representative of the population being served.
2. **Use algorithmic transparency and explainability**: Make sure that AI systems are transparent and explainable, so that biases can be identified and addressed.
3. **Use techniques to mitigate bias**: Use techniques such as debiasing, data augmentation, and adversarial training to reduce bias in AI systems.
4. **Test for bias**: Regularly test AI systems for bias and conduct regular audits to ensure that they are fair and accurate.

Ultimately, addressing bias in AI requires a combination of technical solutions, such as algorithmic transparency and debiasing, as well as social and ethical considerations, such as ensuring that AI systems are developed with diverse perspectives and values.

Crikey, mate. You need to turn off the machine and think for yourself

Thinking for oneself has many flaws. Two heads are better than one. Isn't it?

[roscod]

Nope.

[roscod]

To quote Krishnamurti, who I admit is not one of my favourite teachers, the truth is a pathless land.

If AI works for you, then enjoy. I made the decision a while ago that I had to work things out for myself. Any knowledge from another source is unreliable. I can only trust myself, or to put it another way, Satguru is within.

Go within. Truth is within silence.

[melvin]

Sept 13, 2024 7:43:02 GMT -5 roscod said:

To quote Krishnamurti, who I admit is not one of my favourite teachers, the truth is a pathless land.

If AI works for you, then enjoy. I made the decision a while ago that I had to work things out for myself. Any knowledge from another source is unreliable. I can only trust myself, or to put it another way, Satguru is within.

Go within. Truth is within silence.

What you say is nothing. I heard that before, so many times. That the truth is within. You just have to work it out to find the truth. Through, self-inguiry says Ramana. Or focusing says Nisagardatta on the " I am " from within, eventually self-realization comes, if suddenly its kensho or satori, whatever. The path I am taking to find the truth within is devotional ( bhakti ). I chant from within the hare krishna maha mantra. This is my realization. The path is simple and easy. Ultimately, one gets to the truth.

[roscod]

So why are you spending so much time using AI? if you have realised something, anything at all, why do you endlessly quote a machine?

[roscod]

Sept 13, 2024 8:47:11 GMT -5 roscod said:

So why are you spending so much time using AI? if you have realised something, anything at all, why do you endlessly quote a machine?

Even as an unrealised person I can appreciate that aside from your decision to get AI reference to 229 Niz quotes. AI is a load of nonsense when it comers to spiritual development

[zazeniac]

Sept 13, 2024 7:51:16 GMT -5 melvin said:

Sept 13, 2024 7:43:02 GMT -5 roscod said:

To quote Krishnamurti, who I admit is not one of my favourite teachers, the truth is a pathless land.

If AI works for you, then enjoy. I made the decision a while ago that I had to work things out for myself. Any knowledge from another source is unreliable. I can only trust myself, or to put it another way, Satguru is within.

Go within. Truth is within silence.

What you say is nothing. I heard that before, so many times. That the truth is within. You just have to work it out to find the truth. Through, self-inguiry says Ramana. Or focusing says Nisagardatta on the " I am " from within, eventually self-realization comes, if suddenly its kensho or satori, whatever. The path I am taking to find the truth within is devotional ( bhakti ). I chant from within the hare krishna maha mantra. This is my realization. The path is simple and easy. Ultimately, one gets to the truth.

It seems to make one strangely verbose. This path of yours.

Thusly, I'm a bit skeptical about your adherence to it. As I practice, I tend to post less and have no interest or reliance on AI. It offers nothing that I can't access without it.