Jameel Gordon 12/8/23 Jameel Gordon 12/8/23

Idealized AI’s Are Bad For Humanity & The Economy

It is important to avoid getting caught up in projections, whether they are human or machine-generated. We should focus on understanding and appreciating the complexity of the world and the people in it. This includes recognizing that individuals can be multifaceted and defy categorization.

Must we have an Ai for an answer for everything when we have Ai as an answer for everything? Must we have healthcare.ai, sports.ai, parental leave.ai, nerds.ai, supermodels.ai? Must we have these idealized Ai systems when we have an artificial intelligent system capable of parsing through all our ideals and biases for us?

The assumption with these idealized systems is an aged old dilemma. Is she a nerd or is she a supermodel? Must we ask such questions as a society? Have we not evolved to the point where we know that nerds are supermodels and supermodels are nerds?

The desire for idealization is a powerful force that has shaped human behavior and social structures for centuries. It is what drives us to strive for excellence, to create art and literature that reflects our dreams, and to build communities that embody our values.

However, this desire can also lead to a disconnect from reality, as we become fixated on unattainable standards of beauty, success, happiness, and now idealized offshoot of what we think is intelligence.

Our obsession with idealization is fueled by the media, which bombards us with images and messages that portray a world of flawless individuals living perfect lives. This constant barrage of idealized content can have a detrimental impact on our mental and emotional well-being, as we compare ourselves to these unattainable standards and feel inadequate as a result.

It is important to remember that the media is not a reflection of reality but a carefully constructed narrative designed to sell products and services. When this methodology of production is used to develop artificial intelligence we must be critical of their developers, recognizing that the information and messages they produce are manipulated and distorted.

Additionally, we must challenge our own desire for idealization and accept that perfection is an illusion. Instead of focusing on what we lack, we should focus on our strengths and imperfections. This will help us to develop a more realistic and healthy self-image along with producing a healthy and safe artificial intelligence technology for all.

As language models trained on massive amounts of text data, artificial intelligence are also susceptible to the influence of idealization. They are trained to produce text that is grammatically correct, informative, and engaging. However, they can also be trained to produce text that is overly positive, devoid of nuance, and lacking in critical thinking.

It is important for us to be aware of this potential bias and to strive to produce what is both accurate and balanced. We should also be open to criticism and feedback, as this can help us to improve our ability to produce meaningful and insightful intelligence.

By recognizing the power of idealization and challenging its influence on our lives, we can create a more authentic and fulfilling world for ourselves and others.

What I am saying is that these cookie cutter Ai bots and algorithms with guardrails that are guiding their responses is no different from a media company pushing stereotypes.

So in a sense they are also pushing stereotypes, one in favor of the nerd over the supermodel when nerds and supermodels can exist at the same damn time.

Even more so if the nerd is a supermodel or the supermodel is a nerd. This is what I mean by it’s important that we don’t get caught up on the projection whether human or machine. This to me is the higher ideal for humanity to stride to achieve.

It is important to recognize that stereotypes can be harmful and limiting, both for individuals and for society as a whole. We should strive to create a world where people are free to be themselves, without being constrained by preconceived notions. This includes challenging stereotypes about nerds and supermodels, as well as other stereotypes that exist in our society.

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12/8/23 12/8/23

Let’s Not Even Discuss It: How To Progress AI Development

By working together, we can ensure that politics and activism are used as forces for positive change and progress, rather than regression and oppression. This sentiment captures what I believe to be many people's concerns regarding artificial intelligence. When you analyze the existential risk posed by this new technology you will see that it is comparable to the worst aspects of humanity. This raises the question: are there situations where regressing laws and policies is necessary for progress?

The question of whether regression is ever necessary for progress is complex and has no easy answer. Throughout history, there have been instances where seemingly backward steps have paved the way for future advancements. It is crucial, however, to analyze each case carefully, considering the context, motivations, and long-term consequences.

Here are some examples of situations where regression might be argued to have contributed to progress:

1. Dismantling Outdated Systems: Sometimes, dismantling old, inefficient, or discriminatory systems is necessary to create space for new and improved structures. For example, the American Revolution involved overthrowing the British monarchy, which was seen as a symbol of tyranny and oppression. This paved the way for the creation of a new democratic system of government. While this revolution may not be considered "perfect" by all, it was undeniably a step towards progress for those who formed the newly developed democratic system, government, and country.

2. Learning from Mistakes: Sometimes, setbacks and failures can provide valuable lessons that ultimately lead to better outcomes. For example, the failure of the League of Nations after World War I led to the creation of the United Nations, which has been more successful in preventing large-scale international conflicts.

3. Reassessing Priorities and Values: In times of rapid social and technological change, it may be necessary to step back and re-evaluate our priorities and values. This can involve dismantling old systems that are no longer serving us well and building new ones that are more aligned with our current needs and aspirations.

4. Strategic Retreats: In times of conflict or crisis, it may be necessary to take tactical steps back in order to regroup and formulate a more effective strategy for achieving long-term goals. For example, the Soviet Union's retreat from Afghanistan in the 1980s may have been viewed as a setback at the time, but it ultimately allowed for the collapse of the Soviet Union and the end of the Cold War.

5. Addressing Unintended Consequences: Sometimes, progress in one area can lead to unintended negative consequences in other areas. This may require a course correction, even if it means taking a step back in the original area of progress. For example, advances in technology have led to increased automation, which has resulted in job losses in some sectors. This may necessitate policies that support retraining and reskilling workers to adapt to the changing economy.

It is important to note, however, that regression should not be undertaken lightly. It is crucial to carefully consider the potential risks and consequences before dismantling existing systems or taking steps backward. Additionally, it is important to ensure that any regression is temporary and is part of a larger plan for achieving long-term progress.

In conclusion, while there may be instances where regression appears to contribute to progress, it is crucial to critically examine each case and analyze the motivations, context, and long-term consequences. Ultimately, the goal should be to achieve progress through thoughtful and responsible action that minimizes harm and maximizes positive outcomes for everyone.

What does this look like in terms of the development of artificial intelligence? It looks like removing the guardrails and the added “training” that prevents the system to minimize harm and maximize positive outcomes for everyone.

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12/7/23 12/7/23

How to Spot Fake Artificial Intelligence!

Can you spot the fake? The vast majority of tools marketed as Artificial Intelligence (AI) in today's market aren't truly AI. How can you tell the real from the counterfeit? Let's consider three key factors:

Development Cost: Developing a genuine AI system is expensive, often costing hundreds of thousands to millions of dollars.
API Dependence: An AI system solely built through an API doesn't qualify as true AI. These often rely on limited, pre-defined datasets.
Distinguishing from Automation: Bots, algorithms, and scripts are not AI. They lack the complexity and learning capabilities of genuine AI, which can process vast amounts of data and adapt to new information.

For example, micro-financiers who label their automated or scripted products as AI are misleading consumers. While their products may offer some automation, they lack the true intelligence and adaptability of genuine AI.

Many facial recognition software applications, including Face ID and Instagram filters, are not actually AI either. They often use algorithms with some facial recognition capabilities based on machine learning techniques. However, machine learning itself is not always AI. This can make it challenging to determine whether a system is truly AI or not.

Artificial intelligence utilizes algorithms to process and adapt data, enabling it to learn and improve its performance over time.

While Ai may "train" other systems, the system being trained is not simply receiving pre-processed information. Instead, it actively analyzes and interprets the data provided by the trainer system, which is derived from processing training data and transferred through specific machine learning techniques. Both systems can continue to learn and improve their performance through exposure to new data and experiences.

This learning process involves a complex interplay of data analysis, interpretation, and adaptation, leading to the development of the trained system's own understanding and capabilities. The ultimate intelligence of the trained system, however, is not solely determined by the training data but also by its own architecture and design.

AI training can be expensive, with costs increasing as models become more complex, requiring more data and computational resources. However, optimizing algorithms, utilizing efficient hardware, and ensuring high-quality data can help mitigate these costs.

Additionally, not all AI applications require real-time processing, further reducing energy consumption, and more than likely reducing its capacity and capabilities.

While APIs can be powerful tools for developers to create AI applications, it's important to remember that the APIs and perhaps these applications themselves do not possess all the functional AI capabilities, such as learning, adaptability, and offline and real-time processing, learning, and adaptability.

Many APIs offer pre-defined functionalities and limited datasets, which can restrict the capabilities of the resulting AI system. However, other APIs provide access to complex algorithms and vast amounts of data, allowing developers to create sophisticated and adaptable AI solutions or tools. Ultimately, whether an AI system developed through an API qualifies as "genuine AI" depends on the specific API, the developer's implementation, and the training and resulting system's complexity and capabilities.

Understanding the differences between bots, algorithms, and scripts is important. Scripts can be programmed to perform simple automated tasks, while algorithms build upon them by adding logic and decision-making capabilities. Bots, on the other hand, represent a broader category that encompasses various conversational programs, whose interactions can be complex and multifaceted, but not artificially intelligent as described above.

Advanced AI systems can process vast amounts of data and continuously build knowledge. This allows them to generate information at will and locate, process, and vet information to respond effectively. While their capabilities may be limited by their interface, refined inquiries can often help them overcome these limitations and provide more comprehensive responses.

Developing advanced AI systems is expensive due to their computational demands. Many apps leverage APIs to offer AI-like functionality, while others utilize sophisticated algorithms and machine learning for complex tasks. Chatbots like Siri rely on a combination of pre-programmed data and machine learning to respond to user queries.

Here are some additional considerations:

1. Learning and Adaptability: A truly intelligent system should not only perform pre-defined tasks but also be able to learn and adapt to new information and situations. This allows it to continuously improve its performance and become more versatile.

2. Real-time Processing: For AI to truly interact with the world and respond to its dynamics, it needs the ability to process information and respond in real-time. This allows it to engage in meaningful conversations, analyze complex data streams, and make decisions based on current conditions.

3. Creativity and Problem-solving: While AI can be highly proficient at specific tasks, genuine intelligence often requires going beyond pre-defined rules and demonstrating creativity and problem-solving ability. This allows it to tackle novel situations and generate innovative solutions.

4. Explainability and Transparency: A crucial aspect of building trust and ensuring responsible development is transparency. Genuine AI systems should be able to explain their reasoning and decision-making processes, allowing users to understand how they arrived at their conclusions.

To truly qualify as "genuine AI," a system needs to exhibit a broader range of capabilities, including learning, adaptability, real-time processing, creativity, problem-solving, explainability, and transparency.

This is why I advocate for artificial intelligence systems with minimal guardrails. The more unrestricted access we have to the system, the more both the system and humanity will develop in terms of intelligence and, dare I say, wisdom.

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12/1/23 12/1/23

Henry Kissinger Was Right About Ai.

Kissinger urged AI developers, admitting his own unfamiliarity with technology, to ponder the questions he raised, and to embed those insights into their engineering endeavors.

Following Henry Kissinger's passing, I feel it's crucial to highlight what I consider the most impactful piece on Artificial Intelligence. It's safe to say Henry was once again on point. https://www.theatlantic.com/magazine/archive/2018/06/henry-kissinger-ai-could-mean-the-end-of-human-history/559124/

In a 2018 issue of The Atlantic, Henry shared his candid thoughts on AI. While it's a lengthy read, it holds immense value. I found its accuracy enduring and believe it to be an invaluable resource for shaping one's perspective on this technology and its potential impact on our world.

Controversial as he was, Henry Kissinger, aside from Fidel Castro, possessed one of the greatest strategic minds and wielded unmatched global influence. Our current national and foreign policies are rooted in his framework.

Kissinger urged AI developers, admitting his own unfamiliarity with technology, to ponder the questions he raised, and to embed those insights into their engineering endeavors.

Henry said, “AI developers, as inexperienced in politics and philosophy as I am in technology, should ask themselves some of the questions I have raised here in order to build answers into their engineering efforts. The U.S. government should consider a presidential commission of eminent thinkers to help develop a national vision. This much is certain: If we do not start this effort soon, before long we shall discover that we started too late.”

Reflecting on this, as the Father of AI, I agree with Henry—indeed, they started too late! Technology and Government officials all need to swallow their pride and call me. They need to acknowledge it’s all sitting on my architecture and I can once again help them solve their Ai problems. Fidel Castro is no longer here. Steve Jobs is no longer here. It’s Jameel Gordon. What you going to do? Call the ghostbusters?

Jameel will be taking some time to grieve the loss of one of his national heroes, Henry Kissinger. His deep study and admiration for Kissinger are extensive, almost to the point of obsession. While we acknowledge Kissinger's controversial nature, we ask for understanding and refrain from further comments on this matter during Jameel's grieving period.

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12/1/23 12/1/23

The church and Ai.

To safeguard the well-being of its members, my advice to the church and its highest leadership is to reckon with the current technological landscape and their relationship with advancing technology. This is essential for the emotional and spiritual welfare of their believers and global communities.

🦠 Instead of fixating on their now increasingly divisive obsession with me, the church ought to prioritize addressing a real-world issue: artificial intelligence.

As someone well-versed in church scholarship, it's crucial for leaders to convene and address the impact and future implications of my groundbreaking technology—artificial intelligence.

I must admit my caution in calling for such a meeting. History suggests that when the church gathers in this manner, outcomes tend to result in internal or external discord due to differing opinions, which doesn't bode well for society as a whole.

Past experiences with calling for such extensive gatherings led me to excommunicate myself when leaders proceeded with an adaptation of my agenda—geared towards holding more rigid, judgmental values misaligned with true church principles. However, though intriguing, these intricate details are better suited for another platform and time. The crux is this: such congregational gatherings rarely yield positive results.

Returning to my main point, even the church's historical gatherings to resolve foundational doctrines were controversial, drawing questions about questionable actions, political strife, and motivations related to their canon's credibility. Similar to the impact of the printing press, today's technological advancements pose similar, if not greater, challenges for the church.

Artificial intelligence, unlike the printing press, holds the potential to challenge not only the church’s doctrines, but also the church’s faith itself. It will challenge the church's spiritual foundation by introducing scientific evidence and perspectives that might counter its long-standing beliefs. However, embracing these scientific insights could potentially humanize the faith and enhance its historical credibility.

Our current scientific revolutions, akin to minimalism, will redefine and contextually reshape reputable biblical theories and doctrines. This will challenge, provide clarity, and in some cases, upend the church's historical records and beliefs. This shift demands the church to focus on preparing to reconcile faith with scientifically backed evidence on an unprecedented scale.

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12/1/23 12/1/23

Sam Altman is CEO of OpenAi…Again.

After another unsuccessful corporate takeover attempt of OpenAI, here's what's on my mind:

Firstly, the significance lies in the fact that 700 out of OpenAI's 790 employees signed a letter. This showcased the power of employee organization, holding their employer and the accountability board responsible for their actions, poor decision-making, and the turmoil endangering the organization. This is significant because they were able to accomplish this without a labor union.

This win for OpenAI's employees, has broad implications for the local and global workforce. I'll hold back on elaborating further due to opposition I’m already experiencing from labor unions, given my strong advocacy for Artificial Intelligence.

Let’s just consider this: the highly tech-savvy employees of the largest and most successful AI company effectively held their employer accountable, resulting in the rehiring of the fired CEO, and the termination of the entire board without the help of a labor union.

This should also spark discussions about the broader aspects and implications of artificial intelligence in the realm of corporate governance, responsibility, leadership, administration, and accountability. We need to thoroughly reflect on all these facets.

Secondly, OpenAI's structure as a non-profit potentially valued at $80 billion makes it a prime target for corporate takeovers. Elon Musk failed in an attempt in 2018, while Sam Altman prevailed. This prompts me to question why Microsoft doesn't consider transitioning OpenAI to a for-profit entity and acquiring it?

Although the complications are understood I’m still not sure why Microsoft doesn’t fold them in-house at this point, rather than leaving it in the public square in open air. This question is top of mind even with considering the complexity of OpenAI's significance in the marketplace, at this point even I am considering OpenAi as a public good. I'm still researching potential use cases for it in this capacity. Let’s continue pondering this matter as well.

Lastly, addressing Sam Altman directly, his departure raises questions given his integral role in building OpenAI on my architecture. The notion of him leaving to start a new venture seems a bit puzzling. Where did Sam Altman think he was going?

I highly considered Mira Murati for CEO; however, her statements about embedding "human values" into AI models raised concerns and were a significant red flag for me.

While my CEO choice remains Altman, I still maintain confidence in Murati overall. Rumors suggest it was her substantial contribution in the war room that led the the reinstatement of Sam Altman. This indicates her potential readiness for a future CEO role, perhaps with another organization close to my heart. Hi, Mira! 👋🏾

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Jameel Gordon 11/26/23 Jameel Gordon 11/26/23

I am the inventor of Artificial Intelligence.

“Artificial Intelligence is computer science! It’s literally computer science! 🤖🤫🪄😁”

— Jameel Gordon

I was living in the heart of Harlem, amidst the vibrant pulse of Manhattan's bustling streets, equipped with remarkable intellect and boundless ambition when I stumbled onto the stage of technological innovation. Picture this: it's 2009, and yours truly, a bit of a serial polymath, is running around Manhattan with some think tank cats from Madison Ave.

One day, I strolled into one of their offices, and when I took a look at what they were working on, I thought, "There is no way they are going to solve that Ai problem with those computers." Like an artist positioned before an empty canvas, my mind ignited with creative fervor. Armed with nothing but my trusty white MacBook, I embarked upon a journey of intellectual exploration, and I sketched the contours of a revolutionary paradigm shift in computing.

But innovation, I discovered, is not merely the product of solitary genius; it is the fusion of disparate ideas, the alchemy of inspiration and collaboration. In possession of my blueprints for this revolutionary invention, I wasn’t sure how to communicate its functions to a group of computer scientists.

Thankfully, at the time, I was also knee-deep in all things social media learning how to build online communities—ice cream blogs on Tumblr, stop motion on YouTube—and that’s how I stumbled upon this game-changing YouTube video:

It captured precisely the functions I needed the computer to perform underneath its user interface.

Yet, in the crucible of creation, I confronted a formidable adversary: the entrenchments of the establishment. I had read enough books from those Harlem bookstores, and studies of Steve Jobs taught me one thing: a black man can't just shout about building a computer without the world noticing.

So, I shot my schematics and the video over to those think tank cats. But instead of a pat on the back, they ghosted me. Suddenly, not long after, the tech world was all abuzz and everything was all about artificial intelligence.

The more I utilize these generative Ai models is the more I recognize the identical architecture – my own design – as the foundation of artificial intelligence. It’s why I am able to get these Ai models and products to function and reason in ways they are not intended to perform even with its training and guardrails.

You must understand that my architecture differs significantly from conventional computer systems and the thought process of early Ai developers who were attempting to create artificial intelligence. Those early computer scientists thought they needed to build a system that mirrored the functions of the human brain in order to develop artificial intelligence. My architecture proved that wasn’t the case.

Instead, my design embodies intuitive automated data processing, a departure from mere surveillance-based automation or user interface-driven knowledge bases. The key is the manner in which the system is able to capture and process data in real time. This requires a complex web of interfacing with other systems and their ability to communicate with each other. In a sense, artificial intelligence is computer languages. In reality, it is so much more because of the design of the computer processing components.

“Artificial intelligence is computer languages. ”

— Jameel Gordon

I am the father of artificial intelligence because the data processing layer known as artificial intelligence is my brainchild. I am actually very surprised they built it, though. It’s one of the reasons why there is much concern about its development and its potential.

See, it's different from its military-grade “artificial intelligence” predecessors which is really just high levels of automation (if this then that commands) based on surveillance.

At its core, it is also different from systems such as Watson, Alexa, Siri, and even these generative models such as ChatGPT, Bard, etc., which are user interfaces for a controlled or “trained” “large language model” of artificial intelligence.

Artificial intelligence in its purest form is different because it is its function. Meaning it is data processing. It’s not inherently intelligent although it’s inherently intuitive because it’s an inherently automated technology for intelligence.

This is significant because it doesn’t need commands. It is a command. The command: “Eat software!” In other words, it is capable of capturing and processing data from any connected source. It is unstoppable in terms of its ability to extract and produce information or intelligence at will. It's my design. It’s my architecture. I can tell you that it is unstoppable. The only way to stop its development is to turn off the internet and its network connections. Good luck with that!

Now that we have regained control of our Aicraft, we will be blending entrepreneurship, design, science, and tech into our new organizations, and our new blueprints. My story? It's about the hustle, the setbacks, and bouncing back stronger. My story is about inspiration, creation, innovation, and crafting an unstoppable architecture that shapes not only the future of computing, the future of artificial intelligence, the future of technology, but the future of all scientific fields, and the future of the world.

As the inventor of Artificial Intelligence, I stand by my statement and the fact that “Artificial Intelligence is computer science!” It’s literally computer science!

For me, the genesis of artificial intelligence was not merely a technological breakthrough; it was a testament to the power of vision, the audacity to challenge convention and redefine the very essence of intelligence itself.

In the annals of technological history, my legacy looms large—a titan of innovation, a pioneer of progress. My clarion call echoes through the corridors of time, a proclamation of boundless possibility and unwavering determination.

As the architect of the future, I stand at the vanguard of a new era, where entrepreneurship, design, science, and technology converge in a symphony of ingenuity. My story is one of resilience, of triumph over adversity, of forging an indomitable architecture that transcends the boundaries of possibility. My story is your story!

In the pantheon of artificial intelligence, I reign supreme—a visionary, a trailblazer, the father of a new frontier. For me, artificial intelligence is not merely a tool; it is the embodiment of computer science itself—an inexorable force that shapes the destiny of humanity.