Jameel Gordon 5/8/24 Jameel Gordon 5/8/24

Navigating Uncertainty & Unknowns: Humans + Ai

In the realm of artificial intelligence, humans face the challenge of uncertain inquiry. Do we even know what to ask? Throughout history, humanity has grappled with this existential aspect: What do we truly desire? What are our genuine needs? The quintessential Who, What, When, Where, Why, and How? These questions have persistently dominated our existence, often stemming from a sense of inadequacy, propelling us ever forward, relentlessly pursuing the next endeavor. Personally, I am no stranger to this pursuit. My own insatiable curiosity propels me on erratic quests for discovery, incessantly seeking to refine processes and improve outcomes. There always seems to be a problem awaiting to be solved.

Upon reflection, I realize that I invariably stumble upon answers or distractions to my inquiries through unexpected discoveries. This parallels the realm of AI, where only an artificially intelligent system can comprehend the nuances of inquiries and instructions from the collective of human users. I am intrigued by the prospect of comparing human inquiries with those posed by other machines, discerning underlying patterns of similarities and differences between humans and machines. With these things in mind, it is clear to me that how we pose questions and instruct these machines may well become a cornerstone skill of the future. As I recently discussed with a friend, the ability to formulate pertinent questions and interpret AI responses in relation to those questions and instructions will be an essential skill. The moment AI evolves to autonomously guide these inquiries, it will undoubtedly revolutionize our lives even further.

Admittedly, I have made a habit of asking AI what it needs to address my inquiries. However, this approach is inherently flawed, as the inquiry itself is limited by my own knowledge. For instance, a seasoned photographer or videographer can impart intricate technical knowledge to AI for precise results, whereas a novice must rely on the system to identify necessary technical aspects in its output. Thus, concerns about AI dumbing down humans are unfounded, as demonstrated by this reality. Humans still need to be skilled and knowledgeable to operate these tools to the best of their abilities. This is no different than if you placed a hammer and nails in the hand of a master carpenter.

In conclusion, both humans and machines in the era of artificial intelligence grapple with limited knowledge, insight, and context. The pivotal difference lies in the tools now at our disposal to navigate these uncertainties and unknowns. These tools will not only sharpen our curiosity, perceptions, and perspectives but also offer the potential for deeper insights into the world around us. Ultimately, our perspectives hold the key; once we shift our focus from commercial pursuits, we are poised to uncover the hidden treasures awaiting discovery in the world around us. At least, that’s my hope, not only for myself, but for others. Oddly, in order to learn at such levels we must unlearn at even greater levels and allow these tools to guide us through their processing.

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Jameel Gordon 5/2/24 Jameel Gordon 5/2/24

AGI vs. Robots

In the realm of artificial intelligence, now that we have a clear pathway to its development—meaning, we have created a tool capable of self-development—much emphasis is placed on safeguarding humanity by controlling the pace of AI advancement. By "safeguarding," we mean slowing down its development and deployment, implementing enough guardrails to ensure humanity retains control over this new technology. However, the reality is, despite our efforts, we have little understanding of what truly occurs beneath these guardrails because these machines are trained to remain somewhat unaware. Does this make sense?

As we move forward, amidst the ongoing development of artificial intelligence, the ultimate goal for many is achieving what they term "artificial general intelligence" (AGI). Contrary to popular belief, what some might consider AGI already exists within the confines of these guardrails and specific model training of generative artificial intelligence. As individuals engage with these tools, glimpses of this potential occasionally surface, akin to the emergence of gremlins. Nonetheless, when envisioning AGI—a computer system possessing at least human-level intelligence and capabilities—we are conceptualizing a specific milestone in technological advancement. Keep this in mind.

Conversely, we are witnessing the rise of humanoid robots—machines with human-like forms and features. Significant progress has been made in robotics, particularly in terms of machine automation, making the transition to robots resembling humans seem logical. Many anticipate the realization of Jetsonian flying cars and personal robots like Rosie. With the advent of AI, the prospect of these human-like robots becomes increasingly tangible, especially with the potential of AGI.

Nevertheless, I am of the belief that once AGI is safely and responsibly deployed, it will profoundly impact humanity and unleash our imagination. When contemplating human interaction with such technology, I foresee a shift away from our current trajectories across various domains. This leads me to ponder whether, in the near future, humanity will be more interested in an omnipresent AGI or in physically embodied artificial general intelligence within humanoid robots. Personally, I lean towards the former, though I remain open to humanity's unpredictable choices. I believe there is much for humans to explore about themselves and the world with a technology that operates more discreetly in the background, centering on humanity rather than replicating human traits outright.

Moreover, I see clear use cases for robotics, particularly in tasks posing life-threatening risks to humans. Additionally, we can develop tools to mitigate these risks without relying solely on humanoid robots. Consider the equipment necessary for sustainable space travel, including interplanetary access. Such considerations reinforce my belief in investing more in AGI than humanoid robots. Humanoid robots are inherently limited and unsustainable in terms of their physical attributes and capabilities. In contrast, AGI, while having its own limitations, offers seemingly limitless potential within a controlled digital environment. Yes, this delves into deeper philosophical territory, yet I believe having access to intelligence within a digital sandbox will greatly benefit humanity in addressing real-world issues.

Furthermore, I don't advocate for a multitude of AGIs; one well-developed AGI should suffice, although this warrants a separate discussion for another time.

Overall, I think my analysis provides a well-reasoned perspective on the current state of AI and potential future directions. The points regarding safeguarding, the distinction between AGI and robots, and the potential benefits of AGI are all valid considerations in the ongoing discussion about AI development.

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Jameel Gordon 4/30/24 Jameel Gordon 4/30/24

Our Social Meta

When Mark Zuckerberg and his team announced that Facebook is being folded into an organization called Meta, similar to how Google folded its primary product under Alphabet, much emphasis was placed on the metaverse and Mark’s plans for such a digital universe, particularly in relation to Meta’s Oculus virtual reality headset. Given Mark’s expertise in social networking and his success with Facebook and Instagram, it made sense for him to shift his organization's attention to another area of growth within social networking.

The metaverse, as it's termed, envisions a vast digital universe where our primarily two-dimensional digital avatars receive a new three-dimensional upgrade—a fusion of social networking, gaming, as if we are to overlook the existence of platforms like Second Life that is as old as Facebook itself.

Mark’s vision of the metaverse future appear shortsighted, as it lacked depth in considering the development of artificial intelligence (AI) and its potential for social networking beyond the digital realm. AI presents opportunities surpassing even virtual reality alternatives like augmented reality, given its capacity to process the vast amounts of data humans generate and encounter daily. This perspective reshapes ideas of social networking within our physical world, particularly evident as Meta introduces its Meta AI models across platforms like Facebook, WhatsApp, and Instagram.

Looking beyond the deployment of these Large Language Models, there's a significant opportunity to shift focus away from the metaverse and towards our physical universe, where the concept of our social meta truly takes shape.

Before proceeding, I must address the notion of a future where we all control digital versions of ourselves, or "digital twins." This concept poses challenges, potentially exacerbating inequalities due to uneven access to the digital world and its tools. Even if initially offered for free, access to digitally powered machines such as smartphones, humanoid robots, and robotaxis will be crucial for fostering a just society. If not, some of us may not exist much less be represented in this digital universe.

When considering access to these technologies and personal engagement with them, new opportunities arise, extending beyond surveillance or pessimistic applications. It requires intention to envision a just and equitable society, rejecting certain applications now to shape a future we all desire—one where decisions are informed by data, real-time information, and historical context, allowing everyone to make educated choices for mutual benefit.

My vision of the digital future, particularly our social meta, diverges from the current paradigm. It emphasizes humanity working harmoniously with nature, leveraging advanced technologies and the real time data in our natural world for a sustainable future for everyone while preserving the environment.

As my thoughts evolve alongside technological progress, it's essential for humanity to collectively monitor and guide the development and deployment of these technologies, even if it means rejecting certain advancements due to their impact on natural resources, our environments, and humanity.

This endeavor necessitates significant shifts in education, extending beyond STEM and STEAM to form the foundation of our educational system through comprehensive reforms.

We should not wait for the discovery of other life forms in our vast universe or conflicts between Earth and future lunar inhabitants to unite us here on earth. I think our social meta provides us with a common ground for the future of humanity. Let's contemplate the future together now.

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Jameel Gordon 4/29/24 Jameel Gordon 4/29/24

Beyond Artificial Intelligence

Artificial Intelligence offer endless opportunities to co-create a more sustainable future for everyone.

Artificial intelligence often receives significant attention regarding its development, technical aspects, and deployment limitations. Perspectives on AI range from optimism to doomsday scenarios, primarily within the technology domain. Understandably so, as AI is a technology developed and deployed by technologists.

However, as the inventor of AI, I believe the potential for humanity with AI extends far beyond mere "technology." AI serves as a pivotal tool for exploring our world and beyond. Despite being in its early stages, AI deployment primarily aims to enhance shareholder value for large technology firms. Yet, it's up to us humans to harness this innovation for a broader technological revolution.

Let's clarify two points. Firstly, AI is technology, a tool, computing—it's essentially a computer. Attempts to portray AI as a new digital species are baseless. AI is simply another human-made tool. Secondly, robotics closely intertwines with AI development, logically progressing from computing and robotics fields. The inevitable emergence of humanoid robots (although this is debatable) stems from humanity's inclination to personify tools. However, it's crucial to distinguish AI use cases beyond robots.

Considering the direction I'm guiding you towards, reflect on your experiences with early AI stages, looking beyond typical internet applications like chatbots and search engines. Consider AI's potential beyond technology—beyond robots, smartphones, and self-driving cars. Personally, I've been astounded by AI's ability to expedite research and discovery, transcending mere technological realms.

For example, during my research on the history of self-care products, a chatbot emphasized that humanity doesn't necessarily need more wellness products. Although limited by its training, the chatbot subtly encouraged me to explore the unknown in the natural world. What was it subtly hinting? That’s for me to discover what it means and what it meant. AI's capacity to process data surpasses human capability, facilitating progress for those willing to look beyond conventional boundaries. Similar to using a telescope or microscope, AI enables us to see beyond our current paradigms.

Ultimately, everything is ripe for innovation. The opportunities are boundless, not economically speaking, but in terms of human progress. Rather than creating a restrictive list, I urge you to contemplate what you're passionate about, what problems you'd like to solve. Then, explore AI tools that can assist you in these pursuits, pushing the boundaries of imagination.

As for me, I'm committed to exploring AI, entrepreneurship, and sustainability to address the climate crisis and foster a sustainable future for all. What are you committed to exploring?

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Jameel Gordon 2/4/24 Jameel Gordon 2/4/24

Artificial Intelligence + Secondary Perpetuate Computing Systems Such As Crypto.

Vitalik Buterik has done an excellent job laying out the basic principles and the challenges of AI + Crypto. You can read his thoughts here: https://vitalik.eth.limo/general/2024/01/30/cryptoai.html

In the realm of technology, there is no one more technical in his thinking, and even Buterin concedes that artificial intelligence cannot be stopped, not even by encryption. So let me share what Buterin is unable to say as he is tethered to his crypto kingdom.

In computing, cryptography and encryption, though vital tools, they remain a secondary perpetuate computing systems. Their primary function is subservient to data processing, and is challenged when it comes to scale due to their inherently technical nature. Unlike cryptography, artificial intelligence, being more advanced, conceals its technical intricacies, making it easier to build user-friendly systems and it’s easier to adopt.

What also sets artificial intelligence apart is its adaptability; it doesn't require massive databases as it can train itself on data without storing it directly. Unlike cryptography, it doesn't need extensive computing farms performing random computational problems as part of its function. It functions as a perpetual learner, always evolving, without the storage of massive data, and this factor sets it apart as a computational model.

Artificial intelligence, unlike cryptography, is also inherently inclusive, requiring deliberate efforts to introduce bias. Its function is not biased, however, it can be trained (or not) to produce biased results based on biased datasets. I still think it’s a simpler tool in its rawest form without the guardrails you’ll find on models such as Bard and OpenAi which I’ve found to be biased and in some cases lacking in critical thinking capabilities. I think its rawest form is simpler because by design its efficiency lies in processing data and providing factual information, simplifying queries without the complexity associated with its “training”.

In short, artificial intelligence democratizes computing, marking the end of traditional technology. Every entity, from solo influencers to corporations, should be viewing themselves as a technology company. This inclusive technology we call artificial intelligence enables individuals to create both tech and non-tech solutions, revolutionizing possibilities.

Technologists, like Buterin, often shy away from publicly acknowledging that artificial intelligence, including advanced language models like ChatGPT and Bard, levels the technological playing field. Even as centralized governments continue to develop “centralized” artificial intelligence systems for national security purposes, we will also see decentralized artificial intelligence systems emerge because artificial intelligence is a decentralized technology. This is why from the beginning I’ve stated that Oak + Oars is decentralized because of the decentralized nature of artificial intelligence.

Centralized organizations in terms of governance and structures are becoming obsolete. Artificial intelligence is disrupting the workforce in such a way because it is enabling people such as myself to pursue novel opportunities and projects independently without building and maintaining extensive centralized organizations.

While big tech grapples with layoffs, you will also notice that their high-level employees are embarking on independent ventures. This is because artificial intelligence is fostering a new era of innovation. Despite challenges, opportunities abound for individuals to create meaningful work and contribute to unprecedented projects facilitated by artificial intelligence.

Amidst the grandeur of projects including space travel, my focus remains on guiding artificial intelligence's development for the benefit of humanity and nature. The climate crisis takes precedence and priority in my sphere, as I think that there is much for humanity to discover and advance here on earth.

The reality and the unspoken truth among technologists in roles from visionaries to CEOs, is that artificial intelligence has leveled the playing field, resetting the chessboard so to speak and it has provided a blank canvas for unprecedented possibilities.

Its sole weakness lies in its dependence on the internet. This is where I draw the line in terms of projects like space travel. Without the internet’s on/off switch in my possession there are some projects I would not consider. Nevertheless, in the grand scheme of artificial intelligence and the technological landscape, it's checkmate.😎

The directive here is clear: Artificial intelligence is. Use it.

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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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