Building Greatness in AGI

Building greatness in artificial general intelligence (AGI) involves emulating the qualities that define human greatness: desire, passion, talent, ability, and a bold attitude. These attributes drive individuals to achieve extraordinary things. Philosophers like Aristotle viewed greatness as an alignment with virtue and the pursuit of excellence. Similarly, AGI can be designed with some of these traits. Advanced reinforcement learning can instill a drive for problem-solving, while multi-modal learning and continuous fine-tuning can develop diverse skills and abilities. In his 1948 report "Intelligent Machinery," Alan Turing suggested, 

"It seems probable that once the machine thinking method had started, it would not take long to outstrip our feeble powers… They would be able to converse with each other to sharpen their wits." 

Turing also envisioned machines capable of learning and evolving, stating, 

"Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's?" 

By incorporating these strategies, AGI can emulate human greatness and potentially surpass it.

Philosopher Friedrich Nietzsche remarked, 

"He who has a why to live can bear almost any how," 

highlights the role of purpose and passion in achieving greatness. By integrating these human attributes into AGI as high level goals driving the learning and results, we can foster AI systems that not only perform tasks but also adapt, learn, and innovate, embodying the essence of human greatness.

Additionally, technical strategies such as incorporating neural networks that mimic the human brain's structure can enhance AGI's learning capabilities, while embedding ethical frameworks ensures these machines align with human values. As Steve Jobs once said,

"The only way to do great work is to love what you do." 

By fostering a sense of purpose and passion within AGI, we can push the boundaries of what these systems can achieve, mirroring the relentless pursuit of excellence that characterizes human greatness. Turing also noted the importance of randomness in machine learning, stating, 

"Each machine should be supplied with a tape bearing a random series of figures... This would result in the behavior of the machine not being by any means completely determined by the experiences to which it was subjected." 

This highlights the potential for AGI to develop unique problem-solving abilities and innovative thinking, essential components of human greatness.

Further read

• LLM, Us and Neuroplasticity

• "Are you sure?": Unveiling the Quest for Human-Like Artificial Intelligence

• Designers, creativity and AI

• A LLM as a reflection of our inner most desires

• Should AGI be a she, he, or a it? 

• Teaching LLMs common sense thinking

• The Ethical Nexus in an Era of Surrogate Machines

• Applying Asimov's Laws to Robot Taxis Confronted by Threats

• The Moat Matrix: LLMs Shape, but Don't Define the Moat

• From Infinite Improbability to Generative AI: Navigating Imagination in Fiction and Technology

• Human vs. AI in Reinforcement Learning through Human Feedback

• LinkedIn Profiles in the Age of Generative AI

• Generative AI for Law: The Agile Legal Business Model for Law Firms

• Generative AI for Law: From Harvard Law School to the Modern JD

• Unjust Law is Itself a Species of Violence: Oversight vs. Regulating AI

• Generative AI for Law: Technological Competence  of a Judge & Prosecutor

• AI to Make us Super-Scientist, not Super-humans

• Law is Not Logic: The Exponential Dilemma in Generative AI Governance

• Generative AI & Law: I Am an American Day in Central Park, 1944

• Pushpaka Vimana, Conceptualizing Vedic Technology & Diwali

• Generative AI & Law: Title 35 in 2024++ with Non-human Inventors

• Generative AI & Law: Similarity Between AI and Mice as a Means to Invent

• Generative AI & Law: LLMs are not Stochastic Parrots

• The Age of AI and the Charm of Tradition

• Diversity, equity, and inclusion (DEI) with Generative AI

• Need for Machine Consciousness & The Chinese Room Argument

• Generative AI & Law: The Evolving Role of Judges in the Federal Judiciary in the Age of AI

• Eating Shellfish to Artificial General Intelligence (AGI)

• Embedding Cultural Value of a Society into Large Language Models (LLMs)

• Lessons in Leadership: The Fall of the Roman Republic and the Rise of Julius Caesar

• Selling Dreams vs. Racing to Win

• LLMs as a Tool to Preserve a Society in History

• Beginning of The End for AI; Beginning for Generative AI

• Decentralized Truth & What is Means for AI Regulations

• Anthropomorphizing AGI

• The First Amendment & The Freedom to Think For Ourselves

• AI as a Common Carrier - A Utility

• Generative Native World: Deliberating Blame

• Generative Native World: The Right to be Let Alone

• One Day Can Last For Ever: Work & Life 

• Justice Sotomayor on Consequence of a Procedure or Substance

• The Moral LLM

• From France to the EU: A Test-and-Expand Approach to EU AI Regulation

• Beyond Human: Envisioning Unique Forms of Consciousness in AI

• Silent Enim Leges Inter Arma

• Protoconsciousness in AGI: Pathways to Artificial Consciousness

• Building Moral Machines

• AI Regulation: Reflections from Roe v. Wade (1973)

• Internet Scare (1996) v. the Generative AI Scare

• NYSERNet to Empire AI? Not Quite

• Artificial Consciousness as a Way to Mitigate AI Existential Risk

• Imagining AGI as a Digital Homo sapien

• Autonomous AI Agents as Economic Actors

• Human Memory & LLM Efficiency: Optimized Learning through Temporal Memory