The Alignment Problem: How Can Artificial Intelligence Learn Human Values - Episode I - Day 5

"This series explores how we as researchers, policymakers, and Business Leaders can close the gap regarding the alignment problem. I have chosen the same title as Brian Christians's book where I am reversing and upgrading some of the core themes mentioned in the book." Enjoy The Series

Prologue:

Steve Jobs was a charismatic pioneer of the personal computer era. With Steve Wozniak, Jobs founded Apple Inc. in 1976 and transformed the company into a world leader in telecommunications. Widely considered a visionary and a genius, he oversaw the launch of such revolutionary products as the iPod and the iPhone.

The story continued to build the 2nd most valuable company in the world as grounded new product managers to greater innovations long after they left the secret, closed-source giant.

Now Generative AI has emerged and partnered with the world's number one most valuable company Microsoft with its sidekick - OpenAI. An interesting Batman and Robin saga indeed.

I for one am deeply embedded in my research into Micro Language Models which by my Hypothesis have the power to save lives and protect the innocent against national and foreign security threats.

In essence, some say that we are moving too fast in the domain of GenAI according to Elon Musk and his famous musketeers - I for one back Microsoft and OpenAI in their new heroic adventure to save the world from chaos - maybe!

Introduction

Let's dive into my journey of pioneering the concept of Micro Language Models. For those new to AI, let's set the stage with some essential background before exploring the origins of this fascinating series.

Micro Language Models stand in contrast to their larger counterparts by their compact size and minimal data requirements for training. While companies like OpenAI have historically fed colossal datasets from the internet into their algorithms to create extensive, albeit imperfect, language systems, Micro Language Models take a different approach.

Consider the concept of word embedding systems, which essentially train AI to predict subsequent words in a sequence, exemplified by: Sun + beach = holiday. This foundation aims to mimic human language understanding and prediction, albeit with ongoing challenges in fully replicating the complexity of human thought and communication.

The journey into AI and language models reveals a continuous learning process about neural networks and the human brain. Despite lacking a master's degree in machine learning or psychology, one can appreciate the ongoing discoveries in how AI can address some of humanity's most pressing issues, despite inherent imperfections in current generative AI models.

As OpenAI ventures into utilizing the internet as a primary data source for models like ChatGPT, legal and ethical challenges emerge. Yet, my focus as a researcher and author is to distil current and future AI trends into a digestible format for my readers, combining my passions for reading and writing with my role as a thought leader.

So, what have I done to develop a safer language model? Armed with basic resources—a laptop, a desktop, my intellect, and a wealth of information from AI literature and the internet—I embark on this quest.

Here's my preliminary hypothesis: I aim to invert the concept of Large Language Models, creating smaller, more efficient technologies that defy the conventional need for vast data sets. Instead, I propose leveraging academic research to craft educational avatars. This shift stems from my unique background and classified knowledge gained as a former British Army reservist, which highlights the urgency of this research due to broader security implications.

Embarking on this AI exploration, I've been rapidly absorbing and applying AI knowledge, building upon my history of quick, impactful research. This book aims to take readers on a meaningful journey, simplifying complex concepts for widespread understanding. My lifelong commitment to learning and sharing knowledge underpins this endeavour, aiming to enhance global comprehension of AI through easily accessible content.

Experimenting with Large Language Models in social media has yielded intriguing preliminary results, suggesting that a single Micro Language Model could significantly streamline business operations without extensive data storage needs. Although this marks uncharted territory and presents challenges, especially for someone with limited coding experience, the potential for breakthroughs is exhilarating.

Predictions impact of Generative AI, particularly in software development and social media, hint at profound shifts in how technology is created and utilized. The goal is not just to innovate but to empower individuals and communities to harness these tools for their advancement.

As we venture into this exploration together, stay tuned for insights and lessons on leveraging AI to create a more equitable and empowered world.

Chapter Four

Forward - note - This morning I want to thank the following LinkedIn Professionals who have helped me identify a customer persona below derived from ChatGPT4 - While the idea of finding a publisher is great - I have decided to self-publish this book ASAP when I get to 25,000 words which won't take me believe me.

Stanley Russel Vincent Valentine ?? Shravan Kumar Chitimilla Alex Armasu

Your ideal customer persona, based on the comments and roles you've shared, seems to be: A forward-thinking professional at the intersection of technology and leadership, such as a CEO or founder of a tech-focused company (particularly in AI, cybersecurity, or cloud services), who values the integration of artificial intelligence with human values and is actively looking for insightful, impactful content to expand their understanding and applications of AI in creating a safer, more equitable world.

This persona appreciates both the technical depth and the broader implications of AI on society and seeks resources that are not only informative but also align with their vision of technological advancement for the betterment of humanity.

Neural Networks and Learning About Ai

????LIVE RECORDED TALK

I've revised the transcript to include all points while improving its clarity, grammar, and readability. This version is more detailed and faithful to the original content:

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"I'm excited about AI's potential to save lives. My role is to introduce new ideas to the conversation on neural networks and AI learning. It's an intriguing topic because I've only recently begun to grasp how neural networks aim to replicate the human brain. This isn't a technical discussion but rather an exploration of the various disciplines that contribute to our evaluation of AI's value and the development of policies for AI, particularly concerning the basics of neural networks. Though we won't delve deeply into what a neural network is, it fundamentally involves math—attempting to mimic the brain using math and equations, or linear algebra, to create a smart system.

My independent research into micro language models employs a similar mathematical framework, albeit on a smaller scale since I'm limited to using a personal computer instead of a large database. This research involves coding words with decimal numbers between 0 and 1, employing a method common in machine learning for classifying data. This coding strategy is crucial for AI, particularly for word embedding systems that assign values to words for classification purposes.

Despite my lack of a technical background, I appreciate the underlying math and science principles that AI operates on. It's revolutionary, altering markets and introducing new opportunities. Daniel Priestley emphasized the importance of deciding whether to be a creator or a consumer. I consider myself a creator, particularly with my brand, Healthy Secrets, but also a researcher.

Discussing neural networks, the complexity of the human brain is enormous. While AI can mimic certain aspects, fully replicating human emotions like stress, anger, or anxiety is far-fetched. Advances in large language models by OpenAI are commendable. They utilize word embedding systems to simulate understanding, associating terms like "beach" and "sun" with "holiday." However, completely mimicking the human brain is a far-off goal, primarily due to AI's tendency to produce hallucinations.

My passion for AI research is fueled by the potential dangers and benefits it presents. Nations like China might exploit AI advancements in ways that could endanger human life. My work, though not technical, strives to understand and articulate the subtleties of AI and its overlap with quantum computing, a combination that promises significant future impact.

In essence, my live talk and this transcript seek to demystify complex AI and neural network information, making it accessible and understandable. As we delve into these technologies, caution and informed policymaking are essential to address their inherent challenges. Thank you for watching and for any feedback that aids this research. Have a wonderful day!"

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"This version aims to faithfully capture the depth and breadth of your original talk, including all discussed points while ensuring the text is coherent and engaging for readers." ChatGPT4