Artificial General Intelligence: Lessons in AI on the Road to AGI
I was asked to create an article on Artificial General Intelligence (AGI) for clients, and I found the process and the results share-worthy.
It illuminated the need to play with different LLMs in order to get the best possible answer for your audience.
Process reproduced here FYI.
The beauty of Poe and access to several LLMs
This is a second ‘how to’ article (read the first here) that might help folks understand how generative AI and Large Language Models (LLMs), work for me. As I’ve said multiple times here, poe.com allows me to play with multiple LLMs without needing multiple subscriptions - my one-year subscription was about $17 per month, paid up front.
I wanted an article on AGI to share with colleagues because it burst into the news recently with OpenAI’s launch of o-3 and some statements by Sam Altman of OpenAI that AGI will be reached in 2025.
In an interesting article on tomsguide.com they noted:
“OpenAI has a vested interest in declaring AGI has been reached. The OpenAI deal with Microsoft comes to an end once AGI is achieved, forcing MSFT to sign a fresh agreement and potentially pay more to use the OpenAI models in Copilot.”
Why wouldn’t he say it’ll be here this year? Riiight? But I digress. Back to how I wrote the AGI post.
The First Prompt —> OpenAI’s o-1 mini
I'd like to write an article of about 1000 words maximum - geared toward business professionals - about the notion of Artificial General Intelligence. What it is, why it matters, and a little bit about the work that it might take to get there. (It's been in the news lately, so people are beginning to hear of it, and I want to demystify it from a less technical perspective.
Before you write a draft, what am I missing in terms of you understanding what I want? What else can I provide? Thank you in advance
o-1 mini to me:
Your request is clear and well-defined, providing a solid foundation for drafting the article on Artificial General Intelligence (AGI) tailored for business professionals. To ensure the final piece aligns perfectly with your expectations and effectively resonates with your target audience, here are a few additional details and clarifications that would be helpful:
Target Audience Specifics:
Industry Focus: Are you targeting professionals from specific industries (e.g., technology, finance, healthcare) or a general business audience?
Role and Expertise Level: Are the readers executives, managers, entrepreneurs, or a mix? Understanding their familiarity with AI concepts can help adjust the technical depth.
Key Objectives:
Primary Goal: Is the aim to inform, persuade, or encourage action (e.g., investment in AGI research)?
Takeaways for Readers: What should business professionals walk away with after reading the article? For instance, understanding potential business impacts, recognizing opportunities for innovation, or being aware of ethical considerations.
Content Emphasis:
Importance of AGI: Should there be a stronger focus on the strategic advantages AGI might offer businesses or the potential risks and challenges?
Current Developments: Do you want to highlight recent breakthroughs or ongoing debates in the AGI landscape?
Practical Applications: Are you interested in exploring specific use cases or hypothetical scenarios where AGI could transform business operations?
Tone and Style Preferences:
Formal vs. Conversational: Would you prefer a more formal, authoritative tone or a conversational, approachable style?
Use of Jargon: Should the article minimize technical jargon to remain accessible, or is a certain level of technical language acceptable given the professional audience?
…. and five more requests for clarifications which I answered
o-1 mini’s resulting post
Demystifying Artificial General Intelligence: What Business Leaders Need to Know
Artificial General Intelligence (AGI) has been a buzzword in the tech circles for decades, but recently it has surged into mainstream news, capturing the attention of business professionals across various industries. As executives with an entrepreneurial spirit and a high-level understanding of AI, it's crucial to grasp what AGI is, why it matters, and the journey required to achieve it. This article aims to demystify AGI, balancing its potential rewards with the inherent risks, and highlighting its relevance to your professional endeavors.
What is Artificial General Intelligence?
At its core, Artificial General Intelligence refers to a machine's ability to understand, learn, and apply knowledge across a wide range of tasks at a level comparable to human intelligence. Unlike narrow AI, which excels in specific areas like image recognition or language translation, AGI possesses the versatility to perform any intellectual task that a human can OpenAI. This means AGI systems could potentially reason, plan, solve problems, think abstractly, and comprehend complex ideas, making them transformative tools in the business landscape.
Why AGI Matters to Your Business
Unlocking Innovation and Efficiency
AGI promises unprecedented innovation and efficiency. Imagine a system that can autonomously develop new products, optimize supply chains in real-time, or provide strategic insights by analyzing vast datasets beyond human capability. Such capabilities could revolutionize industries, from healthcare—with personalized medicine and advanced diagnostics—to finance, where AGI could enhance risk assessment and fraud detection MIT Technology Review.
Competitive Advantage
Early adopters of AGI could secure significant competitive advantages. By integrating AGI-driven solutions, businesses can streamline operations, reduce costs, and enhance customer experiences. This technological leap could redefine market standards and set new benchmarks for excellence, positioning forward-thinking companies as industry leaders.
Strategic Decision-Making
AGI can augment decision-making processes by providing comprehensive analyses and predictive modeling. Executives can leverage AGI to forecast market trends, assess potential investments, and devise strategic plans with greater accuracy and confidence Harvard Business Review.
The Current Breakthroughs Fueling AGI Buzz
The recent surge in AGI discussions stems from significant advancements in machine learning, neural networks, and computational power. Breakthroughs in natural language processing, exemplified by models like GPT-4, have showcased machines' ability to generate human-like text, engage in meaningful conversations, and perform complex tasks OpenAI GPT-4. Additionally, increased investments from both the public and private sectors have accelerated AGI research, bringing it closer to reality than ever before.
….
And on and on and on… which was quite thorough, and resulted in some really good fodder. But did I want something quite that deep as an introduction to AGI? Maybe not.
And so I turned —> to my friend Claude
My request of Claude - my usual writing partner - was this:
I have a new blog post ready to go (delimited by ///) and I'd like to have you write / edit as you've done in the past for me, with a fresh voice but not hyperbolic or pedantic. This post is for organizational leaders to understand AGI and some potential risks and rewards. Please don't lose the source links - keep them as I have them, but make sure this is an accessible article for professional leaders. Thank you.
///Demystifying Artificial General Intelligence: What Organizational Leaders Need to Know
Artificial General Intelligence (AGI) has been a buzzword in the tech circles for decades, but recently it has surged into mainstream news, capturing the attention of business professionals across various industries. As executives with an entrepreneurial spirit and a growing understanding of AI, it's crucial to grasp what AGI is, why it matters, and the journey required to achieve it. This article aims to demystify AGI, balancing its potential rewards with the inherent risks, and highlighting its relevance to your professional endeavors.
What is Artificial General Intelligence?
At its core, Artificial General Intelligence refers to a machine's ability to understand, learn, and apply knowledge across a wide range of tasks at a level comparable to human intelligence.
…. (the rest of the o-1 mini-generated article followed)
Claude’s resulting post:
Here's my edited version of your article, maintaining its core message while making it more accessible and engaging for organizational leaders:
Demystifying Artificial General Intelligence: A Leader's Guide to the Next Technological Frontier
As Artificial General Intelligence (AGI) moves from science fiction to boardroom discussions, organizational leaders need to understand its implications for business and society. This guide breaks down what AGI means for your organization and why it demands attention now.
What Is AGI?
AGI represents the next evolution in artificial intelligence - systems that can match or exceed human-level intelligence across virtually any task. Unlike today's specialized AI that excels at specific functions, AGI would be able to reason, learn, and adapt across different domains, much like the human brain.
The Business Case for AGI
Transformative Potential
AGI could revolutionize how organizations operate, from autonomous product development to real-time supply chain optimization. Industries like healthcare could see breakthroughs in personalized medicine, while financial services could achieve unprecedented accuracy in risk assessment and fraud detection.
Setting Standards
Major tech players are already working to define AGI's parameters. As Sean Legg, DeepMind co-founder, notes, "Now that AGI is becoming such an important topic—you know, even the UK prime minister is talking about it—we need to sharpen up what we mean." (MIT Technology Review)
The Acceleration Timeline
In a surprising development, OpenAI's CEO Sam Altman recently predicted AGI arrival by 2025, starting with AI agents entering the workforce. As he stated, "We are now confident we know how to build AGI as we have traditionally understood it... We believe that, in 2025, we may see the first AI agents 'join the workforce' and materially change the output of companies." (Tech Radar)
Navigating Opportunities and Challenges
Opportunities
Automated complex decision-making
Enhanced operational efficiency
Revolutionary product innovation
Competitive market advantages
Challenges
Workforce transformation
Privacy concerns
Ethical considerations
Bias mitigation
MIT professor Max Tegmark frames the challenge starkly: organizations must choose between using AI responsibly to solve real problems or risking the creation of uncontrollable technology. (NextGov/FCW)
The Path Forward
Regulatory Compliance
Organizations must prepare for emerging regulations like the EU AI Act while maintaining innovation momentum. (European Commission on AI Regulation)
Safety and Ethics
Recent developments, like United Healthcare's challenges, highlight the critical importance of human oversight in AI systems. The Partnership on AI emphasizes that safety requires collaboration across all stakeholders - from developers to end-users. (Partnership on AI)
Strategic Implementation
Success with AGI will require:
Robust testing and validation processes
Comprehensive safety protocols
Ethical framework implementation
Stakeholder engagement strategies
Continuous monitoring and adjustment
Leading in the AGI Era
As organizational leaders, preparing for AGI means balancing innovation with responsibility. While the technology promises unprecedented opportunities, success will depend on thoughtful implementation that considers both business objectives and broader societal impacts.
The World Economic Forum suggests organizations should not only prepare for AGI's benefits but also plan for potential challenges. This includes developing strategies for workforce adaptation, ethical deployment, and maintaining social responsibility.
Succinct, yet not enough —> enter Human In The Loop!
And my work began, checking URL references for the original article from OpenAI (many of the references simply didn’t exist) and working through the language from Claude and o-1 mini to enrich the story and make it my own. Once again, the opportunity to work with two great LLMs made my work both easier and better. I still spent good time on the article, but had the opportunity to build on past work with both of my LLM partners to the benefit of the work itself, and the bonus (😉!) of this blog post.
I certainly hope this was helpful to those who made it ALL the WAY here! And that you learned a little about AGI in the process.
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