AInsights: What your C-suite insights mean for the latest in generative artificial intelligence…
OpenAI outlines a five-tier system for tracking progress toward human-level intelligence (also known as artificial general intelligence (AGI)) from artificial intelligence (AI). According to an OpenAI spokesperson, the company told Bloomberg The company is approaching level two “reasoners,” where AI can solve problems as well as humans with PhDs but without access to the tools.
How far is OpenAI from Level 2?
Let's take a step back to understand the current state of generative AI and how it differs from artificial general intelligence (AGI).
Generative artificial intelligence and artificial general intelligence (AGI) represent two different stages of artificial intelligence development, each with unique capabilities and limitations.
Generative AI is currently a powerful tool for specific tasks involving content creation and pattern recognition, and is widely used in various industries to increase productivity and creativity. But there is a lack of real understanding and adaptation.
AGI is a type of artificial intelligence that can learn to perform any intellectual task a human or animal can perform, or surpass human capabilities in most economically valuable tasks. It represents the future goal of artificial intelligence research, aiming to create machines with human-like cognitive abilities that can understand, learn and innovate in different fields. Despite its transformative potential, AGI remains a theoretical pursuit with significant challenges to overcome.
However, OpenAI clarifies the perception stage from genAI to AGI.
Let’s review a summary of each stage:
Level 1: Conversational AI (where we are now)
In this initial stage, the AI system can engage in natural language conversations with humans. Examples include chatbots and virtual assistants such as OpenAI's ChatGPT. These systems can handle customer service interactions and provide basic assistance, but are limited to language-based tasks and lack the ability to solve complex problems.
Level 2: Reasoner
The second phase involves artificial intelligence systems that are capable of solving problems at the level of humans with PhDs, but without access to external tools. These “reasoners” are expected to excel in academic and professional fields, solving complex problems independently. This marks a major leap in the cognitive capabilities of artificial intelligence, enabling applications in research, medicine and engineering.
Level 3: Agent
At this stage, the artificial intelligence system (called an “agent”) can perform tasks autonomously on behalf of the user for an extended period of time. These systems can operate independently without the need for constant human intervention, potentially revolutionizing business operations and efficiency by handling a variety of tasks in different areas.
Level 4: Innovator
The fourth level, called “Innovators,” describes artificial intelligence systems that can help develop new inventions. These systems can promote scientific discovery and technological advancement by generating innovative solutions and ideas. This stage marks the ability of artificial intelligence not only to perform tasks, but also to create and innovate.
Level 5: Organization
The final phase envisions AI systems capable of performing the work of the entire organization. These “organizations” can manage and perform all functions of the enterprise, surpassing traditional human operations in terms of efficiency and productivity. This stage represents the pinnacle of the development of artificial intelligence, which can autonomously operate complex organizational structures.
OpenAI believes it is currently at level 1 and is approaching level 2. Progress through these stages highlights the incremental advances in AI capabilities and the transformative potential of general AI.
Let’s revisit the question. How far is OpenAI from achieving a second-level “reasoner”?
The answer is a secret, and the codename seems to be “Project Strawberry.”
Project Strawberry aims to enhance the reasoning capabilities of artificial intelligence, enabling models to plan ahead, browse the Internet autonomously, and conduct in-depth research. The initiative builds on technologies such as Stanford University's Self-Teaching Reasoner (STaR), which allows AI models to iteratively create their own training data to improve their reasoning skills over time.
Current capabilities and demos:
OpenAI’s recent demonstrations show promising progress toward human-like reasoning. For example, internal testing reportedly found that the AI model scored more than 90 percent on a challenging math test, an important indicator of higher-order problem-solving ability. These features show that OpenAI is on the verge of achieving the reasoning skills required for Level 2.
Challenges and prospects:
Despite this progress, the exact timeline for the public release of these features remains uncertain. From what I understand, the development process requires constant fine-tuning and testing to ensure reliability and effectiveness. While significant progress has been made, the leap from current capabilities to fully achieving Level 2 is still a work in progress.
I think we'll know when they're ready to let us know.
Artificial Intelligence Insights
openAI What do the five stages of artificial intelligence mean for business and technology leaders?
For business and technology executives, OpenAI's five stages of artificial intelligence evolution present both opportunities and challenges. Embracing and strategically leveraging these advances can lead to significant gains in efficiency, innovation, and competitive advantage.
Phase One: Chatbot
Customer Service: Artificial Intelligence systems such as ChatGPT and ServiceNow Assistance Now Customer service has been enhanced by providing 24/7 support, handling daily queries and increasing customer satisfaction.
Internal productivity: Businesses are using chatbots to perform internal functions such as employee onboarding, IT support, and HR inquiries to streamline operations and reduce costs.
Precautions:
User experience: Investing in a user-friendly interface and continually improving your chatbot’s functionality is critical to maximizing its effectiveness.
Stage 2: The Reasoner
High-level problem solving: Current artificial intelligence systems can solve complex problems at a level comparable to humans with PhDs. This can revolutionize fields such as research, finance and engineering by delivering expert-level insights and solutions without human intervention.
Strategic decision-making: Enterprises can use these artificial intelligence systems for strategic planning, risk assessment, and data analysis to enhance the decision-making process.
Precautions:
Integration: Ensuring these advanced AI systems integrate seamlessly with existing business processes and tools is critical.
Ethical use: Establishing guidelines for ethical use and addressing potential bias in AI decision-making is critical to maintaining trust and compliance. From this stage to stage five, ethics also apply to how employers use AI to upskill and empower employees.
Organizational and business model innovation: Here and at every stage, top management needs to proactively reimagine organizational and business model transformation to prepare for the autonomous enterprise to come.
The third stage: agency
Autonomous operation: AI agents can perform tasks autonomously for long periods of time, handling complex workflows without constant human supervision, potentially transforming business operations. This is autonomy, Autonomous driving company.
Operational efficiency: These agents can optimize supply chains, manage logistics, and even handle customer relationships autonomously, significantly improving efficiency and reducing operating costs.
Precautions:
Monitoring: Implement robust monitoring systems to oversee AI agents and ensure they are performing their tasks correctly and ethically.
Adaptability: Ensuring that AI agents can adapt to changing business circumstances and needs is critical to long-term success.
Stage 4: Innovators
Innovation and R&D: Innovative artificial intelligence systems can contribute to new product development, scientific research and technological progress, and may lead to breakthroughs in various industries.
Competitive advantage: Businesses that leverage innovative artificial intelligence can gain a significant competitive advantage by bringing new products and solutions to market faster.
Precautions:
Collaboration: Encourage collaboration between AI systems and human experts to maximize innovation potential.
Intellectual property rights: Manage intellectual property rights and ensure that innovations generated by artificial intelligence are effectively protected and utilized.
Stage 5: Organization
Full Automation (Autonomous Enterprise): Today’s AI systems can perform the entire organization’s work, from strategic planning to operational execution, potentially making traditional organizational structures obsolete
Efficiency and Productivity: Stage 5 AI systems can operate with unparalleled efficiency, reducing costs and increasing productivity across all business functions.
Precautions:
Workforce: Address the impact on the workforce, including potential job losses and the need to reskill and upskill.
Governance and ethics: Establish a governance framework to ensure that artificial intelligence systems operate in an ethical, transparent manner and are consistent with organizational goals and social values.
Now, understanding and preparing for each stage is absolutely critical to leading the future landscape of AI-driven business transformation.
Please subscribe to AInsights, here.
If you would like to join my main mailing list for news and events please follow, Solis Quantum.
