Polymorphic Applications: Mission-Driven Software, Cognitive Architectures, NEXT-GEN PARADIGMS

David Shapiro
21 Jul 202331:29

TLDRDavid Shapiro introduces the concept of polymorphic applications, self-changing software driven by AI's cognitive abilities. He discusses the importance of mission-oriented programming and cognitive architecture, emphasizing the need for a clear purpose and the ability to adapt and make decisions autonomously. Shapiro outlines a six-layer model for developing autonomous cognitive entities, from aspirational goals to task execution, and suggests that this paradigm shift is essential for future-proofing businesses against the rapid advancements in generative AI.

Takeaways

  • 🚀 Introduction to polymorphic applications, self-changing software paradigms.
  • 🌟 Microsoft CEO Satya Nadella's emphasis on AI capabilities at Microsoft Inspire 2023.
  • 🧠 The concept of a reasoning engine in AI, beyond text generation to problem-solving and decision-making.
  • 🛠️ Mission-oriented programming as the next paradigm beyond object-oriented programming.
  • 📚 The importance of a clear, measurable mission driving software behavior, adaptation, and evolution.
  • 🤖 Defining autonomy and agency in software: the ability to make decisions and adapt in pursuit of a mission.
  • 🧱 Building blocks of polymorphic applications: micro-frameworks, configurable fronts ends, and back-ends.
  • 🔄 The role of generative AI as a new form of automation, extending existing capabilities.
  • 🔍 Problem-solving techniques in AI like 'tree of thought' enhancing cognitive capabilities.
  • 🔧 The concept of cognitive architecture as a framework for next-gen applications and polymorphic applications.
  • 📈 The ACE model (Autonomous Cognitive Entities) as a six-layer framework for developing advanced AI systems.

Q & A

  • What is the core concept of polymorphic applications as discussed in the transcript?

    -Polymorphic applications refer to self-changing applications that are designed and built around a clear, measurable, and purposeful mission. They are active agents that pursue their respective missions, adapting and evolving their behavior to achieve their goals.

  • What are the two primary components of AI as outlined by Microsoft CEO Satya Nadella in the keynote?

    -The two primary components of AI outlined by Satya Nadella are natural language interface, which includes voice chat and emails, and the reasoning engine, which involves problem-solving, decision-making, and other cognitive functions.

  • What is the significance of cognitive architecture in the context of polymorphic applications?

    -Cognitive architecture is crucial for polymorphic applications as it provides a framework for creating autonomous cognitive entities that can reason, plan, adapt, and make decisions in pursuit of their missions. It is the basis for the next generation of software development that leverages AI capabilities.

  • How does the concept of 'Mission Oriented Programming' relate to traditional object-oriented programming?

    -Mission Oriented Programming is a paradigm shift from traditional object-oriented programming. Instead of focusing on objects, this new paradigm centers on missions as the primary organizing feature of software. The software is designed to actively pursue its mission, making it more dynamic and adaptive.

  • What are the key features of polymorphic applications?

    -Polymorphic applications are characterized by mission-centric design, autonomy and agency, adaptability and flexibility, and dynamic tool creation. They can change their behavior and structure to better pursue their defined missions.

  • How does the speaker describe the role of generative AI in the context of automation?

    -The speaker describes generative AI as a new kind of automation that provides additional capabilities. It is seen as a tool that can write code, solve problems, make decisions, and essentially automate various tasks within an organization's tech stack.

  • What is the significance of the ACE model mentioned in the transcript?

    -The ACE model, or Autonomous Cognitive Entities, is a conceptual framework for building next-generation AI systems. It consists of six layers: Aspirational, Global Strategy, Agent Model, Executive Function, Cognitive Control, and Task Prosecution, each responsible for different aspects of the AI's cognitive processes and behavior.

  • What are the six layers of the ACE model?

    -The six layers of the ACE model are: 1) Aspirational Layer, which deals with mission, values, purpose, ethics, and morals; 2) Global Strategy Layer, focusing on long-term thinking and context; 3) Agent Model, concerned with the AI's capabilities and self-understanding; 4) Executive Function, about planning and resource management; 5) Cognitive Control, dealing with task selection and switching; and 6) Task Prosecution, the execution of tasks and evaluation of their success or failure.

  • How does the speaker suggest we should think about generative AI in relation to existing roles in tech?

    -The speaker suggests that we should think about generative AI as another kind of automation. Whether you are an infrastructure engineer, IT professional, software developer, or architect, you should view generative AI as an additional tool in your toolkit that enhances your capabilities.

  • What is the importance of the aspirational layer in the ACE model?

    -The aspirational layer is the highest and most abstract layer in the ACE model. It sets the moral compass and guiding principles for the AI, defining its mission and purpose. It is the layer that ensures the AI stays true to its intended goals and ethical boundaries, serving as the ultimate arbiter for moral dilemmas.

  • How does the speaker view the potential impact of generative AI on business models?

    -The speaker believes that generative AI will have a profound impact on business models, suggesting that it will disrupt and potentially destroy many existing models. He emphasizes the need for businesses to adopt sophisticated approaches like cognitive architecture and polymorphic applications to remain viable in the face of rapidly advancing AI technology.

Outlines

00:00

🚀 Introduction to Polymorphic Applications

The speaker, David Shapiro, introduces the concept of polymorphic applications, which are self-changing applications, and shares his experience with consulting and teaching. He mentions Microsoft CEO Satya Nadella's keynote speech on AI and its capabilities, emphasizing the importance of natural language interface and reasoning engines. The speaker advocates for cognitive architecture and its role in software development, suggesting that language models are capable of various cognitive tasks like problem-solving and decision-making.

05:01

🤖 Mission-Oriented Programming and Automation

The speaker discusses mission-oriented programming as the next paradigm beyond object-oriented programming, where software is designed around a clear, measurable mission. He explains that polymorphic applications are active agents pursuing their missions and highlights components such as mission-centric design, autonomy, adaptability, and dynamic tool creation. The speaker also talks about the potential of generative AI as a form of automation, comparing it to a replicator from Star Trek that can fabricate tools on-demand.

10:02

🧠 Cognitive Architecture and the ACE Model

The speaker introduces the ACE (Autonomous Cognitive Entities) model, a framework for next-gen applications that involves six layers. The aspirational layer at the top sets the mission and ethical guidelines, while the global strategy layer considers long-term thinking and context. The agent model layer focuses on the capabilities of the machine, understanding its own configuration and operational conditions. The speaker emphasizes the importance of these layers in creating advanced AI systems like Commander Data or C-3PO from Star Trek.

15:02

📈 Planning and Executive Functions in AI

The speaker delves into the lower layers of the ACE model, discussing the executive function layer, which is about planning and resource management, and the cognitive control layer, which involves task selection and switching. He explains how these layers work together to maintain focus and adapt to challenges, using frustration signals and cognitive damping to adjust strategies and ensure the AI's actions align with its mission and capabilities.

20:03

🛠️ Task Prosecution and the Role of Cognitive Damping

The speaker describes the bottom两层 of the ACE model, focusing on task prosecution, which involves executing low-level tasks, and cognitive damping, which slows down decision-making to prevent mistakes. He uses examples from everyday life to illustrate how these concepts work in practice, emphasizing the importance of detecting success or failure and adjusting plans accordingly.

25:04

🌐 The Future of Software Development

The speaker concludes by emphasizing the importance of adopting cognitive architecture and polymorphic applications in software development. He advises startups to think in terms of these advanced concepts to survive the disruptive impact of generative AI. The speaker also mentions his availability for consultation and points to his books and GitHub for further information on the topic.

Mindmap

Keywords

💡Polymorphic Applications

Polymorphic applications refer to self-changing applications that evolve and adapt based on their mission. These applications are not just tools but active agents pursuing their objectives. In the context of the video, polymorphic applications are a new paradigm in software development and architecture, emphasizing adaptability and flexibility, allowing the software to change its behavior and structure in response to its environment and goals.

💡Cognitive Architecture

Cognitive architecture is a framework that models the structure and function of the mind, particularly in the context of artificial intelligence. It involves creating a system that mimics human cognitive processes, such as reasoning, problem-solving, and decision-making. In the video, the speaker discusses the importance of cognitive architecture for developing advanced AI systems, like polymorphic applications, that can understand their environment, set goals, and act autonomously to achieve them.

💡Mission-Oriented Programming

Mission-oriented programming is a software development paradigm where applications are designed and built around a clear, measurable, and purposeful mission. This approach shifts the focus from objects, as in object-oriented programming, to missions, which serve as the core driver of the software's behavior, adaptation, and evolution. The mission is central to the application's design and guides its development and functionality.

💡Autonomy

Autonomy in the context of the video refers to the ability of a software system or AI to operate independently, make decisions, and take actions without human intervention. It is a key aspect of mission-oriented programming and polymorphic applications, allowing the system to adapt and pursue its mission with minimal external control.

💡Reasoning Engine

A reasoning engine is a component of AI systems that enables them to perform complex tasks such as problem-solving, decision-making, and logical deduction. It goes beyond simple text generation to utilize the AI's understanding of language and context to interact with various systems and data, providing intelligent responses and solutions.

💡Generative AI

Generative AI refers to artificial intelligence systems that can create new content, such as text, images, or code. These systems use machine learning models to generate outputs based on input data, and they are capable of a wide range of creative and functional tasks, from writing emails to coding and testing software.

💡Micro Frameworks

Micro frameworks are lightweight, modular software frameworks that are used to build applications and services. They are designed to be highly adaptable and flexible, allowing developers to create configurable front ends and back ends that can be easily changed or extended as needed. In the context of the video, micro frameworks enable polymorphic applications to change and adapt their structure and functionality in response to their mission and environment.

💡Plug and Play Architecture

Plug and play architecture refers to a system design where components can be easily added, removed, or upgraded without requiring significant changes to the existing system. This design philosophy allows for flexibility and scalability, as components can be swapped in and out as needed to meet evolving requirements or to incorporate new technologies.

💡Cognitive Control

Cognitive control is the process by which an AI system manages its focus, task selection, and task switching. It involves the ability to prioritize tasks, monitor progress, and adjust actions based on the success or failure of previous tasks. Cognitive control is a critical component of mission-oriented programming and polymorphic applications, as it enables the system to navigate complex tasks and make strategic decisions.

💡Task Prosecution

Task prosecution refers to the execution of individual tasks within a larger project or mission. It involves focusing on one task at a time and assessing its success or failure before moving on to the next. In the context of polymorphic applications, this concept is crucial for the system to understand its progress and make necessary adjustments to its strategy based on the outcomes of its actions.

Highlights

David Shapiro introduces the concept of polymorphic applications, self-changing applications that represent a new paradigm in software development and architecture.

Polymorphic applications are active agents pursuing their respective missions, moving beyond traditional tools to become autonomous entities.

Microsoft CEO Satya Nadella's keynote at Microsoft Inspire 2023 emphasized AI's new capabilities in natural language interface and reasoning engines.

A reasoning engine, as opposed to language models that generate text, is capable of problem-solving, coding, testing, and decision-making.

Cognitive architecture is the focus for the next generation of applications, emphasizing the cognitive engine or reasoning engine at the core.

Mission-oriented programming is the new paradigm beyond object-oriented programming, organizing software around clear, measurable missions.

Polymorphic applications can create and adapt tools on-demand, functioning as an automated tool factory or replicator for code.

Generative AI can be viewed as a new kind of automation, offering enhanced capabilities but fundamentally changing the automation landscape.

The automation engine or reasoning engine can automate various tasks, including problem-solving and decision-making, given a clear objective or mission.

The ACE (Autonomous Cognitive Entities) model is introduced as a framework for next-gen applications, with six layers for cognitive architecture.

The aspirational layer is the highest level of the ACE model, setting the mission, values, purpose, and ethics of the cognitive entity.

The global strategy layer is concerned with long-term thinking and contextual awareness, functioning like a CEO for the cognitive entity.

The agent model layer is about the cognitive entity's capabilities and self-understanding, allowing it to make informed decisions and adapt itself.

Executive function layer involves planning and resource management, acting as an internal project manager for the cognitive entity.

Cognitive control layer is about task selection and switching, maintaining focus and adjusting plans based on success and failure rates.

Task prosecution layer is the lowest level, dealing with the execution of individual tasks and reporting success or failure back to the cognitive control layer.

The framework presented is new and evolving, with more detailed information available in David Shapiro's books and GitHub repository.

David Shapiro emphasizes the importance of adopting this level of sophistication in software development to stay competitive in the era of generative AI.