AI-based System Development Strategy

A AI-based System Development Strategy is a software technology development strategy that is an AI strategy which outlines the AI-based system development methodologies, AI-based system development tools, and AI-based system development practices used to create, enhance, and deploy artificial intelligence-based systems.

• Context:
  • It can (typically) involve the construction of AI Technology Roadmaps that delineate the progression of AI engine development over time.
  • It can (often) include strategic decisions regarding Resource Allocation, Technical Talent Recruitment, and prioritizing Research Focus Areas to support targeted AI advancements.
  • It can (typically) contain sections such as:
    • AI Resource Allocation Plan: Decisions regarding the allocation of resources for AI development.
    • AI Talent Recruitment Plan: Strategies for recruiting and retaining AI talent.
    • AI Research Plan: Prioritizing research areas to support targeted AI advancements.
    • AI Collaboration Plan: Plans for collaboration with academic institutions and industry partners.
    • AI Ethics Plan: Ensuring adherence to ethical standards in AI development practices.
  • It can align with an organization's broader Artificial Intelligence (AI) Strategy, integrating specific development activities with overarching business objectives and digital transformation initiatives.
  • It can range from being a Conservative AI-based System Development Strategy, which emphasizes incremental improvements and risk management, to being an AggressiveAI-based System Development Strategy, aimed at rapid innovation and market disruption.
  • It can reference AI Ethics Guidelines to ensure development practices adhere to ethical standards and societal expectations.
  • ...
• Example(s):
  • Organizational AI Development Strategies, such as:
    • PlayStation's AI-based System Development Strategy, which focuses on leveraging AI to enhance gaming experiences and improve system performance for PlayStation Inc..
    • Spotify Technology's AI-based System Development Strategy, which emphasizes personalized recommendations and user experience optimization using advanced AI models for Spotify Inc..
    • Intuit's AI Development Strategy, which centers on using AI to automate financial processes and provide intelligent insights to users for Intuit Inc..
    • LegalTech Startup's AI Development Strategy, which involves the development of AI tools to streamline legal research, case analysis, and document automation for LegalTech Startup.
    • ...
  • A Risk Tolerance-based AI Development Strategy, such as:
    • An Aggressive AI Development Strategy utilized by a startup in the autonomous vehicle industry, focusing on the rapid integration of state-of-the-art machine learning models to outpace competitors, anticipating near-term improvements in AI capabilities.
    • A Conservative AI Development Strategy employed by a financial institution, prioritizing incremental improvements and thorough testing to ensure reliability and compliance, suitable for long-term AI advancements.
  • A Development Pace-based AI Development Strategy, such as:
    • An Incremental AI Development Strategy implemented by a healthcare technology company, planning for steady enhancements in AI capabilities while being ready to incorporate breakthroughs in AI diagnostics quickly.
    • A Dynamic AI Development Strategy adopted by a tech giant, engineered to continuously integrate the latest developments in natural language processing to enhance its digital assistants, reflecting expectations of ongoing, rapid advancements.
  • An Approach to Innovation-based AI Development Strategy, such as:
    • A Breakthrough-driven AI Development Strategy by a biotech firm collaborating with academic institutions, aimed at harnessing cutting-edge AI research to transform the processes of drug discovery and development.
    • An Iterative AI Development Strategy used by an e-commerce platform, where insights from customer feedback and behavioral data are used to consistently refine recommendation algorithms.
  • ...
• Counter-Example(s):
  • an AI Production Engine Development Strategy, such as OpenAI's AI Production Engine Development Strategy, which includes OpenAI LLM models.
  • an AI Online Platform Development Strategy, such as OpenAI's AI Online Platform Development Strategy, which includes its APIs and Playground.

This term nicely encapsulates the idea of developing the infrastructure and interfaces that make AI accessible via the internet. The word "Platform" suggests a broader ecosystem that includes not just the API, but potentially also documentation, usage metrics, scaling infrastructure, and other elements that support the online accessibility of AI capabilities.

• • Ad-Hoc Development Strategys, which lack structured planning and long-term goals, often resulting in fragmented and inefficient AI development efforts.
  • ...
• See: AI Model Deployment, AI Ethics Guidelines, Technology Adoption Lifecycle, Artificial Intelligence (AI) Strategy.

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References

2024

• https://www.youtube.com/watch?v=G8T1O81W96Y
  • QUOTE:
    • Sam Altman: “There are two strategies to build on AI right now. There's one strategy which is assume the model is not going to get better, and then you kind of like build all these little things on top of it. There's another strategy which is build assuming that OpenAI is going to stay on the same rate of trajectory and the models are going to keep getting better at the same pace. ... It would seem to me that 95% of the world should be betting on the latter category, but a lot of the startups have been built in the former category."
  • NOTES:
    • AI Development Strategies: There are two prevailing strategies for AI development. The first assumes that AI models will not improve significantly, leading to startups building independent solutions on existing technology. The second strategy anticipates continuous improvements in AI models, as exemplified by OpenAI’s expectations.
    • Strategy Assuming No Improvement: This approach builds upon the assumption that AI models will not improve significantly over time. Developers and organizations adopting this strategy focus on enhancing the existing capabilities of AI models and creating solutions based on the current state of technology without anticipating major advancements.
    • Strategy Anticipating Continuous Improvement: Contrary to the first strategy, this one is built on the belief that AI technologies, particularly models, will improve rapidly. This strategy aligns with the trajectory that organizations like OpenAI are following, where they expect ongoing advancements and enhancements in AI capabilities.

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