Sign up to save tools and stay up to date with the latest in AI
bg
bg
2

Why LLMs Within Software Development May Be a Dead End

Nov 18, 2024 - thenewstack.io
The article discusses the limitations of Large Language Models (LLMs) in software development, highlighting their lack of decomposability and explainability. The author argues that LLMs, unlike other software components, cannot be broken down into smaller, reusable parts, and their operation cannot be separated from their training data. This lack of transparency and control makes them unsuitable for component development and raises concerns about security, privacy, and legal ownership. The author also criticizes the trend of introducing LLMs as services within products, warning that it could lead to a loss of control over the product's development roadmap.

The author suggests that software developers should strive for truly explainable AI with testable components. They should insist on AI components that are monitorable, reportable, repeatable, explicable, and reversible. The author also emphasizes the importance of being able to correct any false beliefs held by an LLM. While acknowledging the current challenges, the author expresses hope that these issues can be addressed in the future, but warns against treating AI as a "holy relic" that cannot be questioned or tested.

Key takeaways:

  • Current AI systems, particularly Large Language Models (LLMs), lack internal structure that relates meaningfully to their functionality, making them difficult to develop or reuse as components.
  • LLMs are problematic in the software development lifecycle due to their lack of decomposability and explainability, and their inseparability from their training data.
  • There are several business and legal concerns associated with LLMs, including security and privacy issues, legal ownership problems, and their high carbon footprint.
  • Software developers should aim for truly explainable AI with testable components, and any necessary training should be monitored, reportable, repeatable, explicable, and reversible.
View Full Article

Comments (0)

Be the first to comment!