Kartik Details Harness Engineering for AI Control in Latest Blog Post
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| Source: Mastodon | Original article
AI systems require engineered environments and constraints. A new series explores harness engineering for probabilistic models.
Kartik's blog has released the fifth installment of the "Turing's Parrot" series, focusing on harness engineering as a crucial discipline in designing environments and constraints for AI and Large Language Models (LLMs). The core idea is that while the model itself remains probabilistic, the surrounding system must be carefully engineered to provide reins for the parrot, essentially guiding and controlling its output.
This matters because the development of AI and LLMs is not just about creating more advanced models, but also about building the infrastructure and systems that can effectively utilize and manage them. As noted in a recent Microsoft AI paper, progress in AI is driven by the ability to continually improve upon the current state of models, which requires a strong foundation in software engineering and harness engineering.
As the series is set to conclude with a sixth part on BMAD — The Agile Harness, it will be interesting to watch how Kartik's ideas on harness engineering are further developed and applied in real-world scenarios, particularly in the context of building more effective and controlled AI systems.
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