Thoughtworks Technology Podcast Generative AI's uncanny valley: Problem or opportunity?
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Dec 12, 2024 Srinivasan Raguraman, a Principal Technologist at Thoughtworks and co-author on generative AI's uncanny valley, dives into intriguing concepts surrounding AI. He discusses how the uncanny valley can unsettle users due to the unpredictable nature of AI outputs. The conversation covers the distinction between deterministic and non-deterministic outputs, user misconceptions about these technologies, and the challenges of integrating AI into workflows. Raguraman emphasizes the need for responsible implementation to navigate both the opportunities and emotional implications of AI mimicking human behavior.
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Uncanny Valley in Tech
- The uncanny valley in tech arises from unmet user expectations, like clunky mobile apps or inconsistent AI.
- LLMs, being non-deterministic, can trigger this feeling due to their unpredictable outputs.
Non-Deterministic Nature of LLMs
- LLMs are non-deterministic, meaning the same input can yield various outputs, unlike a calculator.
- This unpredictability is both useful for creative text generation and problematic for reliability.
The Stone Soup Analogy
- Srini uses the "stone soup" analogy to explain LLMs.
- The output depends on what you contribute, emphasizing that LLMs aren't magical solutions.