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AutoToS makes LLM planning fast, accurate and inexpensive
LLM planning is slow and expensive. AutoToS will enable enterprises to solve real-world planning problems faster and with fewer LLM calls.
AutoToS automates the feedback and exception handling process using unit tests and debugging statements, combined with few-shot and chain-of-thought (CoT) prompting techniques. ToS and AutoToS are examples of neuro-symbolic AI, a hybrid approach that combines the strengths of deep learning and rule-based systems to tackle complex problems. “I don’t think that there is any doubt about the role of hybrid systems in the future of AI,” Harsha Kokel, research scientist at IBM, told VentureBeat.
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