"The conventional answer to why AI struggles with invoices is that they are perception problems requiring better models. However, this perspective may be misguided."
"Competitive mathematics involves a few hundred proof techniques that AI can remix effectively, while clerical tasks resemble the math problem rather than the unique challenges of chess."
"Chess engines succeeded by creating systems around neural networks rather than solely increasing their size, highlighting the importance of task-specific approaches in AI."
Advanced AI models can solve complex mathematical problems but often fail to extract simple totals from invoices. This discrepancy arises because competitive mathematics relies on a limited set of proof techniques, allowing AI to excel through composable pattern matching. In contrast, clerical tasks, such as invoice processing, involve messy layouts and varied formats, making them more challenging for AI. The solution may not lie in simply improving models but in understanding the nature of the tasks and how AI can be effectively applied.
Read at Fast Company
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