AI and Mathematics 2024 – Amit Somech Data Speaking LLM Agents Made with Clipchamp скачать в хорошем качестве

AI and Mathematics 2024 – Amit Somech Data Speaking LLM Agents Made with Clipchamp

We all know that LLMs are great for all kinds of everyday tasks—writing, editing, summarizing articles, and even generating code on demand. But can we rely on them for data-focused tasks? On one hand, LLMs are trained on massive text datasets, some of which include structured data like CSVs and JSON files. Plus, thanks to forums like Stack Overflow, they should be able to help with writing SQL queries and data-processing code. However, we’ve found that when it comes to working with data, LLMs aren't as "fluent" as we might hope. When faced with larger tables, they often struggle to fully understand the structure or produce accurate tabular output. They also aren’t great at verifying facts when the information is presented in table form, even if they "know" the facts. In this talk, we’ll introduce several non-trivial data tasks, review how standard LLMs perform, and explore new architectures that could push the current capabilities forward.