Anjney Midha, General Partner at a16z, believes that mechanistic interpretability (a fancy term for "reverse engineering" AI models) will take center stage in 2024.

In this discussion, we move beyond the black box and explore pivotal questions: Why do AI models make specific statements? What influences the success of certain prompts? Most crucially, how can we control these models in real-world scenarios?

Topics Covered:
00:00 - Big Ideas in Tech 2024
01:39: AI Interpretability: From Black Box to Clear Box
02:21: What do we and don’t understand about LLM black boxes and interpretability
04:23 - Research in interpretability
06:43 - Features represented in the outputs from LLMs
08:16 - Unlocks in interpretability
11:49 - The engineering challenges
14:10 - Scaling mechanistic interpretability research
17:27 - A new focus on explainability

Resources:
View all 40+ big ideas: https://a16z.com/bigideas2024
Find Anish on Twitter:   / anjneymidha  

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.