Episode 37: Prompt Engineering, Security in Generative AI, and the Future of AI Research Part 2

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Oct 8, 2024

Guest

Dennis Peskoff

Join Sander Schulhoff, a specialist in prompt engineering, Philip Resnik, a computational linguistics professor, and Dennis Peskoff from Princeton as they delve into the cutting-edge world of AI. They explore the security risks of prompt hacking and its implications for military use. Discussion highlights include the evolving role of generative AI across various fields, innovative techniques for improving AI self-criticism, and the pressing need for energy-efficient large language models. Their insights offer a fascinating glimpse into the future of AI research.

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INSIGHT

Future AI Security Threats

Generative AI will increasingly create significant security threats like language model-generated cyberattacks and viruses.
Future AI models might independently move through systems without relying on external APIs, causing new risks.

INSIGHT

LLM Self-Criticism and Multi-Agent Systems

Self-criticism and adversarial criticism by LLMs hold promise for improving output quality and problem solving.
Multi-agent systems enable models to critique and improve each other's responses collaboratively.

INSIGHT

Agents and Structured Outputs

Agents are generative AI connected to external systems like APIs or other AIs, enabling complex tasks.
Structured outputs for API calls require precise prompt engineering to avoid parsing issues.

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Hugo speaks with three leading figures from the world of AI research: Sander Schulhoff, a recent University of Maryland graduate and lead contributor to the Learn Prompting initiative; Philip Resnik, professor at the University of Maryland, known for his pioneering work in computational linguistics; and Dennis Peskoff, a researcher from Princeton specializing in prompt engineering and its applications in the social sciences.

This is Part 2 of a special two-part episode, prompted—no pun intended—by these guys being part of a team, led by Sander, that wrote a 76-page survey analyzing prompting techniques, agents, and generative AI. The survey included contributors from OpenAI, Microsoft, the University of Maryland, Princeton, and more.

In this episode, we cover:

The Prompt Report: A comprehensive survey on prompting techniques, agents, and generative AI, including advanced evaluation methods for assessing these techniques.
Security Risks and Prompt Hacking: A detailed exploration of the security concerns surrounding prompt engineering, including Sander’s thoughts on its potential applications in cybersecurity and military contexts.
AI’s Impact Across Fields: A discussion on how generative AI is reshaping various domains, including the social sciences and security.
Multimodal AI: Updates on how large language models (LLMs) are expanding to interact with images, code, and music.
Case Study - Detecting Suicide Risk: A careful examination of how prompting techniques are being used in important areas like detecting suicide risk, showcasing the critical potential of AI in addressing sensitive, real-world challenges.

The episode concludes with a reflection on the evolving landscape of LLMs and multimodal AI, and what might be on the horizon.

If you haven’t yet, make sure to check out Part 1, where we discuss the history of NLP, prompt engineering techniques, and Sander’s development of the Learn Prompting initiative.

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