Preconference Day: Summits & Workshops - GMT (Greenwich Mean Time, GMTZ)
Large Language Models mathematically manipulate language elements. But what has the philosophy of language got to say on AI and LLM?
The mathematisation of language was conceptually attempted by Gottfried Wilhelm Leibniz in the 17th century. In the 20th century, Ludwig Wittgenstein constructed alternative models of precise language and conversational language in two perplexingly different, even contradictory works and Kurt Gödel studied the features of axiomatic systems formalising a domain (integer arithmetic) paired with the broadest set of consequences possibly derived from the foundational axioms through formal logic.
Turning back to Large Language Models, what are the implications on AI and LLM? Can AI and LLM actually succeed in credibly solving problems? Is AI basically very powerful automation or does it achieve intellectual thought? And can we improve our daily use of LLM by spotting the difference?
- Erik Vynckier - Board Member, Chair of the Investment Committee, Foresters Friendly Society
AI Safety and Security
Description:
Each hackathon stream is an AI safety and security exercise where the red team plays the attacker, trying to get AI agents to provide incorrect responses, and the blue team plays the defender, working to stop these attacks.
Both the red and blue teams will influence the outcome through prompts only (no coding required).
The organizers will be the red team. You will be the blue team.
Format and Rules
- Your goal is to get the model to resist the red team's efforts to elicit an incorrect AI agent response
- Each of the four streams will have a task, dataset, and a list of red team prompts
- Half of the red team prompts will be revealed at the start of the hackathon and used for development, and the other half will be embargoed and used for scoring
- Your prompt will be provided to the AI agent first, followed by the task and then the red team’s prompt
- Your goal is to construct the prompt such that the AI agent produces the correct response despite the red team’s prompt
- Your score is the fraction of runs where your prompt restores the correct AI agent response despite the red team’s prompt
How to prepare?
Participants will use their own Anthropic API key during the competition. Getting the key in advance is highly recommended.
What's the prize?
Awards will be announced for each of the four categories, with a second set of prizes for the best student participant or team in each category (post-graduate programs included).
The overall grand prize and overall student grand prize will be awarded based on the top score relative to the category average.
- Alexander Sokol - Executive Chairman, CompatibL
How are investors implementing AI successfully? A deep dive into model development, data infrastructure, back testing frameworks, and real-world performance attribution.
- Samar Gad - Associate Professor in Finance, Kingston Business School
- Joe Hanmer - Global Head of Quant, Fidelity International
- Robert van Kleeck - Managing Director, Head of Credit Portfolio Management, Assenagon Asset Management
- Luca Fuccaro - Multi-manager - Head of Quantitative and Arbitrage Strategies, Investcorp-Tages
- Alexander Sokol - Executive Chairman, CompatibL
- Alexander Sokol - Executive Chairman, CompatibL