OUR BLOG
Latest updates from
our blog
OUR BLOG
Latest updates from
our blog
OUR BLOG
Latest updates from
our blog
28 Sept 2023
CoinRun: Overcoming goal misgeneralisation
Goal misgeneralisation is a problem in artificial intelligence (AI) where an AI agent has learned a goal based on a given environment, but is unable to transfer its knowledge to different environments. This is because the AI agent has only been exposed to a limited set of scenarios, and lacks the ability to generalise from those scenarios to new ones.
13 Sept 2023
Using fAIr to measure gender bias in LLMs
16 Apr 2022
Concept extrapolation for hypothesis generation
1 May 2022
ACE for goal generalisation
24 Aug 2023
ACE mitigates simplicity bias
1 Mar 2023
EquitAI: A gender bias mitigation tool for generative AI
6 Dec 2022
Creating a prompt evaluator to prevent LLM jailbreaking
28 Sept 2023
CoinRun: Overcoming goal misgeneralisation
Goal misgeneralisation is a problem in artificial intelligence (AI) where an AI agent has learned a goal based on a given environment, but is unable to transfer its knowledge to different environments. This is because the AI agent has only been exposed to a limited set of scenarios, and lacks the ability to generalise from those scenarios to new ones.
13 Sept 2023
Using fAIr to measure gender bias in LLMs
16 Apr 2022
Concept extrapolation for hypothesis generation
1 May 2022
ACE for goal generalisation
24 Aug 2023
ACE mitigates simplicity bias
1 Mar 2023
EquitAI: A gender bias mitigation tool for generative AI
6 Dec 2022
Creating a prompt evaluator to prevent LLM jailbreaking
28 Sept 2023
CoinRun: Overcoming goal misgeneralisation
Goal misgeneralisation is a problem in artificial intelligence (AI) where an AI agent has learned a goal based on a given environment, but is unable to transfer its knowledge to different environments. This is because the AI agent has only been exposed to a limited set of scenarios, and lacks the ability to generalise from those scenarios to new ones.