●  Hallucinations: AI systems regularly produce plausible yet incorrect answers and state 

these answers with high confidence.61 This might be addressed by systems using 
knowledge repositories,62 improved fine-tuning, or new methods for teaching the model 
what it does and does not know.  

●  Coherence over extended durations: AI models are less reliable on tasks that require 
long-term planning or taking a large number of sequential steps (e.g. writing a novel).63 
This is partially due to their restricted context length and the scarcity of long-duration 
task training data.64 These limitations might be addressed by algorithmic innovations to 
give AI a source of long-term memory, creating more data on long-horizon tasks, better 
scaffolds that help AI agents spot and correct their own errors,65 or improved techniques 
for breaking long tasks into multiple small steps66. 

●  Lack of detailed context: Many tasks in the real economy require extensive context
Capabilities and risks from frontier AI 