glossary.

When an LLM creates an inaccurate, false, or fabricated output. LLMs are prediction machines, trained on a huge body of past data (their corpus). Hallucinations can happen because of gaps or errors in that training data, but more often they're just a side effect of the prediction process itself. It does this confidently (even when wrong), and even when challenged directly it can take several turns of pushing before a model will admit something was fabricated or inaccurate. The major labs claim to have brought hallucination rates down for simple tasks, but it remains a huge challenge for generative AI, which is stochastic by nature.

The hypothetical moment where we create a greater than human intelligence that triggers further extremely rapid technological and self-reinforcing change. Beyond this proposed moment, AI is no longer controlled by humans and is capable of such rapid self-improvement that everything is unpredictable beyond anything we've experienced before. Human civilisation would, at this point, change significantly and it's a historic turning point. Our world would be without our control and it's likely that technological innovation would be beyond our understanding or visibility from this point on. Many believe reaching the singularity would be catastrophic for us humans. Some believe we might already be at the singularity with the recursive model training and development already being used. Why "singularity"? It's a term taken from maths and physics with sci-fi connotations. In maths it's where an equation zooms to infinity, and in physics it's more like the centre of a black hole where time and space are mushed into one and there's no going back.