like? there is that too much hinders? l, like? there is that too much hinders? like? there is that too much hinders? a, , hinders? you can see across europe and the us hinders? you can see across europe and the us divide hinders? you can see across europe and the us divide when hinders? you can see across europe and the us divide when it hinders? you can see across europe and the us divide when it comes - hinders? you can see across europe and the us divide when it comes to | and the us divide when it comes to regulating ai the us is very much pushing for less regulation. in the uk, we are trying to take a pure innovation approach with the five principles that it has recently pushed out. when it comes to response when it ai does, it is now the right time to have this discussion and the uk is really leading in the discussion. we have been working on this area in the uk across many universities, producing across many universities, producing a large body of evidence to
are pushing these out there without being open about how they are doing it and regulators need to talk about, for example with the programme i run in the uk, we have worked across multiple disciplines, notjust worked across multiple disciplines, not just a worked across multiple disciplines, notjust a community worked across multiple disciplines, not just a community scientist giving advice but lawyers, working. we have done this in health care, defence security, and what we are seeing is that there are any concerns around privacy and copyright, intellectual property, physical and mental well being when it comes to getting advice from a large language based model assistance. we large language -based model assistance. large language -based model assistance. ~ . ~ ., , assistance. we will talk about this a . ain assistance. we will talk about this aaain i m assistance. we will talk about this again i m sure- assistance. we will talk about this again i m sure. thank assistance. we w