The plan is still for 1.6 to be the new LTS. There are always features in new releases that someone would like to have in an LTS version. Aside from the manifest format, which is being backported to 1.6, none of these seem like show-stoppers.
The vast majority of people should be using whatever the latest Julia version is, not staying on the LTS. There seems to be some misunderstanding that the LTS is better to run for some reason, which is very much not the case. You should only be using the LTS if it’s very expensive or risky for you to go through the process of upgrading, which is not the case for 99% of users. People who need the latest and greatest in machine learning capabilities are very much not the target audience for the LTS release and should be using whatever the current stable Julia version is. Packages should support whatever earliest Julia version they can conveniently support. If that’s the LTS, great; if not, that’s also fine. For example, for many packages Julia 1.3 has been a lower bound for a long time because it introduced artifacts and multithreading. Even though that wasn’t the official LTS, it was a fine lower bound for packages to have.
In hindsight, the amount of time spent on the 1.6 release was probably a mistake and we should just do timed releases like we normally do regardless of whether something is going to be an LTS or not. And we should probably just do a timed LTS as well on a two year cadence. So whatever 1.x release is first cut in 2023 would be the next LTS.