I used https://learn.mangolanguages.com/ to get to something like ~b1/b2 in French after a year. I did a lesson or two every day, and did all of the review, pretty much much every day.
I spent 8 years in jr high - college studying German without having any real competency in German, it did however teach me something about learning another language.
Mango isn't gamified. Its basically a curated set of flashcards, and the lessons are essentially flashcards themed together. There are some extra explainers throw in that are helpful. I really enjoyed it.
On top of Mango as the primary lessons, I've been listening to podcasts, watching series in french, reading books, etc.
I didn't pay anything for mango, it was entirely funded by my local library so that was great.
I did full CS / Software Engineering curriculum. There was a lot that I taught myself because I was curious / passionate. I learned a lot about things not covered in classes. But the classes also taught the boring details of things like data structures that you can generally ignore until you hit some level of scale/success.
I've seen self-taught software engineers build great looking UIs and during the code review point out things like "data structure X" would work better. I get a response about "Premature Optimization," when in fact the right data structure would be less code and I have to show them.
I've also met self-taught engineers who read detailed research papers on topics on and sometimes made things perhaps more complicated than they ever needed to be.
passion & formal education definitely play interesting roles in what people produce.
I think this makes sense for applications applications that are just managing data maybe? But if your application needs to do things when you change that data (like call to a third party system)... Syncing is maybe not the solution. What happens when the total dataset is large, do you need to download 6gb of data every time you log in? Now you've blown up the quota on local storage. How do you make sure the appropriate data is downloaded or enough data? How do you prioritize the data you need NOW instead of waiting for that last byte of the 6gb to download?
It is like a useful tool, but not the only future.
Sure in an ideal world we don't need to worry about resources and everything is easy. There are very good reason why they are separated now. There have been systems like 4th dimension and K that combine them for decades. They're great for systems of a certain size. They do struggle once their workload is heavy enough, and seem to struggle to scale out. Being able to update my application without updating the storage engine reduces the risk. Having standardized backup solutions for my RDBMS means is a whole level of effort I don't have to worry about. Data storage can even be optimized without my application having to be updated.
In very simple systems that makes sense. But as soon as your validation requires talking to a third party, or you have side effects like sending emails you have to suddenly move all that logic back out. You end up with system that isn't very easy to iterate on.
I've definitely worked in places where "Move fast and break things" tended to focus on breaking things. There would be bugs that we didn't fix because "We can just fix the database when it happens." It would take 2hours to fix a bug that would cause of 10's of hours of weekly support request, but the focus would always be on building new features, of which 10% got any real usage.
That may be true, but this isn't exactly a new drug overall. It has been available as a diabetes treatment since about 2005. So we should have some longer-term data on the topic.
The article is from thehollywoodreporter, so it is expected to not go into great detail. There is real research around these lines and links between Alzheimers and insulin resistance. I'm not in the field to really be able to vet, but it seems more than pseudoscience. Here is some more research on the topic: https://pmc.ncbi.nlm.nih.gov/articles/PMC2769828/
Test results are already reported from testing equipment a value and expected range (to account for a specific machine/reagant's calibration). Notifying when out of range hardly seems like a AI, but it certainly might be marketed as such.
Maybe there is some nuance for things like a patient in for liver issues where their liver enzymes are expected to be abnormal, but identifying when it is abnormal for them.
I spent 8 years in jr high - college studying German without having any real competency in German, it did however teach me something about learning another language.
Mango isn't gamified. Its basically a curated set of flashcards, and the lessons are essentially flashcards themed together. There are some extra explainers throw in that are helpful. I really enjoyed it.
On top of Mango as the primary lessons, I've been listening to podcasts, watching series in french, reading books, etc.
I didn't pay anything for mango, it was entirely funded by my local library so that was great.