I bet you plenty of people absolutely do want this.
Most people can barely use a computer and would love this if it worked well.
You forget a huge percentage of users can barely access their emails.
Lemmy is very techcentric and most users on here are far from the average consumer on technical literacy.
You just aren’t the target audience.
It’s amazingly good at moderating user content to flag for moderator review. Existing text analysis completely falls down beyond keyword filtering tbh.
It’s really good at sentiment analysis. Which is great for things like user reviews. The Amazon ai notes on products are actually brilliant at summarizing the pros and cons of a product. I work for a holiday let company and we experimented with using it to find customers we need to follow up with and the results were amazing.
It smashes other automated translating services as well.
I use it a lot as a programmer to very quickly learn new topics. Also as an interactive docs that you can ask follow up questions to. I can pick up a new language as I go much faster than with traditional resources.
It’s honestly a complete game changer.
I’m guessing they have limited resources for direct intervention so use this to flag up people who have the most risk factors.
It doesn’t sound like this is people asking for help but more trying to predict who might need it.
after an investigation by The Fuller Project and The Markup found the department’s algorithm prioritized White, male veterans. It also gave preference to veterans who are “divorced and male” and “widowed and male” but not to any group of female veterans.
It shouldn’t favour anyone. It should treat each person as an individual and figure out what they need based on their characteristics. If it’s been designed to only work well for white men it’s been designed poorly.
It has always had structs. They are often used for interop but can be used to avoid allocations and they are memory safe out the box, which nice.
Both languages are really great in my opinion. But very different use cases generally.
The reason is the vast majority of places use c# to avoid this stuff. So performance is often not the first priority
The complexity it adds takes away from the readability and maintainability. Which is often the priority.
But in a hot path where you need optimization these are a good send as previously you had to use raw pointers and completely side step all the safety of the language.
I would say 90% of c# developers will never touch these. It’s more for library and framework writers.
I believe most of these features are driven by what the Microsoft Devs need to write asp.net and EF.
It’s 100% not a borrow checker because c# doesn’t have borrowing. It’s just static analysis to ensure memory safety. But the author acknowledges that.
It’s just checking the scopes the variables are defined in in the first example.
As a type 1 diabetic with multiple attachments already this sounds great.
They can still revoke its use anytime they want. Which is the main issue right?
No it’s a neural network. They may be over-hyped but they are 100% an AI.
August 31, 1955 The term “artificial intelligence” is coined in a proposal for a “2 month, 10 man study of artificial intelligence” submitted by John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Nathaniel Rochester (IBM), and Claude Shannon (Bell Telephone Laboratories)
http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html
This is just literally not true.
Point 3 is what LLMs are.
You are thinking of general artificial intelligence from sci-fi
An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans,
This is what artificial intelligence actually means. Solving problems that traditionally require intelligence
Path finding algorithms in games are AI. And have always been referred to as such. We studied them my AI module at uni.
Machine learning is just a specific field in AI. It’s all AI. Anything that attempts to mimic intelligence is.
All the things you mentioned are neural networks which are some of the oldest AIs.
Tbh as an experienced programmer I knew exactly what it was straight away. And I don’t know rust. I would imagine the others are similar.
The reason that example is simpler is because JSON is literally JavaScript Object Notation.
It’s also not the same thing. HashMap have type parameters. So you can only add strings to that HashMap whereas you can add anything in js. Does that code even compile?
You can also do “text”.to_string() which simplifies it more.
I feel you’re quite inexperienced and once you do more in different languages you’ll begin to realise why things are like this.
Rust is a compiled language with static typing so these things are required for the compiler to do its job.
It’s also a performance focused language and would blow ts/js out of the water completely on that metric.
Languages are just tools and they all have advantages and disadvantages. You use the right tool for the job.
That example is so insanely readable lol
Absolutely standard looking code for many languages.
Seems sensible. Check the output of AI tools before posting. Be pretty stupid not to proof read it at a minimum.
Yeah tagging things for debug purposes feels odd
Super nice to have a proper metric.
People always talk about how great rust is. But I feel how gross c++ is isn’t talked about enough.
How would you check two variables have equal values without changing the value of one otherwise?
Assignment you are assigning a value to the left side. Equality you are checking if the left and right are equal.
It’s “set equal to” Vs “is equal to” one is an operation the other is a condition.