It's the same for me. I'm in Australia and on my work laptop I'm connected to an American VPN. It's showing my location as USA. I was wondering how it's detecting the country.
I've been through two restructures and both times I'd full access to everything for a month until my position was being decided. There thousand plus employees affected and not a single one did anything like what you've described. I'm Australian if that helps.
A 2mph bump isn’t nothing. If it failed to stop it can trample people. It can still do damage to elderly or disabled people. The 17mph collision may have caused some minor damage to the “fixed object” but that fixed object could've been someone standing still. Tesla is not making an effort, they're doing the bare minimum.
Shouldn't these workers in Phillipines be required to be licensed to drive cars in the USA to operate those vehicles (even remotely)? I understand that they're not really driving those cars. But they've control over these cars and they do operate them when required on public roads.
Well, they make perfect sense to buy down here in here Australia. When I replace my current seven year old ICE car, it'll either be a diesel or a petrol electric hybrid. In either case it'll be a Japanese one.
Environmental restrictions! All our data is on cloud and for customer privacy we're not allowed to download anything locally. We've access to most of the LLM models from all big vendors. I've found them to be very similar.
The site/visualisations look great. But having used AI tools in my programming, I still haven't been able to justify the cost (to the planet too) vs benefit. I've noticed that it's great for pattern recognition and if I've missed something small or missed a variable name here and there, then it's quite good at finding those problems. However, if I ask it to produce a complete piece of work, I've never been able to get something without any bugs. Forget about getting it to design data pipelines with customer privacy and data security in mind!
For reference I work in finance/econometrics and the code is often about numerical analysis written in SQL and python. More often than not I end up wasting a lot of time fixing issues with AI generated code. None of these nuances ever gets captured by metrics like these and it makes me question people (mostly sales and top execs) that push for "AI" at work.
Yes, the programming languages course on Coursera! Yes, you're right, Scala is a lot more prevalent mostly because of Spark. I work on Spark occasionally but mostly use pySpark. But I'm fascinated by the world of functional programming. I think I tried setting up Elixir on my Mac a couple of years ago and it didn't work for some reasons and I almost forgot about it after that. I'm a bit interested in F# as a lot of finance companies use it. It's not that popular. I learned a bit from a Udemy course and I really liked the language even thought I'm not a fan of Microsoft. And it works perfectly on Macs! :)
I thought Elm was very much about web development. And Elixir is too in some ways. Both Scala and F# have a lot going on in the data space. Scala more so than F#. Standard ML is exciting because it's not big. And probably a better choice for understanding the fundamentals but Scala or F3 for something serious? This is just my best guess. Actually that reminds me of a very nice course in Standard ML from the University of Washington on Coursera, but it's not a book.