I have never before felt so much kinship from a single comment.
@lemmy.zip
I see Mullvad's move away from OpenVPN mentioned a lot, but not the reasons for it. So for anyone like me who is reading this and curious, here's a link to why they decided to move to Wireguard
Recovering fat guy here. Was 335 last year, down to 188 now. This is exactly it. I don't have that feeling at all. When I eat the only thing that tells me to stop is when I'm physically incapable of eating any more. Realizing that some people have that switch was a big part of what helped me figure out what I needed to do to lose weight. I have to count the calories of every single thing I eat and make sure it doesn't add up to more than I need in energy for the day. If I don't, I'll end up right back where I started.
It's one of the oldest dog breeds. Has less DNA in common than the Shiba Inu, but it's number two last I checked. There's paper floating around from a university in Hawaii that goes into more detail, but I couldn't dig it up in a quick search. Will try to find it and reply with it when I have more time later.
More than mildly disappointed to hear, though I totally understand. Yours was, in my opinion, the best content on the Fediverse. You will be sorely missed, and I hope where you go next ends up a more peaceful and less disruptive experience. o7
So, I was just at the Microsoft Power Platform conference in Vegas last week for work and while there was still obviously a TON of Copilot push, there was also a subtle tone running through the keynotes and panels lead by Microsoft where they kept saying "Pro code isn't going anywhere" and "People will always be a necessary step in any process". I get the impression Microsoft is panicking a bit about companies adopting their previous stance on AI too hard and promptly imploding. At least that's what I tell myself to sleep at night now.
That's not what science is, though. Science is about pushing the boundaries of human knowledge. Science isn't about having a problem and trying to find a solution -- that's engineering, which is informed by science.
I'm curious how far that stance goes. I live in an apartment and own a small breed dog. I work from home, so I'm with her all day. Additionally, she gets a minimum one mile walk in the morning regardless of weather or season, and the same after work in the evening. I've trained her since she was a puppy to be silent. She doesn't bark at all, the most noise she makes is some light whining when one of her favorite people come over.
In your opinion, should I not own her? Obviously I think I should, and feel like I've done my due diligence to provide exercise, entertainment, and training to give her and my neighbors a high quality of life. But I'm curious if your stance holds in every circumstance.
I'd argue the two greatest barriers for the average, non-STEM individual adopting metric in America is the speed limits being in mph and the temperature being in °F. Both are convertible easily enough, but when you constantly have to do so to engage with critical infrastructure or safety (cooking temps, etc.) It provides a barrier against adoption for anyone without the drive to make a concerted effort to use metric.
I have the Samsung Galaxy Z Fold 3. I absolutely adore this phone. It's thick, but I watch a lot of shows on my phone and having a tablet sized screen to watch them on without having to carry a separate device is amazing. They're not for everyone, I think, but if the flaws in current foldable technology aren't a problem for you and you have the right use cases, they're great.
If you're cooking, the strategy that has worked best for me is to measure all calories that go into the product, then divide it by the amount of servings you plan to consume. So if I make spaghetti and I plan on getting 6 meals from a batch, I'll divide the total calories by 6. As long as you're paying attention and accurately measuring out ingredients, it's going to be pretty close.
Constant combinator reading full belt, decider combinator sending an activation signal to an inserter with a filter determined by how much you want to keep. Inserter dumps off the side. It's how my space platform is running right now.
Hey there. Went through something similar about five years ago now. For me, the path to testing was through depression and anxiety therapy. Went to sessions for about a year exploring CBT with no success, and I kept mentioning my issues focusing. Eventually my therapist recommended looking into medication, and had added ADHD to my diagnosis. The meds specialist I saw immediately recommended treatment via Vyvanse. I know this isn't a straightforward path and might not work for you, but it got me to the point where there was at least some progress instead of constantly being stonewalled. A heads up, if you're dealing with depression around your exhaustion and focus issues getting treatment for ADHD isn't a cure all. I'm still working on a lot to try to get back to a healthy place. But it definitely makes it easier to work your way forward. Best of luck.
I work in IT with end users who average 45-50 years old. I can tell you where that message came from.
We've got users working with sensitive private information who are starting to use tools like ChatGPT and Gemini because their college kids told them they're helpful for checking writing, or work better than search engines. Our users work remotely and if they decide to take a picture of what they're working on and feed it into an OCR, there's not much we can do to stop it. So we need to provide a sanctioned tool that at least gives us some controls over how data is handled and stored (not that Microsoft provides anything vaguely resembling perfect data transit and analysis into Copilot) so we can try to protect sensitive information and our end users as much as possible. Are we happy about having to deploy AI tools? Not even a little bit. I'd be happier if we all just collectively rolled back a few years. But our options are sanctioned tool and policy or failing audits and here we are.
https://www.startpage.com/av/proxy-image?piurl=https%3A%2F%2Ftse4.mm.bing.net%2Fth%2Fid%2FOIP.jC52jjQnoxcQVERXNWnXLwHaDg%3Fpid%3DApi&sp=1766676135T84a90782420127bfcca174ff887d2e8a98f98b845243704ca7b4943087b5061f These are the graphs meteorologists have to interpret. This is after models have produced the data (which includes fourth order Runge-Kutta error correction differential equations) and interpreted it into a comprehensible form. Anybody working in weather sciences is a magician in every practical way, so far as I'm concerned. I worked an internship doing some of this a while back and came away wildly impressed with the systems and knowledge required to even try to guess how weather will behave over a day, much less a week.
thanks for using Leebra!
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