Wow, thanks. I’m even coming up with 500K chatGPT queries for the amount of energy consumed as a KG of beef, though I might have moved a decimal place somewhere - feel free to check my math :)
“average query uses about 0.34 watt-hours of energy” - or 0.00034MWH
Using this calculator: https://www.epa.gov/energy/greenhouse-gas-equivalencies-calc... - in my zip, 0.0002KG of CO2 per MWH. (Though, I suppose it depends more on the zip where they’re doing inference, however this translation didn’t seem to vary much when I tried other zips)
Then, 99.48KG/0.0002KG= 497,400 chatGPT queries worth of CO2 per KG of beef?
This is really neat! I work in machine learning but still feel imposter syndrome with my foundations with math (specifically linear algebra and matrix/tensor operations). Does anyone have any more good resources for problem sets with an emphasis on deep learning foundational skills? I find I learn best if I do a bit of hands-on work every day (and if I can learn things from multiple teachers’ perspectives)
They know what you like, but that doesn't mean they will show you those profiles. Their goal is to maximize revenue, not maximize users finding good matches.
And at some places like Hinge, they'll identify your type so well that your "standouts" page (the one you have to pay to message people on) will be composed of 100% people you would probably like to speak to while your free feed will just be composed of people you have no interest in talking to!
I disagree. "The algorithm" is understood by everyone in 2025 to be a more-or-less perfect attention hoarder. TikTok, Insta, YouTube, etc. have proven they can definitely surface the content that users will like. I see no reason why profiles would be different.
They know what you like, but remember they want to make money. You finding success means you are probably less likely to get desperate and pay for premium options on their app. They drip feed you as little success as possible to still keep you on the app, but make you desperate.
It sucks, but a dating app doesn't want you successful, they want you to use their app for as long as possible.
I also had that reaction, but I kept reading and it was worth it. They mean it in a very narrow sense, and talk about the nuances and challenges of practical recommendation for much of the rest of the article.
This is great. Found myself on 5/30/22. Looking forward to catching up with photos of people I hiked with. Also love the pics from ‘79 - total time capsule! Short-shorts never went out of style in the hiking community.
I'm an AT hiker but I hate the short-shorts. I prefer the length to be just above the knee. If you've ever walked through a tall patch of poison ivy before you noticed what it was, you'll understand.
I’m in the shortest-shorts camp too. Less about the UL-value of the shorts, more about the mobility to lift my leg as high as I can (specifically to reduce friction going uphill). When you take literally millions of steps on a thru-hike, even the smallest things start to add up.
I’ll bite. I worked at a very large Fortune 500 company for a few years. Through some twist of fate, I ended up on an overfunded ML organization that was under no pressure to produce anything of business value. The executive in charge of this operation let this fly for about a year before they realized they weren’t getting anything valuable out of it. They put pressure on the VP of the org to start producing business value or else.
Fast forward another month or so and there are six hastily thrown together initiatives in which our organization is contracted to other organizations to “help them out”. The team dynamics were atrocious - our team was met with skepticism as to why we were helping out (was the other team not doing their job well enough?), and people on our team were often clueless on the business subject matter that we were supposed to be consulting on.
I was assigned to one of these initiatives, and upon digging into the business problem, our team realized that the feature importance was completely contained within a single categorical feature in the model. All other features in the model were comparable to uniformly randomly generated features. In the selfish interest of being able to claim that they “solved their problem with ML”, it was clear that either the model developer or the team at large had obscured this fact.
In an effort to save face, the VP kept us on the project, despite the poor relations and lack of useful features to improve the model. We didn’t improve the model and eventually, the VP ended up being “pushed out”. Last I checked, this VP is currently the CEO of a startup that recently raised a $100M seed round.
I imagine that’s just about the starkest within-US move you could make with regard to bike friendliness. I once made the mistake of visiting Houston without a rental car, and it was bleak. Welcome to NYC!
This is such a good idea, I wish I’d thought of it. I have trouble maintaining consistency in journaling, but this makes it a heck of a lot easier. I just signed up - good luck!
This is great. I remember finding another really good resource on the Bernoulli bandit that was interactive. Putting feelers out there to see if anyone knows what I’m talking about off the top of their heads.
I’m in a bit of a privileged position, but I took a fair bit of time off to pursue personal goals. I got extremely burnt out after 6 years of full-time work at big corp (simultaneously being in part-time grad school for the final 3 years).
I found it took me 3-4 months of absolutely nothing to not feel burnt out. It took much longer than that to get to a point where I was able to pick up my computer and have fun programming again. I’m now working on a webapp that I intend to turn into a business. I have been pouring myself into it in a way that I haven’t done since I was a new hire.
Hang in there. Maybe ask your boss if you can take an unpaid sabbatical. You will ultimately be much more productive if you get a break, and the time off will give you a chance to clarify to yourself what it is that you want.
> I found it took me 3-4 months of absolutely nothing to not feel burnt out.
That seems a universal experience. And to be more clear, absolutely nothing to think about, because even a sabbatical wouldn't save you if you think about post-sabbatical matters.
I took a year of non-employment in 2022 after 7 1/2 years of working in the same big corp. My experience shows that it takes me 1 to 2 years until I start to feel burnt out and need something new to work on, and fortunately the company was able to provide such refresher on time (not necessarily at my request) but wasn't able to do this time. So I quit, and next 3--4 months were absolutely non-productive time for me. (I have a ton of side projects at any moment and I realized my burn-out from not being able to work on any of them.) But that followed by a very productive period without any frustration [1], and I was eventually energized enough at the end of 2022.
Sadly not everyone can't afford this, I know, but if you can, consider doing so too. A year should be enough to clear your mind and start anew again, assuming you don't have any other significant problem affecting your life.
Entirely correct, it's really unfortunate that this advice is not actionable for everyone. I was able to pull it off partly because I had enough saving and I lived alone.
I’m unemployed in NYC right now - so, zero consistent income. I’m one of those people with the very worst marketplace health plans. Here’s what I get for $640/mo (with a $120 tax credit, oh boy!):
- Visits to my general practitioner (but not so fast! no diagnostic tests or ANYTHING else - those are 100% out of pocket until my $9,000 deductible is met)
- Pregnancy care (it’s currently a biological impossibility for me to give birth)
Everything else is entirely out of pocket until my $9,000 deductible is met. My coverage is basically a $6,000 guarantee that I won’t be completely bankrupted if I get run over by a garbage truck and live to tell the tale. Otherwise, it’s completely useless. Something’s gotta give.
