462 karma · joined December 14, 2017
“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?
Thanks for sharing!
It’s hard to take the rest of the article seriously after reading this!
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 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.
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.
Then, a month later, I receive a bill indicating a routine procedure that I assumed out of ignorance was covered by insurance (since they took my card and entered the numbers without saying anything to the contrary) for $500 (or, god forbid, more).
If I knew a salad at a restaurant were $200, I probably wouldn’t order it. There is no basic transparency in medical billing, and that needs to change.
So far, I have one other interview from an internal referral, but haven’t heard anything back from the ~10-15 other applications I’ve sent out. I’m getting a bit discouraged and feel similarly as you - it would be nice to take more time off (maybe I don’t actually love working in tech?), but I have the same worried as you. Feels good to vent in this thread, though :)
>> Indeed, this very essay, which I’d long planned to write some version of, is coming out now because the same effective altruist organization is offering a $20,000 prize to whomever gives the best critique of effective altruism this month.
I think this sentence tells you everything you need to know about this guy’s philosophy. The article also ends with him suggesting, as an “alternative”, to give a money to fundamentally utilitarian/effectively altruistic sources (AI safety research) and to fund projects that he’s interested in under the premise that these underfunded scientific fields are “awesome and epic”.
Another book that is relatively new that I loved was Designing Machine Learning Systems by Chip Huyen. I worked in productionizing ML systems for 3 years and this book equips you with exactly what you need to do so. It does a great job of explaining the whole ML modeling pipeline and some of the commonly overlooked nuances that can cause your models to fail spectacularly in production. I will be referencing this book for years to come.
It’s SO cool to see this on here. I’ve been tracking him using it when we get separated. Andy, if you see this, hello from Deadweight :).
Without actually looking through the code, I have a few questions:
1. How slow is it loading webpages? I think SMS would be a little sluggish since each message can only contain 160 characters.
2. How do you guys manage out of order text messages? Is there some sort of metadata that governs the order of a multi-part SMS?
Thanks so much for posting this - really a blast from the past.
1) Collected Fictions by Borges
2) The Complete Stories of Franz Kafka
3) The Master and Margarita by Mikhail Bulgakov
4) Invisible Man by Ralph Ellison
5) 9 Stories by J.D. Salinger
6) 60 Stories by Donald Barthelme
7) 100 Years of Solitude by Gabriel Garcia Marquez
8) The Sound and the Fury by William Faulkner
Do you have any advice for an AT hopeful for next year? I have done a fair amount of planning and have completed a ~250 mile thru-hike this past summer, but would still love some advice from a veteran (i.e. tent vs. hammock, how many sets of each type of clothing you ended up using, etc.)