Google "ai" encouraging people to build their own fuses.

Between this and AI-run websites buying up all of the SEO its become really hard to google quizlets with the answers to your homework.

Big

Energy

i work with a bunch of former googlers and googleXers(?) and they are some of the most insufferable people on the planet

"Oh hey, do you know that the future is (grifty startup)? I can get you in on the ground floor; everyone's going to be using (grifty startup) very soon so let me hook you up to..."
- also see:
  
  "oh hey did you know Joan Norbaberts?" "yeah, she was an amazing xingbongler!" "yeah well i heard she went to Zombubo with Dave Bilbby" "oh yeah, but did you know Dave and Zach Erawan were working in building 42 back in 2009?" "no it wasn't building 42 it was building 87, the one with the spaceship themed ball pit on floor 7" "oh, no you're thinking of building 27, building 87 had the 360 degree wall of tvs that you could zoom in from space to see peoples' nose hairs" "oh yeah, but anyway Zeny Bazinga worked as an SRE with Dave... do you know Barla Bingus?" "yeah I worked with Barla Bingus on ads, but then Zipity Duda came and requisitioned a server farm in Alabama, oh hoo hoooo" "ohhh man you remember that? yeah oh my god, and LARRY SCHDMITDT WAS SO MAD" "YEAH LOL"
  
  and on... and on... and on... and on..

It's not that they hired the wrong people, it's that LLMs struggle with both numbers and factual accuracy. This isn't a personel issue, it's a structural issue with LLMs.

Because LLMs just basically appeared in Google search and it was not any Google employee's decision to implement them despite knowing they're bullshit generators /s
- I mean, define employee. I'm sure someone with a Chief title was the one who made the decision. Everyone else gets to do it or find another job.
They're Rube Goldbergian machines of bullshit but the bullshit peddlers (and the glazers) insist that adding more Rube Goldbergian layers to the Rube Goldberg machines will remove the systemic problems with it instead of just hiring people to fact-check. Hatred of human workers is the point, and even when they are used, they're made as invisible as possible, so it's just a Mechanical Turk in that case.

All of this, all that wasted electricity, all that extra carbon dumped into the air, all so credulous rubes can feel like the Singularity(tm) is nigh.
- Google gets around 9 billion searches per day. Human fact checking google search quick responses would be an impossible. If each fact check takes 30 seconds, you would need close to 10 million people working full time just to fact check that.

I feel like such a shitty engineer for not remembering or having the slightest interest in even the most basic electrical shit. i don’t even get this fucking meme.

I can do civil/mech/chem but show me electricity and I feel like I’m in preschool.

Pre 18th century ass brain capacity

North America uses 120 V for most circuits. Power is the product of voltage and current.

At 1 Amp, 120 watts are dissipated by the circuit. About the heat of two incandescent light bulbs.

At 10 Amps, 1200 watts are dissipated by the circuit, about the heat of a space heater.

At 551 Amps, 66,000 watts are dissipated by the circuit. I don't even have a good comparison. That's like the power draw of 50 homes all at once.

The higher the gauge, the lower the diameter of the wire. The lower the diameter of the wire, the more of that 66,000 watts is going to be dissipated by the wire itself instead of the load where it is desired. At 22 gauge, basically all of it will be dissipated by the wire, at least for the first fraction of a second before the wire vaporizes in a small explosion.

EDIT: In this scenario, the total resistance of the circuit must be at most 0.22 Ω. Otherwise, the current will not reach 551 A due to Ohm's Law, V=I×R. This resistance corresponds to a maximum length of 13 feet for copper wire and no load.
- That’s like the power draw of 50 homes all at once.
  
  So the average crypto mining rig?
- By dissipated by the wire instead of the load what do you mean?
- I ran this by my brother who’s an electrician and he inferred that might be where the number is coming from, some data on how many amps you can dump into various wire gauges before they simply stop being solids.
551 amps is an amount you would put in a comedic joke about using way too many amps
551 amps will vaporize the wire and cause Fun for all involved.
imagine trying to direct the output of a fire hose on full blast through one of those thin red drinking straws that come with cocktails
- Isn't that pretty much how a CNC machine works?
According to powerstream, the max amps 22 AWG can handle is 7 for chassis wiring, 0.92 for power transmission.
0.2 amps of current going through a human torso is fatal in virtually all cases.
Yeah, it took me a few minutes to realize "551 amps? that's an insane cartoonish number", also in the engineering field, but not electrical stuff

they've been paid off by the electrical fire lobby

kelly AI? More like A Lie

My job wants to use an AI medical notetaker instead of hiring someone for it... Surely nothing like this will happen :clueless:

return to oracles huffing gas in a cave, this shit sucks

putting the VFD into the ketchup every single time.

265k watts lol

For reference, 22awg solid is telephone wire. 22awg stranded is a hair thinner. I’ve made 22awg glow red-hot by dumping 12v and just a lil bit of anmps into it.

Shake hands with danger

my company is going full steam ahead with AI stuff and a coworker (who is lebanese and we talk about palestine but he has jewish cabal conspiracy brainworms ) loves the promise (fantasy?) of AI, especially GenAI. This mfer uses it to summarize short articles and write his emails. I feel like I'm a crazy person because I enjoy reading stuff and writing too.

He sent me a demo yesterday where they had a local instance of an LLM trained on internal data and sure enough it was able to pull info from disparate sources and it was legit kinda neat. Most of what it did was chatbot stuff but with NLP and NLG. To me, this seems like really complicated way of having a search algorithm which we know to be more efficient and faster especially since it was just fetching info.

However it was only neat bc it was running on internal data with strict boundaries, also it belies that a massive, comprehensive data dictionary had to be made and populated by people to allow for these terms/attributes/dimensions to be linked together. One of the things it did in the demo was execute SQL based off of a question how many of these items on this date? which it then provided as select sum(amount) from table where report_date = date and it also provided graphs to show fluctuations in that data over time. I didn't validate the results but I would hope it wouldn't make stuff up especially since the training set was only internal. My experience with other AI apps is that you can ask the thing the same question and you'll get different results.

but I would hope it wouldn't make stuff up especially since the training set was only internal

I use an internal LLM at one of the biggest tech companies and it makes shit up all the time lol
- Jfc. Like who do you blame here? The model for being stupid, the prompter for not validating and if they’re validating then are there any time savings?