What makes that the more likely scenario?

Because it’s their facility

this facility has never had this issue until the FBI showed up to commandeer their incinerator.

Says who?

For all we know they’ve had issues everytime they incinerate but they ignored it cuz a lil bit of smoke from 1 cat is way easier to shrug off compared to a huge amount of meth

It’s very possible they just have been ignoring the problem because normal smoke from incineration a very small cadaver isn’t a big deal, whereas meth fumes are extremely toxic and not something you can just shrug off

Lord knows I’ve worked with workers who have the “I’ve been doing it this way for 10 years and never had an issue, don’t be a pussy” type of attitude too

So hard to say, without more info it’s basically just us speculating.

rather than the FBI for their clear incompetence?

The article has not stated who was responsible for operation of the facility.

It’s more likely the responsibility was on the staff to ensure the equipment at their own facility was functioning right

This sort of error should have been covered by prior operation licensing checks, a facility with an incinerator on premises shouldn’t have negative pressure issues

So something somehow caused a negative pressure issue.

Usually the culprit is some kind of exhaust fan being run, or a door being left open too long

Based on time of year and how hot out it is, I wonder if a staff member left a door propped open or something.

Incinerator systems need positive pressure overall.

Anyone who lives in the north and has a gas based furnace heating system knows how deadly negative air pressure can be…

Read the article:

The incinerator is usually used by animal control officers to dispose of euthanised animals, but local authorities said it can also be used by law enforcement to burn seized narcotics.

The incident was caused when smoke was pushed in the wrong direction because of negative pressure, according to Assistant City Administrator Kevin Iffland.

That sounds like it wasn’t a method specific issue, and if anything had been burnt in that incinerator it would’ve caused the same issue.

Sounds like the facility wasn’t setup right, any facility with an incinerator should definitely have positive pressure, not negative.

Source? This is just some random picture, I’d prefer if stuff like this gets posted and shared with actual proof backing it up.

While this might be true, we should hold ourselves to a standard better than just upvoting what appears to literally just be a random image that anyone could have easily doctored, not even any kind of journalistic article or etc backing it.

Anytime an article posts shit like this but neglects to include the full context, it reminds me how bad journalism is today if you can even call it that

If I try, not even that hard, I can get gpt to state Hitler was a cool guy and was doing the right thing.

ChatGPT isn’t anything in specific other than a token predictor, you can literally make it say anything you want if you know how, it’s not hard.

So if you wrote an article about how “gpt said this” or “gpt said that” you better include the full context or I’ll assume you are 100% bullshit

Sorry. Naive and easily fooled by propaganda and disinformation that feeds into their bigotry

My bad ❤️

Not appropriate enough.

Unironically over 30% of people somehow still voted conservative.

I’m ashamed to admit a very large amount of them are from my area.

I don’t know what is wrong with some people. The education system has clearly desperately failed many of the people here though.

Wow, that sure is something else.

This genuinely made me do an IRL spit take, holy shit.

Same, but they did set up a self hosted instance for us to use and, tbh, it works pretty good.

I think it’s s good tool specifically for helping when you dunno what’s going on, to help with brainstorming or exploring different solutions. Getting recommended names of tools, finding out “how do other people solve this”, generating documentation, etc

But for very straightforward tasks where you already know what you are doing, it’s not helpful, you already know what code you are going to write anyways.

Right tool for the right job.

I primarily use GPT style tools like ChatGPT and whatnot.

The key is, rather than asking it to generate code, specify that you dont want code and instead want it to help you work through the solution. Tell it to ask you meaningful questions about your problem and effectively act as a rubber duck

Then, after you’ve chosen a solution with it, ask it to generate code based on all the above convo.

This will typically produce way higher quality results and helps avoid potential X/Y problems.

For sure, much like how a cab driver has to know how to drive a cab.

AI is absolutely a “garbage in, garbage out” tool. Just having it doesn’t automatically make you good at your job.

The difference in someone who can weild it well vs someone who has no idea what they are doing is palpable.

Good, fire 2 devs out of 3.

Companies that do this will fail.

Successful companies respond to this by hiring more developers.

Consider the taxi cab driver:

With the invention if the automobile, cab drivers could do their job way faster and way cheaper.

Did companies fire drivers in response? God no. They hired more

Why?

Because they became more affordable, less wealthy clients could now afford their services which means demand went way way up

If you can do your work for half the cost, usually demand goes up by way more than x2 because as you go down in wealth levels of target demographics, your pool of clients exponentially grows

If I go from “it costs me 100k to make you a website” to “it costs me 50k to make you a website” my pool of possible clients more than doubles

Which means… you need to hire more devs asap to start matching this newfound level of demand

If you fire devs when your demand is about to skyrocket, you fucked up bad lol

You skipped possibility 3, which is actively happening ing:

Advancements in tech enable us to produce results at a much much cheaper cost

Which us happening with diffusion style LLMs that simultaneously cost less to train, cost less to run, but also produce both faster abd better quality outputs.

That’s a big part people forget about AI: it’s a feedback loop of improvement as soon as you can start using AI to develop AI

And we are past that mark now, most developers have easy access to AI as a tool to improve their performance, and AI is made by… software developers

So you get this loop where as we make better and better AIs, we get better and better at making AIs with the AIs…

It’s incredibly likely the new diffusion AI systems were built with AI assisting in the process, enabling them to make a whole new tech innovation much faster and easier.

We are now in the uptick of the singularity, and have been for about a year now.

Same goes for hardware, it’s very likely now that mvidia has AI incorporating into their production process, using it for micro optimizations in its architectures and designs.

And then those same optimized gpus turn around and get used to train and run even better AIs…

In 5-10 years we will look back on 2024 as the start of a very wild ride.

Remember we are just now in the “computers that take up entire warehouses” step of the tech.

Remember that in the 80s, a “computer” cost a fortune, took tonnes of resources, multiple people to run it, took up an entire room, was slow as hell, and could only do basic stuff.

But now 40 years later they fit in our pockets and are (non hyoerbole) billions of times faster.

I think by 2035 we will be looking at AI as something mass produced for consumers to just go in their homes, you go to best buy and compare different AI boxes to pick which one you are gonna get for your home.

We are still at the stage of people in the 80s looking at computers and pondering “why would someone even need to use this, why would someone put one in their house, let alone their pocket”

No, it’s just not something exposed to you to see

But under the hood it very much does shift gears depending on what you ask it to do

It’s why gpt can do stuff now like analyze contents of images, basic OCR, but also generate images too.

Yet it can also do math, talk about biology, give relationship advice…

I believe open AI called the term “specialists” or something vaguely like that, at the time.

I am indeed getting more time off for PD

We delivered on a project 2 weeks ahead of schedule so we were given raises, I got a promotion, and we were given 2 weeks to just do some chill PD at our own discretion as a reward. All paid on the clock.

Some companies are indeed pretty cool about it.

I was asked to give some demos and do some chats with folks to spread info on how we had such success, and they were pretty fond of my methodology.

At its core delivering faster does translate to getting bigger bonuses and kickbacks at my company, so yeah there’s actual financial incentive for me to perform way better.

You also are ignoring the stress thing. If I can work 3x better, I can also just deliver in almost the same time, but spend all that freed up time instead focusing on quality, polishing the product up, documentation, double checking my work, testing, etc.

Instead of scraping past the deadline by the skin of our teeth, we hit the deadline with a week or 2 to spare and spent a buncha extra time going over everything with a fine tooth comb twice to make sure we didn’t miss anything.

And instead of mad rushing 8 hours straight, it’s just generally more casual. I can take it slower and do the same work but just in a less stressed out way. So I’m literally just physically working less hard, I feel happier, and overall my mood is way better, and I have way more energy.

Meanwhile a huge chunk of the software industry is now heavily using this “dead end” technology 👀

I work in a pretty massive tech company (think, the type that frequently acquires other smaller ones and absorbs them)

Everyone I know here is using it. A lot.

However my company also has tonnes of dedicated sessions and paid time to instruct it’s employees on how to use it well, and to get good value out of it, abd the pitfalls it can have

So yeah turns out if you teach your employees how to use a tool, they start using it.

I’d say LLMs have made me about 3x as efficient or so at my job.

They did that awhile ago, it was a big feature if gpt 3

We already did this like a year ago mate. That was like v3 of gpt