Just ask Claude or Replit to write your application. Coding is dumb. Software companies should fire all their autistic snooty computer science nerds and hire English majors instead.

We now also have the "improved" under new management BLS ... :-)

I don't think OP was dissing EVs, just noting that they, like other things, also use petroleum product for things other than fuels and some things that use fuels can't be easily replaced with EVs.

Former national security adviser Michael Flynn pleaded guilty to lying to the FBI and he got a pardon from the current President. If she doesn't have the political connections, this might cost just her some $$$ -- crypto or cash, they're not picky. /s

Swapped in someone else's urine for the test.

That's a trick question.

Answer: None. In 2025, Everything's Computer.

It ain't right what they did, opening it up like that.

Pretty sure we reached that point on November 5, 2024.

So close. More accurately, "Out of sock". :-)

Economists don't say this, what they say is a small amount of predictable inflation is better than deflation.

They do say it, and the reason they say it is that "wages are sticky" -- that is, they tend not to drop even when the market-clearing wage drops. Since it's very hard to reduce wages in nominal terms, inflation helps allow labor prices to drop in real terms.

Nevermind, it was just shitty AT&T 5G coverage as usual.

Claude, Gemini, ChatGPT, Meta, and Grok.

I can't believe it took this long for them to realize people didn't want a camera that they could not fully control within their own private homes possibly recording and displaying everything to random people at the company that built and maintains the device and potentially for anyone who found a security flaw in it.... I mean, really, what a smart item to stick into a TV that might go in say a bedroom, because nothing happens in there that shouldn't be broadcast across the world and saved forever....

What too many people do not seem to understand with LLMs is that everything it spits out is simply a probability matrix based on the input you gave it. It will first attempt to deconstruct the input you provided and use statistical analysis against it's trained knowledge base to then spit out letters, words, phrases and punctuation that statistically resembles the outputs it was trained to produce in it's training materials.

Until this version, ChatGPT obviously suffered from a lack of training materials within it's trained neural network to have it overcome the English language's typed grammar rules for it to be able to discern that em dashes are not typically used in everyday conversations and/or that the input to not use them needed to change it's underlying probability network to be able to ignore the English language's grammar rules and adopt it's output without the use of the em dash. This is a very difficult concept to train into a neural network as it needs to have been training on specifically this input/output case long enough to have that training override the base English grammar language model, which is a fundamental piece of knowledge a LLM requires to function and one of the very first things it is trained to handle.

It also exposes a flaw in how neural networks are typically working. There is a training/learning mode and then there is the functional mode of just using the trained network. In the functional mode, the neural network links, nodes, and function are effectively static. Without having built in-puts to the network so that it can flag certain functionality, it can not change it's underlying probability matrix to effectively forget something it was trained to do. Once that training has changed any of the underlying neural network, you can not effectively untrain it (without simply reverting to a previous backup copy of the network before it was trained). This is why it is so important to scrutinize every piece of data that is used to train the network. One you have added some piece of garbage input training, you are stuck with the changes it made to the probabilities of the output. Any model that is effectively training against the content of the internet itself is so full of bad information that the results can never really be trusted for anything other than probability of asking a random person for the answer because it will have trained on and included phases like "The earth is flat", "birds are not real", and "the moon landing was a hoax". It will have seen those things enough times that it will include them as higher and higher percentages of the proper response to questions about them....

All this time I thought I was the cool kid on the block with not just cable but HBO. And analog scrambled porn.