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“And you know, you go back through history, this is like just before the Holocaust. I swear. If you look, it’s the same thing,” Trump said. “You had a weak president or head of the country. And it just built and built. And then, all of a sudden, you ended up with Hitler. You ended up with a problem like nobody knew.”
So Trump is claiming that Biden is a weak leader, and that after the weak leader comes somebody like Hitler. Trump hopes to be the person that comes after Biden…
Programmer pay is so bizarre, it makes me cynical about our entire economy.
If I’m a blue-collar worker maintaining the wires between banks, I get paid little. If I’m a programmer maintaining the banking software that controls everyone’s money and is essential to the entire nation, I’m paid a little more, but not as much as some programmers.
If I’m a young man who creates a webpage that barely works venture capitalists are tripping over themselves trying to shove millions of dollars into my hands.
(Although, creating a webpage was the hot thing last decade, now the hot thing is creating an AI.)
I think the joke is that the Jr. Developer sits there looking at the screen, a picture of a cat appears, and the Jr. Developer types “cat” on the keyboard then presses enter. Boom, AI in action!
The truth behind the joke is that many companies selling “AI” have lots of humans doing tasks like this behind the scene. “AI” is more likely to get VC money though, so it’s “AI”, I promise.
The “trees” for an LLM are their neural networks and word vectors. The forest is a word prediction algorithm. There is no higher level to what they do.
At what level do LLMs teach? Something was teaching me linear algebra and I thought it was the GPT4. When GPT4 was able to recognize a valid mathematical proof that was previously unknown to it, what level was it operating at?
As a programmer I can confirm that LLMs definitely have loops. Look at the code, look at the algorithms, you will see the loops. The “core loop” in the LLM algorithm is “read the context, produce the next work, read the context, produce the next word”.
The core loop in animals is “receive stimulus using senses, move muscles, receive stimulus using senses, move muscles”. That’s all humans do, that’s all animals do.
I think there’s a possibility that humans are simply very advance machines. Look at the debate over whether humans have free will, it’s an interesting question and the important take away is that we still have a lot to learn about our brains and physics. I don’t want to get into that though.
You’ve ignored my main complaint. I said that you treat LLMs and humans at different levels of abstraction:
It’s not fair to say that LLMs simply predict the next word and humans have feelings and reason.
It would be fair though, to say that LLMs simply predict the next word and humans simply bounce electric-chemical signals between neurons and move muscles.
I don’t think that way about people or LLMs though. I think people have feeling and reason, and I think LLMs reason too. LLMs aren’t the same as people and aren’t as good though. But LLMs are good enough to say that they can “reason” in my experience[0].
[0]: I formed this opinion when learning linear algebra from GPT4. It was quite a good teacher. The textbook I’m using made a mistake that GPT4 caught. I encountered a proof that GPT4 wasn’t aware of, and GPT4 wouldn’t agree with me that C(A) = C(AA^T) until I explained the proof, and then GPT4 could finally reason for itself and see for itself that C(A) = C(AA^T). As an experiment, I started a new GPT4 session and repeated the experiment using a faulty proof, but I wasn’t able to convince GPT4 with a faulty proof, it was able to reason through the math concepts well enough to recognize when a mathematical proof was faulty and could not be convinced by a faulty proof. I tried this experiment 4 or 5 times. To be clear, what happened here is that GPT4 was able to learn a near math concept in one shot (within a single context window), but only if accompanied by a proper mathematical proof, and was smart enough to recognize faulty proofs as being faulty. To me, that rises to the level of “reason”.
You apply a reductionist view to LLMs that you do not apply to humans.
LLMs receive words and produce the next word. Humans receive stimulus from their senses and produce muscle movements.
LLMs are in their infancy, but I’m not convinced their “core loop”, so to speak, is any more basic than our own.
In the world of text: text in -> word out
In the physical word: sense stimulation in -> muscle movement out
There’s nothing more to it than that, right?
Well, actually there is more to it than that, we have to look at these things on a higher level. If we believe that humans are more than sense stimulation and muscle movements, then we should also be willing to believe that LLMs are more than just a loop producing one word at a time. We need to assess both at the same level of abstraction.
Yes. I learned this from Haskell. I like Haskell, but it has a lot of very granular functions.
Earlier comment said that breaking up 1 function into 3 improves readability? Well, if you really want readability then break it up into 30 functions using Haskell. Your single function with 25 lines will become 30 functions, so readable (/s).
In truth, there’s a balance between the two. Breaking things up into function does have advantages, but, as you say, it makes it more likely that you’ll have to jump around a lot to understand a single process.
Shorter code is almost always better.
Should you use a class? Should you use a Factory pattern or some other pattern? Should you reorganize your code? Whichever results in the least code is probably best.
A nice thing about code length is it’s objective. We can argue all day about which design pattern makes more sense, but we can agree on which of two implementations is shorter.
It takes a damn good abstraction to beat having shorter code.
LIke 15% of the nation is working in healthcare if you include insurance and all the supporting industries. No wonder our health care costs are high. My medical bill has to keep 15% of the nation afloat and most of it ain’t going to the doctors and nurses.
Simplify the system, more doctors and nurses, fewer insurance executives. Single payer would do this.
Some people have bad eyesight. Some people have been deeply trained by the modern web to ignore most of what’s on the page (most of it being ads or other bullshit). Some people make mistakes.
Have some patience and kindness.
And to those who wont be patient or kind, just know that the next time the self-checkout machine yells at you and the cashier has to come scan their badge and gives you grief, you deserve it. Can’t you just use the machine correctly!?!
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It’s funny because JD Vance is overshadowing Trump. I see more talk about JD Vance than I do about Trump.
Trump needs the hate and attention, his supporters like him because he is counter-culture. Trump is their guy in the fight. If that stops then Trump becomes just an old rich white guy. This is why Trump plays the victim card every speech and talks about all the attacks he’s constantly suffering.