A bunch of corporations been recording me and using my data for their own gain for a decade. Now you tell me some normie is going to record me? Do I care?
I was reading about the Unity debacle and thought thank God Gabe that Steam has never pulled shit like this.
I think part of the problem is too many companies are controlled by venture capitalists, or private equity, or whatever you call it. The point is that a single entity owns multiple companies from the shadows.
Companies are supposed to compete and the best company win, that's good in theory. But when a single shadow entity owns multiple companies they'll do something like squeeze customers of one company, which drives customers to their competitor, which, surprise, is owned by the same shadow entity.
I wish we had a branch of government filled with randomly selected people.
Imagine if we filled each house seat by randomly selecting 5 people, having the 5 people debate, and then people could vote for which of the 5 they wanted. We would then have a government filled with normal but likable people.
This is actually a legit excuse. If someone is working more than one job to afford rent, are we just going to tell them to walk an hour back and forth to the grocery store every day for food?
If the solution is for people to do things that require more time, the first step is to make sure people have more time.
Teetering on the edge is where you have a chance to win.
When things are going easy and you stick to your goals, good job, but will it stick?
When thins are hard and you stick to your goals, that's like a Matrix "he is beginning to believe" moment. You show yourself that hard times aren't enough to distract your from your goals.
Best wishes, keep trying, if you fail and try again, that's another important moment.
Projects that have coding standards that are documented. If you want to contribute to one of these projects then read the coding documentation and follow it. People will help you write code that fits the standards.
Projects that don't have coding standards. When you look at such a project you'll see endless layers of shitty hacks that mostly work, sometimes. Add your own shitty hack to the pile and as long as everything still mostly works, you're good.
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(AAT) until I explained the proof, and then GPT4 could finally reason for itself and see for itself that C(A) = C(AAT). 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.
Buttons @ Buttons @programming.dev Posts 7Comments 359Joined 2 yr. ago
Everyone talks about how great Nokia bricks are, but you actually do have to be careful not to drop them or you might damage the floor.