Anthropic has developed an AI 'brain scanner' to understand how LLMs work and it turns out the reason why chatbots are terrible at simple math and hallucinate is weirder than you thought
Anthropic has developed an AI 'brain scanner' to understand how LLMs work and it turns out the reason why chatbots are terrible at simple math and hallucinate is weirder than you thought

Anthropic has developed an AI 'brain scanner' to understand how LLMs work and it turns out the reason why chatbots are terrible at simple math and hallucinate is weirder than you thought

Is that a weird method of doing math?
I mean, if you give me something borderline nontrivial like, say 72 times 13, I will definitely do some similar stuff. "Well it's more than 700 for sure, but it looks like less than a thousand. Three times seven is 21, so two hundred and ten, so it's probably in the 900s. Two times 13 is 26, so if you add that to the 910 it's probably 936, but I should check that in a calculator."
Do you guys not do that? Is that a me thing?
I think what's wild about it is that it really is surprisingly similar to how we actually think. It's very different from how a computer (calculator) would calculate it.
So it's not a strange method for humans but that's what makes it so fascinating, no?
This is pretty normal, in my opinion. Every time people complain about common core arithmetic there are dozens of us who come out of the woodwork to argue that the concepts being taught are important for deeper understanding of math, beyond just rote memorization of pencil and paper algorithms.
How I'd do it is basically
72 * (10+3)
(72 * 10) + (72 * 3)
(720) + (3*(70+2))
(720) + (210+6)
(720) + (216)
936
Basically I break the numbers apart into easier chunks and then add them together.
Nah I do similar stuff. I think very few people actually trace their own lines of thought, so they probably don’t realize this is how it often works.
I do much the same in my head.
Know what's crazy? We sling bags of mulch, dirt and rocks onto customer vehicles every day. No one, neither coworkers nor customers, will do simple multiplication. Only the most advanced workers do it. No lie.
Customer wants 30 bags of mulch. I look at the given space:
"Let's do 6 stacks of 5."
Everyone proceeds to sling shit around in random piles and count as we go. And then someone loses track and has to shift shit around to check the count.
But you wouldn't multiply, say, 7414 to get the answer.
72 * 10 + 70 * 3 + 2 * 3
That's what I do in my head if I need an exact result. If I'm approximateing I'll probably just do something like 70 * 15 which is much easier to compute (70 * 10 + 70 * 5 = 700 + 350 = 1050).
Well, I guess I do a bit of the same:) I do (70+2)(10+3) -> 700+210+20+6
I would do 720 + 3 * 70 + 3 * 2
I wouldn't even attempt that in my head.
I can't keep track of things and then recall them later for the final result.
Thanks
🙏
Thanks for copypasting. It should be criminal to share a clickbait non-descriptive headline without atleast copying a couple paragraphs for context.
Thanks for copypasting here. I wonder if the "prediction" is not as expected only in that case, when making rhymes. I also notice that its way of counting feels interestingly not too different from how I count when I need to come up fast with an approximate sum.
Isn't that the "new math" everyone was talking about?
How is this surprising, like, at all? LLMs predict only a single token at a time for their output, but to get the best results, of course it makes absolute sense to internally think ahead, come up with the full sentence you're gonna say, and then just output the next token necessary to continue that sentence. It's going to re-do that process for every single token which wastes a lot of energy, but for the quality of the results this is the best approach you can take, and that's something I felt was kinda obvious these models must be doing on one level or another.
I'd be interested to see if there are massive potentials for efficiency improvements by making the model able to access and reuse the "thinking" they have already done for previous tokens
I wanted to say exactly this. If you’ve ever written rap/freestyled then this is how it’s generally done.
You write a line to start with
“I’m an AI and I think differentially”
Then you choose a few words that fit the first line as best as you could: (here the last word was “differentially”)
Then you try them out and see what clever shit you could come up with:
Then you sort them in a way that makes sense and come up with word play/schemes to embed it between, break up the rhyme scheme if you want (AABB, ABAB, AABA, etc)
You get the idea.
Edit: in hindsight, that was a horrendous example. I suck at this, colossally.
well because when you say things like "it plans ahead" or "our method is inspired by brain scanners" etc it makes a connection between AI and real thinking and generates hype.
My favourite part of the day: commenting LLMentalist under AI articles.
that was a insightful piece, thanks for sharing
This reminds me of learning a shortcut in math class but also knowing that the lesson didn't cover that particular method. So, I use the shortcut to get the answer on a multiple choice question, but I use method from the lesson when asked to show my work. (e.g. Pascal's Pyramid vs Binomial Expansion).
It might not seem like a shortcut for us, but something about this LLM's training makes it easier to use heuristics. That's actually a pretty big deal for a machine to choose fuzzy logic over algorithms when it knows that the teacher wants it to use the algorithm.
You're antropomorphising quite a bit there. It is not trying to be deceptive, it's building two mostly unrelated pieces of text and deciding the fuzzy logic is getting it the most likely valid response once and that the description of the algorithm is the most likely response to the other. As far as I can tell there's neither a reward for lying about the process nor any awareness of what the process was anywhere in this.
Still interesting (but unsurprising) that it's not getting there by doing actual maths, though.
So it does the math in its head and gives the correct answer and copies the answersheet from the teachers book into the "show your work" section. Pretty much what i would have done as a kid if i could have, instead i had to fight them and take a hit to my score for not showing my work.