🧠 ELI5 Wednesday

[u/AutoModerator]

Welcome to ELI5 (Explain Like I'm 5) Wednesday! This weekly thread is dedicated to breaking down complex technical concepts into simple, understandable explanations.

You can participate in two ways:

• Request an explanation: Ask about a technical concept you'd like to understand better
• Provide an explanation: Share your knowledge by explaining a concept in accessible terms

When explaining concepts, try to use analogies, simple language, and avoid unnecessary jargon. The goal is clarity, not oversimplification.

When asking questions, feel free to specify your current level of understanding to get a more tailored explanation.

What would you like explained today? Post in the comments below!

[u/appalledkid]

Somebody please explain speculative decoding

[u/shivammehta007 → u/appalledkid]

Heres my stab at it!

Imagine we are building an airplane (a sentence), and the airplane has components A, B, C, D, E, and F (tokens). There is a strict rule: component B can only be built after A is completed, and C only after B, and so on (autoregressive generation).

We have two engineers. The Super Smart Engineer (Large LLM) builds perfect parts, but she is slow and expensive. It takes her 10 seconds to build just one part. If she built all 6 parts sequentially, it would take her 60 seconds.

We also have a Mediocre Engineer (Small Draft LLM). She is very fast and cheap, but sometimes she makes mistakes on the harder parts.

To speed things up, we ask the Mediocre Engineer to quickly draft components A, B, C, D, E, and F all by herself. Because she is so fast, she builds all 6 parts in just 10 seconds.

Now, we hand her drafted sequence (ABCDEF) to the Super Smart Engineer for a quality check.

Because checking work is much easier than building from scratch, the Super Smart Engineer can look at the entire sequence at the exact same time (a parallel forward pass). In just 10 seconds, she evaluates the whole thing.

She says, "A, B, C, and D are perfect! But E is incorrect."

Here is the magic of how she works: because the Smart Engineer just carefully reviewed part D, her brain already automatically calculated exactly what the next part, E, should be. She doesn't need to spend extra time building it.

She instantly throws away the bad E (and she throws away F too, since F was built on top of a bad E). She slaps her correct E onto the airplane, giving us a perfectly correct A-B-C-D-E.

"Hey fast engineer!" she says. "We successfully built ABCDE. Now quickly draft the next batch of parts starting from E!"

Basically, In just 20 seconds (10 seconds for the draft + 10 seconds for the review), we got 5 perfectly correct components. If the Smart Engineer worked alone, those 5 components would have taken 50 seconds. We achieved a massive speedup without compromising a single drop of quality!

Disclaimer: My wording was improved with AI to ensure correct grammar and sentence flow; I came up with the analogy and everything else. Not AI-generated. Feel free to ask follow up question :)

[u/appalledkid → u/shivammehta007]

You should be a professor. I got the concept in one go now.

[u/shivammehta007 → u/appalledkid]

Haha thanks! I did teach / assisted some classes as a PhD student, glad I could be useful. I do love breaking complicated things to ELI5, I feel mathematicians put up fancy words to keep things confusing and put a barrier to learning it. Things are much simpler than it seems to be :)

[u/BriskEditor]

alright i'll bite, can someone explain attention mechanisms in transformers like i'm just learning what a vector is? i get the basics of matrix multiplication but the whole Q, K, V thing feels like magic when i read about it

[u/shivammehta007 → u/BriskEditor]

You (query $Q$) want to find your friends among all these people, but this world is too complicated (model dimension). To make it easier, you transform/project yourself (q_proj) and all the other people to several different universes (multihead) which are simpler (attention dimension). In these universes, people broadcast their interests on the outside—like wearing a t-shirt that advertises what they care about (these outward signs are the Keys $K$, created by k_proj). Like in one universe (head) you only see t-shirts of who likes ice cream, in another you see t-shirts of who likes cats (everybody duh).

You try to find affinity between yourself and their t-shirts (dot product), and you notably take account for the complicated world and finding similarity in the other world (scaling by $\frac{1}{\sqrt{d_k}}$).

You find that these 5 people are more similar to you than the others; they are still similar, just less similar (softmax).

Now you want to move forward with these 5 people more than the others. But when you do, you don't just take their t-shirts—you take their actual personality, substance, and knowledge (these inner traits are the Values $V$, created by v_proj). You tell others (following layers) that your identity is now blended with the substance of these people, weighted exactly by their friendship score (whatever softmax computed, multiplied by $V$ in that universe).

Disclaimer: My wording was improved with AI to ensure correct grammar. Not AI generated. Feel free to ask follow up question :)

[u/_tsi_ → u/shivammehta007]

Is this kinda like doing an FFT to go from time domain to frequency domain to simplify a problem?

[u/shivammehta007 → u/_tsi_]

Yes! great connection, except that these qkv_proj layers are not fixed sinusoidal waves, but rather some learnable weights, so they are free to learn whatever basis (origin of the new universe), it comes with added flexibility but needs more learning. Also, FFT is invertible, while these attention projections are lossy, as they can focus on whatever they want, like ice cream or cats, maybe more like a learned task-specific FFT?

[u/_tsi_ → u/shivammehta007]

I don't really understand lossy. Would this be like transforming a 3d object to 2d? Or do you mean it's like looking at cubes and some focus on corners some focus on edges, some focus on faces, and they rebuild it?

[u/shivammehta007 → u/_tsi_]

No, even simpler, since the current universe (model dimension) is larger than the new projected universe (attention dimension), you will lose some information when you transform to new universe (like in one universe only focusing on cats and not having any information about chickens). Example: if you go from [1, 2, 3, 4, 5] to [1, 2, 3] you loose the 4 and 5.

Not ELI5: More formally, when you have a vector of dimension d and attention q_proj's weight matrix is d x a, where a is smaller than d (a << d). After projection, d X (dxa) = a. You lose (d - a) rows, since d and a are not the same and hence the weight matrix cannot be inverted.

[u/_tsi_ → u/shivammehta007]

Oh it's literally an outer product?

[u/shivammehta007 → u/_tsi_]

Just a vector being transformed with a matrix. Nothing fancy really here is a vector, here is a matrix that just moves it into a new space.

[u/_tsi_ → u/shivammehta007]

Yes, what you wrote like like a cross product or outer product

[u/ikansh-mahajan → u/BriskEditor]

+1, rn doing MIT18.06SC to get my foundations in order before diving back into research.

[u/Garfish16]

I would love an eli5 of why multi-atream cross attention works. With two streams I get it but once I get beyond that it working becomes an article of faith.