If you guys do not know,

chat, chat, everybody in here, Casey,

trash,

the startup is going through a bit of a

change, all right? There's been some

investment interest.

And we are now raising a series A like

any proper multi-billion dollar unicorn

startup.

>> Cool.

>> And so therefore

>> Decacorn.

>> Decacorn, really? We're a decacorn? And

so

>> Yeah.

>> I don't know what that means yet, but

someone told me it's like that's the

best kind of unicorn. I think it means

it has multiple horns. I don't know what

it means.

>> 10 10 horns.

>> 10 horns.

>> 10 horns.

>> Okay, nice. So it's kind of like the the

beast in the Bible, the devil, right?

Very cool.

>> have 10, does it?

>> Yeah, yeah, yeah, yeah, yeah, yeah,

yeah, yeah, yeah, yeah, yeah.

Uh anyways, I'm sorry.

>> Fact checkers? Fact checkers?

>> Fact checkers?

And so with that

>> teacher who will fact check that one.

>> I actually thought TJ was going to fact

check me, but he fact checked me

incorrect.

>> It didn't seem 10, but that it could be,

could be.

>> Bunch of you know who's read Revelation.

What the hell's going on here, guys?

>> Hold on, hold on. Well, that is kind of

what they what it answers, you know.

>> [laughter]

>> Anyway.

>> All right, so he has 10 horns. Called

it. Okay, primary reference, I got it.

Okay, I was I was correct on that one.

>> Okay, good.

>> Referenced. All right, so with that in

mind, we

>> for our theology. All right.

>> [laughter]

>> Just let it happen, everybody, okay?

My gosh. All right, this is not starting

off the way I wanted it to. So anyways,

nor does any standup. All right, so with

all of that said, that means as part of

our amazing content, I have now

organized us an amazing linear board,

which will help us walk through a more

organized standup, because if there's

one thing I know about in raising a

series A is they want to see

agile, okay? I'm pretty sure that's

correct still in today's day and age, so

we're getting really agilized. No, it's

actually going to be it's going to make

us hopefully have a more organized and

amazing standup, so that the world's

most attended standup, which is our

current standup right now, right now,

just in case you're wondering.

You know, you may not know this, Casey.

There's There is

There's 2,500 people on the stand-up

right now. This is the world's most

attended stand-up.

>> Oh.

>> It's like you couldn't even like it we

previously no one knew if that many

people could even stand at the same

time.

>> Yes. Yes. Yes. Yes. Yes. Yes. Yes. Yes.

Yes. Yes. Yes. Yes. Yes. Yes. Yes. Yes.

Yes. Yes.

>> We shattered records. Okay.

>> Oh, yeah, definitely. What was the

record before? Like 100 people, maybe?

>> Yeah, like 100 to 200, I don't know.

Maximum.

>> Now we're at 2,500 is with world It's

It's world shattering.

>> Yes, totally. It's a game changer.

>> Yeah. I want to add, though, we didn't

get an invite or the topics until this

morning, like 2 hours

>> No, yeah, so this

This stand-up's going to be amazing cuz

cuz Prime's like, uh

we're going to talk about this new Well,

you know what? I won't spoil it, but

let's put it put it this way. It

probably was a topic that would have

been nice to research beforehand if

we're going to talk about it. That's

That's all I'm going to say. I don't

want to spoil anything.

>> I had to listen to Jim listen to YouTube

videos about it. Would have BEEN NICE.

>> [laughter]

>> WELL, YOU KNOW, THAT

>> That makes this authentic, uh Casey. You

get a react to Trash's workout gym

knowledge.

>> Okay.

>> Right. Rather than that, Trash is the

expert. You get Trash back.

>> I am not the expert.

>> Trash is the expert. Trash is the

expert.

>> I was like, "Oh, no."

>> Dude, if there was a trash fact every

episode, that would be That would be

fire.

>> It's It's literally going It's going on

the linear board.

>> I literally have endless lore since

then.

>> Um another thing that I would like to to

uh ask at this point is if we are

serious about this series A, which I

think we should be,

uh is it time for us to start putting

together a pitch deck?

>> Oh, wow.

>> don't know what one of those are, but I

think we need to do that. I think you're

I think you're going to do it.

>> We need some slides.

>> My startup, dailybjj.ai,

is going nuclear.

>> Congratulations on product market fit.

>> Sorry I called you the Diffeler.

>> I knew you weren't the Diffeler. I

always thought it was the intern with

the weird glasses.

>> You should have seen his code.

>> But anyways, if you want to get in the

ground floor of this thing, we're taking

angel investments.

>> [laughter]

>> So, you finally cracked the case, Merge

Cop.

>> You put the white space in the diff. You

made the synthetic traffic.

You made me approve that PR. You're the

diffler. I ALWAYS KNEW IT.

>> [screaming]

[laughter]

>> YOU'VE MERGED YOUR LAST PR, DIFFLER.

>> I already clicked merge on my PR 35

seconds ago.

>> Huh?

>> My merge is blocked.

CURSE YOU, CODE RABBIT.

>> YOU SAVED THE CITY from a code

review-related crime.

>> Thanks, Commish.

>> Well, technically, it was Code Rabbit

that saved the day. Not only do they

have advanced AI features that can

detect security vulnerabilities, like

what the diffler was trying to merge,

they also have ways to enforce styling,

[music] linting, and a variety of other

tools. And so, you can stop wasting time

reviewing code that humans don't need to

review.

>> You can try it yourself at

coderabbit.ai.

>> So, Merge Cop, I would say it's a little

misleading to say you did it all by

yourself.

>> Huh. Would you like some cake?

>> Oh, sure. Thanks.

>> All right. So, Casey, I saw this tweet

and I figured you could maybe give me

like a little I think I understand the

purpose here

and what the problem is of it. But, I

thought maybe you could help me a little

bit on this one. This is my blocker, by

the way, for the day. Which is I saw

this where someone said, "Hey, don't use

division. Use reciprocal math instead.

>> Okay.

>> Can you can you can you can you maybe

give us like us dumb [clears throat]

people why this is either good or bad

idea?

>> Oh boy.

I have no idea what that means.

>> Well, right here he's doing array

index I divided by pi versus array index

I multiplied by the reciprocal. So, 1

divided by pi. So, he does the division

thing once and then hits it with a bunch

of multiplications.

>> Yeah. Um

So, there's a lot of things that you

would want to talk about here and that's

I actually saw that tweet that you're

talking about. Yes. And unfortunately

>> your account?

>> [laughter]

>> No. I mean, see here's the here's the

problem, right? So, delete your account.

I love delete your account and I love

what Ryan's doing there.

>> [laughter]

>> But what mostly what he's doing there is

he's just like

and he even described this on one of his

own streams. He's just saying like look,

basically like you guys are all the

people who like come up and and and beg

for change on the street or something.

Like you're just totally making the

world difficult to live in by like

trying to get all of like just just

hounding everyone who goes into a

particular area to try and get them to

give you something, right? Which is your

attention or whatever. They're they're

like these AI shill accounts or

whatever. People trying to get

engagement. They're trying to get

follows, whatever it is, right? And it

just really degrades the experience of

being in that place. That's basically

what he said on like one of his streams.

I'm probably phrasing it poorly. Um I I

think he

>> [laughter]

>> he said I think he said the phrase

"If you go to a third-world country like

France." Was the WAS [laughter]

LITERALLY I THINK the phrase he used.

>> I love Ryan.

>> in that stream. So, I don't know don't

don't blame me. Don't come after me for

this. I'm just repeating what I believe

it was.

Um

>> [laughter]

>> But anyway, the point is just that uh

that was sort of the point of delete

your account. And I And I'm He's right.

Like, there's just all of this kind of,

you know, really bad behavior that's

going on there.

And the uh this tweet I don't really

like being harsh on people who are

trying to talk about performance because

I'm glad that we somehow went, you know,

uh over the past, you know, 10 years or

so to people actually starting to think

that it matters that you're thinking

about how the CPU is going to do things.

So, I don't want to like be mean to

anyone who's at least trying to say

like, "Hey, let's think about what this

is doing." The problem is that it

requires some actual knowledge to like

actually get these things right. And a

lot of times, if you just ask the AI or

if you just read something on a blog and

you then

repeat that, it's not accurate, right?

Because performance is a very specific

thing. It's It's kind of like repairing

a car or something. You can't just know

like one thing about like, "Oh, yeah,

you know, the carburetor or something."

Right? It's like, you have to actually

know how the whole thing works.

Right? [laughter]

>> Carburetor.

>> car is short for. No, me exactly. Like,

I'd use it I'm using that as as an

example. Like Like, I'd just be like,

"Uh the spark plug." Or Right? You know,

it's like, I don't even really know much

beyond like there's a thing that ignites

the gas, right? Then okay, that's it. I

couldn't tell you like is it broken? Is

it working properly? Does it need to be

tuned? What's going on? Right?

>> Spark plugs are for electric cars,

right? Cuz you get it from the battery.

>> I mean, that's There you go. That's Must

be. I mean, clearly.

So, yeah, this particular tweet is not

is not good though because it misleads

people, I think, on a lot of points. I'm

not sure if the person actually tested

this. They've got like seconds listed

there, which is a little weird cuz I

don't The Those numbers um

I I mean, there's there's a lot of

things that could have happened there. I

don't know. So, I don't know the

circumstances of it. But, I just don't

want people to be misled.

When you're looking at a loop like this

both of those loops that are in that

tweet, cuz I remember this. Of course, I

can't read what's on prime screen cuz

Riverside won't let me, but I remember

it fairly well.

You're basically going You're going

through arrays

and it's basically a read-modify-write,

right? It's It's loading a value out of

array. The value is a floating-point

number.

Um loading a floating-point value out of

an array.

It's modifying that floating-point

number and writing it back to the array,

right?

And uh the operation that's being done

on the array, the only difference

between the loops is one of them is

doing a divide, so it's loading,

dividing, and rewriting. And the other

one is loading, multiplying, and

rewriting.

>> Correct.

>> Now, obviously, in math

if you do a uh divide of a number, if

you say, "I'm going to divide by X."

There's no difference between that and

saying I'm going to multiply by one over

X,

right?

>> True.

>> True.

>> That's true in math, meaning in like in

grade school, you write it down. If

someone said, "Oh, you know, A divided

by

What's sorry?

>> Okay. All right. All right. [laughter]

TJ was a math major, so okay, he's

flexing that he knows these things,

okay.

>> Math major, get out of here.

>> Yeah, TJ.

>> This is This is like in in like junior

high, right? You Or earlier probably,

right?

>> Yeah, yeah, totally junior high, yep.

>> Yeah, totally.

>> [laughter]

>> Come on, guys. LIKE SERIOUSLY, LIKE I AM

NOT GOOD AT MATH. I AM NOT GOOD AT MATH.

IF I know this, you know this. Come on.

>> Yes, Casey, this is true. This is true

and and straightforward, yes.

>> Um this is just something people did in

grade school, right? And so uh the idea,

this was certainly true in the old days

um for computing, right? Is Look, if I

have floating point, right? If I have

the ability to use floating-point

numbers. Integers, obviously, if we're

using integers, then you have to do a

lot of much more crazy stuff if you

wanted to divide instead I mean multiply

instead of divide. Go into that cuz

that's a whole 'nother ball game. But if

assuming you're in floating point, then

that means that you could literally just

store the number one over X, whatever

you're going to divide by, and then

multiply by it instead. So if you're

going to do a bunch of multiplies, this

is potentially an attractive option

if dividing is slow, right? So if we

look at divide and we go the dividing's

too slow, we could just do it once and

then multiply if the if the multiply is

faster. Now, it's worth noting that

these are not necessarily the same

operation because in floating point,

right? An actual divide, this divided by

that, right?

May produce a different answer because

you don't know like when you do it an

inversion like that, you're only

capturing part of the answer. Like the

answer might have gone on for quite some

time and you're only getting a smaller

part of it. So you're not doing infinite

precision math and so you also have to

be aware of the fact that this will

change the answer. So you have to you

have to know, right? If that mattered to

you or not when you're doing this. So if

it's just some random thing you're doing

for some UI element or something like

that, then it probably will never

matter. If this is scientific computing,

it could be a very big difference. And

so this is the first thing that I want

to point out is that this is not a thing

you can just tell somebody always invert

your numbers and then multiply because

that may be very bad advice in certain

circumstances. That's thing one that

wasn't mentioned in the tweet that you

have to understand.

>> The butterfly effect.

>> Uh yeah, well, it's yeah, basically

like, you know,

>> Jeff Goldblum with the water going down

his hand effect.

>> It might even just be the

>> Good movie.

>> the the the 1,000 mile butterfly. Like

it's this huge butterfly because it

could be literally it could just be just

literally the answer you get right here

could be wrong enough that you care,

right? Depending on the circumstances

and depending on what those input

numbers were and what their scales were

and all this stuff, right?

>> Casey, can you just I there is a decent

chance a few people in the audience

don't understand why that happens on a

computer.

>> Well, so to be fair, I'm the wrong one

to explain it because I don't work on

scientific computing, right? And people

who work on scientific computing are

much better at analyzing things like,

you know, what's called ULP or basically

like the last what happens to the final

bits

in floating point numbers and things

like that. But in general, when you're

working with floating point on a

computer, what's actually happening

there is that you're taking the size of

the storage that you, you know, made for

those numbers. So let's say that you're

doing 32-bit floating point numbers. In

scientific computing it might be 64-bit

numbers, whatever it is.

If you just have 32 bits, you only have

a certain amount of space to store what

you would prefer was an infinite series.

Like let's say we want to compute with

pi. Right? Everyone knows from grade

school pi is this infinitely long

series. Like there is no storage that

can store pi. It just keeps going.

So we have to approximate that, right?

By putting it into some format. And all

the numbers that we work with in

floating point computing, they have this

kind of format. Just something simple.

>> you for a quick second? Trash, when he

says pi, he's not talking about a snack.

Just in case you're wondering.

>> I don't even like pi, actually. I

actually hate [laughter] pi.

>> Me neither. Trash, yes.

>> There's another reason Trash is the star

of the stand-up. No pi zone.

>> Yeah, that's true.

>> Yeah, what's your favorite pi adjacent

kind of thing? Like is it cake or

brownies or like what is it then?

>> Love brownies.

>> Pi is not adjacent to cake and you'll

take that back. We can We know we just

got to move on cuz that was very

offensive.

>> Okay, that's it. Put that next next

episode.

>> I'm putting it in the backlog. How

adjacent How adjacent [laughter]

is cake to pi?

>> Okay, so

>> anyway, if you if you look at what

happens to these things during all your

computations, every computation that you

do is going to have some infinitely

precise answer that's the answer you

actually wanted and that you will want

you would have wanted to carry through

all of your subsequent operations,

but at every step of the way, the

computer has to like round it basically

to whatever will fit back into that

32-bit encoding. And that 32-bit

encoding is basically, you know, it's a

sign bit that says whether the thing's

positive or negative. It's some number

of bits for the exponent, right? Which

says

>> I think is

the sign.

>> is the next thing.

>> Oh, the next thing. That's right. That's

right.

>> Uh the exponent basically says what the

scale is, like how big roughly is this

number.

And then the mantissa are the bits that

actually say like what the number is.

So, the reason it's called floating

point is because it's broken up into

these pieces.

Floating point, the point is the decimal

point, if you will. The floating part is

that we store an exponent, so we say

where the decimal point is, and then the

mantissa is just the actual digits. So,

we're basically floating the point to

where it needs to go using the exponent,

right? And the reason we do this is

because we're trying to compute with

extremely large and extremely small and

everything in between, and so we can't

just take 32 bits, which has a very

small range if we just use an integer,

right? If we fixed point, if we just

said the decimal point is here, it would

kind of suck. That's what floating

point's for. It's why we use it for

everything that isn't just nice, you

know, typical whole number kinds of

stuff that we're doing, right? You know,

usually when we when we use

uh just answer things like that, just

integer numbers.

>> The common The common one that people

laugh at, right, is it's what 0.2 + 0.1

in JavaScript, and you get the 0.299999,

right? So, it's like this is This is why

that happens, though. So, just I feel

like there's probably a decent amount of

people who are like just haha JavaScript

stupid. I mean, you're right, but like

that's not that's like a right for the

wrong reason JavaScript problem.

Exactly.

>> That works in C, it works in Java, it

works in all of them.

>> Yeah.

>> yeah, JavaScript is weird in that it

kind of only has double precision

arithmetic period. Like it's just like

that's just what we do everywhere, I

think.

>> Yeah, unless you use bitwise operations,

then it converts to a signed 32-bit

number.

>> No, it will just magically at that time

>> one moment you can actually do a you can

actually do a a overflow

at 32 bits.

Only if you use uh bitwise stuff.

>> Again, this is always why JavaScript

compilers are so hard, right? Like cuz

they have to go like, "Oh, I don't you

don't want to do double precision

arithmetic for like your loops and like

counter and things like that." So, it

has to analyze and go, "Okay, I can turn

this into an integer for this code."

Right? It's got to do that work. Normal

languages, it's already knows, right?

It's just been told like this integer

doesn't have to think about that, right?

But anyway, so

that's that's the floating-point math

thing. And that's sort of what this this

uh this snippet was trying to say is

just invert the floating-point number so

you only pay for the divide once, then

multiply by it cuz that'll give you the

same answer. Again, the tweet didn't say

no, it's not quite the same answer, and

it might matter depending on what you're

doing and depending on what the inputs

are.

But anyway, uh the other problem I have

with this is it misrepresents the

performance as well for a number of

reasons.

So, the first reason it mis-

misrepresents the performance is because

it has some weird statements about how

long a division is. So, it said

something like 20 to 40 cycles for a

divide or something like that,

I think.

>> Yes, 20 to 40.

>> And I just have no idea where that's

coming from, right? Like I've no idea

where they got that number from. They

like I really wish it had said where it

got that number from, right?

>> came from his heart, all right?

>> It came from his

>> Yeah.

>> Yeah.

>> He could feel it.

>> He could feel those cycles.

>> The CPU whisperer.

>> Yeah.

>> So, a floating-point divide

um

you know, if you look So, if you look at

a modern chip, like let's say a Zen a

Zen 4 or Zen 5 chip, right? Something

that you might be running today that

might be in a computer you'd buy today.

Typically, their floating point divide

units are extraordinary.

Very fast. I want to say that they can

complete these things in I don't know,

five, six cycles, something like five

cycles, maybe. I'm not sure what it is.

We should probably look it up. But, 40

is no no where to be found. I mean,

that's it's not quite off by 10, but

it's something like 10. Like, it's very

very wrong.

>> I think it's from uh ChatGPT cuz if I'm

not mistaken, I actually asked this

question not too long ago and I got the

answer of like eight to 30 or something

like that cycles for a divide depending

on the CPU and architecture.

>> I mean, the part the part that the

ChatGPT got right is the depending on

the the architecture part cuz it

[laughter] does depend.

>> Okay, okay.

>> Uh but like let's sit here, I'll just

look it up on my machine right now.

Like, we'll just see what roughly it is.

So, if I go in and I say I want to do a,

you know, 32-bit um

uh like we're going to do a div PS here

or a div uh SS, let's say. And we look

at what's going to happen on a Zen 5

chip, um the the total latency, right,

is less than 10 cycles for for that

operation, latency, right?

So, that means that if you

>> about multiply then?

>> Sorry?

>> What what about for multiply?

>> Multiply will be four.

>> Okay.

>> I want to say, right?

Um so, three three on the Zen 5.

>> though, Casey? We just need to know how

many [laughter] FPS's 10 cycles.

>> Right.

>> If it were a bouncing ball

>> Casey, how fast is that ball?

>> [laughter]

>> So, three on that and I think four four

is on my CPU, which is Zen 4. I think it

should be four, right?

Uh is that correct? Zen 4. Also three.

So, all right, this is better than I

would have expected. I'm used to four,

these get three,

right?

Now, so in general,

that is the number that you would use if

you were trying to analyze how long it

takes you to get the answer back, right?

These loops don't care how long it takes

to get the answer back because nothing

is waiting for that, right? On the

iteration of the loop, as you go

through, right?

You're going to do a load,

the floating point op, either divide or

multiply, and then the store,

right?

When you do that, the next iteration of

the loop doesn't have to wait for that

to complete. So, those are just in the

scheduling queue going, they can be

dispatched. The next iteration of the

loop is already decoded and probably

also in the scheduler, given this is a

hot loop, presumably we're just running

about, you know,

>> It's good looking at that. It's good

looking, for sure.

>> It's [laughter] just cooking.

So, these are all going to pile up in

the scheduler, scheduler's going to

dispatch them every cycle as it can.

And so, what we care about is not how

long it takes to get the answer cuz no

one cares.

What we care about is how long will it

take us to issue the next one. So, if we

issue them on this cycle, how long does

it take us to issue the next one, right?

And so, that's what we typically call

that's a throughput number. So, we

typically call that, right?

And if you look at the throughput

numbers for multiply, right?

Typically, you can issue two floating

point multiplies per cycle,

which means it takes half a cycle

effectively to multiply. Half a cycle,

okay?

That is what you That is the number you

should be listing or thinking about when

you're looking at this loop.

For divides, the throughput again is

remarkably good on modern CPUs, so it's

like in the two to three range.

So, is multiply faster than divide?

Sure, right? Half a cycle versus three

cycles when we're analyzing this loop,

let's say, or something along those

lines.

But then you have to ask the question,

do you care?

This is a load

a op

and a store.

Unless you're entirely out of the L1

cache, which is going to service, you

know, at about, you know, like let's

say,

uh one, you know,

it's probably like two per cycle, three

per cycle, it could get you answers back

from the L1 cache, right?

If you're talking about the L2 cache,

then, I mean,

I don't know, the number of clocks it's

probably going to take 14 cycle latency,

something like this.

If we're looking at how long it takes

you to actually get the memory back,

it's not clear to me that unless the

unless the CPU was predicting extremely

well what you were going to do and

always had things, like you'd have to go

look at the actual bandwidth to see if

you were actually going to get enough

back such that you could operate them on

them at that speed. Maybe you can.

It's it's not in my brain right now as

to whether you would actually be able to

do that at a speed that would matter at

the like, let's say, three cycles, uh

throughput number that you're going to

get on the divide.

So, it really just it was very

misleading, the whole thing, and

as I you know, you heard me say all that

stuff,

I would want to go look at this loop and

and check it first, and I'd want to

think about it a little bit before I

would post anything like that, and it

was just that clearly wasn't done.

Because the none of those numbers make

sense that are placed there. Is it true

that multiply is faster than divide?

Yes.

Does it even matter in this case? No. I

don't think it probably does, but maybe.

And furthermore, usually, in most cases,

right?

When you're looking at actual loops,

more is going on.

And so, it's also going to mislead

people. So, point number three, it's

also going to mislead people in this

final way, which is to think that they

always have to do this. It's the This is

the problem with these kind of like out

of context performance things. People

read it, they think, "Oh, I just need to

invert all my numbers, and then my code

goes fast." And then they go around

inverting all of their numbers and

turning them into multiplies. And the

problem with that is in a lot unless you

were unless you had serial dependency

chains that really could have been

unblocked by this change,

you're just wasting your time. The

divide would have been just as fast. It

would have overlapped with other things

you're doing in the loop. You were

The thing was waiting on a on an

uncashed read or something, so the whole

loop was was waiting 80 cycles anyway,

so none of this mattered, right? So, the

problem again is that like performance

is a thing, performance is a process.

It's an understanding. You have to

understand all those things that I just

said. They're not actually that hard to

understand. You just You can't You just

need to learn them. You need to spend a

few weeks learning this stuff. And then

you can think about do I need to invert

this number? Do I not need to invert it

at that point. What you don't want to do

is try to package it into a tweet like

that when you haven't really done the

work of understanding why it matters or

anything like that because other people

will take away the wrong lessons. So,

that was a very long-winded way of

trying to explain everything I didn't

like about that tweet. Again, no

offense. Sorry to the person who posted

it. It's just I don't think that kind of

thing is helpful. It's sort of like

saying always call memset or never call

memset or these other weird performance

things that people pass around, which

out of context don't help anybody

because you're just going to make

incorrect decisions if you think that

the key to performance is always do X or

never do X. That's not how it works.

Spark plugs.

>> Great job, Casey. Thank you.

>> I did my best.

>> I figured you'd be able to help me on

that one because I had the rough idea

that it would introduce error, but I had

no idea to the extent that divide and

multiply may not make any sort of actual

real difference in your program.

Plus all the crappy things I do anyways

probably destroy my program's

performance long [laughter] before we

get to this loop.

>> Yeah, Prime, we've got other issues

before we get to whether we're

multiplying or dividing, I think. Yeah.

>> I just really want to take my Lua

program seriously, TJ, okay?

>> [laughter]

>> It's It's usually I'll The one thing I

can put in someone's head that's

generally not wrong is

Don't confuse integer multiply with

floating-point multiply. Floating-point

multiplies are much faster than integer

multiplies typically. And so some of the

time when you see people saying, "Oh my

god, in like divide is so bad."

Sometimes they're thinking about integer

divide. And there's a lot of reasons

There are a lot of reasons why integer

divide is bad. A lot of reasons.

>> to put that on the block list for next

week. You can We can We can talk about

that cuz that's actually a

That seems very interesting.

>> Hey guys, if you like this episode, you

can watch the rest of it on Spotify.

And don't forget to like AND SUBSCRIBE.

WOO!

SEE YOU LATER.

>> [singing]

>> Five code errors on my screen. [music]

Terminal coffee

Living the

dream.