WEBVTT

00:00.710 --> 00:03.590
And welcome to week four, day three.

00:03.590 --> 00:09.650
As we are about to embark upon another business project which will add real commercial value.

00:09.680 --> 00:12.260
It's going to be an exciting project.

00:12.260 --> 00:17.450
It's going to be a difficult challenge, and we're going to have, as always, a blast doing it.

00:17.480 --> 00:19.250
Let's get started.

00:19.280 --> 00:25.400
So first of all, just a recap of all the things you can do this time I'm going to let you read it,

00:25.400 --> 00:31.190
but after today you're going to be able to assess models for coding ability and use frontier models

00:31.190 --> 00:36.710
to generate code building a solution that uses Llms for code generation.

00:36.710 --> 00:39.710
And of course, it's going to include a user interface.

00:39.710 --> 00:45.470
It's going to include a lot of the bits and pieces to package it up nicely to be an app.

00:45.920 --> 00:47.810
So a quick reminder of the challenge.

00:47.810 --> 00:53.660
We want to build a tool that can convert Python to C plus plus for performance.

00:53.660 --> 00:57.320
And this time today we're going to do a frontier model solution.

00:57.320 --> 01:04.820
Next time we're going to add open source models as we battle the the frontier closed source versus open

01:04.820 --> 01:07.520
source and see what wins out.

01:08.030 --> 01:12.380
Uh, first, just a quick a quick explanation of what we're going to do.

01:12.380 --> 01:18.710
So we're going to prompt our models with a prompt that explains what we want them to re-implement Python

01:18.710 --> 01:19.550
code and C plus.

01:19.550 --> 01:20.390
Plus.

01:20.420 --> 01:24.320
Um, it's maybe going to be a little bit more wordy than this one, but it'll be along these lines,

01:24.350 --> 01:30.680
uh, trying to convince the model not to do any explanation, just simply to provide the C plus plus

01:30.680 --> 01:31.430
code.

01:31.430 --> 01:37.250
And its objective should be to do whatever it takes to run faster and give the same output.

01:37.250 --> 01:40.040
But otherwise, the world is its oyster.

01:40.070 --> 01:44.120
It can do what it wants, it just has to give the same output.

01:44.150 --> 01:49.190
And this is a bit of code that we'll start with to try out in Python.

01:49.190 --> 01:56.120
Uh, you may know already that there is a series which very slowly converges to a nice number, and

01:56.120 --> 02:05.270
that series is one minus a third plus a fifth, minus a seventh plus a ninth, minus 11th, and so on.

02:05.300 --> 02:06.350
You get the idea.

02:06.380 --> 02:12.950
Uh, if you keep that series going and you multiply the result by four, you gradually converge on pi.

02:12.980 --> 02:14.840
But it takes a very long time.

02:14.960 --> 02:21.890
And so we can run it for the first 100 million iterations, and we will actually get quite close to

02:21.920 --> 02:23.030
pi at that point.

02:23.150 --> 02:28.670
But you'd have to do an awful lot of typing on your calculator to to do 100 million iterations.

02:28.730 --> 02:30.830
Uh, but Python will do it reasonably fast.

02:30.830 --> 02:35.690
But we'll be hoping that C plus plus can do it a whole lot faster, and that Frontier models will help

02:35.690 --> 02:36.410
us get there.

02:36.410 --> 02:37.400
Let's find out.