We won't lie, starting with this video we fall into a refactoring phase, and fix a lot of bugs along the way. You'll see later, there were a few of them even in the sampling kernel. It is kind to point at the particular impact of what we will be doing, as it feels vague in our mind. We can only hope that the way we use GADTs in the new ML library will be of interest.

One significant addition to the language (coming a few vids after this one) will be adding higher ranked types to the language so look forward to that.

Our current status at the time of writing this description is that we've just finished putting the neural (random) player into the Leduc game and are in the process of doing the same for the NL Limit one. After we've done that, we'll actually be capable of training the agents.

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#spiral #functionalprogramming #machinelearning #reinforcementlearning #programming #cpp #programminglanguage #compiler #parallelprogramming #cuda #gpu

Playlist(Staged FP in Spiral):    • Staged Functional Programming In Spiral  
Spiral: https://github.com/mrakgr/The-Spiral-...
Spiral's ML Library: https://github.com/mrakgr/Spiral-s-ML...
Github: https://github.com/mrakgr/

If you have interesting work opportunities and require an expert functional programmer, don't hesitate to get in touch. My email is on my Github profile. Put "Work" as the subject in order to avoid the spam filters.

TOC:

00:00:00 - Start
00:00:02 - Getting the Leduc example to work with the new library
01:00:37 - The frontend for Leduc training
01:19:39 - Opening a bug report for ECharts
02:05:40 - Going with Chart.js
02:26:52 - Adding data to the chart
02:41:01 - Feeling out the design
02:57:42 - The solution to the ECharts tooltip issue
03:21:31 - Making the chart Lit element based on an ECharts chart
04:31:38 - Dealing with numerical inputs in the frontend
05:27:08 - Dealing with font sizes in Shoelace components