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+WEBVTT
+
+
+00:00:00.000 --> 00:01:40.719
+Introduction
+
+00:01:40.720 --> 00:02:23.599
+What is an LLM?
+
+00:02:23.600 --> 00:05:11.700
+Using this library
+
+00:05:11.701 --> 00:08:00.159
+Further instructions
+
+00:08:00.160 --> 00:09:33.480
+Room for improvement
diff --git a/2023/captions/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.vtt b/2023/captions/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.vtt
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+WEBVTT captioned by sachac, checked by sachac
+
+NOTE Introduction
+
+00:00:00.000 --> 00:00:03.039
+Hi, my name is Abhinav and I'm going to talk about
+
+00:00:03.040 --> 00:00:06.199
+this tool that I've been working on called MatplotLLM.
+
+00:00:06.200 --> 00:00:09.519
+MatplotLLM is a natural language interface
+
+00:00:09.520 --> 00:00:12.479
+over matplotlib, which is a library I use a lot
+
+00:00:12.480 --> 00:00:14.439
+for making visualizations.
+
+00:00:14.440 --> 00:00:18.679
+It's a pretty common Python library used a lot everywhere
+
+00:00:18.680 --> 00:00:22.479
+where there's need of plotting and graphing.
+
+00:00:22.480 --> 00:00:25.359
+I usually use it in reports.
+
+00:00:25.360 --> 00:00:27.359
+Whenever I'm writing a report in org mode,
+
+00:00:27.360 --> 00:00:31.559
+I tend to write a code block which is in Python.
+
+00:00:31.560 --> 00:00:34.079
+And then that code block has usage of matplotlib
+
+00:00:34.080 --> 00:00:35.999
+to produce some reports.
+
+00:00:36.000 --> 00:00:38.319
+That works really well.
+
+00:00:38.320 --> 00:00:39.999
+But at times what happens is
+
+00:00:40.000 --> 00:00:43.959
+I have to make a very custom graph, let's say.
+
+00:00:43.960 --> 00:00:46.919
+And then while I'm writing a report,
+
+00:00:46.920 --> 00:00:50.679
+it's kind of a huge leap of abstraction
+
+00:00:50.680 --> 00:00:51.519
+when I'm working on text
+
+00:00:51.520 --> 00:00:54.879
+versus going into actual low-level matplotlib code
+
+00:00:54.880 --> 00:00:56.239
+to do that graphing.
+
+00:00:56.240 --> 00:00:59.679
+So that's something I don't want to do.
+
+00:00:59.680 --> 00:01:00.479
+Here's an example.
+
+00:01:00.480 --> 00:01:03.999
+This is a graph which is... I think it was made
+
+00:01:04.000 --> 00:01:05.839
+like five or six years back.
+
+00:01:05.840 --> 00:01:08.399
+And then there are some common things
+
+00:01:08.400 --> 00:01:09.959
+like scatter plot here,
+
+00:01:09.960 --> 00:01:12.239
+the dots that you can see here scattered.
+
+00:01:12.240 --> 00:01:16.279
+Then... But there are a few things which, to do them,
+
+00:01:16.280 --> 00:01:19.159
+to make them, you will actually have to go--at least me,
+
+00:01:19.160 --> 00:01:20.839
+I have to go to the documentation
+
+00:01:20.840 --> 00:01:24.119
+and figure out how to do it. Which is fine,
+
+00:01:24.120 --> 00:01:26.519
+but I don't want to do this, you know,
+
+00:01:26.520 --> 00:01:29.199
+spend so much time here, when I'm working on
+
+00:01:29.200 --> 00:01:32.319
+a tight deadline for a report.
+
+00:01:32.320 --> 00:01:33.919
+That's the motivation for this tool.
+
+00:01:33.920 --> 00:01:35.199
+This tool basically allows me
+
+00:01:35.200 --> 00:01:38.479
+to get rid of the complexity of the library
+
+00:01:38.480 --> 00:01:40.719
+by working via an LLM.
+
+NOTE What is an LLM?
+
+00:01:40.720 --> 00:01:43.399
+So an LLM is a large language model.
+
+00:01:43.400 --> 00:01:45.079
+These are models which are
+
+00:01:45.080 --> 00:01:49.399
+trained to produce text, generate text.
+
+00:01:49.400 --> 00:01:51.519
+And just by doing that,
+
+00:01:51.520 --> 00:01:55.079
+they actually end up learning a lot of common patterns.
+
+00:01:55.080 --> 00:01:56.799
+For example, if you ask a question,
+
+00:01:56.800 --> 00:01:58.919
+you can actually get a reasonable response.
+
+00:01:58.920 --> 00:02:00.759
+If you ask to write a code for something,
+
+00:02:00.760 --> 00:02:01.879
+you'll actually get code
+
+00:02:01.880 --> 00:02:04.759
+which can also be very reasonable.
+
+00:02:04.760 --> 00:02:06.599
+So this tool is basically a wrapper
+
+00:02:06.600 --> 00:02:10.999
+that uses an LLM. For the current version,
+
+00:02:11.000 --> 00:02:13.919
+we use GPT-4, which is OpenAI's model.
+
+00:02:13.920 --> 00:02:17.919
+It's not open in the sense of open source.
+
+00:02:17.920 --> 00:02:21.119
+So that's a problem that it has.
+
+00:02:21.120 --> 00:02:23.599
+But for this version, we are going to use that.
+
+NOTE Using this library
+
+00:02:23.600 --> 00:02:25.479
+Using this library is pretty simple.
+
+00:02:25.480 --> 00:02:27.399
+You basically require the library
+
+00:02:27.400 --> 00:02:30.719
+and then you set up your OpenAI API key here.
+
+00:02:30.720 --> 00:02:33.359
+Then you get a code block
+
+00:02:33.360 --> 00:02:35.759
+where you can specify the language as `matplotllm`.
+
+00:02:35.760 --> 00:02:38.279
+And then what you can do is,
+
+00:02:38.280 --> 00:02:40.799
+you can basically describe what you want
+
+00:02:40.800 --> 00:02:41.799
+in natural language.
+
+00:02:41.800 --> 00:02:45.279
+I'll take this example of this data set.
+
+00:02:45.280 --> 00:02:48.599
+It's called the Health and Wealth of Nations.
+
+00:02:48.600 --> 00:02:49.639
+I think that was
+
+00:02:49.640 --> 00:02:51.399
+the name of a visualization where it was used.
+
+00:02:51.400 --> 00:02:53.399
+This is basically life expectancy,
+
+00:02:53.400 --> 00:02:59.279
+GDP of various countries starting from 1800.
+
+00:02:59.280 --> 00:03:02.719
+I think it goes up to 2000 somewhere.
+
+00:03:02.720 --> 00:03:07.479
+So earlier, I would try to write code which reads this CSV
+
+00:03:07.480 --> 00:03:09.839
+and then does a lot of matplotlib stuff
+
+00:03:09.840 --> 00:03:11.679
+and then finally produces a graph.
+
+00:03:11.680 --> 00:03:13.879
+But with this tool, what I'll do is
+
+00:03:13.880 --> 00:03:17.679
+I'll just provide instructions in two forms.
+
+00:03:17.680 --> 00:03:18.879
+So the first thing I'll do is
+
+00:03:18.880 --> 00:03:21.359
+I'll just describe how the data looks like.
+
+00:03:21.360 --> 00:03:29.039
+So I'll say data is in a file called `data.csv`,
+
+00:03:29.040 --> 00:03:33.159
+which is this file, by the way, on the right.
+
+00:03:33.160 --> 00:03:39.799
+It looks like the following.
+
+00:03:39.800 --> 00:03:44.359
+I just pasted a few lines from the top, which is enough.
+
+00:03:44.360 --> 00:03:47.119
+Since it's a CSV, there's already a structure to it.
+
+00:03:47.120 --> 00:03:50.079
+But let's say if you have a log file
+
+00:03:50.080 --> 00:03:53.759
+where there's more complexities to be parsed and all,
+
+00:03:53.760 --> 00:03:55.039
+that also works out really well.
+
+00:03:55.040 --> 00:03:58.079
+You just have to describe how the data looks like
+
+00:03:58.080 --> 00:04:01.159
+and the system will figure out how to work with this.
+
+00:04:01.160 --> 00:04:06.404
+Now, let's do the plotting. So what I can do is...
+
+00:04:06.405 --> 00:04:09.559
+Let's start from a very basic plot
+
+00:04:09.560 --> 00:04:11.620
+between life expectancy and GDP per capita.
+
+00:04:11.621 --> 00:04:13.800
+I'll just do this.
+
+00:04:13.801 --> 00:04:17.280
+"Can you make a scatter plot
+
+00:04:17.281 --> 00:04:26.399
+for life expectancy and GDP per capita?"
+
+00:04:26.400 --> 00:04:29.639
+Now, you can see there are some typos,
+
+00:04:29.640 --> 00:04:31.719
+and probably there will be some grammatical mistakes
+
+00:04:31.720 --> 00:04:32.919
+also coming through.
+
+00:04:32.920 --> 00:04:37.119
+But that's all OK, because the models are supposed to
+
+00:04:37.120 --> 00:04:40.559
+handle those kinds of situations really well.
+
+00:04:40.560 --> 00:04:43.239
+So I send the request to the model.
+
+00:04:43.240 --> 00:04:47.119
+Since it's a large model--GPT-4 is really large--
+
+00:04:47.120 --> 00:04:50.519
+it actually takes a lot of time to get the response back.
+
+00:04:50.520 --> 00:04:53.359
+So this specific response took 17 seconds,
+
+00:04:53.360 --> 00:04:54.239
+which is huge.
+
+00:04:54.240 --> 00:04:57.439
+It's not something you would expect
+
+00:04:57.440 --> 00:04:59.599
+in a local file running on a computer.
+
+00:04:59.600 --> 00:05:01.879
+But I've got what I wanted. Right.
+
+00:05:01.880 --> 00:05:04.119
+So there's a scatter plot here, as you can see below,
+
+00:05:04.120 --> 00:05:08.879
+which is plotting what I specified it to do,
+
+00:05:08.880 --> 00:05:11.700
+though it looks a little dense.
+
+NOTE Further instructions
+
+00:05:11.701 --> 00:05:12.640
+What I can do is
+
+00:05:12.641 --> 00:05:16.000
+I can provide further instructions as feedback.
+
+00:05:16.001 --> 00:05:18.400
+I try to feed back on this. So I can say,
+
+00:05:18.401 --> 00:05:30.599
+"Can you only show points where year is the multiple of 50?"
+
+00:05:30.600 --> 00:05:33.519
+So since it's starting from 1800, the data points,
+
+00:05:33.520 --> 00:05:34.719
+there are too many years,
+
+00:05:34.720 --> 00:05:37.239
+so I'll just try to thin them down a little.
+
+00:05:37.240 --> 00:05:40.199
+Now what's happening in the background
+
+00:05:40.200 --> 00:05:42.719
+is that everything below this last instruction
+
+00:05:42.720 --> 00:05:45.719
+is going out as the context to the model
+
+00:05:45.720 --> 00:05:47.399
+along with the code that it wrote till now.
+
+00:05:47.400 --> 00:05:50.079
+And then this instruction is added on top of it
+
+00:05:50.080 --> 00:05:53.079
+so that it basically modifies the code to make it work
+
+00:05:53.080 --> 00:05:55.079
+according to this instruction.
+
+00:05:55.080 --> 00:05:58.439
+As you can see now, the data points are much fewer.
+
+00:05:58.440 --> 00:06:01.519
+This is what I wanted also.
+
+00:06:01.520 --> 00:06:02.799
+Let's also do a few more things.
+
+00:06:02.800 --> 00:06:05.439
+I want to see the progression through time.
+
+00:06:05.440 --> 00:06:13.079
+So maybe I'll do something like, color more recent years
+
+00:06:13.080 --> 00:06:15.439
+with a darker shade of...
+
+00:06:15.440 --> 00:06:21.719
+Let's change the color map also.
+
+00:06:21.720 --> 00:06:24.159
+Now, this again goes back to the model.
+
+00:06:24.160 --> 00:06:26.799
+Again, everything below before this line
+
+00:06:26.800 --> 00:06:29.119
+is the context along with the current code,
+
+00:06:29.120 --> 00:06:31.799
+and then this instruction is going to the model
+
+00:06:31.800 --> 00:06:37.039
+to make the changes. So now this should happen, I guess.
+
+00:06:37.040 --> 00:06:41.319
+Once this happens. Yeah. So. OK.
+
+00:06:41.320 --> 00:06:44.599
+So we have this new color map,
+
+00:06:44.600 --> 00:06:46.599
+and there's also this change of color.
+
+00:06:46.600 --> 00:06:51.719
+And also there's this range of color from 1800 to 2000,
+
+00:06:51.720 --> 00:06:53.399
+which is a nice addition.
+
+00:06:53.400 --> 00:06:55.839
+Kind of smart. I didn't expect...
+
+00:06:55.840 --> 00:06:58.959
+I didn't exactly ask for it, but it's nice.
+
+00:06:58.960 --> 00:07:00.959
+So there's a couple more things.
+
+00:07:00.960 --> 00:07:07.759
+Let's make it more minimal. "Let's make it more minimal.
+
+00:07:07.760 --> 00:07:17.319
+Can you remove the bounding box?"
+
+00:07:17.320 --> 00:07:21.399
+Also, let's annotate a few points.
+
+00:07:21.400 --> 00:07:23.719
+So I want to annotate the point
+
+00:07:23.720 --> 00:07:25.839
+which has the highest GDP per capita.
+
+00:07:25.840 --> 00:07:33.599
+"Also annotate the point with highest GDP per capita
+
+00:07:33.600 --> 00:07:36.999
+with the country and year."
+
+00:07:37.000 --> 00:07:41.599
+So again, forget about the grammar.
+
+00:07:41.600 --> 00:07:43.599
+The language model works out well.
+
+00:07:43.600 --> 00:07:46.159
+Usually it takes care of
+
+00:07:46.160 --> 00:07:47.439
+all those complexities for you.
+
+00:07:47.440 --> 00:07:53.119
+This is what we have got after that.
+
+00:07:53.120 --> 00:07:55.719
+As you can see, there's the annotation, which is here.
+
+00:07:55.720 --> 00:07:56.679
+I think it's still overlapping,
+
+00:07:56.680 --> 00:07:58.559
+so probably it could be done better,
+
+00:07:58.560 --> 00:08:00.159
+but the box is removed.
+
+NOTE Room for improvement
+
+00:08:00.160 --> 00:08:03.359
+Now, as you can see, the system is...
+
+00:08:03.360 --> 00:08:04.879
+You will be able to see this
+
+00:08:04.880 --> 00:08:07.479
+that the system is not really robust.
+
+00:08:07.480 --> 00:08:10.079
+So the GitHub repository has some examples
+
+00:08:10.080 --> 00:08:12.119
+where it fails miserably,
+
+00:08:12.120 --> 00:08:13.679
+and you'll actually have to go into the code
+
+00:08:13.680 --> 00:08:14.999
+to figure out what's happening.
+
+00:08:15.000 --> 00:08:17.879
+But we do expect that to improve slowly,
+
+00:08:17.880 --> 00:08:21.039
+because the models are improving greatly in performance.
+
+00:08:21.040 --> 00:08:22.479
+This is a very general model.
+
+00:08:22.480 --> 00:08:24.479
+This is not even tuned for this use case.
+
+00:08:24.480 --> 00:08:26.639
+The other thing is that
+
+00:08:26.640 --> 00:08:29.639
+while I was trying to provide feedback,
+
+00:08:29.640 --> 00:08:32.199
+I was still using text here all the time,
+
+00:08:32.200 --> 00:08:34.559
+but it can be made more natural.
+
+00:08:34.560 --> 00:08:36.159
+So, for example, if I have to annotate
+
+00:08:36.160 --> 00:08:37.439
+this particular point,
+
+00:08:37.440 --> 00:08:42.239
+I actually can just point my cursor to it.
+
+00:08:42.240 --> 00:08:44.519
+Emacs has a way to figure out
+
+00:08:44.520 --> 00:08:45.799
+where your mouse pointer is.
+
+00:08:45.800 --> 00:08:49.620
+And with that, you can actually go back into the code
+
+00:08:49.621 --> 00:08:51.960
+and then see which primitive
+
+00:08:51.961 --> 00:08:54.480
+is being drawn here in Matplotlib.
+
+00:08:54.481 --> 00:08:55.719
+So that there is a way to do that.
+
+00:08:55.720 --> 00:08:58.439
+And then, if you do that, then it's really nice to
+
+00:08:58.440 --> 00:09:01.319
+just be able to say
+
+00:09:01.320 --> 00:09:04.279
+put your cursor here and then say something like,
+
+00:09:04.280 --> 00:09:04.999
+"Can you make this?
+
+00:09:05.000 --> 00:09:06.599
+Can you annotate this point?"
+
+00:09:06.600 --> 00:09:10.719
+Because text is, you know... There are limitations to text.
+
+00:09:10.720 --> 00:09:12.479
+And if you're producing an image,
+
+00:09:12.480 --> 00:09:13.959
+you should be able to do that, too.
+
+00:09:13.960 --> 00:09:16.399
+So I do expect that to happen soonish.
+
+00:09:16.400 --> 00:09:19.839
+If not, from the model side, the hack that I mentioned
+
+00:09:19.840 --> 00:09:21.359
+could be made to work.
+
+00:09:21.360 --> 00:09:24.439
+So that will come in in a later version, probably.
+
+00:09:24.440 --> 00:09:27.599
+Anyway, so that's the end of my talk.
+
+00:09:27.600 --> 00:09:29.759
+You can find more details in the repository link.
+
+00:09:29.760 --> 00:09:33.480
+Thank you for listening. Goodbye.
diff --git a/2023/info/matplotllm-after.md b/2023/info/matplotllm-after.md
index b418580f..6b2ebde4 100644
--- a/2023/info/matplotllm-after.md
+++ b/2023/info/matplotllm-after.md
@@ -1,6 +1,211 @@
 <!-- Automatically generated by emacsconf-publish-after-page -->
 
 
+<a name="matplotllm-mainVideo-transcript"></a>
+# Transcript
+
+[[!template new="1" text="""Hi, my name is Abhinav and I'm going to talk about""" start="00:00:00.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""this tool that I've been working on called MatplotLLM.""" start="00:00:03.040" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""MatplotLLM is a natural language interface""" start="00:00:06.200" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""over matplotlib, which is a library I use a lot""" start="00:00:09.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""for making visualizations.""" start="00:00:12.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""It's a pretty common Python library used a lot everywhere""" start="00:00:14.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""where there's need of plotting and graphing.""" start="00:00:18.680" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I usually use it in reports.""" start="00:00:22.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Whenever I'm writing a report in org mode,""" start="00:00:25.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I tend to write a code block which is in Python.""" start="00:00:27.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And then that code block has usage of matplotlib""" start="00:00:31.560" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""to produce some reports.""" start="00:00:34.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""That works really well.""" start="00:00:36.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""But at times what happens is""" start="00:00:38.320" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I have to make a very custom graph, let's say.""" start="00:00:40.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And then while I'm writing a report,""" start="00:00:43.960" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""it's kind of a huge leap of abstraction""" start="00:00:46.920" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""when I'm working on text""" start="00:00:50.680" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""versus going into actual low-level matplotlib code""" start="00:00:51.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""to do that graphing.""" start="00:00:54.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So that's something I don't want to do.""" start="00:00:56.240" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Here's an example.""" start="00:00:59.680" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""This is a graph which is... I think it was made""" start="00:01:00.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""like five or six years back.""" start="00:01:04.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And then there are some common things""" start="00:01:05.840" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""like scatter plot here,""" start="00:01:08.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""the dots that you can see here scattered.""" start="00:01:09.960" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Then... But there are a few things which, to do them,""" start="00:01:12.240" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""to make them, you will actually have to go--at least me,""" start="00:01:16.280" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I have to go to the documentation""" start="00:01:19.160" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and figure out how to do it. Which is fine,""" start="00:01:20.840" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""but I don't want to do this, you know,""" start="00:01:24.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""spend so much time here, when I'm working on""" start="00:01:26.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""a tight deadline for a report.""" start="00:01:29.200" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""That's the motivation for this tool.""" start="00:01:32.320" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""This tool basically allows me""" start="00:01:33.920" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""to get rid of the complexity of the library""" start="00:01:35.200" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""by working via an LLM.""" start="00:01:38.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template new="1" text="""So an LLM is a large language model.""" start="00:01:40.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""These are models which are""" start="00:01:43.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""trained to produce text, generate text.""" start="00:01:45.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And just by doing that,""" start="00:01:49.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""they actually end up learning a lot of common patterns.""" start="00:01:51.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""For example, if you ask a question,""" start="00:01:55.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""you can actually get a reasonable response.""" start="00:01:56.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""If you ask to write a code for something,""" start="00:01:58.920" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""you'll actually get code""" start="00:02:00.760" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""which can also be very reasonable.""" start="00:02:01.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So this tool is basically a wrapper""" start="00:02:04.760" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""that uses an LLM. For the current version,""" start="00:02:06.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""we use GPT-4, which is OpenAI's model.""" start="00:02:11.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""It's not open in the sense of open source.""" start="00:02:13.920" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So that's a problem that it has.""" start="00:02:17.920" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""But for this version, we are going to use that.""" start="00:02:21.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template new="1" text="""Using this library is pretty simple.""" start="00:02:23.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""You basically require the library""" start="00:02:25.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and then you set up your OpenAI API key here.""" start="00:02:27.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Then you get a code block""" start="00:02:30.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""where you can specify the language as `matplotllm`.""" start="00:02:33.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And then what you can do is,""" start="00:02:35.760" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""you can basically describe what you want""" start="00:02:38.280" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""in natural language.""" start="00:02:40.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I'll take this example of this data set.""" start="00:02:41.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""It's called the Health and Wealth of Nations.""" start="00:02:45.280" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I think that was""" start="00:02:48.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""the name of a visualization where it was used.""" start="00:02:49.640" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""This is basically life expectancy,""" start="00:02:51.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""GDP of various countries starting from 1800.""" start="00:02:53.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I think it goes up to 2000 somewhere.""" start="00:02:59.280" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So earlier, I would try to write code which reads this CSV""" start="00:03:02.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and then does a lot of matplotlib stuff""" start="00:03:07.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and then finally produces a graph.""" start="00:03:09.840" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""But with this tool, what I'll do is""" start="00:03:11.680" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I'll just provide instructions in two forms.""" start="00:03:13.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So the first thing I'll do is""" start="00:03:17.680" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I'll just describe how the data looks like.""" start="00:03:18.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So I'll say data is in a file called `data.csv`,""" start="00:03:21.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""which is this file, by the way, on the right.""" start="00:03:29.040" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""It looks like the following.""" start="00:03:33.160" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I just pasted a few lines from the top, which is enough.""" start="00:03:39.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Since it's a CSV, there's already a structure to it.""" start="00:03:44.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""But let's say if you have a log file""" start="00:03:47.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""where there's more complexities to be parsed and all,""" start="00:03:50.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""that also works out really well.""" start="00:03:53.760" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""You just have to describe how the data looks like""" start="00:03:55.040" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and the system will figure out how to work with this.""" start="00:03:58.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Now, let's do the plotting. So what I can do is...""" start="00:04:01.160" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Let's start from a very basic plot""" start="00:04:06.405" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""between life expectancy and GDP per capita.""" start="00:04:09.560" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I'll just do this.""" start="00:04:11.621" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""&quot;Can you make a scatter plot""" start="00:04:13.801" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""for life expectancy and GDP per capita?&quot;""" start="00:04:17.281" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Now, you can see there are some typos,""" start="00:04:26.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and probably there will be some grammatical mistakes""" start="00:04:29.640" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""also coming through.""" start="00:04:31.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""But that's all OK, because the models are supposed to""" start="00:04:32.920" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""handle those kinds of situations really well.""" start="00:04:37.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So I send the request to the model.""" start="00:04:40.560" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Since it's a large model--GPT-4 is really large--""" start="00:04:43.240" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""it actually takes a lot of time to get the response back.""" start="00:04:47.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So this specific response took 17 seconds,""" start="00:04:50.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""which is huge.""" start="00:04:53.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""It's not something you would expect""" start="00:04:54.240" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""in a local file running on a computer.""" start="00:04:57.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""But I've got what I wanted. Right.""" start="00:04:59.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So there's a scatter plot here, as you can see below,""" start="00:05:01.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""which is plotting what I specified it to do,""" start="00:05:04.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""though it looks a little dense.""" start="00:05:08.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template new="1" text="""What I can do is""" start="00:05:11.701" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I can provide further instructions as feedback.""" start="00:05:12.641" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I try to feed back on this. So I can say,""" start="00:05:16.001" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""&quot;Can you only show points where year is the multiple of 50?&quot;""" start="00:05:18.401" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So since it's starting from 1800, the data points,""" start="00:05:30.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""there are too many years,""" start="00:05:33.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""so I'll just try to thin them down a little.""" start="00:05:34.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Now what's happening in the background""" start="00:05:37.240" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""is that everything below this last instruction""" start="00:05:40.200" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""is going out as the context to the model""" start="00:05:42.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""along with the code that it wrote till now.""" start="00:05:45.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And then this instruction is added on top of it""" start="00:05:47.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""so that it basically modifies the code to make it work""" start="00:05:50.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""according to this instruction.""" start="00:05:53.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""As you can see now, the data points are much fewer.""" start="00:05:55.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""This is what I wanted also.""" start="00:05:58.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Let's also do a few more things.""" start="00:06:01.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I want to see the progression through time.""" start="00:06:02.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So maybe I'll do something like, color more recent years""" start="00:06:05.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""with a darker shade of...""" start="00:06:13.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Let's change the color map also.""" start="00:06:15.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Now, this again goes back to the model.""" start="00:06:21.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Again, everything below before this line""" start="00:06:24.160" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""is the context along with the current code,""" start="00:06:26.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and then this instruction is going to the model""" start="00:06:29.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""to make the changes. So now this should happen, I guess.""" start="00:06:31.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Once this happens. Yeah. So. OK.""" start="00:06:37.040" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So we have this new color map,""" start="00:06:41.320" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and there's also this change of color.""" start="00:06:44.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And also there's this range of color from 1800 to 2000,""" start="00:06:46.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""which is a nice addition.""" start="00:06:51.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Kind of smart. I didn't expect...""" start="00:06:53.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I didn't exactly ask for it, but it's nice.""" start="00:06:55.840" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So there's a couple more things.""" start="00:06:58.960" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Let's make it more minimal. &quot;Let's make it more minimal.""" start="00:07:00.960" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Can you remove the bounding box?&quot;""" start="00:07:07.760" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Also, let's annotate a few points.""" start="00:07:17.320" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So I want to annotate the point""" start="00:07:21.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""which has the highest GDP per capita.""" start="00:07:23.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""&quot;Also annotate the point with highest GDP per capita""" start="00:07:25.840" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""with the country and year.&quot;""" start="00:07:33.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So again, forget about the grammar.""" start="00:07:37.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""The language model works out well.""" start="00:07:41.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Usually it takes care of""" start="00:07:43.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""all those complexities for you.""" start="00:07:46.160" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""This is what we have got after that.""" start="00:07:47.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""As you can see, there's the annotation, which is here.""" start="00:07:53.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I think it's still overlapping,""" start="00:07:55.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""so probably it could be done better,""" start="00:07:56.680" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""but the box is removed.""" start="00:07:58.560" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template new="1" text="""Now, as you can see, the system is...""" start="00:08:00.160" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""You will be able to see this""" start="00:08:03.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""that the system is not really robust.""" start="00:08:04.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So the GitHub repository has some examples""" start="00:08:07.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""where it fails miserably,""" start="00:08:10.080" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and you'll actually have to go into the code""" start="00:08:12.120" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""to figure out what's happening.""" start="00:08:13.680" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""But we do expect that to improve slowly,""" start="00:08:15.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""because the models are improving greatly in performance.""" start="00:08:17.880" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""This is a very general model.""" start="00:08:21.040" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""This is not even tuned for this use case.""" start="00:08:22.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""The other thing is that""" start="00:08:24.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""while I was trying to provide feedback,""" start="00:08:26.640" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I was still using text here all the time,""" start="00:08:29.640" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""but it can be made more natural.""" start="00:08:32.200" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So, for example, if I have to annotate""" start="00:08:34.560" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""this particular point,""" start="00:08:36.160" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""I actually can just point my cursor to it.""" start="00:08:37.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Emacs has a way to figure out""" start="00:08:42.240" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""where your mouse pointer is.""" start="00:08:44.520" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And with that, you can actually go back into the code""" start="00:08:45.800" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""and then see which primitive""" start="00:08:49.621" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""is being drawn here in Matplotlib.""" start="00:08:51.961" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So that there is a way to do that.""" start="00:08:54.481" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And then, if you do that, then it's really nice to""" start="00:08:55.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""just be able to say""" start="00:08:58.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""put your cursor here and then say something like,""" start="00:09:01.320" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""&quot;Can you make this?""" start="00:09:04.280" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Can you annotate this point?&quot;""" start="00:09:05.000" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Because text is, you know... There are limitations to text.""" start="00:09:06.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""And if you're producing an image,""" start="00:09:10.720" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""you should be able to do that, too.""" start="00:09:12.480" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So I do expect that to happen soonish.""" start="00:09:13.960" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""If not, from the model side, the hack that I mentioned""" start="00:09:16.400" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""could be made to work.""" start="00:09:19.840" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""So that will come in in a later version, probably.""" start="00:09:21.360" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Anyway, so that's the end of my talk.""" start="00:09:24.440" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""You can find more details in the repository link.""" start="00:09:27.600" video="mainVideo-matplotllm" id="subtitle"]]
+[[!template text="""Thank you for listening. Goodbye.""" start="00:09:29.760" video="mainVideo-matplotllm" id="subtitle"]]
+
+
+
+Captioner: sachac
+
 Questions or comments? Please e-mail [abhinav@lepisma.xyz](mailto:abhinav@lepisma.xyz?subject=Comment%20for%20EmacsConf%202022%20matplotllm%3A%20MatplotLLM%2C%20iterative%20natural%20language%20data%20visualization%20in%20org-babel)
 
 
diff --git a/2023/info/matplotllm-before.md b/2023/info/matplotllm-before.md
index 7e70b0cf..54eb6dab 100644
--- a/2023/info/matplotllm-before.md
+++ b/2023/info/matplotllm-before.md
@@ -8,12 +8,19 @@ The following image shows where the talk is in the schedule for Sat 2023-12-02.
 Format: 10-min talk; Q&A: Etherpad <https://pad.emacsconf.org/2023-matplotllm>
 Etherpad: <https://pad.emacsconf.org/2023-matplotllm>  
 Discuss on IRC: [#emacsconf-dev](https://chat.emacsconf.org/?join=emacsconf,emacsconf-dev)  
-Status: Ready to stream  
+Status: Now playing on the conference livestream  
 <div>Times in different timezones:</div><div class="times" start="2023-12-02T15:00:00Z" end="2023-12-02T15:10:00Z"><div class="conf-time">Saturday, Dec 2 2023, ~10:00 AM - 10:10 AM EST (US/Eastern)</div><div class="others"><div>which is the same as:</div>Saturday, Dec 2 2023, ~9:00 AM - 9:10 AM CST (US/Central)<br />Saturday, Dec 2 2023, ~8:00 AM - 8:10 AM MST (US/Mountain)<br />Saturday, Dec 2 2023, ~7:00 AM - 7:10 AM PST (US/Pacific)<br />Saturday, Dec 2 2023, ~3:00 PM - 3:10 PM UTC <br />Saturday, Dec 2 2023, ~4:00 PM - 4:10 PM CET (Europe/Paris)<br />Saturday, Dec 2 2023, ~5:00 PM - 5:10 PM EET (Europe/Athens)<br />Saturday, Dec 2 2023, ~8:30 PM - 8:40 PM IST (Asia/Kolkata)<br />Saturday, Dec 2 2023, ~11:00 PM - 11:10 PM +08 (Asia/Singapore)<br />Sunday, Dec 3 2023, ~12:00 AM - 12:10 AM JST (Asia/Tokyo)</div></div><div><a href="/2023/watch/dev/">Find out how to watch and participate</a></div>
 
 
 
 
+<div class="vid"><video controls preload="none" id="matplotllm-mainVideo"><source src="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.webm" />captions="""<track label="English" kind="captions" srclang="en" src="/2023/captions/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.vtt" default />"""<track kind="chapters" label="Chapters" src="/2023/captions/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main--chapters.vtt" /><p><em>Your browser does not support the video tag. Please download the video instead.</em></p></video>[[!template id="chapters" vidid="matplotllm-mainVideo" data="""
+00:00.000 Introduction
+01:40.720 What is an LLM?
+02:23.600 Using this library
+05:11.701 Further instructions
+08:00.160 Room for improvement
 
+"""]]<div></div>Duration: 09:34 minutes<div class="files resources"><ul><li><a href="https://pad.emacsconf.org/2023-matplotllm">Open Etherpad</a></li><li><a href="https://pad.emacsconf.org/2023-matplotllm">Open public Q&A</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--final.webm">Download --final.webm (49MB)</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--intro.vtt">Download --intro.vtt</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--intro.webm">Download --intro.webm</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main--chapters.vtt">Download --main--chapters.vtt</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.opus">Download --main.opus (5MB)</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.txt">Download --main.txt</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.vtt">Download --main.vtt</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--main.webm">Download --main.webm (49MB)</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--normalized.opus">Download --normalized.opus (8.3MB)</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--original.webm">Download --original.webm (462MB)</a></li><li><a href="https://media.emacsconf.org/2023/emacsconf-2023-matplotllm--matplotllm-iterative-natural-language-data-visualization-in-orgbabel--abhinav-tushar--reencoded.webm">Download --reencoded.webm (46MB)</a></li><li><a href="https://toobnix.org/w/7bwq1vAqYzY24iEMYAdcB1">View on Toobnix</a></li></ul></div></div>
 # Description
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