davidshapiro_youtube_transcripts / Accelerating Science with AI Quickly Read Every Paper and Get Key Insights in Bulk_transcript.csv
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hey everybody David Shapiro here with,0.659,3.781
another video so it's a really exciting,2.76,5.28
time because research is accelerating,4.44,5.699
um just in the last couple days a whole,8.04,3.66
bunch of interesting papers have come,10.139,5.521
out on archive and um you know I I could,11.7,6.24
read them all myself the the hard way,15.66,4.44
the long way but you know what I'm,17.94,5.759
really lazy and you know how uh Mr Henry,20.1,5.519
Ford he said uh allegedly said I don't,23.699,2.881
know if he actually said this but he,25.619,2.941
said uh give your hardest problems to,26.58,3.42
the laziest Engineers because they'll,28.56,3.24
find an easier way to do it that's me,30.0,3.239
that's why I became an automation,31.8,3.66
engineer uh back in the day I told,33.239,4.081
people like I would rather spend a week,35.46,4.56
building an automation tool that I can,37.32,4.259
then just push the button and for the,40.02,3.359
rest of my life it makes that job easier,41.579,4.381
and guess what that's how I automated a,43.379,5.401
three petabyte environment because why I,45.96,4.86
didn't want to manage it myself okay so,48.78,5.04
uh with the volume of paper that came,50.82,5.16
out because all of these came out Monday,53.82,5.64
so we've got five interesting papers,55.98,5.46
that came out on the same day and this,59.46,4.259
happens pretty much every day lately and,61.44,4.14
it is entirely too much to keep up with,63.719,5.341
so rather than having to read all of,65.58,5.76
these papers every day I wanted a way to,69.06,4.26
digest them so I could quickly just one,71.34,4.98
skim and keep on top of things uh and,73.32,6.06
then also just uh basically make it,76.32,4.92
sustainable or make it operationalized,79.38,3.779
and so what I mean by that is something,81.24,3.48
that you can just fully automate and,83.159,3.981
then just maybe get an email every day,84.72,5.219
or you know have the interns do it or,87.14,4.299
use this as part of your literature,89.939,3.0
review for science because one of the,91.439,2.881
things that I want to do,92.939,4.021
is use this technology to accelerate,94.32,6.06
science as much as possible and uh you,96.96,4.74
know one of the things that I hear from,100.38,3.059
some of my friends in science is that,101.7,3.48
just keeping up with things is getting,103.439,4.441
harder and harder uh at least in these,105.18,5.16
high velocity spaces some places like,107.88,4.08
oceanography they don't change that much,110.34,3.9
they don't change that fast but,111.96,4.26
certainly computer science artificial,114.24,4.32
intelligence uh and that sort of thing,116.22,4.859
cyber security Quantum Computing these,118.56,5.16
things are moving so incredibly fast we,121.079,6.0
need the AI to help us keep up so let me,123.72,6.3
show you what I've done uh let's see,127.079,4.38
where should I start I guess I'll just,130.02,2.88
start with uh some some of the final,131.459,3.481
reports so basically what I do is I just,132.9,4.32
copy paste the text of the thing into,134.94,4.92
here obviously the figures help but,137.22,3.9
language models are already pretty,139.86,2.519
intelligent so they don't even really,141.12,4.44
need the figures and then what I do is I,142.379,5.521
feed it a series of,145.56,5.16
um of questions and it gives me answers,147.9,5.94
and so this basically summarizes it from,150.72,6.42
you know know maybe twenty thousand,153.84,4.979
forty thousand hundred thousand,157.14,3.78
characters down to four thousand,158.819,4.321
characters so we get a compression ratio,160.92,4.92
of at least five to one but also it's,163.14,4.739
often in much simpler language and,165.84,3.42
probably what I'll do is I'll add a,167.879,3.301
second step that will render this as an,169.26,4.14
HTML document maybe I'll do that at the,171.18,3.66
end,173.4,4.8
um but anyways so the idea is I plug in,174.84,5.399
the text if it's if it's a little too,178.2,3.72
long it'll trim it but you know you get,180.239,4.08
the first 22 000 characters of a paper,181.92,5.039
you've got the general gist,184.319,4.14
um and in many cases you actually have,186.959,4.261
the whole paper uh now so I say can you,188.459,4.321
give me a very clear explanation of the,191.22,2.939
core assertions implications and,192.78,3.959
mechanics elucidated in this paper very,194.159,4.741
simple prompt it comes back and says you,196.739,3.661
know yada yada yada the paper explores,198.9,3.54
the concept of continual learning okay,200.4,4.32
cool uh you know so it asks that,202.44,4.86
question and so basically this is a this,204.72,5.34
is a standard chat GPT conversation so,207.3,5.1
this is a way to implement a chain of,210.06,3.36
thinking,212.4,3.419
um but it's really an automated dialogue,213.42,4.62
so imagine that you you have an intern,215.819,4.381
or a research assistant that read the,218.04,3.96
paper and you can ask them a couple,220.2,4.2
questions and you can change this uh on,222.0,5.04
your own by the way very easily so in,224.4,4.68
the code I have it here you can just add,227.04,3.479
whatever questions or change whatever,229.08,3.54
questions you want here and it will be,230.519,4.14
happy to take it and run with with it,232.62,5.16
for you entirely on its own so you,234.659,4.681
change these questions if you want you,237.78,4.26
add more you know depending on the,239.34,4.38
research that you're looking for so,242.04,4.979
let's say for instance you are in a very,243.72,5.46
specific domain maybe you're trying to,247.019,4.5
do this for medical research and you're,249.18,3.9
really just looking for what are the,251.519,5.46
implications for let's say Rejuvenation,253.08,6.119
therapy or regenerative medicine or even,256.979,4.5
a something even more specific maybe,259.199,3.78
you're trying to research a specific,261.479,5.101
kind of cancer or a specific uh any kind,262.979,5.461
of metabolic disorder really,266.58,4.619
so then you can say first you want it to,268.44,3.96
just tell me what are the implications,271.199,3.241
and then you could say okay what are the,272.4,4.26
implications with respect to my,274.44,5.1
particular domain what are the what what,276.66,4.86
is you know what is the what is the,279.54,4.62
impact to my area of research so restate,281.52,4.44
it for me and then you can have it,284.16,4.2
automatically spider a whole bunch of,285.96,3.72
documents so one of the things that I'm,288.36,3.059
going to do with this is that rather,289.68,4.86
than have just one input at a time I'm,291.419,4.5
going to create a folder where you give,294.54,3.06
it you just download the PDFs to,295.919,4.021
directly it'll scrape the PDFs and go,297.6,4.379
through all of them as part of the,299.94,4.68
automated process and it'll whatever the,301.979,4.621
questions that you have it will kind of,304.62,3.6
break it down but anyways,306.6,3.48
so I have a I have a few standard,308.22,3.84
questions can you explain the value of,310.08,3.3
this in basic terms like you're talking,312.06,3.54
to a CEO so what what's the bottom line,313.38,4.68
here and it's really good at explaining,315.6,4.379
things in simple terms so in this case,318.06,4.02
uh this paper says the research is about,319.979,4.201
making code generation models which are,322.08,3.54
tools that help programmers by,324.18,3.66
automating some of their work more,325.62,4.079
adaptable and efficient currently these,327.84,3.66
models need to be retrained every time,329.699,3.121
there's a significant change to the,331.5,3.419
programming languages or libraries they,332.82,3.48
work with which this is what some people,334.919,3.661
are noticing and I notice this too is,336.3,4.26
that sometimes it'll program with an,338.58,4.38
outdated version which of course limits,340.56,4.8
the utility of coding models,342.96,4.019
the bottom line is that this research,345.36,2.76
could lead to more efficient and,346.979,3.0
adaptable code generation models this,348.12,3.24
means less time and money spent on,349.979,2.641
retraining these models and more,351.36,2.52
up-to-date and effective tools for,352.62,3.419
programmers so the implication for this,353.88,3.9
just reading that one paragraph to me,356.039,3.72
says okay cool this is going to be part,357.78,4.919
of the acceleration because if we come,359.759,5.581
up with a way to make coding models uh,362.699,4.741
updated they're updatable you know using,365.34,4.799
continuous learning great excellent and,367.44,4.199
then I said can you give me an analogy,370.139,2.521
or metaphor that will help me explain,371.639,2.761
this to a broad audience why because I'm,372.66,4.92
a YouTuber right so the basically what I,374.4,5.46
want is to be able to explain this paper,377.58,5.88
in real basic terms real fast and,379.86,5.7
contrary to the belief about a year ago,383.46,3.78
language models are actually really good,385.56,3.9
at analogy and metaphor,387.24,3.36
um so it says sure let's think of the,389.46,2.64
code generation models as chefs in a,390.6,3.3
kitchen kitchen these chefs are trained,392.1,3.24
to prepare a variety of dishes using,393.9,3.0
specific recipes and ingredients however,395.34,3.9
the culinary world is always evolving,396.9,4.32
with new recipes and ingredients being,399.24,4.019
introduced regularly in the current,401.22,4.02
scenario every time a new recipe or,403.259,4.021
ingredient is introduced the chef has to,405.24,3.54
go through a complete retraining process,407.28,3.96
which is time consuming and expensive,408.78,4.259
it's as if the chef forgets all of the,411.24,3.299
old recipes when they learn a new one,413.039,4.141
see that's a good metaphor,414.539,4.801
or I guess that's an analogy that's not,417.18,5.28
a metaphor the researchers in this study,419.34,4.32
developed a new Training Method for,422.46,2.459
these chefs instead of forgetting old,423.66,2.819
recipes when learning new ones the chefs,424.919,3.141
can now continually learn and adapt,426.479,3.961
adding new recipes to the repertoire,428.06,4.06
while still remembering the old ones,430.44,3.0
this is like a chef who can learn to,432.12,2.579
cook a new dish while still remembering,433.44,2.819
to cook all the previous dishes they've,434.699,3.361
ever learned this new Training Method is,436.259,3.301
called prompt pooling with teacher for,438.06,4.199
Teacher forcing makes chefs or in the,439.56,4.139
real case the code generation models,442.259,3.06
more efficient and adaptable yada yada,443.699,4.021
okay you get the idea so this only takes,445.319,4.021
a few seconds and it takes only a few,447.72,2.879
cents to run,449.34,3.479
and so actually probably what I'll do is,450.599,3.72
I'll pause it and I'll I'll go ahead and,452.819,3.181
update it so that it'll just ingest,454.319,3.301
everything in a folder and then I'll,456.0,3.599
show you a nice cleaned up output so,457.62,4.94
actually we'll be right back,459.599,2.961
um okay so speaking of being lazy I just,463.02,3.06
wanted to show you real quick I'm using,464.759,2.701
my coding chat bot to do this because,466.08,3.6
I'm ultra lazy,467.46,5.4
work smart not hard so basically I took,469.68,4.799
the script and I just copied it into my,472.86,3.839
coding chat bot uh which you can find it,474.479,3.421
it's literally just called coding,476.699,2.821
underscore chatbot underscore assistant,477.9,4.26
on my GitHub so I copied the script that,479.52,5.22
I had which is all of 99 lines and I,482.16,4.08
came over to my coding chatbot and I,484.74,3.179
said hey can you do this for me instead,486.24,3.66
and it's like sure,487.919,4.981
um Okay cool so uh basically I said,489.9,6.0
let's get a folder so we're using this,492.9,5.579
folder so we can just download the PDFs,495.9,4.44
directly to there rather than copy and,498.479,3.801
pasting the text and we're just gonna,500.34,4.919
take the output folder or the input,502.28,4.66
folder for the PDFs and then an output,505.259,5.16
folder for the um Whatchamacallit whoops,506.94,7.5
okay so we come over to here and it,510.419,8.101
wants us to add OS and Pi PDF,514.44,4.86
um,518.52,4.439
that's fine so we add that and then we,519.3,5.76
see what else it wants to do if name,522.959,4.921
equals main yep so it's going to do all,525.06,4.02
that,527.88,3.66
PDF file replace yep cool so I just I,529.08,3.9
gave it really simple instructions I,531.54,3.299
said can you modify this script so that,532.98,3.78
it will one open every PDF in the input,534.839,4.201
folder one by one and perform the same,536.76,5.28
operation and two check an output folder,539.04,6.919
for the report as the same PDF uh or,542.04,7.14
blah check the output folder for a file,545.959,4.661
of the same name this will enable us to,549.18,2.82
run batches without duplicating effort,550.62,2.52
should be pretty straightforward let me,552.0,2.94
know if you have any questions,553.14,4.98
um and okay so let's put this over here,554.94,6.66
and see if it worked,558.12,4.68
okay,561.6,4.679
so um PDF files for files in OS Lister,562.8,5.64
that looks right,566.279,3.24
um,568.44,4.92
open read binary as file PDF reader yep,569.519,6.361
so we get that it gets all the page,573.36,4.26
numbers that should all work I've used,575.88,3.24
that I've used this this module before,577.62,5.58
pi pdf2 and PDF file reader if it's over,579.12,7.02
22 000 characters just cut it off it,583.2,5.579
seems to work well enough and then we,586.14,5.639
get the report so on and so forth,588.779,5.161
um let's see,591.779,5.601
it looks like it's not actually checking,593.94,7.519
if the file exists,597.38,7.12
yep okay so this is this is close so,601.459,4.541
let's take this over to the scratch pad,604.5,3.54
and then we'll say,606.0,4.1
um,608.04,2.06
let's see it will then check the output,610.92,3.66
folder for the report wait am I missing,612.72,4.04
something,614.58,2.18
it doesn't have a continue function,616.98,7.979
um okay sorry I I think we need to check,620.04,9.54
um if the final file name exists in the,624.959,9.481
output folder first and then use a,629.58,10.58
continue to skip the process make sense,634.44,8.64
I found that if you obviously like if,640.16,4.359
you get frustrated with like no you eat,643.08,3.54
it like it'll be apologetic and it'll,644.519,4.141
spend more time apologizing,646.62,3.42
um so don't be mean to the machine if,648.66,2.64
you just say sorry I think there was a,650.04,2.58
misunderstanding it's actually much more,651.3,3.42
helpful so words matter,652.62,4.98
um be polite to your coding assistant,654.72,4.739
um because if it's if just like a human,657.6,3.9
if the human is spending mental energy,659.459,4.141
trying to placate you know a frustrated,661.5,4.32
friend or whatever it's going to waste a,663.6,6.299
little bit more time and energy okay,665.82,4.079
um sure here's the modified script the,670.019,2.701
script will first check if the report,671.579,2.581
already exists in the output folder if,672.72,3.0
it does it will skip the current PDF and,674.16,3.66
move to the next one excellent so let's,675.72,4.5
check this out and see,677.82,5.94
if it works if it if it looks how I,680.22,6.679
think it should look,683.76,3.139
so we'll come over here all right so for,686.94,5.76
PDF file and PDF files first all right,690.0,4.74
yep so first we list there we go that's,692.7,4.98
what I was expecting if it exists then,694.74,4.38
continue so you just skip the whole,697.68,4.26
thing otherwise go ahead and open it yep,699.12,4.38
there we go so we said because we set,701.94,3.3
the file name first all right so this,703.5,3.48
should be fine,705.24,4.26
um okay I think that's I think that's uh,706.98,5.039
good so let's come over here let's exit,709.5,4.86
out of my coding chatbot assistant,712.019,3.781
um so again like I had to put very,714.36,2.76
little energy into that all I had to do,715.8,2.88
was check and honestly what I could have,717.12,3.959
done is just ask it to check its work,718.68,4.08
like you know does it do the thing that,721.079,3.841
I think it is but you saw I didn't,722.76,4.319
really do any coding all I did was copy,724.92,5.58
paste okay uh so let's go back out of,727.079,6.121
here quickly extract science papers and,730.5,6.0
then we'll do python whoops generate,733.2,8.639
multiple reports no module named pi pdf2,736.5,6.54
I thought I already had it maybe that,741.839,3.261
was my previous install pip install,743.04,5.16
ipdf two,745.1,7.08
Pi PD F2,748.2,3.98
this is the boring part okay now it,752.76,4.38
should work,754.92,4.8
um is deprecator and was removed used,757.14,4.98
PDF reader instead so this is exactly,759.72,6.0
exactly the problem that uh that the um,762.12,5.82
uh this one of the papers addresses is,765.72,3.9
the fact that the modules have been,767.94,4.86
updated and so now it's it's uh out of,769.62,5.64
date so we gotta go we gotta go switch,772.8,4.74
to this thing over here,775.26,5.639
um all right oh I forgot to save it,777.54,5.46
that could be a problem,780.899,4.56
um all right so,783.0,5.76
if it ends with otherwise,785.459,5.641
all right let's see if that fixed it and,788.76,4.019
also it might have yard anyways because,791.1,4.26
I forgot to save uh reader num pages is,792.779,5.581
deprecated use Len reader pages instead,795.36,4.74
okay at least at least their,798.36,3.3
documentation is good and it's helping,800.1,3.06
me fix it,801.66,3.859
um okay,803.16,2.359
um,807.72,2.119
okay that should be good,812.16,5.76
int object is not iterable,814.86,3.93
uh,817.92,2.039
[Music],818.79,5.25
and um let's see for page in so if we're,819.959,7.38
doing a length so that's an end we don't,824.04,5.099
need that we just need number of pages,827.339,4.68
so we should do um,829.139,8.76
uh let's see list of range of 0 to was,832.019,7.44
it zero to that I think that's how that,837.899,3.721
formatting is so I'm having to fix some,839.459,3.721
of it because exactly the problem,841.62,3.659
virtual list cannot be interpreted as an,843.18,3.06
integer,845.279,3.06
hang on,846.24,4.8
huh,848.339,4.921
let me just come back over here and say,851.04,4.94
um I don't know what I'm doing I'm lost,853.26,5.639
uh python chat,855.98,5.58
um let's see,858.899,2.661
I got,867.06,3.06
shift enter,868.56,5.779
um and you help me I'm lost,870.12,4.219
I probably have the the range formatted,879.24,5.36
wrong or something,881.94,2.66
um let's see is typically blah blah okay,885.6,6.78
four page in list range zero PDF reader,889.5,5.24
pages,892.38,2.36
yeah that's the that's the correct line,895.92,3.68
list range zero length Okay interesting,904.26,5.16
okay so it was it was not lying to me,907.5,3.959
when it said I needed length of PDF,909.42,4.32
reader Pages all right cool so let's see,911.459,4.101
if that fixed it so let's come over here,913.74,5.339
so four page in it seems like it's,915.56,5.5
getting kind of long,919.079,4.921
all right here let's just open another,921.06,5.88
terminal uh CD quickly,924.0,6.24
yada yada yada anyways well here let me,926.94,5.759
just go ahead and see if it works python,930.24,5.099
generate,932.699,4.561
still doesn't work it's deprecated and,935.339,3.841
removed,937.26,4.819
oh okay,939.18,2.899
there we go reader pages,943.019,4.141
so we found another bug,945.24,4.039
um,947.16,2.119
the page num,951.36,6.5
almost there oops,954.12,3.74
reader is not defined,957.959,3.721
[Laughter],959.84,6.119
uh oh right PDF reader there we go,961.68,4.279
extract text is deprecated and removed,967.68,6.3
use extract underscore text instead,970.44,6.3
man okay this is like an object lesson,973.98,5.76
as to why uh why this uh continuous,976.74,5.099
learning needs to be done okay cool now,979.74,3.599
it's thinking all right I think we fixed,981.839,4.201
it so ideally what should happen is uh,983.339,5.881
we'll get a list of outputs here that,986.04,4.979
are going to have the same name as those,989.22,3.84
so then it will not uh duplicate the,991.019,3.721
efforts in the future I'll go ahead and,993.06,3.899
delete the reports folder uh we can,994.74,5.519
delete the inputs delete the generate,996.959,6.901
report there we go okay so here we go,1000.259,5.041
The Continuous learning this would have,1003.86,3.479
actually helped this so this will,1005.3,4.8
actually uh this kind of thing I've,1007.339,4.081
actually had some conversations with,1010.1,4.08
people because with chat GPT having had,1011.42,5.82
the cutoff date in 2021 it's already,1014.18,5.76
losing utility because it's increasingly,1017.24,5.039
out of date some of that I think is,1019.94,3.899
deliberate on the part of open AI,1022.279,2.881
because they didn't want it to be able,1023.839,4.1
to use other people to use it to,1025.16,5.34
accelerate language model research or,1027.939,5.26
who knows what else is going on,1030.5,5.76
um but yeah so there there it is so we,1033.199,5.461
should have our first output here there,1036.26,5.1
we go so now you can correlate it back,1038.66,4.86
to exactly the same thing and you will,1041.36,4.68
be able to just quickly grab a whole,1043.52,4.679
bunch of stuff okay,1046.04,3.3
um yep,1048.199,4.641
excellent excellent excellent,1049.34,3.5
um,1053.419,5.76
python uh chat pie okay great,1054.7,6.54
um,1059.179,2.061
uh let's see,1061.88,5.22
I have a folder,1064.34,4.26
um or here let's go ahead and grab the,1067.1,3.84
updated version of this,1068.6,5.52
and put this no we can get rid of that,1070.94,6.72
put this in scratch pad,1074.12,5.28
so we've got,1077.66,3.42
coding,1079.4,3.36
scratch pad,1081.08,3.839
all right so let's put it there and then,1082.76,6.74
we'll say I have a folder uh output,1084.919,10.681
that is full of uh uh text files,1089.5,10.9
um with the file name being the name of,1095.6,5.88
M,1100.4,4.159
archive paper,1101.48,7.64
I would like to render,1104.559,9.221
all those files to HTML,1109.12,5.62
um,1113.78,4.139
let's use the file name,1114.74,7.62
as a header where is my there we go,1117.919,8.301
let's use the file name as a header,1122.36,3.86
uh,1126.38,4.86
for each section,1128.539,4.081
um,1131.24,5.34
and then there is uh there is a,1132.62,5.6
conversation,1136.58,4.76
of QA,1138.22,7.54
within each file which I'd like to,1141.34,9.579
present on the page pretty simply so,1145.76,7.32
let's go ahead and grab an example of,1150.919,3.5
the report,1153.08,3.719
and put it in the scratch Pad so it can,1154.419,3.88
see,1156.799,3.601
because then in the scratch Pad you just,1158.299,3.781
give it examples,1160.4,4.56
um of what you're talking about you can,1162.08,7.16
see an example of the plain text report,1164.96,7.56
in your scratch Pad,1169.24,9.059
um okay go uh the final output should be,1172.52,8.96
report dot HTML,1178.299,8.5
which should be fully self-contained,1181.48,5.98
um,1186.799,3.12
and pretty all right so let's see what,1187.46,4.68
it gives me for that meanwhile this,1189.919,4.321
should be the other one should be pretty,1192.14,5.22
much done yep so we should have we've,1194.24,4.799
got four we've got four papers,1197.36,3.48
summarized and like I said this probably,1199.039,4.321
cost a few cents,1200.84,3.3
um,1203.36,4.199
because it was uh you know it it does,1204.14,4.98
add up a little bit because each paper,1207.559,3.061
actually you,1209.12,2.76
um you have to read the entire paper,1210.62,3.12
three times because the conversation is,1211.88,4.08
three messages long so that's that's one,1213.74,3.72
of the only things to keep in mind is,1215.96,3.0
that the the more questions you ask it,1217.46,3.54
you're basically reading the entire,1218.96,4.68
paper every time to keep asking or to,1221.0,5.1
keep answering those questions about it,1223.64,6.3
um let's see get status get add,1226.1,7.86
get commit am all done,1229.94,6.3
and uh get pushed so you guys can use,1233.96,4.26
this and then let's hop up back over to,1236.24,5.88
my coding chatbot to see what it said,1238.22,6.48
okay cool,1242.12,4.74
um let's see from bs4 import beautiful,1244.7,4.8
soup and I'm just gonna fully send this,1246.86,5.04
to see if it works,1249.5,4.5
um just,1251.9,4.62
all right so then not coding chatbot,1254.0,4.679
quickly extract and we're going to come,1256.52,5.48
up here and just save this as um uh,1258.679,6.62
renderreport.pi so let's jump over here,1262.0,6.46
oops wrong terminal python,1265.299,6.161
renderreport.pi,1268.46,3.0
um no module named bs4,1272.12,6.299
um import uh no,1275.539,8.461
pip install darn it pip install vs4,1278.419,8.301
there we go,1284.0,2.72
all right let's try that again,1287.6,3.48
all right and that ran pretty much,1289.28,4.379
instantly so let's see if that worked,1291.08,5.339
hey cool look at that so it could be it,1293.659,4.081
could it could stand to be a little bit,1296.419,3.901
prettier but this is this is definitely,1297.74,4.02
good enough,1300.32,3.599
um where it's got each one with a header,1301.76,4.32
and so there you have it you've now got,1303.919,4.441
everything rendered to a nice report you,1306.08,4.979
can print this to PDF if you want it's,1308.36,4.98
searchable right you could you can say,1311.059,4.98
okay uh prompt where else is prompt,1313.34,4.8
listed excellent,1316.039,4.201
um yeah so I think I'm done uh I'll be,1318.14,4.98
using this uh to help with my video prep,1320.24,4.679
I can imagine that there's a whole bunch,1323.12,4.439
of other AI commentators out there who,1324.919,5.341
might be used who might start using this,1327.559,4.201
um but yeah it's super super simple,1330.26,3.48
brain dead tool hopefully it'll help,1331.76,3.72
accelerate science,1333.74,3.78
um and yeah it's out there under the MIT,1335.48,4.26
license so please take it use it let's,1337.52,4.26
accelerate science let's accelerate all,1339.74,5.48
science with this all right cheers,1341.78,3.44