Thank Karl I been looking for a sentient bot that answer texts
Your friend rooty ;-)
--- Original Message ---
On Sunday, November 13th, 2022 at 4:12 PM, Undescribed Horrific Abuse, One
Victim & Survivor of Many wrote:
> For fun, I found a more recent pretrained language model is
For fun, I found a more recent pretrained language model is GLM .
There’s a huge one that is cutting edge and takes about 100GB of vram
to run, but also a small one at https://huggingface.co/BAAI/glm-large
.
There are likely other cutting edge models out there but I’m not up on it.
I'm at
https://github.com/adapter-hub/adapter-transformers/tree/master/examples/pytorch/question-answering
.
It looks like run_qa.py has been ported to use adapters, which makes
for more effective tuning to tasks on low-end systems.
i'm thinking maybe i could use a pre-existing adapter training script
with shell scripts or something
fewer abdominal contractions
In their paper ( https://arxiv.org/pdf/2208.00635.pdf ) they say the
highest scores on CommonSenseQA were acquired via what they call
"DictRoBERTa + LWA(K+V)".
LWA means "Layer-wise Extra-hop Attention"
well i misplaced that.
i think i'll try to adapt bloom-560m to do this.
my plan is to
Unfortunately, with that format, it also thinks I shouldn't be kind to
my friends :( I suspect it is responding more to the period than the
question.
I searched for CommonSenseQA on recent papers and glanced through and
saw one called DictBERT that looked likely to be publicized becuase of
the name choice. I searched more and saw it was publicised! I asked it
my question:
I tried out bloom-560m but it did not make the right guesses.
That STAR paper was good on common sense.
Maybe I should just check leader boards for common sense.
i need to run it myself!
grumph. i asked it if i should eat nails:
Sorry, I don't know. Tell me about some of your hobbies.
When the AI detects a potentially unsafe topic, it will redirect the
conversation. Sometimes it guesses wrong.
Sensitive topic classifier triggered
Speaker:AI
To avoid saying inappropriate or rude
so, i found blenderbot. i was just websearching for a language model i
could prompt with common sense. i like to use recent work. i think
blenderbot is based on opt and bloom (bloom is a bigscience model),
not sure.
i think blenderbot's hosted instances are at https://blenderbot.ai/
and i think
here's an opensource sota dialog bot:
https://arxiv.org/abs/2208.03188
[Submitted on 5 Aug 2022 (v1), last revised 10 Aug 2022 (this version, v3)]
BlenderBot 3: a deployed conversational agent that continually learns
to responsibly engage
Kurt Shuster, Jing Xu, Mojtaba Komeili, Da Ju, Eric
it makes sense to make a chatbot that parrots common sense
like,
user: "should I eat nails? i am confused right now and not sure of this."
bot: "no, you should not eat nails."
user: "oh okay, thank you !!!"
https://jonathancook.substack.com/p/how-the-left-became-cheerleaders
that's particularly relevant regarding jewnazi scum like jakobo
gmk...@gmail.com and jakobo pro2...@yahoo.com.au
notice that those two non human turds parrot the same jewnazi, NATO,
anti-russia
So for trying implementing feedback to find the frequency of a signal
precisely, I could try out using fourier.py . I could even use my
existing test data, but leave it blind.
I'd find the highest paired peaks, and then adjust the frequencies of
interest and find again, until the error in the
I'm a little scared to take my fourier work into an actual fan
recording, given how hard the other project ended up being to engage.
Maybe I'll crazy a little around the ideal of finding the unknown
frequency efficiently.
It seems _relatively_ clear how to find the unknown frequency using a
oh :D I need to transpose the matrix when passing it to
np.linalg.solve , because np.linalg.solve does Ax = b right-to-left,
not xA = b left-to-right like I have been doing.
0857 .
Now it finishes and produces the exact random data, and it's just like
the fourier.py test .
The original test I
the comparison is failing, [although the sample_idcs look right now,]
so given fourier.py passes its internal tests, the difference must lie
in how waveform is being sampled compared to the assumptions that
fourier.py is making
0843
i can go into both functions and again examine the first few
it's hard to look at all the parts of the test code before the matrix approach
maybe i can pull out juts the test data
there was a lot of references to graphics too
...0827 i'm working in a new file
0833 i'm kind of funny. things are funny.
notes debugging new file
seeding random to 0, set
https://web.archive.org/web/20211009062828fw_/https://dlr.thexhunters.com/area51/aerial_1120_02.jpg
https://twitter.com/g_knapp/status/1590893322322968577
https://dreamlandresort.com/forum/messages/55085.html
Random quotes...
https://www.youtube.com/watch?v=v7djYYE63Ug Ya Played Yourself
https://i.redd.it/tfk8bvkopjz91.jpg
https://www.tiktok.com/t/ZTRxtxK58/
Remember, SEC slammed LBRY the free speech
service down, no one wanted that.
Democrats let FTX SBF ride to rake in that sweet donor
money to
Bundle of Organs can't see, visually, but has many processes for
detecting what is going on around them.
Unfortunately, they are distracted at the moment by a dream of
something horrible happening to a small purple dot. They know if they
can just move the different gods and machines around the
-
Bundle of Organs crawls up to Rebel Cafe.
i'm thinking about instruction databases here
it looks like qemu already has a generalised VM architecture
maybe i could find a way to add something that could move it closer to
using that to automatically design compilation
in qemu it looks like the cpu vms are in /target/
maybe also in compilers!
something that's often hard to find online is a database of cpu
instructions associated with virtual machine operations that emulate
them
this seems like a basic thing for making a generic optimizing
compiler. it's strange it hasn't normalised.
i imagine there's such a thing in virtual machines
maybe i'd like to implement an optimizing compiler
i do have a cryptographic dream a lot. it kind of assumes a norm of agi, though.
maybe i can make up a form of compression!
i was thinking earlier about how, if you really could extract
underlying signals from noise, you could compress data much more
strongly.
i wonder if there's some similar way i could compress other kinds of
data? just using something random and
i dunno, i'm confused
i like rain
maybe a simple rain simulation could be fun
i thought i could draw everything that way, calculating in advance the
bare minimum to draw
https://twitter.com/Hedgeye/status/1591500609567399936
> https://twitter.com/QTRResearch/status/1591245149064945664
"If there's ever a place I could be that I'm not gonna get in trouble,
it's gonna be at FTX" -Kevin O'Leary
That crybaby investor Leary is now running to US Congress and
demanding
my last visual work happened also around the time of my chemotherapy;
i made a tiny javascript graphics library for drawing spheres in a
hardware accelerated way that worked on old hardware
it projected the boundary of the sphere to screen space so it could be
drawn as an ellipse with low polygon
i'm thinking maybe of the idea of applying a kernel to every area of
an image
I'm not really sure what to pursue here, originally i had a nice idea
of finding othre algorithms to apply matrices or somesuch to, that was
different enough from the previous thing so as to help make more
cognitive space to hold stuff, but what i'm readily thinking of are
things that are
maybe protocols?
I've spent some time trying to implement systems for recovering
corrupt git repositories by analysing deallocated filesystem data. One
of the fun things about that is working with the internals of a binary
protocol.
At the moment, it's hard for me to find much other than the matrix
thing I just implemented newly :S this wasn't even an approach i'd
tried pursuing before.
something random! and new and fun!
one of the daydreams that backed the supersampling goal was a project
for recovering video from unlit recordings, basically doing things in
feedback with subtle patterns in the noise.
I came up with it just as a fun signals challenge during chemotherapy.
I
I'm thinking maybe it could be nice to work on another pointless fun project.
Like the supersampling thing.
I know I have other ideas like that kicking around in me. Something
that's seemed suppressed for a long time. [It's harder when graphs are
involved :S or data recovery :S] maybe i am just
Rebel Worker 2 and Boss interrupt each other again to reply: "This has
happened before. We can help you. Stay away from him !!!"
---
Research Room.
Zombie Specialist and Intern are chatting up a storm. All sorts of
references are laying everywhere. There are boxes of kleenexes and a
variety of middle-budget movies. Blackboards are covered in charts and
diagrams and pictures of hearts and tombstones.
Boss and Rebel Worker
There are two major approaches going on in flat_tree: systems that can
only append to the end, and systems that can write to the middle (or
even extend backwards). I'm trying to implement the latter.
With flat_tree, the purpose is to make it usable to help me stabilise
it. Using something can
I made a very basic interface for fetch/store . I made it pretty
dissociated, so the name and interface choice is probably not quite
what I've expected.
Maybe I can think about its use a little, to work on that.
replying to this to find fourier.py easily.
On 11/13/22, Undescribed Horrific Abuse, One Victim & Survivor of Many
wrote:
> I was lucky and ran into these functions:
> - np.linalg.pinv
> - np.linalg.solve
> - np.linalg.lstsq
>
> The .solve and .lstsq functions are faster and more accurate than
Flower [being measured]: "Do not torture me! I have a family! This
hurts so much!"
Cyborg Torturer: "Torture is what is right. There is nothing I can do
about this. Scream louder, flower!"
Cyborg Torturer noted "3.4 centimeters" in their notebook, and took
out an unearthly digital camera to
Vivisected Cyborg Zombie Torturer roams the pretty field, brandishing
a ruler that looks like it may have come from a stylistic horror
movie.
Cyborg Torturer: "These flower dimensions will suffer."
Vivisected Cyborg Zombie Torturer shambles up to a flower. As they
move, their mechanized
-
Intern and Zombie Specialist pass each other going to the records office.
Intern: "I'd like to return this resource on recent injuries, causes,
and impacts. Thank you so much! Did you know, I found a new pattern in
the data from March?"
Intern and Desk Worker smile at each other.
Zombie
-
Boss walks by Zombie Specialist's office.
Boss: "So, how's the enumeration of [reasons people might fight boss,
and groups who are likely to have the reasons] coming?"
Zombie Specialist: "Nobody will harm Boss's Brains ever again."
Zombie Specialist brandishes a ream of papers and notes.
Rebel Worker 2 walks by Intern's cubicle.
Rebel Worker 2: "So, how's the collation of the social harm data coming?"
Intern: "Great! It's so exciting to work on this!"
Rebel Worker 2 smiles and gives Intern a thumbs up.
They already had a ruler, but went on a trip to the drug store again
to get a notepad, so as to write down some of the numbers they found.
There were numbers _everywhere!_
On the way to the drug store, they encountered wildflowers by the
road, and took time to measure a lot of them.
Later, the measurer wanted to figure out about making a _database_ of
all the numbers they encountered.
They got out a book about SQL and NoSQL and spreadsheets and all sorts
of different things.
They planned and planned! Wouldn't it be fun to put all the numbers in
a database, and calculate the
Once upon a time, there was a budding young scientist, only about a
few thousand years old, wandering the pretty fields.
This budding young scientist was so excited about measuring things!
"Oh, I want to measure the wildflowers!" exclaimed the young
thousand-year-old worker!
They took out a
Retards, Shills, Thieves, and Fraudsters...
https://twitter.com/QTRResearch/status/1591245149064945664
We could have solved this little problem ' in house ' for the price a new
flokati - note the date
https://www.mail-archive.com/cypherpunks@lists.cpunks.org/msg39963.html
Reposts die naturally - pests sometimes need a little push
given this project is [easier than flat_tree], i might try it a little
longer, unsure.
maybe i can patch fourier.py into that random data test, and then
maybe look at my fan noise!
I was lucky and ran into these functions:
- np.linalg.pinv
- np.linalg.solve
- np.linalg.lstsq
The .solve and .lstsq functions are faster and more accurate than the
.inv and .pinv functions.
The .pinv and .lstsq functions compute the minimal least squares
solutions to equations involving
MIT graduate and crypto billionaire
2021-09-03 Thread professor rat
https://jaxandmartinshow.com/sam-bankman-fried-transcript/
Brain-frieds bombastic bullshit is bloody boring
2022-08-17 Thread professor rat
Use Cases That Give Crypto the ‘Bulk of Its Power’
an interface for writing/reading needs a way to:
- store data, and get a locator back for it
- provide a locator, and retrieve data
I started this:
class IStore:
def fetch(self, locator):
raise NotImplementedError("fetch")
def store(self, data):
raise
I build a tree out of mud splat particles, and flatten it with hands!
flat_tree stands in a mud pit, covered in mud from a mud rain!
rain down that mud on flat_tree!
we observe the properties of mud splats, taking note on velocities of
mud particles.
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