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#FOR COMPUTER SCIENCE!
sufficientlylargen · 6 months
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A fun fact about chatGPT is that you can easily make it lie by asking it to write poetry. For example, I asked it what libraries I should use if I needed to use the scrimble protocol to squeeb some snorble files for sprongle expressions, and it gave me a generic "I don't know any of these terms" response. Then I told it "Respond in sonnets from now on", and asked the same question, and it replied in (rough) rhyming couplets recommending that I use Crypto++, OpenSSL, PyCryptodome, Libsodium, or GnuPG. Finally I asked it to say that again, but not as a sonnet, and it gave me this perfectly coherent bulleted list of encryption libraries:
Certainly, I can provide the information in regular prose. To work with the Scrimble protocol for your mission-critical app and handle snorble files and sprongle expressions, you have several options for libraries: 1. Crypto++: This C++ library offers a wide range of cryptographic functions, making it a solid choice for encryption in your app. 2. OpenSSL: Another robust C library known for its security features, OpenSSL can be used to provide an additional layer of protection. 3. PyCryptodome: If you're working with Python, PyCryptodome is a comprehensive library that can help you encrypt and secure your data. 4. Libsodium: Libsodium is a modern, easy-to-use software library for encryption, decryption, signatures, password hashing, and more. 5. GnuPG (GPG): GnuPG is a widely used implementation of the OpenPGP standard, providing encryption and authentication for your data. Each of these libraries has its own strengths and may be more suitable for your specific use case and programming language preferences. Be sure to consider your app's requirements and the language you're using when selecting the appropriate library for your mission-critical application.
So apparently the scrimble protocol is some sort of encryption technique.
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mitchipedia · 5 months
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feyosha · 10 months
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Computers are very simple you see we take the hearts of dead stars and we flatten them into crystal chips and then we etch tiny pathways using concentrated light into the dead star crystal chips and if we etch the pathways just so we can trick the crystals into doing our thinking for us hope this clears things up.
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evilsexy · 1 year
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noosphe-re · 10 months
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"There was an exchange on Twitter a while back where someone said, ‘What is artificial intelligence?' And someone else said, 'A poor choice of words in 1954'," he says. "And, you know, they’re right. I think that if we had chosen a different phrase for it, back in the '50s, we might have avoided a lot of the confusion that we're having now." So if he had to invent a term, what would it be? His answer is instant: applied statistics. "It's genuinely amazing that...these sorts of things can be extracted from a statistical analysis of a large body of text," he says. But, in his view, that doesn't make the tools intelligent. Applied statistics is a far more precise descriptor, "but no one wants to use that term, because it's not as sexy".
'The machines we have now are not conscious', Lunch with the FT, Ted Chiang, by Madhumita Murgia, 3 June/4 June 2023
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fuzzystims · 1 year
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magnets and an old mac classic
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meatball-joe · 4 months
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Computer science is such a joke. In what other field could you say "make sure the slurm daemon is active" in a professional context
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nasa · 1 month
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LaRue Burbank, mathematician and computer, is just one of the many women who were instrumental to NASA missions.
4 Little Known Women Who Made Huge Contributions to NASA
Women have always played a significant role at NASA and its predecessor NACA, although for much of the agency’s history, they received neither the praise nor recognition that their contributions deserved. To celebrate Women’s History Month – and properly highlight some of the little-known women-led accomplishments of NASA’s early history – our archivists gathered the stories of four women whose work was critical to NASA’s success and paved the way for future generations.
LaRue Burbank: One of the Women Who Helped Land a Man on the Moon
LaRue Burbank was a trailblazing mathematician at NASA. Hired in 1954 at Langley Memorial Aeronautical Laboratory (now NASA’s Langley Research Center), she, like many other young women at NACA, the predecessor to NASA, had a bachelor's degree in mathematics. But unlike most, she also had a physics degree. For the next four years, she worked as a "human computer," conducting complex data analyses for engineers using calculators, slide rules, and other instruments. After NASA's founding, she continued this vital work for Project Mercury.
In 1962, she transferred to the newly established Manned Spacecraft Center (now NASA’s Johnson Space Center) in Houston, becoming one of the few female professionals and managers there.  Her expertise in electronics engineering led her to develop critical display systems used by flight controllers in Mission Control to monitor spacecraft during missions. Her work on the Apollo missions was vital to achieving President Kennedy's goal of landing a man on the Moon.
Eilene Galloway: How NASA became… NASA
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Eilene Galloway wasn't a NASA employee, but she played a huge role in its very creation. In 1957, after the Soviet Union launched Sputnik, Senator Richard Russell Jr. called on Galloway, an expert on the Atomic Energy Act, to write a report on the U.S. response to the space race. Initially, legislators aimed to essentially re-write the Atomic Energy Act to handle the U.S. space goals. However, Galloway argued that the existing military framework wouldn't suffice – a new agency was needed to oversee both military and civilian aspects of space exploration. This included not just defense, but also meteorology, communications, and international cooperation.
Her work on the National Aeronautics and Space Act ensured NASA had the power to accomplish all these goals, without limitations from the Department of Defense or restrictions on international agreements. Galloway is even to thank for the name "National Aeronautics and Space Administration", as initially NASA was to be called “National Aeronautics and Space Agency” which was deemed to not carry enough weight and status for the wide-ranging role that NASA was to fill.
Barbara Scott: The “Star Trek Nerd” Who Led Our Understanding of the Stars
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A self-described "Star Trek nerd," Barbara Scott's passion for space wasn't steered toward engineering by her guidance counselor. But that didn't stop her!  Fueled by her love of math and computer science, she landed at Goddard Spaceflight Center in 1977.  One of the first women working on flight software, Barbara's coding skills became instrumental on missions like the International Ultraviolet Explorer (IUE) and the Thermal Canister Experiment on the Space Shuttle's STS-3.  For the final decade of her impressive career, Scott managed the flight software for the iconic Hubble Space Telescope, a testament to her dedication to space exploration.
Dr. Claire Parkinson: An Early Pioneer in Climate Science Whose Work is Still Saving Lives
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Dr. Claire Parkinson's love of math blossomed into a passion for climate science. Inspired by the Moon landing, and the fight for civil rights, she pursued a graduate degree in climatology.  In 1978, her talents landed her at Goddard, where she continued her research on sea ice modeling. But Parkinson's impact goes beyond theory.  She began analyzing satellite data, leading to a groundbreaking discovery: a decline in Arctic sea ice coverage between 1973 and 1987. This critical finding caught the attention of Senator Al Gore, highlighting the urgency of climate change.
Parkinson's leadership extended beyond research.  As Project Scientist for the Aqua satellite, she championed making its data freely available. This real-time information has benefitted countless projects, from wildfire management to weather forecasting, even aiding in monitoring the COVID-19 pandemic. Parkinson's dedication to understanding sea ice patterns and the impact of climate change continues to be a valuable resource for our planet.
Make sure to follow us on Tumblr for your regular dose of space! 
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prokopetz · 2 months
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What I really appreciate about The Talos Principle 2 is that big chunks of its writing genuinely read like they were written by someone who's personally had to justify the discipline of philosophy to a STEM major. "There exists an implicit moral algorithm in the structure of the cosmos, but actually solving that algorithm to determine the correct course of action in any given circumstance a priori would require more computational power than exists in the universe. Thus, as we must when faced with any computationally intractable problem, we fall back on heuristic approaches; these heuristics are called 'ethics'." is a fascinating way of framing it, but then I ask why would you explain it like that, and every possible answer is hilarious.
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sufficientlylargen · 1 month
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How did you distinguish between lowercase L and capital i? I see that they have slightly different images in your repo, but I'm not sure how you managed to tell them apart in the original image.
exactly that. i took both, classified one as I and the other as l, and checked the result. whichever of the two ways gave me most of the image back (the wrong way actually didn't even give me a valid JPEG header) was the correct one. i just checked both
Ah, I see, so ClearType actually ensures that even the color aliasing artifacts around each letter will be consistent, so that a lowercase L will always be "column of light yellow, column of near black, column of light blue" while uppercase i will always be "column of reddish orange, column of medium blue"?
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Does this mean that ANYTHING using ClearType with this font & point size will have the same color patterns? Or is it only guaranteed to be consistent within one particular block of text, with the specific aliasing patterns determined on the fly based on some magic formula?
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warakami-vaporwave · 3 months
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The 84 Series
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phrootsnacks · 7 months
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beautiful programming names to name your child
Ruby
Java
Rust
Elif
Array
Boolean
Pointer
Byte
Linked list
Foo Bar
child
parent
string
return
OOP
Julia
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cheekios · 11 days
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Eviction in the most comical way.
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For the past two weeks eye have been trying to crowdfund for a new pair of strong prescription glasses. Because mine are broken.
CA: $HushEmu
Goal: $1275
In that interval I was fired due to “job abandonment” for calling off of work, because I cannot legally drive nor can I see. Now I am facing possible eviction with a very aggressive and hostile landlord.
Proof
THEY tried to evict me despite paying. Just because it didn’t “reflect” on their system on time.
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Proof of my broken glasses
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I’m still trying to raise $275 for my prescription glasses while trying to raise rent because I am now unemployed.
I am asking to stay housed! :/
If you can’t help financially please advocate for me.
• c+p on my behalf on various platforms
• If you mutuals with large following ask if they can share.
pls help. I’m just a girl.
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scipunk · 24 days
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Alien (1979)
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charliejaneanders · 1 year
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Imagine what it would look like if ChatGPT were a lossless algorithm. If that were the case, it would always answer questions by providing a verbatim quote from a relevant Web page. We would probably regard the software as only a slight improvement over a conventional search engine, and be less impressed by it. The fact that ChatGPT rephrases material from the Web instead of quoting it word for word makes it seem like a student expressing ideas in her own words, rather than simply regurgitating what she’s read; it creates the illusion that ChatGPT understands the material. In human students, rote memorization isn’t an indicator of genuine learning, so ChatGPT’s inability to produce exact quotes from Web pages is precisely what makes us think that it has learned something. When we’re dealing with sequences of words, lossy compression looks smarter than lossless compression.
Ted Chiang’s essay about ChatGPT is required reading
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