「 CakeML is a functional programming language and an ecosystem of proofs and tools built around the language. The ecosystem includes a proven-correct compiler that can bootstrap itself 」
Last November, NASA's Voyager 1 sent home garbled data, and engineers traced the problem to the flight data subsystem (FDS). The problem turned out to be a single chip in the FDS memory. They couldn't repair the chip but could move the affected code into sections and store them in different parts of the FDS system. They tested the new system this week, sending signals to the Voyager 1, 22.5 light-hours away. It worked, and Voyager 1 is back.
☢️ What John von Neumann really did at Los Alamos
—3 Quarks Daily
「 Johnny von Neumann was the multifaceted intellectual diamond of the 20th century. He contributed so many seminal ideas to so many fields so quickly that it would be impossible for any one person to summarize, let alone understand them. He may have been the last universalist in mathematics, having almost complete command of both pure and applied mathematics 」
Going back to the actual point that matters most, to me at least.
What's the total carbon footprint of the advertising and social media-based web? (Not just the highly optimised servers)
Finally getting around to my new year’s resolution… I’m looking for PhD opportunities! I’m enjoying myself doing professional software dev right now, but I promised myself after my master’s that I’d try going back to academia eventually; this is the year I want to set that up. So I’m wondering if anyone on here knows of anything that's available. :>
Generally I’d love to do work involving programming languages in the broadest sense of the word, but also involving something that's not traditionally PL theory. For example:
Human factors in PL design: learnability, cognitive processing, etc.
Going beyond plain text for programming: graphical languages, alternative ways of storing & editing code (e.g. Unison), etc.
Applying proof assistants / type theories outside of pure mathematics: natural language semantics, experiment design, etc.
My name is Alessio, I have a PhD in computer science and work as a Research Software Engineer at the Netherlands eScience Center. My expertise is high-performance computing, and in particular acceleration of scientific software using GPUs and accelerators, and auto-tuning.
I'm trying to figure out the performance differences between 1Rx4 and 2Rx4 (single rank vs dual rank) memory modules.
From what I can logically conclude 2R (dual rank) should be slower, as you will have to wait a few cycles while switching between ranks, but it's incredibly hard to find information about this online.
Mostly because a lot of people confuse memory channels with memory ranks and this has poisoned the search results.
(Dual channel is faster then Single channel, but if I'm right Dual rank should be slower then Single Rank right?)
TL;DR:
Can anyone tell me the bandwidth and latency differences between 1Rx4 and 2Rx4 DDR4 RDIMM memory?
Does anyone here have experience with procedural text generation? I want to implement procedural descriptions for the planets in my game which are not toooo repetitive to read :o I read about Markov chains but I'm not sure how I can incorporate the different planet parameters, features, etc. And I'm also wondering what other methods there are^^ #computerscience#python#gamedev#gamedevelopment#coding#development#compsci
Any #compsci teachers who use GitHub Codespaces (or similar) for teaching? We're a Chromebook school and can't put student devices into developer mode because of reasons. Codespaces seems like a good fit for different runtimes, but I have zero experience.
Any tips or thoughts would be appreciated. We're hoping to start in fall of 2024, so I have some time to tinker.
For #ArtAdventCalendar Day 10: Happy birthday to Ada Lovelace (1815-1852), who published the first computer program. She worked together with Charles Babbage, the inventor of the Difference Engine and the Analytical Engine (the first - analogue! - #computers), correcting his notes on how to calculate Bernoulli Numbers with the Analytical Engine. 🧵1/n
I am legitimately saddened by how many graduate students, postdocs, and university professors altered their research direction to encompass large language models because of the attention they've been receiving in other areas of life outside of academia. Whether it's to critique them, enhance them, use them, or something else, I view it as a sign that as a research discipline, computer science is unhealthy. We call them "research disciplines" because they're meant to be disciplined about this sort of buffeting.
Diversity of ideas is important. Sticking with a research program long enough to see it through is also important. Changing up what you're working on every time Silicon Valley ejects a new artifact that gets news coverage endangers both of those values.
And holy hell is the monotony boring. Computer science is an interesting, sprawling field with a lot going on! Let's keep it that way!
I'm aware that over the last year or so I've been a critic of #LLM hype so I too am reacting to it. Lately I've been considering changing that up.
I worked with python to practice graph theory which can be very bland when only studied theoretically xD Does anyone have any ideas what else I could add? Maybe even some potential use cases so that those graphs become a meaning? I'm a bit lost now but it was so fun to do and I wanna continue to do more stuff with it c: https://github.com/Zitronenjoghurt/GraphTheory
Maybe I'm living behind the moon but it seems unreal how fast #AI is improving, wth? How can GPT-4 describe this weird image so accurately and even make out the little light switch next to the door on the left??? That's just insane and probably a great tool for auto generated ALT-texts :o #chatgpt#GPT4#OpenAI#accessibility#compsci#tech
Anyway, bringing it back to CS... if you think you'd like a half-teaching, half-research tenure-track position in CS at a friendly, mid-sized school in a unique city in a beautiful place, then consider applying here!