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Items tagged with: LLMs


Oh boi, do I have thoughts about #nanowrimo. Disclosure; I have written millions of words (most of them technical), I have done #NaNoWriMo a few times, and I have been writing about #AI since the early 90s.

#LLMs are NOT AI. LLMs are vacuums which sort existing data into sets. They do not create anything. Everything they output depends on stolen data. There is no honest LLM.

This year, Nano is sponsored by an LLM company, and after pushback, they said anyone suggesting AI shouldn't be used was "ableist and "classist"....which....whooweee , that's a mighty bold stance.

LLMs are being sued to hell by authors for slurping up all their content. The reason you can "engineer a prompt" by including "in the style of RR Martin" is because the LLM has digested ALL of RRMartin.

Re: "ableism", I'm going to direct you to Lina² neuromatch.social/@lina/113069…, who writes about the issue better than I could. And I want to thank @LinuxAndYarn for coming up with my fave new Nano tag: #NahNoHellNo.


We are recruiting for the position of a PhD/Junior Researcher or PostDoc/Senior Researcher with focus on knowledge graphs and large language models connected to applications in the domains of cultural heritage & digital humanities.

More info: fiz-karlsruhe.de/en/stellenanz…

Join our @fizise research team at @fiz_karlsruhe
@tabea @sashabruns @MahsaVafaie @GenAsefa @enorouzi @sourisnumerique @heikef #knowledgegraphs #llms #generativeAI #culturalHeritage #dh #joboffer #AI #ISE2024 #PhD #ISWS2024


New bookmark: React, Electron, and LLMs have a common purpose: the labour arbitrage theory of dev tool popularity.

“React and the component model standardises the software developer and reduces their individual bargaining power excluding them from a proportional share in the gains”. An amazing write-up by @baldur about the de-skilling of developers to reduce their ability to fight back against their employers.


Originally posted on seirdy.one: See Original (POSSE). #GenAI #llms #webdev


Like many other technologists, I gave my time and expertise for free to #StackOverflow because the content was licensed CC-BY-SA - meaning that it was a public good. It brought me joy to help people figure out why their #ASR code wasn't working, or assist with a #CUDA bug.

Now that a deal has been struck with #OpenAI to scrape all the questions and answers in Stack Overflow, to train #GenerativeAI models, like #LLMs, without attribution to authors (as required under the CC-BY-SA license under which Stack Overflow content is licensed), to be sold back to us (the SA clause requires derivative works to be shared under the same license), I have issued a Data Deletion request to Stack Overflow to disassociate my username from my Stack Overflow username, and am closing my account, just like I did with Reddit, Inc.

policies.stackoverflow.co/data…

The data I helped create is going to be bundled in an #LLM and sold back to me.

In a single move, Stack Overflow has alienated its community - which is also its main source of competitive advantage, in exchange for token lucre.

Stack Exchange, Stack Overflow's former instantiation, used to fulfill a psychological contract - help others out when you can, for the expectation that others may in turn assist you in the future. Now it's not an exchange, it's #enshittification.

Programmers now join artists and copywriters, whose works have been snaffled up to create #GenAI solutions.

The silver lining I see is that once OpenAI creates LLMs that generate code - like Microsoft has done with Copilot on GitHub - where will they go to get help with the bugs that the generative AI models introduce, particularly, given the recent GitClear report, of the "downward pressure on code quality" caused by these tools?

While this is just one more example of #enshittification, it's also a salient lesson for #DevRel folks - if your community is your source of advantage, don't upset them.


Let’s be honest, if you’re a software engineer, you know where all this compute and power consumption is going. While it’s popular to blame #LLMs, y’all know how much is wasted on #docker, microservices, overscaled #kubernetes, spark/databricks and other unnecessary big data tech. It’s long past time we’re honest with the public about how much our practices are hurting the climate, and stop looking for scapegoats thereader.mitpress.mit.edu/the…


This is a really nice read about whether #LLMs can actually reason: aiguide.substack.com/p/can-lar…
I think expecting language models to reason like the math engines maght be a bit out of range! Nice try!
#LLMs


Three years in the making - our big review/opinion piece on the capabilities of large language models (LLMs) from the cognitive science perspective.

Thread below! 1/

#AI #cogneuro #NLP #LLMs #languageandthought

arxiv.org/abs/2301.06627