Upvoted for classic 24 hour party people reference

This caused me to delete Google Maps, but their removal of Black History month from Google Calendar is what’s making me contemplate migrating everything else away from them…

Seriously, why the fuck is he still CEO of that company? He’s actively undermining them in every way on a global scale. Tesla shareholders are idiots…

Honestly I find this feature of my washer/dryer super-useful because it reminds me to turn the stuff over instead of forgetting and letting it sit in the washer getting midlewy

I mean you’re technically correct from a copyright standpoint since it would be easier to claim fair use for non-commercial research purposes. And bots built for one’s own amusement with open-source tools are way less concerning to me than black-box commercial chatbots that purport to contain “facts” when they are known to contain errors and biases, not to mention vast amounts of stolen copyrighted creative work. But even non-commercial generative AI has to reckon with it’s failure to recognize “data dignity”, that is, the right of individuals to control how data generated by their online activities is shared and used… virtually nobody except maybe Jaron Lanier and the folks behind Brave are even thinking about this issue, but it’s at the core of why people really hate AI.

Yes, you’re absolutely right. The first StarCoder model demonstrated that it is in fact possible to train a useful LLM exclusively on permissively licensed material, contrary to OpenAI’s claims. Unfortunately, the main concerns of the leading voices in AI ethics at the time this stuff began to really heat up were a) “alignment” with human values / takeover of super-intelligent AI and b) bias against certain groups of humans (which I characterize as differential alignment, i.e. with some humans but not others). The latter group has since published some work criticizing genAI from a copyright and data dignity standpoint, but their absolute position against the technology in general leaves no room for re-visiting the premise that use of non-permissively licensed work is inevitable. (Incidentally they also hate classification AI as a whole; thus smearing AI detection technology which could help on all fronts of this battle. Here again it’s obviously a matter of responsible deployment; the kind of classification AI that UHC deployed to reject valid health insurance claims, or the target selection AI that IDF has used, are examples of obviously unethical applications in which copyright infringement would be irrelevant.)

I had never heard of it before now–thanks!

I’m honestly surprised that nobody has said anything about MS Office, but it’s not like I expect anyone to miss the application itself, it’s just that if your work requires you to interface with it, there really is no alternative to running Windows or MacOS. Microsoft’s own Office Online versions of the apps do a worse job of maintaining DOC/PPT formatting consistency than the possible Russian spyware that is OnlyOffice, which also screws things up too often to be relied upon. LibreOffice is, let’s be honest, a total mess (with the exception of Calc, which also isn’t consistent with the current version of Excel, but can do some things that Excel no longer can do, so I appreciate it more as a complementary tool than as a replacement).

this is learning completely the wrong lesson. it has been well-known for a long time and very well demonstrated that smaller models trained on better-curated data can outperform larger ones trained using brute force “scaling”. this idea that “bigger is better” needs to die, quickly, or else we’re headed towards not only an AI winter but an even worse climate catastrophe as the energy requirements of AI inference on huge models obliterate progress on decarbonization overall.

those are all classification problems, which is a fundamentally different kind of problem with less open-ended solutions, so it’s not surprising that they are easier to train and deploy.

I really wish it were easier to fine-tune and run inference on GPT-J-6B as well… that was a gem of a base model for research purposes, and for a hot minute circa Dolly there were finally some signs it would become more feasible to run locally. But all the effort going into llama.cpp and GGUF kinda left GPT-J behind. GPT4All used to support it, I think, but last I checked the documentation had huge holes as to how exactly that’s done.

One of the reasons I love StarCoder, even for non-coding tasks. Trained only on Github means no “instruction finetuning” bullshit ChatGPT-speak.

this; every time the ublock origin absolutists insist that everyone must use Firefox or die I just wonder if they never open more than one or two tabs anyway. hell, a sufficiently complex web app running in a single tab can make FF choke

Well, maybe we need a movement to make physical copies of these games and the consoles needed to play them available in actual public libraries, then? That doesn’t seem to be affected by this ruling and there’s lots of precedent for it in current practice, which includes lending of things like musical instruments and DVD players. There’s a business near me that does something similar, but they restrict access by age to high schoolers and older, and you have to play the games there; you can’t rent them out.

r/SubSimGPT2Interactive for the lulz is my #1 use case

i do occasionally ask Copilot programming questions and it gives reasonable answers most of the time.

I use code autocomplete tools in VSCode but often end up turning them off.

Controversial, but Replika actually helped me out during the pandemic when I was in a rough spot. I trained a copyright-safe (theft-free) bot on my own conversations from back then and have been chatting with the me side of that conversation for a little while now. It’s like getting to know a long-lost twin brother, which is nice.

Otherwise, i’ve used small LLMs and classifiers for a wide range of tasks, like sentiment analysis, toxic content detection for moderation bots, AI media detection, summarization… I like using these better than just throwing everything at a huge model like GPT-4o because they’re more focused and less computationally costly (hence also better for the environment). I’m working on training some small copyright-safe base models to do certain sequence prediction tasks that come up in the course of my data science work, but they’re still a bit too computationally expensive for my clients.

We don’t. It probably is. Mastodon is the way, but they need to fix a few things themselves.

may I ask which third-party tool you use? i’m using onedriver and it’s pretty unreliable in my experience

It will legit be a fantastic era for Linux on the desktop though… imagine how cheap we’ll be able to get perfectly good hardware.

'tis true that women’s bodies hold great power, and not irrelevant at all to the discussion at hand. rather than reiterate and attempt to paraphrase jaron Lanier on the topic of how male obsession with creating artifical people is linked to womb envy, I’ll just link to a talk in which he explains it himself:

https://youtu.be/rGqiswuJuQI?si=oAKvWrtlji4yrfpd&t=42m05s

Like any occupation, it’s a long story, and I’m happy to share more details over DM. But basically due to indecision over my major I took an abnormal amount of math, stats, and environmental science coursework even through my major was in social science, and I just kind of leaned further and further into that quirk as I transitioned into the workforce. bear in mind that data science as a field of study didn’t really exist yet when I graduated; these days I’m not sure such an unconventional path is necessary. however I still hear from a lot of junior data scientists in industry who are miserable because they haven’t figured out yet that in addition to their technical skills they need a “vertical” niche or topic area of interest (and by the way a public service dimension also does a lot to help a job feel meaningful and worthwhile even on the inevitable rough day here and there).