Wonder how the survey was sent out and whether that affected sampling.
Regardless, with -3-4k responses, that’s disappointing, if not concerning.
I only have a more personal sense for Lemmy. Do you have a source for Lemmy gender diversity?
Anyway, what do you think are the underlying issues? And what would be some suggestions to the community to address them?
I use gitlab ci mainly and dabble in github actions. Can you clarify how “Not even Github managed to pull that off”? IIRC, actions is quite featureful and it’s open-source, so I assume that can be run with self-hosted runners as well.
I’m also curious. A quick search came up with these. Not sure which one is most reliable/updated
Many things are called “AI models” nowadays (unfortunately due to the hype). I wouldn’t dismiss the tools and methodology yet.
That said, the article (or the researchers) did a disservice to the analysis by not including a link to the report (and code) that outlines the methodology and how the distribution of similarities look. I couldn’t find a link in the article and a quick search didn’t turn up anything.
you should try to ask the same question using xAI / Grok if possible. May also ask ChatGPT about Altman as well
Based on this reddit comment, that website is not affiliated with the magic-wormhole CLI tool
I believe experiments like these should move slower and with more scrutiny. As in more animal testing before moving on to humans, esp. due to the controversies surrounding Neuralink’s last animal experiments.
re: your last point, AFAIK, the TLDR bot is also not AI or LLM; it uses more classical NLP methods for summarization.
Is there a database tracking companies that start out with good intentions and then eventually gets bought out or sells out their initial values? I’m wondering what the deciding factors are, and how long it takes for them to turn.
Reminds me of this article https://www.alexmurrell.co.uk/articles/the-age-of-average where the author pulls in different examples of designs and aesthetics converging to some “average”.
I’m feeling conflicted with these trends, on one hand it seems like things are becoming more accessible, while on another, feels like a loss.
This especially may be relevant with generative AI - at least for the very few generative arts I look at, at some point they start to feel the same, impersonal.
They don’t seem to allow account deletions. Does it mean that this could include accounts that they still keep but people don’t use their services anymore?
suggests either these people are so detached from reality, or they are appealing this to very specific sets of people under the guise of a general appeal
Something like this, unless they know the root cause (I didn’t read the paper so not sure if they do), or something close to it, may still be exploitable.
what are the other alternatives to ENV that are more preferred in terms of security?
yeah I guess maybe the formatting and the verbosity seems a bit annoying? Wonder what the alternatives solution could be to better engage people from mastodon, which is what this bot is trying to address.
edit: just to be clear, I’m not affiliated with the bot or its creator. This is just my observation from multiple posts I see this bot comments on.
I’m curious, why is this bot currently being downvoted for almost every comment it makes?
Thanks for the suggestions! I’m actually also looking into llamaindex for more conceptual comparison, though didn’t get to building an app yet.
Any general suggestions for locally hosted LLM with llamaindex by the way? I’m also running into some issues with hallucination. I’m using Ollama with llama2-13b and bge-large-en-v1.5 embedding model.
Anyway, aside from conceptual comparison, I’m also looking for more literal comparison, AFAIK, the choice of embedding model will affect how the similarity will be defined. Most of the current LLM embedding models are usually abstract and the similarity will be conceptual, like “I have 3 large dogs” and “There are three canine that I own” will probably be very similar. Do you know which choice of embedding model I should choose to have it more literal comparison?
That aside, like you indicated, there are some issues. One of it involves length. I hope to find something that can build up to find similar paragraphs iteratively from similar sentences. I can take a stab at coding it up but was just wondering if there are some similar frameworks out there already that I can model after.
yeah agreed with your sentiment. I think it’s good to have an intuition about something, but it’s much better when there’s data to back it up.
Cuz then, they can do the same with others, say Youtube or other streaming services, and start to compare the numbers, like % of ads, what types of ads, how long are the ads relative to content, how many of these ads are political, how many of these ads may be harmful, …
Having these numbers can be quite handy for other researchers and regulators to look into these issues more concretely, rather than just say, “as your brothers and sisters already know, tiktok serves ads”
got into coding cuz I found out that’s how I can automate analysis and play with research questions more easily.
In this scenario, I think the pronouns should be changed regardless of the gender of the devs. Here’s a screenshot of the suggested changes, which are quite minimal. The reason why I think this should be changed is because this is in the build instructions for a project that many devs are needed. Hence, they should at least be open to discussion rather than shutting it off completely. And honestly, this is a small change. Their reaction to this made it more political than the commit itself, and honestly the commit was not political in my mind. Their reaction also demonstrated how they respond to contributions, and an ambitious project like this will need a lot of contributors. If their leadership keeps this up, it is very off-putting for people to collaborate with them.