fascinating. I wonder where the line is between the cold preserving the body and the cold causing hypothermia that could lead to death.
fascinating. I wonder where the line is between the cold preserving the body and the cold causing hypothermia that could lead to death.
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.
this is interesting, but it’s not open source yet? Couldn’t find the code. I only saw the author saying that the intent is to be open source.
I think apps like this is really interesting and could really benefit from selfhosting (either/both the LLM or the app deployment), especially due to the potential security/privacy issues, as well as lock-in issues with OpenAI.
got into coding cuz I found out that’s how I can automate analysis and play with research questions more easily.
I think many have also been wondering about version control of legislation/law documents for some time as well. But I never understand why it’s not realized yet.
such a rad pic!
Great explanation. Two question, what’s the likelihood of an SSO page being spoofed? This seems like an all-eggs-in-one-basket sitch, so what are the potential threats to this?
I remember reading that this may be already happening to some extent, eg people sharing tips on creating it on the deep web, maybe through prompt engineer, fine tuning or pretraining.
I don’t know how those models are made, but I do wonder the ones that need retraining/finetuning by using real csam can be classified as breaking the law.
lol I know you’re kidding, but there’s implication of those willing to get things implanted. Society seems to run on hype nowadays. Look at AI and how fast people are jumping on board with trying it, sometimes out of FOMO. Not to say there’s no merit, but if that FOMO feeling spreads real quick, without proper guardrails, Musk will eventually get what he wants.
Not at the cost of humanity. Plus, that statement can be recycled to defend all the horrible inventions and experiments in the past.
so u’re implying there’s potential corruption? or is there a scenario things are still legal but his (or his people’s) influence is somehow large enough to push it to be approved?
I really wonder if the FDA publishes the reviews and also the names of the reviewers. The latter may be a stretch and potentially abusive. But the former, if available, might make it easier for outside scientists to further inspect.
what really confuses me is how the FDA approves this without a few more years of animal testing and protocol refinement.
Let me see if I get your point. Are you saying most questions on Lemmy ask for opinions, which makes them look like they are asked to use for training AI models?
If so, I’m not entirely sure I agree. There’s tons of info online about any given topics, which can be very overwhelming. Maybe that causes people to prefer to seek out personal experience and opinions from others on such topics, rather than just hard cold facts.
It may also depend on which communities the questions you’re sampling are asked as well.
thanks for your answer! Is this same or different from indexing to provide context? I saw some people ingesting large corpus of documents/structured data, like with LlamaIndex. Is it an alternative way to provide context or similar?
I know nothing about “in context learning” or legal stuff, but intuitively, don’t legal documents tend to reference each other, especially the more complicated ones? If so, how would you apply in context learning if you’re not aware which ones may be relevant?
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.