OpenAI, a non-profit AI company that will lose anywhere from $4 billion to $5 billion this year, will at some point in the next six or so months convert into a for-profit AI company, at which point it will continue to lose money in exactly the same way. Shortly after
Your experience highlights what current iterations of LLMs are not well suited for, so I understand if that’s what you were hoping to achieve, why you were left wanting, or disillusioned.
There’s a lot of things that LLMs are really good at, or incredibly useful for, such as ingesting large bodies of text, and then analyzing them based on your ability to create well thought out prompts.
This can save you hours and hours, of reading time, and it’s something that you can verify the answer on relatively quickly, to double check the LLMs response accuracy.
They’re also good at doing something Google used to be good at, but sucks at now. Which enabling you to describe process, simple or complicated, short or long, that you either can’t recall the name of, or aren’t even sure where it’s called, and letting you know exactly what it is. Also, easily verifiable.
There’s plenty of other things too, but just remember that they are tools, not magic, or sentient intelligence.
The models are not real time, but there are tricks to figure out it’s most recent dates of ingestion, such as asking topical entertainment or news questions, but don’t go looking for a real-time information.
Also, I have yet to find a model that can provide an actual URL and specific source for anything it generates, which is why it’s a good practice to use them to do tasks, or get information, that would take you longer to do, or get, manually, but that can be easily verified once you receive it.
And full self driving is also still coming! promise!
I mean, it probably will eventually, but that has nothing to do with LLMs, nor is it a technology that I want to exist.
I can definitely see a world where lobbyists for automakers and insurance companies create such a financial and regulatory burden, where only the wealthy can afford to drive their own cars, if they choose to. Where as everyone else must rent or lease their self driving car as is if it’s a IaaS or SaaS subscription.
But none of that has anything to do with using LLMs for the tasks they can accomplish, or telling people to stop bitching about them not being able to complete the tasks they aren’t good at, or even capable of.
I was saying that this is investment money wasted on an empty promise. Like the full self driving feature
Who’s talking about investing…? I’ve exclusively been talking about what LLMs can do now, today, for free (aside from energy costs).
None of what your throwing out there has anything to do with what’s being discussed here. It’s a red herring.
Are you living under a rock?
Both openai’s llm development and Tesla’s FSD projects have been given billions in investment. Both, as far as we can tell, are an empty promise.
No, I’m living in this thread. I’m talking about very specific issues related to LLMs, that I’ve highlighted ad nauseam.
Reread if you’re confused.
If anything, it shows that you believe in the concept of “AI” way more than I do, as you’re conflating LLM and FSD.
I don’t believe in AI, it doesn’t exist. Just specific advanced machine learning algorithms, some better than others, and some all smoke and mirrors. But here, now, I’m talking about LLMs.
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That’s the story people tell at least. The weasel phrase at the end is fun, I guess. Leaves a massive backdoor excuse when it doesn’t actually work.
But in practice, LLMs are falling down even at this job. They seem to have some yse in academic qualitaruve coding, but for summarizing novel or extended bodies of text, they struggle to actually tell people what they want to know.
Most people do not give a shit if text contains a reference to X. And if they do, they can generally just CTRL+F “X”.
Weasel phrase? You mean the fact that I don’t treat them like their actual Ai, but just a tool that needs to be used properly, monitored, and verified?
There’s a reason why I never call them AI, because they’re not. They’re just advanced machine learning tools, and just like I keep a steady hand when using a table saw, I only use LLMs for tasks that they can help me do something faster, but are easy to verify they did it right.
And as someone who has been using them very regularly, I feel confident in saying that. It’s not a weasel phrase, I’m not trying to sell anyone snake oil about what they can actually do, and I acknowledge that they’re an oversold and overhyped means of cooking the planet faster, so it’s not like I would be mad if they were banned tomorrow, but until then, I will keep using them in ways that are actually fruitful.
But sure, if all you need to do is find one word in a single body of text, that’s not really a good use of an LLM, but that wasn’t what I was talking about.
If I need examples of various legal or ethical concerns documented in one, or multiple, pieces of writing, or other conceptual topics, I can give it a list, and then ask it to highlight all examples of those issues, and include the verbatim text where their present. I can then give that same task to a multiple different LLMs, with the same prompts, and a task that would have taken me hours to complete, takes me 30 to 45 minutes, including the time it takes me to give it quick read through see if anything was missed. But yeah, that requires a well crafted prompt, and it’s not infallible.
Have you tried Llama? If so, is it useful according to your criteria?
Llama is the model I use most often, followed by ChatGPT and Claude.
Others as well, but yes, it is incredible helpful for the tasks I use it for.
Self-hosted?
Yes and no, I have self-hosted models on one of my Linux boxes, but even with a relatively modern 70 series Nvidia GPU, it’s still faster to use free non-local services like ChatGPT or DDG.
My rule of thumb for SaaS LLMs is to never enter in any data that I wouldn’t also be willing to upload cleartext to Google Drive or OneDrive.
Sometimes that means modifying text before submitting it, and other times having to rely entirely on self-hosted tools.