891–900 of 1001 posts
Is it me, or did it still get at least three placements of components (RAM and PCIe slots, plus it's DisplayPort and not HDMI) in the motherboard image[0] completely wrong? Why would they use that as a promotional image? 0: https://images.ctfassets.net/kftzwdyauwt9/6lyujQxhZDnOMruN3f...
And here is Gemini 3: https://media.licdn.com/dms/image/v2/D5610AQH7v9MtrZxxug/ima...
In my experience, the best models are already nearly as good as you can be for a large fraction of what I personally use them for, which is basically as a more efficient search engine. The thing that would now make the biggest difference isn't "more intelligence", whatever that might mean, but better grounding. It's still a big issue that the models will make up plausible sounding but wrong or misleading explanations…
I agree, but the question is how better grounding can be achieved without a major research breakthrough. I believe the real issue is that LLMs are still so bad at reasoning. In my experience, the worst hallucinations occur where only handful of sources exist for some set of facts (e.g laws of small countries or descriptions of niche products). LLMs know these sources and they refer to them but they are interpreting t…
One of these days I had a doubt about something related to how pointers work in Swift and I tried discussing with ChatGPT (don’t remember exactly what, but it was purely intellectual curiosity). It gave me a lot of explanations that seemed correct, but being skeptical and started pushing it for ways to confirm what it was saying and eventually realized it was all bullshit.
This kind of thing makes me basically wary of using LLMs for anything that isn’t brainstorming, because anything that requires knowing information that isn’t easily/plentifully found online will likely be incorrect or have sprinkles of incorrect all over the explanations.
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That’s not a very useful observation though is it? The purpose of mechanisation is to standardise and over the long term reduce errors to zero. Otoh “The final truth is there is no truth”
A lot of mechanisation, especially in the modern world, is not deterministic and is not always 100% right; it's a fundamental "physics at scale" issue, not something new to LLMs. I think what happened when they first appeared was that people immediately clung to a superintelligence-type AI idea of what LLMs were supposed to do, then realised that's not what they are, then kept going and swung all the way over to "the…
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No-one should have the expectation LLMs are giving correct answers 100% of the time. It's inherent to the tech for them to be confidently wrong Code needs to be checked References need to be checked Any facts or claims need to be checked
"confidently" is a feature selected in the system prompt. As a user you can influence that behavior.
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No, it's not the same. Search results send/show you one or more specific pages/websites. And each website has a different trust factor. Yes, plenty of people repeat things they "read on the Internet" as truths, but it's easy to debunk some of them just based on the site reputation. With AI responses, the reputation is shared with the good answers as well, because they do give good answers most of the time, but also h…
Community notes on X seems to be one of the highest profile recent experiments trying to address this issue
For the first time, I've actually hidden an AI story on HN. I can't even anymore. Sorry this is not going anywhere.
How this is different to any other post announcing an incremental improvement in an app or service?
Again I just tap the sign. All of your benchmarks mean nothing to me until you include Claude Sonnet on them. In my experience, GPT hasn’t been able to compete with Claude in years for the daily “economically valuable” tasks I work on.
Claude is pretty trash for anything besides coding
I feel there is a point when all these benchmarks are meaningless. What I care about beyond decent performance is the user experience. There I have grudges with every single platform and the one thing keeping me as a paid ChatGPT subscriber is the ability to sort chats in "projects" with associated files (hello Google, please wake up to basic user-friendly organisation!) But all of them * Lie far too often with confi…
I'm always impressed how fast people get used to new things. couple of years ago something like chatgpt was completely impossible, and now people complain it something's does mit do what you told it to and sometimes lies. (not saying your points are not valid or you should not raise them) Some of the points are just not fixable at this point due to tech limitations. A language model currently simply has no way to giv…
In my experience, the best models are already nearly as good as you can be for a large fraction of what I personally use them for, which is basically as a more efficient search engine. The thing that would now make the biggest difference isn't "more intelligence", whatever that might mean, but better grounding. It's still a big issue that the models will make up plausible sounding but wrong or misleading explanations…
My biggest problem with LLM's at this point is that they produce different and inconsistent results or behave differently, given the same prompt. The better grounding would be amazing at this point. I want to give an LLM the same prompt on different days and I want to be able to trust that it will do the same thing as yesterday. Currently they misbehave multiple times a week and I have to manually steer it a bit whic…