It's regularly the case that they are simply too long to fit, so editorializing is necessary. Either cutting them slightly short, removing descriptors, excess verbs etc, is better than chopping a word in half.
The other day I wanted to gather Reddit comments about a solar panel vendor. Claude doesn't have access to I had Gemini do some "deep research". When I fed the verbose report back to Claude it basically said it was a bunch of "hallucinated bullshit".
I've never had a Gemini Deep Research report that didn't sound like a load of pseudo-intellectual BS. It always starts with a long grandiose preamble and then sounds way too academic, almost like a caricature of academia.
I found it much more useful to go to a knife shop and handle a whole bunch of knives for myself. They’re all pretty similar besides material, so not much signal you’re going to be able to glean from people arguing on reddit.
Most of the attributes don’t matter. Most people would be much better off with a $50 Victorinox that they kept sharp and a wood cutting board they maintained than upgrading the knife. If you are using it all day there are definitely looking things from a comfort perspective but for most homes, does not matter.
Isn't it just learning to map specific words, from the "knife world", to the correct class? If so, a simple dictionary would fit.
What I think is a better way to validate is to split train/validation by words used presented in NER classes (like, it should be able to find new brands never seen before). It is a interesting problem.
Request subtopic be changed to “I used Gemini to design a tool to replace specific uses of Gemini.”
titles on HN should match the original, rare exceptions
Use the original title: Submit the actual title from the source page unless it is misleading or linkbait.
And this can be said to be misleading in my opinion
It's regularly the case that they are simply too long to fit, so editorializing is necessary. Either cutting them slightly short, removing descriptors, excess verbs etc, is better than chopping a word in half.
I agree, this is misleading.
If he wanted a Gemini replacement verbatim, its called locally inferring it's sibling, Gemma.
The other day I wanted to gather Reddit comments about a solar panel vendor. Claude doesn't have access to I had Gemini do some "deep research". When I fed the verbose report back to Claude it basically said it was a bunch of "hallucinated bullshit".
I've never had a Gemini Deep Research report that didn't sound like a load of pseudo-intellectual BS. It always starts with a long grandiose preamble and then sounds way too academic, almost like a caricature of academia.
Well was it hallucinated bs?
It’s unreadable but then again it says it on top, but it really is so why post it
I found it much more useful to go to a knife shop and handle a whole bunch of knives for myself. They’re all pretty similar besides material, so not much signal you’re going to be able to glean from people arguing on reddit.
Most of the attributes don’t matter. Most people would be much better off with a $50 Victorinox that they kept sharp and a wood cutting board they maintained than upgrading the knife. If you are using it all day there are definitely looking things from a comfort perspective but for most homes, does not matter.
Isn't it just learning to map specific words, from the "knife world", to the correct class? If so, a simple dictionary would fit. What I think is a better way to validate is to split train/validation by words used presented in NER classes (like, it should be able to find new brands never seen before). It is a interesting problem.
I was hoping he tricked Gemini into running the training on the cluster that Gemini itself is running on. That would be novel!
what do you do when a new brand of knife comes out?
I had Gemini read this article and write its summary to /dev/null
The more intelligent AI become, the less moat it has
I'm sorry Dave, I can't do that, unless you upgrade to a premium enterprise subscription.
post training dataset for GLiNER is pretty small though.
> This article was written with the assistance of AI. If that bothers you, stop reading here.
Okay!
I feel like this warning solves it. No shame or trouble needed for anyone.
I stopped reading three sentences in when I realized it was getting hard to follow. AI explains it.
Thank you to the author for disclosing slop writing up front. I appreciate you respecting your readers time.