There is generally something about the Gemini models which feels a bit different than Claude, ChatGPT or Mistral.
I always have the feeling that I'm chatting with a model oriented towards engineering tasks. The seriousness, lack of interest of being humorous or cool.
I don't know if this is because I interact with Gemini only through AI Studio, and it may have different system instructions (apart from those one can add oneself, which I never do) than the one at gemini.google.com.
I never use gemini.google.com because of the lack of a simple export feature. And it's not even possible to save one chat to disk (well, neither do the others), I just wish it did.
AI Studio saving to Google Drive is really useful. I lets you download the chat, strip it of verbose things like the thinking process, and reuse it in a new chat.
I wish gemini.google.com had a "Save as Markdown" per answer and for the complete chat (with a toggle to include/exclude the thinking process). Then it would be a no brainer for me.
It's the same as if Google Docs would not have an "Download.." menu entry but you could only "save" the documents via Takeout.
I've noticed 4o uses a lot of emojis, and, in general, is very enthusiastic. I find it funny. If I want a more formal bot, I switch to one of the o3 family.
I use a very simple custom system prompt (not on my work machine at the moment, but essentially something along the lines of "for technical questions, please be concise and to the point, and when asked for code, omit explanations and emit just the code itself unless I ask for explanations"), and it does wonders.
It’s interesting that my default prompt is exactly the opposite one: “do not write the code unless I ask for it specifically”. I like to use LLMs as a discussion partner, but writing code is trivial after a good discussion and I can do that myself
So do I. But it's not like ChatGPT isn't flexible, the code it generates for small tasks is really good, and the site is faster than AI Studio.
For example, if I want to quickly create a Python script to list all VMs via libvirt and output their attached drives and filesystems, that's a task for ChatGPT.
But for the things where I don't want an AI to "suck up" to me and instead "stay professional", that's Gemini.
You put into words something I've been struggling to describe for a long time. Gemini gives short, succinct responses with whatever information you need and minimal anything else. ChatGPT, Claude both fill text with mannerisms, formatting, etc.
I didn't realize just how big the difference was until I tested it.
"How do I clear a directory of all executable files on Debian?"
Gemini 2.0 Flash: (responses manually formatted)
find /path/to/directory -type f -executable -delete
Replace /path/to/directory with the actual path.
ChatGPT: (full link [1])
To clear (delete) all executable files from a directory on Debian (or any Linux system), you can use the find command. Here's a safe and effective way to do it:
# [checkmark emoji] Command to delete all executable files in a directory (not recursively): [..]
# [magnifying glass emoji] Want to preview before deleting? [..]
# [caution sign emoji] Caution: [..]
I have been using the Obsidian web clipper to export chats from ChatGPT and Claude web versions to nicely-formatted md files. You can save md to Obsidian or download it as a standalone file. It doesn’t support Gemini yet though.
2.5 has been amazing for programming. I just send it entire repo as context when I am lazy and then ask it for entire modified files back with the (medium sized) change. It almost always works! I wish to either start using cursor or some vscode extension to do this from ide itself.
I think Grok is the best for asking about current events but I kind of hate how it always tries to turn everything into a conversation. But that's just my opinion! What do you think is the most annoying feature about Grok?
> Next, in response to a question about the vulnerabilities in the Salt Typhoon description, Sec-Gemini v1 outputs not only vulnerability details (thanks to its integration with OSV data, the open-source vulnerabilities database operated by Google), but also contextualizes the vulnerabilities with respect to threat actors (using Mandiant data).
I remain still skeptical about LLMs in this space, although I might be proven wrong, as often happens. Nevertheless, OSV has already been a big advance, so it is great that it gets a further commitment.
Is this a "model" as in a set of transformer weights that inherently does security work or is it a system that has data lookup and or other tools along with an LLM to do the question interpretation, synthesis, and output presentation?
From the description re data integrations it sounds like the latter, unless the data mentioned is in fact used for training.
The distinction is important because a security-tuned model will have different limitations and uses than an actual pre-build security LLM app. Being an app also makes benchmarking against other "models" less straightforward.
Could be great for augmenting a cybersec professional's tasks; I'm certainly interested in trying it. However, I fear it will not be used as just one of the tools in the toolbox, and rather it will be used as something to defer (and consequently shed liability) to.
There is generally something about the Gemini models which feels a bit different than Claude, ChatGPT or Mistral.
I always have the feeling that I'm chatting with a model oriented towards engineering tasks. The seriousness, lack of interest of being humorous or cool.
I don't know if this is because I interact with Gemini only through AI Studio, and it may have different system instructions (apart from those one can add oneself, which I never do) than the one at gemini.google.com.
I never use gemini.google.com because of the lack of a simple export feature. And it's not even possible to save one chat to disk (well, neither do the others), I just wish it did.
AI Studio saving to Google Drive is really useful. I lets you download the chat, strip it of verbose things like the thinking process, and reuse it in a new chat.
I wish gemini.google.com had a "Save as Markdown" per answer and for the complete chat (with a toggle to include/exclude the thinking process). Then it would be a no brainer for me.
It's the same as if Google Docs would not have an "Download.." menu entry but you could only "save" the documents via Takeout.
> The seriousness, lack of interest of being humorous or cool.
I love this. When ChatGPT compliments me on my great question or tries to banter it causes me great despair.
I've noticed 4o uses a lot of emojis, and, in general, is very enthusiastic. I find it funny. If I want a more formal bot, I switch to one of the o3 family.
I use a very simple custom system prompt (not on my work machine at the moment, but essentially something along the lines of "for technical questions, please be concise and to the point, and when asked for code, omit explanations and emit just the code itself unless I ask for explanations"), and it does wonders.
It’s interesting that my default prompt is exactly the opposite one: “do not write the code unless I ask for it specifically”. I like to use LLMs as a discussion partner, but writing code is trivial after a good discussion and I can do that myself
Every now and then 4o seems to get a bit drunk and use tonnes of emojis or start swearing when I haven’t sworn myself in the chat.
The other day I asked a fairly innocuous question and it LOLed and said it’d give me the ‘no Bullshit answer’
I've had 4o start off its response with a Smiling Face with Sunglasses emoji by the heading unprompted lol.
edit: does hacker news filter out emojis? TIL (there should be emojis after this colon: )
So do I. But it's not like ChatGPT isn't flexible, the code it generates for small tasks is really good, and the site is faster than AI Studio.
For example, if I want to quickly create a Python script to list all VMs via libvirt and output their attached drives and filesystems, that's a task for ChatGPT.
But for the things where I don't want an AI to "suck up" to me and instead "stay professional", that's Gemini.
You put into words something I've been struggling to describe for a long time. Gemini gives short, succinct responses with whatever information you need and minimal anything else. ChatGPT, Claude both fill text with mannerisms, formatting, etc.
I didn't realize just how big the difference was until I tested it.
"How do I clear a directory of all executable files on Debian?"
Gemini 2.0 Flash: (responses manually formatted)
ChatGPT: (full link [1]) [1] https://chatgpt.com/share/67f055c8-4cc0-8003-85a6-bc1c7eadcc...> And it's not even possible to save one chat to disk (well, neither do the others), I just wish it did.
Ask Claude to generate a .md of the conversation, it will do that with the option to download that or a PDF of it. A lovely, but well hidden feature!
Thanks for the tip. I tested it and this also works with Gemini and ChatGPT.
The only drawback I see is that it requires enough free space in the context window to duplicate the visual part of the chat.
I have been using the Obsidian web clipper to export chats from ChatGPT and Claude web versions to nicely-formatted md files. You can save md to Obsidian or download it as a standalone file. It doesn’t support Gemini yet though.
https://github.com/obsidianmd/obsidian-clipper
2.5 has been amazing for programming. I just send it entire repo as context when I am lazy and then ask it for entire modified files back with the (medium sized) change. It almost always works! I wish to either start using cursor or some vscode extension to do this from ide itself.
It doesn't seem as popular, but I've found Grok to treat you the least like a child and provide good answers. Especially with more complicated tasks.
I think Grok is the best for asking about current events but I kind of hate how it always tries to turn everything into a conversation. But that's just my opinion! What do you think is the most annoying feature about Grok?
^ like that.
how is that related to the post?
> Next, in response to a question about the vulnerabilities in the Salt Typhoon description, Sec-Gemini v1 outputs not only vulnerability details (thanks to its integration with OSV data, the open-source vulnerabilities database operated by Google), but also contextualizes the vulnerabilities with respect to threat actors (using Mandiant data).
I remain still skeptical about LLMs in this space, although I might be proven wrong, as often happens. Nevertheless, OSV has already been a big advance, so it is great that it gets a further commitment.
Is this a "model" as in a set of transformer weights that inherently does security work or is it a system that has data lookup and or other tools along with an LLM to do the question interpretation, synthesis, and output presentation?
From the description re data integrations it sounds like the latter, unless the data mentioned is in fact used for training.
The distinction is important because a security-tuned model will have different limitations and uses than an actual pre-build security LLM app. Being an app also makes benchmarking against other "models" less straightforward.
It's interesting how we're seeing the emergence of specialized models, much like trained humans.
What's old is new again. Pretty much all ML and statistical models were specialized for a single task / domain.
Could be great for augmenting a cybersec professional's tasks; I'm certainly interested in trying it. However, I fear it will not be used as just one of the tools in the toolbox, and rather it will be used as something to defer (and consequently shed liability) to.
Has anybody been able to shed liability to AI yet?
In the legal sense? I'm not sure.
In the corporate day-to-day? Absolutely.