>You can ask 4o about this yourself. Here's what it said to me:
>"So while I’m deeply multimodal in cognition (understanding and coordinating text + image), image generation is handled by a linked latent diffusion model, not an end-to-end token-unified architecture."
Models don't know anything about themselves. I have no idea why people keep doing this and expecting it to know anything more than a random con artist on the street.
This is overly cynical. Models typically do know what tools they have access to because the tool descriptions are in the prompt. Asking a model which tools it has is a perfectly reasonable way of learning what is effectively the content of the prompt.
Of course the model may hallucinate, but in this case it takes a few clicks in the dev tools to verify that this is not the case.
>Of course the model may hallucinate, but in this case it takes a few clicks in the dev tools to verify that this is not the case.
I don't know - or care to figure out - how OpenAI does their tool calling in this specific case. But moving tool calls to the end user is _monumentally_ stupid for the latency if nothing else. If you centralize your function calls to a single model next to a fat pipe it means that you halve the latency of each call. I've never build, or seen, a function calling agent that moves the api function calls to client side JS.
You should check out Claude desktop or Roo-Code or any of the other MCP client capable hosts. The whole idea of MCP is providing a universal pluggable tool api to the generative model.
They can. Fine tune them on documents describing their identity, capabilities and background. Deepseek v3 used to present itself as ChatGPT. Not anymore.
>Like other AI models, I’m trained on diverse, legally compliant data sources, but not on proprietary outputs from models like ChatGPT-4. DeepSeek adheres to strict ethical and legal standards in AI development.
> They can. Fine tune them on documents describing their identity, capabilities and background. Deepseek v3 used to present itself as ChatGPT. Not anymore
Yes, but many people expect the LLM to somehow self-reflect, to somehow describe how it feels from its first person point of view to generate the answer. It can't do this, any more than a human can instinctively describe how their nervous system works. Until recently, we had no idea that there are things like synapses, electric impulses, axons etc. The cognitive process has no direct access to its substrate/implementation.
If fine-tune ChatGPT into saying that it's an LSTM, it will happily and convincingly insist that it is. But it's not determining this information in real time based on some perception during the forward pass.
I mean there could be ways for it to do self reflection by observing the running script, perhaps raise or lower the computational cost of some steps, check the timestamps of when it was doing stuff vs when the GPU was hot etc and figure out which process is itself (like making gestures in front of a mirror to see which person you are). And then it could read its own Python scripts or something. But this is like a human opening up their own skull and look around in there. It's not direct first-person knowledge.
>"So while I’m deeply multimodal in cognition (understanding and coordinating text + image), image generation is handled by a linked latent diffusion model, not an end-to-end token-unified architecture."
Models don't know anything about themselves. I have no idea why people keep doing this and expecting it to know anything more than a random con artist on the street.