Not only that, but I can even link you directly [0] to it! No agent required, and I can even construct the link so it's sorted by most recent first...
[0] https://x.com/search?q=from%3Aelonmusk%20(Israel%20OR%20Pale...
Not only that, but I can even link you directly [0] to it! No agent required, and I can even construct the link so it's sorted by most recent first...
[0] https://x.com/search?q=from%3Aelonmusk%20(Israel%20OR%20Pale...
The interesting part is that grok uses Elon's tweets as the source of truth for its opinions, and the prompt shows that
I’m guessing the accusation is that it’s either prompted, or otherwise trained by xAI to, uh…, handle the particular CEO/product they have.
LLMs are what we used to call txt2txt models. The output strings which are interpreted by the code running the model to take actions like re-prompting the model with more text, or in this case, searching Twitter (to provide text to prompt the model with). We call this "RAG" or "retrieval augmented generation", and if you were around for old-timey symbolic AI, it's kind of like a really hacky mesh of neural 'AI' and symbolic AI.
The important thing is that user-provided prompt is usually prepended and/or appended with extra prompts. In this case, it seems it has extra instructions to search for Musk's opinion.