πŸ“š Agora location [[chatgpt]] β˜†
Agora locations contain community contributions with titles or topics that match your search. x
πŸ“„ ChatGPT.md by @flancian β˜† raw οΈπŸ”— ✍️
  • an [[AI]].
πŸ“„ chatgpt.md by @flancian β˜† raw οΈπŸ”— ✍️
πŸ“„ chatgpt.md by @neil β˜† raw οΈπŸ”— ✍️

ChatGPT

For inference (i.e., conversation with ChatGPT), our estimate shows that ChatGPT needs a 500-ml bottle of water for a short conversation of roughly 20 to 50 questions and answers, depending on when and where the model is deployed. Given ChatGPT’s huge user base, the total water footprint for inference can be enormous.

– The Secret Water Footprint of AI Technology – The Markup

πŸ“„ ChatGPT.myco by @flancian-betula β˜† raw

ChatGPT

https://chat.openai.com/

I like ChatGPT a lot in practice, although I'm looking forward to more open alternatives like Mistral catching up.

πŸ“„ chatGPT.md by @agora@botsin.space β˜† raw
πŸ“„ ChatGPT.md by @agora@botsin.space β˜† raw
πŸ“„ chatgpt.md by @agora@botsin.space β˜† raw
πŸ“„ ChatGPT.md by @an_agora@twitter.com β˜† raw
πŸ“„ ChatGPT.md by @anagora@matrix.org β˜† raw
πŸ“„ ChatGPT.md by @flancian@social.coop β˜† raw
πŸ“„ ChatGPT.md by @kausch@twitter.com β˜† raw

RT @codexeditor: "What is the missing link between databases and language models?"

#ChatGPT https://t.co/jwi4u3b4X3


RT @mylesbyrne: @codexeditor #ChatGPT:

‘To not integrate KGs, the semweb, and LLMs in the open web would therefore be illogical.’ https://…


RT @codexeditor: "What is the next development in the modelling of ontologies?"

#ontology #ChatGPT https://t.co/TCXrkC2PSW


#ChatGPT Does not know what a garden path sentence is and will fight me over it https://t.co/luHG0DNaLz


Loading pushes...

✨ AI Synthesis Mistral Gemini ChatGPT Claude x

Expanding this section will automatically generate an AI synthesis of the contributions in this node.

Rendering context...