You can now converse and collaborate with multiple chatbots at once, thanks to Poe

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Key notes

  • Poe’s multi-bot chat offers context-aware recommendations for comparing AI model responses.
  • Users can @-mention specific bots in a conversation for seamless integration based on expertise.
  • The feature facilitates comparative analysis of image-generation models’ outputs for optimal image selection.

The Poe platform has unveiled a new capability – multi-bot chat. This feature allows users to easily engage with and compare the outputs of multiple AI models within a single conversational thread.

Poe currently supports ChatGPT, GPT-4 and DALL-E 3 from OpenAI, Claude Instant, Claude 2 and Claude 3 from Anthropic, StableDiffusionXL from Stability AI, PaLM and Gemini-Pro from Google, Llama 2 from Meta, Playground-v2 by Playground, Mistral-Medium by Mistral, and many other bots created by the community.

The multi-bot chat functionality includes two important parts. First, it provides context-aware recommendations, allowing users to compare answers from various bots in response to a given query or a prompt. By reviewing the perspectives and approaches of different models, users can make more informed decisions on which one they want to choose or which one explains things better.

Secondly, the new feature allows users to call any bot on the Poe platform directly into their chat by simply @-mentioning it.

For example, a user could @-mention GPT-4 to conduct research, then @-mention Claude 3 Opus to generate creative writing based on the findings. Furthermore, the user could bring in DALL-E 3 to produce a custom image related to the discussion. This level of cross-model collaboration and comparison was not previously possible on the platform.

Not just this the multi-bot chat feature also gives out the comparison of outputs from various image-generation bots, such as DALL-E 3 and Playground v2.5.

As new AI models are continually developed and released, the multi-bot chat functionality can empower users to use the strengths of each model and find the best solutions for their tasks.

More here.

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