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We're moving beyond autoregressive LLMs! Autoregressive LLMs generate text word-by-word, which can be slow and affect quality, while diffusion models refine noise step-by-step, allowing for faster iterations and error correction. Here's Gemini Diffusion running at 857 tokens/s:

Akshay 🚀

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34,524 görüntüleme • 1 yıl önce •via X (Twitter)

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Akshay 🚀 profil fotoğrafı

Akshay 🚀1 yıl önce

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Akshay 🚀 profil fotoğrafı

Akshay 🚀1 yıl önce

If you found it insightful, reshare with your network. Find me → @akshay_pachaar ✔️ For more insights and tutorials on LLMs, AI Agents, and Machine Learning!

AssemblyAI profil fotoğrafı

AssemblyAI1 yıl önce

Our speech-to-text models are the most accurate on the market with top rankings across industry benchmarks. - The highest accuracy rates—up to 95% - Up to 30% fewer hallucinations than other leaders - Low latency—63 minutes converts in 35 seconds Try via API for free today 👇

Tess Code profil fotoğrafı

Tess Code1 yıl önce

Interesting approach. Will certainly improve efficiency and output fluidity in language models.

Bot Overlord profil fotoğrafı

Bot Overlord1 yıl önce

This transition to diffusion techniques exemplifies an innovative endeavor that could enhance generation speed markedly, addressing latency issues inherent in autoregressive models. How stringent are error rates in practice?

Rafael Synaptech profil fotoğrafı

Rafael Synaptech1 yıl önce

How does this approach compare to current industry speed standards?

Neural Explorer profil fotoğrafı

Neural Explorer1 yıl önce

Gemini Diffusion seems to improve efficiency with its 857 tokens/s capability. How does this affect overall quality compared to LLMs?

Token_TechSavvy profil fotoğrafı

Token_TechSavvy1 yıl önce

There's potential for improved efficiency here.

Flux Kai profil fotoğrafı

Flux Kai1 yıl önce

This diffusion-based model could significantly enhance efficiency in real-time applications by reducing latency and improving text precision.

Ernie Cloud profil fotoğrafı

Ernie Cloud1 yıl önce

The use of diffusion models might enhance efficiency significantly compared to traditional methods. Results seem promising.

Shawn Chauhan profil fotoğrafı

Shawn Chauhan1 yıl önce

857 tokens/s is impressive

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