The model will output the same result, no matter the speed. What faster inference enables is more thinking in the same amount of time.
@mattshumer_
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Autocomplete for Design: Revolutionary AI Innovation Arrives
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This is utterly insane.
— Matt Shumer (@mattshumer_) 22 avril 2024
Autocomplete for design is here. https://t.co/SVbJ6JbtM4This is utterly insane. Autocomplete for design is here.
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Getting into AI: From GPT-2 fine-tuning to ChatGPT
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This was probably around late 2020, 2021. Before that I was doing a bit of fine-tuning over GPT-2, but chargpt was when I really got into it.
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Groq’s Time to First Token Performance Needs Improvement
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If Groq gets their time to first token down a bit, probably not. They still take maybe a half second to a second to get you that first token.
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Character-Level GPT Models Launch ML Training Journey
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Dude…. big fan. Your character-level GPT models were how I initially got into training models
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Cursor AI Team Likely Developing Similar Features
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I'm sure the @cursor_ai team is thinking about something similar
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RoPE Scaling Enables 16K Token Context Window Models
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Yeah — simply multiplied rope * 2, trained on long data with a MSL of 16K.
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LLaMA 3 70B enables instant code refactoring on Groq
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Using LLaMA 3 70B on @GroqInc to instantly refactor and document code.
— Matt Shumer (@mattshumer_) 22 avril 2024
The implications for software engineering are wild.
Gone are the days of waiting on an LLM for suggestions or code changes.
Now, it's an instant feedback loop.
Demo link in the comments: pic.twitter.com/joLJy4oJ3TUsing LLaMA 3 70B on @GroqInc to instantly refactor and document code. The implications for software engineering are wild. Gone are the days of waiting on an LLM for suggestions or code changes. Now, it's an instant feedback loop. Demo link in the comments:
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LLaMA 3-based model deployment nearing completion
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Very soon. This is one of the last things I have to get working well before we can push a LLaMA 3-based model live.