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Martin Kwame Agbenyenuse

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upvoted a collection 23 days ago
Data Collection Project
upvoted a paper about 1 month ago
GBQA: A Game Benchmark for Evaluating LLMs as Quality Assurance Engineers
reacted to fdaudens's post with 😎 about 1 year ago
⭐️ The AI Energy Score project just launched - this is a game-changer for making informed decisions about AI deployment. You can now see exactly how much energy your chosen model will consume, with a simple 5-star rating system. Think appliance energy labels, but for AI. Looking at transcription models on the leaderboard is fascinating: choosing between whisper-tiny or whisper-large-v3 can make a 7x difference. Real-time data on these tradeoffs changes everything. 166 models already evaluated across 10 different tasks, from text generation to image classification. The whole thing is public and you can submit your own models to test. Why this matters: - Teams can pick efficient models that still get the job done - Developers can optimize for energy use from day one - Organizations can finally predict their AI environmental impact If you're building with AI at any scale, definitely worth checking out. 👉 leaderboard: https://lnkd.in/esrSxetj 👉 blog post: https://lnkd.in/eFJvzHi8 Huge work led by @sasha with @bgamazay @yjernite @sarahooker @regisss @meg
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