> A new 70B open-source LLM beats Claude-3.5-Sonnet and GPT-4o! Matt Schumer, CEO from Hyperwrite AI, had an idea he wanted to try out: why not fine-tune LLMs to always output their thoughts in specific parts, delineated by tags? Even better: inside of that, you
MACHINE LEARNING
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Bridging the Gap Between AI Potential and Current Implementation
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because i feel a gap between potential of technology and current state of usage
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AI Training Progress Requires Years More Data and Compute
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Sadly you will need about 2-4 more years of training data, additional compute, and a bunch of post training before you can expect major improvements.
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Prompt Engineering Integration into Model Training Approaches
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honestly some of the technical details of AI models are beyond me. love the simplicity of this approach! prompt engineering getting baked into model training!
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Generate Synthetic Data for LLM Fine-Tuning with Minimal Examples
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Is a lack of data holding you back from training your next model?
— Predibase by Rubrik (@predibase) 5 septembre 2024
Learn how you can generate synthetic data from as few as 10 seed examples for fine-tuning an LLM that outperforms GPT-4.
Watch this 90-second or try for yourself with our free trial: https://t.co/XX3F43IRMu pic.twitter.com/1aWOigZtp1Is a lack of data holding you back from training your next model? Learn how you can generate synthetic data from as few as 10 seed examples for fine-tuning an LLM that outperforms GPT-4. Watch this 90-second or try for yourself with our free trial: https://
pbase.ai/47iRWlq -
Model Collapse Paper Misses Key Data Retention Finding
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Also the widely-shared model collapse paper ignored the earlier research that showed that models don't actually collapse at all if you keep even a bit of the original data around.
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NeuralGCM: AI Climate Modeling Breakthrough Explained
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Is NeuralGCM an atmospheric or climate model? Swipe to see the answer and why it matters. Learn more about how NeuralGCM is changing #AI modeling at: https://
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SubgoalXL: AI Breakthrough in Automated Mathematical Theorem Proving
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New blog alert Introducing SubgoalXL, a significant step forward in the field of AI-powered theorem proving. By combining novel methodologies with state-of-the-art hardware, we've demonstrated that AI can tackle increasingly complex mathematical reasoning tasks with
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AI clusters’ power consumption to rival entire countries by 2028
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> By 2028, AI Clusters will reach the power consumption of entire countries Reminder : “Scaling laws” are empirical laws saying that if you keep multiplying your compute by x10, your models will mechanically keep getting better and better. To give you an idea, GPT-3 can barely
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Challenge: Code an AI SaaS platform for pro photos in 2 days
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I set myself a small challenge: to code in 2 days a French SaaS platform that generates professional photos by training its own AI model in just 2 clicks (yes, yes…) with the latest models while respecting privacy. I'm almost done, but I have