Podcast · 156 episodes on record

OLMoE and the hidden simplicity in training better foundation models

Published

September 4, 2024

Length

10 min

Position

45 of 156

September 4, 2024

OLMoE and the hidden simplicity in training better foundation models

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OLMoE and the hidden simplicity in training better foundation models

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Summary

Ai2 released OLMoE, which is probably our "best" model yet relative to its peers, but not much has changed in the process. This is AI generated audio with Python and 11Labs. Source code: <a class="linkified" href="https://github.com/natolambert/interconnects-tools" target="_blank">https://github.com/natolambert/interconnects-tools</a> Original post: <a class="linkified" href="https://www.interconnects.ai/p/olmoe-and-building-better-llms" target="_blank">https://www.interconnects.ai/p/olmoe-and-building-better-llms</a>00:00 OLMoE and the hidden simplicity in training better foundation models 02:04 Frontier model team compute allocations 04:19 De-risking training complexity 06:40 On organizational complexity 09:05 Compounding improvements -- the key to building better language modelsFig 1: <a class="linkified" href="https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_005.png" target="_blank">https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_005.png</a> Fig 2: <a class="linkified" href="https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_007.png" target="_blank">https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_007.png</a> Fig 3: <a class="linkified" href="https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_009.png" target="_blank">https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_009.png</a> Fig 4: <a class="linkified" href="https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_011.png" target="_blank">https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_011.png</a> Fig 5: <a class="linkified" href="https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_028.png" target="_blank">https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_028.png</a> Fig 6: <a class="linkified" href="https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_030.png" target="_blank">https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_030.png</a> Fig 7: <a class="linkified" href="https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_032.png" target="_blank">https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_032.png</a> This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit <a href="https://www.interconnects.ai/subscribe?utm_medium=podcast&utm_campaign=CTA_2">www.interconnects.ai/subscribe</a>

OLMoE and the hidden simplicity in training better foundation models

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OLMoE and the hidden simplicity in training better foundation models

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A post-training approach to AI regulation with Model Specs

Futures of the data foundry business model

[Article Voiceover] Reverse engineering OpenAI's o1

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(Voiceover) Why I build open language models

Interviewing Andrew Carr of Cartwheel on the State of Generative AI

Interviewing Tim Dettmers on open-source AI: Agents, scaling, quantization and what's next

Summary