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Scaling Up Test-Time Compute with Latent Reasoning with Jonas Geiping - #723

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

CHAPTER

Scaling Challenges in AI Model Development

This chapter explores the hurdles encountered while scaling a model from millions to billions of parameters, focusing on supercomputer constraints and outdated hardware. It highlights innovative solutions for optimizing resource use and addresses the importance of reproducibility in machine learning experiments, concluding with a commitment to open-source contributions.

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