Artificial Intelligence #164

Hey, in this issue: a list of totally open alternatives to ChatGPT; how AI could write our laws; techniques to make your PyTorch models train much faster; PyTorch 2.0: faster, more pythonic, and dynamic than ever; and more.

This issue is sponsored by AtScale and Pachyderm.

• A list of totally open alternatives to ChatGPT
• [IEEE] Human-AI team-ups could slash chip-development costs
• [MIT TR] How AI could write our laws
• The multi-modal, multi-model, multi-everything future of AGI
• [Sponsored] Free Access | Semantic Layer Summit w/ 50+ Enterprise Data Leaders

Join us on April 26th for an in-depth look at the concept of Data Mesh and proven strategies - both technological and organizational - for achieving it. Don't miss out on this opportunity to learn how to revolutionize your data strategy.

• [Tutorial] Some techniques to make your PyTorch models train (much) faster
• [Project] Alpaca-30B: Facebook's 30B parameter LLaMa fine-tuned on the Alpaca dataset (weights)
• [Sponsored] Rise of the Canonical Stack in Machine Learning
• [Project] nanoT5: a repository for pre-training T5-style LLMs under a limited budget in PyTorch
• PyTorch 2.0: faster, more pythonic, and dynamic than ever

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