Congratulations to the team @mosaicml for launching this exciting new model! Advanced LLMs like MosaicML’s and our own are changing the game for developers everywhere. How did we get here and what comes next?
AI
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SQL Meets Document Model: Hybrid Database Innovation
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Have your SQL cake and eat it, too, but with the power of the document model? Sounds tasty!
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Multi-framework world: JAX, TensorFlow, and PyTorch coexistence
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I'd add JAX to the list as well. In my view all three frameworks are here to stay for the long term and you should have at least some familiarity with all three. We're in a multi-framework world now. For applied ML & production, TF remains the most well-rounded option.
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PyTorch Preference: Balancing Ease of Use with Flexibility
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For me it's PyTorch because I like the trade-off between being ease of use but also being flexible and customizeable. Plus almost all people I interact with (research and companies) are using PyTorch. But yeah, I think your mileage may vary based on your collaborators.
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Contrastive Search vs Greedy Search for LLM Generation
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Yeh! Would deffo recommend contrastive search. It works quite well (however, over generates sometime ) Greedy search simply results in lost context.
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Fine-tuned Models Performance on Multilingual Translation Tasks
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Agreed! From my experience, it works well on languages that were abundant in the train set and also had lang -> en translate pairs. I’ll run some experiments to see how well do fine-tuned models perform. Quite lovely to see ya already using this
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Deep Learning Expertise Shortage More Critical Than GPU Scarcity
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The shortage of folks who actually understand how deep learning works and what it can/cannot do is gearing up to be even more dire than the upcoming GPU shortage.
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Whisper Transcription Capabilities and Language Translation Features
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Ha! Semantics – in this case we literally force it to transcribe into a target language. So, technically you can say it is translating! Whisper traditionally only translates from language “X” into English.
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Databricks Acquires MosaicML for $1.3B in AI Database Battle
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Databricks’s $1.3 billion buy of MosaicML is a battle for the future of the database At the heart of MosaicML’s approach is the “lottery ticket hypothesis of Jonathan Frankle and Michael Carbin of MIT. @MosaicML @databricks @OpenAI $ORCL $MDB $BASE $MSFT #investing #AI
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Fabric positioned between PyTorch and Trainer abstraction levels
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Glad to hear it's useful! Btw if you are already using the Trainer, then you probably don't need Fabric. I would think of Fabric as a thing between pure PyTorch and using the Trainer 🙂