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RESEARCH
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PyTorch dominance in latest LLM and vision transformer research
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That's totally true, but I think the problem is once you want to adopt or use more of the recent (research) stuff and/or need more customization. E.g., all the latest LLM and vision transformer is basically exclusively PyTorch.
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Live Panel on Future of LLMs with MosaicML Chief Scientist
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Join us this Wednesday for a live panel discussion with @mosaicml
’s Chief Scientist @jefrankle and our CEO @amasad to learn more about the future of LLMs. Our VP of AI @pirroh will be facilitating this illuminating conversation. -
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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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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Testing Model Performance on Untrained Tasks: Benchmarking Results
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Quick caveat: It's a task that the model isn't explicitly trained on, so test it thoroughly before us We'll run more benchmarks this week and share our findings soon! Help us test it better? 🙂
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Convergence Analysis of Unadjusted Langevin Algorithm
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On the Convergence of the Unadjusted Langevin Algorithm https://
bit.ly/3Cy99sj #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Guide pratique sur l’utilisation des LLMs : modèles, données et applications
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Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond This survey paper provides a comprehensive and practical guide on working with LLMs for various settings(in-context learning & fine-tuning). I like how it approach LLMs usage in lens of models, data, and
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SAS Vrushali Sawant: Three Principles for Inclusive Technology Innovation
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SAS' Vrushali Sawant offers 3 guiding principles for making inclusivity a priority for innovation. She writes: "Recognizing and mitigating bias are important steps toward shaping a future where technology will be inclusive and fair." http://
2.sas.com/6019PBDzf