How do you protect data sovereignty, reduce cloud costs, and future-proof your infrastructure investments? On Nov. 10, top experts—including @nvidia
's VP of Enterprise Computing, @ManuvirDas
—explain how you do all that in the real world. #MLOps Register: https://
domino.buzz/3UjejzD
TOOLS
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Data Sovereignty and Cloud Cost Optimization in MLOps
By
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LangChain 0.0.9: Hugging Face Embeddings and API Key Management
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LangChain version 0.0.9 Support for embeddings with @huggingface through `sentence_transformers` from @abdrahman_issam (example notebook: https://colab.research.google.com/drive/1lbjO0-nITa5c8RXfagsIZDqxZ_mVl_2k?usp=sharing…) Better support for different ways of specifying API keys from @camjuu
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AudioGen: Meta’s Revolutionary Text-to-Audio AI Model
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AudioGen, Meta AI's text-to-audio AI model https://actuia.com/actualite/audiogen-le-modele-dia-text-to-audio-de-meta-ai/
… #AI #artificialintelligence #audio -
YOLOv7 Pose: Single-Stage Multi-Person Keypoint Detection
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Unlike conventional Pose Estimation algorithms, YOLOv7 pose is a single-stage multi-person keypoint detector. It is similar to the bottom-up approach but heatmap free. It is an extension of the one-shot pose detector – YOLO-Pose. https://
learnopencv.com/yolov7-pose-vs
-mediapipe-in-human-pose-estimation/
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#yolov7 #poseestimation -
MidJourney Progress Examples Summer Launch
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A few more examples – and remember, MidJourney just launched this summer, so this is a couple of months of progress (and this is without optimizing the prompts for the new version of the software, which would require some new approaches to get right)
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Andrew’s Takahe Project Development Gains Excitement
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I'm excited about the one Andrew is building at the moment – haven't looked for any others yet though https://
github.com/andrewgodwin/t
akahe
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NLLB-200 Achieves Lowest Content Deletion Rate Among Translation Services
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NLLB-200 sees only 0.13% of translated content deleted. That’s the lowest percentage across all machine translation services available on the platform, suggesting that the resulting translations are being understood & accepted. 3/5
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NLLB-200 Achieves Superior Translation Quality Across All Languages
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Across all languages, NLLB-200 is seeing the best results for translations modified <10% compared to all other MT services on the platform — a strong signal for the quality of translations that are being generated. 4/5
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NLLB-200 becomes third most-used translation engine in four months
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NLLB-200 now represents 3.8% of all machine translations on the platform. This makes it the third most-used machine translation engine across all published translations just four months after launch. 2/5
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No Language Left Behind Improves Wikipedia Translation Tool Usage
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In July, we launched No Language Left Behind to more languages in @Wikimedia
’s Content Translation tool that helps Wikipedia editors jumpstart article translation — a new report is already showing encouraging impact on usage & translation quality https://
bit.ly/3NO63VR /5