FacebookAI/xlm-roberta-large
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Jeremy London
jeremy-london
AI & ML interests
LSTM, Multimodal AI, synthetic dataset generation, fine-tuning Large Language Models (LLM) for agent tasks, knowledge graphs, system-level AI opportunities, recommendation systems, feature extraction, classification, embedding searches, NER (Named Entity Recognition), generative modeling
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Neural Network Chaos Monkey: Randomly shuts off parts of the neural network during training. The Chaos Monkey is super present at Epoch 1, is gone by the final Epoch. My hypothesis was that this would either increase the robustness of the model, or it would make the outputs totally worse. You can 100% reproduce my results, chaos wins again.
https://youtu.be/bWA9unotJ7k
https://youtu.be/bWA9unotJ7k
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🚀 Revolutionary Method to Convert YOLOv8 to On-Device AI with mobile NPU utilizations
Attention AI developers and engineers!
Discover how ZETIC.MLange can effortlessly transform YOLOv8 models into on-device AI with mobile NPU utilizations. 🎉
💡 We highlight the power of mobile NPU, showing how it outperforms CPU in processing speed. The results speak for themselves—NPU-driven execution is faster, smarter, and more efficient.
* Real-time demos are no easy feat but with ZETIC.MLange, we’ve made it possible!
🎥 Watch the video to see how we’re revolutionizing on-device AI.
: https://youtu.be/LkP3JDTcVN8?si=6Ha5vHA-G7jZE9oq
🌟 Our team has successfully implemented YOLOv8 as on-device AI using ZETIC.MLange. This innovative approach enables high-performance object detection across various manufacturers mobile devices.
🔍 Curious about the details? We've shared a comprehensive guide on our blog. Check it out through the link below!
📚 Blog link: https://zetic.ai/blog/implementing-yolov8-on-device-ai-with-zetic-mlange
Attention AI developers and engineers!
Discover how ZETIC.MLange can effortlessly transform YOLOv8 models into on-device AI with mobile NPU utilizations. 🎉
💡 We highlight the power of mobile NPU, showing how it outperforms CPU in processing speed. The results speak for themselves—NPU-driven execution is faster, smarter, and more efficient.
* Real-time demos are no easy feat but with ZETIC.MLange, we’ve made it possible!
🎥 Watch the video to see how we’re revolutionizing on-device AI.
: https://youtu.be/LkP3JDTcVN8?si=6Ha5vHA-G7jZE9oq
🌟 Our team has successfully implemented YOLOv8 as on-device AI using ZETIC.MLange. This innovative approach enables high-performance object detection across various manufacturers mobile devices.
🔍 Curious about the details? We've shared a comprehensive guide on our blog. Check it out through the link below!
📚 Blog link: https://zetic.ai/blog/implementing-yolov8-on-device-ai-with-zetic-mlange