ByteDance Seed công bố mô hình Stable-DiffCoder-8B-Instruct, mở đường cho AI tạo văn bản/lập trình bằng kỹ thuật diffusion. Mô hình đã được đăng tải trên Hugging Face và nhận nhiều sự chú ý từ cộng đồng.
#AI #DeepLearning #MáyHọc #ByteDance #HuggingFace #CodeAI #DiffusionModel #CôngNghệ

https://www.reddit.com/r/LocalLLaMA/comments/1qpm48y/bytedanceseedstablediffcoder8binstruct_hugging/

Explore Kuramoto models as gradient flows across spheres, unitary groups, and hyperbolic balls. https://hackernoon.com/kuramoto-models-as-gradient-flows-langevin-dynamics-and-hyperbolic-geometry #deeplearning
Kuramoto Models as Gradient Flows: Langevin Dynamics and Hyperbolic Geometry | HackerNoon

Explore Kuramoto models as gradient flows across spheres, unitary groups, and hyperbolic balls.

Learn about complex-valued ODEs, Riccati equations, and non-Euclidean dynamics for advanced Geometric Deep Learning. https://hackernoon.com/generalizing-kuramoto-models-collective-motion-on-lie-groups-and-spheres-in-machine-learning #deeplearning
Generalizing Kuramoto Models: Collective Motion on Lie Groups and Spheres in Machine Learning | HackerNoon

Learn about complex-valued ODEs, Riccati equations, and non-Euclidean dynamics for advanced Geometric Deep Learning.

== MÃ BÍ ẨN CỦA VỊ TRÍ 193: PHÁT HIỆN BẤT THƯỜNG TRONG MÃ HÓA ẢNH CỦA GEMMA 3 ==
Nghiên cứu phát hiện vị trí 193 trong 256 mã hóa hình ảnh của Gemma 3 hoạt động khác biệt (95% ảnh), không phụ thuộc không gian (không thay đổi khi xoay ảnh) và ảnh hưởng đến khả năng xử lý dữ liệu. Khi bị "đảo ngược", mô hình AI vẫn "nhìn" được nhưng trả lời hỗn loạn. #AI #ML #TríTuệNhânTạo #AIResearch #DeepLearning #NeuralNetwork #TechNews #MysteryInAI

https://www.reddit.com/r/LocalLLaMA/comments/1qpg4ty/the_my

DeepSeek OCR 2 hiện hỗ trợ định dạng CPU, MPS và CUDA, cho phép chạy cục bộ trên laptop/Mac. Cập nhật từ Dogacel mở rộng tính linh hoạt của mô hình OCR này. #DeepLearning #OCR #CPU #MPS #CUDA #MachineLearning #HọcMáy #AI #CôngNghệ

https://www.reddit.com/r/LocalLLaMA/comments/1qpf7f8/universal_deepseek_ocr_2_cpu_mps_cuda_support/

We’re looking for a way to version and catalogue self-trained deep learning models (training data, code revision, etc.) from our Tissue-Concepts family of medical foundation models.

We’ve briefly looked at #W&B, #MLflow (now integrated into GitLab), and intensely tried storing more-or-less-documented model snapshots to disk.

Has anyone had good or bad experiences with these tools in research / medical ML settings? Any recommendations?

#ComputationalPathology #datascience #deeplearning

I like W&B
I like MLflow
Dumping to disk is just fine
Something else!
Poll ends at .

The exact detail needing recall
Where it appeared earlier
How often to mention it

For example: Include the cafe's broken neon sign (from message 7) in two subtle ways per response.

Specific instructions work better than long prompts. Try this on your next scene.

#DeepLearning #NeuralNetworks #AI #PromptEngineering #AIPrompts #GenerativeAI #ProfessionalGrowth #DigitalSkills #DigitalTransformation #FutureOfWork (2/2)

Anaconda vs Miniconda vs Mamba Guide

Complete comparison of Anaconda, Miniconda, and Mamba for Python package management. Learn installation, performance differences, and when to use each tool for data science and development.

Rost Glukhov | Personal site and technical blog

#1 OT/ICS CYBERSECURITY TRAINING AND GEN AI TRAINING IN DELHI NCR AND IN INDIA
#MachineLearningTraining #LearnMachineLearning #DataScience
#DeepLearning #SkillUp #JobGuarantee #TechCareer #FutureReady #CareerInTech
#UnlockYourFuture #ITJobs
#Technology #Innovation #Python
#Coding #programminglife

visit-www.theevolvedge.com
mail - info@theevolvedge.com
ph no :+917982403420
+919311805027
6m