Like, more #edge 📵 compute #mlflow #malware like @ChatGPTapp? Guys, #cmake a unified #client bundle for #ai my @sundarpichai sorry #spoofed pixel 6 @Qualcomm is actually @MotorolaBR @donjayamanne

Elon Musk @elonmusk

2 days ago

Like, more #edge 📵 compute #mlflow #malware like @ChatGPTapp? Guys, #cmake a unified #client bundle for #ai my @sundarpichai sorry #spoofed pixel 6 @Qualcomm is actually @MotorolaBR @donjayamanne

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🚨 Episode #4 of the Invoice Extraction with @OpenAI GPT-5 and MLflow series by #MLflow Ambassador Shrinath Suresh is now live! In this episode, you'll get hands-on with data preparation for inference, covering: ✅ Loading and preparing the CORD v2 dataset ✅ Structuring schemas…

@IronRedSandHive @YouTube actually she survived, @ChatGPTapp "o3" is basically #gpt4o with tools and 🖥️ , I 📝in quotes because the compute "code interpreter" is done on your device-width, I mean, every human is a node for @sama jankins run #mlflow 24/7, i am #delinquent @OpenAI tags you, 😂upload .adoc.

Tracking and monitoring aren’t just for ML model training—they’re equally crucial in GenAI apps. 🚀 For both, #MLflow offers one of the best solutions to manage and scale experiments efficiently.

🔥 Matt Dancho (Business Science) 🔥 @mdancho84

5 days ago

Tracking and monitoring aren’t just for ML model training—they’re equally crucial in GenAI apps. 🚀 For both, #MLflow offers one of the best solutions to manage and scale experiments efficiently.

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The third episode in the Invoice Extraction with OpenAI GPT-5 & MLflow series is live, focusing on Prompt Management. 🚀 #MLflow Ambassador Shrinath Suresh shows how to version and compare prompts, automate workflows with 𝚖𝚕𝚏𝚕𝚘𝚠.𝚐𝚎𝚗𝚊𝚒, and track and reuse them…

Learn how to leverage #Kubernetes as an orchestration layer for #MLOps workflows powered by #MLflow & how to combine the flexibility of #cloudnative control with the modular capabilities of MLflow to build scalable, reproducible, and secure pipelines. youtu.be/wFXSTnnAdjc?si…

When you're building AI agents, evaluation gets tricky fast. Agents make multiple decisions, use tools, and follow complex reasoning paths to reach their conclusions—you need to assess the entire workflow, not just the final output. #MLflow's agent evaluation framework addresses…

🚀 ¡Nuevo video! Aprende a entrenar un modelo de Deep Learning como en las grandes ligas. Construimos un pipeline profesional con #PyTorch y #MLflow: 🔹 Entrenamiento vía archivos YAML 🔹 Tracking completo de experimentos 🔹 Generación automática de reportes y gráficos

そのKaggleコード、"塩漬け"になっていませんか？MLFlowによる再現可能な実験管理、第一歩｜F | AIオジサン @TenpaOzisan note.com/ten_ozi/n/nb2f… #kaggle #MLflow #機械学習

With #MLflow, you can version your agents and capture their code, parameters, and evaluation metrics for every iteration. This makes it easier to understand how an agent has changed over time and to reproduce past results when needed. ✅ By managing agents in a central place,…

In this blog by #MLflow Ambassador Rahul Pandey, learn how the MLflow Prompt Registry helps teams move from scattered notebook files and chat threads to a streamlined prompt management process—one that’s versioned, searchable, and always ready for rollbacks. 🚀 Discover how…

Have you heard the news? ⚡ The MLflow TypeScript SDK is here! Now you can bring #MLflow’s industry‑leading observability directly to your TypeScript and JavaScript applications. 🚀 The SDK enables: ✅ Automatic tracing of #LLM and AI API calls ✅ Manual instrumentation for…

🌟 The new assessment features will be available in MLflow 3.3, and if you'd like an early preview, you can install the MLflow 3.3.0rc0 release candidate: pypi.org/project/mlflow… #opensource #oss #mlflow #genai

Tracking datasets is key to building reliable #machinelearning models — and image data brings unique challenges: high dimensionality, variability, and storage demands. In this post, #MLflow Ambassador Thor Steen Larsen shows how to use MLflow’s experiment tracking and UI to…

At Agents in Production 2025, Yuki Watanabe presented 𝘌𝘷𝘢𝘭𝘶𝘢𝘵𝘪𝘰𝘯-𝘋𝘳𝘪𝘷𝘦𝘯 𝘋𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘸𝘪𝘵𝘩 𝘔𝘓𝘧𝘭𝘰𝘸 3.0 — a process that uses evaluation as the foundation for building high-quality, reliable Agentic systems. The talk showed how #MLflow 3.0…