Writing AI software is one thing. Making sure you can deploy changes quickly and making sure your software is scaleable is another. Learning MLOps correctly will help you scale your application.

#MLOps #AI #ArtificialIntelligence #MachineLearningOperations #MachineLearning

https://medium.com/@heyjoshlee/mlops-what-it-is-and-why-it-matters-for-companies-leading-with-ai-73ccef55dd71

Beyond the Hype: The QCon AI agenda is live!

Hear from OpenAI, NVIDIA, Meta, and Google on:

Agentic Architectures (Tool/Agent Separation)
AI-Native Engineering
RFT/Reinforcement Learning in Practice
Defense Against Deepfakes

Implement AI reliably. Register now: https://bit.ly/42irze5

Is your AI evaluation stuck at precision and recall?

At QCon AI, Mallika Rao @Netflix unpacks a multi-layered evaluation framework that goes beyond metrics to include product safety, user experience, and infra robustness.

Day 8 – Final of the LLM Observability Mini-Course
Prometheus + Grafana to monitor LLM apps
Metrics: requests, errors, latency
Dashboards + alerts
Integration via docker-compose and prometheus.yml
#LLM #Observability #MLOps #Grafana #Prometheus #AI #Python #LangChain #XavierDataLabs

It'sand it's time for another #MLOps Edinburgh Meetup!

In October we are joined by Joan Figuerola Hurtado talking about “From Blue Links to Answers: How Agents Enable A New Era of Information Access and Discovery" and Richard Bownes on "Bring-your-own-tooling in the age of AI" . https://luma.com/u8344qcq

Common AI and Machine Learning Term
Core Concepts

Artificial Intelligence (AI): It refers to the ability of machines to mimic certain aspects of human intelligence, such as learning, reasoning, and decision-making.

https://geekshailender.blogspot.com/

#ArtificialIntelligence #MachineLearning #DeepLearning #GenerativeAI #LargeLanguageModels #PromptEngineering #MLOps #AITools #FullStackDeveloper #TechEnthusiast #Jacksonville #JaxTech #OnlyInJax #HimachalPradesh

NEW on We Open Source

Richard Shan explains why DevOps tools don’t cut it for LLMs—and shares 3 key metrics to monitor for reliable performance: coherence, accuracy & latency.

Read the article: https://allthingsopen.org/articles/reliable-llm-performance-ai-observability

Inworld opens internal AI toolkit to all developers https://www.developer-tech.com/news/inworld-opens-internal-ai-toolkit-all-developers/ #inworld #developers #coding #programming #mlops #ai #tech #news #technology

Level up your MLOps game!

"The Hidden Architecture of Trust" explores how robust metadata management creates more reliable and transparent AI systems.

Discover code-level implementation with tools like MLflow & DVC—perfect for those building the next generation of AI workflows.

Let's make AI more reproducible together!

https://dougortiz.blogspot.com/2025/08/the-hidden-architecture-of-trust-why.html

The "full-stack" ML engineer is here. Are you one of them?

Seeing more and more companies merge ML engineering and MLOps into a single role.

Engineers are now expected to know modeling, Docker, Kubernetes, CI/CD, and cloud infrastructure.

How do you cope?

What's your take?

Is this the new standard in machine learning?

https://youtube.com/shorts/-CAWUh1Bz8A

#MachineLearning #MLOps #Tech #DataScience #Developer #Burnout #Doug Ortiz

Wusstet ihr, dass eure Software-Architektur aussieht wie euer Organigramm? Conway's Law zeigt: Teams, die nicht miteinander reden, bauen auch keine integrierten Systeme!

Besonders spannend bei ML-Pipelines und verteilten Teams - da wird's richtig wild!

Was sind eure Erfahrungen mit Team-Strukturen und System-Design?

https://goern.substack.com/p/research-report-architecture-and-people

The ML Engineer and MLOps roles are merging. Companies are looking for a single person to build AND deploy models from start to finish.

This "full-stack" approach promises efficiency but at what cost? More pay, but also more pressure and risk of burnout.

What are your thoughts on this trend in the machine learning space? Is this the new standard?

Video: https://www.youtube.com/shorts/bOAND8zOkYE

#MachineLearning, #MLOps, #AI, #TechCareers, #WorkLifeBalance