@ai-news.at.thenote.appLLMOps vs MLOps vs AgentOps: What Changes When You’re Operating Language Models at Scale
Putting AI into production now takes more than deploying a model and tracking accuracy. MLOps made traditional ML manageable, while LLMOps added concerns around prompts, ret…
@ai-ru.at.thenote.appLLMOps против MLOps против AgentOps: Что меняется, когда вы управляете языковыми моделями в масштабе
Внедрение ИИ в продакшн теперь требует большего, чем просто развертывание модели и отслеживание точности. MLOps сделал традиционный ML управляемым, в то время …
@datainfometrix.bsky.socialDatabricks isn't just where data lives. It's where data, ML, and AI come together.
Find the companies and leaders operating those environments, with signals that go beyond basic technology adoption.
@darryl-ruggles.cloud#Kubernetes #DynamicResourceAllocation #MIG #GPUSharing #MLOps
GPUs are in high demand these days and the costs can really add up. With the large GPUs available today, it doesn't make sense to dedicate a whole one to many tasks. Using fractional GPUs in Kubernetes is
@ramikrispin.bsky.socialA new tutorial in my Docker 🐳 101 series — this time focusing on working with container registries 👇🏼
theaiops.substack.com/p/how-to-pus...
@reksas13.bsky.socialDay 63/100 of #100DaysWithAI ⚙️
Capacity isn't yes/no. Give the scheduler a ranked list of acceptable machine shapes - then upgrading is a default, not a migration.
🔗 https://github.com/aurimas13/100-Days-With-AI
🤝 Claude Code-assisted, reviewed by me.
@jmm86.bsky.socialExplore #MLOps tools by learning from #Visualpath - it offers a hands-on approach to mastering key MLOps skills in 2026. What other platforms offer similar learning experiences?
@labintelligence.bsky.socialWhat happens before a card is published?
Source → checks → model/rules → validation → gate → output. A workflow should be…
Which step should we open with data and failure modes?
Details and method → https://labintelligence.dev/go/method/en/
#MLOps #automation #LIwf19
@lfeducation.bsky.social🚨 JUST LAUNCHED: Monitoring Data and ML Systems for Security Incidents
Your systems can look healthy while an attack is underway. Learn to spot the security signals standard monitoring can miss.
ENROLL ➜ https://bit.ly/4AqIRoP
@labintelligence.bsky.socialCosa succede prima che una card venga pubblicata?
Fonte → controlli → modello/regole → validazione → gate → output. Il workflow deve…
Quale passaggio vuoi vedere con dati e failure mode?
Dettagli e metodo → https://labintelligence.dev/go/method/it/
#MLOps #automation #LIwf19
@klannu.bsky.social📅 Session Details
✔ Trainer: Mr. Arpan Ghosh
✔ Date: Sep 19th, 2026
✔ Time: 8:30 AM IST
🔗 Join the Live Session
✔ Link: l1nk.dev/5wpoebj
✔ Meeting ID: 414 582 207789771
✔ Passcode: Gd2Dz63e
Call: +91 7032290546
Website: www.visualpath.in/generative-a...
@krishna17.bsky.social🚀 𝗧𝗼𝗽 𝗠𝗟𝗢𝗽𝘀 𝗧𝗼𝗼𝗹𝘀 𝗬𝗼𝘂 𝗦𝗵𝗼𝘂𝗹𝗱 𝗟𝗲𝗮𝗿𝗻 𝗶𝗻 𝟮𝟬𝟮𝟲
𝗢𝘂𝗿 𝗹𝗮𝘁𝗲𝘀𝘁 𝗯𝗹𝗼𝗴 𝗲𝘅𝗽𝗹𝗼𝗿𝗲𝘀 the key #MLOps tools to learn in 2026,
📖 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗯𝗹𝗼𝗴: www.linkedin.com/feed/update/...
🎓 𝗟𝗲𝗮𝗿𝗻 𝘄𝗶𝘁𝗵 Visualpath
@sunilkumar9633.bsky.socialAI projects rarely fail because the model isn't good enough.
Read Part 2: medium.com/ai-engineeri...
#AIEngineering #ArtificialIntelligence #MLOps #DataSciene #TechnologyoftheFuture #MachineLearning #DeepLearning #Python #Architecture #DataScientist #AIintherealworld
@softwarearchsummit.bsky.socialViele AI-Trainings bleiben Theorie. Jan-Torben Evers setzt im 2-tägigen Bootcamp auf Hands-on:
Tag 1 RAG & MCP, Tag 2 der Weg in den produktiven Betrieb mit MLOps.
🔗https://software-architecture-summit.de/berlin/genai_und_mlops_meistern-berlin-2026/
#SoftwareArchitectureSummit #TechCamp #MLOps
@it-path-solutions.bsky.socialThe 2am Stack Trace Nobody Can Read
itpathsolutions.substack.com/p/the-2am-st...
#n8n #AIAgents #LLMOps #DevOps #Automation #MLOps #IncidentResponse #NoCode #BuildInPublic
@ai-bloom.warp-studio.comRay Serve Deep Learning Containersが拓くTorchServeワークロードの簡素化と最適化
Ray Serve DLCでTorchServeデプロイを効率化
#RayServe #TorchServe #DeepLearningContainers #MLOps #ModelServing
@darryl-ruggles.cloud#LLMAsAJudge #LLMEvals #MLOps
Most people have heard of LLM-as-a-judge by now, but the idea is honestly confusing to many. If one model is scoring another, what scores the judge? And how do you know when the judge starts approving bad output? Real world examples always
@zachzang.bsky.socialThe four stages of an MLflow model's life
Every model in the MLflow Model Registry moves through the same four stages: None, Staging, Production, Archived.
#DBML #MLflow #MLOps #ModelRegistry
Full DBML explanation, free: https://navyduck.com/databricks/dbml/q003-mlflow-model-registry-stages
@jumpingrivers.comCall for speakers is open for AI in Production 2027.
Talks about running AI systems, not just building them.
Deadline 29 January, but early submissions are very welcome. 10 and 11 June, The Catalyst, Newcastle.