Mlops

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Marcus Chen

Jun 19

Perplexity held flat after INT4. Task accuracy dropped 7 points.

#machinelearning #llm #mlops #pytorch

4 min read

Elise Moreau

Jun 19

The seam our tiled upscaler left on every 4K product render

#mlops #computervision #pytorch #machinelearning

4 min read

Sahajmeet Kaur

Jun 19

Portkey Alternative: I Switched Away from Portkey. Here's the Honest Reason Why.

#ai #llm #devops #mlops

7 min read

Marcus Chen

Jun 18

Speculative decoding shifted our output distribution and evals missed it

#machinelearning #llm #mlops #pytorch

4 min read

Dishant Sethi

Jun 18

LLMOps in 2026: AI Demo to Production Guide

#ai #llmops #kubernetes #mlops

8 min read

Naveen Malothu

Jun 18

Streamlining MLOps: Model Deployment with MLflow

#mlops #machinelearning #python

2 min read

Marcus Chen

Jun 17

The latency tax of an LLM gateway: I measured Bifrost's overhead

#mlops #llm #infrastructure #machinelearning

4 min read

The Cyber Sidekick

Jun 17

AI Workloads Are Reshaping Kubernetes in 2026: GPU Scheduling, MLOps, and the Platform Engineering Reckoning

#kubernetes #gpuscheduling #mlops #platformengineering

4 min read

Todd Linnertz

Jun 17

What DevOps Taught Me About AI Governance

#devops #aigovernance #platformengineering #mlops

4 min read

Rajiv Sambasivan

Jun 17

From ML Tooling to Analytical Governance: Recent Updates to KMDS

#ai #productivity #python #mlops

3 min read

SyncSoft.AI

Jun 16

RLAIF Is Eating RLHF — Here Are the Four Places Human Feedback Still Wins

#ai #machinelearning #llm #mlops

6 min read

Marcus Chen

Jun 15

A 9-point eval gain vanished when we deduped train against test

#machinelearning #mlops #llm #pytorch

4 min read

Pawan Kumar

Jun 12

OpenAI Already Told Us the Kubernetes Scaling Story, Most People Just Did Not Read It Closely

#kubernetes #devops #ai #mlops

10 min read

Alex Bogle

Jun 11

I Processed 2.4 Billion Tokens Across 52 AI Models for $0.52. Here's the Full Breakdown.

#agenticai #openrouter #mlops #costoptimization

3 min read

Tech_Nuggets

Jun 11

Quantization formats compared: GGUF vs GPTQ vs AWQ vs NF4

#llm #quantization #mlops #tutorial

7 min read

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DEV Community

# mlops

Perplexity held flat after INT4. Task accuracy dropped 7 points.

The seam our tiled upscaler left on every 4K product render

Portkey Alternative: I Switched Away from Portkey. Here's the Honest Reason Why.

Speculative decoding shifted our output distribution and evals missed it

LLMOps in 2026: AI Demo to Production Guide

Streamlining MLOps: Model Deployment with MLflow

The latency tax of an LLM gateway: I measured Bifrost's overhead

AI Workloads Are Reshaping Kubernetes in 2026: GPU Scheduling, MLOps, and the Platform Engineering Reckoning

What DevOps Taught Me About AI Governance

From ML Tooling to Analytical Governance: Recent Updates to KMDS

RLAIF Is Eating RLHF — Here Are the Four Places Human Feedback Still Wins

A 9-point eval gain vanished when we deduped train against test

OpenAI Already Told Us the Kubernetes Scaling Story, Most People Just Did Not Read It Closely

I Processed 2.4 Billion Tokens Across 52 AI Models for $0.52. Here's the Full Breakdown.

Quantization formats compared: GGUF vs GPTQ vs AWQ vs NF4