MilvusAI EngineerExaDatabricksUberSingleStoreCoreweaveQdrant+42

MilvusBlog3d

Jev vs. LLMs in Agentic Search

AI EngineerYouTube3d

We Mapped 115 Microservices for Our Coding Agents — Kamalakannan Nandagopal, Postman

ExaBlog4d

ATLAS: Evaluating Agents on Search-Intensive Tasks

DatabricksBlog6d

The lakehouse is a better data warehouse: 2026 benchmarks and proof

UberBlog1w

Designing MCP Gateway Uber's MCP Management Platform

SingleStoreBlog1w

Introducing the Query Tuning Agent: Optimize Your Most Complex Workloads

CoreweaveBlog1w

First Vera Rubin NVL72 Customer Sees 4.8x Throughput

QdrantBlog1w

Constella Preview: Swap Query Models Without Re-Embedding

GitHubBlog2w

Improving site performance by shipping more CSS

QdrantBlog2w

Oxidizing Cross-Encoders

GoogleBlog2w

Reproducing OLMo 3 7B Pre-training in MaxText: case study of large scale training on TPUs- Google Developers Blog

UberBlog2w

Taming the ML Firehose: Scaling Feature Consistency

Hugging FaceBlog3w

tokenizers v1: encode, decode and scaling, measured

MeilisearchBlog3w

How to diagnose search performance problems in B2B SaaS

LambdaBlog3w

MLPerf Inference v6.1: pioneering agent, VLM benchmarks

Hugging FaceBlog3w

Your Agent Aced the Task. Will It Do It Again?

UberBlog3w

Large-Scale Automated Dependency Analysis Across Uber's Service Mesh

NVIDIABlog2 Sept

The Modern CUDA Toolbox in Practice: A Step-by-Step Optimization Walkthrough

Hugging FaceBlog1 Sept

Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI

BasetenBlog29 Aug

Agentic kernels in production

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