Deploy Meta Llama 3.1 405B on Google Cloud Vertex AI

Deploying 🤗 ViT on Vertex AI

Making thousands of open LLMs bloom in the Vertex AI Model Garden

Build and Run Your Own AI Agent in the Cloud

Build and deploy an agent on AWS with Strands and AgentCore The post Build and Run Your Own AI Agent in the Cloud appeared first on Towards Data Science .

Llama can now see and run on your device - welcome Llama 3.2

Welcome Llama 3 - Meta's new open LLM

Make your llama generation time fly with AWS Inferentia2

TGI Multi-LoRA: Deploy Once, Serve 30 Models

Towards Agentic Cloud Engineering: Graph and Loop Engineering with a Zero-Trust Agent Harness

The paper introduces Agentic Cloud Workflow Engineering, a framework that converts natural‑language agentic cloud‑engineering tasks into validated code repositories and verified cloud deployments. It separates graph engineering for long‑horizon workflow progression, loop engineering for bounded diagnosis and recovery, and agent harness engineering for zero‑trust execution. Experiments on Google Cloud show that executions either produce a verified deployment or an auditable terminal failure within bounded recovery limits.

Forward-Deployed Full-Stack Engineering for Autonomous Cloud MLOps

The paper introduces a multi‑agent framework that transforms natural‑language MLOps tasks into verified repositories and operational cloud deployments. It uses a stateful Graph Orchestrator to coordinate agents for repository generation, review, execution, verification, release, and monitoring, ensuring lifecycle transitions only occur when supported by verifiable evidence. The framework, implemented on Google Cloud Platform, demonstrates prevention of unsupported transitions and drives each run toward a verified deployment or an auditable failure.

Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence

arXiv:2608.21156v1 Announce Type: cross Abstract: LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms includi...

Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot

Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence

LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms including Prompt Engineering to elicit model capabilities,...