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38 articles
This article explains the forward-deployed engineering model in enterprise AI, where specialized teams are embedded within client organizations to overcome deployment bottlenecks and ensure successful AI implementation.
This article explains on-device inference - the practice of running AI models directly on user devices rather than in the cloud - and why it matters for privacy, performance, and scalability in modern AI applications.
This article explains how AWS's integration of vibe-coding tools like Superblocks into private clouds represents a major shift toward decoupling AI applications from their underlying models, enabling more flexible and enterprise-ready AI deployment patterns.
A Marc Benioff-backed startup called June has raised $20 million to tackle the complex challenge of AI deployment for enterprises. The company aims to simplify AI adoption by abstracting the technical complexities of bringing AI models into production environments.
Even perfectly aligned AI models cannot guarantee control or accountability in production environments, raising critical questions about current AI governance strategies.
OpenAI introduces OpenAI Presence, a managed enterprise AI agent service that pairs AI agents with dedicated Forward Deployed Engineers for customized deployments.
OpenAI introduces Presence, an enterprise AI agent platform designed to help organizations deploy trusted voice and chat agents for customer and internal workflows.
OpenAI shares critical insights from deploying long-running AI models, highlighting new safety risks and improved safeguards through iterative deployment strategies.
Vercel CEO Guillermo Rauch advocates for separating AI models from agents to optimize production environments and improve cost-effectiveness. His perspective highlights the growing need for modular AI architectures that can adapt to enterprise requirements.
Microsoft launches a $2.5 billion initiative to embed 6,000 AI engineers within enterprise clients, aiming for measurable ROI and platform-neutral AI integration.
Microsoft has launched its own AI deployment company with a $2.5 billion commitment, entering the competitive AI infrastructure market alongside Amazon, OpenAI, and Anthropic.
Microsoft launches a $2.5 billion AI deployment business with 6,000 engineers to accelerate enterprise AI adoption.
