Our team’s insights on building better and scaling smarter.
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Alyssa Mazzina
10 April 2025
The Future of AI Training: Are GPUs Enough?
GPUs still dominate AI training in 2025, but emerging hardware and hybrid infrastructure are reshaping what's possible. Here’s what GTC revealed—and what it means for you.
Llama 4 Scout and Maverick Are Here—How Do They Shape Up?
Meta’s Llama 4 models, Scout and Maverick, are the next evolution in open LLMs. This post explores their strengths, performance, and deployment on Runpod.
Built on RunPod: How Cogito Trained Models Toward ASI
San Francisco-based Deep Cogito used RunPod infrastructure to train Cogito v1, a high-performance open model family aiming at artificial superintelligence. Here’s how they did it.
Bare Metal vs. Instant Clusters: What’s Best for Your AI Workload?
Runpod now offers Instant Clusters alongside Bare Metal. This post compares the two deployment options and explains when to choose one over the other for your compute needs.
Introducing Instant Clusters: On-Demand Multi-Node AI Compute
Runpod’s Instant Clusters let you spin up multi-node GPU environments instantly—ideal for scaling LLM training or distributed inference workloads without config files or contracts.
Machine Learning Basics (for People Who Don’t Code)
You don’t need to code to understand machine learning. This guide explains how AI models learn, and how to explore them without a technical background.