How to Stop Agent Mistakes: Custom Policies for Real-Time AI Governance 🛡️

9 Books That Help You Understand AI

For Your After Holiday Reading

Guest Post: How Science Actually Uses Machine Learning in 2025

Analysis from 5000+ research papers

Guest Post: We benchmarked 7 AI code review tools on large open-source projects.*

Here are the results

Guest Post: Distributed Self-Distillation*

Three strategies Speechmatics tested in production while scaling self-distillation

💻 How to Maximize Resiliency with AI-Native Observability – Nov 24

30-minute session on how deep observability powers AI infra resiliency

Agents in Production - MLOps x Prosus

Free Virtual Conference – November 18

Agentic Transformation: Navigating the 4 Stages of AI Agent Maturity*

Super practical session

Guest Post: AI-powered engineering at scale*

the adoption playbook

📖 Expert Guide to Multi-Agent Systems*

Learn how to build reliable multi-agent systems with Galileo's in-depth eBook

Guest Post: The Coding Personalities of Leading LLMs*

How to cut AI storage costs up to 65% – without slowing down innovation*

Join CoreWeave experts to see how storage built for the realities of AI eliminates tiers, replication, and hidden fees

Guest Post: The art and science of context engineering for AI code reviews*

The difference between a mediocre and exceptional AI agent comes down to one thing: context.

Guest post: Why Not All VectorDBs Are Agent-Ready*

Guest post: Why AI Databases Don't Need SQL*

🔹 Ready to accelerate your AI innovation? The time is now.

Join us for this exclusive virtual event from AI innovators CoreWeave and NVIDIA to help us collaboratively redefine the future of AI

DeployCon SF: Free GenAI Summit ft. DoorDash, ConverseNow, and more

Guest Post: Open Recommender System Datasets – A Current Landscape

📍Shared vs Private LLMs: How to Unlock Improved Latency, Cost, and Control

join us at live webinar

Guest Post: Building a Self-Improving Agent with Arize Phoenix and DSPy

Using prompt optimization, evaluation, and observability to create an automated improvement process

Why NVIDIA Blackwell on CoreWeave [💡Webinar ]

Unlock the full potential of your AI innovations

How to Fine-tune DeepSeek with Reinforcement Learning [webinar]

eBook: Mastering AI Agents

Learn how to create powerful, reliable AI agents with Galileo's in-depth eBook

🌁#85: Curiosity, Open Source, and Timing: The Formula Behind DeepSeek’s Phenomenal Success

How an open-source mindset, relentless curiosity, and strategic calculation are rewriting the rules in AI and challenging Western companies, plus an excellent reading list and curated research collection

Guest post: Enhancing RAG with RA-DIT: A Fine-Tuning Approach to Minimize LLM Hallucinations*

RA-DIT, or Retrieval-Augmented Dual Instruction Tuning, is a method for fine-tuning both the LLM and the retriever in a RAG setup to enhance overall response quality