Today, every LLM has its own way of connecting to your databases and tools. It’s a chaos of proprietary integrations. MCP (Model Context Protocol) promises to end this by becoming the ‘universal plug’ of AI. We analyze if it’s truly the future or just another standard that will die trying.
Everyone talks about what AI can do. Almost no one talks about what AI costs to do. After more than 6 months operating autonomous agents in production with Gemini, CrewAI and GitHub Actions, I open the books and break down every euro invested — and every surprise I found along the way.
While the world awaits the arrival of fully functional quantum computers, a company from San Sebastián is using the mathematics that underpin them to solve AI’s most urgent problem today: efficiency. Multiverse Computing has developed a technology based on ‘Tensor Networks’ that compresses large language models (LLMs) by up to 95%, allowing them to run on standard hardware and edge devices. This pragmatic ‘quantum-inspired’ approach has earned them a $500M valuation and partnerships with giants like Bosch and Iberdrola. We analyze their strategy, technology, and business model.