Artificial Intelligence

1. The Execution Chasm Companies invest millions in planning software and ERPs. They spend months integrating data, cleaning records, and tuning demand forecasts. Yet, at the end of the day, execution often relies on an analyst staring at a dashboard. A human reading charts, finally drafting an email to the plant director to request production adjustments. That human delay is inefficient, error-prone, and, frankly, unnecessary in the modern era. Pure mathematics has no value if it isn’t executed. ...

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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.

Remember your first day amidst mountains of paperwork? Traditional onboarding costs time and money, and often fails in its mission. A recent report reveals alarming figures: 24 days on average to complete the process and only 12% of employees satisfied. The solution is not more paper, it’s Artificial Intelligence. Discover how the combination of IDP for bureaucracy and GenAI as a virtual mentor can automate document management and personalize information delivery, freeing up HR to focus on culture and people.

While the world gets distracted by chatbots writing poems, DeepMind has been playing a much deeper game. The documentary ‘The Thinking Game’ reveals the untold story behind AlphaGo and AlphaFold: a decades-long mission to solve intelligence and use it to decode biology itself. We analyze the technical milestones, the ethical philosophy, and why Demis Hassabis believes AI is a discovery on the level of fire or electricity.

The ‘Organic Traffic Plateau’ is real. To overcome it without losing focus on engineering, I’m launching an extreme ‘dogfooding’ experiment: automating Datalaria’s distribution using Gemini, CrewAI, and GitHub Actions. This is the Master Plan.

Describing a complex industrial process in text is inefficient. In this post, we explore how to use LLMs to translate the business logic of a comprehensive S&OP into visual diagrams, choosing the right tool (Miro, Mermaid, or BPMN.io) based on the project phase.