Post by Fernando SantaCruz

$115 billion wasn't enough. One developer with one GPU did more. Meta delayed its flagship "Avocado" model this week because it couldn't compete with Google's Gemini in internal testing. The company with the largest AI budget on the planet even discussed licensing a competitor's model while theirs matures. Crazy, right? $115 billion in CAPEX, and they considered borrowing the brain from the neighbour. Same week: Andrej Karpathy released Autoresearch: an agent that runs experiments, evaluates results, and decides what to keep or discard autonomously. In two days it generated 700 experiments. Found 20 real improvements. A 0.8 billion parameter model outperformed one twice its size. One computer. No GPU cluster. No massive budget. Donald Knuth, the 87-year-old mathematician who wrote the reference books of programming, published a paper titled "Claude's Cycles" that opens with "Shock! Shock!" because Claude solved an open graph theory problem he'd spent weeks unable to close. A street food cook with three ingredients and a borrowed stove outperforming a five-star kitchen with a $200,000 budget. That's what this week looked like. Exactly what I see with clients every week at Adivor. The companies producing the best AI results aren't the ones spending the most. They're the ones asking better questions and designing smarter experiments. The bottleneck was never the budget. It's the imagination to know what to build and the judgement to know when it's working. Is your AI investment sized by strategy or by anxiety? There's a difference, and this week proved it costs $115 billion. #AIStrategy #EnterpriseAI #GenerativeAI #DigitalTransformation #AIAdoption #AILeadership #ScalableAI