In a recent study from the Stanford University SALT Lab (Shao et al., 2025) titled “Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce” , the authors offer a thoughtful, data-driven assessment of how AI agents map to real human work.   In this post, I summarise the paper's key findings—and situate them within my own AI philosophy and approach at Accéder , where I firmly believe that intelligent machines should augment  huma

Introduction: A New Kind of Neural Network For decades, Spiking Neural Networks (SNNs)  were primarily studied in neuroscience as models of how biological neurons communicate. The complexity of their training limited their commercial potential—until recent breakthroughs in algorithms and neuromorphic hardware changed the game. Today, SNNs can be trained using surrogate-gradient methods  and hybrid ANN→SNN conversion , running efficiently on GPUs or on emerging neuromorphic pr

A deep dive inspired by EY’s latest Agentic AI in the Workplace report By Oscar González Iñiguez (OGI)  – Founder & CEO, Accéder Artificial Intelligence has finally entered its Agentic  phase — where AI systems go beyond simple tasks to act, reason, and decide alongside humans. And according to a major new study by Ernst & Young LLP (EY US) , employees are not resisting this evolution. In fact, 84% of workers are eager  to embrace Agentic AI in their roles. But here’s the par

Over the past decade, most major tech firms — including Microsoft, Amazon, Google, Tesla, IBM, and Duolingo  — have pursued automation as a way to cut costs and increase productivity. Yet today, many are quietly reversing course. According to Economy Media Research , nearly 55% of companies that replaced human workers with AI now regret the decision . Why? Because AI, when used as a substitute for human judgment, tends to amplify fragility rather than resilience. The Illusion