Imagine trying to train a dog to fetch a specific toy in a cluttered house, but you only give it a treat when it successfully brings back that exact toy, and nothing for any other behavior – not for sniffing the right toy, not for picking up a wrong toy and dropping it, not even for finding the room the toy is in. How would the dog learn? It would likely wander around aimlessly, getting no positive feedback for its efforts, and might never figure out what you want. This scena

In the relentless pursuit of artificial general intelligence (AGI) , the focus often lands on AI agents capable of complex, long-term planning , anticipating future states, and optimizing for distant rewards. These "far-sighted" agents are undoubtedly powerful. However, there's a compelling and often overlooked case to be made for their simpler, more immediate cousins: Myopic AI Agents . Myopic AI agents, by definition, are "short-sighted." They optimize their actions based

For a startup, initial traction feels like striking gold . Customers are signing up, revenue is trickling in, and the team is buzzing...

Artificial intelligence is rapidly evolving, moving from narrow task-specific tools towards more general, autonomous systems . As AI becomes more capable and integrated into our lives, ensuring its safety and alignment with human values is paramount. One of the most crucial, yet often subtle, concepts in AI safety is Corrigibility . It's the idea that an AI system should allow itself to be corrected, modified, or even shut down by its human operators, even if doing so conf

Isaac Asimov , a titan of science fiction, introduced his " Three Laws of Robotics " not merely as a set of rules for fictional machines,...

Imagine trying to bake a complex soufflé for the first time. A small mistake early on – perhaps mismeasuring the flour or over-whipping...

The principles of trust, data access, and the Context-Aware Interface (CAI) , as explored in " The AI App Success Equation ," are not merely confined to standalone applications. They are the foundational pillars upon which a new, more intelligent, and deeply personal internet experience will be built. This evolution, however, points towards a significant divergence in how the web is structured and experienced: a robust, public-facing internet primarily for information dissemi

From composing music to diagnosing diseases and driving cars, AI systems are performing tasks once considered uniquely human. Yet, beneath this veneer of rapid progress lies a fundamental challenge, one articulated decades before the first perceptron fired: Polanyi's Paradox . This paradox, which states " we can know more than we can tell, " continues to shape, constrain, and inspire the field of AI. What is Polanyi's Paradox? Coined by Hungarian-British polymath Michael Pola