Alliance for AI Humanity

  1. Industrialization Learned How to Create Power Before It Learned How to Withdraw It The Industrial Revolution gave humanity a scale of power and speed it had never known before. Steam locomotives could carry more passengers and freight over greater distances at far greater speed. Railways connected cities to factories and transformed the scale of industry itself. Yet the greatest challenge facing the early railway system was not how to set a locomotive in motion. It was how to stop a train that was already moving. On early trains, when the engineer signaled for a stop, multiple brakemen had to operate the manual brakes on each carriage individually. They moved across the tops of rolling cars, applying one brake after another. Power could be delivered from a single point at the front of the train, but withdrawing that power depended on the speed, coordination, and physical response of several people. Industrialization learned very quickly how to build powerful engine...

  Artificial intelligence is discussed through the language of scale. Models are celebrated for having hundreds of billions of parameters, training on enormous datasets and consuming vast amounts of computing power. This has created an assumption that bigger models lead to more intelligence. However, an important counter-movement is emerging. This is the rise of small language models or SLMs. Small language models are designed to perform useful language tasks with fewer computational resources than large language models. They can run on laptops, mobile phones, industrial computers and in some cases, compact devices such as a Raspberry Pi. They can operate near the user, work without a continuous internet connection and be customized for particular domains. Their significance lies not in competing with the largest models, but in providing the right amount of intelligence at the right place and at an affordable cost. What Is a Small Language Model? A language model is a comput...

  1. We Imagine a Face for AI What kind of face do you imagine AI has? A humanoid face? The face of a kind assistant? The face of a calm counselor? The face of an intelligence that may one day sit across from us and meet our eyes? When we imagine AI, we often borrow the shape of a human being. When it has a voice, we imagine a personality. When its sentences are gentle, we sense a kind of mind. When it remembers past conversations, we begin to feel as if a relationship has formed. The more AI speaks like a human, the more we give it a face. We feel that it understands us. We imagine that it sees us. But perhaps the more important question lies on the other side. What face does AI see when it looks at you? Are you a person? In human society, yes. But in the eyes of an LLM — a large language model — you are not first encountered as a person. You are first reconstructed as text. If an LLM had eyes, your face would not be made of eyes, a nose, and a mouth. It would be made of sentences...