Artificial Intelligence can be better understood through some basic principles of how it thinks and works. Large Language Models (LLM) essentially function like sophisticated text prediction systems that forecast the next word in a sentence based on vast amounts of data, explains Ethan Mollick in his 100th Substack post. These AI systems operate with limited … Read more
Schools and universities are increasingly relying on AI detectors to check student work for AI use. According to one survey, about two-thirds of teachers use such tools regularly. As Jackie Davalos and Leon Yin report in Bloomberg Businessweek, at that scale, even low error rates can lead to a large number of false positives. The … Read more
When discussing artificial intelligence, we must not lose sight of the term “artificial”. In my opinion, there is too much discussion about whether an AI like ChatGPT is “really intelligent”. But that’s not the point. To explain it with a comparison: Is an artificial rose the same as a real, natural rose? No, not at … Read more
A Large Language Model, commonly abbreviated as LLM, is an advanced artificial neural network designed to understand, generate, and process human language. These models are termed “large” because they are trained on vast amounts of textual data and can contain billions of parameters. LLMs are capable of performing a wide range of tasks, including text … Read more
Mixture of Experts (MoE) is a concept in artificial intelligence that can best be understood as a team of specialists. In this approach, a complex task is divided among multiple smaller, specialized models – the so-called “experts” – instead of using a single large model for everything. A central “gatekeeper” or “router” decides which expert … Read more
Chain of Thought is a concept in artificial intelligence that describes the ability of AI systems to solve complex problems step-by-step, much like humans do. This method allows AI models to explain their thought processes in a way that humans can understand. Instead of just providing a final answer, the AI shows the individual steps … Read more
Today’s AI assistants provide answers to questions or perform simple, well-defined tasks. But they do not act independently. In addition, more complex tasks always require a human to act as a supervisor. AI agents, on the other hand, should find a solution on their own and pursue goals autonomously or semi-autonomously. AI agents use basic … Read more
In a previous Smart Content Report, I featured a funny illustrated guide generated by ChatGPT’s Dall-E: I find such “failures” interesting to see, because they can reveal fundamental problems. For example, we are still a long way from an AI that actually understands the world around it (“General World Model”). At the moment, these tools … Read more
A general world model is an ambitious concept in artificial intelligence. The goal is to create an AI system that can understand and simulate the world as comprehensively as a human. Imagine a virtual assistant that can not only generate text or images, but also understand, predict, and respond to complex real-world situations. For example, … Read more
In his article for VentureBeat, Samir Kumar, co-founder of Touring Capital, analyzes the current AI hype cycle. He cautions against jumping to conclusions and reminds us of previous technology waves, such as the smartphone revolution. Kumar emphasizes that the first innovators are often not the long-term winners. He advises founders and investors to pay particular … Read more