#pre-trained-models

#pre-trained-models

Legacy software, often described as 'big balls of mud,' has accumulated over decades, becoming difficult to maintain and understand. These systems rely on extensive teams to function, despite their outdated technology.

Meta's Muse Spark is the company's first AI model since the social media giant's previous initiatives, and analysts are optimistic about its potential.

What happens under the hood? How is the search engine able to take that simple query, look for images in the billions, trillions of images that are available online? How is it able to find this one or similar photos from all that? Usually, there is an embedding model that is doing this work behind the hood.

For the past few years, artificial intelligence has been discussed almost exclusively in terms of models. Bigger models, faster models, smarter models. More recently, the focus shifted to agents, systems capable of planning, reasoning, and acting autonomously. Yet the real leap in usefulness does not happen at the model level, nor at the agent level. It happens one layer above, at the level of Skills.