Should AI models be like Swiss Army knives, versatile and handy in a variety of scenarios? Or do we prefer them as precision tools, finely tuned for specific tasks? In the world of artificial intelligence, and natural language processing specifically, this is an ongoing debate. The question boils down to whether models trained for specific tasks are more effective at these tasks than general models. Task-specific models: specialization and customization In my last blog post , we looked at the rise of personalized LLMs, customized for specific users. Personalized LLMs can be seen as an extreme form of task-specific model. Fans of task-specific models stress that these kinds of models are better suited for tasks involving confidential or proprietary data. This is obviously true. But some people also believe that specialized models necessarily perform better in their specific domains. It may sound logical, but the ans...
“And I heard the dude, the old dude that created AI saying, ‘This is not safe, 'cause the AIs got their own minds, and these motherf*ckers gonna start doing their own s**t.’ I'm like, are we in a f***ing movie right now, or what? The f**k, man?” - Snoop Dogg The rise of Artificial Intelligence, particularly ChatGPT, has been sparking intense discussions. Specifically, over the last few months, more and more concerns have been raised about the creation of AI tools. This culminated in an Open Letter in late March, calling for a halt to AI experiments. This letter was supported by, among others, Elon Musk and Steve Wozniak. Enter the Hinton Adding to this chorus, Geoffrey Hinton, a prominent figure in the development of AI, has recently resigned from his position at Google. Hinton, widely known as the “Godfather of AI”, announced his departure from the tech giant in an interview with the New York Times. While t...