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...
Introduction Artificial intelligence (AI) is transforming various industries in today’s fast-paced digital world. Recruitment is no exception. The adoption of AI technology in the hiring process has revolutionized how candidates are evaluated. AI in recruitment can assess large amounts of data quickly. However, it is essential to balance AI's capabilities and the valuable role of human recruiters. According to a recent report by the World Economic Forum, AI is not poised to completely replace HR professionals soon. While AI systems offer strengths in certain areas, they also have limitations. Most AI tools are designed to help with specific parts of HR tasks. They are not meant to replace human involvement. This post will explore some strengths and drawbacks of using AI in recruitment. We will see how combining AI and human intelligence is an optimal solution in the near term. The strengths of AI in recrui...