The remarkable performance of Large Language Models (LLMs) highly relies on crafted prompts. However, manual prompt engineering is a laborious process, creating a core bottleneck for practical application of LLMs. This phenomenon has led to the emergence of a new research area known as Automatic Prompt Optimization (APO), which develops rapidly in recent years. Existing APO methods such as those based on evolutionary algorithms or trial-and-error approaches realize an efficient and accurate prompt optimization to some extent. However, those researches focus on a single model or algorithm for the generation strategy and optimization process, which limits their performance when handling complex tasks. To address this, we propose a novel framework called Ensemble Learning based Prompt Optimization (ELPO) to achieve more accurate and robust results. Motivated by the idea of ensemble learning, ELPO conducts voting mechanism and introduces shared generation strategies along with different search methods for searching superior prompts. Moreover, ELPO creatively presents more efficient algorithms for the prompt generation and search process. Experimental results demonstrate that ELPO outperforms state-of-the-art prompt optimization methods across different tasks, e.g., improving F1 score by 7.6 on ArSarcasm dataset.

How smart can technology be? Apparently, as smart as you make it to be. One of the first algorithms with which Google started marketing products and displaying advertisements was based on search results. You'd search for an air ticket, logged in to your Google account, and Google would throw up ads for air tickets. You want to buy an air conditioner; Google knows.

Machine learning and artificial intelligence have allowed Google and others to move to smarter Bayesian techniques.

Who will build the self-driving car of the future? Fired-up by Google's driverless prototype, carmakers such as Mercedes-Benz and Volvo are already testing autonomous vehicles on public roads. But the advanced sensors and electronics that form the building blocks of self-driving cars are often made by suppliers, not the car manufacturer. "It's all the suppliers into the industry who, in the fullness of time, will gain the power," says a senior industry analyst, who works closely with the leading carmakers. Carmakers have been gradually adding autonomous elements to their vehicles since Jaguar introduced adaptive cruise control in its XK sports car in 1996.