Artificial Intelligence Revolutionizing Media Landscape
Artificial intelligence (AI) is transforming the media landscape, with chatbots and advanced algorithms taking center stage. These AI-powered tools can now generate content, have human-like conversations, and even analyze emotions from text—an ability once thought to be exclusive to humans. This breakthrough has significant implications for sentiment analysis and content monitoring, as AI can now decode emotions from written words, potentially revolutionizing media analytics. However, there are still limitations to AI’s ability to recognize emotions from text, as understanding emotional tones requires a deep understanding of the world and social norms that AI lacks.
SenticNet: Advancing AI Emotion Analysis
SenticNet, an AI platform developed by Professor Erik Cambria from NTU’s School of Computer Science and Engineering, aims to address the challenges faced by AI in understanding human languages. By integrating human learning modes with traditional machine learning approaches, SenticNet improves the algorithm’s ability to analyze emotions. Unlike conventional sentiment analysis models, which lack transparency in their reasoning process, SenticNet follows a logical framework resembling commonsense reasoning, making its results transparent, reproducible, and reliable. In tests, SenticNet outperformed other machine-learning models in emotion analysis, paving the way for enhanced sentiment analysis and emotion monitoring in media and beyond.
Making Video Content Searchable
Assoc Prof Sun Aixin, also from NTU’s School of Computer Science and Engineering, has developed an innovative algorithm that allows users to search for specific moments in video content. By treating videos as text passages, the algorithm matches keywords with on-screen images, making video content more searchable and engaging. This approach is particularly valuable for educational and entertainment purposes, as users can easily find relevant information within long video clips. Unlike conventional computer vision techniques, which struggle with searching long videos, Assoc Prof Sun’s method enables more efficient and accurate video content search. The researchers are now focusing on refining the algorithm’s search accuracy and exploring its potential application in medical education and surveillance videos.
Addressing the Threat of Fake Images
As AI tools become more advanced, new threats have emerged, including the proliferation of fake images designed to deceive or scam audiences. To combat this issue, Seq-DeepFake, developed by researchers at NTU, can detect altered images and recover their original versions. This technology has significant implications for preventing the spread of fake images and protecting audiences from manipulation. With the advancement of AI, it is crucial to develop countermeasures to ensure the responsible and ethical use of this powerful technology.
The Future of AI in Media
As AI continues to revolutionize media and communication, we can expect further advancements in sentiment analysis, emotion monitoring, content searchability, and image authentication. The ability of AI to decode emotions from text opens up new possibilities for understanding audience sentiment, enhancing media monitoring, and combating the spread of malicious content. However, it is vital to strike a balance between the efficiency and transparency of AI systems, ensuring that they can explain their reasoning without compromising performance. As researchers at NTU push the boundaries of AI technology, the future of media and communication looks promising, with AI-powered tools providing valuable insights and enhancing the overall user experience.
Analyst comment
Positive news: Artificial intelligence (AI) is revolutionizing the media landscape, offering new capabilities in content generation, sentiment analysis, and emotion monitoring. SenticNet, an AI platform, improves emotion analysis, enabling more accurate sentiment analysis. An innovative algorithm allows users to effectively search for specific moments in video content. Seq-DeepFake addresses the threat of fake images, enhancing image authentication. The future of AI in media looks promising, with advancements in sentiment analysis, content searchability, and image authentication.
