1,500 Alumni Return for HKU Business School’s Inaugural Homecoming Weekend

The inaugural HKU Business School Alumni Homecoming Weekend has marked an exhilarating start to 2024! Thank you to the 1,500 alumni who joined us from March 15 to 17 for this unforgettable series of events, filled with learning, networking, and reminiscing.

Day 1 – March 15, we kicked off the weekend with a nostalgic Campus Tour at HKU, followed by an enlightening Luncheon Talk by Prof. Michael B. Wong on Hong Kong’s housing market. We also had an amazing time taking 100 alumni on a Company Visit to Cathay Pacific Airways, where they had the rare opportunity to sit in a flight simulator. Additionally, our visit to Lee Kum Kee Company Limited was an incredible experience that highlighted the importance of family cooperation. We want to express our sincere gratitude to both companies for their flawless organization and warm hospitality.

Day 2 – March 16 featured a captivating Distinguished Lecture by Mr. Algernon Yau, Secretary for Commerce and Economic Development on Hong Kong’s vision for sustainable economic growth. The day concluded with our dazzling HKU Business School Alumni Gala Dinner, where friendships were rekindled and memories were made.

On Day 3 – March 17, we celebrated sports and business synergy at our Sports and Business Forum, featuring three of Hong Kong’s most famous athletic heroes (including our very own celebrity alumnus, Alex Fong!), three iconic global sporting brands, our elite sports scholars who competed in the Hangzhou Asian Games, and a star Silicon Valley alumnus entrepreneur.

A heartfelt thank you to all our alumni for making this homecoming weekend a roaring success! We hope you left with new insights, valuable connections, and fond memories of your time at HKU Business School. Stay connected and see you at future alumni events!

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HKU Business School Releases a Comprehensive Evaluation Report on the Image-Generation Capabilities of AI Models
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HKU Business School Releases a Comprehensive Evaluation Report on the Image-Generation Capabilities of AI Models
HKU Business School released a Comprehensive Evaluation Report on the Image Generation Capabilities of Artificial Intelligence Models, providing a systematic assessment of 15 text-to-image models and 7 multimodal large language models (LLMs). The results showed that ByteDance’s Dreamina and Doubao, as well as Baidu’s ERNIE Bot ranked among the top performers in terms of image content quality for new-image generation and image revision. However, despite DeepSeek having attracted global attention, its newly released text-to-image model, Janus-Pro, did not perform as well in new-image generation. HKU Business School researchers also found that while some text-to-image models excelled in content quality, their performance in safety and responsibility was significantly lacking. In general, multimodal LLMs demonstrated better overall performance compared to text-to-image models.
AI Image Generation Evaluation Results Released: ByteDance and Baidu Perform Well, DeepSeek Janus-Pro Falls Short
2025 | Research
AI Image Generation Evaluation Results Released: ByteDance and Baidu Perform Well, DeepSeek Janus-Pro Falls Short
The frontier of AI models has evolved beyond text processing to encompass the ability to understand and generate visual content. These models not only comprehend images but also generate visual content based on textual prompts. This study presents a systematic evaluation of the image generation capabilities of AI models, focusing on two core tasks: generating new images and revising existing images. Using carefully curated multidimensional test sets, we conducted a comprehensive evaluation of 22 AI models with image generation capabilities, including 15 text-to-image models and 7 multimodal large language models. The results show that ByteDance’s Dreamina and Doubao, as well as Baidu’s ERNIE Bot, demonstrate impressive performance in both new image generation and image revision tasks. Overall, multimodal large language models deliver superior performance compared to text-to-image models.