In 2017, if you asked me what the deepest feeling was, as a tech media professional, I would say: AI is hot. Driven by supportive policies, this application-focused AI trend seems to be maturing the underlying technologies behind it.
Artificial intelligence is set to permeate various fields and applications, and the next decade will be a crucial time for its real-world implementation. Therefore, identifying the first breakthrough that successfully lands in practical use has become essential.
Looking at the market trends over the past two years, we've witnessed the rising popularity of smart voice technology and seen face recognition emerging as the next big battleground. AI is spreading within the biometrics field, which has now become a focal point and area of competition among global internet giants. It seems reasonable to conclude that biometrics have become one of the most significant breakthroughs for AI’s initial practical application.
On December 15, Jinji Lake Think Tank in the park and Hefei.com jointly hosted a technical salon event titled “New Interaction, New Future.†The event featured presentations from several industry experts, including President Xu Fei from the University of Science and Technology, Professor Shu Hongping, Market Director Yuan Cong from Suzhou Mindray Microelectronics, and Professor Huang Kaizhu from Xi'an Jiaotong-Liverpool University. Each speaker provided insightful discussions on AI and biometrics.
From Perception to Cognition
The historical mission of artificial intelligence is to free humans from heavy mental labor. Today’s AI wave represents the third major surge after two previous “winters.â€
From the 2016 Go match between AlphaGo and Lee Sedol, to the TV series Westworld, and then to smart speakers, AI suddenly became everywhere—like a spring breeze in the night.
But beneath this hype, what is the reality? How should we rationally view this third AI boom? At the event, the three guests addressed these questions from both academic and industrial perspectives.
AI's Three Stages
**Computational Intelligence**
This enables machines to perform calculations like humans, such as through neural networks and genetic algorithms, allowing them to process massive data more efficiently.
**Perceptual Intelligence**
This allows machines to understand language and perceive the world. Speech and visual recognition fall into this category, helping humans accomplish tasks more effectively.
**Cognitive Intelligence**
Here, machines can actively think and take actions, providing comprehensive assistance or even replacing human work.
Professor Shu Hongping noted that speech synthesis has surpassed human levels, speech recognition accuracy exceeds that of stenographers, and intelligent evaluation systems outperform human teachers. However, current AI excels in computational intelligence but still lags behind in cognitive intelligence.
A 2017 test by the HKUST robot demonstrated that it performed well in math-related subjects but struggled with liberal arts, highlighting the limitations of current AI.
Professor Huang Kaizhu remarked, “This is the best era in AI history, but the age of artificial intelligence has not yet arrived.â€
Today’s AI is still far from achieving general artificial intelligence. For example, while dialogue robots are popular, they cannot engage in meaningful conversations for an entire year. Similarly, AlphaGo learned to play Go by analyzing thousands of games and self-playing, but the same program cannot be applied to master chess.
The journey toward true AI is long, but the potential is immense. As we continue to explore and innovate, the future of AI looks promising.
Shenzhen Ousida Technology Co., Ltd , https://en.osdvape.com