In the second part of our discussion on the webinar we explore key measures that governments can take to ensure the safety of AI. By addressing these aspects, we find that when governments contribute to fostering an AI landscape, it not only thrives on innovation but also upholds ethical principles, accountability, and global cooperation.

Navigating the delicate balance between fostering innovation and addressing potential risks, governments play a crucial role in shaping the responsible development and deployment of AI technologies. Listen with us as we discuss the importance of the role governments play in the AI industry.

Explore the intersection of AI, governance, and global impact through the insights of leading experts in our recent webinar. From the safety of AI to the imperative need for governance and regulation, our distinguished panel delved into crucial topics shaping the future.

With all the furor about AI one would expect to see it in wide application, yet it is not, and, where it does deploy, mostly augments rather than replacing human workers. Former National University of Singapore Engineering and Technology Management Prof Jeffrey Lee Funk cites use cases.

A Malay prince saw an orange beast at a river mouth in 1299. Though undoubtedly a tiger, he was told it was a lion. This omen induced him to build a city there - Singapura - from Sanskrit singa (lion) and pura (city). From that ex-British Far East fortress, on day 15 of The Yuan’s journey of smart discovery tech Prof Jeffrey Lee Funk forecasts that AI’s ‘emergence’ may prove as elusive as a lion in Lion City.

Even as headline-grabbing AI ventures fail or fall short of expectations, one should not lose hope because 2023 will still see plenty of augmentation and gradual innovation going on quietly behind the scenes that will set the stage for even greater breakthroughs.

This second episode of the Delta Dialog deals with a very different perspective on open medical data than the first session, namely the difficulty of the challenges to be overcome. These are data quality, utility of AI within open medical data, policy, funding, and human capital.

Self-driving cars, or autonomous vehicles, have garnered a great deal of attention in recent years, and despite the huge amounts of money and resources pouring in, the industry continues to disappoint. Is a technological breakthrough imminent, or should one expect more underperformance?

Open access to data must focus on their quality, not just quantity. Opening data will not ensure quality, buy may even have the opposite effect, argues Prof Jeffery Lee Funk as part of The Yuan’s Open Data 2022 series.

Much hype has surrounded AI startups in recent years, but some of this may be overblown as such startups have tended to underperform compared with their peers in other fields. Such companies’ profitability, or lack thereof, along with decisions about whether to go ahead with IPOs or SPACs offer insights into the current state of the AI sector, and what the near future holds.

The promise of AI technology has often failed to live up to its hype. How to learn from past successes and failures to adjust the expectations for AI and change how new technologies are applied to do so more successfully is the issue The Yuan contributor Prof Funk grapples with in this his inaugural article.