Who should lead the regulation of AI? Government has the tools to require compliance, but risks constraining innovation. Industry has the know-how to ensure relevance, but risks self-interest trumping consumer protection. This debate will discuss whether AI should be regulated by industry or by government, covering perspectives on how regulation – broadly understood to include rules, standards, and supervised self-regulation – can and should balance reaping the benefits of AI against minimising avoidable harms. Getting this balance right is important not only to ensure that AI is trustworthy, but it will also determine whether consumers do in fact trust it in practice.
As data starts to take centre stage and organisations start to bring their businesses into the next phase of the digital age, putting the human being at the centre of our thinking when it comes to designing new technologies is crucial to ensuring that these technological innovations serve people and not the other way around.
In today's world, sea traffic is only expected to grow with the rising volume of trade and e-Commerce activities. For Singapore to be one of the world's leading smart ports, continuous knowledge-based port services and maritime-related expertise must be developed.
Precision medicine aims to find the best, personalised treatment for diseases. It includes health approaches that can better predict, prevent, treat, and manage the disease outside hospitals, such as disease prevention and health promotion activities.
Industry: Health and BioMedical Sciences
In the information era, we generate tons of data every second: emails, images, videos, sound, metadata. Storing all this information requires extensive data centres and huge costs in infrastructure and maintenance. However, Nature has figured out how to store and process large amounts of data billions of years ago: store them in DNA. Could we do the same and use DNA for long- and short-term storage of our valuable information?
Industry: Health and BioMedical Sciences
Recent breakthroughs in artificial intelligence and machine learning - such as deep neural networks, the availability of powerful computing platforms and big data, are providing us with technologies to perform tasks that once seemed impossible. In the near future, autonomous vehicles and drones, intelligent mobile networks, and intelligent internet-of-things (IoT) will become a norm. At the heart of this technological revolution, it is clear that we will need to have artificial intelligence over a massively scalable, ultra-high capacity, ultra-low latency, and dynamic new network infrastructure. In this talk, we will provide a simple overview of AI from the perspective of networking and communications and share some interesting applications. In addition, we will also share some of our preliminary works in this area.
Deep Tech trailblazers will share how they harness the power of AI to change the investments and funds management scene. Beyond industry insights, this session also briefly traces their startup journeys and offer you an opportunity to work with them via SGInnovate's Summation Programme.
One of the biggest goals of any manufacturing professional is improving workflows and running a smooth shop floor with minimal downtime and high profitability. What is the key to unlocking this? Data.
Important decisions that impact the manufacturing process should always be based on cold, hard data and not guesses, wishes, theories, or opinions. Data-driven manufacturing is the way for manufacturing operations to drive efficient and responsive production systems and improve the bottom line. With the ongoing digital transformation and capabilities, and proliferation of the latest data-capturing technologies such as Internet of Things (IoT) devices and their applications of big data and analytics, manufacturers can effectively collect data in real-time and make informed decisions.
In this session, learn more about how you can transform data into actionable business insights for optimised production capabilities. Discover how data insights from the Industrial IoT and digitisation can drive production floor improvements and quality. Learn to maximise the value of data through analytics from real-time notifications to statistical process control for immediate gains and explore the potential of predictive maintenance with connectivity and data collection to enhance customer experience and enhance loyalty.
Industry: Advanced Manufacturing
Deep Tech has evolved into a distinct approach to innovation and will drive the next great wave of innovation. While the narrative evolves quickly, it has also developed very specific characteristics.
In the race to achieve the ever-increasing ambitions towards net-zero emissions, the voluntary carbon market is gaining momentum with keen buyers seeking to offset the climate footprint of their fossil fuels. Nature-based Solutions (NbS) - as actions that harness the power of nature to tackle social and environmental challenges - is a core foundation to achieving carbon neutrality for its way to build resilience to the consequences of warmer temperatures whilst helping to limit further rises by acting as carbon sinks.
To effectively harness the power of AI in the aviation sector, the industry should start to develop and adopt an AI ethical framework. In this event, our speakers will share their perspectives on the responsible application and the social values of AI in aviation for the future.
Industry: Aerospace / Space
We have entered a new era where Artificial Intelligence (AI) enhances human decisions. Every industry is going through a significant transformation - the food industry is no different. Food innovation, mainly in flavour and ingredient innovation, which previously required significant manual research, can be accelerated much more efficiently with the help and proper use of Artificial Intelligence.