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Leveraging Graph Database Capabilities for AI/ML in Singapore Businesses

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AI Singapore (AISG) is looking to boost Singapore’s Artificial Intelligence (AI) and machine learning (ML) capabilities with the use of graph technology, which enhances analytics by finding unknown relationships in data that are not being identified by traditional means.

While traditional relational databases will still have many use cases, graph databases present many new possibilities for AI and ML applications. The new technology will be useful for solving some of today’s AI problems. For example, new analytics innovation or new graph algorithms may drive superior outcomes to solve the AI problem.

– Laurence Liew, Director for AI Innovation at AISG

A graph database, with its structure of nodes and edges, creates connecting and traversing links which allow for accelerated processing of inter-connected data. This makes it possible to process terabytes of data and traverse millions of connections in a fraction of a second.

AISG recently signed a memorandum of understanding (MOU) with a graph database vendor to help Singapore businesses to leverage graph database capabilities for AI/ML, and to build Singapore’s graph database capabilities and talent pool.

The collaboration is committed to helping build a steady pipeline of AI professionals with graph database analytics capabilities by supporting the research and development needs of the apprentices in AISG’s AI Apprenticeship Programme (AIAP).

The partnership is setting up a Graph AI Centre of Excellence to conduct proof-of-concept and customer projects under the 100 Experiments initiative, which seeks to help organisations solve their AI problems where no commercial off-the-shelf AI solution exists, and to build their own AI teams.

AISG is relentless about nurturing innovation and research breakthroughs that will give birth to bold ideas and applications of AI to solve societal or business challenges. With the partnership, AISG will be exploring the limitless possibilities of a graph database in support of AI and ML applications and will continue to punch above our weight in the technological and economic race.

According to Asia Pacific AI Readiness Index, Singapore is again at the top spot for readiness in the adoption of AI, compared to 10 other economies in the region. the index assesses the readiness of governments, businesses, and consumers across eleven APAC economies in their adoption of AI technologies.

Singapore leads all three indices with an overall score of 65.7 of 100. Globally, AI is expected to contribute approximately US$15.7 trillion to the world’s GDP by 2030, a $2 trillion increase from 2019. In Singapore, the AI market is projected to reach US$960 million in 2022 and US$16 billion by 2030.

COVID-19 has accelerated investment in AI across economies in APAC, with governments continuing to lead the charge on these efforts. In Singapore, whole-of-government strategies are guiding the development of AI ecosystems, and the use of AI is becoming ubiquitous.

The report recommends several measures to boost economies’ effective use of AI, including having a national AI strategy backed by robust principles; growing AI ecosystems and investing in talent; ensuring trust, as well as applying AI for social good.

The study finds that Singapore’s strong commitment to AI and its robust policy and regulatory framework is allowing it to successfully maximise the impact of AI on its economy. On business readiness, Singapore scored 49.7 points. Indicators measured include digital adoption by businesses, business sophistication as well as knowledge and creative outputs. Companies in the financial services, healthcare, tourism, and transport and logistics sectors in Singapore were found to be well-equipped to adopt AI.

The report also offers three recommendations for Singapore to maximise the use of AI in a safe and inclusive manner. First is expanding participation in regional and international AI standards-setting exercises; second is sustaining investments in bridging the AI skills gap and; third is strengthening AI provisions in Digital Economy Agreements.


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