Modern moderation systems increasingly support multiple languages, but often fail to address localisation and low-resource variants - creating safety gaps in real-world deployments. Small models offer a potential alternative to large LLMs, yet still demand considerable data and compute. We present LionGuard 2, a lightweight, multilingual moderation classifier tailored to the Singapore context, supporting English, Chinese, Malay, and partial Tamil. Built on pre-trained OpenAI embeddings and a multi-head ordinal classifier, LionGuard 2 outperforms several commercial and open-source systems across 17 benchmarks, including both Singapore-specific and public English datasets. The system is actively deployed within the Singapore Government, demonstrating practical efficacy at scale. Our findings show that high-quality local data and robust multilingual embeddings can achieve strong moderation performance, without fine-tuning large models. We release our model weights and part of our training data to support future work on LLM safety.

Large Language Models (LLMs) are emerging as powerful tools in healthcare, particularly for complex, domain-specific tasks. This study describes the development and evaluation of the PErioperative AI CHatbot (PEACH), a secure LLM-based system integrated with local perioperative guidelines to support preoperative clinical decision-making. PEACH was embedded with 35 institutional perioperative protocols in the secure Claude 3.5 Sonet LLM framework within Pair Chat (developed by Singapore Government) and tested in a silent deployment with real-world data. Accuracy, safety, and usability were assessed. Deviations and hallucinations were categorized based on potential harm, and user feedback was evaluated using the Technology Acceptance Model (TAM). Updates were made after the initial silent deployment to amend one protocol. In 240 real-world clinical iterations, PEACH achieved a first-generation accuracy of 97.5% (78/80) and an overall accuracy of 96.7% (232/240) across three iterations. The updated PEACH demonstrated improved accuracy of 97.9% (235/240), with a statistically significant difference from the null hypothesis of 95% accuracy (p = 0.018, 95% CI: 0.952-0.991). Minimal hallucinations and deviations were observed (both 1/240 and 2/240, respectively). Clinicians reported that PEACH expedited decisions in 95% of cases, and inter-rater reliability ranged from kappa 0.772-0.893 within PEACH and 0.610-0.784 among attendings. PEACH is an accurate, adaptable tool that enhances consistency and efficiency in perioperative decision-making. Future research should explore its scalability across specialties and its impact on clinical outcomes.

SINGAPORE – Prime Minister Fumio Kishida and his Singaporean counterpart, Lee Hsien Loong, have reaffirmed their commitment to uphold the rules-based international order amid Russia's aggression against Ukraine and China's growing military and economic clout. During talks Friday at Singapore's Changi Airport following a six-day visit to Africa, Kishida told Lee that negotiations on a deal that would allow the transfer of defense equipment and technology between the two countries are making progress, according to the Japanese Foreign Ministry. "We want to strengthen security and defense cooperation," Kishida was quoted as saying, while also calling for deepening cooperation in areas such as start-ups and building resilient supply chains. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites.

In the shipping industry, document classification plays a crucial role in ensuring that the necessary documents are properly identified and processed for customs clearance. OCR technology is being used to automate the process of document classification, which involves identifying important documents such as Commercial Invoices, Packing Lists, Export/Import Customs Declarations, Bills of Lading, Sea Waybills, Certificates, Air or Rail Waybills, Arrival Notices, Certificate of Origin, Importer Security Filings, and Letters of Credit. By using OCR technology, the shipping industry can improve accuracy and efficiency in document classification and streamline the customs clearance process. The aim of this study is to build a robust document classification system based on keyword frequencies. The research is carried out by analyzing Contract-Breach law documents available with IN-D. The documents were collected by scraping the Singapore Government Judiciary website. The database developed has 250 Contract-Breach documents. These documents are splitted to generate 200 training documents and 50 test documents. A semi-automatic approach is used to select keyword vectors for document classification. The accuracy of the reported model is 92.00 %.

In the future, if armies deploy autonomous robot soldiers and they fire on the wrong targets, who will we hold responsible - the general who deployed them or their designer, Singapore law professor Simon Chesterman asks in We, the Robots.

Spear phishing is a social engineering technique targeted towards a targeted individual to divulge confidential information. But creating highly targeted mass spear-phishing emails could take a lot of effort and time. In a recent test conducted by a team of researchers, it was found that they could use Natural Language Processing (NLP) to devise targeted phishing emails. At the end of the research, the team revealed that AI/ML could be used to develop spear-phishing campaigns at a devastating scale. In the recently held Black Hat Defcon security conference in Las Vegas, a team of researchers hailing from the Singapore Government Technology Agency presented the results of their AI/ML generated phishing email test.

Illustration: Chaitanya Dinesh Surpur Artificial intelligence (AI) is fast becoming a topic that is relevant to everyone today and, therefore, a subject that everyone ought to learn at least the rudiments of, say experts. From the humble milkman delivering packets of milk to households in the morning to the highest lawmakers and biggest industrialists, AI will increasingly touch everyone. "A lot of people look at AI as a vertical that calls for experts to develop," says Amit Anand, founding partner at Jungle Ventures, a VC firm in Singapore that has invested in several tech startups in India. However, both in his own mind and as an advisor to the Singapore government on the ethical use of AI, "We have taken a view that AI is going to affect everybody, and hence everyone should be knowledgeable and have a certain level of understanding of AI." Click here to see Forbes India's comprehensive coverage on the Covid-19 situation and its impact on life, business and the economy You can buy our tablet version from Magzter.com. To visit our Archives, click here.)

The Github repo for this post contains a notebook and the data needed to generate some of the charts in this post, as well as a sample of the Plotly chart and CSV table of the results. The code can be easily tweaked if you wish to generate results for multiple speeches in one go. The data comprises six official speech transcripts taken from the websites of the Singapore Government as well as the Prime Minister's Office. These speeches focused on the Government's plans to deal with the challenges from Covid-19, and are set to frame the broader debate for Singapore's upcoming election. Some excessively long chunks of text were broken up into smaller paragraphs for a fairer assessment of the sentiment, but the vast majority of the speeches were analysed in their original form.

Retailers in Asia-Pacific are struggling to unite online and offline data and this will hinder their ability to recognise customers who engage with their brands across both channels. Furthermore, while most acknowledge the importance of artificial intelligence (AI) to their organisation's competitiveness, few have started to deploy such tools. While some retail organisations recognised the need to straddle both the online and offline channels, the biggest challenge these omnichannel retailers faced today was pulling data from both realms to establish a common view of their customers, said Raj Raguneethan, Microsoft's Asia regional business lead for retail and consumer goods. This gap hindered their ability, for instance, to recognise customers who had engaged the brand online when they walked into a physical store. To plug the gap, Raguneethan said retailers should establish a data management platform to pull together all customer information and stitch these together to provide unified profiles of their customers. With the launch of its national artificial intelligence (AI) strategy, alongside a slew of initiatives, the Singapore government aims to fuel AI adoption to generate economic value and provide a global platform on which to develop and testbed AI applications.

Singapore's digital national trade platform has launched Tradeteq's AI-based credit scoring system to enable its users to better assess counterparty risk in trade deals. The system is being used to leverage various data sources to provide thorough credit reports for users of Singapore's Networked Trade Platform (NTP), including data on each company in the supply chain as well as each receivable. The NTP is a digital national trade information management system backed by the Singaporean government, which aims to make trade flowing through Singapore more efficient. Launched in September last year, the NTP brings the entire trade ecosystem to a single online location, digitising the trade processing process. It replaced two existing trade facilitation platforms in Singapore, TradeXchange and TradeNet.