Singapore has launched a national artificial intelligence (AI) programme in finance to build deep AI capabilities in its financial sector and strengthen customer service, risk management and business competitiveness. Announced by Singapore's deputy prime minister, Heng Swee Keat, at the Singapore FinTech Festival, the programme is a joint initiative by the Monetary Authority of Singapore (MAS) and the National AI Office at the Smart Nation and Digital Government Office (SNDGO). Through the programme, which is part of Singapore's broader national AI strategy, financial institutions will be able to enhance their ability to research, develop and deploy AI solutions to increase productivity and create new jobs, among other goals. MAS and SNDGO will provide funding, contribute government data and bring together experts to drive AI adoption in the financial sector. One of the key initiatives to be developed under the programme is an AI technical platform called Nova! to generate insights on financial risk.

A new generation of farmers is turning to technologies such as the internet of things (IoT) and machine learning to automate agricultural production, alleviating the need to toil on the land while keeping a watchful eye on their crops. Joining their ranks is Phoebe Xie, director and co-founder of Singapore-based agrotechnology startup AbyFarm. Teaming up with technology service provider SPTel, Xie is building a smart hydroponics farm in a greenhouse that uses a plethora of IoT sensors, including video cameras, to keep the farm humming around the clock. "To run a self-regulating farm at optimal temperature with optimal water and nutrient supply, and to control the quality and taste of vegetables and fruits, we need IoT sensors," she said, adding that the farm and its sensors collect and monitor thousands of data points, including humidity and temperature. With the data and in certain environmental conditions, processes and actions are automatically triggered to protect crops from the elements.

The objective of most Reinforcement Learning painting agents is to minimize the loss between a target image and the paint canvas. Human painter artistry emphasizes important features of the target image rather than simply reproducing it (DiPaola 2007). Using adversarial or L2 losses in the RL painting models, although its final output is generally a work of finesse, produces a stroke sequence that is vastly different from that which a human would produce since the model does not have knowledge about the abstract features in the target image. In order to increase the human-like planning of the model without the use of expensive human data, we introduce a new loss function for use with the model's reward function: Content Masked Loss. In the context of robot painting, Content Masked Loss employs an object detection model to extract features which are used to assign higher weight to regions of the canvas that a human would find important for recognizing content. The results, based on 332 human evaluators, show that the digital paintings produced by our Content Masked model show detectable subject matter earlier in the stroke sequence than existing methods without compromising on the quality of the final painting.

SINGAPORE - Businesses in Singapore are set to benefit from free health screenings to spot weaknesses in their Web domain, e-mail system and connectivity. This freely provided diagnostic is part of the newly unveiled Safer Cyberspace Masterplan 2020 that aims to protect Singapore's digital sphere. The national plan also outlines the use of artificial intelligence (AI) to sniff out security threats in key infrastructure, including broadband and 5G networks, and consumer devices such as webcams and Wi-Fi routers. Coordinated by the Cyber Security Agency (CSA) of Singapore, the masterplan is central to Singapore's plans to lead in AI and smart nation deployments globally, and comes amid rapid digitalisation in recent months. "The pandemic accelerated the pace of change... Telecommuting, video calls, e-learning, online shopping, and digital payment surged," said Deputy Prime Minister Heng Swee Keat in unveiling the masterplan on Tuesday (Oct 6).

In 2019, companies looking to gain an edge on competitors and insight into customers and trends have come to rely more heavily on data scientists to inform their business decisions. A good data scientist is invaluable to a company with any online presence. They will assess and interpret complex information and build out machine learning algorithms. Data volume keeps growing, and the amount of skill and effort needed to create data-driven initiatives is certainly keeping pace with that growth. Mistakes can produce huge consequences and, while the tools may change, the mistakes stay the same. Over the course of my career I've seen every permutation of these common mistakes, and my hope here is to help you identify and avoid them within your own teams.

SINGAPORE: By 2022, people living in Singapore will be able to report municipal issues via a chatbot that asks for details in real time and automatically identifies the correct government agency in charge. This will be made possible by artificial intelligence (AI), which is also set to power a tool that helps in the detection of diabetic eye disease and an automated marking system for English in primary and secondary education by the same year. More initiatives tapping on AI technologies, such as machine learning and computer vision, are in the pipeline over the next decade, according to five projects unveiled on Wednesday (Nov 13) as part of Singapore's new "National AI Strategy". The new strategy, which maps out how Singapore will develop and use AI to transform the economy and improve peoples' lives, was announced by Deputy Prime Minister Heng Swee Keat at the final day of the "Singapore FinTech Festival (SFF) x the Singapore Week of Innovation and TeCHnology (SWITCH) Conference". Describing it as the next step in Singapore's Smart Nation Journey, Mr Heng said: "Countries will need to keep pace with technology, and harness it to tackle common challenges and national priorities."

TEACH a man how to fish, and you can feed him for a lifetime. Homegrown artificial intelligence (AI) company Xjera Labs aims to do just that, with the aid of neural networks and deep learning algorithms. Its AI engine Athena can train software to perform specific tasks, whether these pertain to recognising sushi, teaching drones to fly or spotting intruders. The company's co-founder and chief executive Ethan Chu compares Athena to a school for its "pupils" - in Xjera's case, these are its products named XIntelligence, XTransport and XHound. Taken together, the trio offers a bevy of functions, including facial recognition, emotional analysis and identifying vehicle types.

NANJING: China has been invited to test its artificial intelligence (AI) solutions in Singapore and work together to help the region tackle everyday problems in areas such as healthcare and banking. Minister for Finance Heng Swee Keat made this invitation at the first Sino-Singapore Artificial Intelligence Forum in Nanjing on Friday (Jun 1), which was attended by about 350 AI experts from both countries. During his speech, which was partly delivered in Chinese, Mr Heng said that there was big potential for both countries to develop AI. "For example, the Monetary Authority of Singapore has a financial technology (Fintech) sandbox for companies to develop new financial solutions before launching them in the market," said Mr Heng, who is also in China for a series of meetings. Sandboxes are platforms that allow software to be securely tested in an environment where legal and regulatory requirements are relaxed. The Land Transport Authority is also testing driverless vehicle systems in such sandboxes in Singapore, Mr Heng said.

Support Vector Machine (SVM) is an efficient classification approach, which finds a hyperplane to separate data from different classes. This hyperplane is determined by support vectors. In existing SVM formulations, the objective function uses L2 norm or L1 norm on slack variables. The number of support vectors is a measure of generalization errors. In this work, we propose a Minimal SVM, which uses L0.5 norm on slack variables. The result model further reduces the number of support vectors and increases the classification performance.

The firm says it will grow its team to more than 100 researchers and engineers by the end of the year, and has already moved several staff from its new Autonomous Driving Unit (ADU) to Sunnyvale and hired a Tesla Autopilot software engineer. Liang Heng, a PhD graduate in Electrical Engineering from Stanford, joined Tesla last year after CEO Elon Musk requested hardcore software engineers join the firm's efforts to make its Autopilot system fully autonomous. He has left Tesla after just 5 months to join Baidu's team as a software architect. Before joining Tesla, Heng worked at Google on Street View. The person in charge of Baidu's ADU, Jing Wang, also just happens to be a former Google employee.