Singapore Advances Artificer Intellect by Integrating Quantum Computing & Data Hubs - Insights From ZDNet

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Singapore is looking to carve out a global footprint in artificial intelligence (AI) with the release of international standards for large language model (LLM) testing and investments in quantum computing and new data center capacity.

Quantum has the potential to unlock new value, where higher processing capabilities can be harnessed in areas such as simulating complex molecules for drug discovery, said Deputy Prime Minister Heng Swee Keat at last week’s Asia Tech x Singapore 2024 summit.

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He added that quantum computing can also have synergies with AI, for example, in improving the efficiency of developing and training advanced AI models. This development, in turn, can further drive innovations in deep learning, natural language processing, and computer vision.

However, there still are challenges to resolve in quantum, including requirements for cryogenic cooling and error correction, Heng said. He noted that researchers worldwide were assessing different approaches to achieve scale and enable quantum computing to be commercially viable.

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Singapore wants to address these challenges with its National Quantum Strategy, coupled with almost SG$300 million ($221.99 million) in investment. This cash is on top of a previous SG$96.6 million commitment announced in 2022. The new investment is earmarked for five years, through to 2030, to boost the country’s position as a leading hub in the development and deployment of quantum technologies, Heng said.

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This roadmap focuses on four areas, including initiatives in quantum research, such as quantum communications and security and quantum processors, and a scholarship program to produce 100 PhD and 100 master’s-level graduates over the next five years, he said.

Efforts are underway for Singapore to build capabilities in the design and development of quantum processors . This work will encompass research on qubit technologies , including photonic networks, neutral atoms, and superconducting circuits.

ZDNET understands Singapore’s target is to have the first prototype ready in the next three years and scale out production in five years.

The government in 2022 unveiled a three-year initiative to build a quantum-safe network that it hopes will showcase “crypto-agile connectivity” and facilitate trials with both public and private organizations. The initiative also includes a quantum security lab for vulnerability research.

Laying the ground for green data centers

Singapore last week also launched its green data center roadmap to chart “digital sustainability and chart green growth pathways” for such facilities, supporting AI and computing developments.

The country has over 1.4 gigawatts of data center capacity and is home to more than 70 cloud, enterprise, and co-location data centers.

Singapore is aiming to add at least 300 megawatts of additional data center capacity “in the near term” and another 200 megawatts through green energy deployments, said Janil Puthucheary, senior minister of state for the Ministry of Communications and Information, at the summit.

Efforts will be made to enhance efficiency through both hardware and software, Puthucheary said, pointing to technologies that maximize energy efficiency and capacity, and green software tools.

He added that improving data center efficiency is also about greening software, so the carbon emissions of applications can be reduced.

He said the focus will be placed on data centers to accelerate their use of green energy, with the government offering support via grants and incentives to switch to energy-efficient IT equipment. In addition, the Infocomm Media Development Authority (IMDA) will work with PUB to help data centers push their water usage effectiveness (WUE) to 2.0 cubic meters or less per megawatt hour, up from the 2021 median WUE of 2.2 cubic meters.

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IMDA will jointly develop standards and certifications with industry partners to drive the development and operation of data centers with power usage effectiveness (PUE) of 1.3 or lower.

In addition, the BCA-IMDA Green Mark for data centers will be refreshed by year-end to raise the standards for energy efficiency in data centers. IMDA will also introduce standards for IT equipment energy efficiency and liquid cooling by 2025, to drive the adoption of these technologies in Singapore.

The green data center roadmap outlines plans to reduce energy use for air-cooling by raising operating temperatures via IMDA’s tropical DC methodology .

According to the government agency, data centers can achieve 2% to 5% energy savings for every 1°C increase in operating temperature.

It also pointed to simulations that have found existing data centers can achieve a 50% reduction in energy consumption of supporting infrastructure, with energy-efficient retrofits and upgrades for key equipment, such as chiller plants and uninterruptible power supplies.

“We aim to uplift all data centers in Singapore to achieve PUE of less than 1.3 at 100% IT load over the next 10 years,” IMDA said. “This gives existing data centers sufficient time to plan for upgrades.”

The tech industry today emits an estimated 1.5% to 4% of global greenhouse gas emissions, Heng noted, with this figure projected to climb as the use of AI expands alongside the need for data storage and processing.

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He said technologies that drive the country’s digital economy, such as cloud and AI, fuel demand for powerful and energy-intensive computing.

“Data centers lie at the heart of such activities and require large amounts of energy for processing and cooling. Greening ICT, especially data centers, is therefore crucial in a digital and carbon-constrained world,” he said.

“There is a need to balance the economic and social benefits of digital applications with the environmental effects from the resultant emissions,” he said, noting that Singapore has committed to a net-zero target by 2050.

“The [green data center] roadmap sets out low-carbon energy sources that data centers can explore, which include bioenergy, fuel cells with carbon capture, low-carbon hydrogen and ammonia for a start,” Puthucheary explained. “We welcome proposals from the industry to push boundaries in realizing these pathways in Singapore.”

Charting global test standards for AI models

Meanwhile, the country wants to lead the way by releasing standards for large language model (LLM) testing, developed via partnerships with global organizations such as MLCommons, IBM, and Singtel.

Dubbed Project Moonshot, the LLM testing tool provides benchmarking, red-teaming, and testing baselines to help developers and organizations mitigate risks associated with LLM deployment.

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LLMs without guardrails can reinforce biases and create harmful content, with unintended consequences. “IMDA is seeking to establish guardrails to manage the risks while enabling space for innovation,” the government agency said.

“It is important to adopt an agile, test-and-iterate approach to address key risks in model development and use. Project Moonshot provides intuitive results, so testing unveils the quality and safety of a model or application in an easily understood manner, even for a non-technical user.”

The testing tool provides a five-tier scoring system where each completed scoring sheet will place the application on a scale. Grade cut-offs can be determined by the author of each of these scoring sheets.

AI Verify Foundation and MLCommons jointly developed the testing LLM benchmarks. The latter is an open-engineering consortium supported by Qualcomm, Google, Intel, and NVIDIA and recognized by the US National Institute of Science and Technology under its AI Safety Consortium. AI Verify Foundation is Singapore’s not-for-profit foundation that focuses on developing AI testing tools.

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Project Moonshot is currently available as an open beta.

IMDA said it is working with companies such as Anthropic to develop a practical guide to multilingual and multicultural red-teaming for LLMs. The guide is slated for release later this year for global use.