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Business Times
5 days ago
- Business
- Business Times
NIE, Amazon Web Services set up AI-focused innovation hub for edtech research
[SINGAPORE] The National Institute of Education (NIE) and Amazon Web Services (AWS) on Thursday (May 29) announced the launch of the Technology for Education Centre (TEC) – a new initiative aimed at driving applied innovation and research in the space of education technology. A three-year memorandum of understanding was signed between the two organisations for this venture. The partnership is expected to facilitate research and experimentation with emerging technologies in education, including artificial intelligence (AI) and cloud computing. NIE is an autonomous institute within Nanyang Technological University (NTU). TEC will be located on NIE's campus, and is designed as a collaborative hub where student teachers, academics and education researchers can prototype and test new learning tools. It will be housed in a new annex building at NIE, as part of an initiative to refresh the campus, and will be ready around the same time as the opening of Nanyang Crescent MRT station, which will serve the NTU Smart Campus. The centre is fundamentally intended to provide an environment for both the development of edtech and its application in real-world settings. A NEWSLETTER FOR YOU Friday, 3 pm Thrive Money, career and life hacks to help young adults stay ahead of the curve. Sign Up Sign Up The initiative supports Singapore's broader ambitions under the National AI Strategy 2.0 to develop an AI-ready workforce. It also aligns with the community pillar of AWS' ongoing AI Spring Singapore programme, which is designed to equip 5,000 individuals with AI skills from 2024 to 2026. In May 2024, AWS announced that it would be investing S$12 billion in Singapore's cloud infrastructure by 2028, with its expected contribution to Singapore's gross domestic product at S$23.7 billion, while supporting more than 12,000 jobs annually. One of TEC's early goals will be to advance cloud-based learning and upskilling for educators. Resources such as AWS Skill Builder and cloud simulations will be made available to help participants strengthen their digital competencies. Additionally, the centre will support applied research projects that seek to integrate AI and analytics into teaching practices and policy development in Singapore. NIE director Professor Liu Woon Chia said the partnership will help to 'shape the future through ethical and inclusive use of technology' at a media briefing. 'We must teach our teachers differently so they can ensure students learn differently, paving the way for an education that is future-ready.' The venture also includes student-driven service-learning initiatives that leverage generative AI tools such as Amazon Bedrock and Amazon Q Developer to address community challenges. TEC will serve as a training ground through workshops, hackathons and forums that explore ethical issues related to AI in education, such as data privacy and bias, in addition to prototyping and research. When asked about the number of students that will benefit from this initiative, Prof Liu said every student teacher at NIE will have the opportunity to experience the process of learning and solutionising with AI at TEC. 'Not all students may be involved in the creation of prototypes, but we are confident that many will want to be involved.' Elsie Tan, AWS' country manager, public sector (Singapore), said the partnership highlights the role of educators in preparing future-ready workers. 'We are helping to equip the education sector for the digital age by combining NIE's pedagogical leadership with AWS' cloud capabilities,' she said. Position on industry partners While AWS is the first industry partner, Prof Liu noted that it would not be the only one. 'Right now, AWS is a front runner in terms of technology expertise. At NIE, we know the pedagogy and our students, so this collaboration will allow us to accelerate a tech-enabled education we envision,' she said. Prof Liu said 'an experimental space' setting is envisaged for the TEC, where students, faculty and AWS specialists can collaborate in an environment where solutions can be developed to meet the needs of students and society at large. 'We want some student teachers working on certain projects to be able to work with the people at TEC to build their prototypes and create solutions with the technology available,' she said.
Techday NZ
26-05-2025
- Business
- Techday NZ
If you view AI as purely technical, your projects will fail
Use the right training strategy to bring every employee on your AI journey Originally published on iTNews, we share insights on the need for an organisation-wide program to plan for, upskill in and implement artificial intelligence technology. The extraordinary capabilities of generative AI (genAI) platforms have captured the business world's imagination – and a growing portion of its IT budgets. Yet even as tech giants work to make genAI technology more accessible, experts warn that companies focused solely on that technology are bound to fail. That's because genAI isn't a silver bullet for every business problem. Simply directing developers and IT leaders to join the stampede towards the technology is unlikely to deliver the benefits business leaders want from it. "Organisations have a wide variety of reasons" for embracing AI, noted James Finley, Senior Systems trainer with training provider Lumify Work (formerly DDLS in Australia and Auldhouse in New Zealand). Lumify offers a range of AI-intensive training courses, including its 8-week CloudUp and AWS Generative AI Accelerator boot camps, AWS Skill Builder on-demand digital training, and AI-related practitioner certifications. In working with early adopters across the ANZ region, Finley has seen companies embrace AI for both internally focused projects—those using the technology to improve internal efficiencies—and those building "externally facing solutions" to support customer care and other operations. "Every organisation is different, and it comes down to what their first jumping-off point is," Finley said, "but I am seeing people coming from a wide variety of platforms." Perhaps instinctively, he noted, early adopters are often technical – data platform experts, infrastructure, sysops or developer team members – with many people doubling up on roles as enthusiastic team members expand their skills in more than one area. Many companies "are looking at people they know and trust internally to get that foothold," he explained, "but when they get some known quantities and start saying that they need more staff, they need someone who understands the business and what they're trying to achieve." Moreover, according to the Accelerating AI Skills: Preparing the Asia Pacific Workforce for Jobs of the Future report, while almost every department in an organisation can derive significant value from AI applications, many view just three departments as getting the most benefits, when in reality, AI should boost all parts of the organisation. In Australia, the perceived top three AI beneficiaries are IT (87 per cent), sales and marketing (83 per cent), and business operations (82 per cent). In New Zealand, the big three AI beneficiaries are IT (86 per cent), sales and marketing (85 per cent), and finance (83 per cent). Extending AI from technical project to business driver Changing your approach from technical project to business driver is essential for AI success, and truly integrating AI into the business requires time, patience, and widespread buy-in. Without such buy-in, many executives risk becoming disillusioned by AI in the short term, Gartner recently advised, predicting that companies will abandon 30 per cent of genAI projects by the end of 2025. This attrition will be written large as organisations drop millions on integrating genAI services into their apps and building custom models from scratch, then find they solved a different problem than they needed to—or commit resources to solving business problems without considering whether AI is even the appropriate solution. The benefits of genAI "are very company, use case, role and workforce specific," Gartner distinguished VP analyst Rita Sallam said, noting that the impact of genAI projects "may not be immediately evident and may materialise over time." Keeping that focus can be tough given the sheer breadth and capability of genAI and broader AI capabilities available through APIs that tap services like AWS Bedrock, which offers developers a smorgasbord of technological solutions encompassing a range of genAI technologies. Indeed, some estimates suggest that 80 per cent of AI projects will fail—twice the rate of non-AI projects—with one recent study blaming a range of issues, including stakeholders failing to effectively communicate the problem that needs solving, the lack of the necessary data and infrastructure to train and deliver AI, or teams focused more on the latest and greatest technology than on solving real problems for their users. "The foundation models are capable of doing a whole bunch of things," said AWS technical trainer Peter Vandaele, "and then it's up to you as a programmer or as a developer to focus it so you can integrate that into your own application." "We try to be very, very broad and allow you to use that inside your application through a simple, unified API that lets you start adding more things like extra knowledge bases or even giving it agency to execute tasks." "It's not doing your job, but it is an assistant." Where are the champions? Many technical staff will have dabbled in AI for their own knowledge – either by experimenting with hosted AI systems or by working on early-stage pilot programs – but companies looking to get serious about AI must consider a more structured program of technical and business training to ensure the whole company is on board. "Understanding how to unlock the technology through core cloud training and skills is absolutely critical to be able to make the most of AI," explained Leif Pedersen, APAC cloud and AI product manager with Lumify Work. Once known as Dimension Data Learning Services (formerly DDLS in Australia and Auldhouse in New Zealand), Lumify has positioned its broad range of technical and business training offerings as what Pedersen called a "one-stop shop for organisations and customers to come get everything they need from a training and development certification point of view." Yet such training is only part of the change that companies need to plan to make their AI and genAI projects a success: companies also need to cater to non-technical teams by establishing internal teams to advocate and train employees in ways that are meaningful to them. As in many other business change projects, the appointment of 'champions of change' can be invaluable to helping extend AI culture across the organisation. "Any sort of adoption process or cultural change inside an organisation, really just needs some champions to pick it up," Pedersen said, noting that companies choosing technical AI training should also consider how to identify and train those champions. Ultimately, technical teams and AI-focused managers should engage with those champions to build end-user acceptance of new technologies that will improve how they work. "This is not something that should be forced down from the top," said Vandaele. "You want buy-in from the ground up, and training can really help blanket the organisation with education." This is particularly important regarding genAI, he added, because "there's a lot of talk about it, a lot of buzz, and a lot of myths and fear going around." "The more we know about something and the more we understand something, the less we fear it – so it is going to be really important moving forward that organisations spend time really creating buy-in on a very broad level."
Time Business News
12-05-2025
- Business
- Time Business News
Which Cloud Computing Course Is Right for You? AWS, Azure, or Google Cloud?
Cloud computing is no longer a niche skill, but rather a foundational piece of modern IT infrastructure, software development, and digital innovation. If you're ready to embark on a path toward becoming a cloud engineer or you're an established IT professional seeking transition, considering the appropriate cloud computing course could have a meaningful impact on your career for many years to follow. Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) are among the three most prominent platforms, each having its own advantages compared to the others. But how do you determine which one is right for you? This guide will outline what each offering has and suggest the course that is best aligned with your goals, field, and area of technical expertise. Demand is spiking for cloud-certified experts, as companies of every size move to the cloud. This is not just a function of storage and scalability; it is all about speed, cost, security, and innovation. Higher salaries and job security Roles across DevOps, data science, AI/ML, security, and architecture Opportunities to work in hybrid, multi-cloud, or serverless environments Certifications from AWS, Azure, or Google Cloud validate your expertise and prove you're ready to take on modern cloud infrastructure challenges. Amazon Web Services (AWS) is the largest cloud provider and has been the industry leader in cloud services for more than a decade. It is utilized by businesses, governments, startups, and individual developers worldwide. Professionals looking for maximum job flexibility Engineers aiming to work in startup and enterprise environments Individuals who want broad exposure to cloud services AWS Certified Cloud Practitioner – A beginner-friendly entry point – A beginner-friendly entry point AWS Certified Solutions Architect – Associate – Great for aspiring architects – Great for aspiring architects AWS Certified DevOps Engineer – Ideal for DevOps and automation roles AWS Skill Builder (official) A Cloud Guru Udemy's AWS Bootcamps AWS is a great place to start if you want to build a well-rounded cloud foundation. If you're working in an organization that heavily uses Microsoft products (like Windows Server, Office 365, or Active Directory), Azure is the natural extension of that ecosystem. Azure's deep integration with enterprise tools makes it the go-to platform for corporations and governments. IT pros already familiar with Microsoft technologies Developers in enterprise and .NET environments Cloud architects targeting corporate or government roles Microsoft Certified: Azure Fundamentals (AZ-900) Azure Administrator Associate (AZ-104) Azure Solutions Architect Expert (AZ-305) Microsoft Learn (free, interactive modules) Pluralsight (partnered with Microsoft) LinkedIn Learning – Azure-focused content Azure is the best choice for those who want to thrive in enterprise-grade IT environments. Google Cloud is known for its leadership in AI, machine learning, data analytics, and open-source technologies like Kubernetes and TensorFlow. GCP is often chosen by tech-forward startups, developers, and researchers. Data engineers and scientists AI/ML professionals Developers working with open-source, scalable applications Associate Cloud Engineer – A solid starting point – A solid starting point Professional Cloud Architect – Advanced architecture certification – Advanced architecture certification Professional Data Engineer – Ideal for data-driven roles Google Cloud Skills Boost (official) Coursera – Google Cloud specialization Qwiklabs – Interactive, hands-on GCP labs Choose Google Cloud if your focus is on big data, analytics, and AI innovation. Each cloud platform supports different career paths. Here's how they generally align: Career Path Best Platform Cloud Infrastructure AWS or Azure DevOps Engineering AWS or Azure Enterprise IT Management Azure Data Science/Analytics Google Cloud AI/ML Engineering Google Cloud or AWS Cloud Architecture All (AWS, Azure, GCP) If you're still unsure, start with a foundational course on any platform. Once you have a basic grasp, it's easier to branch into more specialized roles. Here are some questions to guide your decision: Are you already working in a Microsoft-centric environment? → Go with Azure → Go with Do you want the most job opportunities globally? → Choose AWS → Choose Are you aiming for AI, data, or startup work? → Pick Google Cloud → Pick Do you want to work in government or regulated industries? → Azure is often preferred → Azure is often preferred Are you starting from scratch? → AWS or Azure offer more beginner content While choosing a platform to start with is essential, becoming familiar with multiple cloud environments is becoming the norm. Many companies are embracing multi-cloud strategies to avoid vendor lock-in and improve resilience. Once you've gained confidence in one platform, consider expanding into another. Being certified in both AWS and Azure (or GCP) can set you apart as a multi-cloud expert—a highly sought-after skill set in today's market. The cloud journey is long, not short. The best platform to start on depends on your goals, technical background, and regional job market or industry. If you are new and want to develop a more general, flexible skill set: AWS is your best first choice in a cloud platform If you work in enterprise IT, or job role primarily uses Microsoft tools: Azure should be your first platform If you want to get into data science, ML, or startup: Google Cloud You won't be able to meaningfully explore your other options on any platform until you get your first certification, gain some fundamental knowledge of the cloud, and understand how cloud platforms work, the cloud is vast, there is no ending to your learning journey after one course… it is just the beginning. TIME BUSINESS NEWS
