Microsoft Copilot for M365 is the generative AI that revolutionises organisations’ efficiencies by surfacing strategic insights, finding information, assisting with the curation of content, even summarising and planning your day as efficiently as clicking a button! What is missing from this equation is that deploying the technology isn’t as simple as flicking a switch and ‘going live” with Copilot for Microsoft 365. While the competitive advantage Copilot for Microsoft 365 offers is unparalleled, ensuring the protection of your organisation and its information assets requires more than activating the licenses.

This article examines the necessary preparation organisations should go through to prepare and mitigate potential pitfalls before integrating Copilot for Microsoft 365 into your organisation.

Despite the recent surge in interest in AI over the last 12 months, generative AI is a relatively young discipline as a technology that can engage with everyday users conversationally. Just a few years ago, AI was confined to academic research institutions, the subject of peer-reviewed papers and the research conference circuit. Organisations like OpenAI brought this technology to everyday users and now the workplace has realised the possibilities that context-based GenAI offers, igniting the interest in Copilot for Microsoft 365.

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Copilot for Microsoft 365  allows users and workgroups to automate their day, collaborate more efficiently, be more productive and use collated data from across the organisation to make more informed decisions; all based on information reserves that are continually added to.

While there are benefits generative AI can bring, organisations must address significant concerns regarding security and data governance when embracing such technology.

Here we delve into three steps crucial for the successful implementation of generative AI:

 Step One: Prepare the Environment and Consolidate Your Data

“Make Microsoft 365 the core of organisational information “

Making Microsoft 365 the core basis for business data, and therefore business intelligence is the most operationally logical choice for the majority of organisations. Most IT professionals understand that information becomes much more valuable when it is at users’ fingertips in the most-used platforms, rather than kept  in isolated silos. Migrating data into M365 allows the smart algorithms of Copilot for Microsoft 365 to access relevant information, enabling the AI to enhance its understanding of how your organisation works based on the information available to it.

Fortunately, the AvePoint Confidence Platform helps organisations achieve this consolidation of content through migration, a process which goes beyond a straightforward lift-and-shift.

AvePoint Fly empowers organisations to move from on-premises or remote email to digital collaboration platforms like Google Workspaces, Box, Dropbox, Slack and other collaboration platforms to M365. It discovers and maps existing applications and content, creating migration schedules that minimise operational disruption and downtime. With multiple legacy tenants’ data in one place, businesses can start to better capitalise on their digital resources immediately.

Step Two: Identify and Organise

“Strengthen your data to enable strong Copilot for M365 results”

AvePoint’s Insights and Policies provides the framework to identify high risk content and build efficient and compliant workflows automatically to remediate any potential breaches. Reviewing and strengthening information security provides the ability to establish a solid foundation, encompassing robust cyber protections, identifying areas of sensitive and overshared content and classifying of information according to sensible privilege rules. This is a vital preparatory stage to protect your intellectual property (IP) and ensure your information remains secure and accessible to the right audience.

AvePoint Opus streamlines the classification and organisation of information within M365 (amongst other repositories), ensuring a standard approach to manage content that minimises user intervention. The aim is to ensure information remains accessible and supports compliance with relevant standards and legislation while being available to those who need it.

Simultaneously, organisations should reassess privilege hierarchies and security rules, considering the large investments in solutions like Teams, Groups, OneDrive, SharePoint, Power Automate and so on. Resolving and revising access accumulated access rights accrued over the years, helps bolster security and internal operational efficiency through simplification and consolidation.

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Step Three: Continuous data management

“Ensuring relevant resources”

Tools such as Copilot for Microsoft 365 increase their value to the organisation over time, as they continually improve and refine their capabilities with the accumulation of information.

This is however contingent on the accuracy of your information. Keeping information that is no longer relevant and no longer serves a purpose can impact on the accuracy of machine learning’s findings. Information may represent older products or abandoned work practices that are no longer suitable for the organisation’s current environment.

It is however important to properly store and archive all data, both for compliance and as a source of contextual information for business intelligence with Copilot AI. Here, AvePoint Opus has you covered, keeping data accessible and secure.

Addressing ‘data hygiene’ regularly is imperative, yet many organisations have the resources to manage every aspect of their information assets. AvePoint   automates content lifecycle management by automating the archival of inactive or ROT content and disposing of content that has exceeded its regulatory lifecycle. Furthermore, addressing data hygiene issues also offers a mechanism to reducing storage costs associated with M365.

As outlined in this article, the presence of shadow IT and siloed information can significantly impact the effectiveness of generative AI-driven content curation. Just having access to Copilot for M365 as part of a M365 license does not guarantee quality generate content. Without careful consideration of the organisations information structures, classification methods and content lifecycle management, the potential power of generative AI tools are unrealised.

For organisations committed to realising the maximum benefits of Copilot for M365, we recommend seeking specialised guidance to become “AI ready”. As an early adopter of machine learning technologies, AvePoint has assisted hundreds of organisations across various customer segments to unlock the full potential of generative AI.

With AvePoint’s expert guidance, you can navigate the Copilot for Microsoft 365 journey confidently, leveraging  technology that is specifically designed to deliver optimal results.

To find out more about Copilot for M365 and how it and AvePoint can transform your organisation’s approach to data-based driven operations, contact AvePoint for a demo.

The post 3 Steps to Successfully Automate Copilot for Microsoft 365 Implementation appeared first on Tech Wire Asia.

Recent mainstream media coverage of Canada Air’s AI bot mis-step and a New York lawyer’s submission of hallucinated case law show that, at least in the public’s perception, running effective AI instances leaves a great deal to be desired.

Perhaps the disparity between the technology’s potential and its real-world worst-case outcomes is down to the nature of decision-making in large organizations. In fact, an Innovation Catalysts study published this year found that 81% of business decision makers believe there are reasons to exclude the IT department from strategic business decision making. Sure, the IT function has a responsibility to investigate and advocate for technology’s benefits, but it could be argued that there may be broader enterprise concerns that need to be addressed which involves all stakeholders, including IT.

The advantages of deploying AI in workflows for data processing, creativity, and operations are well-known, although every use case varies according to the organization and its approach. But harnessing the technology in production where results are based on local data means considering safeguards around intellectual property and legal & compliance issues, plus the need to embed transparency into the solution. This transparency is important to satisfy regulatory authorities concerned over issues like data processing and sovereignty, as well as customers’ and service users’ concerns about privacy and data practice.

Trustworthy generative AI is a phrase that encompasses a set of smart services and practices that ensure safe operation: trustworthy, legally compliant, and transparent. Building those necessary elements is not a simple undertaking and represents a significant addition to the normal overheads associated with machine learning (compute and storage), and includes extra processes like query & response validation, bias monitoring, data sanitization, and provenance checking.

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Some vendors offer pre-trained models that can form some of the basis of a GenAI solution. But until now, there has been nothing on the market where a solution includes data security, use and development guardrails, manageability, and vendor support. In short, those elements that are mandatory to transform what’s essentially experimental (and therefore has potential risk) into a reliable production-ready platform – which is what Dell and NVIDIA can now offer.

The AI industry is doing its best to address many of the needs of larger organizations that are concerned about some of the potential misfirings that a premature rollout of GenAI could create. NIST’s Artificial Intelligence Safety Institute Consortium (AISIC), for example, has come about to create safe and trustworthy artificial intelligence and comprises more than 200 bodies. It produces empirically backed standards for AI measurement and policy, so organizations leveraging GenAI have guides to safe and legal AI deployment.

NVIDIA, a key member of AISIC, now offers NeMo Guardrails which is designed to support enterprise data security and governance standards, acting as a two-way arbiter between user queries and AI responses.

In enterprise use cases, working with internal data also brings challenges with regard to an organization’s intellectual property. Without proper safeguards, any GenAI instance represents a potential danger to an organization’s ongoing viability. It’s with that challenge and those detailed above that Dell and NVIDIA have partnered to offer a GenAI system that boasts topical, safety and security features, producing the closest to a production-ready, drop-in GenAI solution currently available on the market.

Dell Technologies’ Generative AI Solutions encompass best-of-breed infrastructure designed to greatly simplify the adoption of generative AI for organizations that need the power of machine learning technologies to leverage the value of their digital assets without compromising their ethos, data, customers, or third parties.

Based around the Dell PowerEdge XE9680 GPU-accelerated server, it’s designed for generative AI training, model customization and large-scale inferencing. It comes with NVIDIA AI Enterprise software, which allows rapid deployment of production-ready models in local, hybrid, and remote computing topologies.

The Dell Generative AI Solution range is highly scalable, with hardware that can be expanded according to need, with eight NVIDIA H100 or A100 GPUs fully interconnected with NVLink. The air-cooled 6U devices offer any variation of local and remote deployment at a lower TCO than equitable processing power from other vendors.

With NVIDIA AI Workbench, developers can experience easy GPU environment setup and the freedom to work, manage, and collaborate across workstation and data center platforms regardless of skill-level.

The combination of hardware and software designed from the ground up for generative AI development and deployment, comes with guardrails, data governance, and security baked in. Together, the two mean that organizations can deploy powerful AI-based applications safely and responsibly.

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Building trustworthy generative AI means greater buy-in from business decision-leaders outside IT, as many of their rightly-held concerns around the technology are addressed: transparent development and use, safeguarded IP and customer-facing responses, statutory compliance, and best-in-class operating costs.

To find out more about how the Dell Generative AI Solution portfolio takes machine learning to a fully-viable production setting, contact your nearest representative.

Dell Technologies: https://www.dell.com/en-sg/dt/solutions/artificial-intelligence/generative-ai.htm

NVIDIA: https://www.nvidia.com/en-sg/ai-data-science/generative-ai/

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In one of the largest and widest-reaching surveys on IT in recent years, the Innovation Catalysts study quizzed over 6,000 respondents globally, who gave their answers to a range of queries around innovation, AI, and ML and how their organizations were responding to new technology. (The full survey from Dell Technologies is available here.) The majority of IT professionals (85%) agreed with the proposition that AI and GenAI will significantly transform their industry. And 76% of respondents reported that their organization is already providing intelligent technology in the form of AI optimization software that improves their work experiences.

Given the obvious benefits of AI to all business functions, it’s important, therefore, to understand that access to the compute power and tools required for advanced intelligent algorithms is a prerequisite for today’s businesses. In today’s technology landscape, access to the most advanced AI tools and capabilities can be challenging, especially for businesses looking to innovate and differentiate themselves. The dominance of a few major technology providers has led to a proprietary approach, where the latest AI innovations may be tightly controlled and not easily accessible to a broader range of organizations. This proprietary nature of some AI ecosystems can present obstacles for businesses, especially those in the APJ region, to truly innovate and be creative with AI. They want to use the latest and greatest AI capabilities, but the lack of openness and compatibility between different AI systems gets in their way.

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The need for openness

Developers need open standards to create new uses for AI because it gives them the flexibility to deploy their solutions on-premise, in the cloud, and on edge devices; wherever, in fact, the business’s needs dictate. In parallel with that is the need for compute engines optimized for different devices, capable of delivering AI performance at the point of consumption. Open standards in software and hardware enable interoperability, providing customers the freedom to leverage the AI tools and infrastructure that best suit their unique needs and workflows. This empowers businesses to innovate with generative AI on their own terms, without being limited by a single vendor’s ecosystem.

What the technology industry must pursue, therefore, is a policy of the democratization of GenAI, and those goals are realized by open ecosystems and silicon diversity. Organizations pursuing this strategy of flexibility and choice will gain a significant strategic edge over competitors who primarily rely on public cloud services to manage their AI workloads. This is the key strategy to helping organizations gain a competitive advantage. Empowering businesses with access to the latest hardware optimized for generative AI can further amplify these strategic advantages.

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Powerful hardware

For organizations developing custom AI models and processing large bodies of data, the latest hardware designed from the ground up to be optimized for GenAI significantly lowers TCO, meaning leeway for research and experimentation even within tight budgets.

Better hardware also means projects reach production quicker, and end-users get faster results and an overall better experience. The new Dell PowerEdge XE9680 Server is designed for today’s GenAI workloads. It offers up to eight AMD Instinct MI300X accelerators and provides 1.5TB of coherent GPU accelerator memory per server (the highest ratio in the GPU market currently). That means a lower DC footprint, yet with an increased inference capacity, so very large training datasets can be ingested quickly.

Open software

Hardware power and capabilities unlock an organization’s freedom to innovate without cost overrun, but the software running on it has to offer compatibility with existing AI frameworks, libraries, and models for true portability and compatibility.

Without openness, it’s impossible to achieve that portability across platforms, and therefore, AI can’t be considered democratized. The AMD MI300X Instinct Accelerators in the Dell XE9680 Server, which will be ready to ship in May, offers over 21 petaflops of FP16 performance, yet out-of-the-box, run the common standards in data science of PyTorch and TensorFlow, plus natively supports JAX, Open Neural Network Xchange (ONNX), and OpenAI Triton, inside the AMD ROCm software stack.

ROCm consists of a collection of drivers, development tools, and APIs that enable GPU programming from low-level kernel to end-user applications, and brings together hardware and software optimized for GenAI, large models and fast time-to-market for a business’s AI projects.

AMD’s ROCm is optimized for Instinct MI300X accelerators and is a freely available open software stack that’s capable of evolution and adaptation according to a business’s evolving needs.

An integral part of democratized GenAI is, of course, the open-source ethos. OSS (open-source software) drives quality and excellence, with thousands of users and developers refining and improving the code, allowing increased innovation.

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Better together

Open-source also equates to open flexibility, a situation that means developers can create GenAI-based products and services that operate on a range of devices with upstream support that is available from hundreds of the open-source projects that dominate the GenAI world.

The ultimate flexibility possible today is provided by the combination of the Dell PowerEdge XE9680, AMD’s Instinct MI300X accelerators’ 3rd Gen AMD CDNA (Compute DNA), and ROCm 6 software. A firm foundation and open portability allow businesses and organizations the tools and infrastructure needed to innovate at this critical juncture in technology’s evolution.

GenAI’s transformative powers offer APJ businesses a unique opportunity to develop the next generation of AI-powered software outside the constraints and deliberate roadblocks placed by big tech’s policies of separation and compartmentalization. The horizons can open with just a straightforward deployment configuration tailored to their needs and running on optimized hardware.

To find out more about the Dell PowerEdge XE9680, head to these pages according to your geography: Australia, New Zealand, Singapore, or India. Plus, you can head here to read more about the AMD Instinct MI300X accelerator at the heart of Dell’s next-gen AI-focused hardware.

The post Strategies for Democratizing GenAI appeared first on Tech Wire Asia.

领先的数据中心提供商 EdgeConneX 和朝亚于2021年12月宣布建立战略合作伙伴关系。EdgeConneX 已经是超大规模数据中心部署领域的全球领导者，因其在全球不同市场提供顶级解决方案方面的丰富经验和熟练程度而广受赞誉。朝亚在中国开发和运营前沿的超大规模数据中心园区，以其成熟的高密度、高性能计算（HPC）完备设计而闻名，朝亚擅长提供高效、定制的数据中心解决方案，从而加速客户业务的上市速度。EdgeConneX 与朝亚合作提供最先进的基础设施解决方案，以满足日益数字化的生态系统不断增长的需求。

Tech Wire Asia 采访了 EdgeConneX 亚太区董事总经理 Kelvin Fong 和朝亚首席执行官 James Wei，了解他们对中国如何在 2024 年维持蓬勃发展的数据中心格局的见解。

TWA：是什么推动了中国数据中心行业的增长？

JW：“中国在发展和提升云、人工智能和量子计算等关键技术能力的愿望正在创造合适的条件，让各种技术创新能够在中国蓬勃发展。

“人们越来越需要数字基础设施来支持新的企业应用和用户在线服务，特别是在互联网普及率继续以健康的速度增长的情况下。2023 年初，互联网普及率约为 73.7%。到 6 月份，这一比例已增至约 76.4%。

“此外，人工智能驱动的服务和能力的爆炸式增长需要比以前更多的高密度数据中心支持。随着人工智能技术不断融入日常应用，导致对人工智能训练和推理的电力需求更大。强大的超融合基础设施（HCI）系统可提供更强大的内部部署能力和计算能力。

“由于这些新的高密度系统，机架级的能源需求预计将迅速增加。这推动了更新的解决方案设计和功能，用于提供足够的能源和足够的冷却。”

KF：“中国一直在人工智能研发方面投入巨资。机器学习和深度学习等人工智能技术的实施需要大量的计算能力，因此需要先进的数据中心。

“此外，中国政府一直在推动政务云服务的发展。中国各个电信公司在建设和维护这些政府云基础设施方面发挥着至关重要的作用，满足了对强大数据中心的需求。

“中国蓬勃发展的电子商务行业也产生了大量与在线交易、用户行为和物流相关的数据。中国数字支付和金融分析等金融科技服务的发展推动了对数据存储和处理能力的需求不断增长。

“最后，自动驾驶汽车的开发和测试在很大程度上依赖于数据处理和存储。中国在自动驾驶汽车技术方面一直在进步。此外，实时收集和分析来自传感器和摄像头的大量数据，需要强大的数据中心基础设施。”

TWA：企业如何利用数据中心获得增长机会，同时有效管理计算能力需求和挑战？

KF：“中国企业可以利用数据中心的能力来适应下一代技术，特别是人工智能。数据中心提供人工智能算法、机器学习和数据处理所需的计算资源，使公司能够提取有价值的见解并改进决策流程。

JW：“数据中心还必须跟上技术发展的步伐并采用相关的尖端系统来增强数据中心的能力和性能。”

KF：“中国企业可以利用数据中心作为创新枢纽来促进协作、创造和创新。通过创造一个鼓励实验和开发尖端解决方案的环境，中国企业可以在快速发展的技术领域保持领先地位。”

JW：“企业可以与拥有技术能力的领先数据中心运营商合作，提供具有市场领先能量使用效率（PUE）的高效设计。在此过程中，企业可以采用根据具体要求量身打造的定制数据中心部署，以最大限度地减少效率低下的情况。”

TWA：据您所知，客户是否积极寻求节能解决方案，特别是那些旨在实现低 PUE 值的解决方案？

KF：“低 PUE 值的重要性取决于所涉及的具体技术。例如，在涉及人工智能训练的应用中，延迟不是关键因素，重点往往会转向优化计算机性能，而不是尽量减少延迟。在这类情况下，管理 PUE 值变得至关重要，许多客户探索各种策略，例如采用可再生能源来增强可持续性。

“此外，投资太阳能或风能等可再生能源可以带来长期成本节约。通过采用可再生能源，中国企业可以为更加稳定和可持续的商业模式做出贡献。”

TWA：您如何看待朝亚与 EdgeConneX 之间建立合作伙伴关系来支持中国不断增长的数字基础设施需求？

JW：“[通过]利用彼此最好的数据中心专业知识和能力。EdgeConneX 在全球超大规模部署方面拥有丰富的经验，而朝亚是中国[本土]平台和市场专家，拥有深厚的本地关系。由于朝亚很熟悉中国数据中心生态系统，我们可以快速执行。

“我们共同提供了一个完整的全球超大规模数据中心平台，涵盖 50 多个最热门的市场，随时随地满足企业的扩张需求。”

KF：“随着中国企业踏上全球扩张之旅，与强大的合作伙伴合作对于精简化这个扩张过程至关重要。这一战略联盟有潜力提供宝贵的专业知识、必要资源和专业服务，从而支持中国企业在数字领域的国际化努力。

“汇集我们的优势，我们可以利用双方顶级数据中心无与伦比的知识和能力。朝亚对中国数据中心的生态系统的熟悉程度将使我们能够快速执行。我们的合作伙伴关系将加速我们的集体成功。

“此外，两家公司都在积极培养自己在高性能计算解决方案方面的能力。这种融合符合我们的共同目标，并针对‘东数西算’战略建立了理想的双赢局面。”

要了解更多关于京津数据中心园区的信息，请访问：https://www.edgeconnex.com/locations/asia-pacific/tianjin/

有关大上海数据中心的更多信息，请访问：https://www.edgeconnex.com/locations/asia-pacific/shanghai-data-center-campus/

The post 中国迈向2024年数字化技术先进时代的征程：对话 对话EdgeConneX和朝亚 和朝亚 appeared first on Tech Wire Asia.

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Leading data center providers EdgeConneX and Chayora unveiled a strategic partnership in December 2021 to expand their solutions throughout mainland China, including Beijing and Shanghai.  EdgeConneX has carved its niche as a global leader in hyperscale data center deployments, recognized for its extensive experience and proficiency in delivering top-tier solutions across diverse markets worldwide. Chayora is a trailblazer in data center innovation in China, renowned for its proven high-density, High-Performance Computing (HPC)-ready designs. The company excels in delivering efficient, customized data center solutions, allowing unparalleled speed to market. The collaboration between EdgeConneX and Chayora provides state-of-the-art infrastructure solutions in China that cater to the burgeoning demands of an increasingly digitalized ecosystem.

TechHQ spoke with Kelvin Fong, the Managing Director of EdgeConneX Asia Pacific, and James Wei, the CEO of Chayora, to uncover their insights on how China can sustain a thriving data center landscape in 2024.

THQ: What is driving the growth of the data center industry in China?

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JW: “The country’s desire to develop and advance capability in key technologies such as cloud, AI, and quantum computing is creating the right conditions for tech innovations to bloom and flourish in China.

“There is growing demand for digital infrastructure to power new business applications and online services for users, especially as internet penetration continues to grow at a healthy rate. At the start of 2023, internet penetration was about 73.7 percent. By June, it had increased to about 76.4 percent.

“In addition, the explosion of AI-powered services and capabilities requires more high-density data centers than before to support. The continued integration of AI technologies into everyday applications will culminate in greater power demand for AI training and inferencing. Powerful hyper-converged infrastructure (HCI) systems deliver more powerful on-premises and computing capabilities.

“Power demands at the rack level are expected to increase rapidly due to these new high-density systems. This drives newer solution designs and features to provide enough power along with adequate cooling.”

KF: “China has been investing heavily in AI research and development. The implementation of AI technologies, such as machine learning and deep learning, requires significant computational power, driving the need for advanced data centers.

“Furthermore, the Chinese government has been promoting the development of government cloud services. Chinese telecommunications companies play a crucial role in building and maintaining these government cloud infrastructures, contributing to the demand for robust data centers.

“The booming e-commerce industry in China also generates massive amounts of data related to online transactions, user behavior, and logistics. The growth of fintech services in China, such as digital payments and financial analytics, contributes to the increasing demand for data storage and processing capabilities.

“Finally, the development and testing of autonomous vehicles rely heavily on data processing and storage. China has been making strides in autonomous vehicle technology. Further, collecting and analyzing vast amounts of data from sensors and cameras in real-time require robust data center infrastructure.”

THQ: How can businesses utilize data centers for growth opportunities while effectively managing computing power demands and challenges?

KF: “Chinese businesses can harness the power of data centers to accommodate next-generation technologies, particularly AI. Data centers provide the computational resources needed for AI algorithms, machine learning, and data processing, enabling companies to extract valuable insights and improve decision-making processes.

JW: “They must also stay abreast of technological developments and adopt relevant cutting-edge systems to enhance data center capabilities and performance.”

KF: “Chinese businesses can foster collaboration, creativity, and innovation by leveraging data centers as innovation hubs. By creating an environment that encourages experimentation and the development of cutting-edge solutions, they can stay ahead in the rapidly advancing tech landscape.”

JW: “Businesses can partner with leading data center operators with the technical capabilities to deliver efficient design with market-leading power usage effectiveness (PUE). In doing so, they can adopt customized data center deployments tailored to exact requirements to minimize inefficiencies.”

THQ: To your knowledge, are customers actively pursuing energy-efficient solutions, particularly those aimed at achieving a low PUE?

KF: “The importance of low PUE varies depending on the specific technology involved. For instance, in applications that involve AI training, where latency is not a critical factor, the focus tends to shift towards optimizing computer power rather than minimizing latency. In these cases, managing PUE becomes crucial, and many customers explore strategies such as incorporating renewable energy sources to enhance sustainability.

“Furthermore, investing in renewable energy, such as solar or wind power, can lead to long-term cost savings. By adopting renewable energy sources, Chinese businesses can contribute to a more stable and sustainable business model.”

THQ: How do you see the partnership between Chayora and EdgeConneX supporting China’s rising demand for digital infrastructure?

JW: “[By] leveraging the best-of-the-breed data center know-how and capabilities from each other. EdgeConneX has extensive experience in global hyper-scale deployments, while Chayora is the China [native] platform and market expert with deep local relationships. We can execute quickly through Chayora’s familiarity with the Chinese data center ecosystem.

“Together, we provide a complete global hyperscale data center platform spanning over 50 of the hottest markets, spring-boarding businesses’ expansion where and when they need it.”

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KF: “As Chinese enterprises embark on their global expansion journey, collaborating with a robust partner becomes pivotal in streamlining this process. This strategic alliance has the potential to provide invaluable expertise, essential resources, and specialized services, thereby bolstering the internationalization endeavors of Chinese companies operating in the digital sector.

“Pooling our strengths, we can harness the unparalleled knowledge and capabilities of top-tier data centers from both sides. Leveraging Chayora’s familiarity with the intricacies of the China data center ecosystem will enable us to execute swiftly. Our partnership is poised to accelerate our collective success.

“Moreover, both organizations are actively cultivating their proficiency in high-performance computing solutions. This convergence aligns with our shared objectives and establishes the ideal win-win scenario for ‘East Data and West Computing’.”

For more information on the Beijing-Tianjin Data Center Campus, please visit here.

For more information on the Greater Shanghai Data Center, please visit here.

The post China’s journey towards a digitally advanced 2024: In conversation with EdgeConneX and Chayora appeared first on Tech Wire Asia.

Yet there’s a delicate balance between digital innovation and human interaction: the human part of the equation will always be critical. AI solutions can handle routine queries where human interaction isn’t essential, while human expertise is necessary for those requiring empathy.

The need for a seamless omnichannel experience

Customers today expect organisations to understand their needs and preferences and offer help, support, and solutions (or just a friendly ear) across all channels. Text, voice, messaging – each carries the company’s brand, so each is to be valued.

Research shows, however, that the transition between customer service channels still creates pain points for customers. A seamless omnichannel CX is imperative, and this can be achieved with a state-of-the-art cloud solution.

Centralised data storage means that regardless of the channel the customer chooses, the right information is there for the agent or automated system. When there’s a need or a preference to switch channels, the customer’s experience never drops in quality.

The role of AI in enhancing CX

AI technologies (natural language processing, large language models, cognitive algorithms and so on) can decipher complex queries, understand emotional tone through sentiment analysis, and recognise intent.

Source: Shutterstock

This additional context enables agents to accurately anticipate the customer’s needs and tailor their responses accordingly, perhaps by directing them to a more suitable resource. Issues are ultimately addressed more quickly, leading to improved CX and loyalty, but inimitable human empathy is retained.

Making it better, all the time

The nature of AI is that it learns continuously, so the sooner contact centres begin their AI journey, the better their CX will be. Smart algorithms learn the patterns of interactions, get to know the sentiments expressed at every touchpoint, and can find faster ways to resolve issues.

Most contact centre solutions in this space will come pre-trained to some degree. But it’s after the embedding of an AI-powered system that the real results start to appear. Today’s omnichannel contact centre solutions with AI at their heart help brands’ operations at the point of contact by:

– Sorting and prioritising according to need.

– Allocating the right solution, be that human or ‘bot’.

– Freeing up agents to tackle both the challenging and the interesting.

– Handling the day-to-day problems that would otherwise waste skilled agents’ abilities.

Furthermore, many users of AI in this critical role, central to the brand, will find several other pluses that positively impact elsewhere in the business. That happens when machine learning helps with the following:

– Building impactful data on customers, their behaviours, and preferences.

– Taking more and more repetitive work from human agents.

– Helping skilled workers forge new careers working with AI technology.

– Driving down staff churn by offering engaging and interesting work to employees.

Leading CX solutions for 2024

Two suppliers have emerged as leaders in this field: Nexon Asia Pacific and Genesys. Nexon Asia Pacific (Nexon) offers comprehensive digital solutions plus a critically important consultative service.

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Nexon leverages the technology from Genesys, a global cloud leader in AI-powered experience orchestration, so organisations can seamlessly coordinate technology, interactions, and touchpoints and deliver superior end-to-end customer and employee experiences at scale. By utilising the all-in-one platform Genesys Cloud, organisations can coordinate experiences for customers and employees through a single cloud contact centre platform.

Nexon Asia Pacific

Navigating a successful digital journey toward next-generation technology is a collaborative endeavour. Many Australian organisations use Nexon to consult, deliver, and manage their integrated CX strategy and solution.

Working closely with clients, Nexon’s solution architects begin by thoroughly understanding their current position in their CX journey and identifying their desired destination. They then identify a potential future state and map out the complete solution from start to finish. The team is adept at recommending and deploying cutting-edge technologies that propel clients ahead of the competition, providing full visibility into all operations to harness valuable insights.

Throughout the implementation process, Nexon’s solution architects offer consistent guidance, ensuring clients remain informed and empowered while the project team delivers solutions with rapid time-to-value.

AI is proven to enhance customer journeys and provide predictive insights, providing significant infrastructure cost reductions, and a host of other wins in productivity and operations. By harnessing the power of AI, Nexon enables continuous, personalised engagements across the entire customer journey. This approach enhances customer and employee experiences, driving efficiency and overall business performance.

The partnership between Nexon and Genesys offers clients customised CX solutions for their environment, with ongoing support as organisations evolve.

To explore further about Nexon’s delivered Genesys Cloud CX solution, empowered by AI, please click here.

Genesys – AI-powered experience orchestration platform

Through Genesys Cloud, the number one AI-powered experience orchestration platform, Genesys delivers the future of CX to organisations of all sizes so they can provide empathetic, personalised experiences at scale. As the trusted, all-in-one platform born in the cloud, Genesys Cloud accelerates growth for organisations by enabling them to differentiate with the right customer experience at the right time, while driving stronger workforce engagement, efficiency, and operational improvements.

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It has forged a strategic partnership with Nexon Asia Pacific and names it a trusted MSP (managed service provider) of its own contact centre.

Boasting performance metrics like a 94 per cent average response rate, 90 per cent first-call resolution and a 20 per cent increase in agent productivity, Genesys Cloud sets businesses up to deliver faster, fully personalised customer interactions.

Genesys Cloud has an intuitive, user-friendly design, AI-augmented tools, and a modular architecture that scales to the needs of businesses as they grow.

The platform complies with rigorous security regulations, offering unparalleled protection through TLS encryption for secure traffic and encryption for data at rest with 256-bit AES technology.

Read more on Tech Wire Asia about Security Bank and healthcare provider Maxicare and the benefits their businesses experienced after implementing Genesys Cloud.

The post The future of exceptional personalised CX: Unveiling leading solutions for 2024 and beyond appeared first on Tech Wire Asia.

Data center builders and operators are drawn to Indonesia’s strategic location in the Asia Pacific region, abundant land and power resources, and youthful and tech-savvy population. Furthermore, the government’s supportive policies have created an enabling environment for technology sector investments.

Shifting tides and market dynamics

Indonesia’s data center market, once characterized by an unwavering upward trajectory, is now facing pressing questions about the sustainability of its burgeoning demand for data. Take-up from large enterprises of cloud services has continued. However, major cloud platforms are looking to individual consumers for growth alongside businesses, tapping into their near-constant application use for everyday needs and streaming content. Artificial intelligence (AI) is a growing factor in new deployments, driven by the scalable and relatively low-cost power available locally.

Indonesia’s data center market remains resilient, supported by robust network connectivity, diversity, and strong demand for data services. As the market continues its rapid growth, it remains to be seen if power availability will continue to match or if constraints seen throughout much of Asia will appear in Indonesia.

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Exploring new frontiers

Beyond the confines of the Greater Jakarta area, Indonesia’s data center market is venturing into new territories. Batam Island has emerged as a potential data center hub thanks to its proximity to Singapore. However, its development has been hampered by the sluggish pace of infrastructure development and power availability, posing significant challenges to its integration into the broader data center ecosystem.

Long-term prospects amidst short-term challenges

The nation’s long-term growth prospects remain bright. Propelled by a growing population, a flourishing digital economy, and a stable political climate, Indonesia is a compelling contender within the global data center landscape.

The thriving digital economy, projected to reach a gross merchandise value of $360 billion by 2030, will be a crucial driver for sustained demand. Additionally, enticing government incentives, such as tax reductions for data-related industries, will further boost investment.

The Indonesian government’s ambitious digital transformation initiatives, including the complete digitalization of its services by 2025, will also lead to a sharp increase in demand for data services. Progressive data protection regulations will also create a mature environment for long-term development.

However, the political uncertainty surrounding the 2024 presidential elections poses a potential obstacle. Navigating this transition period effectively will require a delicate balance between addressing short-term challenges and capitalizing on the country’s long-term technological advancement potential.

Moving forward: A path to success

Indonesia’s data center market stands at a crossroads, grappling with a multitude of challenges while poised to seize many opportunities. Navigating the shifting tides of the market demands a nuanced understanding of the intricate dynamics, a commitment to innovation, and a strategic approach that balances between short-term obstacles and long-term ambitions.

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As the industry evolves, collaboration among stakeholders, infrastructure development, and adaptable business strategies will emerge as pivotal factors propelling Indonesia’s data center market towards sustained growth and relevance on the global technological stage. By embracing these essential elements, Indonesia can secure its place as a leading player in the international data center landscape, driving economic growth and shaping the future of digital connectivity.

For more information on EdgeConneX Indonesia, please visit here

The post Navigating challenges and unveiling opportunities in Indonesia’s data center market appeared first on Tech Wire Asia.

Security camera systems today can take surveillance to an entirely new era. In the past, most organizations and law enforcement agencies would need to control and operate camera systems manually. There would be teams to focus on detecting anomalies or any potential crime happening by watching the feed.

Thankfully, advances in facial recognition and other detection techniques embedded with artificial intelligence (AI) have made the process much simpler and more organized today. In fact, modern security camera systems are not only able to detect problems but also send out alerts in real time.

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As the technology has become more affordable, many homeowners have also invested in security camera systems. Some use them to monitor their homes, while others use them to give access to visitors and such. For businesses, AI security camera systems allow them to enhance their security on-premises and monitor their employees.

More recently, AI camera systems have been deployed for monitoring and detection of natural disasters and such. For example, the US and Australia have deployed cameras in hotspots around the country to detect bushfires and monitor the spread of these fires so that they can improve the response time needed to deal with these disasters.

A woman walks past a security camera in Melbourne on February 9, 2023. Australia’s defence department will strip its buildings of Chinese-made security cameras to ensure they are “completely secure”, the government said on February 9. (Photo by William WEST / AFP)

AI camera systems for the military 

Some governments also use AI cameras to monitor their borders and such. According to reports, an Israeli company has developed a device that allows soldiers and rescuers to detect people—and pets—through any wall or barrier in front of them. Using AI, the device can even track a person’s movement patterns, providing crucial intel to soldiers on the other side.

Another Israeli tech company, Axon, provides solutions for computer vision for military vehicles and equipment. Military vehicles and equipment with visual sensors equipped with Axon’s resolutions can provide an insightful view of targets, threats, and obstacles that might be obstructed.

Meanwhile, US marines were reportedly able to trick an AI tested for military use by hiding behind a cardboard box. The scenario highlights why AI camera systems still need to be perfected and why human intervention is still essential for making decisions, especially in times of conflict and in mission scenarios.

A Tweet on the alleged meeting between Huawei and Taliban government.

Talibans to use AI camera systems?

Interestingly, the use of AI camera systems has also caught the attention of Afghanistan’s Taliban government. In a report by Bloomberg, the Afghan government is working with Huawei Technologies to install a wide-ranging surveillance system nationwide.

The surveillance camera system will identify and target insurgents or terrorist activities. Citing a person familiar with the discussions, Bloomberg also reported that representatives from Huawei met with Afghanistan’s Inferior Ministry on August 14 and that a verbal agreement was reached regarding the contract.

In an X (Twitter) post, which has since been deleted, the Afghan interior ministry shared images and details of the meeting with a spokesman stating that Huawei’s advanced camera system was being considered in “every province of Afghanistan.”

Huawei has several advanced camera systems for surveillance. This includes a home video surveillance system, which is designed for homes. For industrial and other surveillance, Huawei’s Video Surveillance uses the edge cloud synergy solution to integrate Huawei Cloud’s powerful intelligent analysis capabilities and open ecosystem. This provides complete and synergetic smart video surveillance, meeting requirements of diverse application scenarios such as campuses, residential buildings, industries, and supermarkets.

Surprisingly, in an email to Bloomberg, Huawei said that the meeting report was “factually incorrect” and that “no plans or agreements were discussed.” There were no further comments from the Taliban government regarding this as well.

A report on Huawei and Taliban

China and Afghanistan 

Huawei has been operating in Afghanistan for some time. The technology company sells mobile phone products in the country through a local distributor.

At the same time, given the country’s geographic location, it will serve as an essential bridge for China’s Belt and Road economic plans. China recently announced a new 3125 km land link that uses both railways and roads to the country that also passes through Kyrgyzstan and Uzbekistan.

On the surveillance camera system, while the Taliban government claims that it will be used to track militants, especially those linked with ISIS, there are concerns that the technology could also be used for other regions.

For one, there are concerns that China will use the technology to profile Afghan citizens. As China expands its influence, some feel this would be an opportunity for them to have a deeper involvement in the country.

The Taliban government could use the cameras to monitor its citizens. According to Human Rights Watch, the Taliban, which took power in August 2021, continued to impose numerous rules and policies violating a wide range of fundamental rights of women and girls, including freedom of movement, proper to work and a livelihood, and access to education and health care.

Authorities also repressed or threatened the media and critics of Taliban rule, forced the closure of civil society organizations, and dismantled government offices meant to promote or uphold human rights. There are concerns that the camera systems could be used to control citizen movements and have stricter rules enforced in the future.

The post Will the Taliban use Huawei’s camera system to locate militants in Afghanistan? appeared first on Tech Wire Asia.

While Labour Day was initially regarded as a day to honor the achievements of workers, most of the roles that were celebrated are becoming increasingly scarce, experiencing a shortage or being replaced with AI. With more industries increasing their use of technology, there are more IT roles in the market, but the skilled IT workforce isn’t enough to meet demand. Hence, organizations are opting to use AI.

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According to a recent IDC report, Enterprise Automation to Mitigate the Digital Skills Shortage , around 60%-80% of Asia Pacific organizations find it difficult or extremely difficult to fill vacancies in many IT roles including security, developers, and data professionals. Major consequences of the skills shortage are increased workload on remaining employees, increased security risks, reduced customer satisfaction, and loss of critical knowledge.

Although big tech companies’ layoff announcements are making headlines, these layoffs are not representative of the overall skills shortage in the market. For organizations, the shortage of workers in the IT sector is still an issue that can’t be resolved by just relying on AI. With technology constantly evolving, the job market in the tech industry is always changing as well.

In this article, Tech Wire Asia takes a look five most challenging roles in IT that require a combination of technical expertise, analytical skills and adaptability, and how AI can help ease the burden.

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Cybersecurity Specialist

Without a doubt, cybersecurity specialists continue to be in demand, especially with increasing cyberthreats today. Responsible for protecting an organization’s network, systems and data from cybercriminals, cybersecurity specialists need to be well-versed in the latest security technologies and techniques and must continually update their skills to keep up with new threats.

Be it the Chief Information Security Officer or any other cybersecurity-related role, being able to take a proactive approach to identifying potential vulnerabilities in systems and networks is a prerogative for them.

While the role is challenging, most cybersecurity specialists today rely on AI-powered tools that can help automate threat detection and response processes, making it easier for them to identify potential vulnerabilities in real time. Machine learning algorithms can also analyze large amounts of data to identify patterns and anomalies, flagging potential security threats before they cause harm.

Cloud Architect

Businesses have increased their cloud adoption as it provides greater flexibility and scalability to their IT infrastructure. The cloud architect is responsible for ensuring the implementation of cloud-based solutions meets the company’s needs while ensuring security and reliability. While there are managed service providers that can manage these for organizations today, businesses should still consider having a cloud architect to help them with their decisions.

At the same time, the role of the cloud architect is also becoming increasingly challenging especially with businesses taking a multi-cloud approach. The complexity of using the multi-cloud requires the cloud architect to be able to understand how to integrate and create a cohesive solution.

Fortunately, cloud architects can rely on AI-powered tools to help automate the deployment, scaling, and management of cloud infrastructure, making it easier for cloud architects to optimize resources and ensure high availability. With machine learning algorithms, cloud architects can also analyze performance data to identify potential bottlenecks or areas for improvement.

Data Scientist

Exponential data growth requires data scientists to uncover insights and solve complex business problems. Today, data scientists are challenged by the sheer volume of data. While data management tools and artificial intelligence is providing them a big help in managing the data, the reality is they still need to have the right understanding of the tools, such as programming languages like Python and Java.

AI can also help automate data processing and analysis tasks, making it easier for data scientists to focus on the most critical tasks. Machine learning algorithms can also help identify patterns and trends in data, making it easier to uncover insights and make predictions.

DevOps Engineer  

Responsible for bridging the gap between software development and IT operations, DevOps engineers must be proficient in both disciplines and have a deep understanding of automation and optimization techniques. One of the biggest challenges faced by DevOps engineers is the need to work across multiple teams and departments. They must be able to communicate effectively with developers, IT operations teams, and other stakeholders to ensure that software releases are timely and meet the needs of the business.

Using AI, software deployment and testing processes can be automated today, making it easier for DevOps engineers to ensure high-quality software releases. DevOps engineers can also rely on machine learning algorithms to analyze performance data to identify potential performance issues or areas for improvement.

(Source – Shutterstock)

Software Engineer

Apart from being proficient in programming, software engineers work collaboratively with data scientists and other team members to design and implement machine learning tools. Software engineers today face the challenge of balancing the technical requirements of machine learning with the needs of the business. They must be able to identify the right algorithms and models to use and must be able to explain their findings to non-technical stakeholders.

With AI, the machine learning model-building process can be automated, making it easier for software engineers to create and deploy machine learning models. To speed up performance data analysis to identify potential performance issues or areas for improvement, machine learning algorithms can be used by software engineers as well.

Can AI solve the skills shortage problem?

Despite AI being capable of automating routine tasks and helping with decision-making processes in various IT roles, it is unlikely that AI will completely take over these roles to solve the skills shortage problem. Organizations still need to invest in their IT workforce. Skilled IT professionals will continue to be required to handle complex situations and communicate effectively with the board.

AI is only as unbiased and ethical as the data it is trained on, and there are concerns about AI being used to automate decisions that should be made by humans. In many IT roles, there are ethical and moral considerations that require human judgment and intervention. For example, while AI can be trained on large amounts of data and algorithms, it cannot replicate the human intuition and judgment that is often required in IT roles.

The post How AI can help with the five hardest roles in IT appeared first on Tech Wire Asia.

New research published today by SnapLogic, a leader in intelligent integration and enterprise automation, reveals attitudes towards AI in the workplace are warming up: with almost two-thirds of workers reporting that they like the idea of using AI in their role, either currently or in the future.

According to SnapLogic’s survey of nearly 1,000 mid-senior management workers within large enterprises across the UK, US, and Australia, all respondents showed a good grasp of AI’s benefits: over half (54%) said they thought using AI would save them time; 46% said it would improve their productivity, and 37% said it would reduce risk and errors in their work.

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When it comes to welcoming the idea of using AI in their role, either currently or in the future, Australians lead the way at 72%, compared to an average of 66%, with the UK respondents the least inclined at 61%.

However, respondents believe skills are an issue, with one-third (34%) of respondents claiming there are very few people within their organization with the skills required to implement and use AI. 39% said it would be hard to get everyone in their organization to fully adopt AI; while 19% were worried that they would not be able to work out how to use AI properly.

Respondents also revealed the main factors that would make them more likely to use AI in their role, either now or in the future: 42% wanted a better understanding of how AI would specifically benefit them in their role, while 36% wanted a safety net to reduce the risk that they would make mistakes.

Jeremiah Stone, CTO of SnapLogic, said, “The current business landscape is unpredictable, and that puts pressure on budgets and resources – and ultimately, on employees. Using AI to automate processes and improve productivity relieves this pressure. It’s very encouraging to hear workers say they understand how AI can benefit them in their own role, as enterprises need employee buy-in if they want to make an AI rollout successful.”

James Campbell, Regional Manager ANZ at SnapLogic said, “Australia’s tech ecosystem is undergoing an exciting period of innovation and incredible growth. Coupled with research showing that Australians are early adopters and strong consumers of technology, it’s not surprising to see the region’s voracious appetite for AI.

“Knowing this, organizations need to step up to the plate, implementing AI-powered technology that’s accessible and easy to use. The linchpin in agility, AI enables organizations to stay flexible and do more with less while keeping employee satisfaction high.”

AI is being integrated into many different technologies and applications, including integration platforms. No stranger to AI in the workplace, SnapLogic developed Iris AI, an industry-first artificial intelligence that helps automate highly repetitive, low-level development tasks, eliminating integration backlogs that can stifle business initiatives.

Iris uses advanced algorithms to learn from billions of metadata elements and millions of data flow via the SnapLogic Intelligent Integration Platform. It then applies that learning to improve the speed and quality of integrations across data, applications, and business processes by suggesting the next integration step, building a complete integration pipeline, or preparing data for app-to-app or data workflows.

To find out more about how SnapLogic is helping the world’s most innovative enterprises get more from their data and applications visit https://www.snaplogic.com/products/iris-artificial-intelligence or view the survey data infographic.

About SnapLogic

SnapLogic powers the automated enterprise. The company’s self-service, AI-powered integration platform helps organizations connect applications and data sources, automate common workflows and business processes, and deliver exceptional experiences for customers, partners, and employees. Thousands of enterprises around the world rely on the SnapLogic platform to integrate, automate, and transform their business. Learn more at snaplogic.com.

Connect with SnapLogic via our Blog, Twitter, Facebook, or LinkedIn.

The post SnapLogic report reveals who leads the way on readiness to embrace AI appeared first on Tech Wire Asia.