Artificial Intelligence

Tech leaders gather to discuss AI Opportunities Action Plan

Technology industry leaders gathered in London this week to discuss the government’s AI Opportunities Action Plan, launched by Prime Minister, Keir Starmer, earlier this week. The meeting, which took place on Wednesday at The Savoy Hotel in central London, saw digital experts discuss the implementation and practicalities of adopting the much-hyped initiative, which is backed by a £14bn investment and set to create over 13,000 jobs. Key attendees included Feryal Clark MP, Minister for AI and Digital Government, who summarised the government’s AI roadmap, and Steven George-Hilley, Founder of Centropy PR. Speaking at the event, John Lucey, VP EMEA North for Cellebrite, commented, “We’ve seen the importance of AI and digital policy this week with the launch of the AI Opportunities Actions Plan poised to position the UK as a global AI leader. Data will play a central role in Britain’s AI future, requiring comprehensive data management systems and data privacy protocols to ensure that AI is trained on trustworthy data and that data inputs don’t breach privacy laws. “In key sectors such as policing and defence, for example, organisations need to be able to trust AI systems to deliver accurate results in a safe manner, maintaining client confidentiality while automating manual processes to drive efficiencies. For AI to be truly successful, it will require investment in data practices and training.” Meanwhile, cyber expert, Andy Ward, SVP International for Absolute Security, stated, “As the UK positions itself as a global AI leader, it’s important that a security-first approach is taken to AI innovation and development to mitigate cyber risks. AI-powered threats are growing increasingly sophisticated, targeting sensitive data from public sector bodies and high-profile individuals, right the way down to small businesses. “Recognising these threats and building cyber resilience frameworks to protect critical IT systems can help organisations to remain operational in the face of threats, allowing them to push forward with innovative AI solutions while limiting potential risks.” Ben Green, Chief Revenue Officer at adCAPTCHA, observed, “The evolution and widespread adoption of AI is showing no signs of slowing down, requiring collaboration between the public sector and industry to shape the UK’s AI future. There’s no question of the benefits that AI can bring, but we must also be mindful of the risks, with trends such as AI-enabled bot attacks continuing to threaten businesses and drain marketing revenues through manipulating ad auctions. “Understanding the threats that AI could pose, as well as where it can be a vital solution, is crucial to the UK’s ambitious AI leadership.”

Industry reacts to AI Opportunities Action Plan

Following yesterday's news about the Government unveiling a new AI Opportunities Action Plan, the industry has naturally been swift to react. Here's a round-up of observations from across the sector: • Mark Yeeles, Vice President, Secure Power division, Schneider Electric UK & Ireland, says, “The UK has long held a rich history of technology leadership and innovation, and the recommendations within the Government's new AI Opportunities Action Plan present an ambitious but essential strategy to accelerate sustainable economic growth. In many respects, it is a crucial first step towards a more digitally driven future, enabled by AI. “I, for one, am delighted to see further recognition of data centres as Critical National Infrastructure, and of their pivotal role in providing the secure, sustainable, and resilient infrastructure foundations that are essential to the countries AI success. “Indeed, the proposed development of AI Growth Zones (AIGZs) presents a logical and effective way to fast-track new AI infrastructure, and to co-develop it with distributed energy resources - addressing the many power challenges that have historically hindered national developments. “What’s critical is that security, sustainability and efficiency remain at the forefront of these developments, and that we continue to create strategies to decouple AI and data centre growth from power consumption, while reducing the technologies demand on the grid. “Additionally, to meet and exceed our ambitions around AI leadership, it’s essential we tackle the skills gaps across several key areas connected to AI, including data centres and digital infrastructure, renewable power, sustainability, and engineering. “We at Schneider Electric are therefore not only glad to see the Government taking proactive steps to address the skills shortage at an industry-level by setting targets to train tens of thousands of AI professionals by 2030, but to see its plans to expand education pathways into AI and to teach higher-education students’ a host of industry-relevant skills. “Further, addressing the diversity issue at root and branch is vital to the future of the UK’s technology industry, and it’s excellent to see the acknowledgment of this within the plan.” • Dame Dawn Childs, CEO of Pure DC, comments, “Pure DC welcomes the UK Government's AI Opportunities Action Plan, which underscores the nation's commitment to advancing artificial intelligence. The establishment of AI Growth Zones, such as the one in Culham, Oxfordshire, is a significant step toward accelerating the development of essential infrastructure. “As a leading data centre provider, Pure DC recognises the importance of translating ambitious plans into tangible outcomes. The successful application and delivery of infrastructure depend on close collaboration between government, industry, and local communities. By aligning these efforts, we can create data centres that not only meet the evolving growth in capacity sought by technology firms, but also respect and actively benefit the communities they serve. “We are particularly encouraged by the plan's focus on creating jobs and fostering innovation in de-industrialised areas. This aligns with our commitment to engaging with local stakeholders to drive economic development and ensure our projects deliver long-term value for communities. “By working together, we can ensure that the UK remains at the forefront of AI and technology, creating a thriving environment for innovation and investment.” • Robin Ferris, AI Lead at digital infrastructure provider, Pulsant, observes, "It takes a long time to plan and build the digital infrastructure that supports AI technology, so the announcement of dedicated AI Growth Zones is fantastic news. But for this to really work, the plan needs to think about the different needs of AI. Training large language models (LLMs) can be more flexible with where it happens, but AI inference – the bit where we actually see AI’s real value – works better when it’s closer to major economic hubs. "Organisations have been working hard to create real-world AI applications, and we are at an inflection point where they are now coming into production, but only if the right infrastructure is available – and fast. The need is now, and while the UK has one of the most advanced digital infrastructures in the world, it has to keep pace with businesses' growing needs. That’s why including brownfield sites would be a smart move. Not only can it be more efficient, but it’s also a greener, more sustainable choice. "Having a spread-out, diverse digital infrastructure across the UK is key to making AI accessible to everyone – not just businesses in specific regions. That way, we can create an environment where innovation thrives everywhere and ideas turn into real-world impact faster." • Tom Whittaker, Director at UK law firm, Burges Salmon, says, “The AI sector will be looking forward to the Spring 2025 Spending Review and the further publications listed in the plan to see what the plan looks like in practice. The plan reflects the public sector's cautious optimism about AI.  “In fact, Government is doing more for the AI sector than what's set out in the AI Opportunities Action Plan. For example, the plan does not refer to the Government's push for public sector organisations to publish on a register where they are developing or using AI. That register shows that there is a wide range of potential uses of AI across the public sector. We can see from research and public registers of AI development and use that there is a great deal of enthusiasm across the public sector to use AI to improve public services.” • Rupert Bedell, CEO at Fasthosts, comments, “Data centres are the engines that will drive the AI Opportunities Action Plan into reality, but their development comes with significant environmental consequences. Managing their energy demands will define whether this AI plan will be a sustainable path forward. “The proposed AI Energy Council must lead in establishing robust standards for energy efficiency and renewable energy use in new data centres. Equally, upgrading existing facilities with advanced technologies and modular designs will be essential to reducing their environmental impact. Relying solely on carbon offsets will not be enough, as true sustainability requires meaningful changes to how data centres are built and maintained throughout their lifecycle. “For AI to truly benefit our society, we must address its environmental footprint head-on. Data centres have a unique opportunity to set the benchmark for how innovation and environmental responsibility can coexist.”

PM unveils AI Opportunities Action Plan

The Prime Minister has unveiled the Government’s AI Opportunities Action Plan, committing £14 billion in investment into ‘game-changing’ artificial intelligence and creating 13,250 jobs. The IMF estimates that AI could increase productivity across the UK by as much as 1.5 percentage points each year, if the technology is fully embraced. These gains may be worth an average of £47 billion to the UK economy every year for over a decade. As part of the plan, the government is creating new AI Growth Zones to fast-track the building of AI infrastructure, starting in Culham and Oxfordshire. These zones will speed up planning permission and generate energy connections needed to power AI. Prime Minister Keir Starmer says, “Artificial Intelligence will drive incredible change in our country. From teachers personalising lessons, to supporting small businesses with their record-keeping, to speeding up planning applications, it has the potential to transform the lives of working people. “But the AI industry needs a government that is on their side; one that won’t sit back and let opportunities slip through its fingers. And in a world of fierce competition, we cannot stand by. We must move fast and take action to win the global race.” The AI Opportunities Action Plan takes forward the 50 recommendations set out by AI expert Matt Clifford, providing the full support of the government. The plan re-enforces the UK commitment to become a global leader in AI, learning from the US and EU’s approach to lead innovation and deliver long-term stability for businesses. Sachin Agrawal, UK Managing Director for Zoho, comments, “Artificial Intelligence is already having a transformative impact on people and businesses, driving efficiencies across areas such as data analysis, fraud detection and forecasting which make a significant difference to people’s lives. The commitment to investment and support in the AI Opportunities Action Plan is hugely encouraging, demonstrating the UK’s ambition as a global AI leader and instilling confidence in businesses to turbocharge innovation. “As part of this innovation push, it is important for the UK to understand how AI regulation and data privacy continue to challenge businesses developing and implementing AI systems. In 2024, multi-agent AI emerged as a significant trend by enabling the collaboration between specialised agents to handle complex workflows in enterprise businesses where structured information and datasets are critical for context. No comprehensive frameworks have been enacted yet in the UK, although renewed commitments such as this and continued efforts indicate the growing recognition of responsible AI governance. According to our Digital Health Study, 78% of businesses have already used AI or are planning to invest heavily in the technology. “As businesses take the next steps of AI adoption, fuelled by this landmark policy, they should be guided by the government, regulators and educators under AI frameworks that promote the safe and ethical development and usage of AI systems.” The Prime Minster highlighted the transformative role that AI can play in driving public sector efficiency, saving time on admin that can be reassigned to improving public services. Speeding up planning consultations to get Britain building, faster and more accurate medical diagnoses, reducing admin for teachers, and AI analysis of camera footage to improve roads were among the examples given by the Prime Minister on the benefits the plans will provide working people. As part of the plan, the government is setting up a new team to build the UK’s sovereign capabilities and seize AI opportunities, as well as creating a new National Data Library to securely unlock the value of public data and support AI development. Andy Ward, SVP International for Absolute Security, comments, “For the AI Opportunities Action Plan to truly deliver the transformative impact we all hope, it is vital that security is at the heart of these developments to ensure that AI systems that are being developed and deployed aren’t posing dangerous security risks. There’s no doubt that AI can bring a wealth of positives to our lives, but there’s a dark side to AI with cybercriminals manipulating it as part of attacks, infiltrating IT systems and increasing the sophistication and volume of attacks.” “While the intention of becoming a global AI leader is encouraging, it requires the government, NCSC and industry to ensure that AI rollouts consider the security risks posed and put in place safeguards to provide additional business protections. Our research found that over half of CISOs feel that their security team is unprepared for evolving AI-powered threats, and 44% have gone as far as banning their employees from using AI due to the security risks. “Cyber attacks have long been a case of when, not just if, and with AI positioned to increase the threat volume, taking a proactive approach to building cyber resilience has never been more important. Security teams not only need to identify and prevent attacks, they need the capability to recover when a breach does occur, shutting off compromised systems and restoring operations quickly and securely.”

Research forecasts AI’s impact on energy consumption

Schneider Electric, an expert in the digital transformation of energy management and automation, has released two reports from its Sustainability Research Institute (SRI). These reports fill key knowledge gaps regarding AI’s impact on sustainability, particularly in energy use. The first research, Artificial Intelligence and Electricity: A System Dynamics Approach, examines four possible scenarios for AI's electricity consumption over the next decade. Considering the growing concern around AI’s energy consumption, Rémi Paccou, Director of Schneider Electric’s Sustainability Research Institute, and Prof. Fons Wijnhoven, Associate Professor at the University of Twente (Netherlands), have built a system dynamics model that forecasts diverse scenarios for AI electricity demand, highlighting the path forward for sustainable AI development strategies and policies to mitigate environmental impacts. The authors construct four scenarios of AI development and their associated impacts on electricity consumption. These scenarios, which are not predictions but rather tools to understand the complex factors shaping our future, span a range of possibilities: from Sustainable AI development to Limits to Growth, including more radical scenarios such as Abundance Without Boundaries and even the possibility of Energy Crises caused by AI. Alongside these forecasts and analysis, the report also contains recommendations for policymakers and decision-makers, contributing to a thoughtful and responsible approach to development, aiming for a path that balances progress with sustainability. The second report, AI-Powered HVAC in Educational Buildings: A Net Digital Impact Use Case, also by Rémi Paccou and Gauthier Roussilhe, Research Fellow and Doctoral Student at RMIT, demonstrates how AI-powered heating, ventilation, and air-conditioning (HVAC) systems can enhance energy efficiency and environmental conservation in buildings. HVAC systems account for 35-65% of total building energy consumption. The study examined over 87 educational properties in Stockholm, Sweden, over an extended period under real-world conditions. Between 2019 and 2023, the study observed a total carbon emission reduction of 65tCO2e/y, roughly 60 times the actual embodied carbon footprint of the AI system deployed. The research reveals opportunities for even greater carbon reductions in environments with more demanding heating, cooling, or air conditioning requirements. A comparative analysis between Stockholm and Boston showed that implementing the same solution in Boston could yield carbon emission savings seven times higher than in Stockholm. The publishing of these reports coincides with the IEA's Global Conference on Energy & AI, where Schneider Electric was in attendance. This conference gathers experts from the energy and tech sectors, government, civil society, and academia to discuss the potential impacts of AI on global energy systems and the opportunities for leveraging AI for energy and climate goals. Schneider Electric’s CEO, Olivier Blum, and Executive Vice President of its Data Centres & Networks Business, Pankaj Sharma, participated in a high-level roundtable discussion. Vincent Petit, Climate and Energy Transition Research SVP at Schneider Electric, notes, “The release of our reports comes at a crucial time, as the IEA conference highlights the transformative power of AI in the energy sector. As a company and as researchers, we are committed to keep shaping the future of energy and climate solutions.” For more from Schneider Electric, click here.

AI security and data availability to underpin 2025 tech trends

AI has continued to be transformative throughout 2024, with accelerating adoption by enterprises and a growing number of use cases. According to experts from data platform, Nasuni, the AI boom will continue in 2025, but will be defined by three key pillars: 1. 2025 will bring a new era of security maturity - The ability to protect and quickly recover data assets underpins every other business process in an AI-first world 2. Data readiness will be central to AI success - As we look toward 2025, data will no longer just support AI, it will shape and limit the scope of what AI can achieve 3. Enterprises will strive to find the real ROI in AI - 2025 will usher in a more measured approach to AI investment, as organisations will be increasingly focused on quantifiable ROI Discussing these predictions, Russ Kennedy, Chief Evangelist at Nasuni, says, “In 2025, data will be more valuable than ever as enterprises leverage AI to power their operations. However, as data’s value grows, so does its appeal to increasingly sophisticated threat actors. This new reality will continue driving organisations to rethink their security frameworks, making data protection and rapid recovery the backbone of any AI strategy. Attackers are evolving, using AI to create more insidious methods, like embedding corrupted models and targeting AI frameworks directly, which makes rapid data recovery as vital as data protection itself. “Businesses will need to deploy rigorous measures not only to prevent attacks, but to ensure that if the worst happens, they can quickly restore their AI-driven processes. 2025 will bring a new era of security maturity, one where the ability to protect and quickly recover data assets underpins every other business process in an AI-first world.” Jim Liddle, Chief Innovation Officer Data Intelligence and AI at Nasuni, comments, “As we look toward 2025, data will no longer just support AI – it will shape and limit the scope of what AI can achieve. A robust data management strategy will be essential, especially as AI continues advancing into unstructured data. For years, companies have successfully leveraged structured data for insights, but unstructured data – such as documents, images, and embedded files – has remained largely untapped. The continued advancements in AI’s ability to process the different types of unstructured data that reside within an enterprise are exciting, but they also require organisations to know what data they have and how and where it’s being used. “2025 will mark the era of ‘data readiness’ for AI. Companies that strategically curate and manage their data assets will see the most AI-driven value, while those lacking a clear data strategy may struggle to move beyond the basics. A data-ready strategy is the first step for any enterprise looking to maximise AI’s full potential in the coming years.” Nick Burling, Senior Vice President, Product at Nasuni, adds, “2025 will usher in a more measured approach to AI investment, as organisations will be increasingly focused on quantifiable ROI. While AI can deliver immense value, its high operational costs and resource demands mean that companies need to be more selective with their AI projects. Many enterprises will find that running data-heavy applications, especially at scale, requires not just investment but careful cost management. Edge data management will be a critical component, helping businesses to optimise data flow and control expenses associated with AI. “For organisations keen on balancing innovation with budgetary constraints, cost efficiency will drive AI adoption. Enterprises will focus on using AI strategically, ensuring that every AI initiative is justified by clear, measurable returns. In 2025, we’ll see businesses embrace AI not only for its transformative potential, but for how effectively it can deliver sustained, tangible value in an environment where budgets continue to be tightly scrutinised.” For more from Nasuni, click here.

Infinidat introduces RAG workflow deployment architecture

Infinidat, a provider of enterprise storage solutions, has introduced new Retrieval-Augmented Generation (RAG) workflow deployment architecture to enable enterprises to fully leverage generative AI (GenAI). The company states that this dramatically improves the accuracy and relevancy of AI models with up-to-date, private data from multiple company data sources, including unstructured data and structured data, such as databases, from existing Infinidat platforms. With Infinidat’s RAG architecture, enterprises utilise Infinidat’s existing InfiniBox and InfiniBox SSA enterprise storage systems as the basis to optimise the output of AI models, without the need to purchase any specialised equipment. Infinidat also provides the flexibility of using RAG in a hybrid multi-cloud environment, with InfuzeOS Cloud Edition, making the storage infrastructure a strategic asset for unlocking the business value of GenAI applications for enterprises. “Infinidat will play a critical role in RAG deployments, leveraging data on InfiniBox enterprise storage solutions, which are perfectly suited for retrieval-based AI workloads,” says Eric Herzog, CMO at Infinidat. “Vector databases that are central to obtaining the information to increase the accuracy of GenAI models run extremely well in Infinidat’s storage environment. Our customers can deploy RAG on their existing storage infrastructure, taking advantage of the InfiniBox system’s high performance, ow latency, and unique Neural Cache technology, enabling delivery of rapid and highly accurate responses for GenAI workloads.” RAG augments AI models using relevant and private data retrieved from an enterprise’s vector databases. Vector databases are offered by a number of vendors, such as Oracle, PostgreSQL, MongoDB and DataStax Enterprise. These are used during the AI inference process that follows AI training. As part of a GenAI framework, RAG enables enterprises to auto-generate more accurate, more informed and more reliable responses to user queries. It enables AI learning models, such as a Large Language Model (LLM) or a Small Language Model (SLM), to reference information and knowledge that is beyond the data on which it was trained. It not only customises general models with a business’ most updated information, but it also eliminates the need for continually re-training AI models, which are resource intensive. “Infinidat is positioning itself the right way as an enabler of RAG inferencing in the GenAI space,” adds Marc Staimer, President of Dragon Slayer Consulting. “Retrieval-augmented generation is a high value proposition area for an enterprise storage solution provider that delivers high levels of performance, 100% guaranteed availability, scalability, and cyber resilience that readily apply to LLM RAG inferencing. With RAG inferencing being part of almost every enterprise AI project, the opportunity for Infinidat to expand its impact in the enterprise market with its highly targeted RAG reference architecture is significant.” Stan Wysocki, President at Mark III Systems, remarks, “Infinidat is bringing enterprise storage and GenAI together in a very important way by providing a RAG architecture that will enhance the accuracy of AI. It makes perfect sense to apply this retrieval-augmented generation for AI to where data is actually stored in an organisation’s data infrastructure. This is a great example of how Infinidat is propelling enterprise storage into an exciting AI-enhanced future.” Inaccurate or misleading results from a GenAI model, referred to as 'AI hallucinations', are a common problem that have held back the adoption and broad deployment of AI within enterprises. An AI hallucination may present inaccurate information as 'fact', cite non-existent data, or provide false attribution – all of which tarnish AI and expose a gap that calls for the continual refinement of data queries. A focus on AI models, without a RAG strategy, tends to rely on a large amount of publicly available data, while under-utilising an enterprise’s own proprietary data assets. To address this major challenge in GenAI, Infinidat is making its architecture available for enterprises to continuously refine a RAG pipeline with new data, thereby reducing the risk of AI hallucinations. By enhancing the accuracy of AI model-driven insights, Infinidat is helping to advance the fulfillment of the promise of GenAI for enterprises. Infinidat’s solution can encompass any number of InfiniBox platforms and enables extensibility to third-party storage solutions via file-based protocols such as NFS. In addition, to simplify and accelerate the rollout of RAG for enterprises, Infinidat integrates with the cloud providers, using its InfuzeOS Cloud Edition for AWS and Azure to make RAG work in a hybrid cloud configuration. This complements the work that hyperscalers are doing to build out LLMs on a larger scale to do the initial training of the AI models. The combination of AI models and RAG is a key component for defining the future of generative AI. For more from Infinidat, click here.

Datadog Monitoring for OCI now widely available

Datadog, a monitoring and security platform for cloud applications and a member of Oracle PartnerNetwork, has announced the general availability of Datadog Monitoring for Oracle Cloud Infrastructure (OCI), which enables Oracle customers to monitor enterprise cloud-native and traditional workloads on OCI with telemetry in context across their infrastructure, applications and services. With this launch, Datadog is helping customers migrate with confidence from on-premises to cloud environments, execute multi-cloud strategies and monitor AI/ML inference workloads. Datadog Monitoring for Oracle Cloud Infrastructure helps customers: - Gain visibility into OCI and hybrid environments: Teams can collect and analyse metrics from their OCI stack by using Datadog's integrations for over 20 major OCI services and more than 750 other technologies. In addition, customers can visualise the performance of OCI cloud services, on-premises servers, VMs, databases, containers and apps in near-real time with customisable, drag-and-drop, and out-of-the-box dashboards and monitors. - Monitor AI/ML inference workloads: Teams can monitor and receive alerts on the usage and performance of GPUs, investigate root causes, monitor operational performance and evaluate the quality, privacy and safety of LLM applications. - Get code-level visibility into applications: Real-time service maps, AI-powered synthetic monitors and alerts on latency, exceptions, code-level errors, log issues and more give teams deeper insight into the health and performance of their applications, including those using Java. “With this announcement, Datadog enables Oracle customers to unify monitoring of OCI, on-premises environments and other clouds in a single pane of glass for all teams,” says Yrieix Garnier, VP of Product at Datadog. “This helps teams migrate to the cloud and execute multi-cloud strategies with confidence, knowing that they can monitor services side-by-side, visualise performance data during all stages of a migration and immediately identify service dependencies.” For more from Datadog, click here.

Custocy partners with Enea for AI-based NDR integration

Custocy, a pioneer in artificial intelligence (AI) technologies for cybersecurity, is to embed Enea Qosmos deep packet inspection (DPI) and intrusion detection (IDS) software libraries in its AI-powered network detection and response (NDR) platform. This integration will enable Custocy to improve accuracy and performance and support product differentiation through detailed traffic visibility and streamlined data inspection. Custocy uses layered, multi-temporal AI functions to detect immediate threats as well as persistent attacks. This approach streamlines the work of security analysts through attack path visualisation, improved prioritisation, workflow support and a radical reduction in the number of false-alarm alerts (‘false positives’). By integrating Enea software into its solution, Custocy will have the exceptional traffic data it needs to extend and accelerate this innovation while meeting extreme performance demands. Enea’s deep packet inspection (DPI) engine, the Enea Qosmos ixEngine, is the most widely embedded DPI engine in the cybersecurity industry. While it has long played a vital role in a wide range of security functions, it is increasingly valued by security leaders today for the value it brings to AI innovation. With market-leading recognition of more than 4,500 protocols and delivery of 5,900 metadata, including unique indicators of anomaly, Qosmos ixEngine provides invaluable fuel for AI innovators like Custocy. In addition, the Enea Qosmos Threat Detection SDK delivers a two-fold improvement in product performance by eliminating double packet processing for DPI and IDS, optimising resources and streamlining overheads. And thanks to Enea Qosmos ixEngine’s packet acquisition and parsing library, parsing speed is accelerated while traffic insights are vastly expanded to fuel next-generation threat detection and custom rule development. These enhancements are important, as demand for high-performing NDR solutions has never been higher. NDR plays a pivotal role in detecting unknown and advanced persistent threats (APTs), which is a challenge certain to become even more daunting as threat actors adopt AI tools and techniques. Custocy is well-positioned to help private and public organisations meet this challenge with a unique technological core built on AI that has earned the company a string of awards; the latest being Product of the Year at Cyber Show Paris. Jean-Pierre Coury, SVP Embedded Security Business Group, comments, “Custocy has developed its solution from the ground up to exploit the unique potential of AI to enhance advanced threat detection and security operations. AI is truly woven into the company's DNA, and I look forward to the additional value it will deliver to its customers as they leverage the enhanced data foundation delivered by Enea software to support their continuous AI innovation.” Custocy CEO, Sebastien Sivignon, adds, “We are thrilled to join forces with Enea to offer our customers the highest level of network intrusion detection. The Enea Qosmos ixEngine is the industry gold standard for network traffic data. It offers a level of accuracy and depth conventional DPI and packet sniffing tools cannot match. Having such a rich source of clean, well-structured, ready-to-use data will enable Custocy to dramatically improve its performance, work more efficiently and devote maximum time to AI model innovation.”

Singtel and Nscale partner to unlock GPU capacity

Singtel and Nscale, a fully vertically integrated AI cloud platform, have announced a strategic partnership that will unlock both companies’ GPU capacity across Europe and Southeast Asia. The collaboration aims to meet the growing global demand from enterprises for generative AI, high-performance computing and data-intensive workloads. Singtel will leverage Nscale’s AMD and NVIDIA GPU capacity in Europe for Singtel’s customer workloads across key markets in the region. This capability ensures that Singtel can deliver to high-volume requirements on demand and maintain service excellence especially when additional capacity is needed. Correspondingly, Nscale will be able to tap into Singtel’s NVIDIA H100 Tensor Core GPU capacity in the Southeast Asian region for its customers’ workloads through an integration with Singtel’s patented orchestration platform, Paragon. Furthermore, as Singtel’s regional data centre arm Nxera expands in the region, its sustainable AI-ready data centres will provide the necessary data centre capacity to support large-scale deployment of Nscale GPU capacity. This partnership will allow Singtel and Nscale to build out a more comprehensive GPU-as-a-Service (GPUaaS) offering globally, ensuring that their customers benefit from the flexibility of a wider geographic footprint and robust infrastructure support. This will also drive greater utilisation in their respective GPU clusters. Bill Chang, CEO of Singtel’s Digital InfraCo and Nxera, says, “As we continue to augment our GPUaaS offerings, we are forging a series of strategic partnerships to grow our ecosystem and broaden our service availability for our customers. Our partnership with Nscale will allow our customers to tap into their high-performance GPU resources on demand, unlocking new possibilities for innovation and efficiency. Our commitment to delivering cost-effective solutions, backed by our state-of-the-art data centres, ensures businesses can access high-performance GPU resources quickly and seamlessly.” Josh Payne, Nscale Founder and CEO, adds, “Nscale is the vertically integrated GPU cloud building the global infrastructure backbone for generative AI. Our sustainable AI-ready data centre together with our GW pipeline of data centre capacity uniquely positions us to deliver sustainable AI infrastructure at any scale for customers worldwide. Through this strategic partnership, Nscale will provide Singtel customers with unmatched access to sustainable, high-performance, and cost-effective AI compute to accelerate enterprise generative AI in the region and beyond.” Singtel previously announced in February that it will be launching its GPUaaS later this year, providing enterprises with access to NVIDIA’s AI computing power. This will enable them to deploy AI at scale quickly and cost-effectively to accelerate growth and innovation. Singtel also recently announced a partnership with Vultr in the US and a strategic partnership with Bridge Alliance that will bring its GPUaaS offerings to enterprises across Southeast Asia. Singtel’s GPUaaS will be expanded to run in new sustainable, hyper-connected, AI-ready data centres by Nxera across Singapore, Thailand, Indonesia and Malaysia when they begin operations from mid-2025 onwards. Nscale's strategic partnership with Singtel follows a number of recent announcements, including a partnership with Open Innovation AI to deliver 30,000 GPUs of consumption to the Middle Eastern market. Integrating Nscale’s powerful GPU infrastructure with Open Innovation AI’s orchestration, data science tools and frameworks. Additionally, Nscale recently acquired Kontena, a leader in high-density modular data centres and AI data centre solutions, further enhancing its ability to provide high-performance, cost-effective AI infrastructure to meet the growing demands of the generative AI market. For more from Singtel, click here.

Is poor data quality the biggest barrier to efficiency?

Employing data specialists, selecting the right tech and understanding the value of a patient and meticulous approach to validation are all fundamental elements of an effective data strategy, according to STX Next, a global leader in IT consulting. Recent research shows that data is an asset that many organisations undervalue, with businesses generating over $5.6 billion in annual global revenue losing a yearly average of $406 million as a direct result of low-quality data. Bad data primarily impacts company bottom lines by acting as the bedrock of underperforming business intelligence reports and AI models – set up or trained on inaccurate and incomplete data – that produce unreliable responses, which businesses then use as the basis for important decisions. According to Tomasz Jędrośka, Head of Data Engineering at STX Next, significant work behind the scenes is required for organisations to be confident in the data at their disposal. Tomasz says, “Approaches to data quality vary from company to company. Some organisations put a lot of effort into curating their data sets, ensuring there are validation rules and proper descriptions next to each attribute. Others concentrate on rapid development of the data layer with very little focus on eventual quality, lineage and data governance. “Both approaches have their positives and negatives, but it’s worth remembering that data tends to outlive all other layers of the application stack. Therefore, if data architecture isn’t designed correctly there could be issues downstream. This often stems from aggressive timelines set by management teams, as projects are rushed to facilitate unrealistic objectives, leading to a less than desirable outcome. “It’s important to remember that the data world is no longer recognisable from where we were 20 years ago. Whereas before we had a handful of database providers, now development teams may pick one of a whole host of data solutions that are available. “Businesses should carefully consider the requirements of the project and potential future areas that it might cover, and use this information to select a database product suitable for the job. Specialist data teams can also be extremely valuable, with organisations that invest heavily in highly skilled and knowledgeable personnel more likely to succeed. “An integral aspect of why high-quality data is important in today’s business landscape is because companies across industries are rushing to train and deploy classical ML as well as GenAI models. These models tend to multiply whatever issues they encounter, with some AI chatbots even hallucinating when trained on a perfect set of source information. If data points are incomplete, mismatched, or even contradictory, the GenAI model won’t be able to draw satisfactory conclusions from them. “To prevent this from happening, data teams should analyse the business case and the roots of ongoing data issues. Too often, organisations aim to tactically fix problems and then allow the original issue to grow bigger and bigger. “At some point, a holistic analysis of the architectural landscape needs to be done, depending on the scale of the organisation and its impact, in the shape of a lightweight review or a more formalised audit where recommendations are then implemented. Fortunately, modern data governance solutions can mitigate a lot of the pain connected with such a process and in many cases make it smoother, depending on the size of the technical debt.” Tomasz concludes, “Employees who trust and rely on data insights work far more effectively, feel more supported and drive improvements in efficiency. Business acceleration powered by a data-driven decision-making process is a true signal of a data-mature organisation, with such traits differentiating companies from rivals.” For more from STX Next, click here.