Latest news with #AbhasRicky
Techday NZ
3 days ago
- Business
- Techday NZ
Cloudera joins AI-RAN Alliance to boost telecom AI networks
Cloudera has joined the AI-RAN Alliance, a consortium of telecom and artificial intelligence companies working towards integrating AI with next-generation telecommunications infrastructure. The AI-RAN Alliance includes companies such as Dell, NVIDIA, SoftBank, and T-Mobile, and focuses on embedding AI into telecommunications systems with a particular emphasis on radio access networks (RAN). The group aims to address challenges such as standardising AI integration, enabling shared AI infrastructure, and developing applications that support the evolution of telecom networks. Telecommunications companies worldwide are increasingly exploring virtualisation and modern infrastructures to optimise network operations and reduce costs. By incorporating AI, these providers seek to enhance network service efficiency and open new avenues for service innovation. However, deploying AI at scale in distributed edge environments and across radio access networks presents a range of technical and operational complexities. Cloudera's addition to the consortium is intended to bolster efforts to manage real-time data, advance edge AI capabilities, and develop hybrid machine learning operations (MLOps) throughout telecom environments. The company brings experience in managing data across hybrid and mixed infrastructure, which the alliance hopes will advance real-time data utilization and edge-to-core orchestration. Within the alliance, Cloudera will participate in the 'Data for AI-RAN' working group. This initiative aims to develop standardised data orchestration frameworks, facilitate automation of network operations using large language models, and implement hybrid-enabled MLOps across telecom and AI workloads. Cloudera's expertise is expected to help align data and AI workflows with the operational requirements of telecom providers and to promote quicker innovation and deployment of AI-native solutions. The company will also contribute to the alliance's three main objectives: AI-for-RAN, AI-and-RAN, and AI-on-RAN. These aims relate to applying AI directly to RAN operations, integrating AI with RAN functions, and deploying AI applications on RAN platforms, respectively. As part of its role, Cloudera plans to help create reference architectures, validate them in live network environments, and encourage model reuse among consortium members. Cloudera's technology will be used to demonstrate real-time decision-making capabilities at the network edge. This includes providing support for scalable preparation of training data, facilitating MLOps, and operationalising AI inference while maintaining governance, visibility, and coordinated orchestration from network edge to core. Abhas Ricky, Chief Strategy Officer at Cloudera, said, "Cloudera is proud to bring its data and AI expertise to the AI-RAN Alliance. The network is the heart of the telecom business, both in driving margin growth and in service transformation, and AI can unlock substantial value across those dimensions. Given our leadership in the domain - having powered data and AI automation strategies for hundreds of telecommunications providers around the world, we now look forward to accelerating innovation alongside fellow AI-RAN Alliance members, and bringing our customers along. Our goal is to help define the data standards, orchestration models, and reference architectures that will power intelligent, adaptive, and AI-native networks of the future." Jemin Chung, Vice President Network Strategy at KT, commented, "We are proud to collaborate with Cloudera and fellow AI-RAN Alliance members in the 'Data for AI-RAN' working group. As AI becomes increasingly central to next-generation networks, the ability to harness data securely and at scale will be a key differentiator. Through this initiative, we look forward to defining best practices that enable AI-centric RAN evolution and improve operational intelligence." Dr. Alex Jinsung Choi, Principal Fellow, SoftBank's Research Institute of Advanced Technology and Chair of the AI-RAN Alliance, said, "Cloudera is an incredible addition to the AI-RAN Alliance, which has grown rapidly as demand for improved AI access and success increases across the industry. The company's leadership in data and AI, combined with their extensive telecommunications footprint, will play a vital role in advancing our shared vision of intelligent, AI-native networks."
Forbes
28-04-2025
- Business
- Forbes
Tap Into The Power Of Agentic AI
AI agents are transforming business operations. Research from Cloudera found that 87% of organizations believe it's important to invest in agents to maintain a competitive edge within their industry. Act Now or Risk Being Left Behind Artificial intelligence continues to reshape the business landscape—but a new chapter is unfolding. The emergence of AI agents marks a significant evolution, moving beyond basic automation or conversational interfaces. While it may be tempting to view agentic AI as simply the next step in chatbot development, the reality is far more sophisticated. These agents are dynamic, interactive systems capable of executing complex tasks, making decisions, and collaborating with users in entirely new ways. Unlike traditional chatbots, which rely on predefined scripts and limited decision trees, AI agents can operate with a high degree of autonomy. This leap in capability is fueling rapid adoption: according to a recent global survey of 1,484 enterprise IT leaders conducted by Cloudera—the only true hybrid platform for data, analytics, and AI—an overwhelming 96% plan to increase their use of AI agents in the coming year. The company's Chief Strategy Officer, Abhas Ricky, emphasized how critical it is to take action on agentic AI. 'As Enterprise AI goes mainstream, existing workflows will be reimagined,' said Ricky, 'AI Agents are the next frontier that will complete complex multi step decisions to power the next wave of productivity and innovation.' Starting with High-impact, Low-complexity Projects Driving successful adoption of AI agents begins with strategic prioritization—specifically, targeting high-impact, low-complexity use cases early in the journey. As organizations transition from experimentation to enterprise-scale deployment, certain applications are emerging as clear front-runners. According to the Cloudera survey, the most widely adopted use cases include performance optimization bots (66%), security monitoring agents (63%), and development assistants (62%). Notably, 81% of IT leaders also reported using AI agents to enhance the effectiveness of their existing generative AI models. 'AI technology similar to AI agents have been created over the last decade, but the natural language processing capabilities of new GenAI models are facilitating systems of agents to plan, collaborate, and improve,' noted Ricky. 'From manufacturing, to finance and telecommunications, innovation around short and long-term memory structures are helping autonomous agents across industries.' In sectors where human outcomes are paramount, such as healthcare, AI agents are already making a measurable difference. From supporting medical professionals with diagnostic insights to recommending evidence-based treatments, these agents are not just streamlining operations, they are helping to save lives. For instance, a diagnostic agent trained on extensive imaging data can flag subtle anomalies in X-rays that might otherwise go unnoticed, enabling earlier intervention. The financial services sector is seeing similarly transformative impacts. AI agents are proving particularly valuable in fraud detection (56%), risk assessment (44%), and investment advisory (38%) scenarios. Fraud detection stands out as a mission-critical application, where early identification of suspicious activity is essential, and increasingly achievable with the precision and speed of agentic AI. 'AI agents are not just an invisible tool operating on the backend of an organization,' said Ricky. 'They are real, impactful, and transformative assistants that have the potential to touch our day-to-day lives on a deeply human level.' Investing in Infrastructure to Power AI Agents Despite the surge in AI investment, organizations continue to face significant challenges in adopting agentic AI. According to Cloudera's survey, the top concerns among IT leaders include data privacy (53%), integration with existing systems (40%), and high implementation costs (39%). 'These are common hurdles—especially around privacy, security, and implementation,' said Ricky. 'But time and again, the hardest thing for an enterprise is to expose high fidelity data to AI agents. The solution here lies in the strength and flexibility of a company's data infrastructure.' Cloudera's platform is built to help ensure that infrastructure is ready for AI. But the company's expertise runs even deeper. Cloudera's AI Ecosystem is vast and consists of a broad set of technology partners ready to help organizations get the most out of their AI initiatives. 'We are always building our capabilities with an eye toward the future. The acceleration of all things AI presents a unique challenge for businesses looking to maximize the value of their data' said Ricky. 'Our Enterprise AI solutions, coupled with our one-of-a-kind ecosystem of partners, has what enterprises need to fully unlock the promise of agentic AI.' At the heart of Cloudera's Enterprise AI platform are tools designed to democratize AI adoption. Low-code and no-code capabilities within AI Inference services and AI studios give teams the power to deploy and scale AI agents with ease. The customizable AI Studio interface streamlines interaction, while dynamic scalability ensures performance matches demand, helping organizations move faster, and with confidence. 2025 is the Year to Move from Experimentation to Execution Agentic AI is already being embedded into the workflows of nearly every data-driven organization in some form. With investment accelerating across industries, the imperative is clear: integrate AI agents into core workflows now, or risk falling behind. This isn't just speculation—83% of organizations believe it's important to invest in agents to maintain a competitive edge within their industry. To stay ahead, enterprises must align their AI strategy with a unified, future-ready data platform. By bringing data and AI together in a single, scalable environment, organizations can move beyond experimentation and unlock real, enterprise-wide impact through agentic AI. To learn more about Cloudera and to download the full report, click here.
Techday NZ
21-04-2025
- Business
- Techday NZ
Exclusive: Abhas Ricky on how Cloudera is powering the AI revolution
Artificial intelligence is moving out of the lab and into the engine rooms of business, according to Cloudera's Chief Strategy Officer, Abhas Ricky. Despite last month's NVIDIA GTC conference already in the rear-view mirror, he believes the momentum behind AI technologies and infrastructure "continues to evolve". "The NVIDIA GTC conference was packed with exciting announcements and insights," Ricky told TechDay during a recent interview. He said the number one thing that stood out to him was "how AI is transitioning from experimentation to enterprise-scale execution - and fast." For Cloudera, another key highlight was NVIDIA's AI Agents Blueprint – a framework that Ricky believes will help businesses integrate intelligent agents into everyday operations. "This blueprint provides a structured approach to building and deploying AI agents that can automate complex tasks, enhance decision-making, and improve operational efficiency," he explained. Cloudera sees agentic AI – systems that can act autonomously based on data and models – as a cornerstone of future enterprise tech. "By integrating such AI agents into Cloudera's platform, businesses can automate workflows, improve customer service, and orchestrate complex processes more effectively," Ricky said. Equally significant, he explained, was the return of focus to on-premises AI infrastructure. "Nearly every enterprise is reevaluating how to bring AI closer to their data," Ricky said. He noted that governance, performance, cost, and data sovereignty are the main drivers. Ricky also pointed to a recent Barclays survey which found 83% of enterprise CIOs plan to repatriate at least some workloads from the cloud to on-premises environments. In response, Cloudera is doubling down on its hybrid strategy. Its new offering, 'AI in a Box', is designed to give enterprises flexibility and control. "We're making it easier to build AI applications and AI agents from edge to AI using our partner ecosystem," Ricky said. "As an NVIDIA partner supporting our AI Inference Service, we believe we're uniquely positioned to help enterprises turn on-prem AI into a lasting competitive advantage." Cloudera is also optimistic about how these AI innovations will play out across sectors like healthcare, telco, finance, public services and retail. "These technologies are set to revolutionise diagnostics, efficiency, security and customer experience," he added. One striking example Ricky highlighted is NVIDIA's partnership with telco players to develop AI-RAN – an AI-powered approach to optimising radio access networks. "It enables AI applications to run on the RAN infrastructure itself, delivering new revenue streams and improving network performance," he said. "To unlock these outcomes, organisations need robust data flow governance and orchestration from edge to cloud – something Cloudera is ready to provide." But while opportunities are vast, Ricky is also clear about the challenges enterprises face when adopting agentic AI. "Security and compliance are critical," he said. "One of the biggest hurdles is ensuring proprietary data remains within the organisation's control. Our Private AI approach keeps all training data, configurations and models inside the security perimeter." Cloudera's solutions are built to meet regulatory frameworks like GDPR and HIPAA, Ricky added, ensuring businesses stay compliant while pushing the boundaries of AI innovation. Then there's infrastructure. "AI agents come with high computational demands," he noted. "Our unified data and AI lifecycle helps eliminate delays and keeps models current. Our hybrid platform allows AI workloads to run on any cloud or data centre, offering the flexibility needed for enterprise-scale deployments." Cloudera's response to these trends is rooted in its end-to-end platform, which enables inference at scale, low-code development through its AI Studios, and seamless integration of NVIDIA's accelerated computing technology. Ricky said users can deploy AI agents in under ten minutes, thanks to unified tools that span ingestion, transformation, model deployment and visualisation. Importantly, Cloudera's AI Inference service offers secure, production-grade deployment capabilities. "Powered by the full-stack NVIDIA accelerated computing platform, it ensures scalable, optimised and secure model deployments powering real-time AI," Ricky said. "Organisations can experience 36 times faster inference on NVIDIA GPUs." Among those seeing results already is Bank Negara Indonesia (BNI), which is using Cloudera's AI Inference within its own virtual private cloud. "BNI can now rapidly scale GenAI operations while maintaining full control over its data," Ricky said. "It's a major step forward in transforming customer service and operational efficiency." Cloudera's strategic direction is anchored in three core pillars: delivering true hybrid cloud capabilities, enabling modern data architectures, and accelerating private enterprise AI. Ricky believes these are the keys to helping organisations turn their data into competitive advantage. "With an open data lakehouse powered by Apache Iceberg, there's no need to copy or move data," he explained. "Our unified data fabric provides consistent security, governance and observability – all essential foundations for successful AI initiatives." Strategic partnerships are central to this vision. Cloudera's collaboration with NVIDIA is just one example, alongside alliances with AWS, Pinecone, Google Cloud, CrewAI and Anthropic. Together, these partners form Cloudera's Enterprise AI Ecosystem – launched last year and expanded in 2024. "We created this ecosystem because we recognise that AI is a team sport," Ricky said. "Joint solution architectures and project accelerators make AI adoption easier, more economical, and safer." More than 20 AI project accelerators have already been deployed over 1,000 times in the past year. One notable success came from a contract procurement use case in a large oil and gas company, which saved around $2 million annually by reducing research time from weeks to days. Beyond AI, Cloudera is also focused on breaking down data silos through its interoperability initiatives. Ricky pointed to Cloudera's REST-Catalog, which enables seamless querying of data across platforms like Snowflake and AWS – reducing data movement costs by as much as 75%. System integrators also play a crucial role in extending Cloudera's reach. "Kolon Benit, for example, has led digital transformations for manufacturing and financial services clients in Korea," Ricky said. Asked how Cloudera plans to keep pushing forward, Ricky was unequivocal. "At Cloudera, we're all about driving business value through innovation," he said. "To truly capture the AI opportunity, organisations need flexibility, privacy, and the right tools. That's what we're building."
