Search Result for 'machine learning'

...players use artificial intelligence and machine learning to deploy fraudulent tactics, financial institutions and merchants also use such technologies. Forrester ...

...be enough data to meet the growing demand for data to train new machine learning algorithms,” Rena Bhattacharyya, chief analyst ...

...to expand from supporting user experience design to full-scale digital product development. Predictive Analytics harnesses machine learning and data modelling ...

...to support AI initiatives. The region excels in hybrid cloud adoption and machine learning, laying a strong foundation for AI ...

...Machine Learning (AI/ML)- based approach to tackling it. API security in APAC Veloo said that even though API Security in ...

...themes. Autonomous AI, advanced AI systems that can perform human tasks, include multiagent systems, large action models, machine customers, humanoid working ...

...Quantum-enhancedAI can significantly accelerate machine learning tasks, making them more powerful and efficient, and paving the way for a brighter ...

...a cloud-based machine learning platform to automate manual processes and improve efficiency," he confided. Ensuring compliance with evolving regulations and ...

The convergence of Artificial Intelligence (AI) and Machine Learning (ML) significantly transforms and enhances enterprise architecture (EA) capabilities, improving analytics ...

...Research at IDC. GenAI Spending on GenAI solutions will be less than the combined total of all other AI applications, ...

OTT video platform provider Mangomolo has expanded its artificial intelligence (AI) and machine learning (ML) to enable broadcasters to automate ...

...No. 71. Data-intensive workloads and services Through GDC, organisations can access core features of Google Cloud’s enterprise AI platform, Vertex ...

...is about more than just providing information. It's about using AI and machine learning to analyse data, identify patterns, and ...

...machine learning bias, scaling issues, and certainly the limited availability of skills and experience in the technology and the workflow. ...

...using AI and machine learning (ML) to solve real-world problems. It has three distinct delivery models leveraging: 1. Citizen data ...

...it. Gartner says that with orders of magnitude less privacy risk than real data, synthetic data can open a range ...

F5’s inaugural 2024 Strategic Insights: API Security in APAC report reveals that one in five APAC organisations has adopted artificial ...

...defines as brand-specific, AI-powered marketing operating systems comprising genAI foundation models, machine learning, customer insights, media data, brand IP, and human ...

...jobs in Singapore mention “machine learning,” while around 54% ask for Python skills, which are highly valued for their flexibility ...

...Notably, 72% of organisations noted customer service chatbots as the most prevalent use case. Organisations also maximise machine learning in ...

...to focus on what matters most – building strong relationships with their customers," said Beerud Sheth, co-founder and CEO of Gupshup. ...

...visual content or advanced machine learning models that generate images or video from text, audio, or video prompts, GenAI for ...

...Palo Alto Networks Inc. has launched AI-powered data security integrated into secure access service edge (SASE), leveraging large language model ...

Tenable Cloud Research Team has discovered a high-severity vulnerability in Azure that affects over 10 Azure services, such as Azure ...

...AI and machine learning needs for research and development in public healthcare use cases," Ngiam Siew Ying, CEO of Synapxe, ...

...shared, and enforced using code." Prem Pavan "What this means is that it automates the compliance process, where the business ...

Gartner predicts more than 70% of government agencies will use artificial intelligence (AI) to enhance human administrative decision-making by 2026. ...

...AI-generated deepfakes. Vaibhav Gundre “Cutting-edge detection methods powered by machine learning are helping to identify and flag manipulated content with ...

...while maintaining high-quality services. "Traditional methods are often insufficient, prompting more companies to use advanced technologies like generative AI for ...

...plan to adopt a hybrid cloud model for AI services. Job creation Some 67% of CSPs project AI to generate ...

...suggestions and notifications for fleet vehicles. It also includes Epicor Grow Inventory Forecasting​ that enables users to leverage predictive analytics ...

...machine learning. The Search AI Lake is distributed - cross-region, cloud, or hybrid to normalise, index, and optimise any data format for ...

...and Trust, IDC. “ExtraHop continues to build upon its proprietary AI and machine learning capabilities, and is driving an innovative ...

...become a beacon in the international AI field,” said Elsie Tan, country manager, Worldwide Public Sector, Singapore, AWS. “By leveraging AWS’s ...

...operate at the same speed and scale as attackers.” AI vs AI-powered attacks The solution leverages AI and machine learning ...

...machine learning, we have the potential to automate routine tasks, increase productivity, and free up mental space so people can ...

...the vulnerabilities of new payment methods. Moving forward, LexisNexis reminds organisations to embrace fraud management and authentication solutions, maximising technologies ...

Google prevented 2.28 million policy-violating apps from being published on Google Play in 2023 due to new and improved security features, policy updates, and machine ...

...new capabilities such as AI and machine learning. It also provides a high-performance multi-model database for multidimensional data and document ...

...decision-making. Government services will significantly improve through machine learning, analytics, and generative AI in the next two years. Digital Platform Agility Government organisations ...

...digitise its finance function and tap into a stream of continuous innovation including AI and machine learning features to improve ...

...handle the copious amounts of data being generated, contributing to analytics and machine learning.” David Chan Andy Ng, vice president ...

...data silos. “One will be looking at artificial intelligence, machine learning, building of the models, training of the models, refining ...

...can leverage massive amounts of internal and external data through AI by integrating and analysing them and offering predictive analytics, ...

Manufacturers find AI and machine learning as the top manufacturing technologies to drive business outcomes and ROI, according to the ...

...based on machine learning algorithms detecting all possible fraud types at every stage of the user journey. To flag suspicious ...

...for organisations taking their AI journey. “Firstly, integrating AI into their digital transformation and machine learning foundation is crucial,” he ...

...potential lies in store for those in banking and financial services? Corporate and investment banks (CIB) have been using AI ...

...to analytics and machine learning,” he commented. Struggles in the data governance journey Make no mistake, organisations will struggle to ...

...solutions to aid the IT security team through aggregating and correlating data from multiple sources in one place. It is ...

...to foster inclusivity in the workplace.  “With the right technology tools, organisations can leverage the power of artificial intelligence and ...

...Application Security at Akamai. “These machine learning enhancements and shared telemetry across Akamai are designed to strengthen and simplify web ...

...bringing the total to 73 MW per rack. It also includes Air-Assisted Liquid Cooling (AALC) technologies, low-latency networks, and high-speed ...

...It also claims to be an industry-first in integrating artificial intelligence (AI) and machine learning (ML) directly into enterprise primary ...

...Vectra AI’s patented Attack Signal ​Intelligence that leverages AI and machine learning to learn unique environments and identify malicious activities.  The new ...

...the business community. Other terms you will hear from practitioners are AI bias, machine learning bias or algorithm bias. Bias ...

...in the role?” he asks himself rhetorically and answers with a resounding yes. “I would say there's no other industry ...

...on cybersecurity and lack of skilled professionals driving the continuous rise in tech compensation,” he says. High demand skills “Software ...

...analytics can use advanced machine learning techniques such as deep learning and neural networks to transform raw data into actionable ...

...hobby. The same apprehensions are coming to the fore once more with the rise of machine learning, language models and ...

...for Generative AI (GenAI) and machine learning.  “That has driven a lot of focus and energy around Research and Development or our investment ...

...leverages AI, Machine Learning (ML), and automation to improve operational efficiency and reduce OpEx. Bruno Cornaglia “AIM promises to unlock ...

...will save more operational data to teach AI, machine learning, and deep learning models, as well as train models on ...

...perceived threats of the technology and practice. A study from academic researchers published by Oak Ridge National Laboratory predicts that ...

...also meant the introduction of AI technologies and practices to support   AI for IT operations simply means applying AI ...

...an established program. AI-fueled security challenge Anthony Spiteri, the Regional CTO APJ at Veeam, says that security challenges are fueled by ...

...are set to offer Artificial Intelligence/Machine Learning (AI/ML) solutions in the next two years.  · The majority of those surveyed ...

...organisations can introduce innovative products and services, such as fraud prevention solutions for second-hand cars from tire manufacturers, or rapid ...

...and friction for our users when accessing critical data and systems. Expanded use of AI and automation – Applying AI ...

...funding in 2024 towards cloud platforms, followed by data analytics (78%). Despite the recent hype, AI and machine learning is ...

...Learning, Deep Learning, Natural Language Processing, Computer Vision, and Reinforcement Learning. Merely possessing theoretical knowledge is insufficient; a minimum of ...

...Southeast Asia and globally; the ongoing global explosion in data creation that continues to drive demand for data centres worldwide; ...

Palo Alto Networks unveiled Cortex XSIAM 2.0, which includes a new bring-your-own machine learning (BYOML) framework upgrading the capability of ...

...frameworks, it has implemented Workday HCM, to enable employees to access information. The interface has automation and self-service functionalities, enabling ...

...the only data platform in the industry with (1) a unified governance layer across data and AI and (2) a ...

...With the growing interest in machine learning (ML) and artificial intelligence (AI) there is the suggestion that a well-designed infrastructure ...

Statista estimates that 65% of the cloud market is dominated by hyperscalers: AWS (32%), Azure (23%) and Google (10%). Organizations use cloud services ...

Artificial intelligence and machine learning are some of the major buzzwords in the technology field in the past few years. ...

...AWS compute, database, analytics, machine learning (ML), networking, mobile, and other services to build security-focused and scalable applications faster.  It ...

...not designed to natively support the integration of machine learning and AI models for advanced predictive and prescriptive analytics. This ...

...This covers the entire spectrum from training, validating, tuning and deploying both traditional machine learning and new generative AI capabilities ...

Workday, Inc.’s latest global study reveals the optimism of leaders about the potential impact of artificial intelligence (AI) and machine learning (ML) ...

...anti-corruption compliance by leveraging risk data, machine learning, and AI technologies. “As the legislative landscape becomes increasingly complex, organizations need ...

...over the world.” AI skills gap According to the C-Suite Perspective, only around 20% of technology executives are confident in ...

ExtraHop open-sourced one of the most robust machine learning datasets to help strengthen defenses against malware, botnets, and domains generated by algorithms (DGAs). Collaboration against ...

...these complex systems but also adapt and self-regulate by simulating multiple scenarios. Through machine learning (ML), these advanced systems can ...

...and ChatGPT and other popular LLMs and machine learning workflows and tools.  Developers can perform common operations like data ingestion, ...

...of sophisticated attackers and it is used to disrupt the machine learning (ML) procedure by injecting a fraction of malicious ...

...should invest in a robust email fraud defence solution that utilises the latest technologies in machine learning and artificial intelligence ...

...a series of tasks that previously required human intervention. Other robotic solutions incorporate machine learning and include cognitive computing and ...

...accordingly." Chiara Girardi Additionally, 63% of top-performing CISOs proactively engage in securing emerging technologies like artificial intelligence (AI), machine learning ...

...solutions like serverless computing, robotic process automation (RPA) software, and artificial intelligence/machine learning (AI/ML) tools, to streamline both business and ...

Gartner defines Artificial Intelligence (AI) “as applying advanced analysis and logic-based techniques, including machine learning (ML), to interpret events, support ...

...type of allegations. AI/ML to reduce compliance burdens The report found that innovative vendors are using AI and machine learning ...

...can be nearly anyone, and they won’t need data science degrees or machine learning expertise to be effective. Why GenAI ...

...business decisions and building sustainable competitive differentiation. These technologies include AI simulation, causal AI, federated machine learning, graph data science, ...

Nutanix GPT-in-a-Box™ is launched to jump-start artificial intelligence (AI) and machine learning (ML) innovation, while maintaining control over customer’s data. ...

...tasks. Using techniques such as fine-tuning, in-context learning, and zero-/one-/few-shot learning, these models can be adapted for downstream (specific) tasks ...

...by process automation, digital-based customer interactions, machine learning, and more. Now, generative AI is accelerating the pace of change tremendously, ...

...suggests the use of platforms that are equipped to audit employee use – or potential misuse — come in handy. ...

Peter Krensky According to Peter Krensky, director analyst at Gartner: “As machine learning adoption continues to grow rapidly across industries, ...

...that many organisations are willing to pay more for cloud-native architecture featuring microservices and containers as well as machine learning ...

...they are looking to enable more advanced analytics like Machine Learning and AI within the context of their enterprise. "This ...

...removing all friction points along the user journey. This is creating an ‘Experience Economy’ for customers, which requires banks to ...

...only 20% of strategists reported using AI-related tools, such as machine learning or natural language processing, for their function. However, ...

...for their organisation’s future. This appears particularly true for artificial intelligence (AI): 75% of respondents invested in AI and machine ...

...AI and machine learning to train large models and process vast amounts of data to keep up with customer demand. ...

...One technology that has become foundational to this drive to become data-driven is advanced analytics – the use of data ...

...machine learning (ML) for advanced threat detection. With AI and ML capabilities in their identity security solution, organisations can analyse ...

...support for HPE’s AI/ML software which includes the HPE Machine Learning Development Environment to rapidly train large-scale models, and HPE ...

...elicitation of requirements, and performing contingent or secondary business tasks. MLOps uses technology and processes to streamline and automate the ...

...them and governance is needed to manage this simplicity," he added. He pointed to solutions that offer detailed reporting on ...

...Deployment pipelines for AI/ML experiment tracking and automated ML workflows, which helps data scientists and intelligent application developers to more ...

...tools that can help improve the overall defence across the organisation include Artificial Intelligence (AI), Machine Learning (ML), and threat ...

...7th annual Global DevSecOps Report, 65% of developers are using artificial intelligence and machine learning in testing efforts or plan ...

...the benefits of improved manufacturing reliability, product traceability and automated data collection by applying technologies like artificial intelligence and machine ...

In the past weeks, leaders in AI and machine learning worldwide have debated the “immediate pause of the training of ...

...the use of renewable energy by (cloud) data centres, the use of more energy-efficient hardware, and the usage of small ...

...providers are using statistical modelling or machine learning approaches to create models that perform the calculations – fully automated continuous ...

...machine learning continuously measures performance and alleviates the strain of in-house IT teams. Denis-Donnelly "To modernise security efforts for a ...

Confirming the limited use of security automation in North Asia, a latest report revealed that only 24% of organisations in ...

...intelligence, security automation, and employee training to enhance security posture is necessary. Advanced technologies (e.g., machine learning and behavioural analytics) ...

...brands now need rich, contextual insights that provide a holistic understanding of their customers’ behaviours, including what’s happening and why, ...

...machine learning and other intelligent technologies into SAP solutions can lead to better business outcomes for our joint customers.” Christian ...

...Asia Pacific-based chief information officers (CIOs) will have successfully harnessed artificial intelligence, machine learning, and deep automation to speed up ...

...by applying a composable architecture. Continuous improvement and modernisation can be achieved by adopting a modular approach to application architecture ...

...business intelligence (BI) and machine learning (ML) on all data. The annual Data + AI World Tour in Hong Kong ...

...refers to the discipline of developing new, connected, and digitally enabled products and services using technologies such as artificial intelligence ...

...technologies such as automation of facilities using machine learning and AI, automation of painting quality inspection under the vehicle; automation ...

...Asia Pacific, Oracle “As a result, we’re extending our commitment to helping organisations in South East Asia embrace technologies like ...

...of the Computing-Tabulating-Recording Company (CTR) in 1911, renamed in 1924 to International Business Machine (IBM). The magnetic tape came to ...

...a technique called “few-shot learning” to train the AI model with just a few data samples, reducing the need to ...

...DataRobot enables customers to leverage multimodal automated machine learning capabilities on top of SAP Datasphere and bring it directly into ...

...platform for motorsports fans. “It feature an open development model, supporting faster progress, faster testing, and greater innovation. Machine learning ...

...as AI-based methods such as machine learning (ML) and deep learning (DL),” he adds. Ariana Leena Lavanya The study underscores ...

...as aerospace, automotive, industrial equipment, office appliances, and medical devices. Through RISE with SAP, Tontec has implemented SAP S/4HANA Cloud ...

...a dynamic security layer at the sensor level, powered by machine learning algorithms, resulting in fewer operational cyber incursions. #5: ...

...as he outlines his plans to further upgrade  the service in the domestic market while taking it global. “Through acquisition ...

...four skill areas of investment are cloud computing, cybersecurity, AI and machine learning, and infrastructure and systems, respectively. This aligns ...

...initiatives improving customer resilience and increasing customer lifetime value. CX investments with capabilities such as a strong foundation of customer ...

...global infrastructure, advanced analytics, and machine learning technologies – specifically Amazon Relational Database Service (Amazon RDS), Amazon Aurora (AWS’s fully ...

...data lakes and artificial intelligence as well as machine learning engines for processing and analytics,” he elaborated. He says this ...

...analytics market: the increasing importance of data in the modern enterprise, the ongoing shift to a public cloud, and the ...

...No-code developer technologies include application development platforms, Web development platforms, and UI/UX design tools. Intelligent developer technologies, which leverage artificial ...

...for Chief Information Officers (CIOs) and heads of infrastructure as they look to bring forward automation, and artificial intelligence/machine learning ...

...referred to as segmentation, marketers have discovered the value of tools like analytics, data mining and, more recently, machine learning ...

...publicly disclose their hiring metrics. Organisations that use AI and machine learning in their hiring processes, as well as the ...

...lake), enabling a single view of customers across ecosystems. Redesigning operations to infuse data across workflows to enable enterprise-level, data-driven ...

...and advanced education programs. This includes an initiative with the Singapore Institute of Technology where Applied employees gain access to ...

...regulation can hamper innovation. Martina Raveni, a thematic analyst at GlobalData, says more governments will enact AI regulations seeking higher ...

...technology with digitalising operations. We used our customer-centric mindset to help us harness data analytics and machine learning techniques to ...

...integration of natural language processing, machine learning (ML) and artificial intelligence (AI) to drive context and insights. It also assists ...

...such as artificial intelligence (AI) and machine learning (ML), and business/data analytics tools.” Apeksha Kaushik At the same time, CIOs ...

...and demonstrate the value of their data investments, they will need to apply the same processes, rigour and metrics used ...

...heavily on AI and machine learning to optimize campaign performance and lower costs. Simultaneously, regulators and advocacy groups are vocalizing ...

...and predictions made by analysing real-time data obtained from sensors and IoT, allowing organisations time to identify and work on ...

...customer demand for AI/ML. As customers seek AI and machine learning for product innovation and greater operating efficiency, database and ...

...volumes grow, data is becoming distributed across clouds, used in more workloads, and accessed by more people than ever before. ...

...will be shared across the 200 million users without any human intervention, through artificial intelligence and machine learning. Adoption of ...

...Building and scaling these desired outcomes will require CX executives to leverage strong technology foundations comprising customer data, artificial intelligence ...

...& Sullivan. “Automated processes, remote monitoring, and digital supply chains accelerate biomanufacturing rates of biopharmaceuticals.” She added that digitalisation deploys ...

...and Culture and equips undergraduates with training in machine learning (ML), cloud computing, and mobile development, along with soft skills ...

...visibility gaps because data traffic is monitored, not individual assets within the infrastructure. Best-in-class NDR systems utilise machine learning and ...

...partners, and more. According to the report, machine identities make up 43% of all identities for the average enterprise, followed ...

...the day before personal computers and smart devices, before artificial intelligence and machine learning, customer satisfaction was measured by how ...

...invest in ‘breakthrough’ technologies that will drive digital business and enterprise success. Forty per cent of board directors consider artificial ...

...trust building will be significant. 10. Machine vision will enable dramatically improved experiences in physical locations. Those organisations that establish ...

...gains. As AI becomes increasingly pervasive and requires more complex machine learning (ML) models, it consumes more data, compute resources ...

...not enough is being invested into training.  The top three most challenging areas to find qualified talent in APAC are ...

...AI/Machine Learning. “As with every crisis, the pandemic showed that organisations which were prepared to be more innovative and progressive ...

...introducing new controls or steps to protect customers.’ Using machine learning, the Callsign platform understands recurring behavioural patterns of users ...

...Fabric helps provide clean, complete, uncompromised data to the MDP, enabling advanced analytics, dashboards, and reporting capabilities that leverage enriched ...

...(AI) and machine learning tools such as Kubeflow, Looker, BigQuery and Vertex AI, to enhance customer interactions and to provide ...

...are looking to invest in four technologies to drive long -term value. These technologies – data and analytics; cloud; internet ...

...and flexible enterprise technology stack. Extract full value from data: Embed repeatable processes for scaling advanced analytics; deploy artificial intelligence ...

...power of Google Cloud to drive data outcomes. Using artificial intelligence (AI) and machine learning (ML) in big data analytics, ...

...of 31.0%. From the perspective of AI software, under the joint promotion of the gradual development of technologies including machine ...

Customer experience has emerged as a key battleground and businesses that can win the customer experience war will be more ...

...we have vast amounts of data, 500 petabytes of data, and we can harness the use of that data in ...

...skill sets and focus on building a culture that has shifted to sustainable ways of working.” What IT organisations can ...

...shape to reduce costs—whichever shape provides the best price performance. Machine Learning:  HeatWave ML provides in-database machine learning capabilities, including training, ...

...with fewer errors when you hit the testing phase,” he added. AI will not displace DevOps teams Despite the continuing ...

...Conversely, new data systems powered by a range of technologies such as machine learning, deep learning, statistical methods, and others ...

...us develop Hong Kong’s first truly credible ESG reporting platform. The cloud allows us to maximise the power of blockchain ...

...customers concerns and enquiries. The new Meralco Data Platform (MDP) processes the utility company’s data and runs various machine learning ...

...feature engineering and machine learning modelling. Because these functions are built into the database, they are highly performant and require ...

...scale)? For enterprises to optimise their adoption of AI, what must they undertake first? There are many use cases of ...

...new agreement, the two organisations will deploy technologies such as extended reality, machine learning, Internet of Things and edge computing ...

...and regional head of cash product infrastructure and systems at CIMB Singapore, while banking is a highly regulated industry, it ...

...causal AI, foundation models, generative design AI and machine learning code generation. Optimised technologist delivery: Successful digital businesses are built, ...

...to get UEBA to work, machine learning and AI (Artificial Intelligence) become very prominent in that piece of technology. AI ...

Donald Feinberg “Data has become the most important asset of any organisation and data and analytics are more critical than ...

...perceptive and safer than anything that exists today," said Marc Raibert executive director of newly-launched Boston Dynamics AI Institute. Experts ...

...incorporates the use of artificial intelligence (AI) and machine learning (ML) models to support this,” said Cheam Tat Inn, managing ...

...pathway to digital transformation. How does AI/machine learning support optimisation? Adrian Bugaian: When optimisation is first rolled out, the requirements ...

...have machine learning and that is the most basic form. Then there is hybrid AI and cognitive AI and lastly, ...

...O’Hara observed that hackers leveraged this and targeted shopping and services sites. “Bad bots benefit from the evolution of technologies ...

...excel. AI and machine learning can capture data and gather intelligence from previous tasks to shorten production lines. But there ...

...Language Processing (NLP), cognitive agents, Machine Learning (ML), and predictive analytics are bringing new levels of capabilities to traditional robotic ...

...for real-time, intelligent responses, ensuring a well-delivered customer experience,” he added. Is there such a thing as smart optimisation? How ...

...analysts should protect against attacks across all the organisation’s environments, including the endpoint, network, cloud, and mobile. Leverage Artificial Intelligence ...

...APIs; and leveraging machine learning have all become table stakes. “Modern bot management tools must keep up with ever-evolving attacks, ...

...matched with machine-learning algorithms provides valuable insights on efficiencies, costs, and new services.” said Yuval Baruch, Chief Executive Officer, Hermes Logistics Technologies ...

...continuity, as well as the ability of their IT systems to cope with it." Businesses hone in on investment priorities ...

...patients for clinical trials and to reduce the turnaround time for clinical studies. “Owing to the growing use of machine ...

...many business and IT processes as possible through the orchestrated use of multiple technologies, such as artificial intelligence (AI) and ...

In recent years, the industry has witnessed the migration of machine learning (ML) closer to the data source to create ...

...the same direction.” Deloitte Analytics says we are living in the “age of with”: humans with machines; data with actions; ...

...and running SaaS functions. Cloud supports innovation Source: Rackspace 2022 Respondents to the survey claim that by combining cloud computing ...

...Vasupradha Srinivasan: The learning specifically over the pandemic is that it is not man against machine. We must figure out ...

...research predicts there will be over 1.7 trillion multi-factor authentication messages delivered globally in 2022. This represents 60% of total ...

...into super apps. Much more change is on the horizon. AI and ML will enable new consumer services: Consumers don't ...

...solution providers should consider: Implementing digital twins to mitigate risks and improve resilience: Solution providers of digital twins, artificial intelligence ...

SailPoint Technologies sets the standard on how identity security must evolve to keep pace with the dynamics of their customers' ...

...as energy operators look to improve their capital allocation and increase their revenues, perhaps even move into a services model, ...

...If people don't incorporate sustainability into their business, they're going to be leaving customers behind,” he elaborated. Technology to support ...

...teams to scale and support a cross-functional governance role requires the introduction of new efficiencies. “This is where modern solutions ...

...supervisory control and data acquisition (SCADA), utility energy management systems and new operationalized real-time capabilities that leverage physical and machine ...

...such as containerisation, database platform-as-a-service (dbPaaS) and artificial intelligence/machine learning contain richer features than commoditised compute such as IaaS or ...

...standards. Adopt behavioural biometrics: Vendors should encourage customers to deploy behavioural biometric security as it uses artificial intelligence (AI) and ...

...technologies such as native integration, process intelligence, low code, business process management (BPM) and diverse forms of machine learning to ...

...the business to understand whether any personally identifiable information (PII), financial data, or intellectual property was taken, and which additional ...

...Chern-Yue Boey SailPoint senior vice president for Asia-Pacific, Chern-Yue Boey, says to make better identity decisions, enterprises need tools that ...

...is driving this increased spending at the edge. The performance requirements of expanding workloads and new use cases that leverage ...

...determine which is best for my business? Dave Russell Dave Russell, VP of enterprise strategy at Veeam, says the transition ...

...that leverage machine learning. “We are now using computers to be able to make an informed decision on a perceived ...

...a compound annual growth rate of over 20%. Virtual machine (VM)-based workloads show a steady decline, with cloud-native environments benefiting ...

According to Frost & Sullivan digital transformation is occurring on a massive scale due to the need for increased efficiency, ...

...as demonstrating improvement and preventing patient abandonment will become a direct monetary issue. Machine learning in an advisory role The ...

...AIOps (artificial intelligence for IT operations) as combining big data and machine learning to automate IT operations processes, including event ...

...Machine learning (ML)-based analytics is expanding from its traditional home in the cloud/data centre- and mobile-based applications to the IoT ...

...rate of predictive analytics at 70% compared to the 47% average across markets; machine learning was the second-most (63%) leveraged ...

...and public clouds, AI (Artificial Intelligence) and ML (Machine Learning) for the adoption of IoT, and hybrid work to connect ...

...that can configure and train machine learning solutions in the specific context of an organisation. “This kind of in-demand machine ...

...than selling me a solution because that doesn't help me in any way.” Songhua Zhang Songhua Zhang, senior vice president ...

...end to end based on machine learning, but it can help to guide the size and help to guide those ...

Data from IDC’s AI InfrastructureView study revealed that while artificial intelligence/machine learning (AI/ML) initiatives are steadily gaining traction, 31% of ...

...budgets to grow over the next two years. Advanced analytics topped the investment list, particularly artificial intelligence (AI) and machine ...

...automated machine learning (AutoML) becomes the dominant method to democratize data science and speed deployment of AI solutions, 60% of ...

...that artificial intelligence and machine learning will increase in sophistication as enterprises demand infrastructure and applications that are operationally self-resilient. ...

...securing data – cloud computing (85%), artificial intelligence (AI) and machine learning (80%) and cybersecurity (71%). AI has also risen ...

...work requirements (39%); and a desire to capitalize on cloud-native technologies (39%) such as artificial intelligence and machine learning (AI/ML), ...

...technology uses artificial intelligence and machine learning to generate a likeness around someone and then make it seem real. It ...

...the platform. Capability to support a variety of dev/ops services, APIs, and microservices, which enhances the client’s ability to integrate ...

...machine learning for real-time transaction monitoring and enables rapid decision making has become critical for fraud prevention,” McDonnell recommended. For ...

...like mobility, AI, and machine learning into their applications. Facilitates integration of services specific to an industry and common business ...

...across distributed landscapes by utilising active metadata semantics and machine learning capabilities. “It drives enterprise-wide data and analytics and also ...

...and faster with machine-learning analytics?  Does it reduce dwell times through easier investigation, faster response, and more automation? “The three ...

...which is machine learning algorithms finding useful patterns, anomalies and data. The bias lies in the data itself and with ...

...Who needs to be involved, how much time, whether they have the capacity or necessary skillsets,” she added. Truog recommended ...

...intelligence’ as they say in the military. Using data analytics and advanced machine learning to create a more personalized and ...

...a 98% effective rate — prevention is possible using machine learning and artificial intelligence,” he elaborated. Why zero-trust make sense ...

...is a creative process, but one that has many repetitive tasks. In 2022, Machine learning (ML) will begin to play ...

...and machine learning (ML) will play a big role in augmenting the capabilities of security solutions today. Ng sees AI ...

...emerge. AI and machine learning (ML) will be critical to optimising the performance of these networks. Greater penetration of digital ...

...capabilities in natural language processing and machine learning to be embedded in mainstream products, making them available at scale across ...

...the benefits of leveraging on AI. When human expertise consults AI and ML technologies to monitor, analyse, and customize machine-led ...

...quantum systems to use machine learning to look for new ways of finding patterns in LHC data. And industrial chemists ...

...and machine learning will be critical to optimising the performance of these networks. It will take focus and time to ...

...of data available to sales organizations and revitalized budgets is driving many sales leaders to invest in AI and machine ...

...priority for the Singapore market (45%). The adoption of AI and machine learning has significantly increased on a global scale. ...

...critical factor to their success. Use of AI/ML in marketing By 2025, one in five B2B companies will use artificial ...

...more insights into warehousing operations, as well as boost predictive analytics. Operators can now deploy Machine Learning (ML) algorithms that ...

...as AI and machine learning, and 82% expressed concerns that not being cloud-ready could be a significant barrier to accelerating ...

...to realizing the full benefits of key emergent technologies, such as AI and machine learning. Steve McMillan Teradata president and ...

...or plan to deploy AI and machine learning technologies within the next 12 months. The reality of AI deployment is ...

...for all potential scenarios. And with the advent of emerging technologies like artificial intelligence and machine learning, banks can better ...

To keep pace with accelerating digital transformation initiatives and the realities of global health, climate, and social challenges, organizations must ...

...need far more understanding of your customer. You will need things like machine learning you are able to provide the ...

Enterprise intelligence is a key driver for growth for organizations of all sizes, across all industries and geographies. The IDC ...

...artificial intelligence (AI), machine learning (ML), big data, blockchain, Internet-of-Things (IoT), augmented reality/virtual reality (AR/VR), robotic process automation (RPA), serverless ...

...executing a strategy to engage and source talent across geographies. Automation solutions in RPO: Cognitive automation solutions driven by artificial ...

...security and performance issues using Artificial Intelligence (AI) and machine learning. This enables the organisation to proactively solve issues before ...

Gartner predicts that by 2025, half of cloud data centres will deploy advanced robots with artificial intelligence (AI) and machine ...

...cloud engineering, artificial intelligence and machine learning (AI/ML), internet of things (IoT), analytics, cybersecurity, and augmented reality and virtual reality ...

...brings to the RPA. In the context of the finance function what is RPA? How has RPA changed how work ...

...continued. The top strategic technology trends for 2022 are: Generative artificial intelligence (AI) One of the most visible and powerful ...

...machine learning to detect threats before any major harm is caused. By establishing a network baseline, businesses have behaviour-based detectors ...

...by vendor Vlad Galabov “As demonstrated by the developments in Q2 21, we should anticipate more innovation around the use ...

...your environments, and leverage on well integrated Artificial Intelligence (AI) and Machine Learning (ML) engines to help you act on ...

...2022. Adopting process mining Source: Everest Group Process mining blends the power of data-based analysis techniques, such as data mining ...

...the need for deeper levels of personalization – all while remaining compliant to regulations and customers’ needs. New purpose for ...

...intelligence and machine learning, together into contemporary processes. “Doing so will release cost savings – may be up to 50% ...

...use cases TIBCO DQ will become the new data quality product family, significantly enhancing current capabilities available throughout the entire ...

...Thirty-six per cent of government respondents in the 2021 Gartner CIO survey indicated that they planned to increase investment in ...

ABI Research predicts that spending in Artificial Intelligence (AI) and machine learning (ML) in the media and entertainment (M&E) to ...

...identify investment priorities for operations over the next five years, organizations ranked cloud highest, followed by wireless connectivity and artificial ...

...recognize that artificial intelligence and machine learning are the basis of competitive advantage in their industry, leading to an explosion ...

...cloud-native applications, Kubernetes containers, artificial intelligence and machine learning pose a risk to data protection, and the lack of data ...

...the Hype Cycle reaching mainstream adoption within two to five years,” said Shubhangi Vashisth, senior principal research analyst at Gartner. ...

...automate elements of digital experience that guide user choices at scale by learning and applying techniques of behavioural science. The ...

...the application of AI/machine learning (ML) and big data and analytics in an intelligent and highly automated manner to address ...

...approach to endpoint defence that leverages artificial intelligence (AI) and machine learning (ML). The endpoint security solution they built, now ...

...bringing in emerging tech solutions like AI, IoT, machine learning and blockchain – but this approach is not sustainable,” he ...

...and was the first Singapore bank to tap AI and machine learning to combat financial crime; not to mention, the ...

...Reg Tech to leverage new technologies like Artificial Intelligence and Machine Learning to help adapt to new regulations, as well ...

...– 11% higher than APJ. Hope on the horizon Although Singapore businesses are struggling today, many have plans to create ...

...technologies such as robotic process automation (RPA) and cognitive/artificial intelligence (AI) based technologies (including natural language processing, machine learning and ...

...and machine learning to provide this integrated solution – an integrated intelligence automation platform,” he added. Why the CIO cares ...

...digital channels especially for B2C business is a key focus. A greater demand for AI / Machine Learning as well ...

...banking, community investment, climate-positive financing, socially responsible business, and financial literacy. Teams are expected to use the likes of big ...

...CIPS providers’ automated programmable infrastructure Gartner expects the broad adoption of fully managed and artificial intelligence (AI)-/machine learning (ML)-enabled cloud ...

...Huat these enhancements include: ●            A search engine that allows customers to search for products faster & easier ●            Mobile-friendly ...

...applications. Optical character recognition (OCR), computer vision, machine learning (ML) and deep learning models, and natural language processing (NLP) are ...

...machine learning and data science models,” he continued. Critical skills lacking “Fundamentally, the role of a data scientist is to ...

...services to full-stack capabilities. To sweeten their appeal, hyperscalers are offering next-generation services including artificial intelligence (AI), machine learning (ML), ...

...surface. Using machine learning, the platform is automated to identify new cyber threats and enable speedy prevention, detection and responses.” ...

...services, given the need to provide outstanding customer experience (CX) remotely. Emerging technologies like artificial intelligence (AI) and machine learning ...

...analytics and machine learning solutions to analyse and test new credit risk and forecasting models. 70% of APAC businesses surveyed ...

...CROs relate to technology and data, including industry disruption due to new technologies (70%), the pace and breadth of change ...

Nearly twice as many companies have now started their AI journey in 2020 compared to 2019, and those that have ...

...10 times Amazon’s net income in the 2020 financial year, demonstrates why merchants must make combatting fraud, through the use ...

...R&R providers are adopting a multi-prong approach to revamp their present capabilities: Developing smarter platform capabilities. R&R solution providers are ...

...will invest in technologies and services that power automation, human-machine collaboration, new organizational structures and leadership styles, dynamic learning opportunities, ...

...allowing for speed and agility gains. “Low-code is moving into different segments of the IT stack, such as integration, visualization ...

...artificial intelligence (AI), machine learning (ML), and natural language processing will take centre stage in the post-pandemic era. Additionally, with ...

...theme reflects the recognition that innovative technologies are often combined together to solve specific supply chain business problems. Hyperautomation Hyperautomation ...

...AI and machine learning (ML) technologies to spot abnormal behaviour and institute policies that ensure accurate identity access. A modern ...

...Palo Alto Networks 2021 Enhanced security: The Advanced URL Filtering service offers industry-first prevention of zero-day web attacks with inline ...

...machine learning, and systems integration. This is because digital twins are not a technology, but a composition of solutions aimed ...

...of ownership (TCO). He cautioned, however, that it is also important to recognise that the cloud enables new technologies like ...

...the business problem you're trying to solve With a well-articulated objective in mind, it should be relatively straightforward to target ...

...three technologies are cloud infrastructure, which enables data on demand, machine learning and artificial intelligence, which help companies automate, and ...

...AI and machine learning are critical for providing vital insights about the virus and realigning supply and the supply chain ...

...through technological developments in multiple fields, including Internet of Things (IoT), additive manufacturing, cloud computing, edge computing, analytics, robotics, cybersecurity, ...

...very effectively with technologies, with artificial intelligence and machine learning models, which can adapt to be able to work out ...

...computing is the future industry and infrastructure disruptor for organizations looking to use large amounts of data, artificial intelligence, and ...

...to be used effectively by advanced technologies such as artificial intelligence, machine learning and augmented reality. Such tools can play ...

...entry for end-users who do not possess data science or machine learning expertise but also enabling them to perform edge ...

...data hungry. “Disruptions such as the COVID-19 pandemic is causing historical data that reflects past conditions to quickly become obsolete, ...

Thanks to advancements in handling big data, machine learning can now change the architecture for AML. Read the SAS whitepaper ...

...in learning and development (L&D) and participating in IT decision making. As organizations plan their strategies for the new normal ...

Despite all the advances in technology, including advanced analytics, data management, artificial intelligence and machine learning, the CEOs that participated ...

...must leverage technologies like machine learning to go beyond the current generation of technologies. “I am starting to worry that ...

Gartner defines AIOps as combining big data and machine learning to automate IT operations processes, including event correlation, anomaly detection ...

...hindered actual adoption. These are the observations drawn from a Juniper Research commissioned of 700 IT decision-makers (globally) with direct ...

...The other area he suggested that CSPs must address is on the mitigation technology itself. He opined that despite advances ...

...the problem is that digital marketing leaders are still scaling their use of emerging technologies, such as artificial intelligence (AI) ...

...in sophistication, companies are looking to more efficient technology solutions that incorporate automation, machine learning and artificial intelligence. Indeed, automated ...

...machine learning (ML) in creating new business models or generating new revenue stream may be stealing leadership and investment capital, ...

...intelligence (AI), machine learning and advanced analytics, at each stage of government activity to improve the efficiency, effectiveness and consistency ...

...even the load and prevent bottlenecks.” Use case for advanced data and predictive analytics NCS will deploy advanced data and ...

...significant and a clear direction towards more accessible AI and machine learning platforms with then public clouds. “But I think ...

...that accelerate their capabilities to anticipate, shift and respond. Trend 1: Smarter, responsible, scalable AI By deploying smarter, more responsible, ...

...action. Hyperautomation involves a combination of technologies that include robotic process automation (RPA), machine learning (ML), artificial intelligence (AI) and ...

...human/machine interaction, robotics engineering, blockchain, and machine learning will offset the 8% of more traditional technology roles that can be ...

...and businesses continue to push for more granularity in answering, “where’s my stuff?” with an ETE, real-time response.”  Synergistic technologies ...

...on governance, risk, and compliance saw double-digit growth in 2020/2019. The report found that 60% of banks in Asia Pacific ...

...managed, and leveraged for dealing with data diversity? We are facing an increasing need for data scientists, but businesses can ...

...as artificial intelligence, data analytics, and machine learning; leveraging their benefits to improve customer experience and product innovation." Described as ...

...areas of a business. Advancements in Machine Learning, Conversational AI, and Computer Vision AI are at the forefront of AI ...

...a skills rotation over 6 months and bring them up to the level required for a machine learning or data ...

...agile, powerful advanced machine learning engine to help master the complex data that’s in cloud environments.” “SAS Viya helps organizations ...

...fiction movies, this is a machine that learns as it interacts with its environment at scale. Reinforcement learning is about ...

...Biometric technologies: With vendors integrating biometric technologies with AI and machine learning, there is a strong market for high-end biometric ...

...enterprise data cloud (EDC) to gain better visibility and control of data, support the use of artificial intelligence/machine learning, and ...

...use cases. “Your (ERP) application needs to be fundamentally built on AI and machine learning, and not a use case-based ...

...no-code and low-code tools, and automation-enabled machine learning will be key to success. This democratization effort also will require contextualization, ...

...Use machine learning and large data to identify and unlock the power of skills adjacencies at scale. Partner with your ...

Driven by consumer demand and transformative technologies, the fourth industrial revolution (4IR) is challenging manufacturers to embrace new business models. ...

...Data companies to use data to fuel the behavioural analytics machine. Data-driven behavioural analytics is a dangerous game to play. ...

...and machine learning capabilities could be leveraged in PAM use cases. The focus of PAM implementations has also expanded from ...

5G is a composition of several network layers that leverage technology with varied maturity levels, such as Open RAN, network ...

...market, presenting lucrative growth prospects for market participants, including: Introducing new technologies such as predictive analytics and machine learning to ...

...and Machine Learning (ML), blockchain, and computer vision systems. For example, self-driving truck company TuSimple partnered with Navistar and Penske ...

...traditional Business Intelligence and visualisation tools to leverage advanced statistical models and machine learning, giving insights that traditional tools are ...

...in the financial services sector, RPA has now proliferated to all industries and been boosted by the growth of hyper-automation ...

...There is also potential for incomplete data for processing for decision-making because of limited data type/format handling. For example, predictive ...

...this unstructured data into a viable structured data source. Using network data, Network Detection and Response (NDR), monitor all communications ...

...while enhancing revenue opportunities,” he elaborated. For his part, Handojo Triyanto, senior research manager at IDC Financial Insights Asia/Pacific, listed ...

...inventory which eventually leads, indirectly, to customer experience. Asked what is next on the horizon, Aguiar was quick to name ...

...as phones and tablets or through the internet-of-things (IoT) sensors at remote or edge devices. Next-generation workloads such augmented reality, ...

...latency-, and security-sensitive workloads at the edge,” explained Lian Jye Su, AI & Machine Learning principal analyst at ABI Research. ...

...providing more immersive and interactive experiences. The deep integration of AI and machine learning into cloud infrastructure, platform, and applications ...

...data). Advice to business leaders: Recent innovations in machine learning have finally unlocked the long-promised potential of artificial intelligence. Now ...

...wherever you are. The Internet of machine learning ML has historically been a computationally heavy workload that’s incapable of running ...

...analysts to share their prognostications. Predictions of greater use of artificial intelligence, machine learning, IoT and robots, to security-centric platforms ...

...and machine vision Developments in computer vision and machine vision solutions are delivering more precise depictions of on-site, regardless of ...

...are perceived as delivering more value-added benefits. Yes, tailored solutions are also starting to become fashionable again. In addition, innovations ...

...and speech recognition. The learning technologies include supervised and unsupervised machine learning, and reinforcement learning, and neural networks. In terms ...

...expect explainable AI to become mainstream in 2021,” opined Lian Jye Su, AI & Machine Learning principal analyst at ABI ...

...when the past no longer reflects the future? Enter reinforcement learning. Rather than analysing a historical data set as traditional ...

...employing techniques such as machine learning to ensure effective and efficient analysis of data at scale. What kind of data ...

...offering can automatically detect sensitive content via advanced machine learning-based data classification and data patterns that leverage over 500+ industry-defined ...