Safeguarding AI and business resilience with NVIDIA NIM

Trend Micro Incorporated has launched multiple efforts to shape the future of AI implementation by enterprises and governments. The new solution, included in Trend Micro’s Vision One™ Sovereign Private Cloud — powered by NVIDIA NIM microservices, part of the NVIDIA AI Enterprise software platform — will allow organizations to maximize the potential of the AI era while maintaining business resilience.

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Eva Chen, Co-Founder and CEO at Trend: “We are not just adapting to an AI-driven world: we are creating it, helping to ensure that any team can securely innovate without elevating risk. New technology implemented appropriately should improve business resilience rather than impair it. Just as we did with the advent of cloud security, we are pioneering AI for security and security for AI.”

“Enterprises and governments are seeking ways to securely integrate AI into mission-critical systems while maintaining full control of proprietary data,” said Justin Boitano, Vice President of Enterprise Products at NVIDIA. “The NVIDIA AI Enterprise software platform provides the performance, reliability and security needed for advanced data protection and operational efficiency.”

Adopting new technology can pose challenges, and leaders in business and governments worldwide are especially concerned with reducing risk at all levels during the process. Trend recognizes the importance of deploying generative AI and is collaborating with NVIDIA to develop strategies to secure generative AI to enable long-term business transformations. Shortsighted integration strategies that over prioritize early outcomes can lead to elevated risks of misconfigurations, vulnerabilities or data breaches.

A leading technology provider supporting systems across Germany, Austria and Switzerland, spoke under anonymity: “Organizations around the world that are required to maintain the most stringent data sovereignty and privacy requirements often cannot use public cloud-based AI. Now get the best of both worlds. These offerings are setting a new standard for securing AI implementations, and we are excited to be a part of this journey.”

Trend is focused on understanding infrastructure changes, user behaviors and operational needs to safeguard data against both known and unknown risks at every stage of adoption in a new technological era.

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Trend technology is certified to meet local compliance requirements in 175+ countries, making it a global leader in adapting to security regulations and protecting data sovereignty. Regardless of the customer environment—cloud, SaaS, on-premises, sovereign, private or AI data centers—Trend spans across Amazon Web Services, Microsoft Azure and Google Cloud clouds and containers that can move around within different platforms.

GMI Cloud supports on-demand access to NVIDIA Tensor Core GPUs and is an AI technology partner with Trend Micro. Alex Yeh, CEO at GMI Cloud, said: “We have yet to see anyone introduce security capabilities at this level for AI technology. We value the ability to use the same AI security rules and platform to manage customers’ AI data tools across any environment.”

Trend’s integration with the NVIDIA AI platform — including NVIDIA AI Enterprise, which includes NVIDIA NIM microservices, the NVIDIA Morpheus cybersecurity framework and more — meets use cases in demand today by enterprises, governments and critical infrastructure organizations worldwide that are seeking reliable and effective technology partners to guide AI implementation and operations.

AI for Security

• Trend Vision One Companion, an AI assistant leveraging NVIDIA NIM microservices and accelerated computing, provides proactive threat detection and response, and sensitive data protection even in air-gapped environments, while accelerating productivity and response to adversaries.
• Customers of Trend Vision One platform, leveraging NVIDIA Morpheus,benefit from extended detection and response (XDR) models that can process and classify larger volumes of user data better than ever—for faster threat and anomaly detections. This can help to de-noise and build up fingerprints from typical user behaviors, allowing human analysts to concentrate on the most important events.

Security for AI

• Even the most tightly controlled organizations, like governments and critical infrastructure groups, can use AI without compromising data sovereignty with Trend Vision One Sovereign and Private Cloud integration with NVIDIA NIM microservices.

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AI Storage as-a-Service and other solutions showcased at //Accelerate deliver the best foundation for AI and cyber resilience

Pure Storage//Accelerate – Pure Storage the IT pioneer that delivers the world’s most advanced data storage technologies and services,announced new capabilities in the Pure Storage platform that are changing the game for how IT and business leaders can radically improve their ability to deploy AI, improve cyber resilience, and modernize their applications.

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The Pure Storage platform delivers agility and risk reduction to organizations with a simple, consistent storage platform and an as-a-service experience for the broadest set of use cases across on-premises, public cloud, and hosted environments. At the heart of the platform, the often imitated but never duplicated Evergreen architecture brings continuous and non-disruptive upgrades, helping enterprises adapt to dynamic business environments. With the industry’s record number of concurrent SLAs, customers get the reliability, performance, and sustainability their business requires.

“Pure is redefining enterprise storage with a single, unified data storage platform that can address virtually all enterprise storage needs including the most pressing challenges and opportunities IT leaders face today, like AI and cyber resilience. The Pure Storage platform delivers unparalleled consistency, resilience, and SLA-guaranteed data storage services, reducing costs and uncertainty in an increasingly complex business landscape.” — Charles Giancarlo, Chairman and CEO, Pure Storage

Today, Pure Storage announced new innovations in the platform including:

• First-of-its-Kind Storage Automation: Pure Fusion unifies arrays and optimizes storage pools on the fly across structured and unstructured data, on-premises, and in the cloud. Now fully embedded into the Purity operating environment designed to continually get better over time via non-disruptive upgrades, the next generation Pure Fusion will be available across the entire Pure Storage platform to all global customers.
• Industry-First Generative AI Copilot for Storage: Extending Pure Storage’s leadership position as the innovator in simplicity, the first AI copilot for storage represents a radically new way to manage and protect data using natural language. This leverages data insights from tens of thousands of Pure Storage customers to guide storage teams through every step of investigating complex performance and management issues and staying ahead of security incidents.

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Accelerating AI Success in the Enterprise with the Pure Storage Platform

In the new Innovation Race survey of 1,500 global CIOs and decision makers commissioned by Pure Storage, nearly all respondents (98%) state that their organization’s data infrastructure must improve to support initiatives like AI. AI is evolving so rapidly that IT is struggling to keep up, much less predict what’s next. Companies large and small are realizing that they are locked into inflexible storage architectures lacking enterprise-grade reliability, unable to resize or upgrade performance without complex and risky infrastructure planning.

Pure Storage is introducing new innovations in the platform that help businesses accelerate successful AI deployments today, and future proof for tomorrow. The Pure Storage platform empowers organizations to unlock the value of their data with AI, while delivering agility to instantly scale capacity and performance up and down independently, without disruption.

• New Evergreen//One for AI – First Purpose-Built AI Storage as-a-Service: Provides guaranteed storage performance for GPUs to support training, inference, and HPC workloads, extending Pure Storage’s leadership position for capacity subscriptions and introduces the ability to purchase based on dynamic performance and throughput needs. The new SLA uniquely delivers the performance needed and eliminates the need for planning or overbuying by paying for throughput performance.
• Secure Application Workspaces with Fine-Grained Access Controls: Combines Kubernetes container management, secure multi-tenancy, and policy governance tools to enable advanced data integrations between enterprise mission-critical data and AI clusters. This makes storage infrastructure transparent to application owners, who gain fully automated access to AI innovation without sacrificing security, independence, or control.

Pure to Expand and Accelerate Enterprise Adoption of AI with Planned NVIDIA DGX SuperPOD Certification

Pure Storage was among the first enterprise storage vendors to work with NVIDIA to achieve NVIDIA DGX BasePOD certification and NVIDIA OVX validation. Building upon this pioneering collaboration for AI-ready infrastructure, Pure expects to be a certified storage solution for NVIDIA DGX SuperPOD by the end of 2024.

Pure Storage’s Ethernet-based storage solution simplifies the integration and deployment of large scale training and inference and helps democratize AI to enterprises that are eager to accelerate their AI initiatives. Pure’s industry-leading energy efficiency, consuming up to 85% less energy than alternative all-flash storage solutions, can help customers overcome data center power constraints in large AI clusters.

“Enterprises adopting AI need storage performance and flexibility as they architect their infrastructure to address AI workloads at scale. Pure Storage’s certification with the NVIDIA DGX and OVX platforms helps deliver highly-performant solutions for customers at every stage of their AI journey.”  – Charlie Boyle, Vice President of DGX Platform, NVIDIA

Customer Perspectives

“As more businesses rely on automation and AI to make near-real-time decisions, at ServiceNow we are committed to meeting their needs. That starts with 24/7 performance and reliability. We couldn’t have chosen a better partner than Pure Storage to scale with our rapid growth. Projects that take other companies three years, take only three months using Pure’s enterprise data storage platform. With Pure, we can do it faster and we can make the enhancements needed to fuel our customers’ success.” — Keith Martin, Vice President of Global Cloud Engineering, ServiceNow

“At Paylocity, data flexibility, precision, and automation are critical to empowering our customers to make strategic human capital decisions swiftly and accurately. We see incredible value in Pure Fusion to unlock both flexibility and self-service for our developers. Pure Fusion promises the true cloud operating model we need to innovate faster and more efficiently, and ultimately deliver valuable outcomes to our customers in the future.” — Dave Pinkawa, Engineering Manager – Virtualization, Paylocity

Also Announced Today at Pure //Accelerate:

• Pure Storage Platform Arms Enterprises in Fight Against Ransomware with Ground Breaking New Cyber Resiliency Services and Capabilities

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• Cloudera is now the only provider to offer an open data lakehouse with Apache Iceberg for public and private clouds 

• Platform will be on display at booth #1534 during the Gartner Data & Analytics Summit in March

Cloudera, the data company for trusted enterprise AI,announced the next phase of its open data lakehouse on private cloud that revolutionizes on-premises data experiences for trusted analytics and AI at scale. With its latest round of enhancements, Cloudera has become the only provider to offer an open data lakehouse with Apache Iceberg for public and now private clouds, helping customers to unlock the enterprise AI potential of all their data.

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Research from Cloudera estimates that 53% of organizations in the U.S. currently use Generative AI technology and more than a third (36%) are in the early stages of exploring AI for potential implementation in 2024. But implementations have stalled as many enterprises struggle to access or achieve business value from their data with AI. Challenges include distributed data infrastructures, governance risks, or security concerns.

By delivering Apache Iceberg for private clouds, Cloudera is empowering every organization to overcome these issues and quickly scale enterprise AI deployments to generate greater value. Apache Iceberg is an open-source, high-performance table format for vast analytic tables. When applied to private clouds, the solution enables companies to apply AI to the vast amounts of mission-critical data that exists both in the cloud and on premises, ultimately allowing them to create new use cases. Cloudera is also now the only company to provide the ability to run a completely air-gapped large language model (LLM) deployment, providing customers with enhanced security and data privacy, as well as improved performance and reduced operational costs.

Cloudera is also rolling out a series of additional updates to its platform that will deliver unprecedented business value to its customer base, including:

• Zero downtime upgrades (ZDU) and security enhancements such as Transport Layer Security (TLS) 1.2 for increased business continuity and minimized interruptions.
• New Apache Ozone capabilities, such as quotas, snapshots, and disaster recovery enhancements that enable vastly greater scalability at lower cost to service the voracious data consumption needs of modern workloads.
• Expanded support for integrations including Python 3.10, RHEL 9.1, RHEL 8.8 FIPS, SLES 15 SP4, Oracle 8.8, and JDK 17 for increased compatibility and flexibility.

“Cloudera’s mission is to empower customers to transform data anywhere into actionable insights by enabling it with AI,” said Dipto Chakravarty, Chief Product Officer at Cloudera. “By giving them a trusted data foundation for analytics, this next phase of cloud-native solutions unlocks endless possibilities for building innovative AI applications.”

“In this AI-powered era, we’ll continue to see formidable AI applications emerge that significantly increase the business value of enterprise data,” said Sanjeev Mohan, Principal, SanjMo. “For organizations to capitalize on this technological gold rush, data cannot be locked away in company data centers. Enterprises need a data management strategy that enables them to transform complex data anywhere into actionable insights through a comprehensive, open, and hybrid platform.”

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“The Iceberg community is very big and is growing fast. It’s being adopted around the world. Cloudera’s open data lakehouse with Iceberg means we have an open table format with a lot of advanced functionality, which makes it easier to use and maintain our data. The open table format is important to us, because it means data can be accessed easily by many users with a variety of tools,” said Matteo Carucci, Head of Data & Analytics, Eutelsat. “The open table format is a fundamental requirement because the company data is the property of the company itself, not a specific vendor. So an open table format guarantees that whatever may happen with technology in the future, you have full ownership of your data. ”

Cloudera will be demonstrating its latest series of updates at the Gartner Data & Analytics Summit, taking place March 11-13, 2024 in Orlando, Florida. Attendees will see firsthand the enhancements to Cloudera’s platform and speak to Cloudera experts onsite about the company’s next phase of cloud- native solutions. Additionally, Cloudera’s Technical Evangelism Director, Jake Bengston, will be leading a session at the event on March 12 titled, “Game-Changing Gen AI: Advancing from Pilot to Production at Enterprise Scale.” The session will cover stories of seasoned AI leaders from top global enterprises about lessons learned, best practices, and avoidable pitfalls so attendees can cut through the hype and deliver production-ready AI for a competitive edge.

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[To share your insights with us as part of editorial or sponsored content, please write to sghosh@martechseries.com]

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According to a recently published report from Dell’Oro Group, the trusted source for market information about the telecommunications, security, networks, and data center industries, 3Q 2023 marks the fifth sequential quarter of double-digit year-over-year (Y/Y) growth for the Data Center Physical Infrastructure (DCPI) market, that has historically grown at mid-single digit rates for the past decade. Growth from pandemic induced orders is waning, but early AI deployments are materializing as a new driver of revenue growth. Some vendors have secured orders for equipment optimized for large scale AI workloads, which are more than offsetting the decline in pandemic-related orders, and backlogs are rising.

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“The generative AI infrastructure story began with the NVDIA H100 in 1Q 2023, which has remained the industry barometer for AI adoption. End-users have utilized significant resources to obtain initial shipments of the costly and supply constrained GPU,” said Lucas Beran, Research Director at Dell’Oro Group. Due to the effort required here, many end-users are only able to address the power and thermal management infrastructure requirements after or close to receiving those initial GPU shipments.

“Without a doubt, these AI related power and cooling investments started contributing to market growth in 3Q 2023. This was particularly prominent for rack power distribution units, where customized products with higher power ratings were notable. The next few quarters will increasingly emphasize the transition in DCPI market drivers, from broad based pandemic induced digitalization and supply chain constraints, to large scale, purpose-built AI facilities,” Beran added.

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Additional highlights from the 3Q 2023 Data Center Physical Infrastructure Quarterly Report:

• Vertiv continued to outpace market growth and gained over 2 percentage points of market share in 3Q 2023.
• North America, Asia Pacific (excluding China), Europe, and the Middle East and Africa (EMEA) were the fastest-growing regions in 3Q 2023, maintaining double-digit growth rates. Caribbean and Latin American (CALA) revenues grew at a high single-digit rate, while the China market was the only region to decline.
• Product growth was broad-based, but Thermal Management and Power Distribution grew at the fastest rates.
• Looking ahead, we forecast worldwide DCPI market growth to moderate in 2024 as pandemic induced orders are filled. However, we predict the market growth rates will remain at higher than historic levels, as AI deployments increasingly materialize throughout the year.

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[To share your insights with us, please write to sghosh@martechseries.com]

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The EY organization announces an alliance between SymphonyAI LLC (SymphonyAI), a leader in high-value enterprise AI software as a service (SaaS), and Ernst & Young LLP (EY US), to help organizations tap the power of AI to transform processes and operations. This strategic relationship brings enterprises predictive and generative AI software implementation at scale to improve efficiency and business performance.

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The EY-SymphonyAI Alliance will focus on financial crime prevention and regulatory compliance, which is a rising concern for large financial customers as fraudsters grow increasingly sophisticated in conducting fraudulent transactions, evasion of sanctions and money laundering. Complementing the SymphonyAI Sensa-NetReveal suite, EY US’ business knowledge, implementation experience and digital transformation capabilities aim to help clients identify and investigate suspicious activities faster and more accurately.

The Alliance will also support the expansion of AI-based solution delivery for retailers, including computer vision-based intelligence capabilities to improve store operations. It will also help to enhance customer experience and digital-industrial manufacturing, through asset management and worker connection solutions, which are intended to progress operations, yields and safety.

Greg Sarafin, EY Global Partner Ecosystem Leader, says: 

“The power of AI in business today is clear. Working with SymphonyAI, we will bring successful AI deployments to organizations around the globe. Initially, we are teaming to help enable financial institutions to level the playing field and meet regulatory as well as societal expectations for fraud detection and prevention more consistently, rapidly and effectively.”

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Kumar Abhimanyu, SymphonyAI Senior VP and Global Head of Strategic Partnerships, says:

“We are pleased to team with EY US on financial technology and beyond, advancing capabilities that drive greater productivity, accuracy and business impact. The power of innovative SymphonyAI solutions and the businesses and technology transformation knowledge of EY US, complemented by deep vertical experience in both organizations, will unlock business value worldwide.”

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AtScale, the leading provider of semantic layer solutions for modern business intelligence and data science teams announced a referral partnership with Dataiku, the platform for Everyday AI, to help speed enterprise artificial intelligence (AI) adoption and empower companies to easily create business value from their organization’s data.

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“The continued investment in AI, combined with the complexity of model deployment highlights just how critical it is for organizations to take an active approach to driving value from AI”

According to IDC, worldwide spending on AI-centric systems will surpass $300B by 2026 with a 26.5% 5-year CAGR. However, the same study concluded that only 25% of AI initiatives – and only 36% of AI models – had been deployed in production. Their research also indicated that 50% of businesses are planning to use AI in their business functions over the next 12 months.

“The continued investment in AI, combined with the complexity of model deployment highlights just how critical it is for organizations to take an active approach to driving value from AI,” said Gaurav Rao, Executive Vice President and General Manager of Machine Learning and AI at AtScale. “AI isn’t just something you can just turn on and instantly see business results from. Enterprises need to surround their AI with tools that make it easier to access and use data – and then apply those insights back into the organization. The lack of understanding and integration is one of the biggest reasons AI deployments are not successful.”

By combining Dataiku’s single data and AI platform with AtScale’s universal semantic layer and AI-Link, organizations will be able to improve data science productivity with business-vetted features for AI model training and feature management. Additionally, the integrated capabilities enable business analysts to seamlessly incorporate AI insights directly into common business intelligence tools such as Tableau, PowerBI, and Excel, on their cloud warehouse of choice, including Snowflake, Databricks, and Google BigQuery.

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Key Benefits of AtScale’s integration with Dataiku include:

• Production-Ready, Enterprise Grade Feature Store: The productivity of data analytics is improved through the use of an integrated feature store. Important features include:
  • Simplified and automated feature creation through a no-code/low-code interface helps to simplify the creation and use of complex dimensions, metrics, and hierarchies.
  • Advanced feature management, including feature serving and sharing, helps make data easily consumable across Dataiku projects, pipelines, and use cases.
• Advanced Time-Series Modeling: Dataiku’s autoML capabilities are combined with a semantic layer understanding of complex time hierarchies, making business forecasting easier and more efficient.
• Best-In-Class MLOps: The integrated solution gives enterprises the ability to publish insights generated in Dataiku ML pipelines directly to business users, in their business intelligence tools of choice. This gives business analysts the ability to conduct advanced predictive and prescriptive analyses more efficiently.
• Query Push Down: AtScale + Dataiku enables a governed and performant query to push down across an enterprise’s AI and BI workloads, ranging from data preparation to MLOps, across the most popular cloud warehouse partners. This helps speed the process and decision-making time for users.

“There is a palpable momentum across all industries in integrating AI, especially Generative AI, into their operations,” said Abhijit Madhugiri, VP of Global Technology Alliances at Dataiku. “In today’s dynamic business environment, the need to adapt existing processes and equip teams to leverage this advanced technology is not just a strategy, but a necessity for staying competitive. Our collaboration with AtScale aims to simplify this transformation, providing a clear pathway for enterprises to harness the potential of AI, drive lasting business impact, and avoid the risk of being left behind.”

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[To share your insights with us, please write to sghosh@martechseries.com]

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Priceline, and Google Cloud announced that Priceline plans to deploy Google Cloud’s generative AI technologies across both customer-facing and internal parts of its business. Customers will soon be able to engage with a new, generative AI-powered chatbot and will also begin to see more personalized offerings when searching for hotels worldwide. In addition, Priceline employees will benefit from increased and easier access to internal information, and realize productivity gains by using AI to automate some of their time-intensive coding and content generation tasks.

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Priceline’s initial Google Cloud generative AI deployments will begin rolling out this summer and include:

• Full-scale travel assistant chatbot to provide customers with a conversational experience in answering any and all questions about trip planning, and the ability to book a trip directly within the chat experience.
• New, AI-powered personalized hotel booking experience to help customers find preferred hotels by proximity to local attractions, restaurants and activities.
• Generative AI-powered marketing platform to enable Priceline teams to automatically generate marketing copy and imagery for customers across all company channels.
• Enhanced developer productivity, automation, and internal database mining tools to be expanded with new internal information search capabilities and software production capabilities.

As demand for travel returns to near pre-pandemic levels in a hyper-competitive industry, Priceline has taken a first-mover approach of using new technologies to differentiate itself — a philosophy grounded in the company’s history and culture. Priceline has specifically tapped into Google Cloud’s generative AI products to create more personalized offerings and  seamless booking experiences for its customers, as well as deploying new workplace tools that drive productivity and enable employees to focus on the most meaningful and high-impact work.

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“Priceline is charting a course to transform the novelty of generative AI into lasting value for our customers and our business. We believe it’s not just about having the latest technology; it’s also about practically targeting innovation to the right challenges and opportunities,” said Marty Brodbeck, Chief Technology Officer, Priceline. “With Google Cloud as our AI innovation partner, we’re doubling down on our commitment to delivering the fastest, most seamless and informative booking experience for our customers, from personalized planning and travel inspiration to customer service.”

“Generative AI holds tremendous potential for the travel industry, and Priceline is at the forefront of bringing its benefits to both customers and employees,” said Thomas Kurian, CEO of Google Cloud. “Together, we’re focused on being bold in our AI innovation and responsible in how this new technology will be deployed.”

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[To share your insights with us, please write to sghosh@martechseries.com]

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CloudFactory, a global leader in human-in-the-loop artificial intelligence (AI),announced that Pieter Nel has joined as Chief Technology Officer (CTO).

Nel brings more than 20 years of experience, across three continents, in technology strategy and software engineering management at fast-growth technology companies. As CTO, he will lead the technology and machine learning (ML) teams, continuously evolving CloudFactory’s platform as a key enabler for clients’ successful AI deployments.

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Nel previously served as CTO at Ocrolus, where he scaled the New York company’s human-in-the-loop AI document processing product. Before Ocrolus, he was at McKinsey, advising clients on AI strategy and co-authoring several of the firm’s AI research studies. Previous experience includes time with Tencent in Hong Kong and as CTO of MXit in South Africa, at the time the largest social network in Africa. He holds an MBA from MIT, where he was a Sloan Fellow, an M.Sc.Eng in machine learning from the University of Stellenbosch, and he is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).

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“We’re incredibly excited to have Pieter join our leadership team,” said Mark Sears, CloudFactory CEO. “His depth of experience in both operating and advising AI-driven businesses makes him the perfect fit to drive our data-centric AI strategy and develop solutions that accelerate innovation for our clients.”

“With machine learning code largely being a solved problem, the ML industry is shifting to focus on engineering the input training data,” said Nel. “Considering all successful AI deployments include humans in the loop, CloudFactory is positioned perfectly to support clients with our experienced annotation workforce and building the infrastructure to enable human-in-the-loop AI deployments. I’m excited to join CloudFactory to build out the leading offering in this space.”

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[To share your insights with us, please write to sghosh@martechseries.com]

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Businesses are in a tearing hurry to become AI-fueled organizations. However, only a handful of these actually manages to truly become one among many in the race.  In a recent report on what makes AI-fueled organizations successful, Deloitte AI Institute has uncovered startling facts related to the association between strong corporate leadership, AI strategy executions, and financial budgeting in AI and machine learning projects.

For example, an enterprise-wide AI strategy and leadership that communicate a bold vision are nearly 1.7 times more likely to achieve high outcomes.

Strategy Leading Practices That Help You Succeed as an AI-Fueled Organization

AI-fueled organizations view AI as a key element of business differentiation and success, and they set an enterprise-wide strategy that is championed from the top.

• Transformers were three times more likely to have an enterprise-wide strategy in place, and twice as likely as Starters to report a differentiated AI approach.
• However, only 40% of survey respondents completely agreed that their company has an enterprise-wide AI strategy in place, leaving room for improvement.
• While 66% of respondents view AI as critical to success, only 38% believe their use of AI differentiates them from competitors.

Deloitte AI Institute’s fourth edition of the “State of AI in the Enterprise” survey, conducted between March and May 2021, explores the deeper transformations happening inside organizations that are using AI to drive value in order to understand what the most “AI-fueled organizations” are doing to drive success. The report finds that AI-fueled organizations leverage data as an asset to deploy and scale AI systematically across all types of core business processes in a human-centered way.

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At the time of this announcement, Nitin Mittal, Deloitte AI co-leader, and principal, Deloitte Consulting LLP said – “Becoming an AI-fueled organization is to understand that the transformation process is never complete, but rather a journey of continuous learning and improvement.”

By surveying 2,875 executives from 11 countries across the Americas, Europe, and Asia, the report identifies the leading practices that were aligned with the marketplace leaders across industries. The findings in the report aim to help companies overcome challenges to becoming an AI-fueled organization, no matter what stage of AI transformation they are in, and especially to help those who are earlier in their transformation.

Profiles in AI maturity

In order to assess organizations’ AI maturity, Deloitte grouped responding organizations into four profiles based on how many types of AI applications they have deployed full-scale and the number of outcomes achieved to a high degree.

• Twenty-eight percent (28%) of survey respondents are “Transformers,” who report high outcomes and a high number of AI deployments. This group has identified and largely adopted leading practices associated with the strongest AI outcomes.
• Twenty-six percent (26%) of respondents are “Pathseekers,” reporting high outcomes, but a low number of deployments. Pathseekers have adopted capabilities and behaviors that are leading to success, but on fewer initiatives and they have not scaled to the same degree as Transformers.
• “Underachievers” were 17% of respondents, reporting low outcomes and a high number of deployments. While these organizations have a significant amount of AI deployment activity, they haven’t adopted enough leading practices to help them effectively achieve meaningful outcomes.
• “Starters” — 29% of survey respondents — reported low outcomes and a low number of deployments. These organizations have gotten a late start in building AI capabilities and are the least likely to demonstrate leading practice behaviors.

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“By embracing AI strategically and challenging orthodoxies, organizations can define a roadmap for adoption, quality delivery and scale to create or unlock value faster than ever before.”
— Irfan Saif, Deloitte AI co-leader, and principal, Deloitte & Touche LLP

“The risks associated with AI remain top of mind for executives. We found that high-achieving organizations report being more prepared to manage risks associated with AI and confident that they can deploy AI initiatives in a trustworthy way.”
— Beena Ammanath, executive director of the Deloitte AI Institute, Deloitte Consulting LLP.

Leading practices drive AI success

In analyzing the four organizational profiles, the report identified the behaviors most associated with strong outcomes, and leading practices in the following categories: strategy, operations, culture and change management, and ecosystems.

Operations leading practice

AI-fueled organizations establish new operating models and processes that drive sustained quality, innovation, and value creation.

• Organizations that have undergone significant changes to workflows or added new roles are almost 1.5 times more likely to achieve outcomes to a high degree.
• Organizations that document and enforce MLOps processes are twice as likely to achieve their goals; nearly two times more likely to report being extremely prepared for risks associated with AI; and nearly two times more confident that they can deploy AI initiatives in a trustworthy way.
• Survey results exposed a disconnect, however, as only about one-third of respondents report that they have adopted leading operational practices for AI.

Culture and Change Management Leading Practice Boost AI ML Adoption

AI-fueled organizations nurture a trusting, agile, data-fluent culture and invest in change management to support new ways of working.

• Organizations that invest in change management to a high degree are 1.6 times more likely to report that AI initiatives exceed expectations and over 1.5 times more likely to achieve their desired goals.
• However, most organizations underinvest this area. Only 37% of survey respondents reported significant investment in change management, incentives, or training activities to help their people integrate new technology into their work, often resulting in a slower, less successful transformation.

Ecosystems leading practice

AI-fueled organizations orchestrate dynamic ecosystems that build and protect competitive differentiation.

• Eighty-three percent (83%) of the highest achieving organizations (Transformers and Pathfinders) create a diverse ecosystem of partnerships to execute their AI strategy.
• Organizations with diverse ecosystems are significantly more likely to have a transformative vision for AI, enterprise-wide AI strategies, and use AI as a strategic differentiator.

The Deloitte AI Institute supports the positive growth and development of AI through engaged conversations and innovative research. It also focuses on building ecosystem relationships that help advance human-machine collaboration in the “Age of With,” a world where humans work side-by-side with machines.

[To share your insights with us, please write to sghosh@martechseries.com]

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Speakers from Huntington National Bank, Royal Bank of Canada and Personetics will take the stage at the Bank AIConference September 27-29 in Austin, TX  

AI-powered banking is already helping millions of bank customers worldwide improve their financial lives, and new implementations underway are projected to double the number of banks offering such solutions in the coming year.

Two of the banks that have turned to AI to help their customers manage their financial affairs will share lessons learned from their journey at the upcoming Bank AI Conference in Austin, TX:

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Right-size AI for Your Bank (Thursday September 27, 2:20pm – 2:50pm)

Panelists:

• Kourtney Dewald, Senior Vice President, Customer Experience Innovation Director, Huntington National Bank
• Rami Thabet, Vice President, Mobile & Digital Money Management, RBC

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Moderator:

• David Sosna, Co-founder and CEO, Personetics

Additional examples of successful AI deployments by financial institutions will be on display throughout the conference at the Personetics stand.

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The post Personetics and Leading Banks to Discuss Customer-facing Uses of Artificial Intelligence at Bank AI Conference appeared first on AiThority.