Information Week

Author and speaker Malcolm Gladwell probably wasn’t an obvious choice to give a guest keynote for an audience of IT leaders gathered this week at Gartner’s IT Symposium/Xpo in Orlando, Florida. His books and talks mostly focus on looking at social issues from different perspectives. But a packed ballroom of CIOs and other IT leaders learned that a conventional approach to problem solving could lead to catastrophe — especially when dealing with “radically asymmetrical” problems that don’t adhere to a normal curve of distribution. Gladwell cited several events that defied conventional wisdom, where the culprit was an exception. From a faulty assumption by health officials during the COVID-19 pandemic, to a particularly gifted North Korean cybercriminal, to LA’s explosion of bank robberies in the 1990s — homing in on outliers may have produced better outcomes and solutions, Gladwell contends. While a normal distribution would be the default way of viewing a problem, where the offenders fit into a category along with many others, radically asymmetrical problems defy a normal distribution, placing the culprits on the extreme. Normal distribution “is our default for making sense of the world,” Gladwell said. “When we look at data, it’s going to organize itself in that kind of shape. We have an expectation about the story that data tells us, and the expectation is that the story is going to be about the middle … My question is, what happens when we have a problem where that story doesn’t work?” Related:2024 InformationWeek US IT Salary Report: Profits, Layoffs, and the Continued Rise of AI The COVID-19 Superspreader Conundrum At the onset of COVID-19, one of the earliest reported largescale outbreaks happened after a Biogen event in Boston, Mass. Many attendees were infected and then traveled to various destinations around the country. According to a report in Science, as many as 300,000 people wound up being infected because of that one event. Gladwell said researchers believe the source was a single person — a superspreader — someone who was genetically inclined to release a much higher level of aerosols. “This was the Taylor Swift of aerosols,” Gladwell said. In this case, the source of the problem was an example of a radically asymmetrical one. Had authorities been able to focus their efforts on so-called superspreaders, instead of focusing on social distancing measures for the general public, the outcome may have been different, Gladwell says. Leaders could have responded differently if they thought in terms of radically asymmetrical possibilities. What Leaders Can Learn? Related:Curtail Cloud Spend With These Strategies Gladwell offered up other scenarios that illustrated his point about radical asymmetry, including a slew of bank robberies in 1990s Los Angeles, the ongoing opioid crisis, and one that hit very close to home for attendees: the case of Park Jin Hyok, a North Korean hacker at the center of several massive cyberattacks, including the massive 2014 hack of Sony Pictures. “If you talk to people who are in the … high-end cybersecurity business, they will say, ‘Look, a lot of the time, all I’m doing is worried about Park Jin. I’m not worried about those hundreds of everyday hackers in Romania or Bulgaria. No, this one guy who had little crew somewhere in North Korea, and he’s the one who keeps me up tonight.’ That is a radical and radically asymmetrical distribution.” The number of doctors who overprescribed opioids in the 1990s was a relatively small subset of doctors. But those exceptional cases launched an epidemic of drug addiction still lingering today, Gladwell says. The slew of bank robberies in Los Angeles — many of those were carried out by one gang. All these problems may have been better addressed if there was more focus on radical asymmetric problems. “So, I would simply say to all of you as you go back home after this conference is over and you participate in society … When a problem comes up and people come up with solutions, just raise your hand and say, ‘Before we go any further, what’s the shape of the curve?’” Related:Forrester Speaker Sneak Peek: Analyst Jayesh Chaurasia to Talk AI Data Readiness source

“Process Orchestration: Harnessing the Transformative Power of Automation by Everest Group, endorsed by UiPath“ Organizations looking to scale their automation programs, executives responsible for digital transformation and automation initiatives, and operational leaders responsible for optimizing business operations will benefit from this report by Everest Group, endorsed by UiPath. In the digital age, enterprises constantly seek innovative ways to streamline operations, improve efficiency, and deliver exceptional customer experiences. This has led to increased adoption of Intelligent Automation (IA) technologies, such as process intelligence, Intelligent Document Processing (IDP), and conversational AI, over the past few years. Enterprises have successfully deployed automations for low-hanging fruits and simpler, high-volume repetitive tasks. However, they face challenges when scaling these initiatives to more complex, long-running processes. This report examines Enterprise business priorities and barriers to scaling automation Why IA is incomplete without process orchestration Process orchestration solutions Process orchestration use cases across key industries Key challenges and best practices when adopting process orchestration for scaling automation Offered Free by: UiPath See All Resources from: UiPath source

Augmented reality (AR), the real-time integration of digital information into a user’s environment, has many applications in industry, entertainment, transportation, and beyond. Yet AR’s most important application could be providing enhanced healthcare.  AR’s power lies in its ability to provide additional context through images, videos, or 3D models overlaid on the physical world, says Julie Stegman, vice president and general manager in the health learning practice at information services firm Wolters Kluwer. “These tools can be invaluable in healthcare in both education and practice as users interact with anatomical structures, models, or even medical devices,” she explains in an online interview.  AR has the potential to revolutionize the healthcare sector by enhancing the precision of medical procedures, improving training and education for healthcare professionals, and providing patients with more interactive and personalized care experiences, says Shash Anand, a senior vice president at enterprise mobility management technology provider SOTI, in an email interview.  Multiple Applications  “It’s an exciting time for the integration of technology and medicine,” observes David Reitzel, leader of the healthcare consulting group at business advisory firm Crowe. Among many other uses, AR can provide surgeons with enhanced visualization of a patient’s anatomy. “By overlaying 3D images of organs, blood vessels, and other critical structures onto the patient’s body, surgeons can perform procedures with greater accuracy, both in pre-surgery evaluation and potentially during actual procedures,” he explains via email.  Related:2024 InformationWeek US IT Salary Report: Profits, Layoffs, and the Continued Rise of AI AR can also assist in diagnostics by overlaying imaging data, such as MRI or CT scans, directly onto a patient. “This can help doctors identify issues more quickly and accurately,” Reitzel says. The technology can also help patients better understand their medical condition and treatment plans. “For instance, a doctor can use AR to show a patient a 3D model of their heart and explain how a particular treatment will work.”  AR can be used in physical therapy and rehabilitation to create engaging and interactive exercises, Reitzel says. “This can motivate patients and help them adhere to their therapy regimens more effectively.”  Interactive Training  Many observers believe that AR’s most immediate benefit will be in training both current and future healthcare professionals. “AR enables students to interact with virtual content in a real-world setting, providing contextualized learning experiences,” Stegman says. Meanwhile, full virtual reality (VR), will offer a completely immersive training environment in which students can practice clinical skills without the risks associated with real patient care.  Related:Curtail Cloud Spend With These Strategies Stegman predicts that over the long term, AR and related technologies will let nursing schools “help students develop clinical judgement, be ready for the demands of a clinical environment, and ensure improved workplace satisfaction for nurses early in their careers to mitigate the ongoing nursing shortage.”  Early Adopters  As AR begins entering the healthcare mainstream, deep-pocketed large hospitals and specialized medical centers will most likely be the leading adopters, says SOTI’s Anand. He reports that his firm’s latest healthcare report found that 89% of US healthcare industry respondents agree that artificial intelligence simplifies tasks. “This gives a hint that healthcare organizations are already on the path to integrating advanced technologies,” Anand notes. “AR is the next logical step, especially when combined with AI to further enhance patient care through real-time data visualization and decision-making.”  Future Outlook  Predicting an exact timeline for the widespread availability of various AR healthcare technologies is challenging, Crowes’ Reitzel states. “It depends on various factors, including technological advancements, regulatory approvals, cost reductions, and adoption rates.”  Related:Forrester Speaker Sneak Peek: Analyst Jayesh Chaurasia to Talk AI Data Readiness AR technology is rapidly evolving, and improvements in hardware (such as AR glasses and headsets), software, and integration with other medical technologies, are rapidly making AR more practical and effective. “As these technologies mature, they will become more accessible and affordable,” Reitzel predicts.  Global governments will also play a key role in AR’s medical market rollout. “The regulatory landscape for medical devices and technologies is complex,” Reitzel says. “AR applications in healthcare need to undergo rigorous testing and receive approval from regulatory bodies, such as the US’s Food and Drug Administration (FDA).” This process can take up to several years, but ongoing advancements and successful pilot programs can expedite approval.  As with any new technology, initial adoption costs will be high. Yet prices are likely to decrease over time as the technology becomes more widespread and production scales up. “Economies of scale, increased competition, and technological advancements will likely drive down costs, making AR more accessible to a broader range of healthcare providers,” Reitzel says.  Besides cost, a significant challenge will be integrating AR into existing healthcare systems and ensuring that the data used by AR applications is secure and complies with regulations such as HIPAA. SOTI’s report found that potential adopters’ biggest concerns are data security (30%), as well as anxiety about the possibility of compromised patient records (98%). “This shows that there could be roadblocks to AR adoption,” Anand says.  Money Matters  “Emerging technologies are always challenged by funding,” Stegman says, noting that obtaining sufficient operational resources, combined with research on ROI and solutions efficacy, is critical before moving forward with AR. source

“How AI-powered Phones are Changing the Modern Workplace“ Learn how completmenting your phone system with an all-in-one collaboration platform with AI capabilities can future-proof your business The way people work together is constantly evolving. Coordinating across different teams and time zones has always been a challenge, and today, remote, hybrid, and in-office workers are trying to sync together in new ways. While these flexible working styles offer benefits, they also create gaps. The good news is that we now have more tools than ever to bridge these gaps. However, figuring out which tools genuinely enhance productivity and which ones fall short is a challenge. It becomes even more difficult when the tools you rely on don’t work well together. In this ebook, we’ll help you: Assess your current phone system and evaluate how it fits into your overall toolkit. Understand how your individual apps and platforms work together in today’s communication landscape. Learn how complementing your phone system with an all-in-one collaboration platform with AI capabilities can future-proof your business and help your teams forge stronger connections. Offered Free by: Zoom See All Resources from: Zoom Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. source

InformationWeek is part of the Informa Tech Division of Informa PLC This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC’s registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726. source

“Cabinet-Integrated Liquid Cooling Supports Rising Power Density and Maximum Sustainability for High-Performance Computing Data Center Environments“ Revolutionizing Data Center Efficiency with Integrated Liquid Cooling Solutions The white paper titled “Cabinet Integrated Liquid Cooling” by Chatsworth Products addresses the increasing demand for efficient cooling solutions in data centers. It explores the advantages of integrating liquid cooling directly into server cabinets to enhance thermal management. The paper highlights how this approach improves cooling efficiency, reduces energy consumption, and supports higher-density computing environments. It also covers the design considerations, implementation strategies, and real-world benefits of adopting cabinet-integrated liquid cooling. By leveraging this technology, data centers can achieve superior performance, cost savings, and sustainability, meeting the challenges of modern high-performance computing demands. Download this whitepaper to learn more. Offered Free by: Chatsworth Products, Inc. See All Resources from: Chatsworth Products, Inc. Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. source

“Future-Ready Database Estates: Strategies for Modernization and Migration“ Thursday, November 7, 2024 at 1:00pm ET In today’s fast-paced digital landscape, modernizing your database estate is essential for agility, security, and performance. Join us for an informative webinar that delves into the latest strategies and tools for successfully modernizing your databases. We’ll start by exploring how to safely and securely adopt open-source Postgres with EDB, guiding you through the essential steps of the migration journey. Next, Nutanix will share insights on simplifying database operations, streamlining management tasks, and enhancing overall efficiency. Finally, Prolifics will provide expert advice on managing database migration projects, offering tools and best practices to ensure a smooth transition. Whether you’re considering a shift to open-source solutions, seeking to optimize your database operations, or navigating the complexities of migration, this webinar will equip you with the knowledge and resources to modernize your database estate effectively. Don’t miss this opportunity to transform your approach to database management. Speakers:Julian Moffett, VP Strategic Alliances, EDBJulian has 15+ years of experience working in the Financial Services sector in various different roles from: Infrastructure engineering, Product and Service Management to Business Application Development Lead and CTO / Enterprise Architect. Most recently Julian has been responsible for designing and building out enterprise scale Postgres managed services on premise and in cloud and managing an Oracle Exit initiative. In his current role as VP of Strategic Alliances Julian plays a crucial role in fostering and managing partnerships that drive growth and innovation for EDB’s customers.  Academically Julian comes from a Legal background (LLB, LPC) but has worked in technology all his professional career. Julian is TOGAF 9 certified. Jamie Frampton, UKI Sales Lead, Nutanix Database Service (NDB)Jamie is responsible for Nutanix’s Database-as-a-Service solution Nutanix Database Service(NDB) which offers automated database operation across multiple database engines, wherever you need to run them. Jamie has experience with clients running traditional RDBMS solutions such as Oracle and SQL Server, as well as modern Opensource database engines such as Postgres and MongoDB. Jamie has been looking after NDB across UK&I for the last 2 years and has previous experience of document databases working at MongoDB, as well as working with clients at IBM across integration. Peter McCullagh, Sales Executive, ProlificsPeter is a Database Migration and Decision Optimization Specialist. He works with clients on data projects to enhance their business. Typical projects are along the lines of the following:● Database Migrations – Using the Automated Database Agnostic Migrator (ADAM) service from Prolifics, Pete is able to automate a large component of database migrations. This allows Pete to offer lower risk and lower cost migrations. Typically, businesses are doing this to reduce license costs, and/or to facilitate a move to the cloud.● Decision Optimization – Using advanced technologies to assist customers with complex business decisions involving many large data sources, multiple trade-off possibilities and complex constraints.● General Data Services – With over a decade of experience in the data space, Pete is able to advise on nearly all data topics, as well as providing specialist consultants to help clients take their vision from the whiteboard to the metaverse. Moderator:Peter Krass, InformationWeek  Offered Free by: EnterpriseDB See All Resources from: EnterpriseDB source

Frustrations with generative artificial intelligence flaws run high and solutions are in high demand. First came the move from large language models to small language models to curb errors through data and task specializations. Then came mini model versions. Now there are highly specialized autonomous AI agents (bots) that work in teams called multi-agent systems.   “This shift leverages specialized AI agents to handle narrow tasks more accurately and cost-effectively, as each agent doesn’t need to be state-of-the-art but simply good enough for its specific role,” says Jesal Gadhia, head of engineering at Thoughtful AI.   The applications for multi-agents appear limitless but they are not a panacea for all AI use cases.  “It’s worth noting that while agents are an important piece of the AI puzzle, they do not replace some LLM-based GenAI tools, nor do they replace predictive AI/ML tools,” says Paul Harmon, senior manager, data science, at Atrium, a consulting firm for data, CRM, and analytics/AI.   “In some cases, AI-based tools may be better used to augment humans, providing insights and recommendations — in such cases an agent may not be needed. But in cases where AI-driven actions can replace rote tasks, agents can provide some significant productivity gains,” says Harmon, who’s also a distinguished member of the American Society for AI.  Related:The Rise of Autonomous AI Agents Ultimately, the concept is to leverage a blend of AI models and data to create a more powerful and targeted mix of tools to handle even the most complex and delicate tasks. For example, consider multi-agents in a customer care scenario for a telco company.   “Because the care agent and network agents leverage different domain-specific contexts, and may also leverage different underlying models and infrastructure, the outcome will theoretically be the ‘best of both worlds’ in terms of accuracy and speed,” says Anthony Goonetilleke, group president, technology and head of strategy at Amdocs, an Israeli multinational telecommunications technology company. “From an end-user perspective, their experience will be more fulfilling as they will not only simplify their care interaction, but also realize a meaningful outcome from the interaction in significantly faster time.”   So much for the high view, let’s now take a closer look at what all of this means to the rest of us:  1. Seismic shift from application to system integrations   Companies are eager to move beyond using GenAI in improving employee productivity to tackle complex use cases but they’re mostly hitting a wall in the process. It won’t be until most or all of an organization’s technology is fully integrated by AI bots that the real magic will occur, let alone at scale.  Related:Is This the End of Mass Production in Everything From Education To Manufacturing? “Today, the challenge for GenAI is that business operations are integrated, but software systems are not,” says Babak Hodjat, CTO of AI at Cognizant. “Multi-agent architectures create a “system of systems” that allows LLMs to interact with one another. AI agents — generative AI LLMs wrapped around any software, function, module, or app — interact with one another within this network, functioning as a virtual working group that can analyze prompts and draw information from across the business. The result? A comprehensive solution not just for the original requestor, but for other teams as well.”  2. Shift of artificial thinking from one agent to a hive mind  GenAI flaws and limitations are glaringly evident. Among them is difficulty in managing complex tasks and long, complicated inputs. Switching from one GenAI tool or “single agent” approach to a “multi-agent” approach instead enables a collection of AIs to each focus on a single task that they can do well.  “The limitations of single agent AI in handling complex, multifaceted tasks have become apparent,” says Loris Degioanni, founder and CTO at real-time cloud security firm, Sysdig. “This inherent limitation has driven a shift towards agentic AI, where multiple agents work collaboratively, much like human teams. This shift is also fueled by advancements in AI technologies that enable more sophisticated coordination and decision-making across agents, and 2024 has become the year when these systems have gained widespread recognition.”   Related:AI and Quantum Computing: High Risks or Big Boons to Fintech? 3. Multi-agents already exist but largely haven’t joined forces yet  Use them if you’ve got them, right? Multi-agents are “out there” they just aren’t organized yet in bigger systems. It’s not that doing so is necessarily an easy task, it’s just that it would be a terrible waste of potential if no one bothered to do so.  “In some ways, multi-agent architectures are already here,” says Deon Nicholas, CEO of Forethought AI. “Most systems are leveraging dozens of separate prompts under the hood, so in a sense these systems are already multi-agent. Unlike humans where each human has a distinct separate consciousness, it’s all kind of working in concert … For example, at Forethought, we have one agent for resolving customer service issues, and a completely separate agent for evaluating the quality of the conversations. This ‘supervisor’ or ‘evaluator’ agent is being used to check the answers of the first, generate further insights, and even provide policy updates for future training of the model. To the customer, it all appears as one cohesive ‘agentic’ system,” Nicolas says.   4. Multi-agent systems won’t replace single-agent applications  The switch to multi-agent systems will not trash any former investments in single agent applications. For example, if your company has already built a GenAI chatbot for HR and another one for customer service, you get to keep using them. Similarly, any investment made by any stakeholder can be protected and bolstered.  “AI can help optimize or create compromise for data gathering — specifically where satellite vs. drone vs. individually gathered sampling is acceptable or required. It is a complicated space with many views. A multi-agent model can ensure each stakeholder has control over their own reasoning and needs,” says Yvette Kanouff, partner at JC2 Ventures.  Kanouff points to the use of AI in land reclamation for mines, oil, and gas

Zoom Workplace vs. Microsoft Teams: Which is best for your organization? source

As financial institutions explore the potential efficiencies of in-house AI deployment, the trend could change the role fintech startups play as purveyors of innovation. The nimble, boundary-pushing nature of startups often means they dabble in novel ideas before incumbents. The more that organizations great and small inject AI into their ecosystems, does it reduce the interest on startups to drive new efficiencies and concepts? In this episode of DOS Won’t Hunt, Angela Friend, vice president of data science and AI with DailyPay; Adnan Masood, chief AI architect with UST; and John Lin, investor with F-Prime Capital, discuss how the spread of AI among incumbent financial institutions might affect their pursuit of innovation through startups. As efficiencies of AI continue to be touted, do incumbent financial institutions still need smaller, nimble startups to catalyze innovation? What are some common pain points financial institutions want to solve via technology? And how might startups try to speak to those pain points in ways large incumbents cannot? Listen to the full podcast here. source