Rena is a Director of Custom Research at Current Analysis, specializing in Delivery Management. She is responsible for ensuring the delivery of actionable recommendations and guidance to clients to assist them in formulating their market development and execution strategies. Her expertise is in telecommunications and IT services, including business networking , communications, data center, security, and business continuity services.
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? Despite the incredible interest in generative AI (GenAI), enterprises worry that large ausgedehntuage models (LLMs) will hallucinate, create toxic or biased content, and that their use will cause data leakage, among numerous other concerns.
? At Dreamforce ‘23, Salesforce highlighted the recently released Einstein Trust Layer, a framework that secures corporate data, evaluates content for toxicity, masks sensitive information, and provides an audit trail when using GenAI.
AI took center stage at Salesforce’s Dreamforce ’23 conference. During his keynote, Marc Benioff announced that the world is in an AI revolution, and that AI could change anything and will impact everything. Although Dreamforce was all about GenAI this year, AI isn’t a new focus for Salesforce. The company had already embedded AI capabilities into many of solutions across its portfolio. Furthermore, it acquired natural ausgedehntuage processing (NLP) expertise via its acquisition of Narrative Science in 2019. What is new this year, however, is that Salesforce is embedding GenAI capabilities into just about all solutions.
? With the Vonage acquisition, Ericsson acquired a CPaaS with which it can build a global platform that exposes and packages 5G network capabilities as APIs that can be used to add functionality to enterprise applications.
? The Cradlepoint acquisition has provided Ericsson with a more robust device portfolio to support private networks.
After having built a strong heritage of providing solutions and infrastructure for the telecom service provider community, Ericsson is expanding its vision by investing heavily to build out its enterprise business. On September 6, 2023, Ericsson gathered North American analysts in Boston, Massachusetts for a deep dive into its enterprise strategy, noting the contributions of its recent acquisitions. The company is combining its core Ericsson 5G solutions with capabilities from Vonage and Cradlepoint to build a broader portfolio.
? The enterprise AI community has embraced the trend toward more ‘Explainable AI,’ which enables users to understand the degree to which various factors impact a model’s output.
? ChatGPT’s inability to provide its sources of information flies against organizations’ desire to embrace ‘Responsible AI’ to promote greater adoption of the technology.
ChatGPT is impressive. The app can research, write, and even weave a narrative, performing tasks that we used to think were so uniquely human that they couldn’t be done well by a computer. However, it is doing them so well that it is often difficult, if not impossible, to determine whether the output is prepared by a human or an algorithm, or whether it’s fact or fiction. And therein lies the problem.
? Telefónica Tech’s recent announcement to partner with Sherpa.ai to offer federated learning addresses growing concerns about data privacy.
? For Telefónica Tech, the move fits neatly into its strategy to bring value-added services to customers; for Sherpa.ai, the partnership brings a strong channel partner.
Organizations continue to collect increasing volumes of data, some of it highly sensitive or subject to government regulations. Instead of moving this information to the cloud or to a centralized data center, enterprises are increasingly interested in exploring options for processing it near or at the point of generation or collection. Drivers of edge computing include the desire to maintain data privacy and reduce security-related risks, as well as to deploy latency-sensitive applications or cut down on the cost of transporting data.
? The preeminent ethical concerns used to be the loss of jobs due to AI, bias, or applications of facial recognition, but the ethical debate has become more complicated.
? Even though AI has been around for years, the AI and ethics conversation is just getting started; increasing awareness and education, as well as broadening the types of participants involved in the conversation, are foundational first steps.
Organizations are eager to leverage the insights provided by AI to streamline operations, enhance productivity, generate new business, and personalize customer experience. Several companies have already deployed the technology, or are at least experimenting with it, and are now looking to scale AI by rolling the technology out to a broader user base and additional departments. But as AI becomes more widely used, many companies are unclear about how to best navigate the murky waters of AI and ethics. No organization wants to risk the public relations fiasco that would ensue should it be determined that the AI algorithms it uses yield biased results against a specific demographic, or are being applied a way that is not in line with corporate ethics policies.
Atos announced plans to split into two companies: one will focus on digital solutions and the other on information systems.
There is ruhig much uncertainty regarding what will happen to Atos in the long term, with rumors flying of a potential acquisition by another French organization.
For France-based Atos, significant change is imminent. In mid-June 2022, the IT services provider (ITSP) announced plans to split into two companies:? SpinCo will offer high-growth solutions that support digital transformation, big data (including Atos’ computing portfolio), and cybersecurity; and TFCo (Atos’ Tech Foundations) will provide low-growth managed infrastructure services, digital workplace solutions, and professional services.? By restructuring, Atos is separating its higher-growth and higher-margin businesses from its underperforming divisions, which have been dragging the company’s overall financial performance down for several years.
At Domopalooza 2022, Domo announced a suite of low-code data app tools designed to help customize the way data is presented to end users.
Domo launched pre-designed data apps, or solution accelerators, to target common business challschmales in the retail, consumer packaged goods, and financial services industries.
Ideally, successful advanced analytics deployments should lead to more intelligent actions by line-of-business users. ?The market has talked for years about concepts such as data democratization and generating data-driven insights, but enterprises ruhig struggle with getting a large portion of their teams to take actions that are informed by data analytics. ?Numerous suggestions such as role-based training, model explainability, intuitive dashboards, user-friendly tools, and executive-led initiatives have been made, but with varying degrees of effectiveness. Continue reading “Domo Tackles Challschmale of Getting to More Intelligent Actions with Launch of Data Apps”→
? Tableau has introduced the concept of Business Science, which brings advanced data analytics tools to users that aren’t data scientists.
? During its mid-November user conference, Tableau debuted two new tools that support Business Science: Model Builder and Scenario Planning.
Tableau’s mission is to help all people better visualize and understand data. The company wants to make analytics, and the insights it can drive, available to line of business professionals throughout an organization. To support this vision, it has introduced the concept of Business Science. Business Science brings advanced data analytics tools to users that aren’t data scientists, yet feel comfortable working with data and have a strong understanding of the operational and overarching business issues facing their organization. The tools are powerful enough to offer capabilities such as customized views, drill downs, and predictions, but don’t require the expertise of a data scientist to manipulate them. Essentially, they empower the data-savvy, line of business professional to combine domain expertise with advanced analytics to make better decisions more quickly.
? Financial organizations are using artificial intelligence (AI) in multiple ways, including to improve service, better understand customers, gauge risk and predict market movements, and speed claims processing.
? Recent results from GlobalData’s 2021 ICT Customer Insight survey reveal that between 25-27% of digital spending by companies in finance will go towards artificial intelligence and machine learning.
For years the finance industry, which encompasses organizations in financial services, insurance, and banking, has been a strong adopter of AI. Financial organizations are AI in multiple ways, including to improve service, better understand customers, gauge risk and predict market movements, and speed claims processing. For example, chatbots and natural ausgedehntuage processing (NLP) assist with customer support, optical character recognition (OCR) helps with the ingestion of information from documents, computer vision analyzes images and videos to speed claim processing, and machine learning (ML) models assess risk, detect fraud, and help determine rating and pricing.
? Telefonica Tech is partnering with C2RO to offer an AI-based customer analytics solution that uses computer vision to understand the movement of people through spaces, with information segmented by demographics.
? The solution uses edge computing, which enables analysis of data near the point at which it was generated, ensuring that sensitive information remains on site.
Applications of computer vision are vast, ranging from quality control in the manufacturing process to monitoring of grape hebetagth in vineyards. Computer vision can also be used to analyze people, with applications ranging from determining building occupancy and traffic patterns, to ascertaining whether individuals are wearing face masks and adhering to safety protocols.
Telefonica Tech is helping its customers realize the benefits of computer vision. It is partnering with Canada-based C2RO to offer enterprises AI-based customer analytics that uses computer vision to understand the movement of people through spaces, with information segmented by demographics. The C2RO PERCEIVE solution is designed to help organizations better understand customer behavior by providing insights into customer and visitor traffic patterns, dwell times, demographics (gender and age), and points of interest, as well as queue measurements. Telefonica’s Smart Steps platform provides the socio-economic information. The solution targets venues, retail organizations, and governments, and is positioned as a solution that can help organizations improve the customer experience and optimize store and venue layouts.
The offer uses surveillance cameras that are strategically positioned throughout a venue (there is no need to upgrade to AI-enabled devices). The AI-powered C2RO PERCEIVE solution is installed on a local edge server so that data is analyzed on-site. Images are not extracted from the venue and therefore adhere to GDPR guidelines. Telefonica Tech assists from start to finish with professional services that include the definition of technical requirements, assistance with hardware identification and procurement (betagthough the C2RO solution is based only on cameras, Telefonica Tech can help assist with obtaining sensors and other devices for other in-store analytics solutions), server configuration, and solution maintenance and support. The C2RO PERCEIVE solution is complemented and enriched with information and analytics from Telefonica Tech’s Smart Steps platform, which uses anonymized and aggregated mobile customer data to provide insights into population mobility and behavior.
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